Fault Detection of Bearing Systems through EEMD and Optimization Algorithm

PubMed Central

Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2017-01-01

This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs) and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space. PMID:29143772

Pedestrian detection based on redundant wavelet transform

NASA Astrophysics Data System (ADS)

Huang, Lin; Ji, Liping; Hu, Ping; Yang, Tiejun

2016-10-01

Intelligent video surveillance is to analysis video or image sequences captured by a fixed or mobile surveillance camera, including moving object detection, segmentation and recognition. By using it, we can be notified immediately in an abnormal situation. Pedestrian detection plays an important role in an intelligent video surveillance system, and it is also a key technology in the field of intelligent vehicle. So pedestrian detection has very vital significance in traffic management optimization, security early warn and abnormal behavior detection. Generally, pedestrian detection can be summarized as: first to estimate moving areas; then to extract features of region of interest; finally to classify using a classifier. Redundant wavelet transform (RWT) overcomes the deficiency of shift variant of discrete wavelet transform, and it has better performance in motion estimation when compared to discrete wavelet transform. Addressing the problem of the detection of multi-pedestrian with different speed, we present an algorithm of pedestrian detection based on motion estimation using RWT, combining histogram of oriented gradients (HOG) and support vector machine (SVM). Firstly, three intensities of movement (IoM) are estimated using RWT and the corresponding areas are segmented. According to the different IoM, a region proposal (RP) is generated. Then, the features of a RP is extracted using HOG. Finally, the features are fed into a SVM trained by pedestrian databases and the final detection results are gained. Experiments show that the proposed algorithm can detect pedestrians accurately and efficiently.

Gas chimney detection based on improving the performance of combined multilayer perceptron and support vector classifier

NASA Astrophysics Data System (ADS)

Hashemi, H.; Tax, D. M. J.; Duin, R. P. W.; Javaherian, A.; de Groot, P.

2008-11-01

Seismic object detection is a relatively new field in which 3-D bodies are visualized and spatial relationships between objects of different origins are studied in order to extract geologic information. In this paper, we propose a method for finding an optimal classifier with the help of a statistical feature ranking technique and combining different classifiers. The method, which has general applicability, is demonstrated here on a gas chimney detection problem. First, we evaluate a set of input seismic attributes extracted at locations labeled by a human expert using regularized discriminant analysis (RDA). In order to find the RDA score for each seismic attribute, forward and backward search strategies are used. Subsequently, two non-linear classifiers: multilayer perceptron (MLP) and support vector classifier (SVC) are run on the ranked seismic attributes. Finally, to capitalize on the intrinsic differences between both classifiers, the MLP and SVC results are combined using logical rules of maximum, minimum and mean. The proposed method optimizes the ranked feature space size and yields the lowest classification error in the final combined result. We will show that the logical minimum reveals gas chimneys that exhibit both the softness of MLP and the resolution of SVC classifiers.

Statistical evaluation of a project to estimate fish trajectories through the intakes of Kaplan hydropower turbines

NASA Astrophysics Data System (ADS)

Sutton, Virginia Kay

This paper examines statistical issues associated with estimating paths of juvenile salmon through the intakes of Kaplan turbines. Passive sensors, hydrophones, detecting signals from ultrasonic transmitters implanted in individual fish released into the preturbine region were used to obtain the information to estimate fish paths through the intake. Aim and location of the sensors affects the spatial region in which the transmitters can be detected, and formulas relating this region to sensor aiming directions are derived. Cramer-Rao lower bounds for the variance of estimators of fish location are used to optimize placement of each sensor. Finally, a statistical methodology is developed for analyzing angular data collected from optimally placed sensors.

A systematic FPGA acceleration design for applications based on convolutional neural networks

NASA Astrophysics Data System (ADS)

Dong, Hao; Jiang, Li; Li, Tianjian; Liang, Xiaoyao

2018-04-01

Most FPGA accelerators for convolutional neural network are designed to optimize the inner acceleration and are ignored of the optimization for the data path between the inner accelerator and the outer system. This could lead to poor performance in applications like real time video object detection. We propose a brand new systematic FPFA acceleration design to solve this problem. This design takes the data path optimization between the inner accelerator and the outer system into consideration and optimizes the data path using techniques like hardware format transformation, frame compression. It also takes fixed-point, new pipeline technique to optimize the inner accelerator. All these make the final system's performance very good, reaching about 10 times the performance comparing with the original system.

Peak tree: a new tool for multiscale hierarchical representation and peak detection of mass spectrometry data.

PubMed

Zhang, Peng; Li, Houqiang; Wang, Honghui; Wong, Stephen T C; Zhou, Xiaobo

2011-01-01

Peak detection is one of the most important steps in mass spectrometry (MS) analysis. However, the detection result is greatly affected by severe spectrum variations. Unfortunately, most current peak detection methods are neither flexible enough to revise false detection results nor robust enough to resist spectrum variations. To improve flexibility, we introduce peak tree to represent the peak information in MS spectra. Each tree node is a peak judgment on a range of scales, and each tree decomposition, as a set of nodes, is a candidate peak detection result. To improve robustness, we combine peak detection and common peak alignment into a closed-loop framework, which finds the optimal decomposition via both peak intensity and common peak information. The common peak information is derived and loopily refined from the density clustering of the latest peak detection result. Finally, we present an improved ant colony optimization biomarker selection method to build a whole MS analysis system. Experiment shows that our peak detection method can better resist spectrum variations and provide higher sensitivity and lower false detection rates than conventional methods. The benefits from our peak-tree-based system for MS disease analysis are also proved on real SELDI data.

Optimization design of the angle detecting system used in the fast steering mirror

NASA Astrophysics Data System (ADS)

Ni, Ying-xue; Wu, Jia-bin; San, Xiao-gang; Gao, Shi-jie; Ding, Shao-hang; Wang, Jing; Wang, Tao; Wang, Hui-xian

2018-01-01

In this paper, in order to design a fast steering mirror (FSM) with large deflection angle and high linearity, a deflection angle detecting system (DADS) using quadrant detector (QD) is developed. And the mathematical model describing DADS is established by analyzing the principle of position detecting and error characteristics of QD. Based on this mathematical model, the variation tendencies of deflection angle and linearity of FSM are simulated. Then, by changing the parameters of the DADS, the optimization of deflection angle and linearity of FSM is demonstrated. Finally, a QD-based FSM is designed based on this method, which achieves ±2° deflection angle and 0.72% and 0.68% linearity along x and y axis, respectively. Moreover, this method will be beneficial to the design of large deflection angle and high linearity FSM.

Dynamic path planning for mobile robot based on particle swarm optimization

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In the contemporary, robots are used in many fields, such as cleaning, medical treatment, space exploration, disaster relief and so on. The dynamic path planning of robot without collision is becoming more and more the focus of people's attention. A new method of path planning is proposed in this paper. Firstly, the motion space model of the robot is established by using the MAKLINK graph method. Then the A* algorithm is used to get the shortest path from the start point to the end point. Secondly, this paper proposes an effective method to detect and avoid obstacles. When an obstacle is detected on the shortest path, the robot will choose the nearest safety point to move. Moreover, calculate the next point which is nearest to the target. Finally, the particle swarm optimization algorithm is used to optimize the path. The experimental results can prove that the proposed method is more effective.

The research of autonomous obstacle avoidance of mobile robot based on multi-sensor integration

NASA Astrophysics Data System (ADS)

Zhao, Ming; Han, Baoling

2016-11-01

The object of this study is the bionic quadruped mobile robot. The study has proposed a system design plan for mobile robot obstacle avoidance with the binocular stereo visual sensor and the self-control 3D Lidar integrated with modified ant colony optimization path planning to realize the reconstruction of the environmental map. Because the working condition of a mobile robot is complex, the result of the 3D reconstruction with a single binocular sensor is undesirable when feature points are few and the light condition is poor. Therefore, this system integrates the stereo vision sensor blumblebee2 and the Lidar sensor together to detect the cloud information of 3D points of environmental obstacles. This paper proposes the sensor information fusion technology to rebuild the environment map. Firstly, according to the Lidar data and visual data on obstacle detection respectively, and then consider two methods respectively to detect the distribution of obstacles. Finally fusing the data to get the more complete, more accurate distribution of obstacles in the scene. Then the thesis introduces ant colony algorithm. It has analyzed advantages and disadvantages of the ant colony optimization and its formation cause deeply, and then improved the system with the help of the ant colony optimization to increase the rate of convergence and precision of the algorithm in robot path planning. Such improvements and integrations overcome the shortcomings of the ant colony optimization like involving into the local optimal solution easily, slow search speed and poor search results. This experiment deals with images and programs the motor drive under the compiling environment of Matlab and Visual Studio and establishes the visual 2.5D grid map. Finally it plans a global path for the mobile robot according to the ant colony algorithm. The feasibility and effectiveness of the system are confirmed by ROS and simulation platform of Linux.

Research on Taxiway Path Optimization Based on Conflict Detection

PubMed Central

Zhou, Hang; Jiang, Xinxin

2015-01-01

Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency. PMID:26226485

Research on Taxiway Path Optimization Based on Conflict Detection.

PubMed

Zhou, Hang; Jiang, Xinxin

2015-01-01

Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency.

Damage Detection Based on Static Strain Responses Using FBG in a Wind Turbine Blade.

PubMed

Tian, Shaohua; Yang, Zhibo; Chen, Xuefeng; Xie, Yong

2015-08-14

The damage detection of a wind turbine blade enables better operation of the turbines, and provides an early alert to the destroyed events of the blade in order to avoid catastrophic losses. A new non-baseline damage detection method based on the Fiber Bragg grating (FBG) in a wind turbine blade is developed in this paper. Firstly, the Chi-square distribution is proven to be an effective damage-sensitive feature which is adopted as the individual information source for the local decision. In order to obtain the global and optimal decision for the damage detection, the feature information fusion (FIF) method is proposed to fuse and optimize information in above individual information sources, and the damage is detected accurately through of the global decision. Then a 13.2 m wind turbine blade with the distributed strain sensor system is adopted to describe the feasibility of the proposed method, and the strain energy method (SEM) is used to describe the advantage of the proposed method. Finally results show that the proposed method can deliver encouraging results of the damage detection in the wind turbine blade.

Solid-phase microextraction of benzimidazole fungicides in environmental liquid samples and HPLC-fluorescence determination.

PubMed

López Monzón, A; Vega Moreno, D; Torres Padrón, M E; Sosa Ferrera, Z; Santana Rodríguez, J J

2007-03-01

Solid-phase microextraction (SPME) coupled with high-performance liquid chromatography (HPLC) with fluorescence detection was optimized for extraction and determination of four benzimidazole fungicides (benomyl, carbendazim, thiabendazole, and fuberidazole) in water. We studied extraction and desorption conditions, for example fiber type, extraction time, ionic strength, extraction temperature, and desorption time to achieve the maximum efficiency in the extraction. Results indicate that SPME using a Carboxen-polydimethylsiloxane 75 microm (CAR-PDMS) fiber is suitable for extraction of these types of compound. Final analysis of benzimidazole fungicides was performed by HPLC with fluorescence detection. Recoveries ranged from 80.6 to 119.6 with RSDs below 9% and limits of detection between 0.03 and 1.30 ng mL-1 for the different analytes. The optimized procedure was applied successfully to the determination of benzimidazole fungicides mixtures in environmental water samples (sea, sewage, and ground water).

Development of a Flexible Broadband Rayleigh Waves Comb Transducer with Nonequidistant Comb Interval for Defect Detection of Thick-Walled Pipelines

PubMed Central

He, Cunfu; Yan, Lyu; Zhang, Haijun

2018-01-01

It is necessary to develop a transducer that can quickly detect the inner and outer wall defects of thick-walled pipes, in order to ensure the safety of such pipes. In this paper, a flexible broadband Rayleigh-waves comb transducer based on PZT (lead zirconate titanate) for defect detection of thick-walled pipes is studied. The multiple resonant coupling theory is used to expand the transducer broadband and the FEA (Finite Element Analysis) method is used to optimize transducer array element parameters. Optimization results show that the best array element parameters of the transducer are when the transducer array element length is 30 mm, the thickness is 1.2 mm, the width of one end of is 1.5 mm, and the other end is 3 mm. Based on the optimization results, such a transducer was fabricated and its performance was tested. The test results were consistent with the finite-element simulation results, and the −3 dB bandwidth of the transducer reached 417 kHz. Transducer directivity test results show that the Θ−3dB beam width was equal to 10 °, to meet the defect detection requirements. Finally, defects of thick-walled pipes were detected using the transducer. The results showed that the transducer could detect the inner and outer wall defects of thick-walled pipes within the bandwidth. PMID:29498636

Development of a Flexible Broadband Rayleigh Waves Comb Transducer with Nonequidistant Comb Interval for Defect Detection of Thick-Walled Pipelines.

PubMed

Zhao, Huamin; He, Cunfu; Yan, Lyu; Zhang, Haijun

2018-03-02

It is necessary to develop a transducer that can quickly detect the inner and outer wall defects of thick-walled pipes, in order to ensure the safety of such pipes. In this paper, a flexible broadband Rayleigh-waves comb transducer based on PZT (lead zirconate titanate) for defect detection of thick-walled pipes is studied. The multiple resonant coupling theory is used to expand the transducer broadband and the FEA (Finite Element Analysis) method is used to optimize transducer array element parameters. Optimization results show that the best array element parameters of the transducer are when the transducer array element length is 30 mm, the thickness is 1.2 mm, the width of one end of is 1.5 mm, and the other end is 3 mm. Based on the optimization results, such a transducer was fabricated and its performance was tested. The test results were consistent with the finite-element simulation results, and the -3 dB bandwidth of the transducer reached 417 kHz. Transducer directivity test results show that the Θ -3dB beam width was equal to 10 °, to meet the defect detection requirements. Finally, defects of thick-walled pipes were detected using the transducer. The results showed that the transducer could detect the inner and outer wall defects of thick-walled pipes within the bandwidth.

Object detection via eye tracking and fringe restraint

NASA Astrophysics Data System (ADS)

Pan, Fei; Zhang, Hanming; Zeng, Ying; Tong, Li; Yan, Bin

2017-07-01

Object detection is a computer vision problem which caught a large amount of attention. But the candidate boundingboxes extracted from only image features may end up with false-detection due to the semantic gap between the top-down and the bottom up information. In this paper, we propose a novel method for generating object bounding-boxes proposals using the combination of eye fixation point, saliency detection and edges. The new method obtains a fixation orientated Gaussian map, optimizes the map through single-layer cellular automata, and derives bounding-boxes from the optimized map on three levels. Then we score the boxes by combining all the information above, and choose the box with the highest score to be the final box. We perform an evaluation of our method by comparing with previous state-ofthe art approaches on the challenging POET datasets, the images of which are chosen from PASCAL VOC 2012. Our method outperforms them on small scale objects while comparable to them in general.

Neural-network-based navigation and control of unmanned aerial vehicles for detecting unintended emissions

NASA Astrophysics Data System (ADS)

Zargarzadeh, H.; Nodland, David; Thotla, V.; Jagannathan, S.; Agarwal, S.

2012-06-01

Unmanned Aerial Vehicles (UAVs) are versatile aircraft with many applications, including the potential for use to detect unintended electromagnetic emissions from electronic devices. A particular area of recent interest has been helicopter unmanned aerial vehicles. Because of the nature of these helicopters' dynamics, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via output feedback control for trajectory tracking of a helicopter UAV using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic, virtual, and dynamic controllers and an observer. Optimal tracking is accomplished with a single NN utilized for cost function approximation. The controller positions the helicopter, which is equipped with an antenna, such that the antenna can detect unintended emissions. The overall closed-loop system stability with the proposed controller is demonstrated by using Lyapunov analysis. Finally, results are provided to demonstrate the effectiveness of the proposed control design for positioning the helicopter for unintended emissions detection.

Direct liquid chromatography method for the simultaneous quantification of hydroxytyrosol and tyrosol in red wines.

PubMed

Piñeiro, Zulema; Cantos-Villar, Emma; Palma, Miguel; Puertas, Belen

2011-11-09

A validated HPLC method with fluorescence detection for the simultaneous quantification of hydroxytyrosol and tyrosol in red wines is described. Detection conditions for both compounds were optimized (excitation at 279 and 278 and emission at 631 and 598 nm for hydroxytyrosol and tyrosol, respectively). The validation of the analytical method was based on selectivity, linearity, robustness, detection and quantification limits, repeatability, and recovery. The detection and quantification limits in red wines were set at 0.023 and 0.076 mg L(-1) for hydroxytyrosol and at 0.007 and 0.024 mg L(-1) for tyrosol determination, respectively. Precision values, both within-day and between-day (n = 5), remained below 3% for both compounds. In addition, a fractional factorial experimental design was developed to analyze the influence of six different conditions on analysis. The final optimized HPLC-fluorescence method allowed the analysis of 30 nonpretreated Spanish red wines to evaluate their hydroxytyrosol and tyrosol contents.

Thermal Preference of Juvenile Dover Sole (Solea solea) in Relation to Thermal Acclimation and Optimal Growth Temperature

PubMed Central

Schram, Edward; Bierman, Stijn; Teal, Lorna R.; Haenen, Olga; van de Vis, Hans; Rijnsdorp, Adriaan D.

2013-01-01

Dover sole (Solea solea) is an obligate ectotherm with a natural thermal habitat ranging from approximately 5 to 27°C. Thermal optima for growth lie in the range of 20 to 25°C. More precise information on thermal optima for growth is needed for cost-effective Dover sole aquaculture. The main objective of this study was to determine the optimal growth temperature of juvenile Dover sole (Solea solea) and in addition to test the hypothesis that the final preferendum equals the optimal growth temperature. Temperature preference was measured in a circular preference chamber for Dover sole acclimated to 18, 22 and 28°C. Optimal growth temperature was measured by rearing Dover sole at 19, 22, 25 and 28°C. The optimal growth temperature resulting from this growth experiment was 22.7°C for Dover sole with a size between 30 to 50 g. The temperature preferred by juvenile Dover sole increases with acclimation temperature and exceeds the optimal temperature for growth. A final preferendum could not be detected. Although a confounding effect of behavioural fever on temperature preference could not be entirely excluded, thermal preference and thermal optima for physiological processes seem to be unrelated in Dover sole. PMID:23613837

Thermal preference of juvenile Dover sole (Solea solea) in relation to thermal acclimation and optimal growth temperature.

PubMed

Schram, Edward; Bierman, Stijn; Teal, Lorna R; Haenen, Olga; van de Vis, Hans; Rijnsdorp, Adriaan D

2013-01-01

Dover sole (Solea solea) is an obligate ectotherm with a natural thermal habitat ranging from approximately 5 to 27°C. Thermal optima for growth lie in the range of 20 to 25°C. More precise information on thermal optima for growth is needed for cost-effective Dover sole aquaculture. The main objective of this study was to determine the optimal growth temperature of juvenile Dover sole (Solea solea) and in addition to test the hypothesis that the final preferendum equals the optimal growth temperature. Temperature preference was measured in a circular preference chamber for Dover sole acclimated to 18, 22 and 28°C. Optimal growth temperature was measured by rearing Dover sole at 19, 22, 25 and 28°C. The optimal growth temperature resulting from this growth experiment was 22.7°C for Dover sole with a size between 30 to 50 g. The temperature preferred by juvenile Dover sole increases with acclimation temperature and exceeds the optimal temperature for growth. A final preferendum could not be detected. Although a confounding effect of behavioural fever on temperature preference could not be entirely excluded, thermal preference and thermal optima for physiological processes seem to be unrelated in Dover sole.

Human emotion detector based on genetic algorithm using lip features

NASA Astrophysics Data System (ADS)

Brown, Terrence; Fetanat, Gholamreza; Homaifar, Abdollah; Tsou, Brian; Mendoza-Schrock, Olga

2010-04-01

We predicted human emotion using a Genetic Algorithm (GA) based lip feature extractor from facial images to classify all seven universal emotions of fear, happiness, dislike, surprise, anger, sadness and neutrality. First, we isolated the mouth from the input images using special methods, such as Region of Interest (ROI) acquisition, grayscaling, histogram equalization, filtering, and edge detection. Next, the GA determined the optimal or near optimal ellipse parameters that circumvent and separate the mouth into upper and lower lips. The two ellipses then went through fitness calculation and were followed by training using a database of Japanese women's faces expressing all seven emotions. Finally, our proposed algorithm was tested using a published database consisting of emotions from several persons. The final results were then presented in confusion matrices. Our results showed an accuracy that varies from 20% to 60% for each of the seven emotions. The errors were mainly due to inaccuracies in the classification, and also due to the different expressions in the given emotion database. Detailed analysis of these errors pointed to the limitation of detecting emotion based on the lip features alone. Similar work [1] has been done in the literature for emotion detection in only one person, we have successfully extended our GA based solution to include several subjects.

Detection of MDR1 mRNA expression with optimized gold nanoparticle beacon

NASA Astrophysics Data System (ADS)

Zhou, Qiumei; Qian, Zhiyu; Gu, Yueqing

2016-03-01

MDR1 (multidrug resistance gene) mRNA expression is a promising biomarker for the prediction of doxorubicin resistance in clinic. However, the traditional technical process in clinic is complicated and cannot perform the real-time detection mRNA in living single cells. In this study, the expression of MDR1 mRNA was analyzed based on optimized gold nanoparticle beacon in tumor cells. Firstly, gold nanoparticle (AuNP) was modified by thiol-PEG, and the MDR1 beacon sequence was screened and optimized using a BLAST bioinformatics strategy. Then, optimized MDR1 molecular beacons were characterized by transmission electron microscope, UV-vis and fluorescence spectroscopies. The cytotoxicity of MDR1 molecular beacon on L-02, K562 and K562/Adr cells were investigated by MTT assay, suggesting that MDR1 molecular beacon was low inherent cytotoxicity. Dark field microscope was used to investigate the cellular uptake of hDAuNP beacon assisted with ultrasound. Finally, laser scanning confocal microscope images showed that there was a significant difference in MDR1 mRNA expression in K562 and K562/Adr cells, which was consistent with the results of q-PCR measurement. In summary, optimized MDR1 molecular beacon designed in this study is a reliable strategy for detection MDR1 mRNA expression in living tumor cells, and will be a promising strategy for in guiding patient treatment and management in individualized medication.

Micro-satellite for space debris observation by optical sensors

NASA Astrophysics Data System (ADS)

Thillot, Marc; Brenière, Xavier; Midavaine, Thierry

2017-11-01

The purpose of this theoretical study carried out under CNES contract is to analyze the feasibility of small space debris detection and classification with an optical sensor on-board micro-satellite. Technical solutions based on active and passive sensors are analyzed and compared. For the most appropriated concept an optimization was made and theoretical performances in terms of number of detection versus class of diameter were calculated. Finally we give some preliminary physical sensor features to illustrate the concept (weight, volume, consumption,…).

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.

Automated Design Framework for Synthetic Biology Exploiting Pareto Optimality.

PubMed

Otero-Muras, Irene; Banga, Julio R

2017-07-21

In this work we consider Pareto optimality for automated design in synthetic biology. We present a generalized framework based on a mixed-integer dynamic optimization formulation that, given design specifications, allows the computation of Pareto optimal sets of designs, that is, the set of best trade-offs for the metrics of interest. We show how this framework can be used for (i) forward design, that is, finding the Pareto optimal set of synthetic designs for implementation, and (ii) reverse design, that is, analyzing and inferring motifs and/or design principles of gene regulatory networks from the Pareto set of optimal circuits. Finally, we illustrate the capabilities and performance of this framework considering four case studies. In the first problem we consider the forward design of an oscillator. In the remaining problems, we illustrate how to apply the reverse design approach to find motifs for stripe formation, rapid adaption, and fold-change detection, respectively.

Big Data-Based Approach to Detect, Locate, and Enhance the Stability of an Unplanned Microgrid Islanding

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

Jiang, Huaiguang; Li, Yan; Zhang, Yingchen

In this paper, a big data-based approach is proposed for the security improvement of an unplanned microgrid islanding (UMI). The proposed approach contains two major steps: the first step is big data analysis of wide-area monitoring to detect a UMI and locate it; the second step is particle swarm optimization (PSO)-based stability enhancement for the UMI. First, an optimal synchrophasor measurement device selection (OSMDS) and matching pursuit decomposition (MPD)-based spatial-temporal analysis approach is proposed to significantly reduce the volume of data while keeping appropriate information from the synchrophasor measurements. Second, a random forest-based ensemble learning approach is trained to detectmore » the UMI. When combined with grid topology, the UMI can be located. Then the stability problem of the UMI is formulated as an optimization problem and the PSO is used to find the optimal operational parameters of the UMI. An eigenvalue-based multiobjective function is proposed, which aims to improve the damping and dynamic characteristics of the UMI. Finally, the simulation results demonstrate the effectiveness and robustness of the proposed approach.« less

Development of GEM detector for plasma diagnostics application: simulations addressing optimization of its performance

NASA Astrophysics Data System (ADS)

Chernyshova, M.; Malinowski, K.; Kowalska-Strzęciwilk, E.; Czarski, T.; Linczuk, P.; Wojeński, A.; Krawczyk, R. D.

2017-12-01

The advanced Soft X-ray (SXR) diagnostics setup devoted to studies of the SXR plasma emissivity is at the moment a highly relevant and important for ITER/DEMO application. Especially focusing on the energy range of tungsten emission lines, as plasma contamination by W and its transport in the plasma must be understood and monitored for W plasma-facing material. The Gas Electron Multiplier, with a spatial and energy-resolved photon detecting chamber, based SXR radiation detection system under development by our group may become such a diagnostic setup considering and solving many physical, technical and technological aspects. This work presents the results of simulations aimed to optimize a design of the detector's internal chamber and its performance. The study of the effect of electrodes alignment allowed choosing the gap distances which maximizes electron transmission and choosing the optimal magnitudes of the applied electric fields. Finally, the optimal readout structure design was identified suitable to collect a total formed charge effectively, basing on the range of the simulated electron cloud at the readout plane which was in the order of ~ 2 mm.

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.

Damage Detection Based on Static Strain Responses Using FBG in a Wind Turbine Blade

PubMed Central

Tian, Shaohua; Yang, Zhibo; Chen, Xuefeng; Xie, Yong

2015-01-01

The damage detection of a wind turbine blade enables better operation of the turbines, and provides an early alert to the destroyed events of the blade in order to avoid catastrophic losses. A new non-baseline damage detection method based on the Fiber Bragg grating (FBG) in a wind turbine blade is developed in this paper. Firstly, the Chi-square distribution is proven to be an effective damage-sensitive feature which is adopted as the individual information source for the local decision. In order to obtain the global and optimal decision for the damage detection, the feature information fusion (FIF) method is proposed to fuse and optimize information in above individual information sources, and the damage is detected accurately through of the global decision. Then a 13.2 m wind turbine blade with the distributed strain sensor system is adopted to describe the feasibility of the proposed method, and the strain energy method (SEM) is used to describe the advantage of the proposed method. Finally results show that the proposed method can deliver encouraging results of the damage detection in the wind turbine blade. PMID:26287200

Adiabatic Quantum Anomaly Detection and Machine Learning

NASA Astrophysics Data System (ADS)

Pudenz, Kristen; Lidar, Daniel

2012-02-01

We present methods of anomaly detection and machine learning using adiabatic quantum computing. The machine learning algorithm is a boosting approach which seeks to optimally combine somewhat accurate classification functions to create a unified classifier which is much more accurate than its components. This algorithm then becomes the first part of the larger anomaly detection algorithm. In the anomaly detection routine, we first use adiabatic quantum computing to train two classifiers which detect two sets, the overlap of which forms the anomaly class. We call this the learning phase. Then, in the testing phase, the two learned classification functions are combined to form the final Hamiltonian for an adiabatic quantum computation, the low energy states of which represent the anomalies in a binary vector space.

Detection and reading distances of retroreflective road signs during night driving.

PubMed

Dahlstedt, S; Svenson, O

1977-03-01

The detectability and legibility of road signs of different reflective intensities were studied in night driving conditions. The results indicated that for obtaining optimal detectability and legibility distances, the reflective intensity of a new road sign should be in the range of 4 to 10 mcd/lux x cm(2). For signs in this range it was shown that doubling the area of a sign increased a detection distance of about 600 m by about 150-200 m. Opposing headlights on an oncoming car decreased detection distances of 500-900 m by about 100 m. Finally, it was found that standard signs, with a text 170 mm high, permitted reading from a distance of about 115 m.

Optimization of medical imaging display systems: using the channelized Hotelling observer for detecting lung nodules: experimental study

NASA Astrophysics Data System (ADS)

Platisa, Ljiljana; Vansteenkiste, Ewout; Goossens, Bart; Marchessoux, Cédric; Kimpe, Tom; Philips, Wilfried

2009-02-01

Medical-imaging systems are designed to aid medical specialists in a specific task. Therefore, the physical parameters of a system need to optimize the task performance of a human observer. This requires measurements of human performance in a given task during the system optimization. Typically, psychophysical studies are conducted for this purpose. Numerical observer models have been successfully used to predict human performance in several detection tasks. Especially, the task of signal detection using a channelized Hotelling observer (CHO) in simulated images has been widely explored. However, there are few studies done for clinically acquired images that also contain anatomic noise. In this paper, we investigate the performance of a CHO in the task of detecting lung nodules in real radiographic images of the chest. To evaluate variability introduced by the limited available data, we employ a commonly used study of a multi-reader multi-case (MRMC) scenario. It accounts for both case and reader variability. Finally, we use the "oneshot" methods to estimate the MRMC variance of the area under the ROC curve (AUC). The obtained AUC compares well to those reported for human observer study on a similar data set. Furthermore, the "one-shot" analysis implies a fairly consistent performance of the CHO with the variance of AUC below 0.002. This indicates promising potential for numerical observers in optimization of medical imaging displays and encourages further investigation on the subject.

Instrumentation and optimization of intra-cavity fiber laser gas absorption sensing system

NASA Astrophysics Data System (ADS)

Liu, Kun; Liu, Tiegen; Jiang, Junfeng; Liang, Xiao; Zhang, Yimo

2011-11-01

Detection of pollution, inflammable, explosive gases such as methane, acetylene, carbon monoxide and so on is very important for many areas, such as environmental, mining and petrochemical industry. Intra-cavity gas absorption sensing technique (ICGAST) based on Erbium-doped fiber ring laser (EDFRL) is one of novel methods for trace gas with higher precision. It has attracted considerable attention, and many research institutes focus on it. Instrumentation and optimization of ICGAST was reported in this paper. The system consists of five parts, which are variable gain module, intelligent frequency-selection module, gas cell, DAQ module and computer respectively. Variable gain module and intelligent frequency-selection module are combined to establish the intra-cavity of the ring laser. Gas cell is used as gas sensor. DAQ module is used to realize data acquisition synchronously. And gas demodulation is finished in the computer finally. The system was optimized by adjusting the sequence of the components. Take experimental simulation as an example, the absorptance of gas was increased five times after optimization, and the sensitivity enhancement factor can reach more than twenty. By using Fabry-Perot (F-P) etalon, the absorption wavelength of the detected gas can be obtained, with error less than 20 pm. The spectra of the detected gas can be swept continuously to obtain several absorption lines in one loop. The coefficient of variation (CV) was used to show the repeatability of gas concentration detection. And results of CV value can be less than 0.014.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-07-19

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

Real-time optimizations for integrated smart network camera

NASA Astrophysics Data System (ADS)

Desurmont, Xavier; Lienard, Bruno; Meessen, Jerome; Delaigle, Jean-Francois

2005-02-01

We present an integrated real-time smart network camera. This system is composed of an image sensor, an embedded PC based electronic card for image processing and some network capabilities. The application detects events of interest in visual scenes, highlights alarms and computes statistics. The system also produces meta-data information that could be shared between other cameras in a network. We describe the requirements of such a system and then show how the design of the system is optimized to process and compress video in real-time. Indeed, typical video-surveillance algorithms as background differencing, tracking and event detection should be highly optimized and simplified to be used in this hardware. To have a good adequation between hardware and software in this light embedded system, the software management is written on top of the java based middle-ware specification established by the OSGi alliance. We can integrate easily software and hardware in complex environments thanks to the Java Real-Time specification for the virtual machine and some network and service oriented java specifications (like RMI and Jini). Finally, we will report some outcomes and typical case studies of such a camera like counter-flow detection.

Development of a ginkgo biloba fingerprint chromatogram with UV and evaporative light scattering detection and optimization of the evaporative light scattering detector operating conditions.

PubMed

van Nederkassel, A M; Vijverman, V; Massart, D L; Vander Heyden, Y

2005-09-02

A fingerprint chromatogram of a standardized Ginkgo biloba extract is developed on a monolithic silica column using a ternary gradient containing water, iso-propanol and tetrahydrofuran. For the detection, UV and evaporative light scattering (ELS) detectors are used, the latter allowing detection of the poor UV absorbing compounds as ginkgolides (A-C and J) and bilobalide in the extract. The complementary information between the UV and ELS fingerprint is evaluated. The ELS detector used in this study can operate in an impactor 'on' or 'off' mode. For each mode, the operating conditions such as the nebulizing gas flow rate, the drift tube temperature and the gain are optimized by use of three-level screening designs to obtain the best signal-to-noise (S/N) ratio in the final ELS fingerprint chromatogram. In both impactor modes, very similar S/N ratios are obtained for the nominal levels of the design. However, optimization of the operating conditions resulted, for both impactor modes, in a significant increase in S/N ratios compared to the initial evaluated conditions, obtained from the detector software.

Using evolutionary computation to optimize an SVM used in detecting buried objects in FLIR imagery

NASA Astrophysics Data System (ADS)

Paino, Alex; Popescu, Mihail; Keller, James M.; Stone, Kevin

2013-06-01

In this paper we describe an approach for optimizing the parameters of a Support Vector Machine (SVM) as part of an algorithm used to detect buried objects in forward looking infrared (FLIR) imagery captured by a camera installed on a moving vehicle. The overall algorithm consists of a spot-finding procedure (to look for potential targets) followed by the extraction of several features from the neighborhood of each spot. The features include local binary pattern (LBP) and histogram of oriented gradients (HOG) as these are good at detecting texture classes. Finally, we project and sum each hit into UTM space along with its confidence value (obtained from the SVM), producing a confidence map for ROC analysis. In this work, we use an Evolutionary Computation Algorithm (ECA) to optimize various parameters involved in the system, such as the combination of features used, parameters on the Canny edge detector, the SVM kernel, and various HOG and LBP parameters. To validate our approach, we compare results obtained from an SVM using parameters obtained through our ECA technique with those previously selected by hand through several iterations of "guess and check".

Detection of Fungus Infection on Petals of Rapeseed (Brassica napus L.) Using NIR Hyperspectral Imaging

NASA Astrophysics Data System (ADS)

Zhao, Yan-Ru; Yu, Ke-Qiang; Li, Xiaoli; He, Yong

2016-12-01

Infected petals are often regarded as the source for the spread of fungi Sclerotinia sclerotiorum in all growing process of rapeseed (Brassica napus L.) plants. This research aimed to detect fungal infection of rapeseed petals by applying hyperspectral imaging in the spectral region of 874-1734 nm coupled with chemometrics. Reflectance was extracted from regions of interest (ROIs) in the hyperspectral image of each sample. Firstly, principal component analysis (PCA) was applied to conduct a cluster analysis with the first several principal components (PCs). Then, two methods including X-loadings of PCA and random frog (RF) algorithm were used and compared for optimizing wavebands selection. Least squares-support vector machine (LS-SVM) methodology was employed to establish discriminative models based on the optimal and full wavebands. Finally, area under the receiver operating characteristics curve (AUC) was utilized to evaluate classification performance of these LS-SVM models. It was found that LS-SVM based on the combination of all optimal wavebands had the best performance with AUC of 0.929. These results were promising and demonstrated the potential of applying hyperspectral imaging in fungus infection detection on rapeseed petals.

A novel visual saliency detection method for infrared video sequences

NASA Astrophysics Data System (ADS)

Wang, Xin; Zhang, Yuzhen; Ning, Chen

2017-12-01

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

Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

NASA Astrophysics Data System (ADS)

Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

2018-03-01

In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

Simple automatic strategy for background drift correction in chromatographic data analysis.

PubMed

Fu, Hai-Yan; Li, He-Dong; Yu, Yong-Jie; Wang, Bing; Lu, Peng; Cui, Hua-Peng; Liu, Ping-Ping; She, Yuan-Bin

2016-06-03

Chromatographic background drift correction, which influences peak detection and time shift alignment results, is a critical stage in chromatographic data analysis. In this study, an automatic background drift correction methodology was developed. Local minimum values in a chromatogram were initially detected and organized as a new baseline vector. Iterative optimization was then employed to recognize outliers, which belong to the chromatographic peaks, in this vector, and update the outliers in the baseline until convergence. The optimized baseline vector was finally expanded into the original chromatogram, and linear interpolation was employed to estimate background drift in the chromatogram. The principle underlying the proposed method was confirmed using a complex gas chromatographic dataset. Finally, the proposed approach was applied to eliminate background drift in liquid chromatography quadrupole time-of-flight samples used in the metabolic study of Escherichia coli samples. The proposed method was comparable with three classical techniques: morphological weighted penalized least squares, moving window minimum value strategy and background drift correction by orthogonal subspace projection. The proposed method allows almost automatic implementation of background drift correction, which is convenient for practical use. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparison of Molecular Typing Methods Useful for Detecting Clusters of Campylobacter jejuni and C. coli Isolates through Routine Surveillance

PubMed Central

Taboada, Eduardo; Grant, Christopher C. R.; Blakeston, Connie; Pollari, Frank; Marshall, Barbara; Rahn, Kris; MacKinnon, Joanne; Daignault, Danielle; Pillai, Dylan; Ng, Lai-King

2012-01-01

Campylobacter spp. may be responsible for unreported outbreaks of food-borne disease. The detection of these outbreaks is made more difficult by the fact that appropriate methods for detecting clusters of Campylobacter have not been well defined. We have compared the characteristics of five molecular typing methods on Campylobacter jejuni and C. coli isolates obtained from human and nonhuman sources during sentinel site surveillance during a 3-year period. Comparative genomic fingerprinting (CGF) appears to be one of the optimal methods for the detection of clusters of cases, and it could be supplemented by the sequencing of the flaA gene short variable region (flaA SVR sequence typing), with or without subsequent multilocus sequence typing (MLST). Different methods may be optimal for uncovering different aspects of source attribution. Finally, the use of several different molecular typing or analysis methods for comparing individuals within a population reveals much more about that population than a single method. Similarly, comparing several different typing methods reveals a great deal about differences in how the methods group individuals within the population. PMID:22162562

NASA Electronic Library System (NELS) optimization

NASA Technical Reports Server (NTRS)

Pribyl, William L.

1993-01-01

This is a compilation of NELS (NASA Electronic Library System) Optimization progress/problem, interim, and final reports for all phases. The NELS database was examined, particularly in the memory, disk contention, and CPU, to discover bottlenecks. Methods to increase the speed of NELS code were investigated. The tasks included restructuring the existing code to interact with others more effectively. An error reporting code to help detect and remove bugs in the NELS was added. Report writing tools were recommended to integrate with the ASV3 system. The Oracle database management system and tools were to be installed on a Sun workstation, intended for demonstration purposes.

MPI Runtime Error Detection with MUST: Advances in Deadlock Detection

DOE PAGES

Hilbrich, Tobias; Protze, Joachim; Schulz, Martin; ...

2013-01-01

The widely used Message Passing Interface (MPI) is complex and rich. As a result, application developers require automated tools to avoid and to detect MPI programming errors. We present the Marmot Umpire Scalable Tool (MUST) that detects such errors with significantly increased scalability. We present improvements to our graph-based deadlock detection approach for MPI, which cover future MPI extensions. Our enhancements also check complex MPI constructs that no previous graph-based detection approach handled correctly. Finally, we present optimizations for the processing of MPI operations that reduce runtime deadlock detection overheads. Existing approaches often require ( p ) analysis time permore » MPI operation, for p processes. We empirically observe that our improvements lead to sub-linear or better analysis time per operation for a wide range of real world applications.« less

Multispectral radiation envelope characteristics of aerial infrared targets

NASA Astrophysics Data System (ADS)

Kou, Tian; Zhou, Zhongliang; Liu, Hongqiang; Yang, Yuanzhi; Lu, Chunguang

2018-07-01

Multispectral detection signals are relatively stable and complementary to single spectral detection signals with deficiencies of severe scintillation and poor anti-interference. To take advantage of multispectral radiation characteristics in the application of infrared target detection, the concept of a multispectral radiation envelope is proposed. To build the multispectral radiation envelope model, the temperature distribution of an aerial infrared target is calculated first. By considering the coupling heat transfer process, the heat balance equation is built by using the node network, and the convective heat transfer laws as a function of target speed are uncovered. Then, the tail flame temperature distribution model is built and the temperature distributions at different horizontal distances are calculated. Second, to obtain the optimal detection angles, envelope models of reflected background multispectral radiation and target multispectral radiation are built. Finally, the envelope characteristics of the aerial target multispectral radiation are analyzed in different wavebands in detail. The results we obtained reflect Wien's displacement law and prove the effectiveness and reasonableness of the envelope model, and also indicate that the major difference between multispectral wavebands is greatly influenced by the target speed. Moreover, optimal detection angles are obtained by numerical simulation, and these are very important for accurate and fast target detection, attack decision-making and developing multispectral detection platforms.

Assessment of Gamma-Ray-Spectra Analysis Method Utilizing the Fireworks Algorithm for Various Error Measures

DOE PAGES

Alamaniotis, Miltiadis; Tsoukalas, Lefteri H.

2018-01-01

The analysis of measured data plays a significant role in enhancing nuclear nonproliferation mainly by inferring the presence of patterns associated with special nuclear materials. Among various types of measurements, gamma-ray spectra is the widest utilized type of data in nonproliferation applications. In this paper, a method that employs the fireworks algorithm (FWA) for analyzing gamma-ray spectra aiming at detecting gamma signatures is presented. In particular, FWA is utilized to fit a set of known signatures to a measured spectrum by optimizing an objective function, where non-zero coefficients express the detected signatures. FWA is tested on a set of experimentallymore » obtained measurements optimizing various objective functions—MSE, RMSE, Theil-2, MAE, MAPE, MAP—with results exhibiting its potential in providing highly accurate and precise signature detection. Finally and furthermore, FWA is benchmarked against genetic algorithms and multiple linear regression, showing its superiority over those algorithms regarding precision with respect to MAE, MAPE, and MAP measures.« less

Optimal filter design with progressive genetic algorithm for local damage detection in rolling bearings

NASA Astrophysics Data System (ADS)

Wodecki, Jacek; Michalak, Anna; Zimroz, Radoslaw

2018-03-01

Harsh industrial conditions present in underground mining cause a lot of difficulties for local damage detection in heavy-duty machinery. For vibration signals one of the most intuitive approaches of obtaining signal with expected properties, such as clearly visible informative features, is prefiltration with appropriately prepared filter. Design of such filter is very broad field of research on its own. In this paper authors propose a novel approach to dedicated optimal filter design using progressive genetic algorithm. Presented method is fully data-driven and requires no prior knowledge of the signal. It has been tested against a set of real and simulated data. Effectiveness of operation has been proven for both healthy and damaged case. Termination criterion for evolution process was developed, and diagnostic decision making feature has been proposed for final result determinance.

Weak Value Amplification is Suboptimal for Estimation and Detection

NASA Astrophysics Data System (ADS)

Ferrie, Christopher; Combes, Joshua

2014-01-01

We show by using statistically rigorous arguments that the technique of weak value amplification does not perform better than standard statistical techniques for the tasks of single parameter estimation and signal detection. Specifically, we prove that postselection, a necessary ingredient for weak value amplification, decreases estimation accuracy and, moreover, arranging for anomalously large weak values is a suboptimal strategy. In doing so, we explicitly provide the optimal estimator, which in turn allows us to identify the optimal experimental arrangement to be the one in which all outcomes have equal weak values (all as small as possible) and the initial state of the meter is the maximal eigenvalue of the square of the system observable. Finally, we give precise quantitative conditions for when weak measurement (measurements without postselection or anomalously large weak values) can mitigate the effect of uncharacterized technical noise in estimation.

Intraoperative Detection of Cell Injury and Cell Death with an 800 nm Near-Infrared Fluorescent Annexin V Derivative

PubMed Central

Ohnishi, Shunsuke; Vanderheyden, Jean-Luc; Tanaka, Eiichi; Patel, Bhavesh; De Grand, Alec; Laurence, Rita G.; Yamashita, Kenichiro; Frangioni, John V.

2008-01-01

The intraoperative detection of cell injury and cell death is fundamental to human surgeries such as organ transplantation and resection. Because of low autofluorescence background and relatively high tissue penetration, invisible light in the 800 nm region provides sensitive detection of disease pathology without changing the appearance of the surgical field. In order to provide surgeons with real-time intraoperative detection of cell injury and death after ischemia/reperfusion (I/R), we have developed a bioactive derivative of human annexin V (annexin800), which fluoresces at 800 nm. Total fluorescence yield, as a function of bioactivity, was optimized in vitro, and final performance was assessed in vivo. In liver, intestine and heart animal models of I/R, an optimal signal to background ratio was obtained 30 min after intravenous injection of annexin800, and histology confirmed concordance between planar reflectance images and actual deep tissue injury. In summary, annexin800 permits sensitive, real-time detection of cell injury and cell death after I/R in the intraoperative setting, and can be used during a variety of surgeries for rapid assessment of tissue and organ status. PMID:16869796

Accuracy of heart rate variability estimation by photoplethysmography using an smartphone: Processing optimization and fiducial point selection.

PubMed

Ferrer-Mileo, V; Guede-Fernandez, F; Fernandez-Chimeno, M; Ramos-Castro, J; Garcia-Gonzalez, M A

2015-08-01

This work compares several fiducial points to detect the arrival of a new pulse in a photoplethysmographic signal using the built-in camera of smartphones or a photoplethysmograph. Also, an optimization process for the signal preprocessing stage has been done. Finally we characterize the error produced when we use the best cutoff frequencies and fiducial point for smartphones and photopletysmograph and compare if the error of smartphones can be reasonably be explained by variations in pulse transit time. The results have revealed that the peak of the first derivative and the minimum of the second derivative of the pulse wave have the lowest error. Moreover, for these points, high pass filtering the signal between 0.1 to 0.8 Hz and low pass around 2.7 Hz or 3.5 Hz are the best cutoff frequencies. Finally, the error in smartphones is slightly higher than in a photoplethysmograph.

FPFH-based graph matching for 3D point cloud registration

NASA Astrophysics Data System (ADS)

Zhao, Jiapeng; Li, Chen; Tian, Lihua; Zhu, Jihua

2018-04-01

Correspondence detection is a vital step in point cloud registration and it can help getting a reliable initial alignment. In this paper, we put forward an advanced point feature-based graph matching algorithm to solve the initial alignment problem of rigid 3D point cloud registration with partial overlap. Specifically, Fast Point Feature Histograms are used to determine the initial possible correspondences firstly. Next, a new objective function is provided to make the graph matching more suitable for partially overlapping point cloud. The objective function is optimized by the simulated annealing algorithm for final group of correct correspondences. Finally, we present a novel set partitioning method which can transform the NP-hard optimization problem into a O(n3)-solvable one. Experiments on the Stanford and UWA public data sets indicates that our method can obtain better result in terms of both accuracy and time cost compared with other point cloud registration methods.

Design and characterization of an optimized simultaneous color and near-infrared fluorescence rigid endoscopic imaging system

NASA Astrophysics Data System (ADS)

Venugopal, Vivek; Park, Minho; Ashitate, Yoshitomo; Neacsu, Florin; Kettenring, Frank; Frangioni, John V.; Gangadharan, Sidhu P.; Gioux, Sylvain

2013-12-01

We report the design, characterization, and validation of an optimized simultaneous color and near-infrared (NIR) fluorescence rigid endoscopic imaging system for minimally invasive surgery. This system is optimized for illumination and collection of NIR wavelengths allowing the simultaneous acquisition of both color and NIR fluorescence at frame rates higher than 6.8 fps with high sensitivity. The system employs a custom 10-mm diameter rigid endoscope optimized for NIR transmission. A dual-channel light source compatible with the constraints of an endoscope was built and includes a plasma source for white light illumination and NIR laser diodes for fluorescence excitation. A prism-based 2-CCD camera was customized for simultaneous color and NIR detection with a highly efficient filtration scheme for fluorescence imaging of both 700- and 800-nm emission dyes. The performance characterization studies indicate that the endoscope can efficiently detect fluorescence signal from both indocyanine green and methylene blue in dimethyl sulfoxide at the concentrations of 100 to 185 nM depending on the background optical properties. Finally, we performed the validation of this imaging system in vivo during a minimally invasive procedure for thoracic sentinel lymph node mapping in a porcine model.

Active Correction of Aperture Discontinuities-Optimized Stroke Minimization. II. Optimization for Future Missions

NASA Astrophysics Data System (ADS)

Mazoyer, J.; Pueyo, L.; N'Diaye, M.; Fogarty, K.; Zimmerman, N.; Soummer, R.; Shaklan, S.; Norman, C.

2018-01-01

High-contrast imaging and spectroscopy provide unique constraints for exoplanet formation models as well as for planetary atmosphere models. Instrumentation techniques in this field have greatly improved over the last two decades, with the development of stellar coronagraphy, in parallel with specific methods of wavefront sensing and control. Next generation space- and ground-based telescopes will enable the characterization of cold solar-system-like planets for the first time and maybe even in situ detection of bio-markers. However, the growth of primary mirror diameters, necessary for these detections, comes with an increase of their complexity (segmentation, secondary mirror features). These discontinuities in the aperture can greatly limit the performance of coronagraphic instruments. In this context, we introduced a new technique, Active Correction of Aperture Discontinuities-Optimized Stroke Minimization (ACAD-OSM), to correct for the diffractive effects of aperture discontinuities in the final image plane of a coronagraph, using deformable mirrors. In this paper, we present several tools that can be used to optimize the performance of this technique for its application to future large missions. In particular, we analyzed the influence of the deformable setup (size and separating distance) and found that there is an optimal point for this setup, optimizing the performance of the instrument in contrast and throughput while minimizing the strokes applied to the deformable mirrors. These results will help us design future coronagraphic instruments to obtain the best performance.

A theoretical measure technique for determining 3D symmetric nearly optimal shapes with a given center of mass

NASA Astrophysics Data System (ADS)

Alimorad D., H.; Fakharzadeh J., A.

2017-07-01

In this paper, a new approach is proposed for designing the nearly-optimal three dimensional symmetric shapes with desired physical center of mass. Herein, the main goal is to find such a shape whose image in ( r, θ)-plane is a divided region into a fixed and variable part. The nearly optimal shape is characterized in two stages. Firstly, for each given domain, the nearly optimal surface is determined by changing the problem into a measure-theoretical one, replacing this with an equivalent infinite dimensional linear programming problem and approximating schemes; then, a suitable function that offers the optimal value of the objective function for any admissible given domain is defined. In the second stage, by applying a standard optimization method, the global minimizer surface and its related domain will be obtained whose smoothness is considered by applying outlier detection and smooth fitting methods. Finally, numerical examples are presented and the results are compared to show the advantages of the proposed approach.

Ultrasound-assisted extraction of amino acids from grapes.

PubMed

Carrera, Ceferino; Ruiz-Rodríguez, Ana; Palma, Miguel; Barroso, Carmelo G

2015-01-01

Recent cultivar techniques on vineyards can have a marked influence on the final nitrogen content of grapes, specifically individual amino acid contents. Furthermore, individual amino acid contents in grapes are related to the final aromatic composition of wines. A new ultrasound-assisted method for the extraction of amino acids from grapes has been developed. Several extraction variables, including solvent (water/ethanol mixtures), solvent pH (2-7), temperature (10-70°C), ultrasonic power (20-70%) and ultrasonic frequency (0.2-1.0s(-)(1)), were optimized to guarantee full recovery of the amino acids from grapes. An experimental design was employed to optimize the extraction parameters. The surface response methodology was used to evaluate the effects of the extraction variables. The analytical properties of the new method were established, including limit of detection (average value 1.4mmolkg(-)(1)), limit of quantification (average value 2.6mmolkg(-)(1)), repeatability (average RSD=12.9%) and reproducibility (average RSD=15.7%). Finally, the new method was applied to three cultivars of white grape throughout the ripening period. Copyright © 2014 Elsevier B.V. All rights reserved.

Optimization of dendrimer structure for sentinel lymph node imaging: Effects of generation and terminal group.

PubMed

Niki, Yuichiro; Ogawa, Mikako; Makiura, Rie; Magata, Yasuhiro; Kojima, Chie

2015-11-01

The detection of the sentinel lymph node (SLN), the first lymph node draining tumor cells, is important in cancer diagnosis and therapy. Dendrimers are synthetic macromolecules with highly controllable structures, and are potent multifunctional imaging agents. In this study, 12 types of dendrimer of different generations (G2, G4, G6, and G8) and different terminal groups (amino, carboxyl, and acetyl) were prepared to determine the optimal dendrimer structure for SLN imaging. Radiolabeled dendrimers were intradermally administrated to the right footpads of rats. All G2 dendrimers were predominantly accumulated in the kidney. Amino-terminal, acetyl-terminal, and carboxyl-terminal dendrimers of greater than G4 were mostly located at the injection site, in the blood, and in the SLN, respectively. The carboxyl-terminal dendrimers were largely unrecognized by macrophages and T-cells in the SLN. Finally, SLN detection was successfully performed by single photon emission computed tomography imaging using carboxyl-terminal dendrimers of greater than G4. The early detection of tumor cells in the sentinel draining lymph nodes (SLN) is of utmost importance in terms of determining cancer prognosis and devising treatment. In this article, the authors investigated various formulations of dendrimers to determine the optimal one for tumor detection. The data generated from this study would help clinicians to fight the cancer battle in the near future. Copyright © 2015 Elsevier Inc. All rights reserved.

Expert opinion paper on atrial fibrillation detection after ischemic stroke.

PubMed

Haeusler, Karl Georg; Gröschel, Klaus; Köhrmann, Martin; Anker, Stefan D; Brachmann, Johannes; Böhm, Michael; Diener, Hans-Christoph; Doehner, Wolfram; Endres, Matthias; Gerloff, Christian; Huttner, Hagen B; Kaps, Manfred; Kirchhof, Paulus; Nabavi, Darius Günther; Nolte, Christian H; Pfeilschifter, Waltraud; Pieske, Burkert; Poli, Sven; Schäbitz, Wolf Rüdiger; Thomalla, Götz; Veltkamp, Roland; Steiner, Thorsten; Laufs, Ulrich; Röther, Joachim; Wachter, Rolf; Schnabel, Renate

2018-04-27

This expert opinion paper on atrial fibrillation detection after ischemic stroke includes a statement of the "Heart and Brain" consortium of the German Cardiac Society and the German Stroke Society. This paper was endorsed by the Stroke Unit-Commission of the German Stroke Society and the German Atrial Fibrillation NETwork. In patients with ischemic stroke, detection of atrial fibrillation should usually lead to a change in secondary stroke prevention, since oral anticoagulation is superior to antiplatelet drugs. The detection of previously undiagnosed atrial fibrillation can be improved in patients with ischemic stroke to optimize stroke prevention. This paper summarizes the present knowledge on atrial fibrillation detection after ischemic stroke. We propose an interdisciplinary standard for a "structured analysis of ECG monitoring" on the stroke unit as well as a staged diagnostic scheme for the detection of atrial fibrillation. Since the optimal duration and mode of ECG monitoring has not yet been finally established, this paper is intended to give advice to physicians who are involved in stroke care. In line with the nature of an expert opinion paper, labeling of classes of recommendations is not provided, since many statements are based on the expert opinion, reported case series and clinical experience. Therefore, this paper is not intended as a guideline.

Constant Communities in Complex Networks

NASA Astrophysics Data System (ADS)

Chakraborty, Tanmoy; Srinivasan, Sriram; Ganguly, Niloy; Bhowmick, Sanjukta; Mukherjee, Animesh

2013-05-01

Identifying community structure is a fundamental problem in network analysis. Most community detection algorithms are based on optimizing a combinatorial parameter, for example modularity. This optimization is generally NP-hard, thus merely changing the vertex order can alter their assignments to the community. However, there has been less study on how vertex ordering influences the results of the community detection algorithms. Here we identify and study the properties of invariant groups of vertices (constant communities) whose assignment to communities are, quite remarkably, not affected by vertex ordering. The percentage of constant communities can vary across different applications and based on empirical results we propose metrics to evaluate these communities. Using constant communities as a pre-processing step, one can significantly reduce the variation of the results. Finally, we present a case study on phoneme network and illustrate that constant communities, quite strikingly, form the core functional units of the larger communities.

Optimization of dual energy contrast enhanced breast tomosynthesis for improved mammographic lesion detection and diagnosis

NASA Astrophysics Data System (ADS)

Saunders, R.; Samei, E.; Badea, C.; Yuan, H.; Ghaghada, K.; Qi, Y.; Hedlund, L. W.; Mukundan, S.

2008-03-01

Dual-energy contrast-enhanced breast tomosynthesis has been proposed as a technique to improve the detection of early-stage cancer in young, high-risk women. This study focused on optimizing this technique using computer simulations. The computer simulation used analytical calculations to optimize the signal difference to noise ratio (SdNR) of resulting images from such a technique at constant dose. The optimization included the optimal radiographic technique, optimal distribution of dose between the two single-energy projection images, and the optimal weighting factor for the dual energy subtraction. Importantly, the SdNR included both anatomical and quantum noise sources, as dual energy imaging reduces anatomical noise at the expense of increases in quantum noise. Assuming a tungsten anode, the maximum SdNR at constant dose was achieved for a high energy beam at 49 kVp with 92.5 μm copper filtration and a low energy beam at 49 kVp with 95 μm tin filtration. These analytical calculations were followed by Monte Carlo simulations that included the effects of scattered radiation and detector properties. Finally, the feasibility of this technique was tested in a small animal imaging experiment using a novel iodinated liposomal contrast agent. The results illustrated the utility of dual energy imaging and determined the optimal acquisition parameters for this technique. This work was supported in part by grants from the Komen Foundation (PDF55806), the Cancer Research and Prevention Foundation, and the NIH (NCI R21 CA124584-01). CIVM is a NCRR/NCI National Resource under P41-05959/U24-CA092656.

Single-view phase retrieval of an extended sample by exploiting edge detection and sparsity

DOE PAGES

Tripathi, Ashish; McNulty, Ian; Munson, Todd; ...

2016-10-14

We propose a new approach to robustly retrieve the exit wave of an extended sample from its coherent diffraction pattern by exploiting sparsity of the sample's edges. This approach enables imaging of an extended sample with a single view, without ptychography. We introduce nonlinear optimization methods that promote sparsity, and we derive update rules to robustly recover the sample's exit wave. We test these methods on simulated samples by varying the sparsity of the edge-detected representation of the exit wave. Finally, our tests illustrate the strengths and limitations of the proposed method in imaging extended samples.

Technology forecasting for space communication. Task one report: Cost and weight tradeoff studies for EOS and TDRS

NASA Technical Reports Server (NTRS)

1974-01-01

Weight and cost optimized EOS communication links are determined for 2.25, 7.25, 14.5, 21, and 60 GHz systems and for a 10.6 micron homodyne detection laser system. EOS to ground links are examined for 556, 834, and 1112 km EOS orbits, with ground terminals at the Network Test and Tracking Facility and at Goldstone. Optimized 21 GHz and 10.6 micron links are also examined. For the EOS to Tracking and Data Relay Satellite to ground link, signal-to-noise ratios of the uplink and downlink are also optimized for minimum overall cost or spaceborne weight. Finally, the optimized 21 GHz EOS to ground link is determined for various precipitation rates. All system performance parameters and mission dependent constraints are presented, as are the system cost and weight functional dependencies. The features and capabilities of the computer program to perform the foregoing analyses are described.

Imaging Tasks Scheduling for High-Altitude Airship in Emergency Condition Based on Energy-Aware Strategy

PubMed Central

Zhimeng, Li; Chuan, He; Dishan, Qiu; Jin, Liu; Manhao, Ma

2013-01-01

Aiming to the imaging tasks scheduling problem on high-altitude airship in emergency condition, the programming models are constructed by analyzing the main constraints, which take the maximum task benefit and the minimum energy consumption as two optimization objectives. Firstly, the hierarchy architecture is adopted to convert this scheduling problem into three subproblems, that is, the task ranking, value task detecting, and energy conservation optimization. Then, the algorithms are designed for the sub-problems, and the solving results are corresponding to feasible solution, efficient solution, and optimization solution of original problem, respectively. This paper makes detailed introduction to the energy-aware optimization strategy, which can rationally adjust airship's cruising speed based on the distribution of task's deadline, so as to decrease the total energy consumption caused by cruising activities. Finally, the application results and comparison analysis show that the proposed strategy and algorithm are effective and feasible. PMID:23864822

All-automatic swimmer tracking system based on an optimized scaled composite JTC technique

NASA Astrophysics Data System (ADS)

Benarab, D.; Napoléon, T.; Alfalou, A.; Verney, A.; Hellard, P.

2016-04-01

In this paper, an all-automatic optimized JTC based swimmer tracking system is proposed and evaluated on real video database outcome from national and international swimming competitions (French National Championship, Limoges 2015, FINA World Championships, Barcelona 2013 and Kazan 2015). First, we proposed to calibrate the swimming pool using the DLT algorithm (Direct Linear Transformation). DLT calculates the homography matrix given a sufficient set of correspondence points between pixels and metric coordinates: i.e. DLT takes into account the dimensions of the swimming pool and the type of the swim. Once the swimming pool is calibrated, we extract the lane. Then we apply a motion detection approach to detect globally the swimmer in this lane. Next, we apply our optimized Scaled Composite JTC which consists of creating an adapted input plane that contains the predicted region and the head reference image. This latter is generated using a composite filter of fin images chosen from the database. The dimension of this reference will be scaled according to the ratio between the head's dimension and the width of the swimming lane. Finally, applying the proposed approach improves the performances of our previous tracking method by adding a detection module in order to achieve an all-automatic swimmer tracking system.

Coherent receiver design based on digital signal processing in optical high-speed intersatellite links with M-phase-shift keying

NASA Astrophysics Data System (ADS)

Schaefer, Semjon; Gregory, Mark; Rosenkranz, Werner

2016-11-01

We present simulative and experimental investigations of different coherent receiver designs for high-speed optical intersatellite links. We focus on frequency offset (FO) compensation in homodyne and intradyne detection systems. The considered laser communication terminal uses an optical phase-locked loop (OPLL), which ensures stable homodyne detection. However, the hardware complexity increases with the modulation order. Therefore, we show that software-based intradyne detection is an attractive alternative for OPLL-based homodyne systems. Our approach is based on digital FO and phase noise compensation, in order to achieve a more flexible coherent detection scheme. Analytic results will further show the theoretical impact of the different detection schemes on the receiver sensitivity. Finally, we compare the schemes in terms of bit error ratio measurements and optimal receiver design.

DESPIC: Detecting Early Signatures of Persuasion in Information Cascades

DTIC Science & Technology

2015-08-27

over NoSQL Databases, Proceedings of the 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2014). 26-MAY-14, . : , P...over NoSQL Databases. Proceedings of the 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2014). Chicago, IL, USA...distributed NoSQL databases including HBase and Riak, we finalized the requirements of the optimal computational architecture to support our framework

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Detection of proteolytic activity by covalent tethering of fluorogenic substrates in zymogram gels.

PubMed

Deshmukh, Ameya A; Weist, Jessica L; Leight, Jennifer L

2018-05-01

Current zymographic techniques detect only a subset of known proteases due to the limited number of native proteins that have been optimized for incorporation into polyacrylamide gels. To address this limitation, we have developed a technique to covalently incorporate fluorescently labeled, protease-sensitive peptides using an azido-PEG3-maleimide crosslinker. Peptides incorporated into gels enabled measurement of MMP-2, -9, -14, and bacterial collagenase. Sensitivity analysis demonstrated that use of peptide functionalized gels could surpass detection limits of current techniques. Finally, electrophoresis of conditioned media from cultured cells resulted in the appearance of several proteolytic bands, some of which were undetectable by gelatin zymography. Taken together, these results demonstrate that covalent incorporation of fluorescent substrates can greatly expand the library of detectable proteases using zymographic techniques.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Optimal estimation of recurrence structures from time series

NASA Astrophysics Data System (ADS)

beim Graben, Peter; Sellers, Kristin K.; Fröhlich, Flavio; Hutt, Axel

2016-05-01

Recurrent temporal dynamics is a phenomenon observed frequently in high-dimensional complex systems and its detection is a challenging task. Recurrence quantification analysis utilizing recurrence plots may extract such dynamics, however it still encounters an unsolved pertinent problem: the optimal selection of distance thresholds for estimating the recurrence structure of dynamical systems. The present work proposes a stochastic Markov model for the recurrent dynamics that allows for the analytical derivation of a criterion for the optimal distance threshold. The goodness of fit is assessed by a utility function which assumes a local maximum for that threshold reflecting the optimal estimate of the system's recurrence structure. We validate our approach by means of the nonlinear Lorenz system and its linearized stochastic surrogates. The final application to neurophysiological time series obtained from anesthetized animals illustrates the method and reveals novel dynamic features of the underlying system. We propose the number of optimal recurrence domains as a statistic for classifying an animals' state of consciousness.

Use of Acoustic Emission and Pattern Recognition for Crack Detection of a Large Carbide Anvil

PubMed Central

Chen, Bin; Wang, Yanan; Yan, Zhaoli

2018-01-01

Large-volume cubic high-pressure apparatus is commonly used to produce synthetic diamond. Due to the high pressure, high temperature and alternative stresses in practical production, cracks often occur in the carbide anvil, thereby resulting in significant economic losses or even casualties. Conventional methods are unsuitable for crack detection of the carbide anvil. This paper is concerned with acoustic emission-based crack detection of carbide anvils, regarded as a pattern recognition problem; this is achieved using a microphone, with methods including sound pulse detection, feature extraction, feature optimization and classifier design. Through analyzing the characteristics of background noise, the cracked sound pulses are separated accurately from the originally continuous signal. Subsequently, three different kinds of features including a zero-crossing rate, sound pressure levels, and linear prediction cepstrum coefficients are presented for characterizing the cracked sound pulses. The original high-dimensional features are adaptively optimized using principal component analysis. A hybrid framework of a support vector machine with k nearest neighbors is designed to recognize the cracked sound pulses. Finally, experiments are conducted in a practical diamond workshop to validate the feasibility and efficiency of the proposed method. PMID:29382144

Use of Acoustic Emission and Pattern Recognition for Crack Detection of a Large Carbide Anvil.

PubMed

Chen, Bin; Wang, Yanan; Yan, Zhaoli

2018-01-29

Large-volume cubic high-pressure apparatus is commonly used to produce synthetic diamond. Due to the high pressure, high temperature and alternative stresses in practical production, cracks often occur in the carbide anvil, thereby resulting in significant economic losses or even casualties. Conventional methods are unsuitable for crack detection of the carbide anvil. This paper is concerned with acoustic emission-based crack detection of carbide anvils, regarded as a pattern recognition problem; this is achieved using a microphone, with methods including sound pulse detection, feature extraction, feature optimization and classifier design. Through analyzing the characteristics of background noise, the cracked sound pulses are separated accurately from the originally continuous signal. Subsequently, three different kinds of features including a zero-crossing rate, sound pressure levels, and linear prediction cepstrum coefficients are presented for characterizing the cracked sound pulses. The original high-dimensional features are adaptively optimized using principal component analysis. A hybrid framework of a support vector machine with k nearest neighbors is designed to recognize the cracked sound pulses. Finally, experiments are conducted in a practical diamond workshop to validate the feasibility and efficiency of the proposed method.

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.

Evaluation of load flow and grid expansion in a unit-commitment and expansion optimization model SciGRID International Conference on Power Grid Modelling

NASA Astrophysics Data System (ADS)

Senkpiel, Charlotte; Biener, Wolfgang; Shammugam, Shivenes; Längle, Sven

2018-02-01

Energy system models serve as a basis for long term system planning. Joint optimization of electricity generating technologies, storage systems and the electricity grid leads to lower total system cost compared to an approach in which the grid expansion follows a given technology portfolio and their distribution. Modelers often face the problem of finding a good tradeoff between computational time and the level of detail that can be modeled. This paper analyses the differences between a transport model and a DC load flow model to evaluate the validity of using a simple but faster transport model within the system optimization model in terms of system reliability. The main findings in this paper are that a higher regional resolution of a system leads to better results compared to an approach in which regions are clustered as more overloads can be detected. An aggregation of lines between two model regions compared to a line sharp representation has little influence on grid expansion within a system optimizer. In a DC load flow model overloads can be detected in a line sharp case, which is therefore preferred. Overall the regions that need to reinforce the grid are identified within the system optimizer. Finally the paper recommends the usage of a load-flow model to test the validity of the model results.

Detecting trihalomethanes using nanoporous-carbon coated surface-acoustic-wave sensors

DOE PAGES

Siegal, Michael P.; Mowry, Curtis D.; Pfeifer, Kent B.; ...

2015-03-07

We study nanoporous-carbon (NPC) grown via pulsed laser deposition (PLD) as a sorbent coating on 96.5-MHz surface-acoustic-wave (SAW) devices to detect trihalomethanes (THMs), regulated byproducts from the chemical treatment of drinking water. Using both insertion-loss and isothermal-response measurements from known quantities of chloroform, the highest vapor pressure THM, we optimize the NPC mass-density at 1.05 ± 0.08 g/cm3 by controlling the background argon pressure during PLD. Precise THM quantities in a chlorobenzene solvent are directly injected into a separation column and detected as the phase-angle shift of the SAW device output compared to the drive signal. Using optimized NPC-coated SAWs,more » we study the chloroform response as a function of operating temperatures ranging from 10–50°C. Finally, we demonstrate individual responses from complex mixtures of all four THMs, with masses ranging from 10–2000 ng, after gas chromatography separation. As a result, estimates for each THM detection limit using a simple peak-height response evaluation are 4.4 ng for chloroform and 1 ng for bromoform; using an integrated-peak area response analysis improves the detection limits to 0.73 ng for chloroform and 0.003 ng bromoform.« less

Phase transition of Surprise optimization in community detection

NASA Astrophysics Data System (ADS)

Xiang, Ju; Tang, Yan-Ni; Gao, Yuan-Yuan; Liu, Lang; Hao, Yi; Li, Jian-Ming; Zhang, Yan; Chen, Shi

2018-02-01

Community detection is one of important issues in the research of complex networks. In literatures, many methods have been proposed to detect community structures in the networks, while they also have the scope of application themselves. In this paper, we investigate an important measure for community detection, Surprise (Aldecoa and Marín, Sci. Rep. 3 (2013) 1060), by focusing on the critical points in the merging and splitting of communities. We firstly analyze the critical behavior of Surprise and give the phase diagrams in community-partition transition. The results show that the critical number of communities for Surprise has a super-exponential increase with the increase of the link-density difference, while it is close to that of Modularity for small difference between inter- and intra-community link densities. By directly optimizing Surprise, we experimentally test the results on various networks, following a series of comparisons with other classical methods, and further find that the heterogeneity of networks could quicken the splitting of communities. On the whole, the results show that Surprise tends to split communities due to various reasons such as the heterogeneity in link density, degree and community size, and it thus exhibits higher resolution than other methods, e.g., Modularity, in community detection. Finally, we provide several approaches for enhancing Surprise.

Preparation and characterization of AuNPs/CNTs-ErGO electrochemical sensors for highly sensitive detection of hydrazine.

PubMed

Zhao, Zhenting; Sun, Yongjiao; Li, Pengwei; Zhang, Wendong; Lian, Kun; Hu, Jie; Chen, Yong

2016-09-01

A highly sensitive electrochemical sensor of hydrazine has been fabricated by Au nanoparticles (AuNPs) coating of carbon nanotubes-electrochemical reduced graphene oxide composite film (CNTs-ErGO) on glassy carbon electrode (GCE). Cyclic voltammetry and potential amperometry have been used to investigate the electrochemical properties of the fabricated sensors for hydrazine detection. The performances of the sensors were optimized by varying the CNTs to ErGO ratio and the quantity of Au nanoparticles. The results show that under optimal conditions, a sensitivity of 9.73μAμM(-1)cm(-2), a short response time of 3s, and a low detection limit of 0.065μM could be achieved with a linear concentration response range from 0.3μM to 319μM. The enhanced electrochemical performances could be attributed to the synergistic effect between AuNPs and CNTs-ErGO film and the outstanding catalytic effect of the Au nanoparticles. Finally, the sensor was successfully used to analyse the tap water, showing high potential for practical applications. Copyright © 2016 Elsevier B.V. All rights reserved.

Numerical predictions and experiments for optimizing hidden corrosion detection in aircraft structures using Lamb modes.

PubMed

Terrien, N; Royer, D; Lepoutre, F; Déom, A

2007-06-01

To increase the sensitivity of Lamb waves to hidden corrosion in aircraft structures, a preliminary step is to understand the phenomena governing this interaction. A hybrid model combining a finite element approach and a modal decomposition method is used to investigate the interaction of Lamb modes with corrosion pits. The finite element mesh is used to describe the region surrounding the corrosion pits while the modal decomposition method permits to determine the waves reflected and transmitted by the damaged area. Simulations make easier the interpretation of some parts of the measured waveform corresponding to superposition of waves diffracted by the corroded area. Numerical results permit to extract significant information from the transmitted waveform and thus to optimize the signal processing for the detection of corrosion at an early stage. Now, we are able to detect corrosion pits down to 80-mum depth distributed randomly on a square centimeter of an aluminum plate. Moreover, thickness variations present on aircraft structures can be discriminated from a slightly corroded area. Finally, using this experimental setup, aircraft structures have been tested.

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

NASA Astrophysics Data System (ADS)

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

2010-02-01

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

Deflection angle detecting system for the large-angle and high-linearity fast steering mirror using quadrant detector

NASA Astrophysics Data System (ADS)

Ni, Yingxue; Wu, Jiabin; San, Xiaogang; Gao, Shijie; Ding, Shaohang; Wang, Jing; Wang, Tao

2018-02-01

A deflection angle detecting system (DADS) using a quadrant detector (QD) is developed to achieve the large deflection angle and high linearity for the fast steering mirror (FSM). The mathematical model of the DADS is established by analyzing the principle of position detecting and error characteristics of the QD. Based on this mathematical model, the method of optimizing deflection angle and linearity of FSM is demonstrated, which is proved feasible by simulation and experimental results. Finally, a QD-based FSM is designed and tested. The results show that it achieves 0.72% nonlinearity, ±2.0 deg deflection angle, and 1.11-μrad resolution. Therefore, the application of this method will be beneficial to design the FSM.

Optimization of Surface-Enhanced Raman Spectroscopy Conditions for Implementation into a Microfluidic Device for Drug Detection.

PubMed

Kline, Neal D; Tripathi, Ashish; Mirsafavi, Rustin; Pardoe, Ian; Moskovits, Martin; Meinhart, Carl; Guicheteau, Jason A; Christesen, Steven D; Fountain, Augustus W

2016-11-01

A microfluidic device is being developed by University of California-Santa Barbara as part of a joint effort with the United States Army to develop a portable, rapid drug detection device. Surface-enhanced Raman spectroscopy (SERS) is used to provide a sensitive, selective detection technique within the microfluidic platform employing metallic nanoparticles as the SERS medium. Using several illicit drugs as analytes, the work presented here describes the efforts of the Edgewood Chemical Biological Center to optimize the microfluidic platform by investigating the role of nanoparticle material, nanoparticle size, excitation wavelength, and capping agents on the performance, and drug concentration detection limits achievable with Ag and Au nanoparticles that will ultimately be incorporated into the final design. This study is particularly important as it lays out a systematic comparison of limits of detection and potential interferences from working with several nanoparticle capping agents-such as tannate, citrate, and borate-which does not seem to have been done previously as the majority of studies only concentrate on citrate as the capping agent. Morphine, cocaine, and methamphetamine were chosen as test analytes for this study and were observed to have limits of detection (LOD) in the range of (1.5-4.7) × 10 -8 M (4.5-13 ng/mL), with the borate capping agent having the best performance.

Design of a sensor network for structural health monitoring of a full-scale composite horizontal tail

NASA Astrophysics Data System (ADS)

Gao, Dongyue; Wang, Yishou; Wu, Zhanjun; Rahim, Gorgin; Bai, Shengbao

2014-05-01

The detection capability of a given structural health monitoring (SHM) system strongly depends on its sensor network placement. In order to minimize the number of sensors while maximizing the detection capability, optimal design of the PZT sensor network placement is necessary for structural health monitoring (SHM) of a full-scale composite horizontal tail. In this study, the sensor network optimization was simplified as a problem of determining the sensor array placement between stiffeners to achieve the desired the coverage rate. First, an analysis of the structural layout and load distribution of a composite horizontal tail was performed. The constraint conditions of the optimal design were presented. Then, the SHM algorithm of the composite horizontal tail under static load was proposed. Based on the given SHM algorithm, a sensor network was designed for the full-scale composite horizontal tail structure. Effective profiles of cross-stiffener paths (CRPs) and uncross-stiffener paths (URPs) were estimated by a Lamb wave propagation experiment in a multi-stiffener composite specimen. Based on the coverage rate and the redundancy requirements, a seven-sensor array-network was chosen as the optimal sensor network for each airfoil. Finally, a preliminary SHM experiment was performed on a typical composite aircraft structure component. The reliability of the SHM result for a composite horizontal tail structure under static load was validated. In the result, the red zone represented the delamination damage. The detection capability of the optimized sensor network was verified by SHM of a full-scale composite horizontal tail; all the diagnosis results were obtained in two minutes. The result showed that all the damage in the monitoring region was covered by the sensor network.

The SalGI restriction endonuclease. Purification and properties

PubMed Central

Maxwell, Anthony; Halford, Stephen E.

1982-01-01

The type II restriction endonuclease SalGI has been purified to near homogeneity. At least 80% of the protein remaining after the final stage of the preparation is SalGI restriction endonuclease; no contaminating nucleases remain detectable. The principal form of the protein under both native and denaturing conditions is a monomer of Mr about 29000. The optimal conditions for both enzyme stability and enzyme activity have been determined. ImagesFig. 1. PMID:6285898

Schmidt-number witnesses and bound entanglement

NASA Astrophysics Data System (ADS)

Sanpera, Anna; Bruß, Dagmar; Lewenstein, Maciej

2001-05-01

The Schmidt number of a mixed state characterizes the minimum Schmidt rank of the pure states needed to construct it. We investigate the Schmidt number of an arbitrary mixed state by studying Schmidt-number witnesses that detect it. We present a canonical form of such witnesses and provide constructive methods for their optimization. Finally, we present strong evidence that all bound entangled states with positive partial transpose in C3⊗C3 have Schmidt number 2.

Optimization and qualification of an Fc Array assay for assessments of antibodies against HIV-1/SIV.

PubMed

Brown, Eric P; Weiner, Joshua A; Lin, Shu; Natarajan, Harini; Normandin, Erica; Barouch, Dan H; Alter, Galit; Sarzotti-Kelsoe, Marcella; Ackerman, Margaret E

2018-04-01

The Fc Array is a multiplexed assay that assesses the Fc domain characteristics of antigen-specific antibodies with the potential to evaluate up to 500 antigen specificities simultaneously. Antigen-specific antibodies are captured on antigen-conjugated beads and their functional capacity is probed via an array of Fc-binding proteins including antibody subclassing reagents, Fcγ receptors, complement proteins, and lectins. Here we present the results of the optimization and formal qualification of the Fc Array, performed in compliance with Good Clinical Laboratory Practice (GCLP) guidelines. Assay conditions were optimized for performance and reproducibility, and the final version of the assay was then evaluated for specificity, accuracy, precision, limits of detection and quantitation, linearity, range and robustness. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Detection of maize kernels breakage rate based on K-means clustering

NASA Astrophysics Data System (ADS)

Yang, Liang; Wang, Zhuo; Gao, Lei; Bai, Xiaoping

2017-04-01

In order to optimize the recognition accuracy of maize kernels breakage detection and improve the detection efficiency of maize kernels breakage, this paper using computer vision technology and detecting of the maize kernels breakage based on K-means clustering algorithm. First, the collected RGB images are converted into Lab images, then the original images clarity evaluation are evaluated by the energy function of Sobel 8 gradient. Finally, the detection of maize kernels breakage using different pixel acquisition equipments and different shooting angles. In this paper, the broken maize kernels are identified by the color difference between integrity kernels and broken kernels. The original images clarity evaluation and different shooting angles are taken to verify that the clarity and shooting angles of the images have a direct influence on the feature extraction. The results show that K-means clustering algorithm can distinguish the broken maize kernels effectively.

Moving target detection for frequency agility radar by sparse reconstruction

NASA Astrophysics Data System (ADS)

Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

2016-09-01

Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

Research on the trace detection of carbon dioxide gas and modulation parameter optimization based on the TDLAS technology

NASA Astrophysics Data System (ADS)

Zhao, Peng; Tao, Jun; Yu, Chang-rui; Li, Ye

2014-02-01

Based on the technology of tunable diode laser absorption spectroscopy, modulation of the center wavelength of 2004 nm distributed feedback laser diode at a room-temperature, the second harmonic amplitude of CO2 at 2004nm can be obtained. The CO2 concentration can be calculated via the Beer-Lambert law. Sinusoidal modulation parameter is an important factor that affects the sensitivity and accuracy of the system, through the research on the relationship between sinusoidal modulation signal frequency, amplitude and Second harmonic linetype, we finally achieve the detection limit of 10ppm under 12 m optical path.

Moving target detection for frequency agility radar by sparse reconstruction.

PubMed

Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

2016-09-01

Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

Taking side effects into account for HIV medication.

PubMed

Costanza, Vicente; Rivadeneira, Pablo S; Biafore, Federico L; D'Attellis, Carlos E

2010-09-01

A control-theoretic approach to the problem of designing "low-side-effects" therapies for HIV patients based on highly active drugs is substantiated here. The evolution of side effects during treatment is modeled by an extra differential equation coupled to the dynamics of virions, healthy T-cells, and infected ones. The new equation reflects the dependence of collateral damages on the amount of each dose administered to the patient and on the evolution of the viral load detected by periodical blood analysis. The cost objective accounts for recommended bounds on healthy cells and virions, and also penalizes the appearance of collateral morbidities caused by the medication. The optimization problem is solved by a hybrid dynamic programming scheme that adhere to discrete-time observation and control actions, but by maintaining the continuous-time setup for predicting states and side effects. The resulting optimal strategies employ less drugs than those prescribed by previous optimization studies, but maintaining high doses at the beginning and the end of each period of six months. If an inverse discount rate is applied to favor early actions, and under a mild penalization of the final viral load, then the optimal doses are found to be high at the beginning and decrease afterward, thus causing an apparent stabilization of the main variables. But in this case, the final viral load turns higher than acceptable.

A System-Oriented Approach for the Optimal Control of Process Chains under Stochastic Influences

NASA Astrophysics Data System (ADS)

Senn, Melanie; Schäfer, Julian; Pollak, Jürgen; Link, Norbert

2011-09-01

Process chains in manufacturing consist of multiple connected processes in terms of dynamic systems. The properties of a product passing through such a process chain are influenced by the transformation of each single process. There exist various methods for the control of individual processes, such as classical state controllers from cybernetics or function mapping approaches realized by statistical learning. These controllers ensure that a desired state is obtained at process end despite of variations in the input and disturbances. The interactions between the single processes are thereby neglected, but play an important role in the optimization of the entire process chain. We divide the overall optimization into two phases: (1) the solution of the optimization problem by Dynamic Programming to find the optimal control variable values for each process for any encountered end state of its predecessor and (2) the application of the optimal control variables at runtime for the detected initial process state. The optimization problem is solved by selecting adequate control variables for each process in the chain backwards based on predefined quality requirements for the final product. For the demonstration of the proposed concept, we have chosen a process chain from sheet metal manufacturing with simplified transformation functions.

Salient object detection based on discriminative boundary and multiple cues integration

NASA Astrophysics Data System (ADS)

Jiang, Qingzhu; Wu, Zemin; Tian, Chang; Liu, Tao; Zeng, Mingyong; Hu, Lei

2016-01-01

In recent years, many saliency models have achieved good performance by taking the image boundary as the background prior. However, if all boundaries of an image are equally and artificially selected as background, misjudgment may happen when the object touches the boundary. We propose an algorithm called weighted contrast optimization based on discriminative boundary (wCODB). First, a background estimation model is reliably constructed through discriminating each boundary via Hausdorff distance. Second, the background-only weighted contrast is improved by fore-background weighted contrast, which is optimized through weight-adjustable optimization framework. Then to objectively estimate the quality of a saliency map, a simple but effective metric called spatial distribution of saliency map and mean saliency in covered window ratio (MSR) is designed. Finally, in order to further promote the detection result using MSR as the weight, we propose a saliency fusion framework to integrate three other cues-uniqueness, distribution, and coherence from three representative methods into our wCODB model. Extensive experiments on six public datasets demonstrate that our wCODB performs favorably against most of the methods based on boundary, and the integrated result outperforms all state-of-the-art methods.

Hybrid optimization and Bayesian inference techniques for a non-smooth radiation detection problem

DOE PAGES

Stefanescu, Razvan; Schmidt, Kathleen; Hite, Jason; ...

2016-12-12

In this paper, we propose several algorithms to recover the location and intensity of a radiation source located in a simulated 250 × 180 m block of an urban center based on synthetic measurements. Radioactive decay and detection are Poisson random processes, so we employ likelihood functions based on this distribution. Owing to the domain geometry and the proposed response model, the negative logarithm of the likelihood is only piecewise continuous differentiable, and it has multiple local minima. To address these difficulties, we investigate three hybrid algorithms composed of mixed optimization techniques. For global optimization, we consider simulated annealing, particlemore » swarm, and genetic algorithm, which rely solely on objective function evaluations; that is, they do not evaluate the gradient in the objective function. By employing early stopping criteria for the global optimization methods, a pseudo-optimum point is obtained. This is subsequently utilized as the initial value by the deterministic implicit filtering method, which is able to find local extrema in non-smooth functions, to finish the search in a narrow domain. These new hybrid techniques, combining global optimization and implicit filtering address, difficulties associated with the non-smooth response, and their performances, are shown to significantly decrease the computational time over the global optimization methods. To quantify uncertainties associated with the source location and intensity, we employ the delayed rejection adaptive Metropolis and DiffeRential Evolution Adaptive Metropolis algorithms. Finally, marginal densities of the source properties are obtained, and the means of the chains compare accurately with the estimates produced by the hybrid algorithms.« less

Interferometric nanoporous anodic alumina photonic coatings for optical sensing

NASA Astrophysics Data System (ADS)

Chen, Yuting; Santos, Abel; Wang, Ye; Kumeria, Tushar; Wang, Changhai; Li, Junsheng; Losic, Dusan

2015-04-01

Herein, we present a systematic study on the development, optical optimization and sensing applicability of colored photonic coatings based on nanoporous anodic alumina films grown on aluminum substrates. These optical nanostructures, so-called distributed Bragg reflectors (NAA-DBRs), are fabricated by galvanostatic pulse anodization process, in which the current density is altered in a periodic manner in order to engineer the effective medium of the resulting photonic coatings. As-prepared NAA-DBR photonic coatings present brilliant interference colors on the surface of aluminum, which can be tuned at will within the UV-visible spectrum by means of the anodization profile. A broad library of NAA-DBR colors is produced by means of different anodization profiles. Then, the effective medium of these NAA-DBR photonic coatings is systematically assessed in terms of optical sensitivity, low limit of detection and linearity by reflectometric interference spectroscopy (RIfS) in order to optimize their nanoporous structure toward optical sensors with enhanced sensing performance. Finally, we demonstrate the applicability of these photonic nanostructures as optical platforms by selectively detecting gold(iii) ions in aqueous solutions. The obtained results reveal that optimized NAA-DBR photonic coatings can achieve an outstanding sensing performance for gold(iii) ions, with a sensitivity of 22.16 nm μM-1, a low limit of detection of 0.156 μM (i.e. 30.7 ppb) and excellent linearity within the working range (0.9983).Herein, we present a systematic study on the development, optical optimization and sensing applicability of colored photonic coatings based on nanoporous anodic alumina films grown on aluminum substrates. These optical nanostructures, so-called distributed Bragg reflectors (NAA-DBRs), are fabricated by galvanostatic pulse anodization process, in which the current density is altered in a periodic manner in order to engineer the effective medium of the resulting photonic coatings. As-prepared NAA-DBR photonic coatings present brilliant interference colors on the surface of aluminum, which can be tuned at will within the UV-visible spectrum by means of the anodization profile. A broad library of NAA-DBR colors is produced by means of different anodization profiles. Then, the effective medium of these NAA-DBR photonic coatings is systematically assessed in terms of optical sensitivity, low limit of detection and linearity by reflectometric interference spectroscopy (RIfS) in order to optimize their nanoporous structure toward optical sensors with enhanced sensing performance. Finally, we demonstrate the applicability of these photonic nanostructures as optical platforms by selectively detecting gold(iii) ions in aqueous solutions. The obtained results reveal that optimized NAA-DBR photonic coatings can achieve an outstanding sensing performance for gold(iii) ions, with a sensitivity of 22.16 nm μM-1, a low limit of detection of 0.156 μM (i.e. 30.7 ppb) and excellent linearity within the working range (0.9983). Electronic supplementary information (ESI) available: The Supporting Information file provides further information about real-time monitoring of ΔOTeff with changes in the refractive index of the medium filling the nanopores, demonstration of visual red shift in a NAA-DBR sample after infiltration with isopropanol and calculations of linearity (R2) for each NAA-DBR coating. See DOI: 10.1039/c5nr00369e

Fast imaging of live organisms with sculpted light sheets

NASA Astrophysics Data System (ADS)

Chmielewski, Aleksander K.; Kyrsting, Anders; Mahou, Pierre; Wayland, Matthew T.; Muresan, Leila; Evers, Jan Felix; Kaminski, Clemens F.

2015-04-01

Light-sheet microscopy is an increasingly popular technique in the life sciences due to its fast 3D imaging capability of fluorescent samples with low photo toxicity compared to confocal methods. In this work we present a new, fast, flexible and simple to implement method to optimize the illumination light-sheet to the requirement at hand. A telescope composed of two electrically tuneable lenses enables us to define thickness and position of the light-sheet independently but accurately within milliseconds, and therefore optimize image quality of the features of interest interactively. We demonstrated the practical benefit of this technique by 1) assembling large field of views from tiled single exposure each with individually optimized illumination settings; 2) sculpting the light-sheet to trace complex sample shapes within single exposures. This technique proved compatible with confocal line scanning detection, further improving image contrast and resolution. Finally, we determined the effect of light-sheet optimization in the context of scattering tissue, devising procedures for balancing image quality, field of view and acquisition speed.

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

PubMed Central

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

2016-01-01

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

Application of Box-Behnken experimental design to optimize the extraction of insecticidal Cry1Ac from soil.

PubMed

Li, Yan-Liang; Fang, Zhi-Xiang; You, Jing

2013-02-20

A validated method for analyzing Cry proteins is a premise to study the fate and ecological effects of contaminants associated with genetically engineered Bacillus thuringiensis crops. The current study has optimized the extraction method to analyze Cry1Ac protein in soil using a response surface methodology with a three-level-three-factor Box-Behnken experimental design (BBD). The optimum extraction conditions were at 21 °C and 630 rpm for 2 h. Regression analysis showed a good fit of the experimental data to the second-order polynomial model with a coefficient of determination of 0.96. The method was sensitive and precise with a method detection limit of 0.8 ng/g dry weight and relative standard deviations at 7.3%. Finally, the established method was applied for analyzing Cry1Ac protein residues in field-collected soil samples. Trace amounts of Cry1Ac protein were detected in the soils where transgenic crops have been planted for 8 and 12 years.

Geometry-based ensembles: toward a structural characterization of the classification boundary.

PubMed

Pujol, Oriol; Masip, David

2009-06-01

This paper introduces a novel binary discriminative learning technique based on the approximation of the nonlinear decision boundary by a piecewise linear smooth additive model. The decision border is geometrically defined by means of the characterizing boundary points-points that belong to the optimal boundary under a certain notion of robustness. Based on these points, a set of locally robust linear classifiers is defined and assembled by means of a Tikhonov regularized optimization procedure in an additive model to create a final lambda-smooth decision rule. As a result, a very simple and robust classifier with a strong geometrical meaning and nonlinear behavior is obtained. The simplicity of the method allows its extension to cope with some of today's machine learning challenges, such as online learning, large-scale learning or parallelization, with linear computational complexity. We validate our approach on the UCI database, comparing with several state-of-the-art classification techniques. Finally, we apply our technique in online and large-scale scenarios and in six real-life computer vision and pattern recognition problems: gender recognition based on face images, intravascular ultrasound tissue classification, speed traffic sign detection, Chagas' disease myocardial damage severity detection, old musical scores clef classification, and action recognition using 3D accelerometer data from a wearable device. The results are promising and this paper opens a line of research that deserves further attention.

Optimal design of experiments applied to headspace solid phase microextraction for the quantification of vicinal diketones in beer through gas chromatography-mass spectrometric detection.

PubMed

Leça, João M; Pereira, Ana C; Vieira, Ana C; Reis, Marco S; Marques, José C

2015-08-05

Vicinal diketones, namely diacetyl (DC) and pentanedione (PN), are compounds naturally found in beer that play a key role in the definition of its aroma. In lager beer, they are responsible for off-flavors (buttery flavor) and therefore their presence and quantification is of paramount importance to beer producers. Aiming at developing an accurate quantitative monitoring scheme to follow these off-flavor compounds during beer production and in the final product, the head space solid-phase microextraction (HS-SPME) analytical procedure was tuned through experiments planned in an optimal way and the final settings were fully validated. Optimal design of experiments (O-DOE) is a computational, statistically-oriented approach for designing experiences that are most informative according to a well-defined criterion. This methodology was applied for HS-SPME optimization, leading to the following optimal extraction conditions for the quantification of VDK: use a CAR/PDMS fiber, 5 ml of samples in 20 ml vial, 5 min of pre-incubation time followed by 25 min of extraction at 30 °C, with agitation. The validation of the final analytical methodology was performed using a matrix-matched calibration, in order to minimize matrix effects. The following key features were obtained: linearity (R(2) > 0.999, both for diacetyl and 2,3-pentanedione), high sensitivity (LOD of 0.92 μg L(-1) and 2.80 μg L(-1), and LOQ of 3.30 μg L(-1) and 10.01 μg L(-1), for diacetyl and 2,3-pentanedione, respectively), recoveries of approximately 100% and suitable precision (repeatability and reproducibility lower than 3% and 7.5%, respectively). The applicability of the methodology was fully confirmed through an independent analysis of several beer samples, with analyte concentrations ranging from 4 to 200 g L(-1). Copyright © 2015 Elsevier B.V. All rights reserved.

DART-MS analysis of inorganic explosives using high temperature thermal desorption†‡

PubMed Central

Sisco, Edward; Staymates, Matthew; Gillen, Greg

2018-01-01

An ambient mass spectrometry (MS) platform coupling resistive Joule heating thermal desorption (JHTD) and direct analysis in real time (DART) was implemented for the analysis of inorganic nitrite, nitrate, chlorate, and perchlorate salts. The resistive heating component generated discrete and rapid heating ramps and elevated temperatures, up to approximately 400 °C s−1 and 750 °C, by passing a few amperes of DC current through a nichrome wire. JHTD enhanced the utility and capabilities of traditional DART-MS for the trace detection of previously difficult to detect inorganic compounds. A partial factorial design of experiments (DOE) was implemented for the systematic evaluation of five system parameters. A base set of conditions for JHTD-DART-MS was derived from this evaluation, demonstrating sensitive detection of a range of inorganic oxidizer salts, down to single nanogram levels. DOE also identified JHTD filament current and in-source collision induced dissociation (CID) energy as inducing the greatest effect on system response. Tuning of JHTD current provided a method for controlling the relative degrees of thermal desorption and thermal decomposition. Furthermore, in-source CID provided manipulation of adduct and cluster fragmentation, optimizing the detection of molecular anion species. Finally, the differential thermal desorption nature of the JHTD-DART platform demonstrated efficient desorption and detection of organic and inorganic explosive mixtures, with each desorbing at its respective optimal temperature. PMID:29651308

Prospects for detecting oxygen, water, and chlorophyll on an exo-Earth

PubMed Central

Brandt, Timothy D.; Spiegel, David S.

2014-01-01

The goal of finding and characterizing nearby Earth-like planets is driving many NASA high-contrast flagship mission concepts, the latest of which is known as the Advanced Technology Large-Aperture Space Telescope (ATLAST). In this article, we calculate the optimal spectral resolution R = λ/δλ and minimum signal-to-noise ratio per spectral bin (SNR), two central design requirements for a high-contrast space mission, to detect signatures of water, oxygen, and chlorophyll on an Earth twin. We first develop a minimally parametric model and demonstrate its ability to fit synthetic and observed Earth spectra; this allows us to measure the statistical evidence for each component’s presence. We find that water is the easiest to detect, requiring a resolution R ≳ 20, while the optimal resolution for oxygen is likely to be closer to R = 150, somewhat higher than the canonical value in the literature. At these resolutions, detecting oxygen will require approximately two times the SNR as water. Chlorophyll requires approximately six times the SNR as oxygen for an Earth twin, only falling to oxygen-like levels of detectability for a low cloud cover and/or a large vegetation covering fraction. This suggests designing a mission for sensitivity to oxygen and adopting a multitiered observing strategy, first targeting water, then oxygen on the more favorable planets, and finally chlorophyll on only the most promising worlds. PMID:25197095

Prospects for detecting oxygen, water, and chlorophyll on an exo-Earth.

PubMed

Brandt, Timothy D; Spiegel, David S

2014-09-16

The goal of finding and characterizing nearby Earth-like planets is driving many NASA high-contrast flagship mission concepts, the latest of which is known as the Advanced Technology Large-Aperture Space Telescope (ATLAST). In this article, we calculate the optimal spectral resolution R = λ/δλ and minimum signal-to-noise ratio per spectral bin (SNR), two central design requirements for a high-contrast space mission, to detect signatures of water, oxygen, and chlorophyll on an Earth twin. We first develop a minimally parametric model and demonstrate its ability to fit synthetic and observed Earth spectra; this allows us to measure the statistical evidence for each component's presence. We find that water is the easiest to detect, requiring a resolution R ≳ 20, while the optimal resolution for oxygen is likely to be closer to R = 150, somewhat higher than the canonical value in the literature. At these resolutions, detecting oxygen will require approximately two times the SNR as water. Chlorophyll requires approximately six times the SNR as oxygen for an Earth twin, only falling to oxygen-like levels of detectability for a low cloud cover and/or a large vegetation covering fraction. This suggests designing a mission for sensitivity to oxygen and adopting a multitiered observing strategy, first targeting water, then oxygen on the more favorable planets, and finally chlorophyll on only the most promising worlds.

3D-nanostructured Au electrodes for the event-specific detection of MON810 transgenic maize.

PubMed

Fátima Barroso, M; Freitas, Maria; Oliveira, M Beatriz P P; de-Los-Santos-Álvarez, Noemí; Lobo-Castañón, María Jesús; Delerue-Matos, Cristina

2015-03-01

In the present work, the development of a genosensor for the event-specific detection of MON810 transgenic maize is proposed. Taking advantage of nanostructuration, a cost-effective three dimensional electrode was fabricated and a ternary monolayer containing a dithiol, a monothiol and the thiolated capture probe was optimized to minimize the unspecific signals. A sandwich format assay was selected as a way of precluding inefficient hybridization associated with stable secondary target structures. A comparison between the analytical performance of the Au nanostructured electrodes and commercially available screen-printed electrodes highlighted the superior performance of the nanostructured ones. Finally, the genosensor was effectively applied to detect the transgenic sequence in real samples, showing its potential for future quantitative analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

Blurred image restoration using knife-edge function and optimal window Wiener filtering.

PubMed

Wang, Min; Zhou, Shudao; Yan, Wei

2018-01-01

Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects.

Blurred image restoration using knife-edge function and optimal window Wiener filtering

PubMed Central

Zhou, Shudao; Yan, Wei

2018-01-01

Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects. PMID:29377950

Tire-road friction estimation and traction control strategy for motorized electric vehicle.

PubMed

Jin, Li-Qiang; Ling, Mingze; Yue, Weiqiang

2017-01-01

In this paper, an optimal longitudinal slip ratio system for real-time identification of electric vehicle (EV) with motored wheels is proposed based on the adhesion between tire and road surface. First and foremost, the optimal longitudinal slip rate torque control can be identified in real time by calculating the derivative and slip rate of the adhesion coefficient. Secondly, the vehicle speed estimation method is also brought. Thirdly, an ideal vehicle simulation model is proposed to verify the algorithm with simulation, and we find that the slip ratio corresponds to the detection of the adhesion limit in real time. Finally, the proposed strategy is applied to traction control system (TCS). The results showed that the method can effectively identify the state of wheel and calculate the optimal slip ratio without wheel speed sensor; in the meantime, it can improve the accelerated stability of electric vehicle with traction control system (TCS).

Tire-road friction estimation and traction control strategy for motorized electric vehicle

PubMed Central

Jin, Li-Qiang; Yue, Weiqiang

2017-01-01

In this paper, an optimal longitudinal slip ratio system for real-time identification of electric vehicle (EV) with motored wheels is proposed based on the adhesion between tire and road surface. First and foremost, the optimal longitudinal slip rate torque control can be identified in real time by calculating the derivative and slip rate of the adhesion coefficient. Secondly, the vehicle speed estimation method is also brought. Thirdly, an ideal vehicle simulation model is proposed to verify the algorithm with simulation, and we find that the slip ratio corresponds to the detection of the adhesion limit in real time. Finally, the proposed strategy is applied to traction control system (TCS). The results showed that the method can effectively identify the state of wheel and calculate the optimal slip ratio without wheel speed sensor; in the meantime, it can improve the accelerated stability of electric vehicle with traction control system (TCS). PMID:28662053

Label-free detection of biomolecules with Ta2O5-based field effect devices

NASA Astrophysics Data System (ADS)

Branquinho, Rita Maria Mourao Salazar

Field-effect-based devices (FEDs) are becoming a basic structural element in a new generation of micro biosensors. Their numerous advantages such as small size, labelfree response and versatility, together with the possibility of on-chip integration of biosensor arrays with a future prospect of low-cost mass production, make their development highly desirable. The present thesis focuses on the study and optimization of tantalum pentoxide (Ta2O5) deposited by rf magnetron sputtering at room temperature, and their application as sensitive layer in biosensors based on field effect devices (BioFEDs). As such, the influence of several deposition parameters and post-processing annealing temperature and surface plasma treatment on the film¡¦s properties was investigated. Electrolyte-insulator-semiconductor (EIS) field-effect-based sensors comprising the optimized Ta2O5 sensitive layer were applied to the development of BioFEDs. Enzyme functionalized sensors (EnFEDs) were produced for penicillin detection. These sensors were also applied to the label free detection of DNA and the monitoring of its amplification via polymerase chain reaction (PCR), real time PCR (RT-PCR) and loop mediated isothermal amplification (LAMP). Ion sensitive field effect transistors (ISFETs) based on semiconductor oxides comprising the optimized Ta2O5 sensitive layer were also fabricated. EIS sensors comprising Ta2O5 films produced with optimized conditions demonstrated near Nernstian pH sensitivity, 58+/-0.3 mV/pH. These sensors were successfully applied to the label-free detection of penicillin and DNA. Penicillinase functionalized sensors showed a 29+/-7 mV/mM sensitivity towards penicillin detection up to 4 mM penicillin concentration. DNA detection was achieved with 30 mV/mugM sensitivity and DNA amplification monitoring with these sensors showed comparable results to those obtained with standard fluorescence based methods. Semiconductor oxides-based ISFETs with Ta2O5 sensitive layer were also produced. Finally, the high quality and sensitivity demonstrated by Ta2O5 thin films produced at low temperature by rf magnetron sputtering allows for their application as sensitive layer in field effect sensors.

Optimized principal component analysis on coronagraphic images of the fomalhaut system

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

Meshkat, Tiffany; Kenworthy, Matthew A.; Quanz, Sascha P.

We present the results of a study to optimize the principal component analysis (PCA) algorithm for planet detection, a new algorithm complementing angular differential imaging and locally optimized combination of images (LOCI) for increasing the contrast achievable next to a bright star. The stellar point spread function (PSF) is constructed by removing linear combinations of principal components, allowing the flux from an extrasolar planet to shine through. The number of principal components used determines how well the stellar PSF is globally modeled. Using more principal components may decrease the number of speckles in the final image, but also increases themore » background noise. We apply PCA to Fomalhaut Very Large Telescope NaCo images acquired at 4.05 μm with an apodized phase plate. We do not detect any companions, with a model dependent upper mass limit of 13-18 M {sub Jup} from 4-10 AU. PCA achieves greater sensitivity than the LOCI algorithm for the Fomalhaut coronagraphic data by up to 1 mag. We make several adaptations to the PCA code and determine which of these prove the most effective at maximizing the signal-to-noise from a planet very close to its parent star. We demonstrate that optimizing the number of principal components used in PCA proves most effective for pulling out a planet signal.« less

Fault diagnosis of rolling element bearing using a new optimal scale morphology analysis method.

PubMed

Yan, Xiaoan; Jia, Minping; Zhang, Wan; Zhu, Lin

2018-02-01

Periodic transient impulses are key indicators of rolling element bearing defects. Efficient acquisition of impact impulses concerned with the defects is of much concern to the precise detection of bearing defects. However, transient features of rolling element bearing are generally immersed in stochastic noise and harmonic interference. Therefore, in this paper, a new optimal scale morphology analysis method, named adaptive multiscale combination morphological filter-hat transform (AMCMFH), is proposed for rolling element bearing fault diagnosis, which can both reduce stochastic noise and reserve signal details. In this method, firstly, an adaptive selection strategy based on the feature energy factor (FEF) is introduced to determine the optimal structuring element (SE) scale of multiscale combination morphological filter-hat transform (MCMFH). Subsequently, MCMFH containing the optimal SE scale is applied to obtain the impulse components from the bearing vibration signal. Finally, fault types of bearing are confirmed by extracting the defective frequency from envelope spectrum of the impulse components. The validity of the proposed method is verified through the simulated analysis and bearing vibration data derived from the laboratory bench. Results indicate that the proposed method has a good capability to recognize localized faults appeared on rolling element bearing from vibration signal. The study supplies a novel technique for the detection of faulty bearing. Copyright © 2018. Published by Elsevier Ltd.

Optimising the diagnostic strategy for onychomycosis from sample collection to FUNGAL identification evaluation of a diagnostic kit for real-time PCR.

PubMed

Petinataud, Dimitri; Berger, Sibel; Ferdynus, Cyril; Debourgogne, Anne; Contet-Audonneau, Nelly; Machouart, Marie

2016-05-01

Onychomycosis is a common nail disorder mainly due to dermatophytes for which the conventional diagnosis requires direct microscopic observation and culture of a biological sample. Nevertheless, antifungal treatments are commonly prescribed without a mycological examination having been performed, partly because of the slow growth of dermatophytes. Therefore, molecular biology has been applied to this pathology, to support a quick and accurate distinction between onychomycosis and other nail damage. Commercial kits are now available from several companies for improving traditional microbiological diagnosis. In this paper, we present the first evaluation of the real-time PCR kit marketed by Bio Evolution for the diagnosis of dermatophytosis. Secondly, we compare the efficacy of the kit on optimal and non-optimal samples. This study was conducted on 180 nails samples, processed by conventional methods and retrospectively analysed using this kit. According to our results, this molecular kit has shown high specificity and sensitivity in detecting dermatophytes, regardless of sample quality. On the other hand, and as expected, optimal samples allowed the identification of a higher number of dermatophytes by conventional mycological diagnosis, compared to non-optimal samples. Finally, we have suggested several strategies for the practical use of such a kit in a medical laboratory for quick pathogen detection. © 2016 Blackwell Verlag GmbH.

Page layout analysis and classification for complex scanned documents

NASA Astrophysics Data System (ADS)

Erkilinc, M. Sezer; Jaber, Mustafa; Saber, Eli; Bauer, Peter; Depalov, Dejan

2011-09-01

A framework for region/zone classification in color and gray-scale scanned documents is proposed in this paper. The algorithm includes modules for extracting text, photo, and strong edge/line regions. Firstly, a text detection module which is based on wavelet analysis and Run Length Encoding (RLE) technique is employed. Local and global energy maps in high frequency bands of the wavelet domain are generated and used as initial text maps. Further analysis using RLE yields a final text map. The second module is developed to detect image/photo and pictorial regions in the input document. A block-based classifier using basis vector projections is employed to identify photo candidate regions. Then, a final photo map is obtained by applying probabilistic model based on Markov random field (MRF) based maximum a posteriori (MAP) optimization with iterated conditional mode (ICM). The final module detects lines and strong edges using Hough transform and edge-linkages analysis, respectively. The text, photo, and strong edge/line maps are combined to generate a page layout classification of the scanned target document. Experimental results and objective evaluation show that the proposed technique has a very effective performance on variety of simple and complex scanned document types obtained from MediaTeam Oulu document database. The proposed page layout classifier can be used in systems for efficient document storage, content based document retrieval, optical character recognition, mobile phone imagery, and augmented reality.

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

PubMed

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

2015-05-01

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

Effervescence-assisted dispersive solid-phase extraction using ionic-liquid-modified magnetic β-cyclodextrin/attapulgite coupled with high-performance liquid chromatography for fungicide detection in honey and juice.

PubMed

Wu, Xiaoling; Yang, Miyi; Zeng, Haozhe; Xi, Xuefei; Zhang, Sanbing; Lu, Runhua; Gao, Haixiang; Zhou, Wenfeng

2016-11-01

In this study, a simple effervescence-assisted dispersive solid-phase extraction method was developed to detect fungicides in honey and juice. Most significantly, an innovative ionic-liquid-modified magnetic β-cyclodextrin/attapulgite sorbent was used because its large specific surface area enhanced the extraction capacity and also led to facile separation. A one-factor-at-a-time approach and orthogonal design were employed to optimize the experimental parameters. Under the optimized conditions, the entire extraction procedure was completed within 3 min. In addition, the calibration curves exhibited good linearity, and high enrichment factors were achieved for pure water and honey samples. For the honey samples, the extraction efficiencies for the target fungicides ranged from 77.0 to 94.3% with relative standard deviations of 2.3-5.44%. The detection and quantitation limits were in the ranges of 0.07-0.38 and 0.23-1.27 μg/L, respectively. Finally, the developed technique was successfully applied to real samples, and satisfactory results were achieved. This analytical technique is cost-effective, environmentally friendly, and time-saving. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

Cancho, B; Ventur, F; Galceran, M

2000-11-03

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

Detection of Scopolamine Hydrobromide via Surface-enhanced Raman Spectroscopy.

PubMed

Bao, Lin; Sha, Xuan-Yu; Zhao, Hang; Han, Si-Qin-Gao-Wa; Hasi, Wu-Li-Ji

2017-01-01

Surface-enhanced Raman spectroscopy (SERS) was used to measure scopolamine hydrobromide. First, the Raman characteristic peaks of scopolamine hydrobromide were assigned, and the characteristic peaks were determined. The optimal aggregation agent was potassium iodide based on a comparative experimental study. Finally, the SERS spectrum of scopolamine hydrobromide was detected in aqueous solution, and the semi-quantitative analysis and the recovery rate were determined via a linear fitting. The detection limit of scopolamine hydrobromide in aqueous solution was 0.5 μg/mL. From 0 - 10 μg/mL, the curve of the intensity of the Raman characteristic peak of scopolamine hydrobromide at 1002 cm -1 is y = 4017.76 + 642.47x. The correlation coefficient was R 2 = 0.983, the recovery was 98.5 - 109.7%, and the relative standard deviation (RSD) was about 5.5%. This method is fast, accurate, non-destructive and simple for the detection of scopolamine hydrobromide.

Integrated explosive preconcentrator and electrochemical detection system for 2,4,6-trinitrotoluene (TNT) vapor.

PubMed

Cizek, Karel; Prior, Chad; Thammakhet, Chongdee; Galik, Michal; Linker, Kevin; Tsui, Ray; Cagan, Avi; Wake, John; La Belle, Jeff; Wang, Joseph

2010-02-19

This article reports on an integrated explosive-preconcentration/electrochemical detection system for 2,4,6-trinitrotoluene (TNT) vapor. The challenges involved in such system integration are discussed. A hydrogel-coated screen-printed electrode is used for the detection of the thermally desorbed TNT from a preconcentration device using rapid square wave voltammetry. Optimization of the preconcentration system for desorption of TNT and subsequent electrochemical detection was conducted yielding a desorption temperature of 120 degrees C under a flow rate of 500 mL min(-1). Such conditions resulted in a characteristic electrochemical signal for TNT representing the multi-step reduction process. Quantitative measurements produced a linear signal dependence on TNT quantity exposed to the preconcentrator from 0.25 to 10 microg. Finally, the integrated device was successfully demonstrated using a sample of solid TNT located upstream of the preconcentrator. Copyright 2009 Elsevier B.V. All rights reserved.

A signal amplification electrochemical aptasensor for the detection of breast cancer cell via free-running DNA walker.

PubMed

Cai, Shuxian; Chen, Mei; Liu, Mengmeng; He, Wenhui; Liu, Zhijing; Wu, Dongzhi; Xia, Yaokun; Yang, Huanghao; Chen, Jinghua

2016-11-15

Herein, a signal magnification electrochemical aptasensor for the detection of breast cancer cell via free-running DNA walker is constructed. Theoretically, just one DNA walker, released by target cell-responsive reaction, can automatically cleave all D-RNA (a chimeric DNA/RNA oligonucleotide with a cleavage point rArU) anchored on electrode into shorter produces, giving rise to considerably detectable signal finally. Under the optimal conditions, the electrochemical signal decreased linearly with the concentration of MCF-7 cell. The linear range is from 0 to 500 cells mL(-1) with a detection limit of 47 cellsmL(-1). In a word, this approach may have advantages over traditional reported DNA machines for bioassay, particularly in terms of ease of operation, cost efficiency, free of labeling and of complex track design, which may hold great potential for wide application. Copyright © 2016 Elsevier B.V. All rights reserved.

SWAN - Detection of explosives by means of fast neutron activation analysis

NASA Astrophysics Data System (ADS)

Gierlik, M.; Borsuk, S.; Guzik, Z.; Iwanowska, J.; Kaźmierczak, Ł.; Korolczuk, S.; Kozłowski, T.; Krakowski, T.; Marcinkowski, R.; Swiderski, L.; Szeptycka, M.; Szewiński, J.; Urban, A.

2016-10-01

In this work we report on SWAN, the experimental, portable device for explosives detection. The device was created as part of the EU Structural Funds Project "Accelerators & Detectors" (POIG.01.01.02-14-012/08-00), with the goal to increase beneficiary's expertise and competencies in the field of neutron activation analysis. Previous experiences and budged limitations lead toward a less advanced design based on fast neutron interactions and unsophisticated data analysis with the emphasis on the latest gamma detection and spectrometry solutions. The final device has been designed as a portable, fast neutron activation analyzer, with the software optimized for detection of carbon, nitrogen and oxygen. SWAN's performance in the role of explosives detector is elaborated in this paper. We demonstrate that the unique features offered by neutron activation analysis might not be impressive enough when confronted with practical demands and expectations of a generic homeland security customer.

Enhanced production and purification of recombinant surface array protein (Sap) for use in detection of Bacillus anthracis.

PubMed

Puranik, Nidhi; Tripathi, N K; Pal, V; Goel, Ajay Kumar

2018-05-01

Surface array protein (Sap) can be an important biomarker for specific detection of Bacillus anthracis , which is released by the bacterium during its growth in culture broth. In the present work, we have cloned and expressed Sap in Escherichia coli . The culture conditions and cultivation media were optimized and used in batch fermentation process for scale up of Sap in soluble form. The recombinant Sap was purified employing affinity chromatography followed by diafiltration. The final yield of purified protein was 20 and 46 mg/l of culture during shake flasks and batch fermentation, respectively. The protein purity and its reactivity were confirmed employing SDS-PAGE and Western blot, respectively. The antibodies raised against purified Sap were evaluated by Western blotting for detection of Sap released by B. anthracis . Our results showed that the Sap could be a novel marker for detection and confirmation of B. anthracis .

Integration of On-Chip Peristaltic Pumps and Injection Valves with Microchip Electrophoresis and Electrochemical Detection

PubMed Central

Bowen, Amanda L; Martin, R. Scott

2010-01-01

A microfluidic approach that integrates peristaltic pumping from an on-chip reservoir with injection valves, microchip electrophoresis and electrochemical detection is described. Fabrication and operation of both the peristaltic pumps and injection valves were optimized to ensure efficient pumping and discrete injections. The final device uses the peristaltic pumps to continuously direct sample from a reservoir containing a mixture of analytes to injection valves that are coupled with microchip electrophoresis and amperometric detection. The separation and direct detection of dopamine and norepinephrine were possible with this approach and the utility of the device was demonstrated by monitoring the stimulated release of these neurotransmitters from a layer of cells introduced into the microchip. It is also shown that this pumping/reservoir approach can be expanded to multiple reservoirs and pumps, where one reservoir can be addressed individually or multiple reservoirs sampled simultaneously. PMID:20665914

Development and Validation of a Spike Detection and Classification Algorithm Aimed at Implementation on Hardware Devices

PubMed Central

Biffi, E.; Ghezzi, D.; Pedrocchi, A.; Ferrigno, G.

2010-01-01

Neurons cultured in vitro on MicroElectrode Array (MEA) devices connect to each other, forming a network. To study electrophysiological activity and long term plasticity effects, long period recording and spike sorter methods are needed. Therefore, on-line and real time analysis, optimization of memory use and data transmission rate improvement become necessary. We developed an algorithm for amplitude-threshold spikes detection, whose performances were verified with (a) statistical analysis on both simulated and real signal and (b) Big O Notation. Moreover, we developed a PCA-hierarchical classifier, evaluated on simulated and real signal. Finally we proposed a spike detection hardware design on FPGA, whose feasibility was verified in terms of CLBs number, memory occupation and temporal requirements; once realized, it will be able to execute on-line detection and real time waveform analysis, reducing data storage problems. PMID:20300592

Anomaly Detection of Electromyographic Signals.

PubMed

Ijaz, Ahsan; Choi, Jongeun

2018-04-01

In this paper, we provide a robust framework to detect anomalous electromyographic (EMG) signals and identify contamination types. As a first step for feature selection, optimally selected Lawton wavelets transform is applied. Robust principal component analysis (rPCA) is then performed on these wavelet coefficients to obtain features in a lower dimension. The rPCA based features are used for constructing a self-organizing map (SOM). Finally, hierarchical clustering is applied on the SOM that separates anomalous signals residing in the smaller clusters and breaks them into logical units for contamination identification. The proposed methodology is tested using synthetic and real world EMG signals. The synthetic EMG signals are generated using a heteroscedastic process mimicking desired experimental setups. A sub-part of these synthetic signals is introduced with anomalies. These results are followed with real EMG signals introduced with synthetic anomalies. Finally, a heterogeneous real world data set is used with known quality issues under an unsupervised setting. The framework provides recall of 90% (± 3.3) and precision of 99%(±0.4).

Advanced mask cleaning for 0.20-μm technology: an integrated user-supplier approach

NASA Astrophysics Data System (ADS)

Poschenrieder, Rudolf; Hay, Bernd; Beier, Matthias; Hourd, Andrew C.; Stuemer, Harald; Gairing, Thomas M.

1998-12-01

A newly developed photomask final cleaning system, STEAG HamaTech's Advanced Single Substrate Cleaner, ASC 500, was assessed and optimized at the Siemens mask shop in Munich, Germany, under production conditions within the Esprit European Semiconductor Equipment Assessment programme (SEA). The project was carried out together with the active participation of Compugraphics Intl. Ltd. (UK), DuPont Photomasks, Inc. (Germany; Photronics-MZD, Germany). The results of the assessment are presented, focusing on the cleaning performance at the 0.25 micrometer defect level on photomasks, equipment reliability and Cost of Ownership data. A reticle free of soft defects on glass and on chrome down to the 0.25 micrometer level requires an excellent cleaning process and the use of high-end inspection tools like the KLA STARlight. In order to get a full understanding of the nature of the detected features additional investigations on the blank quality have been carried out. These investigations include the questions whether a detection is a hard or a soft defect and whether small defects on chrome are able to move on the reticle surface. Final cleaning recipes have been optimized in respect to cleaning efficiency while maintaining high throughput and low Cost of Ownership. A benchmark comparison against other final cleaning tools at the partner's maskshops showed the leading data of the ASC 500. It was found that a cleaning program which includes several substrate flips and a combination of the available cleaning methods acid- dispense, water pressure jet clean, brush and megasonic clean was best suitable to achieve these goals. In particular the use of the brush unit was shown to improve the yield while not adding damage to the plate.

Analysis of light incident location and detector position in early diagnosis of knee osteoarthritis by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Chen, Yanping; Chen, Yisha; Yan, Huangping; Wang, Xiaoling

2017-01-01

Early detection of knee osteoarthritis (KOA) is meaningful to delay or prevent the onset of osteoarthritis. In consideration of structural complexity of knee joint, position of light incidence and detector appears to be extremely important in optical inspection. In this paper, the propagation of 780-nm near infrared photons in three-dimensional knee joint model is simulated by Monte Carlo (MC) method. Six light incident locations are chosen in total to analyze the influence of incident and detecting location on the number of detected signal photons and signal to noise ratio (SNR). Firstly, a three-dimensional photon propagation model of knee joint is reconstructed based on CT images. Then, MC simulation is performed to study the propagation of photons in three-dimensional knee joint model. Photons which finally migrate out of knee joint surface are numerically analyzed. By analyzing the number of signal photons and SNR from the six given incident locations, the optimal incident and detecting location is defined. Finally, a series of phantom experiments are conducted to verify the simulation results. According to the simulation and phantom experiments results, the best incident location is near the right side of meniscus at the rear end of left knee joint and the detector is supposed to be set near patella, correspondingly.

Power line identification of millimeter wave radar based on PCA-GS-SVM

NASA Astrophysics Data System (ADS)

Fang, Fang; Zhang, Guifeng; Cheng, Yansheng

2017-12-01

Aiming at the problem that the existing detection method can not effectively solve the security of UAV's ultra low altitude flight caused by power line, a power line recognition method based on grid search (GS) and the principal component analysis and support vector machine (PCA-SVM) is proposed. Firstly, the candidate line of Hough transform is reduced by PCA, and the main feature of candidate line is extracted. Then, upport vector machine (SVM is) optimized by grid search method (GS). Finally, using support vector machine classifier optimized parameters to classify the candidate line. MATLAB simulation results show that this method can effectively identify the power line and noise, and has high recognition accuracy and algorithm efficiency.

Optimizing Robinson Operator with Ant Colony Optimization As a Digital Image Edge Detection Method

NASA Astrophysics Data System (ADS)

Yanti Nasution, Tarida; Zarlis, Muhammad; K. M Nasution, Mahyuddin

2017-12-01

Edge detection serves to identify the boundaries of an object against a background of mutual overlap. One of the classic method for edge detection is operator Robinson. Operator Robinson produces a thin, not assertive and grey line edge. To overcome these deficiencies, the proposed improvements to edge detection method with the approach graph with Ant Colony Optimization algorithm. The repairs may be performed are thicken the edge and connect the edges cut off. Edge detection research aims to do optimization of operator Robinson with Ant Colony Optimization then compare the output and generated the inferred extent of Ant Colony Optimization can improve result of edge detection that has not been optimized and improve the accuracy of the results of Robinson edge detection. The parameters used in performance measurement of edge detection are morphology of the resulting edge line, MSE and PSNR. The result showed that Robinson and Ant Colony Optimization method produces images with a more assertive and thick edge. Ant Colony Optimization method is able to be used as a method for optimizing operator Robinson by improving the image result of Robinson detection average 16.77 % than classic Robinson result.

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

Liver imaging with ferumoxides (Feridex): fundamentals, controversies, and practical aspects.

PubMed

Clément, O; Siauve, N; Cuénod, C A; Frija, G

1998-06-01

Superparamagnetic nanoparticles (Feridex) have been recently made available to the radiological community as a contrast agent for MR imaging of the liver. This article reviews the principal physicochemical characteristics of this new compound, with an emphasis on the explanation of the contrast obtained (either positive or negative enhancement) that depends on the local concentration and the sequence used. The clinical use of Feridex is detailed, both for lesion detection and characterization. Finally, some guidelines for image optimization are given.

Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications

PubMed Central

Scheler, Ott; Glynn, Barry; Parkel, Sven; Palta, Priit; Toome, Kadri; Kaplinski, Lauris; Remm, Maido; Maher, Majella; Kurg, Ants

2009-01-01

Background Here we present a novel promising microbial diagnostic method that combines the sensitivity of Nucleic Acid Sequence Based Amplification (NASBA) with the high information content of microarray technology for the detection of bacterial tmRNA molecules. The NASBA protocol was modified to include aminoallyl-UTP (aaUTP) molecules that were incorporated into nascent RNA during the NASBA reaction. Post-amplification labeling with fluorescent dye was carried out subsequently and tmRNA hybridization signal intensities were measured using microarray technology. Significant optimization of the labeled NASBA protocol was required to maintain the required sensitivity of the reactions. Results Two different aaUTP salts were evaluated and optimum final concentrations were identified for both. The final 2 mM concentration of aaUTP Li-salt in NASBA reaction resulted in highest microarray signals overall, being twice as high as the strongest signals with 1 mM aaUTP Na-salt. Conclusion We have successfully demonstrated efficient combination of NASBA amplification technology with microarray based hybridization detection. The method is applicative for many different areas of microbial diagnostics including environmental monitoring, bio threat detection, industrial process monitoring and clinical microbiology. PMID:19445684

Development of solution-gated graphene transistor model for biosensors

NASA Astrophysics Data System (ADS)

Karimi, Hediyeh; Yusof, Rubiyah; Rahmani, Rasoul; Hosseinpour, Hoda; Ahmadi, Mohammad T.

2014-02-01

The distinctive properties of graphene, characterized by its high carrier mobility and biocompatibility, have stimulated extreme scientific interest as a promising nanomaterial for future nanoelectronic applications. In particular, graphene-based transistors have been developed rapidly and are considered as an option for DNA sensing applications. Recent findings in the field of DNA biosensors have led to a renewed interest in the identification of genetic risk factors associated with complex human diseases for diagnosis of cancers or hereditary diseases. In this paper, an analytical model of graphene-based solution gated field effect transistors (SGFET) is proposed to constitute an important step towards development of DNA biosensors with high sensitivity and selectivity. Inspired by this fact, a novel strategy for a DNA sensor model with capability of single-nucleotide polymorphism detection is proposed and extensively explained. First of all, graphene-based DNA sensor model is optimized using particle swarm optimization algorithm. Based on the sensing mechanism of DNA sensors, detective parameters ( I ds and V gmin) are suggested to facilitate the decision making process. Finally, the behaviour of graphene-based SGFET is predicted in the presence of single-nucleotide polymorphism with an accuracy of more than 98% which guarantees the reliability of the optimized model for any application of the graphene-based DNA sensor. It is expected to achieve the rapid, quick and economical detection of DNA hybridization which could speed up the realization of the next generation of the homecare sensor system.

Development of solution-gated graphene transistor model for biosensors

PubMed Central

2014-01-01

The distinctive properties of graphene, characterized by its high carrier mobility and biocompatibility, have stimulated extreme scientific interest as a promising nanomaterial for future nanoelectronic applications. In particular, graphene-based transistors have been developed rapidly and are considered as an option for DNA sensing applications. Recent findings in the field of DNA biosensors have led to a renewed interest in the identification of genetic risk factors associated with complex human diseases for diagnosis of cancers or hereditary diseases. In this paper, an analytical model of graphene-based solution gated field effect transistors (SGFET) is proposed to constitute an important step towards development of DNA biosensors with high sensitivity and selectivity. Inspired by this fact, a novel strategy for a DNA sensor model with capability of single-nucleotide polymorphism detection is proposed and extensively explained. First of all, graphene-based DNA sensor model is optimized using particle swarm optimization algorithm. Based on the sensing mechanism of DNA sensors, detective parameters (Ids and Vgmin) are suggested to facilitate the decision making process. Finally, the behaviour of graphene-based SGFET is predicted in the presence of single-nucleotide polymorphism with an accuracy of more than 98% which guarantees the reliability of the optimized model for any application of the graphene-based DNA sensor. It is expected to achieve the rapid, quick and economical detection of DNA hybridization which could speed up the realization of the next generation of the homecare sensor system. PMID:24517158

Optimization of Stripping Voltammetric Sensor by a Back Propagation Artificial Neural Network for the Accurate Determination of Pb(II) in the Presence of Cd(II).

PubMed

Zhao, Guo; Wang, Hui; Liu, Gang; Wang, Zhiqiang

2016-09-21

An easy, but effective, method has been proposed to detect and quantify the Pb(II) in the presence of Cd(II) based on a Bi/glassy carbon electrode (Bi/GCE) with the combination of a back propagation artificial neural network (BP-ANN) and square wave anodic stripping voltammetry (SWASV) without further electrode modification. The effects of Cd(II) in different concentrations on stripping responses of Pb(II) was studied. The results indicate that the presence of Cd(II) will reduce the prediction precision of a direct calibration model. Therefore, a two-input and one-output BP-ANN was built for the optimization of a stripping voltammetric sensor, which considering the combined effects of Cd(II) and Pb(II) on the SWASV detection of Pb(II) and establishing the nonlinear relationship between the stripping peak currents of Pb(II) and Cd(II) and the concentration of Pb(II). The key parameters of the BP-ANN and the factors affecting the SWASV detection of Pb(II) were optimized. The prediction performance of direct calibration model and BP-ANN model were tested with regard to the mean absolute error (MAE), root mean square error (RMSE), average relative error (ARE), and correlation coefficient. The results proved that the BP-ANN model exhibited higher prediction accuracy than the direct calibration model. Finally, a real samples analysis was performed to determine trace Pb(II) in some soil specimens with satisfactory results.

Novel high-resolution computed tomography-based radiomic classifier for screen-identified pulmonary nodules in the National Lung Screening Trial.

PubMed

Peikert, Tobias; Duan, Fenghai; Rajagopalan, Srinivasan; Karwoski, Ronald A; Clay, Ryan; Robb, Richard A; Qin, Ziling; Sicks, JoRean; Bartholmai, Brian J; Maldonado, Fabien

2018-01-01

Optimization of the clinical management of screen-detected lung nodules is needed to avoid unnecessary diagnostic interventions. Herein we demonstrate the potential value of a novel radiomics-based approach for the classification of screen-detected indeterminate nodules. Independent quantitative variables assessing various radiologic nodule features such as sphericity, flatness, elongation, spiculation, lobulation and curvature were developed from the NLST dataset using 726 indeterminate nodules (all ≥ 7 mm, benign, n = 318 and malignant, n = 408). Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) method for variable selection and regularization in order to enhance the prediction accuracy and interpretability of the multivariate model. The bootstrapping method was then applied for the internal validation and the optimism-corrected AUC was reported for the final model. Eight of the originally considered 57 quantitative radiologic features were selected by LASSO multivariate modeling. These 8 features include variables capturing Location: vertical location (Offset carina centroid z), Size: volume estimate (Minimum enclosing brick), Shape: flatness, Density: texture analysis (Score Indicative of Lesion/Lung Aggression/Abnormality (SILA) texture), and surface characteristics: surface complexity (Maximum shape index and Average shape index), and estimates of surface curvature (Average positive mean curvature and Minimum mean curvature), all with P<0.01. The optimism-corrected AUC for these 8 features is 0.939. Our novel radiomic LDCT-based approach for indeterminate screen-detected nodule characterization appears extremely promising however independent external validation is needed.

Near Real-Time Optimal Prediction of Adverse Events in Aviation Data

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander; Das, Santanu

2010-01-01

The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we demonstrate how to recast the anomaly prediction problem into a form whose solution is accessible as a level-crossing prediction problem. The level-crossing prediction problem has an elegant, optimal, yet untested solution under certain technical constraints, and only when the appropriate modeling assumptions are made. As such, we will thoroughly investigate the resilience of these modeling assumptions, and show how they affect final performance. Finally, the predictive capability of this method will be assessed by quantitative means, using both validation and test data containing anomalies or adverse events from real aviation data sets that have previously been identified as operationally significant by domain experts. It will be shown that the formulation proposed yields a lower false alarm rate on average than competing methods based on similarly advanced concepts, and a higher correct detection rate than a standard method based upon exceedances that is commonly used for prediction.

Simultaneous segmentation of the bone and cartilage surfaces of a knee joint in 3D

NASA Astrophysics Data System (ADS)

Yin, Y.; Zhang, X.; Anderson, D. D.; Brown, T. D.; Hofwegen, C. Van; Sonka, M.

2009-02-01

We present a novel framework for the simultaneous segmentation of multiple interacting surfaces belonging to multiple mutually interacting objects. The method is a non-trivial extension of our previously reported optimal multi-surface segmentation. Considering an example application of knee-cartilage segmentation, the framework consists of the following main steps: 1) Shape model construction: Building a mean shape for each bone of the joint (femur, tibia, patella) from interactively segmented volumetric datasets. Using the resulting mean-shape model - identification of cartilage, non-cartilage, and transition areas on the mean-shape bone model surfaces. 2) Presegmentation: Employment of iterative optimal surface detection method to achieve approximate segmentation of individual bone surfaces. 3) Cross-object surface mapping: Detection of inter-bone equidistant separating sheets to help identify corresponding vertex pairs for all interacting surfaces. 4) Multi-object, multi-surface graph construction and final segmentation: Construction of a single multi-bone, multi-surface graph so that two surfaces (bone and cartilage) with zero and non-zero intervening distances can be detected for each bone of the joint, according to whether or not cartilage can be locally absent or present on the bone. To define inter-object relationships, corresponding vertex pairs identified using the separating sheets were interlinked in the graph. The graph optimization algorithm acted on the entire multiobject, multi-surface graph to yield a globally optimal solution. The segmentation framework was tested on 16 MR-DESS knee-joint datasets from the Osteoarthritis Initiative database. The average signed surface positioning error for the 6 detected surfaces ranged from 0.00 to 0.12 mm. When independently initialized, the signed reproducibility error of bone and cartilage segmentation ranged from 0.00 to 0.26 mm. The results showed that this framework provides robust, accurate, and reproducible segmentation of the knee joint bone and cartilage surfaces of the femur, tibia, and patella. As a general segmentation tool, the developed framework can be applied to a broad range of multi-object segmentation problems.

ToTem: a tool for variant calling pipeline optimization.

PubMed

Tom, Nikola; Tom, Ondrej; Malcikova, Jitka; Pavlova, Sarka; Kubesova, Blanka; Rausch, Tobias; Kolarik, Miroslav; Benes, Vladimir; Bystry, Vojtech; Pospisilova, Sarka

2018-06-26

High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall. Here we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user's priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data. ToTem is a tool for automated pipeline optimization which is freely available as a web application at  https://totem.software .

Wind turbine blade shear web disbond detection using rotor blade operational sensing and data analysis.

PubMed

Myrent, Noah; Adams, Douglas E; Griffith, D Todd

2015-02-28

A wind turbine blade's structural dynamic response is simulated and analysed with the goal of characterizing the presence and severity of a shear web disbond. Computer models of a 5 MW offshore utility-scale wind turbine were created to develop effective algorithms for detecting such damage. Through data analysis and with the use of blade measurements, a shear web disbond was quantified according to its length. An aerodynamic sensitivity study was conducted to ensure robustness of the detection algorithms. In all analyses, the blade's flap-wise acceleration and root-pitching moment were the clearest indicators of the presence and severity of a shear web disbond. A combination of blade and non-blade measurements was formulated into a final algorithm for the detection and quantification of the disbond. The probability of detection was 100% for the optimized wind speed ranges in laminar, 30% horizontal shear and 60% horizontal shear conditions. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Efficient broadband energy detection from the visible to near-infrared using a plasmon FET.

PubMed

Cho, Seongman; Ciappesoni, Mark A; Allen, Monica S; Allen, Jeffery W; Leedy, Kevin D; Wenner, Brett R; Kim, Sung Jin

2018-04-11

Plasmon based field effect transistors (FETs) can be used to convert energy induced by incident optical radiation to electrical energy. Plasmonic FETs can efficiently detect incident light and amplify it by coupling to resonant plasmonic modes thus improving selectivity and signal to noise ratio. The spectral responses can be tailored both through optimization of nanostructure geometry as well as constitutive materials. In this paper, we studied various plasmonic nanostructures using gold for a wideband spectral response from visible to near-infrared. We show, using empirical data and simulation results, that detection loss exponentially increases as the volume of metal nanostructure increases and also a limited spectral response is possible using gold nanostructures in a plasmon to electric conversion device. Finally, we demonstrate a plasmon FET that offers a broadband spectral response from visible to telecommunication wavelengths.

Automatic Detection and Evaluation of Solar Cell Micro-Cracks in Electroluminescence Images Using Matched Filters

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

Spataru, Sergiu; Hacke, Peter; Sera, Dezso

A method for detecting micro-cracks in solar cells using two dimensional matched filters was developed, derived from the electroluminescence intensity profile of typical micro-cracks. We describe the image processing steps to obtain a binary map with the location of the micro-cracks. Finally, we show how to automatically estimate the total length of each micro-crack from these maps, and propose a method to identify severe types of micro-cracks, such as parallel, dendritic, and cracks with multiple orientations. With an optimized threshold parameter, the technique detects over 90 % of cracks larger than 3 cm in length. The method shows great potentialmore » for quantifying micro-crack damage after manufacturing or module transportation for the determination of a module quality criterion for cell cracking in photovoltaic modules.« less

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

PubMed

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

2014-03-01

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

Geodetic Volcano Monitoring Research in Canary Islands: Recent Results

NASA Astrophysics Data System (ADS)

Fernandez, J.; Gonzalez, P. J.; Arjona, A.; Camacho, A. G.; Prieto, J. F.; Seco, A.; Tizzani, P.; Manzo, M. R.; Lanari, R.; Blanco, P.; Mallorqui, J. J.

2009-05-01

The Canarian Archipelago is an oceanic island volcanic chain with a long-standing history of volcanic activity (> 40 Ma). It is located off the NW coast of the African continent, lying over a transitional crust of the Atlantic African passive margin. At least 12 eruptions have been occurred on the islands of Lanzarote, Tenerife and La Palma in the last 500 years. Volcanism manifest predominantly as basaltic strombolian monogenetic activity (whole archipelago) and central felsic volcanism (active only in Tenerife Island). We concentrate our studies in the two most active islands, Tenerife and La Palma. In these islands, we tested different methodologies of geodetic monitoring systems. We use a combination of ground- and space-based techniques. At Tenerife Island, a differential interferometric study was performed to detect areas of deformation. DInSAR detected two clear areas of deformation, using this results a survey-based GPS network was designed and optimized to control those deformations and the rest of the island. Finally, using SBAS DInSAR results weak spatial long- wavelength subsidence signals has been detected. At La Palma, the first DInSAR analysis have not shown any clear deformation, so a first time series analysis was performed detecting a clear subsidence signal at Teneguia volcano, as for Tenerife a GPS network was designed and optimized taking into account stable and deforming areas. After several years of activities, geodetic results served to study ground deformations caused by a wide variety of sources, such as changes in groundwater levels, volcanic activity, volcano-tectonics, gravitational loading, etc. These results proof that a combination of ground-based and space-based techniques is suitable tool for geodetic volcano monitoring in Canary Islands. Finally, we would like to strength that those results could have serious implications on the continuous geodetic monitoring system design and implementation for the Canary Islands which is under development nowadays.

Optimizing model: insemination, replacement, seasonal production, and cash flow.

PubMed

DeLorenzo, M A; Spreen, T H; Bryan, G R; Beede, D K; Van Arendonk, J A

1992-03-01

Dynamic programming to solve the Markov decision process problem of optimal insemination and replacement decisions was adapted to address large dairy herd management decision problems in the US. Expected net present values of cow states (151,200) were used to determine the optimal policy. States were specified by class of parity (n = 12), production level (n = 15), month of calving (n = 12), month of lactation (n = 16), and days open (n = 7). Methodology optimized decisions based on net present value of an individual cow and all replacements over a 20-yr decision horizon. Length of decision horizon was chosen to ensure that optimal policies were determined for an infinite planning horizon. Optimization took 286 s of central processing unit time. The final probability transition matrix was determined, in part, by the optimal policy. It was estimated iteratively to determine post-optimization steady state herd structure, milk production, replacement, feed inputs and costs, and resulting cash flow on a calendar month and annual basis if optimal policies were implemented. Implementation of the model included seasonal effects on lactation curve shapes, estrus detection rates, pregnancy rates, milk prices, replacement costs, cull prices, and genetic progress. Other inputs included calf values, values of dietary TDN and CP per kilogram, and discount rate. Stochastic elements included conception (and, thus, subsequent freshening), cow milk production level within herd, and survival. Validation of optimized solutions was by separate simulation model, which implemented policies on a simulated herd and also described herd dynamics during transition to optimized structure.

Optimization of Evans blue quantitation in limited rat tissue samples

PubMed Central

Wang, Hwai-Lee; Lai, Ted Weita

2014-01-01

Evans blue dye (EBD) is an inert tracer that measures plasma volume in human subjects and vascular permeability in animal models. Quantitation of EBD can be difficult when dye concentration in the sample is limited, such as when extravasated dye is measured in the blood-brain barrier (BBB) intact brain. The procedure described here used a very small volume (30 µl) per sample replicate, which enabled high-throughput measurements of the EBD concentration based on a standard 96-well plate reader. First, ethanol ensured a consistent optic path length in each well and substantially enhanced the sensitivity of EBD fluorescence spectroscopy. Second, trichloroacetic acid (TCA) removed false-positive EBD measurements as a result of biological solutes and partially extracted EBD into the supernatant. Moreover, a 1:2 volume ratio of 50% TCA ([TCA final] = 33.3%) optimally extracted EBD from the rat plasma protein-EBD complex in vitro and in vivo, and 1:2 and 1:3 weight-volume ratios of 50% TCA optimally extracted extravasated EBD from the rat brain and liver, respectively, in vivo. This procedure is particularly useful in the detection of EBD extravasation into the BBB-intact brain, but it can also be applied to detect dye extravasation into tissues where vascular permeability is less limiting. PMID:25300427

Optimization of Evans blue quantitation in limited rat tissue samples

NASA Astrophysics Data System (ADS)

Wang, Hwai-Lee; Lai, Ted Weita

2014-10-01

Evans blue dye (EBD) is an inert tracer that measures plasma volume in human subjects and vascular permeability in animal models. Quantitation of EBD can be difficult when dye concentration in the sample is limited, such as when extravasated dye is measured in the blood-brain barrier (BBB) intact brain. The procedure described here used a very small volume (30 µl) per sample replicate, which enabled high-throughput measurements of the EBD concentration based on a standard 96-well plate reader. First, ethanol ensured a consistent optic path length in each well and substantially enhanced the sensitivity of EBD fluorescence spectroscopy. Second, trichloroacetic acid (TCA) removed false-positive EBD measurements as a result of biological solutes and partially extracted EBD into the supernatant. Moreover, a 1:2 volume ratio of 50% TCA ([TCA final] = 33.3%) optimally extracted EBD from the rat plasma protein-EBD complex in vitro and in vivo, and 1:2 and 1:3 weight-volume ratios of 50% TCA optimally extracted extravasated EBD from the rat brain and liver, respectively, in vivo. This procedure is particularly useful in the detection of EBD extravasation into the BBB-intact brain, but it can also be applied to detect dye extravasation into tissues where vascular permeability is less limiting.

An accurate homogenized tissue phantom for broad spectrum autofluorescence studies: a tool for optimizing quantum dot-based contrast agents

NASA Astrophysics Data System (ADS)

Roy, Mathieu; Wilson, Brian C.

2008-02-01

We are investigating the use of ZnS-capped CdSe quantum dot (QD) bioconjugates combined with fluorescence endoscopy for improved early cancer detection in the esophagus, colon and lung. A major challenge in using fluorescent contrast agents in vivo is to extract the relevant signal from the tissue autofluorescence (AF). The present studies are aimed at maximizing the QD signal to AF background ratio (SBR) to facilitate detection. These contrast optimization studies require optical phantoms that simulate tissue autofluorescence, absorption and scattering over the entire visible spectrum, while allowing us to control the optical thickness. We present an optical phantom made of fresh homogenized tissue diluted in water. The homogenized tissue is poured into a clear polymer tank designed to hold a QD-loaded silica capillary in its center. Because of the non-linear effects of absorption and scattering on measured autofluorescence, direct comparison between results obtained using tissue phantoms of different concentration is not possible. We introduce mathematical models that make it possible to perform measurements on diluted tissue homogenates and subsequently extrapolate the results to intact (non-diluted) tissue. Finally, we present preliminary QD contrast data showing that the 380-420 nm spectral window is optimal for surface QD imaging.

Exploration of Objective Functions for Optimal Placement of Weather Stations

NASA Astrophysics Data System (ADS)

Snyder, A.; Dietterich, T.; Selker, J. S.

2016-12-01

Many regions of Earth lack ground-based sensing of weather variables. For example, most countries in Sub-Saharan Africa do not have reliable weather station networks. This absence of sensor data has many consequences ranging from public safety (poor prediction and detection of severe weather events), to agriculture (lack of crop insurance), to science (reduced quality of world-wide weather forecasts, climate change measurement, etc.). The Trans-African Hydro-Meteorological Observatory (TAHMO.org) project seeks to address these problems by deploying and operating a large network of weather stations throughout Sub-Saharan Africa. To design the TAHMO network, we must determine where to locate each weather station. We can formulate this as the following optimization problem: Determine a set of N sites that jointly optimize the value of an objective function. The purpose of this poster is to propose and assess several objective functions. In addition to standard objectives (e.g., minimizing the summed squared error of interpolated values over the entire region), we consider objectives that minimize the maximum error over the region and objectives that optimize the detection of extreme events. An additional issue is that each station measures more than 10 variables—how should we balance the accuracy of our interpolated maps for each variable? Weather sensors inevitably drift out of calibration or fail altogether. How can we incorporate robustness to failed sensors into our network design? Another important requirement is that the network should make it possible to detect failed sensors by comparing their readings with those of other stations. How can this requirement be met? Finally, we provide an initial assessment of the computational cost of optimizing these various objective functions. We invite everyone to join the discussion at our poster by proposing additional objectives, identifying additional issues to consider, and expanding our bibliography of relevant papers. A prize (derived from grapes grown in Oregon) will be awarded for the most insightful contribution to the discussion!

A risk-based multi-objective model for optimal placement of sensors in water distribution system

NASA Astrophysics Data System (ADS)

Naserizade, Sareh S.; Nikoo, Mohammad Reza; Montaseri, Hossein

2018-02-01

In this study, a new stochastic model based on Conditional Value at Risk (CVaR) and multi-objective optimization methods is developed for optimal placement of sensors in water distribution system (WDS). This model determines minimization of risk which is caused by simultaneous multi-point contamination injection in WDS using CVaR approach. The CVaR considers uncertainties of contamination injection in the form of probability distribution function and calculates low-probability extreme events. In this approach, extreme losses occur at tail of the losses distribution function. Four-objective optimization model based on NSGA-II algorithm is developed to minimize losses of contamination injection (through CVaR of affected population and detection time) and also minimize the two other main criteria of optimal placement of sensors including probability of undetected events and cost. Finally, to determine the best solution, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), as a subgroup of Multi Criteria Decision Making (MCDM) approach, is utilized to rank the alternatives on the trade-off curve among objective functions. Also, sensitivity analysis is done to investigate the importance of each criterion on PROMETHEE results considering three relative weighting scenarios. The effectiveness of the proposed methodology is examined through applying it to Lamerd WDS in the southwestern part of Iran. The PROMETHEE suggests 6 sensors with suitable distribution that approximately cover all regions of WDS. Optimal values related to CVaR of affected population and detection time as well as probability of undetected events for the best optimal solution are equal to 17,055 persons, 31 mins and 0.045%, respectively. The obtained results of the proposed methodology in Lamerd WDS show applicability of CVaR-based multi-objective simulation-optimization model for incorporating the main uncertainties of contamination injection in order to evaluate extreme value of losses in WDS.

Enhanced Fuel-Optimal Trajectory-Generation Algorithm for Planetary Pinpoint Landing

NASA Technical Reports Server (NTRS)

Acikmese, Behcet; Blackmore, James C.; Scharf, Daniel P.

2011-01-01

An enhanced algorithm is developed that builds on a previous innovation of fuel-optimal powered-descent guidance (PDG) for planetary pinpoint landing. The PDG problem is to compute constrained, fuel-optimal trajectories to land a craft at a prescribed target on a planetary surface, starting from a parachute cut-off point and using a throttleable descent engine. The previous innovation showed the minimal-fuel PDG problem can be posed as a convex optimization problem, in particular, as a Second-Order Cone Program, which can be solved to global optimality with deterministic convergence properties, and hence is a candidate for onboard implementation. To increase the speed and robustness of this convex PDG algorithm for possible onboard implementation, the following enhancements are incorporated: 1) Fast detection of infeasibility (i.e., control authority is not sufficient for soft-landing) for subsequent fault response. 2) The use of a piecewise-linear control parameterization, providing smooth solution trajectories and increasing computational efficiency. 3) An enhanced line-search algorithm for optimal time-of-flight, providing quicker convergence and bounding the number of path-planning iterations needed. 4) An additional constraint that analytically guarantees inter-sample satisfaction of glide-slope and non-sub-surface flight constraints, allowing larger discretizations and, hence, faster optimization. 5) Explicit incorporation of Mars rotation rate into the trajectory computation for improved targeting accuracy. These enhancements allow faster convergence to the fuel-optimal solution and, more importantly, remove the need for a "human-in-the-loop," as constraints will be satisfied over the entire path-planning interval independent of step-size (as opposed to just at the discrete time points) and infeasible initial conditions are immediately detected. Finally, while the PDG stage is typically only a few minutes, ignoring the rotation rate of Mars can introduce 10s of meters of error. By incorporating it, the enhanced PDG algorithm becomes capable of pinpoint targeting.

Individual differences in attention strategies during detection, fine discrimination, and coarse discrimination

PubMed Central

Hecker, Elizabeth A.; Serences, John T.; Srinivasan, Ramesh

2013-01-01

Interacting with the environment requires the ability to flexibly direct attention to relevant features. We examined the degree to which individuals attend to visual features within and across Detection, Fine Discrimination, and Coarse Discrimination tasks. Electroencephalographic (EEG) responses were measured to an unattended peripheral flickering (4 or 6 Hz) grating while individuals (n = 33) attended to orientations that were offset by 0°, 10°, 20°, 30°, 40°, and 90° from the orientation of the unattended flicker. These unattended responses may be sensitive to attentional gain at the attended spatial location, since attention to features enhances early visual responses throughout the visual field. We found no significant differences in tuning curves across the three tasks in part due to individual differences in strategies. We sought to characterize individual attention strategies using hierarchical Bayesian modeling, which grouped individuals into families of curves that reflect attention to the physical target orientation (“on-channel”) or away from the target orientation (“off-channel”) or a uniform distribution of attention. The different curves were related to behavioral performance; individuals with “on-channel” curves had lower thresholds than individuals with uniform curves. Individuals with “off-channel” curves during Fine Discrimination additionally had lower thresholds than those assigned to uniform curves, highlighting the perceptual benefits of attending away from the physical target orientation during fine discriminations. Finally, we showed that a subset of individuals with optimal curves (“on-channel”) during Detection also demonstrated optimal curves (“off-channel”) during Fine Discrimination, indicating that a subset of individuals can modulate tuning optimally for detection and discrimination. PMID:23678013

A complete solution of cartographic displacement based on elastic beams model and Delaunay triangulation

NASA Astrophysics Data System (ADS)

Liu, Y.; Guo, Q.; Sun, Y.

2014-04-01

In map production and generalization, it is inevitable to arise some spatial conflicts, but the detection and resolution of these spatial conflicts still requires manual operation. It is become a bottleneck hindering the development of automated cartographic generalization. Displacement is the most useful contextual operator that is often used for resolving the conflicts arising between two or more map objects. Automated generalization researches have reported many approaches of displacement including sequential approaches and optimization approaches. As an excellent optimization approach on the basis of energy minimization principles, elastic beams model has been used in resolving displacement problem of roads and buildings for several times. However, to realize a complete displacement solution, techniques of conflict detection and spatial context analysis should be also take into consideration. So we proposed a complete solution of displacement based on the combined use of elastic beams model and constrained Delaunay triangulation (CDT) in this paper. The solution designed as a cyclic and iterative process containing two phases: detection phase and displacement phase. In detection phase, CDT of map is use to detect proximity conflicts, identify spatial relationships and structures, and construct auxiliary structure, so as to support the displacement phase on the basis of elastic beams. In addition, for the improvements of displacement algorithm, a method for adaptive parameters setting and a new iterative strategy are put forward. Finally, we implemented our solution on a testing map generalization platform, and successfully tested it against 2 hand-generated test datasets of roads and buildings respectively.

One-pot synthesis of a multi-template molecularly imprinted polymer for the extraction of six sulfonamide residues from milk before high-performance liquid chromatography with diode array detection.

PubMed

Kechagia, Maria; Samanidou, Victoria; Kabir, Abuzar; Furton, Kenneth G

2018-02-01

A highly selective molecularly imprinted polymer sorbent was synthesized and employed for the simultaneous determination of six sulfonamide antibiotic residues (sulfanilamide, sulfacetamide, sulfadiazine, sulfathiazole, sulfamerazine, and sulfamethizole) in milk samples. Multi-analyte imprinted particles were used as a sorbent in solid-phase extraction. Sulfonamides were separated on a high-performance liquid chromatography column (Merck-Lichrospher RP18e, 5 μm 250 × 4 mm) and further identified and quantified by diode array detection. Several parameters including required loading of the molecularly imprinted polymer sorbent, mass of milk, volume, and type of elution solvent, as well as time for absorption and elution were investigated to obtain optimal experimental conditions. For comparison purpose, a non-imprinted polymer was applied under the optimum conditions. The validation study according to the European Union Decision 2002/657/EC was based on the investigation of linearity, selectivity, stability, limits of detection and quantitation, decision limit, detection capability, trueness, precision, and ruggedness according to Youden's approach. The decision limit and detection capability values in the milk were achieved from 101.9 to 113.5 μg/kg and from 114.4 to 135.4 μg/kg, respectively, depending on the target sulfonamide drug. Finally, the optimized protocol was successfully applied to commercial milk samples and human breast milk. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On-line high-performance liquid chromatography-ultraviolet-nuclear magnetic resonance method of the markers of nerve agents for verification of the Chemical Weapons Convention.

PubMed

Mazumder, Avik; Gupta, Hemendra K; Garg, Prabhat; Jain, Rajeev; Dubey, Devendra K

2009-07-03

This paper details an on-flow liquid chromatography-ultraviolet-nuclear magnetic resonance (LC-UV-NMR) method for the retrospective detection and identification of alkyl alkylphosphonic acids (AAPAs) and alkylphosphonic acids (APAs), the markers of the toxic nerve agents for verification of the Chemical Weapons Convention (CWC). Initially, the LC-UV-NMR parameters were optimized for benzyl derivatives of the APAs and AAPAs. The optimized parameters include stationary phase C(18), mobile phase methanol:water 78:22 (v/v), UV detection at 268nm and (1)H NMR acquisition conditions. The protocol described herein allowed the detection of analytes through acquisition of high quality NMR spectra from the aqueous solution of the APAs and AAPAs with high concentrations of interfering background chemicals which have been removed by preceding sample preparation. The reported standard deviation for the quantification is related to the UV detector which showed relative standard deviations (RSDs) for quantification within +/-1.1%, while lower limit of detection upto 16mug (in mug absolute) for the NMR detector. Finally the developed LC-UV-NMR method was applied to identify the APAs and AAPAs in real water samples, consequent to solid phase extraction and derivatization. The method is fast (total experiment time approximately 2h), sensitive, rugged and efficient.

Optimization and validation of moving average quality control procedures using bias detection curves and moving average validation charts.

PubMed

van Rossum, Huub H; Kemperman, Hans

2017-02-01

To date, no practical tools are available to obtain optimal settings for moving average (MA) as a continuous analytical quality control instrument. Also, there is no knowledge of the true bias detection properties of applied MA. We describe the use of bias detection curves for MA optimization and MA validation charts for validation of MA. MA optimization was performed on a data set of previously obtained consecutive assay results. Bias introduction and MA bias detection were simulated for multiple MA procedures (combination of truncation limits, calculation algorithms and control limits) and performed for various biases. Bias detection curves were generated by plotting the median number of test results needed for bias detection against the simulated introduced bias. In MA validation charts the minimum, median, and maximum numbers of assay results required for MA bias detection are shown for various bias. Their use was demonstrated for sodium, potassium, and albumin. Bias detection curves allowed optimization of MA settings by graphical comparison of bias detection properties of multiple MA. The optimal MA was selected based on the bias detection characteristics obtained. MA validation charts were generated for selected optimal MA and provided insight into the range of results required for MA bias detection. Bias detection curves and MA validation charts are useful tools for optimization and validation of MA procedures.

Microseismic event location using global optimization algorithms: An integrated and automated workflow

NASA Astrophysics Data System (ADS)

Lagos, Soledad R.; Velis, Danilo R.

2018-02-01

We perform the location of microseismic events generated in hydraulic fracturing monitoring scenarios using two global optimization techniques: Very Fast Simulated Annealing (VFSA) and Particle Swarm Optimization (PSO), and compare them against the classical grid search (GS). To this end, we present an integrated and optimized workflow that concatenates into an automated bash script the different steps that lead to the microseismic events location from raw 3C data. First, we carry out the automatic detection, denoising and identification of the P- and S-waves. Secondly, we estimate their corresponding backazimuths using polarization information, and propose a simple energy-based criterion to automatically decide which is the most reliable estimate. Finally, after taking proper care of the size of the search space using the backazimuth information, we perform the location using the aforementioned algorithms for 2D and 3D usual scenarios of hydraulic fracturing processes. We assess the impact of restricting the search space and show the advantages of using either VFSA or PSO over GS to attain significant speed-ups.

Development, optimization and validation of gas chromatographic fingerprinting of Brazilian commercial diesel fuel for quality control.

PubMed

dos Santos, Bruno César Diniz Brito; Flumignan, Danilo Luiz; de Oliveira, José Eduardo

2012-10-01

A three-step development, optimization and validation strategy is described for gas chromatography (GC) fingerprints of Brazilian commercial diesel fuel. A suitable GC-flame ionization detection (FID) system was selected to assay a complex matrix such as diesel. The next step was to improve acceptable chromatographic resolution with reduced analysis time, which is recommended for routine applications. Full three-level factorial designs were performed to improve flow rate, oven ramps, injection volume and split ratio in the GC system. Finally, several validation parameters were performed. The GC fingerprinting can be coupled with pattern recognition and multivariate regressions analyses to determine fuel quality and fuel physicochemical parameters. This strategy can also be applied to develop fingerprints for quality control of other fuel types.

Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept

PubMed Central

Wang, Fei; Salous, Sana; Zhou, Jianjiang

2017-01-01

In this paper, we investigate a low probability of intercept (LPI)-based optimal power allocation strategy for a joint bistatic radar and communication system, which is composed of a dedicated transmitter, a radar receiver, and a communication receiver. The joint system is capable of fulfilling the requirements of both radar and communications simultaneously. First, assuming that the signal-to-noise ratio (SNR) corresponding to the target surveillance path is much weaker than that corresponding to the line of sight path at radar receiver, the analytically closed-form expression for the probability of false alarm is calculated, whereas the closed-form expression for the probability of detection is not analytically tractable and is approximated due to the fact that the received signals are not zero-mean Gaussian under target presence hypothesis. Then, an LPI-based optimal power allocation strategy is presented to minimize the total transmission power for information signal and radar waveform, which is constrained by a specified information rate for the communication receiver and the desired probabilities of detection and false alarm for the radar receiver. The well-known bisection search method is employed to solve the resulting constrained optimization problem. Finally, numerical simulations are provided to reveal the effects of several system parameters on the power allocation results. It is also demonstrated that the LPI performance of the joint bistatic radar and communication system can be markedly improved by utilizing the proposed scheme. PMID:29186850

Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept.

PubMed

Shi, Chenguang; Wang, Fei; Salous, Sana; Zhou, Jianjiang

2017-11-25

In this paper, we investigate a low probability of intercept (LPI)-based optimal power allocation strategy for a joint bistatic radar and communication system, which is composed of a dedicated transmitter, a radar receiver, and a communication receiver. The joint system is capable of fulfilling the requirements of both radar and communications simultaneously. First, assuming that the signal-to-noise ratio (SNR) corresponding to the target surveillance path is much weaker than that corresponding to the line of sight path at radar receiver, the analytically closed-form expression for the probability of false alarm is calculated, whereas the closed-form expression for the probability of detection is not analytically tractable and is approximated due to the fact that the received signals are not zero-mean Gaussian under target presence hypothesis. Then, an LPI-based optimal power allocation strategy is presented to minimize the total transmission power for information signal and radar waveform, which is constrained by a specified information rate for the communication receiver and the desired probabilities of detection and false alarm for the radar receiver. The well-known bisection search method is employed to solve the resulting constrained optimization problem. Finally, numerical simulations are provided to reveal the effects of several system parameters on the power allocation results. It is also demonstrated that the LPI performance of the joint bistatic radar and communication system can be markedly improved by utilizing the proposed scheme.

Advantages of capillary electrophoresis for determination of choline in pharmaceutical preparations.

PubMed

Lambert, A; Colin, J L; Leroy, P; Nicolas, A

1998-01-01

Assay of choline in pharmaceutical preparations was realized by capillary zone electrophoresis (CZE) coupled with indirect UV detection. The suitability of several background electrolytes was investigated to optimize the separation of choline from other components such as amino acids, betaine and cations. Final operating conditions were as follows: a 75 microns x 50 cm uncoated fused-silica capillary with an electrolyte consisting of 5 mM creatinine pH 3.2, a voltage of 25 kV, a temperature of 25 degrees C and an UV detection at 210 nm. Choline migrates in less than 5 min and full selectivity vs other analytes was achieved. Validation data compared with those obtained with HPLC demonstrated the interest of CZE.

High Frequency Active Auroral Research Program (HAARP) imager. Final report, 29 August 1991-29 August 1993

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

Lance, C.; Eather, R.

1993-09-30

A low-light-level monochromatic imaging system was designed and fabricated which was optimized to detect and record optical emissions associated with high-power rf heating of the ionosphere. The instrument is capable of detecting very low intensities, of the order of 1 Rayleigh, from typical ionospheric atomic and molecular emissions. This is achieved through co-adding of ON images during heater pulses and subtraction of OFF (background) images between pulses. Images can be displayed and analyzed in real time and stored in optical disc for later analysis. Full image processing software is provided which was customized for this application and uses menu ormore » mouse user interaction.« less

Simultaneous fault detection and control design for switched systems with two quantized signals.

PubMed

Li, Jian; Park, Ju H; Ye, Dan

2017-01-01

The problem of simultaneous fault detection and control design for switched systems with two quantized signals is presented in this paper. Dynamic quantizers are employed, respectively, before the output is passed to fault detector, and before the control input is transmitted to the switched system. Taking the quantized errors into account, the robust performance for this kind of system is given. Furthermore, sufficient conditions for the existence of fault detector/controller are presented in the framework of linear matrix inequalities, and fault detector/controller gains and the supremum of quantizer range are derived by a convex optimized method. Finally, two illustrative examples demonstrate the effectiveness of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Biotransformation of menadione to its prenylated derivative MK-3 using recombinant Pichia pastoris.

PubMed

Li, Zhemin; Zhao, Genhai; Liu, Hui; Guo, Yugang; Wu, Hefang; Sun, Xiaowen; Wu, Xihua; Zheng, Zhiming

2017-07-01

Prenylated quinones, especially menaquinones, have significant physiological activities, but are arduous to synthesize efficiently. Due to the relaxed aromatic substrate specificity and prenylation regiospecificity at the ortho- site of the phenolic hydroxyl group, the aromatic prenyltransferase NovQ from Streptomyces may be useful in menaquinone synthesis from menadione. In this study, NovQ was overexpressed in Pichia pastoris. After fermentation optimization, NovQ production increased by 1617%. Then the different effects of metal ions, detergents and pH on the activity of purified NovQ were investigated to optimize the prenylation reaction. Finally, purified NovQ and cells containing NovQ were used for menadione prenylation in vitro and in vivo, respectively. Menaquinone-1 (MK-1) was detected as the only product in vitro with γ,γ-dimethylallyl pyrophosphate and menadione hydroquinol substrates. MK-3 at a concentration of 90.53 mg/L was detected as the major product of whole cell catalysis with 3-methyl-2-buten-1-ol and menadione hydroquinol substrates. This study realized whole cell catalysis converting menadione to menaquinones.

Automated Sperm Head Detection Using Intersecting Cortical Model Optimised by Particle Swarm Optimization.

PubMed

Tan, Weng Chun; Mat Isa, Nor Ashidi

2016-01-01

In human sperm motility analysis, sperm segmentation plays an important role to determine the location of multiple sperms. To ensure an improved segmentation result, the Laplacian of Gaussian filter is implemented as a kernel in a pre-processing step before applying the image segmentation process to automatically segment and detect human spermatozoa. This study proposes an intersecting cortical model (ICM), which was derived from several visual cortex models, to segment the sperm head region. However, the proposed method suffered from parameter selection; thus, the ICM network is optimised using particle swarm optimization where feature mutual information is introduced as the new fitness function. The final results showed that the proposed method is more accurate and robust than four state-of-the-art segmentation methods. The proposed method resulted in rates of 98.14%, 98.82%, 86.46% and 99.81% in accuracy, sensitivity, specificity and precision, respectively, after testing with 1200 sperms. The proposed algorithm is expected to be implemented in analysing sperm motility because of the robustness and capability of this algorithm.

Delineation and geometric modeling of road networks

NASA Astrophysics Data System (ADS)

Poullis, Charalambos; You, Suya

In this work we present a novel vision-based system for automatic detection and extraction of complex road networks from various sensor resources such as aerial photographs, satellite images, and LiDAR. Uniquely, the proposed system is an integrated solution that merges the power of perceptual grouping theory (Gabor filtering, tensor voting) and optimized segmentation techniques (global optimization using graph-cuts) into a unified framework to address the challenging problems of geospatial feature detection and classification. Firstly, the local precision of the Gabor filters is combined with the global context of the tensor voting to produce accurate classification of the geospatial features. In addition, the tensorial representation used for the encoding of the data eliminates the need for any thresholds, therefore removing any data dependencies. Secondly, a novel orientation-based segmentation is presented which incorporates the classification of the perceptual grouping, and results in segmentations with better defined boundaries and continuous linear segments. Finally, a set of gaussian-based filters are applied to automatically extract centerline information (magnitude, width and orientation). This information is then used for creating road segments and transforming them to their polygonal representations.

Facile and sensitive determination of N-nitrosamines in food samples by high-performance liquid chromatography via combining fluorescent labeling with dispersive liquid-liquid microextraction.

PubMed

Lu, Shuaimin; Wu, Di; Li, Guoliang; Lv, Zhengxian; Gong, Peiwei; Xia, Lian; Sun, Zhiwei; Chen, Guang; Chen, Xuefeng; You, Jinmao; Wu, Yongning

2017-11-01

The intake of N-nitrosamines (NAs) from foodstuffs is considered to be an important influence factor for several cancers. But the rapid and sensitive screening of NAs remains a challenge in the field of food safety. Inspired by that, a sensitive and rapid method was demonstrated for determination of five NAs (Nitrosopyrrolidine, Nitrosodimethylamine, Nitrosodiethylamine, Nitrosodipropylamine and Nitrosodibutylamine) using dispersive liquid-liquid microextraction (DLLME) followed by high-performance liquid chromatography with fluorescence detection (HPLC-FLD). The NAs were firstly denitrosated and labeled by 2-(11H-benzo[a]carbazol-11-yl) ethyl carbonochloridate (BCEC-Cl) and finally enriched by DLLME. Furthermore, the main DLLME conditions were optimized systematically. Under the optimal conditions, satisfactory limits of detection (LODs) were obtained with a range of 0.01-0.07ngg -1 , which were significantly lower than the reported methods. The developed method showed many merits including rapidity, simplicity, high sensitivity and excellent selectivity, which shows a broad prospect in food safety analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Acid phosphatase test on Phadebas® sheets - An optimized method for presumptive saliva and semen detection.

PubMed

Herman, Yael; Feine, Ilan; Gafny, Ron

2018-04-30

The precise and efficient detection of semen and saliva in sexual assault case-work items is a critical step in the forensic pipeline. The outcome of this stage may have a profound impact on identifying perpetrators as well as on the investigation process and the final outcome in court. Semen detection is usually based on the activity of acid phosphatase (AP), an enzyme found in high concentration in the seminal plasma. Amylase, an enzyme catalyzing starch hydrolysis is found in high concentrations in saliva and therefore is a useful target for its detection. To screen case-work items, both presumptive tests require transfer of biological material from the item to paper in a moisturized environment. Since semen and saliva may appear in the same item, it is required in some cases to perform the tests one after the other. This may reduce the chances of identifying all stains on the item and obtaining a DNA profile. In the present study, we applied the AP biochemical test on a Phadebas ® sheet, a commercial starch containing paper used to detect saliva. This approach was found to be sensitive enough to detect diluted semen (1:50) after performing the Phadebas ® press test. In addition, it enabled detection of adjacent saliva and semen stains and stains containing a semen-saliva mixture. Finally, a DNA profile was successfully obtained from the Phadebas ® sheets after semen detection, a useful feature if the original item is lost or damaged. Taken together, this method provides a practical, reliable and convenient tool for screening sexual assault items of evidence. Copyright © 2018 Elsevier B.V. All rights reserved.

Signal Amplification Technologies for the Detection of Nucleic Acids: from Cell-Free Analysis to Live-Cell Imaging.

PubMed

Fozooni, Tahereh; Ravan, Hadi; Sasan, Hosseinali

2017-12-01

Due to their unique properties, such as programmability, ligand-binding capability, and flexibility, nucleic acids can serve as analytes and/or recognition elements for biosensing. To improve the sensitivity of nucleic acid-based biosensing and hence the detection of a few copies of target molecule, different modern amplification methodologies, namely target-and-signal-based amplification strategies, have already been developed. These recent signal amplification technologies, which are capable of amplifying the signal intensity without changing the targets' copy number, have resulted in fast, reliable, and sensitive methods for nucleic acid detection. Working in cell-free settings, researchers have been able to optimize a variety of complex and quantitative methods suitable for deploying in live-cell conditions. In this study, a comprehensive review of the signal amplification technologies for the detection of nucleic acids is provided. We classify the signal amplification methodologies into enzymatic and non-enzymatic strategies with a primary focus on the methods that enable us to shift away from in vitro detecting to in vivo imaging. Finally, the future challenges and limitations of detection for cellular conditions are discussed.

Microchip-based Integration of Cell Immobilization, Electrophoresis, Post-column Derivatization, and Fluorescence Detection for Monitoring the Release of Dopamine from PC 12 Cells

PubMed Central

Li, Michelle W.; Martin, R. Scott

2008-01-01

In this paper, we describe the fabrication and evaluation of a multilayer microchip device that can be used to quantitatively measure the amount of catecholamines released from PC 12 cells immobilized within the same device. This approach allows immobilized cells to be stimulated on-chip and, through rapid actuation of integrated microvalves, the products released from the cells are repeatedly injected into the electrophoresis portion of the microchip, where the analytes are separated based upon mass and charge and detected through post-column derivatization and fluorescence detection. Following optimization of the post-column derivatization detection scheme (using naphthalene-2,3-dicarboxaldehyde and 2-β-mercaptoethanol), off-chip cell stimulation experiments were performed to demonstrate the ability of this device to detect dopamine from a population of PC 12 cells. The final 3-dimensional device that integrates an immobilized PC 12 cell reactor with the bilayer continuous flow sampling/electrophoresis microchip was used to continuously monitor the on-chip stimulated release of dopamine from PC 12 cells. Similar dopamine release was seen when stimulating on-chip versus off-chip yet the on-chip immobilization studies could be carried out with 500 times fewer cells in a much reduced volume. While this paper is focused on PC 12 cells and neurotransmitter analysis, the final device is a general analytical tool that is amenable to immobilization of a variety of cell lines and analysis of various released analytes by electrophoretic means. PMID:18810283

Power allocation for target detection in radar networks based on low probability of intercept: A cooperative game theoretical strategy

NASA Astrophysics Data System (ADS)

Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

2017-08-01

Distributed radar network systems have been shown to have many unique features. Due to their advantage of signal and spatial diversities, radar networks are attractive for target detection. In practice, the netted radars in radar networks are supposed to maximize their transmit power to achieve better detection performance, which may be in contradiction with low probability of intercept (LPI). Therefore, this paper investigates the problem of adaptive power allocation for radar networks in a cooperative game-theoretic framework such that the LPI performance can be improved. Taking into consideration both the transmit power constraints and the minimum signal to interference plus noise ratio (SINR) requirement of each radar, a cooperative Nash bargaining power allocation game based on LPI is formulated, whose objective is to minimize the total transmit power by optimizing the power allocation in radar networks. First, a novel SINR-based network utility function is defined and utilized as a metric to evaluate power allocation. Then, with the well-designed network utility function, the existence and uniqueness of the Nash bargaining solution are proved analytically. Finally, an iterative Nash bargaining algorithm is developed that converges quickly to a Pareto optimal equilibrium for the cooperative game. Numerical simulations and theoretic analysis are provided to evaluate the effectiveness of the proposed algorithm.

Determination of amantadine in biological fluids using simultaneous derivatization and dispersive liquid-liquid microextraction followed by gas chromatography-flame ionization detection.

PubMed

Farajzadeh, Mir Ali; Nouri, Nina; Alizadeh Nabil, Ali Akbar

2013-12-01

A one-step derivatization and microextraction technique for the determination of amantadine in the human plasma and urine samples is presented. An appropriate mixture of methanol (disperser solvent), 1,2-dibromoethane (extraction solvent), and butylchloroformate (derivatization agent) is rapidly injected into samples. After centrifuging, the sedimented phase is analyzed by gas chromatography-flame ionization detection (GC-FID). The kind of extraction and disperser solvents and their volumes, amount of derivatization agent and reaction/extraction time which are effective in derivatization/dispersive liquid-liquid microextraction (DLLME) procedure are optimized. Under the optimal conditions, the enrichment factor (EF) of the target analyte was obtained to be 408 and 420, and limit of detection (LOD) 4.2 and 2.7ngmL(-1), in plasma and urine respectively. The linear range is 14-5000 and 8.7-5000ng/mL for plasma and urine, respectively (squared correlation coefficient≥0.990). The relative recoveries obtained for the spiked plasma and urine samples are between 72% and 93%. Moreover, the inter- and intra-day precisions are acceptable at all spiked concentrations (relative standard deviation <7%). Finally the method was successfully applied to determine amantadine in biological samples. Copyright © 2013 Elsevier B.V. All rights reserved.

Electrostatic separation for recycling waste printed circuit board: a study on external factor and a robust design for optimization.

PubMed

Hou, Shibing; Wu, Jiang; Qin, Yufei; Xu, Zhenming

2010-07-01

Electrostatic separation is an effective and environmentally friendly method for recycling waste printed circuit board (PCB) by several kinds of electrostatic separators. However, some notable problems have been detected in its applications and cannot be efficiently resolved by optimizing the separation process. Instead of the separator itself, these problems are mainly caused by some external factors such as the nonconductive powder (NP) and the superficial moisture of feeding granule mixture. These problems finally lead to an inefficient separation. In the present research, the impacts of these external factors were investigated and a robust design was built to optimize the process and to weaken the adverse impact. A most robust parameter setting (25 kv, 80 rpm) was concluded from the experimental design. In addition, some theoretical methods, including cyclone separation, were presented to eliminate these problems substantially. This will contribute to efficient electrostatic separation of waste PCB and make remarkable progress for industrial applications.

Application of new methodologies based on design of experiments, independent component analysis and design space for robust optimization in liquid chromatography.

PubMed

Debrus, Benjamin; Lebrun, Pierre; Ceccato, Attilio; Caliaro, Gabriel; Rozet, Eric; Nistor, Iolanda; Oprean, Radu; Rupérez, Francisco J; Barbas, Coral; Boulanger, Bruno; Hubert, Philippe

2011-04-08

HPLC separations of an unknown sample mixture and a pharmaceutical formulation have been optimized using a recently developed chemometric methodology proposed by W. Dewé et al. in 2004 and improved by P. Lebrun et al. in 2008. This methodology is based on experimental designs which are used to model retention times of compounds of interest. Then, the prediction accuracy and the optimal separation robustness, including the uncertainty study, were evaluated. Finally, the design space (ICH Q8(R1) guideline) was computed as the probability for a criterion to lie in a selected range of acceptance. Furthermore, the chromatograms were automatically read. Peak detection and peak matching were carried out with a previously developed methodology using independent component analysis published by B. Debrus et al. in 2009. The present successful applications strengthen the high potential of these methodologies for the automated development of chromatographic methods. Copyright © 2011 Elsevier B.V. All rights reserved.

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

Tripathi, Ashish; McNulty, Ian; Munson, Todd

We propose a new approach to robustly retrieve the exit wave of an extended sample from its coherent diffraction pattern by exploiting sparsity of the sample's edges. This approach enables imaging of an extended sample with a single view, without ptychography. We introduce nonlinear optimization methods that promote sparsity, and we derive update rules to robustly recover the sample's exit wave. We test these methods on simulated samples by varying the sparsity of the edge-detected representation of the exit wave. Finally, our tests illustrate the strengths and limitations of the proposed method in imaging extended samples.

Fault diagnosis for wind turbine planetary ring gear via a meshing resonance based filtering algorithm.

PubMed

Wang, Tianyang; Chu, Fulei; Han, Qinkai

2017-03-01

Identifying the differences between the spectra or envelope spectra of a faulty signal and a healthy baseline signal is an efficient planetary gearbox local fault detection strategy. However, causes other than local faults can also generate the characteristic frequency of a ring gear fault; this may further affect the detection of a local fault. To address this issue, a new filtering algorithm based on the meshing resonance phenomenon is proposed. In detail, the raw signal is first decomposed into different frequency bands and levels. Then, a new meshing index and an MRgram are constructed to determine which bands belong to the meshing resonance frequency band. Furthermore, an optimal filter band is selected from this MRgram. Finally, the ring gear fault can be detected according to the envelope spectrum of the band-pass filtering result. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Information-theoretical noninvasive damage detection in bridge structures

NASA Astrophysics Data System (ADS)

Sudu Ambegedara, Amila; Sun, Jie; Janoyan, Kerop; Bollt, Erik

2016-11-01

Damage detection of mechanical structures such as bridges is an important research problem in civil engineering. Using spatially distributed sensor time series data collected from a recent experiment on a local bridge in Upper State New York, we study noninvasive damage detection using information-theoretical methods. Several findings are in order. First, the time series data, which represent accelerations measured at the sensors, more closely follow Laplace distribution than normal distribution, allowing us to develop parameter estimators for various information-theoretic measures such as entropy and mutual information. Second, as damage is introduced by the removal of bolts of the first diaphragm connection, the interaction between spatially nearby sensors as measured by mutual information becomes weaker, suggesting that the bridge is "loosened." Finally, using a proposed optimal mutual information interaction procedure to prune away indirect interactions, we found that the primary direction of interaction or influence aligns with the traffic direction on the bridge even after damaging the bridge.

Early Obstacle Detection and Avoidance for All to All Traffic Pattern in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Huc, Florian; Jarry, Aubin; Leone, Pierre; Moraru, Luminita; Nikoletseas, Sotiris; Rolim, Jose

This paper deals with early obstacles recognition in wireless sensor networks under various traffic patterns. In the presence of obstacles, the efficiency of routing algorithms is increased by voluntarily avoiding some regions in the vicinity of obstacles, areas which we call dead-ends. In this paper, we first propose a fast convergent routing algorithm with proactive dead-end detection together with a formal definition and description of dead-ends. Secondly, we present a generalization of this algorithm which improves performances in all to many and all to all traffic patterns. In a third part we prove that this algorithm produces paths that are optimal up to a constant factor of 2π + 1. In a fourth part we consider the reactive version of the algorithm which is an extension of a previously known early obstacle detection algorithm. Finally we give experimental results to illustrate the efficiency of our algorithms in different scenarios.

Shell-vial culture and real-time PCR applied to Rickettsia typhi and Rickettsia felis detection.

PubMed

Segura, Ferran; Pons, Immaculada; Pla, Júlia; Nogueras, María-Mercedes

2015-11-01

Murine typhus is a zoonosis transmitted by fleas, whose etiological agent is Rickettsia typhi. Rickettsia felis infection can produces similar symptoms. Both are intracellular microorganisms. Therefore, their diagnosis is difficult and their infections can be misdiagnosed. Early diagnosis prevents severity and inappropriate treatment regimens. Serology can't be applied during the early stages of infection because it requires seroconversion. Shell-vial (SV) culture assay is a powerful tool to detect Rickettsia. The aim of the study was to optimize SV using a real-time PCR as monitoring method. Moreover, the study analyzes which antibiotics are useful to isolate these microorganisms from fleas avoiding contamination by other bacteria. For the first purpose, SVs were inoculated with each microorganism. They were incubated at different temperatures and monitored by real-time PCR and classical methods (Gimenez staining and indirect immunofluorescence assay). R. typhi grew at all temperatures. R. felis grew at 28 and 32 °C. Real-time PCR was more sensitive than classical methods and it detected microorganisms much earlier. Besides, the assay sensitivity was improved by increasing the number of SV. For the second purpose, microorganisms and fleas were incubated and monitored in different concentrations of antibiotics. Gentamicin, sufamethoxazole, trimethoprim were useful for R. typhi isolation. Gentamicin, streptomycin, penicillin, and amphotericin B were useful for R. felis isolation. Finally, the optimized conditions were used to isolate R. felis from fleas collected at a veterinary clinic. R. felis was isolated at 28 and 32 °C. However, successful establishment of cultures were not possible probably due to sub-optimal conditions of samples.

Detection of exudates in fundus images using a Markovian segmentation model.

PubMed

Harangi, Balazs; Hajdu, Andras

2014-01-01

Diabetic retinopathy (DR) is one of the most common causing of vision loss in developed countries. In early stage of DR, some signs like exudates appear in the retinal images. An automatic screening system must be capable to detect these signs properly so that the treatment of the patients may begin in time. The appearance of exudates shows a rich variety regarding their shape and size making automatic detection more challenging. We propose a way for the automatic segmentation of exudates consisting of a candidate extraction step followed by exact contour detection and region-wise classification. More specifically, we extract possible exudate candidates using grayscale morphology and their proper shape is determined by a Markovian segmentation model considering edge information. Finally, we label the candidates as true or false ones by an optimally adjusted SVM classifier. For testing purposes, we considered the publicly available database DiaretDB1, where the proposed method outperformed several state-of-the-art exudate detectors.

Optimization of Methylphenidate Extended-Release Chewable Tablet Dose in Children with ADHD: Open-Label Dose Optimization in a Laboratory Classroom Study.

PubMed

Wigal, Sharon B; Childress, Ann; Berry, Sally A; Belden, Heidi W; Chappell, Phillip; Wajsbrot, Dalia B; Nagraj, Praneeta; Abbas, Richat; Palumbo, Donna

2018-06-01

To examine methylphenidate extended-release chewable tablets (MPH ERCT) dose patterns, attention-deficit/hyperactivity disorder (ADHD) symptom scores, and safety during the 6-week, open-label (OL) dose-optimization period of a phase 3, laboratory classroom study. Boys and girls (6-12 years) diagnosed with ADHD were enrolled. MPH ERCT was initiated at 20 mg/day; participants were titrated in 10-20 mg/day increments weekly based on efficacy and tolerability (maximum dose, 60 mg/day). Dose-optimization period efficacy assessments included the ADHD Rating Scale (ADHD-RS-IV), analyzed by week in a post hoc analysis using a mixed-effects model for repeated measures with final optimized dose (20, 30/40, or 50/60 mg), visit, final optimized dose and visit interaction, and baseline score as terms. Adverse events (AEs) and concomitant medications were collected throughout the study. Mean MPH ERCT daily dose increased weekly from 29.4 mg/day after the first dose adjustment at week 1 (n = 90) to 42.8 mg/day after the final adjustment at week 5 (n = 86). Final optimized MPH ERCT dose ranged from 20 to 60 mg/day. Mean final optimized MPH ERCT dose ranged from 40.0 mg/day in 6-8 year-old participants to 44.8 mg/day for 11-12 year-old participants. There was a progressive decrease in mean (standard deviation) ADHD-RS-IV total score from 40.1 (8.72) at baseline to 12.4 (7.88) at OL week 5, with similar improvement patterns for hyperactivity/impulsivity and inattentiveness subscale scores. Participants optimized to MPH ERCT 50/60 mg/day had a significantly higher mean (standard error) ADHD-RS-IV score at baseline compared with participants optimized to MPH ERCT 20 mg/day (42.4 [1.34] vs. 35.1 [2.55]; p = 0.013). Treatment-emergent AEs were reported by 65/90 (72.2%) participants in the dose-optimization period. Dose-optimization period results describing relationships between change in ADHD symptom scores and final optimized MPH ERCT dose will be valuable for clinicians optimizing MPH ERCT dose.

Optimization of a reusable, DNA pseudoknot-based electrochemical sensor for sequence-specific DNA detection in blood serum.

PubMed

Cash, Kevin J; Heeger, Alan J; Plaxco, Kevin W; Xiao, Yi

2009-01-15

We describe in detail a new electrochemical DNA (E-DNA) sensing platform based on target-induced conformation changes in an electrode-bound DNA pseudoknot. The pseudoknot, a DNA structure containing two stem-loops in which the first stem's loop forms part of the second stem, is modified with a methylene blue redox tag at its 3' terminus and covalently attached to a gold electrode via the 5' terminus. In the absence of a target, the structure of the pseudoknot probe minimizes collisions between the redox tag and the electrode, thus reducing faradaic current. Target binding disrupts the pseudoknot structure, liberating a flexible, single-stranded element that can strike the electrode and efficiently transfer electrons. In this article we report further characterization and optimization of this new E-DNA architecture. We find that optimal signaling is obtained at an intermediate probe density ( approximately 1.8 x 10(13) molecules/cm(2) apparent density), which presumably represents a balance between steric and electrostatic blocking at high probe densities and increased background currents arising from transfer from the pseudoknot probe at lower densities. We also find that optimal 3' stem length, which appears to be 7 base pairs, represents a balance between pseudoknot structural stability and target affinity. Finally, a 3' loop comprised of poly(A) exhibits better mismatch discrimination than the equivalent poly(T) loop, but at the cost of decreased gain. Optimization over this parameter space significantly improves the signaling of the pseudoknot-based E-DNA architecture, leading to the ability to sensitively and specifically detect DNA targets even when challenged in complex, multicomponent samples such as blood serum.

Optimization of a Reusable, DNA Pseudoknot-Based Electrochemical Sensor for Sequence-Specific DNA Detection in Blood Serum

PubMed Central

Cash, Kevin J.; Heeger, Alan J.; Plaxco, Kevin W.; Xiao, Yi

2010-01-01

We describe in detail a new electrochemical DNA (E-DNA) sensing platform based on target-induced conformation changes in an electrode-bound DNA pseudoknot. The pseudoknot, a DNA structure containing two stem-loops in which the first stem’s loop forms part of the second stem, is modified with a methylene blue redox tag at its 3′ terminus and covalently attached to a gold electrode via the 5′ terminus. In the absence of a target, the structure of the pseudoknot probe minimizes collisions between the redox tag and the electrode, thus reducing faradaic current. Target binding disrupts the pseudoknot structure, liberating a flexible, single-stranded element that can strike the electrode and efficiently transfer electrons. In this article we report further characterization and optimization of this new E-DNA architecture. We find that optimal signaling is obtained at an intermediate probe density (~1.8 × 1013 molecules/cm2 apparent density), which presumably represents a balance between steric and electrostatic blocking at high probe densities and increased background currents arising from transfer from the pseudoknot probe at lower densities. We also find that optimal 3′ stem length, which appears to be 7 base pairs, represents a balance between pseudoknot structural stability and target affinity. Finally, a 3′ loop comprised of poly(A) exhibits better mismatch discrimination than the equivalent poly(T) loop, but at the cost of decreased gain. Optimization over this parameter space significantly improves the signaling of the pseudoknot-based E-DNA architecture, leading to the ability to sensitively and specifically detect DNA targets even when challenged in complex, multicomponent samples such as blood serum. PMID:19093760

Image Based Hair Segmentation Algorithm for the Application of Automatic Facial Caricature Synthesis

PubMed Central

Peng, Zhenyun; Zhang, Yaohui

2014-01-01

Hair is a salient feature in human face region and are one of the important cues for face analysis. Accurate detection and presentation of hair region is one of the key components for automatic synthesis of human facial caricature. In this paper, an automatic hair detection algorithm for the application of automatic synthesis of facial caricature based on a single image is proposed. Firstly, hair regions in training images are labeled manually and then the hair position prior distributions and hair color likelihood distribution function are estimated from these labels efficiently. Secondly, the energy function of the test image is constructed according to the estimated prior distributions of hair location and hair color likelihood. This energy function is further optimized according to graph cuts technique and initial hair region is obtained. Finally, K-means algorithm and image postprocessing techniques are applied to the initial hair region so that the final hair region can be segmented precisely. Experimental results show that the average processing time for each image is about 280 ms and the average hair region detection accuracy is above 90%. The proposed algorithm is applied to a facial caricature synthesis system. Experiments proved that with our proposed hair segmentation algorithm the facial caricatures are vivid and satisfying. PMID:24592182

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

NASA Technical Reports Server (NTRS)

2004-01-01

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Dual chronoamperometric detection of enzymatic biomarkers using magnetic beads and a low-cost flow cell.

PubMed

Moral-Vico, Javier; Barallat, Jaume; Abad, Llibertat; Olivé-Monllau, Rosa; Muñoz-Pascual, Francesc Xavier; Galán Ortega, Amparo; del Campo, F Javier; Baldrich, Eva

2015-07-15

In this work we report on the production of a low cost microfluidic device for the multiplexed electrochemical detection of magneto bioassays. As a proof of concept, the device has been used to detect myeloperoxidase (MPO), a cardiovascular biomarker. With this purpose, two bioassays have been optimized in parallel onto magnetic beads (MBs) for the simultaneous detection of MPO endogenous peroxidase activity and quantification of total MPO. Since the two bioassays produced signals of different magnitude for each concentration of MPO tested, two detection strategies have been compared, which entailed registering steady state currents (Iss) under substrate flow, and measuring the peak currents (Ip) produced in a stopped flow approach. As it will be shown, appropriate tuning of the detection and flow conditions can provide extremely sensitive detection, but also allow simultaneous detection of assays or parameters that would produce signals of different orders of magnitude when measured by a single detection strategy. In order to demonstrate the feasibility of the detection strategy reported, a dual MPO mass and activity assay has been finally applied to the study of 10 real plasma samples, allowing patient classification according to the risk of suffering a cardiovascular event. Copyright © 2015 Elsevier B.V. All rights reserved.

Monitoring and decision making by people in man machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.

1979-01-01

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

Pitch-informed solo and accompaniment separation towards its use in music education applications

NASA Astrophysics Data System (ADS)

Cano, Estefanía; Schuller, Gerald; Dittmar, Christian

2014-12-01

We present a system for the automatic separation of solo instruments and music accompaniment in polyphonic music recordings. Our approach is based on a pitch detection front-end and a tone-based spectral estimation. We assess the plausibility of using sound separation technologies to create practice material in a music education context. To better understand the sound separation quality requirements in music education, a listening test was conducted to determine the most perceptually relevant signal distortions that need to be improved. Results from the listening test show that solo and accompaniment tracks pose different quality requirements and should be optimized differently. We propose and evaluate algorithm modifications to better understand their effects on objective perceptual quality measures. Finally, we outline possible ways of optimizing our separation approach to better suit the requirements of music education applications.

Design and test of a capacitance detection circuit based on a transimpedance amplifier

NASA Astrophysics Data System (ADS)

Linfeng, Mu; Wendong, Zhang; Changde, He; Rui, Zhang; Jinlong, Song; Chenyang, Xue

2015-07-01

This paper presents a transimpedance amplifier (TIA) capacitance detection circuit aimed at detecting micro-capacitance, which is caused by ultrasonic stimulation applied to the capacitive micro-machined ultrasonic transducer (CMUT). In the capacitance interface, a TIA is adopted to amplify the received signal with a center frequency of 400 kHz, and finally detect ultrasound pressure. The circuit has a strong anti-stray property and this paper also studies the calculation of compensation capacity in detail. To ensure high resolution, noise analysis is conducted. After optimization, the detected minimum ultrasound pressure is 2.1 Pa, which is two orders of magnitude higher than the former. The test results showed that the circuit was sensitive to changes in ultrasound pressure and the distance between the CMUT and stumbling block, which also successfully demonstrates the functionality of the developed TIA of the analog-front-end receiver. Project supported by the National Natural Science Foundation of China (No. 61127008) and the Subsidized Program of the National High Technology Research and Development Program of China (No. 2011AA040404).

Frequency modulation entrains slow neural oscillations and optimizes human listening behavior

PubMed Central

Henry, Molly J.; Obleser, Jonas

2012-01-01

The human ability to continuously track dynamic environmental stimuli, in particular speech, is proposed to profit from “entrainment” of endogenous neural oscillations, which involves phase reorganization such that “optimal” phase comes into line with temporally expected critical events, resulting in improved processing. The current experiment goes beyond previous work in this domain by addressing two thus far unanswered questions. First, how general is neural entrainment to environmental rhythms: Can neural oscillations be entrained by temporal dynamics of ongoing rhythmic stimuli without abrupt onsets? Second, does neural entrainment optimize performance of the perceptual system: Does human auditory perception benefit from neural phase reorganization? In a human electroencephalography study, listeners detected short gaps distributed uniformly with respect to the phase angle of a 3-Hz frequency-modulated stimulus. Listeners’ ability to detect gaps in the frequency-modulated sound was not uniformly distributed in time, but clustered in certain preferred phases of the modulation. Moreover, the optimal stimulus phase was individually determined by the neural delta oscillation entrained by the stimulus. Finally, delta phase predicted behavior better than stimulus phase or the event-related potential after the gap. This study demonstrates behavioral benefits of phase realignment in response to frequency-modulated auditory stimuli, overall suggesting that frequency fluctuations in natural environmental input provide a pacing signal for endogenous neural oscillations, thereby influencing perceptual processing. PMID:23151506

Best chirplet chain: Near-optimal detection of gravitational wave chirps

NASA Astrophysics Data System (ADS)

Chassande-Mottin, Éric; Pai, Archana

2006-02-01

The list of putative sources of gravitational waves possibly detected by the ongoing worldwide network of large scale interferometers has been continuously growing in the last years. For some of them, the detection is made difficult by the lack of a complete information about the expected signal. We concentrate on the case where the expected gravitational wave (GW) is a quasiperiodic frequency modulated signal i.e., a chirp. In this article, we address the question of detecting an a priori unknown GW chirp. We introduce a general chirp model and claim that it includes all physically realistic GW chirps. We produce a finite grid of template waveforms which samples the resulting set of possible chirps. If we follow the classical approach (used for the detection of inspiralling binary chirps, for instance), we would build a bank of quadrature matched filters comparing the data to each of the templates of this grid. The detection would then be achieved by thresholding the output, the maximum giving the individual which best fits the data. In the present case, this exhaustive search is not tractable because of the very large number of templates in the grid. We show that the exhaustive search can be reformulated (using approximations) as a pattern search in the time-frequency plane. This motivates an approximate but feasible alternative solution which is clearly linked to the optimal one. The time-frequency representation and pattern search algorithm are fully determined by the reformulation. This contrasts with the other time-frequency based methods presented in the literature for the same problem, where these choices are justified by “ad hoc” arguments. In particular, the time-frequency representation has to be unitary. Finally, we assess the performance, robustness and computational cost of the proposed method with several benchmarks using simulated data.

Edge detection and mathematic fitting for corneal surface with Matlab software.

PubMed

Di, Yue; Li, Mei-Yan; Qiao, Tong; Lu, Na

2017-01-01

To select the optimal edge detection methods to identify the corneal surface, and compare three fitting curve equations with Matlab software. Fifteen subjects were recruited. The corneal images from optical coherence tomography (OCT) were imported into Matlab software. Five edge detection methods (Canny, Log, Prewitt, Roberts, Sobel) were used to identify the corneal surface. Then two manual identifying methods (ginput and getpts) were applied to identify the edge coordinates respectively. The differences among these methods were compared. Binomial curve (y=Ax 2 +Bx+C), Polynomial curve [p(x)=p1x n +p2x n-1 +....+pnx+pn+1] and Conic section (Ax 2 +Bxy+Cy 2 +Dx+Ey+F=0) were used for curve fitting the corneal surface respectively. The relative merits among three fitting curves were analyzed. Finally, the eccentricity (e) obtained by corneal topography and conic section were compared with paired t -test. Five edge detection algorithms all had continuous coordinates which indicated the edge of the corneal surface. The ordinates of manual identifying were close to the inside of the actual edges. Binomial curve was greatly affected by tilt angle. Polynomial curve was lack of geometrical properties and unstable. Conic section could calculate the tilted symmetry axis, eccentricity, circle center, etc . There were no significant differences between 'e' values by corneal topography and conic section ( t =0.9143, P =0.3760 >0.05). It is feasible to simulate the corneal surface with mathematical curve with Matlab software. Edge detection has better repeatability and higher efficiency. The manual identifying approach is an indispensable complement for detection. Polynomial and conic section are both the alternative methods for corneal curve fitting. Conic curve was the optimal choice based on the specific geometrical properties.

Simultaneous determination of estrogenic odorant alkylphenols, chlorophenols, and their derivatives in water using online headspace solid phase microextraction coupled with gas chromatography-mass spectrometry.

PubMed

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

2016-10-01

A simple online headspace solid-phase microextraction (HS-SPME) coupled with the gas chromatography-mass spectrometry (GC-MS) method was developed for simultaneous determination of trace amounts of nine estrogenic odorant alkylphenols and chlorophenols and their derivatives in water samples. The extraction conditions of HS-SPME were optimized including fiber selection, extraction temperature, extraction time, and salt concentration. Results showed that divinylbenzene/Carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber was the most appropriate one among the three selected commercial fibers, and the optimal extraction temperature, time, and salt concentration were 70 °C, 30 min, and 0.25 g/mL, respectively. The developed method was validated and showed good linearity (R (2) > 0.989), low limit of detection (LOD, 0.002-0.5 μg/L), and excellent recoveries (76-126 %) with low relative standard deviation (RSD, 0.7-12.9 %). The developed method was finally applied to two surface water samples and some of these target compounds were detected. All these detected compounds were below their odor thresholds, except for 2,4,6-TCAS and 2,4,6-TBAS wherein their concentrations were near their odor thresholds. However, in the two surface water samples, these detected compounds contributed to a certain amount of estrogenicity, which seemed to suggest that more attention should be paid to the issue of estrogenicity rather than to the odor problem.

Sagnac-interferometer-based fresnel flow probe.

PubMed

Tselikov, A; Blake, J

1998-10-01

We used a near-diffraction-limited flow or light-wave-interaction pipe to produce a Sagnac-interferometer-based Fresnel drag fluid flowmeter capable of detecting extremely small flow rates. An optimized design of the pipe along with the use of a state-of-the-art Sagnac interferometer results in a minimum-detectable water flow rate of 2.4 nl/s [1 drop/(5 h)]. The flowmeter's capability of measuring the water consumption by a small plant in real time has been demonstrated. We then designed an automated alignment system that finds and maintains the optimum fiber-coupling regime, which makes the applications of the Fresnel-drag-based flowmeters practical, especially if the length of the interaction pipe is long. Finally, we have applied the automatic alignment technique to an air flowmeter.

Minimum-fuel turning climbout and descent guidance of transport jets

NASA Technical Reports Server (NTRS)

Neuman, F.; Kreindler, E.

1983-01-01

The complete flightpath optimization problem for minimum fuel consumption from takeoff to landing including the initial and final turns from and to the runway heading is solved. However, only the initial and final segments which contain the turns are treated, since the straight-line climbout, cruise, and descent problems have already been solved. The paths are derived by generating fields of extremals, using the necessary conditions of optimal control together with singular arcs and state constraints. Results show that the speed profiles for straight flight and turning flight are essentially identical except for the final horizontal accelerating or decelerating turns. The optimal turns require no abrupt maneuvers, and an approximation of the optimal turns could be easily integrated with present straight-line climb-cruise-descent fuel-optimization algorithms. Climbout at the optimal IAS rather than the 250-knot terminal-area speed limit would save 36 lb of fuel for the 727-100 aircraft.

TU-FG-209-11: Validation of a Channelized Hotelling Observer to Optimize Chest Radiography Image Processing for Nodule Detection: A Human Observer Study

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

Sanchez, A; Little, K; Chung, J

Purpose: To validate the use of a Channelized Hotelling Observer (CHO) model for guiding image processing parameter selection and enable improved nodule detection in digital chest radiography. Methods: In a previous study, an anthropomorphic chest phantom was imaged with and without PMMA simulated nodules using a GE Discovery XR656 digital radiography system. The impact of image processing parameters was then explored using a CHO with 10 Laguerre-Gauss channels. In this work, we validate the CHO’s trend in nodule detectability as a function of two processing parameters by conducting a signal-known-exactly, multi-reader-multi-case (MRMC) ROC observer study. Five naive readers scored confidencemore » of nodule visualization in 384 images with 50% nodule prevalence. The image backgrounds were regions-of-interest extracted from 6 normal patient scans, and the digitally inserted simulated nodules were obtained from phantom data in previous work. Each patient image was processed with both a near-optimal and a worst-case parameter combination, as determined by the CHO for nodule detection. The same 192 ROIs were used for each image processing method, with 32 randomly selected lung ROIs per patient image. Finally, the MRMC data was analyzed using the freely available iMRMC software of Gallas et al. Results: The image processing parameters which were optimized for the CHO led to a statistically significant improvement (p=0.049) in human observer AUC from 0.78 to 0.86, relative to the image processing implementation which produced the lowest CHO performance. Conclusion: Differences in user-selectable image processing methods on a commercially available digital radiography system were shown to have a marked impact on performance of human observers in the task of lung nodule detection. Further, the effect of processing on humans was similar to the effect on CHO performance. Future work will expand this study to include a wider range of detection/classification tasks and more observers, including experienced chest radiologists.« less

User's guide to four-body and three-body trajectory optimization programs

NASA Technical Reports Server (NTRS)

Pu, C. L.; Edelbaum, T. N.

1974-01-01

A collection of computer programs and subroutines written in FORTRAN to calculate 4-body (sun-earth-moon-space) and 3-body (earth-moon-space) optimal trajectories is presented. The programs incorporate a variable step integration technique and a quadrature formula to correct single step errors. The programs provide capability to solve initial value problem, two point boundary value problem of a transfer from a given initial position to a given final position in fixed time, optimal 2-impulse transfer from an earth parking orbit of given inclination to a given final position and velocity in fixed time and optimal 3-impulse transfer from a given position to a given final position and velocity in fixed time.

The Fermi Large Area Telescope: Optimizing and Then Re-Optimizing the Science Return

NASA Astrophysics Data System (ADS)

Atwood, W. B.

2012-01-01

The general concepts of how to do gamma-ray observations in space were well established and vetted by the early 1990's. In particular, the success of EGRET onboard the Compton Gamma Ray Observatory whetted the appetite for a more ambitious follow on. In parallel, advances in high-energy particle detection, spurred on by plans for the Superconducting Super Collider, provided an unprecedented opportunity for space-based detectors. The GLAST concept, now Fermi-LAT, was born at SLAC in May of 1992 and the instrument was subsequently developed by an international collaboration from France, Italy, Japan, Sweden and the United States. An overview of the original design optimization of the LAT instrument, done with the goal of imposing as few limits as possible on its applications in space, is discussed (along with some of the trials and tribulations of construction along the way to launch!). Now with over 3 years of science operations experience, the lessons-learned will be reviewed and assessed against the expectations. Finally, the ongoing re-optimization of the instrument and plans for how to extend the LAT's science window into the future are discussed.

Intelligent Tires Based on Measurement of Tire Deformation

NASA Astrophysics Data System (ADS)

Matsuzaki, Ryosuke; Todoroki, Akira

From a traffic safety point-of-view, there is an urgent need for intelligent tires as a warning system for road conditions, for optimized braking control on poor road surfaces and as a tire fault detection system. Intelligent tires, equipped with sensors for monitoring applied strain, are effective in improving reliability and control systems such as anti-lock braking systems (ABSs). In previous studies, we developed a direct tire deformation or strain measurement system with sufficiently low stiffness and high elongation for practical use, and a wireless communication system between tires and vehicle that operates without a battery. The present study investigates the application of strain data for an optimized braking control and road condition warning system. The relationships between strain sensor outputs and tire mechanical parameters, including braking torque, effective radius and contact patch length, are calculated using finite element analysis. Finally, we suggested the possibility of optimized braking control and road condition warning systems. Optimized braking control can be achieved by keeping the slip ratio constant. The road condition warning would be actuated if the recorded friction coefficient at a certain slip ratio is lower than a ‘safe’ reference value.

Intelligent tires for improved tire safety using wireless strain measurement

NASA Astrophysics Data System (ADS)

Matsuzaki, Ryosuke; Todoroki, Akira

2008-03-01

From a traffic safety point-of-view, there is an urgent need for intelligent tires as a warning system for road conditions, for optimized braking control on poor road surfaces and as a tire fault detection system. Intelligent tires, equipped with sensors for monitoring applied strain, are effective in improving reliability and control systems such as anti-lock braking systems (ABSs). In previous studies, we developed a direct tire deformation or strain measurement system with sufficiently low stiffness and high elongation for practical use, and a wireless communication system between tires and vehicle that operates without a battery. The present study investigates the application of strain data for an optimized braking control and road condition warning system. The relationships between strain sensor outputs and tire mechanical parameters, including braking torque, effective radius and contact patch length, are calculated using finite element analysis. Finally, we suggested the possibility of optimized braking control and road condition warning systems. Optimized braking control can be achieved by keeping the slip ratio constant. The road condition warning would be actuated if the recorded friction coefficient at a certain slip ratio is lower than a 'safe' reference value.

Infrasound workshop for CTBT monitoring: Proceedings

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

Christie, D.; Whitaker, R.

1998-11-01

It is expected that the establishment of new infrasound stations in the global IMS network by the Provisional Technical Secretariat of the CTBTO in Vienna will commence in the middle of 1998. Thus, decisions on the final operational design for IMS infrasound stations will have to be made within the next 12 months. Though many of the basic design problems have been resolved, it is clear that further work needs to be carried out during the coming year to ensure that IMS infrasound stations will operate with maximum capability in accord with the specifications determined during the May 1997 PrepCommore » Meeting. Some of the papers presented at the Workshop suggest that it may be difficult to design a four-element infrasound array station that will reliably detect and locate infrasound signals at all frequencies in the specified range from 0.02 to 4.0 Hz in all noise environments. Hence, if the basic design of an infrasound array is restricted to four array elements, the final optimized design may be suited only to the detection and location of signals in a more limited pass-band. Several participants have also noted that the reliable discrimination of infrasound signals could be quite difficult if the detection system leads to signal distortion. Thus, it has been emphasized that the detection system should not, if possible, compromise signal fidelity. This report contains the workshop agenda, a list of participants, and abstracts and viewgraphs from each presentation.« less

X-ray backscatter imaging for radiography by selective detection and snapshot: Evolution, development, and optimization

NASA Astrophysics Data System (ADS)

Shedlock, Daniel

Compton backscatter imaging (CBI) is a single-sided imaging technique that uses the penetrating power of radiation and unique interaction properties of radiation with matter to image subsurface features. CBI has a variety of applications that include non-destructive interrogation, medical imaging, security and military applications. Radiography by selective detection (RSD), lateral migration radiography (LMR) and shadow aperture backscatter radiography (SABR) are different CBI techniques that are being optimized and developed. Radiography by selective detection (RSD) is a pencil beam Compton backscatter imaging technique that falls between highly collimated and uncollimated techniques. Radiography by selective detection uses a combination of single- and multiple-scatter photons from a projected area below a collimation plane to generate an image. As a result, the image has a combination of first- and multiple-scatter components. RSD techniques offer greater subsurface resolution than uncollimated techniques, at speeds at least an order of magnitude faster than highly collimated techniques. RSD scanning systems have evolved from a prototype into near market-ready scanning devices for use in a variety of single-sided imaging applications. The design has changed to incorporate state-of-the-art detectors and electronics optimized for backscatter imaging with an emphasis on versatility, efficiency and speed. The RSD system has become more stable, about 4 times faster, and 60% lighter while maintaining or improving image quality and contrast over the past 3 years. A new snapshot backscatter radiography (SBR) CBI technique, shadow aperture backscatter radiography (SABR), has been developed from concept and proof-of-principle to a functional laboratory prototype. SABR radiography uses digital detection media and shaded aperture configurations to generate near-surface Compton backscatter images without scanning, similar to how transmission radiographs are taken. Finally, a more inclusive theory of the factors affecting CBI contrast generation has tied together the past work of LMR with the more recent research in RSD. A variety of factors that induce changes in the backscatter photon field intensity (resulting in contrast changes in images) include: changes in the electron density field, attenuation changes along the entrance and exit paths, changes in the relative geometric positioning of the target, feature, illumination beam, and detectors. Understanding the interplay of how changes in each of these factors affects image contrast becomes essential to utilizing and optimizing RSD for different applications.

[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.

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

PubMed

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

2014-05-21

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

Unified framework for triaxial accelerometer-based fall event detection and classification using cumulants and hierarchical decision tree classifier.

PubMed

Kambhampati, Satya Samyukta; Singh, Vishal; Manikandan, M Sabarimalai; Ramkumar, Barathram

2015-08-01

In this Letter, the authors present a unified framework for fall event detection and classification using the cumulants extracted from the acceleration (ACC) signals acquired using a single waist-mounted triaxial accelerometer. The main objective of this Letter is to find suitable representative cumulants and classifiers in effectively detecting and classifying different types of fall and non-fall events. It was discovered that the first level of the proposed hierarchical decision tree algorithm implements fall detection using fifth-order cumulants and support vector machine (SVM) classifier. In the second level, the fall event classification algorithm uses the fifth-order cumulants and SVM. Finally, human activity classification is performed using the second-order cumulants and SVM. The detection and classification results are compared with those of the decision tree, naive Bayes, multilayer perceptron and SVM classifiers with different types of time-domain features including the second-, third-, fourth- and fifth-order cumulants and the signal magnitude vector and signal magnitude area. The experimental results demonstrate that the second- and fifth-order cumulant features and SVM classifier can achieve optimal detection and classification rates of above 95%, as well as the lowest false alarm rate of 1.03%.

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.

Application of biomarkers in cancer risk management: evaluation from stochastic clonal evolutionary and dynamic system optimization points of view.

PubMed

Li, Xiaohong; Blount, Patricia L; Vaughan, Thomas L; Reid, Brian J

2011-02-01

Aside from primary prevention, early detection remains the most effective way to decrease mortality associated with the majority of solid cancers. Previous cancer screening models are largely based on classification of at-risk populations into three conceptually defined groups (normal, cancer without symptoms, and cancer with symptoms). Unfortunately, this approach has achieved limited successes in reducing cancer mortality. With advances in molecular biology and genomic technologies, many candidate somatic genetic and epigenetic "biomarkers" have been identified as potential predictors of cancer risk. However, none have yet been validated as robust predictors of progression to cancer or shown to reduce cancer mortality. In this Perspective, we first define the necessary and sufficient conditions for precise prediction of future cancer development and early cancer detection within a simple physical model framework. We then evaluate cancer risk prediction and early detection from a dynamic clonal evolution point of view, examining the implications of dynamic clonal evolution of biomarkers and the application of clonal evolution for cancer risk management in clinical practice. Finally, we propose a framework to guide future collaborative research between mathematical modelers and biomarker researchers to design studies to investigate and model dynamic clonal evolution. This approach will allow optimization of available resources for cancer control and intervention timing based on molecular biomarkers in predicting cancer among various risk subsets that dynamically evolve over time.

Exposure Time Optimization for Highly Dynamic Star Trackers

PubMed Central

Wei, Xinguo; Tan, Wei; Li, Jian; Zhang, Guangjun

2014-01-01

Under highly dynamic conditions, the star-spots on the image sensor of a star tracker move across many pixels during the exposure time, which will reduce star detection sensitivity and increase star location errors. However, this kind of effect can be compensated well by setting an appropriate exposure time. This paper focuses on how exposure time affects the star tracker under highly dynamic conditions and how to determine the most appropriate exposure time for this case. Firstly, the effect of exposure time on star detection sensitivity is analyzed by establishing the dynamic star-spot imaging model. Then the star location error is deduced based on the error analysis of the sub-pixel centroiding algorithm. Combining these analyses, the effect of exposure time on attitude accuracy is finally determined. Some simulations are carried out to validate these effects, and the results show that there are different optimal exposure times for different angular velocities of a star tracker with a given configuration. In addition, the results of night sky experiments using a real star tracker agree with the simulation results. The summarized regularities in this paper should prove helpful in the system design and dynamic performance evaluation of the highly dynamic star trackers. PMID:24618776

Multivariate optimization of the factors influencing the solid-phase microextraction of pyrethroid pesticides in water.

PubMed

Casas, Vanessa; Llompart, Maria; García-Jares, Carmen; Cela, Rafael; Dagnac, Thierry

2006-08-18

A method based on solid-phase microextraction (SPME) and gas chromatography with micro-electron capture detection (GC-microECD) has been optimized for the analysis of pyrethroids in water samples. The influence of parameters such as temperature, fibre coating, salting-out effect and sampling mode on the extraction efficiency has been studied by means of a mix-level factorial design, which allowed the study of main effects as well as two factor interactions. Finally, a method based on direct SPME at 50 degrees C, using polydimethylsiloxane fibre is proposed. The method showed good linearity (R2>0.995) and repeatability (RSD

Tools for Accurate and Efficient Analysis of Complex Evolutionary Mechanisms in Microbial Genomes. Final Report

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

Nakhleh, Luay

I proposed to develop computationally efficient tools for accurate detection and reconstruction of microbes' complex evolutionary mechanisms, thus enabling rapid and accurate annotation, analysis and understanding of their genomes. To achieve this goal, I proposed to address three aspects. (1) Mathematical modeling. A major challenge facing the accurate detection of HGT is that of distinguishing between these two events on the one hand and other events that have similar "effects." I proposed to develop a novel mathematical approach for distinguishing among these events. Further, I proposed to develop a set of novel optimization criteria for the evolutionary analysis of microbialmore » genomes in the presence of these complex evolutionary events. (2) Algorithm design. In this aspect of the project, I proposed to develop an array of e cient and accurate algorithms for analyzing microbial genomes based on the formulated optimization criteria. Further, I proposed to test the viability of the criteria and the accuracy of the algorithms in an experimental setting using both synthetic as well as biological data. (3) Software development. I proposed the nal outcome to be a suite of software tools which implements the mathematical models as well as the algorithms developed.« less

IDH mutation assessment of glioma using texture features of multimodal MR images

NASA Astrophysics Data System (ADS)

Zhang, Xi; Tian, Qiang; Wu, Yu-Xia; Xu, Xiao-Pan; Li, Bao-Juan; Liu, Yi-Xiong; Liu, Yang; Lu, Hong-Bing

2017-03-01

Purpose: To 1) find effective texture features from multimodal MRI that can distinguish IDH mutant and wild status, and 2) propose a radiomic strategy for preoperatively detecting IDH mutation patients with glioma. Materials and Methods: 152 patients with glioma were retrospectively included from the Cancer Genome Atlas. Corresponding T1-weighted image before- and post-contrast, T2-weighted image and fluid-attenuation inversion recovery image from the Cancer Imaging Archive were analyzed. Specific statistical tests were applied to analyze the different kind of baseline information of LrGG patients. Finally, 168 texture features were derived from multimodal MRI per patient. Then the support vector machine-based recursive feature elimination (SVM-RFE) and classification strategy was adopted to find the optimal feature subset and build the identification models for detecting the IDH mutation. Results: Among 152 patients, 92 and 60 were confirmed to be IDH-wild and mutant, respectively. Statistical analysis showed that the patients without IDH mutation was significant older than patients with IDH mutation (p<0.01), and the distribution of some histological subtypes was significant different between IDH wild and mutant groups (p<0.01). After SVM-RFE, 15 optimal features were determined for IDH mutation detection. The accuracy, sensitivity, specificity, and AUC after SVM-RFE and parameter optimization were 82.2%, 85.0%, 78.3%, and 0.841, respectively. Conclusion: This study presented a radiomic strategy for noninvasively discriminating IDH mutation of patients with glioma. It effectively incorporated kinds of texture features from multimodal MRI, and SVM-based classification strategy. Results suggested that features selected from SVM-RFE were more potential to identifying IDH mutation. The proposed radiomics strategy could facilitate the clinical decision making in patients with glioma.

Use of multiresponse statistical techniques to optimize the separation of diosmin, hesperidin, diosmetin and hesperitin in different pharmaceutical preparations by high performance liquid chromatography with UV-DAD.

PubMed

Sammani, Mohamad Subhi; Clavijo, Sabrina; Portugal, Lindomar; Suárez, Ruth; Seddik, Hassan; Cerdà, Víctor

2017-05-15

A new method for the separation and determination of four flavonoids: hesperidin (HES), diosmin (DIO), hesperitin (HTIN), and diosmetin (DTIN) in pure form and pharmaceutical formulations has been developed by using high performance liquid chromatography (HPLC) with UV-DAD detection. Multivariate statistics (2 k full factorial and Box Behnken Designs) has been used for the multiresponse optimization of the chromatographic separation, which was completed in 22min, and carried out on a symmetry® C18 column (250×3mm; 5µm) as stationary phase. Separation was conducted by gradient elution mode using a mixture of methanol, acetonitrile and water pH: 2.5 (CH 3 COOH), as mobile phase. Analytes were separated setting the column at 22°C, with a flow rate of 0.58mLmin -1 and detected at 285nm. Under the optimized conditions, the flavonoids showed retention times of: 8.62, 11.53, 18.55 and 19.94min for HES, DIO, HTIN and DTIN, respectively. Limits of detection and quantification were <0.0156µgmL -1 and <0.100µgmL -1 , respectively. Linearity was achieved with good correlation coefficients values (r 2 =0.999; n=5). Intra-day and inter-day precision were found to be less than 3.44% (n=7). Finally, the proposed method was successfully applied to determine the target flavonoids in pharmaceutical preparations with satisfactory recoveries (between 95.2% and 107.9%), demonstrating that should also find application in the quality control, as well as in the pharmacokinetic studies of these drugs. Copyright © 2017 Elsevier B.V. All rights reserved.

Determination of nonylphenol and nonylphenol ethoxylates in environmental solid samples by ultrasonic-assisted extraction and high performance liquid chromatography-fluorescence detection.

PubMed

Núñez, L; Turiel, E; Tadeo, J L

2007-04-06

A simple and rapid analytical method for the determination of nonylphenol (NP) and nonylphenol ethoxylates (NPEOx) in solid environmental samples has been developed. This method combines an ultrasonic-assisted extraction procedure in small columns and an enrichment step onto C(18) solid-phase extraction cartridges prior to separation using HPLC with fluorescence detection. Method optimization was carried out using soil samples fortified at different concentration levels (from 0.1 to 100 microg/g). Under optimum conditions, 2g of soil was placed in small glass columns and extraction was performed assisted by sonication (SAESC) at 45 degrees C in two consecutive steps of 15 min using a mixture of H(2)O/MeOH (30/70). The obtained extracts were collected, loaded onto 500 mg C(18) cartridges, and analytes were eluted with 3 x 1 ml of methanol and 1 ml of acetonitrile. Finally, sample extracts were evaporated under a nitrogen stream, redissolved in 500 microl H(2)O/AcN (50/50), and passed though a 0.45 microm nylon filter before final determination by HPLC-FL. The developed procedure allowed to achieve quantitative recoveries for NP and NPEOx, and was properly validated. Finally, the method was applied to the determination of these compounds in soils and other environmental solid samples such as sediments, compost and sludge.

Defining a region of optimization based on engine usage data

DOEpatents

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2015-08-04

Methods and systems for engine control optimization are provided. One or more operating conditions of a vehicle engine are detected. A value for each of a plurality of engine control parameters is determined based on the detected one or more operating conditions of the vehicle engine. A range of the most commonly detected operating conditions of the vehicle engine is identified and a region of optimization is defined based on the range of the most commonly detected operating conditions of the vehicle engine. The engine control optimization routine is initiated when the one or more operating conditions of the vehicle engine are within the defined region of optimization.

Optimal MRI sequences for 68Ga-PSMA-11 PET/MRI in evaluation of biochemically recurrent prostate cancer.

PubMed

Lake, Spencer T; Greene, Kirsten L; Westphalen, Antonio C; Behr, Spencer C; Zagoria, Ronald; Small, Eric J; Carroll, Peter R; Hope, Thomas A

2017-09-19

PET/MRI can be used for the detection of disease in biochemical recurrence (BCR) patients imaged with 68 Ga-PSMA-11 PET. This study was designed to determine the optimal MRI sequences to localize positive findings on 68 Ga-PSMA-11 PET of patients with BCR after definitive therapy. Fifty-five consecutive prostate cancer patients with BCR imaged with 68 Ga-PSMA-11 3.0T PET/MRI were retrospectively analyzed. Mean PSA was 7.9 ± 12.9 ng/ml, and mean PSA doubling time was 7.1 ± 6.6 months. Detection rates of anatomic correlates for prostate-specific membrane antigen (PSMA)-positive foci were evaluated on small field of view (FOV) T2, T1 post-contrast, and diffusion-weighted images. For prostate bed recurrences, the detection rate of dynamic contrast-enhanced (DCE) imaging for PSMA-positive foci was evaluated. Finally, the detection sensitivity for PSMA-avid foci on 3- and 8-min PET acquisitions was compared. PSMA-positive foci were detected in 89.1% (49/55) of patients evaluated. Small FOV T2 performed best for lymph nodes and detected correlates for all PSMA-avid lymph nodes. DCE imaging performed the best for suspected prostate bed recurrence, detecting correlates for 87.5% (14/16) of PSMA-positive prostate bed foci. The 8-min PET acquisition performed better than the 3-min acquisition for lymph nodes smaller than 1 cm, detecting 100% (57/57) of lymph nodes less than 1 cm, compared to 78.9% (45/57) for the 3-min acquisition. PSMA PET/MRI performed well for the detection of sites of suspected recurrent disease in patients with BCR. Of the MRI sequences obtained for localization, small FOV T2 images detected the greatest proportion of PSMA-positive abdominopelvic lymph nodes and DCE imaging detected the greatest proportion of PSMA-positive prostate bed foci. The 8-min PET acquisition was superior to the 3 min acquisition for detection of small lymph nodes.

Designing a Pediatric Severe Sepsis Screening Tool

PubMed Central

Sepanski, Robert J.; Godambe, Sandip A.; Mangum, Christopher D.; Bovat, Christine S.; Zaritsky, Arno L.; Shah, Samir H.

2014-01-01

We sought to create a screening tool with improved predictive value for pediatric severe sepsis (SS) and septic shock that can be incorporated into the electronic medical record and actively screen all patients arriving at a pediatric emergency department (ED). “Gold standard” SS cases were identified using a combination of coded discharge diagnosis and physician chart review from 7,402 children who visited a pediatric ED over 2 months. The tool’s identification of SS was initially based on International Consensus Conference on Pediatric Sepsis (ICCPS) parameters that were refined by an iterative, virtual process that allowed us to propose successive changes in sepsis detection parameters in order to optimize the tool’s predictive value based on receiver operating characteristics (ROC). Age-specific normal and abnormal values for heart rate (HR) and respiratory rate (RR) were empirically derived from 143,603 children seen in a second pediatric ED over 3 years. Univariate analyses were performed for each measure in the tool to assess its association with SS and to characterize it as an “early” or “late” indicator of SS. A split-sample was used to validate the final, optimized tool. The final tool incorporated age-specific thresholds for abnormal HR and RR and employed a linear temperature correction for each category. The final tool’s positive predictive value was 48.7%, a significant, nearly threefold improvement over the original ICCPS tool. False positive systemic inflammatory response syndrome identifications were nearly sixfold lower. PMID:24982852

Automatic Clustering of Rolling Element Bearings Defects with Artificial Neural Network

NASA Astrophysics Data System (ADS)

Antonini, M.; Faglia, R.; Pedersoli, M.; Tiboni, M.

2006-06-01

The paper presents the optimization of a methodology for automatic clustering based on Artificial Neural Networks to detect the presence of defects in rolling bearings. The research activity was developed in co-operation with an Italian company which is expert in the production of water pumps for automotive use (Industrie Saleri Italo). The final goal of the work is to develop a system for the automatic control of the pumps, at the end of the production line. In this viewpoint, we are gradually considering the main elements of the water pump, which can cause malfunctioning. The first elements we have considered are the rolling bearing, a very critic component for the system. The experimental activity is based on the vibration measuring of rolling bearings opportunely damaged; vibration signals are in the second phase elaborated; the third and last phase is an automatic clustering. Different signal elaboration techniques are compared to optimize the methodology.

Optimal directed searches for continuous gravitational waves

NASA Astrophysics Data System (ADS)

Ming, Jing; Krishnan, Badri; Papa, Maria Alessandra; Aulbert, Carsten; Fehrmann, Henning

2016-03-01

Wide parameter space searches for long-lived continuous gravitational wave signals are computationally limited. It is therefore critically important that the available computational resources are used rationally. In this paper we consider directed searches, i.e., targets for which the sky position is known accurately but the frequency and spin-down parameters are completely unknown. Given a list of such potential astrophysical targets, we therefore need to prioritize. On which target(s) should we spend scarce computing resources? What parameter space region in frequency and spin-down should we search through? Finally, what is the optimal search setup that we should use? In this paper we present a general framework that allows us to solve all three of these problems. This framework is based on maximizing the probability of making a detection subject to a constraint on the maximum available computational cost. We illustrate the method for a simplified problem.

On chip preconcentration and fluorescence labeling of model proteins by use of monolithic columns: device fabrication, optimization, and automation.

PubMed

Yang, Rui; Pagaduan, Jayson V; Yu, Ming; Woolley, Adam T

2015-01-01

Microfluidic systems with monolithic columns have been developed for preconcentration and on-chip labeling of model proteins. Monoliths were prepared in microchannels by photopolymerization, and their properties were optimized by varying the composition and concentration of the monomers to improve flow and extraction. On-chip labeling of proteins was achieved by driving solutions through the monolith by use of voltage then incubating fluorescent dye with protein retained on the monolith. Subsequently, the labeled proteins were eluted, by applying voltages to reservoirs on the microdevice, and then detected, by monitoring laser-induced fluorescence. Monoliths prepared from octyl methacrylate combine the best protein retention with the possibility of separate elution of unattached fluorescent label with 50% acetonitrile. Finally, automated on-chip extraction and fluorescence labeling of a model protein were successfully demonstrated. This method involves facile sample pretreatment, and therefore has potential for production of integrated bioanalysis microchips.

Online games: a novel approach to explore how partial information influences human random searches

NASA Astrophysics Data System (ADS)

Martínez-García, Ricardo; Calabrese, Justin M.; López, Cristóbal

2017-01-01

Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of e ach displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches.

Synthesis, crystal structure, biological activity and theoretical calculations of novel isoxazole derivatives

NASA Astrophysics Data System (ADS)

Jin, R. Y.; Sun, X. H.; Liu, Y. F.; Long, W.; Chen, B.; Shen, S. Q.; Ma, H. X.

2016-01-01

Series of isoxazole derivatives were synthesized by substituted chalcones and 2-chloro-6-fluorobenzene formaldehyde oxime with 1,3-dipolar cycloaddition. The target compounds were determined by melting point, IR, 1H NMR, elemental analyses and HRMS. The crystal structure of compound 3a was detected by X-ray diffraction and it crystallizes in the triclinic space group p2(1)/c with z = 4. The molecular geometry of compound 3a was optimized using density functional theory (DFT/B3LYP) method with the 6-31G+(d,p) basis set in the ground state. From the optimized geometry of the molecule, FT-IR, FT-Raman, HOMO-LUMO and natural bond orbital (NBO) were calculated at B3LYP/6-31G+(d,p) level. Finally, the antifungal activity of the synthetic compounds were evaluated against Pythium solani, Gibberella nicotiancola, Fusarium oxysporium f.sp. niveum and Gibberella saubinetii.

Antibunching and unconventional photon blockade with Gaussian squeezed states

NASA Astrophysics Data System (ADS)

Lemonde, Marc-Antoine; Didier, Nicolas; Clerk, Aashish A.

2014-12-01

Photon antibunching is a quantum phenomenon typically observed in strongly nonlinear systems where photon blockade suppresses the probability of detecting two photons at the same time. Antibunching has also been reported with Gaussian states, where optimized amplitude squeezing yields classically forbidden values of the intensity correlation, g(2 )(0 ) <1 . As a consequence, observation of antibunching is not necessarily a signature of photon-photon interactions. To clarify the significance of the intensity correlations, we derive a sufficient condition for deducing whether a field is non-Gaussian based on a g(2 )(0 ) measurement. We then show that the Gaussian antibunching obtained with a degenerate parametric amplifier is close to the ideal case reached using dissipative squeezing protocols. We finally shed light on the so-called unconventional photon blockade effect predicted in a driven two-cavity setup with surprisingly weak Kerr nonlinearities, stressing that it is a particular realization of optimized Gaussian amplitude squeezing.

Continuous-variable quantum probes for structured environments

NASA Astrophysics Data System (ADS)

Bina, Matteo; Grasselli, Federico; Paris, Matteo G. A.

2018-01-01

We address parameter estimation for structured environments and suggest an effective estimation scheme based on continuous-variables quantum probes. In particular, we investigate the use of a single bosonic mode as a probe for Ohmic reservoirs, and obtain the ultimate quantum limits to the precise estimation of their cutoff frequency. We assume the probe prepared in a Gaussian state and determine the optimal working regime, i.e., the conditions for the maximization of the quantum Fisher information in terms of the initial preparation, the reservoir temperature, and the interaction time. Upon investigating the Fisher information of feasible measurements, we arrive at a remarkable simple result: homodyne detection of canonical variables allows one to achieve the ultimate quantum limit to precision under suitable, mild, conditions. Finally, upon exploiting a perturbative approach, we find the invariant sweet spots of the (tunable) characteristic frequency of the probe, able to drive the probe towards the optimal working regime.

Online games: a novel approach to explore how partial information influences human random searches.

PubMed

Martínez-García, Ricardo; Calabrese, Justin M; López, Cristóbal

2017-01-06

Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of e ach displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches.

Baseline estimation in flame's spectra by using neural networks and robust statistics

NASA Astrophysics Data System (ADS)

Garces, Hugo; Arias, Luis; Rojas, Alejandro

2014-09-01

This work presents a baseline estimation method in flame spectra based on artificial intelligence structure as a neural network, combining robust statistics with multivariate analysis to automatically discriminate measured wavelengths belonging to continuous feature for model adaptation, surpassing restriction of measuring target baseline for training. The main contributions of this paper are: to analyze a flame spectra database computing Jolliffe statistics from Principal Components Analysis detecting wavelengths not correlated with most of the measured data corresponding to baseline; to systematically determine the optimal number of neurons in hidden layers based on Akaike's Final Prediction Error; to estimate baseline in full wavelength range sampling measured spectra; and to train an artificial intelligence structure as a Neural Network which allows to generalize the relation between measured and baseline spectra. The main application of our research is to compute total radiation with baseline information, allowing to diagnose combustion process state for optimization in early stages.

PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads

PubMed Central

Cheng, Wen-Chang

2012-01-01

In this paper we propose a robust lane detection and tracking method by combining particle filters with the particle swarm optimization method. This method mainly uses the particle filters to detect and track the local optimum of the lane model in the input image and then seeks the global optimal solution of the lane model by a particle swarm optimization method. The particle filter can effectively complete lane detection and tracking in complicated or variable lane environments. However, the result obtained is usually a local optimal system status rather than the global optimal system status. Thus, the particle swarm optimization method is used to further refine the global optimal system status in all system statuses. Since the particle swarm optimization method is a global optimization algorithm based on iterative computing, it can find the global optimal lane model by simulating the food finding way of fish school or insects under the mutual cooperation of all particles. In verification testing, the test environments included highways and ordinary roads as well as straight and curved lanes, uphill and downhill lanes, lane changes, etc. Our proposed method can complete the lane detection and tracking more accurately and effectively then existing options. PMID:23235453

Detecting and locating light atoms from high-resolution STEM images: The quest for a single optimal design.

PubMed

Gonnissen, J; De Backer, A; den Dekker, A J; Sijbers, J; Van Aert, S

2016-11-01

In the present paper, the optimal detector design is investigated for both detecting and locating light atoms from high resolution scanning transmission electron microscopy (HR STEM) images. The principles of detection theory are used to quantify the probability of error for the detection of light atoms from HR STEM images. To determine the optimal experiment design for locating light atoms, use is made of the so-called Cramér-Rao Lower Bound (CRLB). It is investigated if a single optimal design can be found for both the detection and location problem of light atoms. Furthermore, the incoming electron dose is optimised for both research goals and it is shown that picometre range precision is feasible for the estimation of the atom positions when using an appropriate incoming electron dose under the optimal detector settings to detect light atoms. Copyright © 2016 Elsevier B.V. All rights reserved.

Multiobjective optimizations of a novel cryocooled dc gun based ultrafast electron diffraction beam line

NASA Astrophysics Data System (ADS)

Gulliford, Colwyn; Bartnik, Adam; Bazarov, Ivan

2016-09-01

We present the results of multiobjective genetic algorithm optimizations of a single-shot ultrafast electron diffraction beam line utilizing a 225 kV dc gun with a novel cryocooled photocathode system and buncher cavity. Optimizations of the transverse projected emittance as a function of bunch charge are presented and discussed in terms of the scaling laws derived in the charge saturation limit. Additionally, optimization of the transverse coherence length as a function of final rms bunch length at the sample location have been performed for three different sample radii: 50, 100, and 200 μ m , for two final bunch charges: 1 05 electrons (16 fC) and 1 06 electrons (160 fC). Example optimal solutions are analyzed, and the effects of disordered induced heating estimated. In particular, a relative coherence length of Lc ,x/σx=0.27 nm /μ m was obtained for a final bunch charge of 1 05 electrons and final bunch length of σt≈100 fs . For a final charge of 1 06 electrons the cryogun produces Lc ,x/σx≈0.1 nm /μ m for σt≈100 - 200 fs and σx≥50 μ m . These results demonstrate the viability of using genetic algorithms in the design and operation of ultrafast electron diffraction beam lines.

Complementary molecular and elemental detection of speciated thioarsenicals using ESI-MS in combination with a xenon-based collision-cell ICP-MS with application to fortified NIST freeze-dried urine.

PubMed

Ellis, Jenny L; Conklin, Sean D; Gallawa, Christina M; Kubachka, Kevin M; Young, Andrea R; Creed, Patricia A; Caruso, Joseph A; Creed, John T

2008-04-01

The simultaneous detection of arsenic and sulfur in thioarsenicals was achieved using xenon-based collision-cell inductively coupled plasma (ICP) mass spectrometry (MS) in combination with high-performance liquid chromatography. In an attempt to minimize the (16)O(16)O(+) interference at m/z 32, both sample introduction and collision-cell experimental parameters were optimized. Low flow rates (0.25 mL/min) and a high methanol concentration (8%) in the mobile phase produced a fourfold decrease in the m/z 32 background. A plasma sampling depth change from 3 to 7 mm produced a twofold decrease in background at m/z 32, with a corresponding fourfold increase in the signal associated with a high ionization surrogate for sulfur. The quadrupole bias and the octopole bias were used as a kinetic energy discriminator between background and analyte ions, but a variety of tuning conditions produced similar (less than twofold change) detection limits for sulfur ((32)S). A 34-fold improvement in the (32)S detection limit was achieved using xenon instead of helium as a collision gas. The optimized xenon-based collision cell ICP mass spectrometer was then used with electrospray ionization MS to provide elemental and molecular-based information for the analysis of a fortified sample of NIST freeze-dried urine. The 3sigma detection limits, based on peak height for dimethylthioarsinic acid (DMTA) and trimethylarsine sulfide (TMAS), were 15 and 12 ng/g, respectively. Finally, the peak area reproducibilities (percentage relative standard deviation) of a 5-ppm fortified sample of NIST freeze dried urine for DMTA and TMAS were 7.4 and 5.4%, respectively.

Multiobjective optimization design of an rf gun based electron diffraction beam line

NASA Astrophysics Data System (ADS)

Gulliford, Colwyn; Bartnik, Adam; Bazarov, Ivan; Maxson, Jared

2017-03-01

Multiobjective genetic algorithm optimizations of a single-shot ultrafast electron diffraction beam line comprised of a 100 MV /m 1.6-cell normal conducting rf (NCRF) gun, as well as a nine-cell 2 π /3 bunching cavity placed between two solenoids, have been performed. These include optimization of the normalized transverse emittance as a function of bunch charge, as well as optimization of the transverse coherence length as a function of the rms bunch length of the beam at the sample location for a fixed charge of 1 06 electrons. Analysis of the resulting solutions is discussed in terms of the relevant scaling laws, and a detailed description of one of the resulting solutions from the coherence length optimizations is given. For a charge of 1 06 electrons and final beam sizes of σx≥25 μ m and σt≈5 fs , we found a relative coherence length of Lc ,x/σx≈0.07 using direct optimization of the coherence length. Additionally, based on optimizations of the emittance as a function of final bunch length, we estimate the relative coherence length for bunch lengths of 30 and 100 fs to be roughly 0.1 and 0.2 nm /μ m , respectively. Finally, using the scaling of the optimal emittance with bunch charge, for a charge of 1 05 electrons, we estimate relative coherence lengths of 0.3, 0.5, and 0.92 nm /μ m for final bunch lengths of 5, 30 and 100 fs, respectively.

The role of modern control theory in the design of controls for aircraft turbine engines

NASA Technical Reports Server (NTRS)

Zeller, J.; Lehtinen, B.; Merrill, W.

1982-01-01

The development, applications, and current research in modern control theory (MCT) are reviewed, noting the importance for fuel-efficient operation of turbines with variable inlet guide vanes, compressor stators, and exhaust nozzle area. The evolution of multivariable propulsion control design is examined, noting a basis in a matrix formulation of the differential equations defining the process, leading to state space formulations. Reports and papers which appeared from 1970-1982 which dealt with problems in MCT applications to turbine engine control design are outlined, including works on linear quadratic regulator methods, frequency domain methods, identification, estimation, and model reduction, detection, isolation, and accommodation, and state space control, adaptive control, and optimization approaches. Finally, NASA programs in frequency domain design, sensor failure detection, computer-aided control design, and plant modeling are explored

Health Monitoring Survey of Bell 412EP Transmissions

NASA Technical Reports Server (NTRS)

Tucker, Brian E.; Dempsey, Paula J.

2016-01-01

Health and usage monitoring systems (HUMS) use vibration-based Condition Indicators (CI) to assess the health of helicopter powertrain components. A fault is detected when a CI exceeds its threshold value. The effectiveness of fault detection can be judged on the basis of assessing the condition of actual components from fleet aircraft. The Bell 412 HUMS-equipped helicopter is chosen for such an evaluation. A sample of 20 aircraft included 12 aircraft with confirmed transmission and gearbox faults (detected by CIs) and eight aircraft with no known faults. The associated CI data is classified into "healthy" and "faulted" populations based on actual condition and these populations are compared against their CI thresholds to quantify the probability of false alarm and the probability of missed detection. Receiver Operator Characteristic analysis is used to optimize thresholds. Based on the results of the analysis, shortcomings in the classification method are identified for slow-moving CI trends. Recommendations for improving classification using time-dependent receiver-operator characteristic methods are put forth. Finally, lessons learned regarding OEM-operator communication are presented.

Phosphorescence detection of manganese(VII) based on Mn-doped ZnS quantum dots

NASA Astrophysics Data System (ADS)

Deng, Pan; Lu, Li-Qiang; Cao, Wei-Cheng; Tian, Xi-Ke

2017-02-01

The phosphorescent L-cysteine modified manganese-doped zinc sulfide quantum dots (L-cys-MnZnS QDs) was developed for a highly sensitive detection of permanganate anions (MnO4-). L-cys-MnZnS QDs, which were easily synthesized in aqueous media using safe and low-cost materials, can emit intense phosphorescence even though the solution was not deoxygenated. However, the phosphorescence of L-cys-Mn-ZnS QDs was strongly quenched by MnO4- ascribed to the oxidation of L-cys and the increase of surface defects on L-cys-MnZnS QDs. Under the optimal conditions, L-cys-MnZnS QDs offer high selectivity over other anions for MnO4- determination, and good linear Stern-Volmer equation was obtained for MnO4- in the range of 0.5-100 μM with a detection limit down to 0.24 μM. The developed method was finally applied to the detection of MnO4- in water samples, and the spike-recoveries fell in the range of 95-106%.

Strategies for early detection of resectable pancreatic cancer

PubMed Central

Okano, Keiichi; Suzuki, Yasuyuki

2014-01-01

Pancreatic cancer is difficult to diagnose at an early stage and generally has a poor prognosis. Surgical resection is the only potentially curative treatment for pancreatic carcinoma. To improve the prognosis of this disease, it is essential to detect tumors at early stages, when they are resectable. The optimal approach to screening for early pancreatic neoplasia has not been established. The International Cancer of the Pancreas Screening Consortium has recently finalized several recommendations regarding the management of patients who are at an increased risk of familial pancreatic cancer. In addition, there have been notable advances in research on serum markers, tissue markers, gene signatures, and genomic targets of pancreatic cancer. To date, however, no biomarkers have been established in the clinical setting. Advancements in imaging modalities touch all aspects of the clinical management of pancreatic diseases, including the early detection of pancreatic masses, their characterization, and evaluations of tumor resectability. This article reviews strategies for screening high-risk groups, biomarkers, and current advances in imaging modalities for the early detection of resectable pancreatic cancer. PMID:25170207

Dielectrophoresis-Assisted Raman Spectroscopy of Intravesicular Analytes on Metallic Pyramids.

PubMed

Barik, Avijit; Cherukulappurath, Sudhir; Wittenberg, Nathan J; Johnson, Timothy W; Oh, Sang-Hyun

2016-02-02

Chemical analysis of membrane-bound containers such as secretory vesicles, organelles, and exosomes can provide insights into subcellular biology. These containers are loaded with a range of important biomolecules, which further underscores the need for sensitive and selective analysis methods. Here we present a metallic pyramid array for intravesicular analysis by combining site-selective dielectrophoresis (DEP) and Raman spectroscopy. Sharp pyramidal tips act as a gradient force generator to trap nanoparticles or vesicles from the solution, and the tips are illuminated by a monochromatic light source for concurrent spectroscopic detection of trapped analytes. The parameters suitable for DEP trapping were optimized by fluorescence microscopy, and the Raman spectroscopy setup was characterized by a nanoparticle based model system. Finally, vesicles loaded with 4-mercaptopyridine were concentrated at the tips and their Raman spectra were detected in real time. These pyramidal tips can perform large-area array-based trapping and spectroscopic analysis, opening up possibilities to detect molecules inside cells or cell-derived vesicles.

New method for monitoring nitric oxide in vivo using microdialysis sampling and chemiluminescence reaction

NASA Astrophysics Data System (ADS)

Yao, Dachun; Evmiridis, Nick P.; Zhou, Yikai; Xu, Shunqing; Zhou, Huarong

2001-09-01

A new method employing a combination of micro dialysis sampling and chemiluminescence reaction was developed to monitor nitric oxide (NO) in vivo. A special probe was designed with an interference-free membrane to achieve a very high selectivity for NO. High sensitivity was achieved by optimizing the working system and improving the NO sampling time. This system was used in vivo to monitor blood and brain tissue in rats and rabbits. We have established that this system is sensitive enough to detect variations in NO production in difference physiological state. The system can detect NO in the linear range of 5nM-1(mu) M, with a detection limit of 1nM, and real NO concentrations in our experimental animals were found to be in the range of 1-5 nM or even less. Finally, the effects of body temperature, NO donors, Viagra, NO activators, NO cofactors, NO interference were investigated carefully in different physiological situations.

Simulation of Graphene Field-Effect Transistor Biosensors for Bacterial Detection.

PubMed

Wu, Guangfu; Meyyappan, Meyya; Lai, King Wai Chiu

2018-05-25

Foodborne illness is correlated with the existence of infectious pathogens such as bacteria in food and drinking water. Probe-modified graphene field effect transistors (G-FETs) have been shown to be suitable for Escherichia coli ( E. coli ) detection. Here, the G-FETs for bacterial detection are modeled and simulated with COMSOL Multiphysics to understand the operation of the biosensors. The motion of E. coli cells in electrolyte and the surface charge of graphene induced by E. coli are systematically investigated. The comparison between the simulation and experimental data proves the sensing probe size to be a key parameter affecting the surface charge of graphene induced by bacteria. Finally, the relationship among the change in source-drain current (∆ I ds ), graphene-bacteria distance and bacterial concentration is established. The shorter graphene-bacteria distance and higher bacterial concentration give rise to better sensing performance (larger ∆ I ds ) of the G-FETs biosensors. The simulation here could serve as a guideline for the design and optimization of G-FET biosensors for various applications.

Detection of genomic loci associated with environmental variables using generalized linear mixed models.

PubMed

Lobréaux, Stéphane; Melodelima, Christelle

2015-02-01

We tested the use of Generalized Linear Mixed Models to detect associations between genetic loci and environmental variables, taking into account the population structure of sampled individuals. We used a simulation approach to generate datasets under demographically and selectively explicit models. These datasets were used to analyze and optimize GLMM capacity to detect the association between markers and selective coefficients as environmental data in terms of false and true positive rates. Different sampling strategies were tested, maximizing the number of populations sampled, sites sampled per population, or individuals sampled per site, and the effect of different selective intensities on the efficiency of the method was determined. Finally, we apply these models to an Arabidopsis thaliana SNP dataset from different accessions, looking for loci associated with spring minimal temperature. We identified 25 regions that exhibit unusual correlations with the climatic variable and contain genes with functions related to temperature stress. Copyright © 2014 Elsevier Inc. All rights reserved.

The CHARIS High-Contrast Integral-Field Spectrograph

NASA Technical Reports Server (NTRS)

Groff, Tyler D.; Chilcote, Jeffrey; Brandt, Timothy; Kasdin, N. Jeremy; Galvin, Michael; Loomis, Craig; Rizzo, Maxime; Knapp, Gillian; Guyon, Olivier; Jovanovic, Nemanja;

Structural damage detection in wind turbine blades based on time series representations of dynamic responses

NASA Astrophysics Data System (ADS)

Hoell, Simon; Omenzetter, Piotr

2015-03-01

The development of large wind turbines that enable to harvest energy more efficiently is a consequence of the increasing demand for renewables in the world. To optimize the potential energy output, light and flexible wind turbine blades (WTBs) are designed. However, the higher flexibilities and lower buckling capacities adversely affect the long-term safety and reliability of WTBs, and thus the increased operation and maintenance costs reduce the expected revenue. Effective structural health monitoring techniques can help to counteract this by limiting inspection efforts and avoiding unplanned maintenance actions. Vibration-based methods deserve high attention due to the moderate instrumentation efforts and the applicability for in-service measurements. The present paper proposes the use of cross-correlations (CCs) of acceleration responses between sensors at different locations for structural damage detection in WTBs. CCs were in the past successfully applied for damage detection in numerical and experimental beam structures while utilizing only single lags between the signals. The present approach uses vectors of CC coefficients for multiple lags between measurements of two selected sensors taken from multiple possible combinations of sensors. To reduce the dimensionality of the damage sensitive feature (DSF) vectors, principal component analysis is performed. The optimal number of principal components (PCs) is chosen with respect to a statistical threshold. Finally, the detection phase uses the selected PCs of the healthy structure to calculate scores from a current DSF vector, where statistical hypothesis testing is performed for making a decision about the current structural state. The method is applied to laboratory experiments conducted on a small WTB with non-destructive damage scenarios.

Large-scale metabolite analysis of standards and human serum by laser desorption ionization mass spectrometry from silicon nanopost arrays

DOE PAGES

Korte, Andrew R.; Stopka, Sylwia A.; Morris, Nicholas; ...

2016-07-11

The unique challenges presented by metabolomics have driven the development of new mass spectrometry (MS)-based techniques for small molecule analysis. We have previously demonstrated silicon nanopost arrays (NAPA) to be an effective substrate for laser desorption ionization (LDI) of small molecules for MS. However, the utility of NAPA-LDI-MS for a wide range of metabolite classes has not been investigated. Here we apply NAPA-LDI-MS to the large-scale acquisition of high-resolution mass spectra and tandem mass spectra from a collection of metabolite standards covering a range of compound classes including amino acids, nucleotides, carbohydrates, xenobiotics, lipids, and other classes. In untargeted analysismore » of metabolite standard mixtures, detection was achieved for 374 compounds and useful MS/MS spectra were obtained for 287 compounds, without individual optimization of ionization or fragmentation conditions. Metabolite detection was evaluated in the context of 31 metabolic pathways, and NAPA-LDI-MS was found to provide detection for 63% of investigated pathway metabolites. Individual, targeted analysis of the 20 common amino acids provided detection of 100% of the investigated compounds, demonstrating that improved coverage is possible through optimization and targeting of individual analytes or analyte classes. In direct analysis of aqueous and organic extracts from human serum samples, spectral features were assigned to a total of 108 small metabolites and lipids. Glucose and amino acids were quantitated within their physiological concentration ranges. Finally, the broad coverage demonstrated by this large-scale screening experiment opens the door for use of NAPA-LDI-MS in numerous metabolite analysis applications« less

Large-scale metabolite analysis of standards and human serum by laser desorption ionization mass spectrometry from silicon nanopost arrays

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

Korte, Andrew R.; Stopka, Sylwia A.; Morris, Nicholas

The unique challenges presented by metabolomics have driven the development of new mass spectrometry (MS)-based techniques for small molecule analysis. We have previously demonstrated silicon nanopost arrays (NAPA) to be an effective substrate for laser desorption ionization (LDI) of small molecules for MS. However, the utility of NAPA-LDI-MS for a wide range of metabolite classes has not been investigated. Here we apply NAPA-LDI-MS to the large-scale acquisition of high-resolution mass spectra and tandem mass spectra from a collection of metabolite standards covering a range of compound classes including amino acids, nucleotides, carbohydrates, xenobiotics, lipids, and other classes. In untargeted analysismore » of metabolite standard mixtures, detection was achieved for 374 compounds and useful MS/MS spectra were obtained for 287 compounds, without individual optimization of ionization or fragmentation conditions. Metabolite detection was evaluated in the context of 31 metabolic pathways, and NAPA-LDI-MS was found to provide detection for 63% of investigated pathway metabolites. Individual, targeted analysis of the 20 common amino acids provided detection of 100% of the investigated compounds, demonstrating that improved coverage is possible through optimization and targeting of individual analytes or analyte classes. In direct analysis of aqueous and organic extracts from human serum samples, spectral features were assigned to a total of 108 small metabolites and lipids. Glucose and amino acids were quantitated within their physiological concentration ranges. Finally, the broad coverage demonstrated by this large-scale screening experiment opens the door for use of NAPA-LDI-MS in numerous metabolite analysis applications« less

Coronary artery segmentation in X-ray angiograms using gabor filters and differential evolution.

PubMed

Cervantes-Sanchez, Fernando; Cruz-Aceves, Ivan; Hernandez-Aguirre, Arturo; Solorio-Meza, Sergio; Cordova-Fraga, Teodoro; Aviña-Cervantes, Juan Gabriel

2018-08-01

Segmentation of coronary arteries in X-ray angiograms represents an essential task for computer-aided diagnosis, since it can help cardiologists in diagnosing and monitoring vascular abnormalities. Due to the main disadvantages of the X-ray angiograms are the nonuniform illumination, and the weak contrast between blood vessels and image background, different vessel enhancement methods have been introduced. In this paper, a novel method for blood vessel enhancement based on Gabor filters tuned using the optimization strategy of Differential evolution (DE) is proposed. Because the Gabor filters are governed by three different parameters, the optimal selection of those parameters is highly desirable in order to maximize the vessel detection rate while reducing the computational cost of the training stage. To obtain the optimal set of parameters for the Gabor filters, the area (Az) under the receiver operating characteristics curve is used as objective function. In the experimental results, the proposed method achieves an A z =0.9388 in a training set of 40 images, and for a test set of 40 images it obtains the highest performance with an A z =0.9538 compared with six state-of-the-art vessel detection methods. Finally, the proposed method achieves an accuracy of 0.9423 for vessel segmentation using the test set. In addition, the experimental results have also shown that the proposed method can be highly suitable for clinical decision support in terms of computational time and vessel segmentation performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Factorial design optimization of experimental variables in the on-line separation/preconcentration of copper in water samples using solid phase extraction and ICP-OES determination.

PubMed

Escudero, Luis A; Cerutti, S; Olsina, R A; Salonia, J A; Gasquez, J A

2010-11-15

An on-line preconcentration procedure using solid phase extraction (SPE) for the determination of copper in different water samples by inductively coupled plasma optical emission spectrometry (ICP-OES) is proposed. The copper was retained on a minicolumn filled with ethyl vinyl acetate (EVA) at pH 8.0 without using any complexing reagent. The experimental optimization step was performed using a two-level full factorial design. The results showed that pH, sample loading flow rate, and their interaction (at the tested levels) were statistically significant. In order to determine the best conditions for preconcentration and determination of copper, a final optimization of the significant factors was carried out using a central composite design (CCD). The calibration graph was linear with a regression coefficient of 0.995 at levels near the detection limit up to at least 300 μg L(-1). An enrichment factor (EF) of 54 with a preconcentration time of 187.5 s was obtained. The limit of detection (3σ) was 0.26 μg L(-1). The sampling frequency for the developed methodology was about 15 samples/h. The relative standard deviation (RSD) for six replicates containing 50 μg L(-1) of copper was 3.76%. The methodology was successfully applied to the determination of Cu in tap, mineral, river water samples, and in a certified VKI standard reference material. Copyright © 2010 Elsevier B.V. All rights reserved.

Network anomaly detection system with optimized DS evidence theory.

PubMed

Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

2014-01-01

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network-complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each sensor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly.

Network Anomaly Detection System with Optimized DS Evidence Theory

PubMed Central

Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

2014-01-01

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network—complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each senor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly. PMID:25254258

Ionic liquid-modified silica-coated magnetic nanoparticles: promising adsorbents for ultra-fast extraction of paraquat from aqueous solution.

PubMed

Latifeh, Farzad; Yamini, Yadollah; Seidi, Shahram

2016-03-01

In the present study, ionic liquid-modified silica-coated magnetic nanoparticles (Fe3O4@SiO2@IL) were synthesized and applied as adsorbents for extraction and determination of paraquat (PQ) followed by high-performance liquid chromatography. For assurance of the extraction efficiency, the obtained results were compared with those obtained by bared magnetic nanoparticles (MNPs). Experimental design and response surface methodology were used for optimization of different parameters which affect extraction efficiency of paraquat using both adsorbents. Under the optimized conditions, extraction recoveries in the range of 20-25 and 35-40 % with satisfactory repeatability values (RSDs%, n = 4) less than 5.0 % were obtained for bared MNPs and Fe3O4@SiO2@IL, respectively. The limits of detection were 0.1 and 0.25 μg/L using Fe3O4@SiO2@IL and bared MNPs, respectively. The linearity was obtained in the range of 0.25 to 25 μg/L and 0.5 to 25 μg/L for Fe3O4@SiO2@IL and bared MNPs, respectively, with the coefficients of determination better than 0.9950. Finally, Fe3O4@SiO2@IL was chosen as superior adsorbent due to more dispersion ability, higher extraction recovery, lower detection limit, as well as better linearity and repeatability. Calculated errors (%) were in the range of 3 to 10 % depicting acceptable accuracy for the analysis of PQ by the proposed method. Finally, the method was successfully applied for extraction and determination of PQ in some water and countryside soil samples.

Pure sources and efficient detectors for optical quantum information processing

NASA Astrophysics Data System (ADS)

Zielnicki, Kevin

Over the last sixty years, classical information theory has revolutionized the understanding of the nature of information, and how it can be quantified and manipulated. Quantum information processing extends these lessons to quantum systems, where the properties of intrinsic uncertainty and entanglement fundamentally defy classical explanation. This growing field has many potential applications, including computing, cryptography, communication, and metrology. As inherently mobile quantum particles, photons are likely to play an important role in any mature large-scale quantum information processing system. However, the available methods for producing and detecting complex multi-photon states place practical limits on the feasibility of sophisticated optical quantum information processing experiments. In a typical quantum information protocol, a source first produces an interesting or useful quantum state (or set of states), perhaps involving superposition or entanglement. Then, some manipulations are performed on this state, perhaps involving quantum logic gates which further manipulate or entangle the intial state. Finally, the state must be detected, obtaining some desired measurement result, e.g., for secure communication or computationally efficient factoring. The work presented here concerns the first and last stages of this process as they relate to photons: sources and detectors. Our work on sources is based on the need for optimized non-classical states of light delivered at high rates, particularly of single photons in a pure quantum state. We seek to better understand the properties of spontaneous parameteric downconversion (SPDC) sources of photon pairs, and in doing so, produce such an optimized source. We report an SPDC source which produces pure heralded single photons with little or no spectral filtering, allowing a significant rate enhancement. Our work on detectors is based on the need to reliably measure single-photon states. We have focused on optimizing the detection efficiency of visible light photon counters (VLPCs), a single-photon detection technology that is also capable of resolving photon number states. We report a record-breaking quantum efficiency of 91 +/- 3% observed with our detection system. Both sources and detectors are independently interesting physical systems worthy of study, but together they promise to enable entire new classes and applications of information based on quantum mechanics.

Determination of oleamide and erucamide in polyethylene films by pressurised fluid extraction and gas chromatography.

PubMed

Garrido-López, Alvaro; Esquiu, Vanesa; Tena, María Teresa

2006-08-18

A pressurized fluid extraction (PFE) and gas chromatography-flame ionization detection (GC-FID) method is proposed to determine the slip agents in polyethylene (PE) films. The study of PFE variables was performed using a fractional factorial design (FFD) for screening and a central composite design (CCD) for optimizing the main variables obtained from the Pareto charts. The variables that were studied include temperature, static time, percentage of cyclohexane and the number of extraction cycles. The final condition selected was pure isopropanol (two times) at 105 degrees C for 16min. The recovery of spiked oleamide and erucamide was around 100%. The repeatability of the method was between 9.6% for oleamide and 8% for erucamide, expressed as relative standard deviation. Finally, the method was applied to determine oleamide and erucamide in several polyethylene films and the results were statistically equal to those obtained by pyrolysis and gas-phase chemiluminescence (CL).

Ultimate limits for quantum magnetometry via time-continuous measurements

NASA Astrophysics Data System (ADS)

Albarelli, Francesco; Rossi, Matteo A. C.; Paris, Matteo G. A.; Genoni, Marco G.

2017-12-01

We address the estimation of the magnetic field B acting on an ensemble of atoms with total spin J subjected to collective transverse noise. By preparing an initial spin coherent state, for any measurement performed after the evolution, the mean-square error of the estimate is known to scale as 1/J, i.e. no quantum enhancement is obtained. Here, we consider the possibility of continuously monitoring the atomic environment, and conclusively show that strategies based on time-continuous non-demolition measurements followed by a final strong measurement may achieve Heisenberg-limited scaling 1/{J}2 and also a monitoring-enhanced scaling in terms of the interrogation time. We also find that time-continuous schemes are robust against detection losses, as we prove that the quantum enhancement can be recovered also for finite measurement efficiency. Finally, we analytically prove the optimality of our strategy.

Image quality, threshold contrast and mean glandular dose in CR mammography

NASA Astrophysics Data System (ADS)

Jakubiak, R. R.; Gamba, H. R.; Neves, E. B.; Peixoto, J. E.

2013-09-01

In many countries, computed radiography (CR) systems represent the majority of equipment used in digital mammography. This study presents a method for optimizing image quality and dose in CR mammography of patients with breast thicknesses between 45 and 75 mm. Initially, clinical images of 67 patients (group 1) were analyzed by three experienced radiologists, reporting about anatomical structures, noise and contrast in low and high pixel value areas, and image sharpness and contrast. Exposure parameters (kV, mAs and target/filter combination) used in the examinations of these patients were reproduced to determine the contrast-to-noise ratio (CNR) and mean glandular dose (MGD). The parameters were also used to radiograph a CDMAM (version 3.4) phantom (Artinis Medical Systems, The Netherlands) for image threshold contrast evaluation. After that, different breast thicknesses were simulated with polymethylmethacrylate layers and various sets of exposure parameters were used in order to determine optimal radiographic parameters. For each simulated breast thickness, optimal beam quality was defined as giving a target CNR to reach the threshold contrast of CDMAM images for acceptable MGD. These results were used for adjustments in the automatic exposure control (AEC) by the maintenance team. Using optimized exposure parameters, clinical images of 63 patients (group 2) were evaluated as described above. Threshold contrast, CNR and MGD for such exposure parameters were also determined. Results showed that the proposed optimization method was effective for all breast thicknesses studied in phantoms. The best result was found for breasts of 75 mm. While in group 1 there was no detection of the 0.1 mm critical diameter detail with threshold contrast below 23%, after the optimization, detection occurred in 47.6% of the images. There was also an average MGD reduction of 7.5%. The clinical image quality criteria were attended in 91.7% for all breast thicknesses evaluated in both patient groups. Finally, this study also concluded that the use of the AEC of the x-ray unit based on the constant dose to the detector may bring some difficulties to CR systems to operate under optimal conditions. More studies must be performed, so that the compatibility between systems and optimization methodologies can be evaluated, as well as this optimization method. Most methods are developed for phantoms, so comparative studies including clinical images must be developed.

Influence of ligand chemistry on silver nanoparticles for colorimetric detection of Cr3+ and Hg2+ ions

NASA Astrophysics Data System (ADS)

Kailasa, Suresh Kumar; Chandel, Madhurya; Mehta, Vaibhavkumar N.; Park, Tae Jung

2018-04-01

In this work, we describe the role of ligand chemistry on the surfaces of silver nanoparticles (Ag NPs) for tuning their analytical applications. The citrate and melamine (MA) molecules were used as ligands for the surface modification of Ag NPs. The addition of Cr3+ ion in citrate-Ag NPs (Cit-Ag NPs) and of Hg2+ ion in melamine-Ag NPs (MA-Ag NPs) cause Ag NPs aggregation, and are accompanied by a color change and a red-shift. The resulting distinctly visual readouts are favorable for colorimetric detection of Cr3+ and Hg2+ ions. Under optimal conditions, the linear ranges are observed in the concentration ranges of 1.0-50.0 and of 10.0-100.0 μM, and with detection limit of 0.52 and 1.80 μM for Cr3+ and Hg2+ ions. The simultaneous detection of Cr3+ and Hg2+ ion is driven by the changing the ligand chemistry on the surfaces of Ag NPs that allows to tune their specific interactions with target analytes. Finally, the functionalized Ag NPs were successfully applied to detect Cr3+ and Hg2+ ions in water samples with satisfactory recoveries.

Virtual-Lattice Based Intrusion Detection Algorithm over Actuator-Assisted Underwater Wireless Sensor Networks

PubMed Central

Yan, Jing; Li, Xiaolei; Luo, Xiaoyuan; Guan, Xinping

2017-01-01

Due to the lack of a physical line of defense, intrusion detection becomes one of the key issues in applications of underwater wireless sensor networks (UWSNs), especially when the confidentiality has prime importance. However, the resource-constrained property of UWSNs such as sparse deployment and energy constraint makes intrusion detection a challenging issue. This paper considers a virtual-lattice-based approach to the intrusion detection problem in UWSNs. Different from most existing works, the UWSNs consist of two kinds of nodes, i.e., sensor nodes (SNs), which cannot move autonomously, and actuator nodes (ANs), which can move autonomously according to the performance requirement. With the cooperation of SNs and ANs, the intruder detection probability is defined. Then, a virtual lattice-based monitor (VLM) algorithm is proposed to detect the intruder. In order to reduce the redundancy of communication links and improve detection probability, an optimal and coordinative lattice-based monitor patrolling (OCLMP) algorithm is further provided for UWSNs, wherein an equal price search strategy is given for ANs to find the shortest patrolling path. Under VLM and OCLMP algorithms, the detection probabilities are calculated, while the topology connectivity can be guaranteed. Finally, simulation results are presented to show that the proposed method in this paper can improve the detection accuracy and save the energy consumption compared with the conventional methods. PMID:28531127

Subnuclear localization, rates and effectiveness of UVC-induced unscheduled DNA synthesis visualized by fluorescence widefield, confocal and super-resolution microscopy.

PubMed

Pierzyńska-Mach, Agnieszka; Szczurek, Aleksander; Cella Zanacchi, Francesca; Pennacchietti, Francesca; Drukała, Justyna; Diaspro, Alberto; Cremer, Christoph; Darzynkiewicz, Zbigniew; Dobrucki, Jurek W

2016-01-01

Unscheduled DNA synthesis (UDS) is the final stage of the process of repair of DNA lesions induced by UVC. We detected UDS using a DNA precursor, 5-ethynyl-2'-deoxyuridine (EdU). Using wide-field, confocal and super-resolution fluorescence microscopy and normal human fibroblasts, derived from healthy subjects, we demonstrate that the sub-nuclear pattern of UDS detected via incorporation of EdU is different from that when BrdU is used as DNA precursor. EdU incorporation occurs evenly throughout chromatin, as opposed to just a few small and large repair foci detected by BrdU. We attribute this difference to the fact that BrdU antibody is of much larger size than EdU, and its accessibility to the incorporated precursor requires the presence of denatured sections of DNA. It appears that under the standard conditions of immunocytochemical detection of BrdU only fragments of DNA of various length are being denatured. We argue that, compared with BrdU, the UDS pattern visualized by EdU constitutes a more faithful representation of sub-nuclear distribution of the final stage of nucleotide excision repair induced by UVC. Using the optimized integrated EdU detection procedure we also measured the relative amount of the DNA precursor incorporated by cells during UDS following exposure to various doses of UVC. Also described is the high degree of heterogeneity in terms of the UVC-induced EdU incorporation per cell, presumably reflecting various DNA repair efficiencies or differences in the level of endogenous dT competing with EdU within a population of normal human fibroblasts.

Subnuclear localization, rates and effectiveness of UVC-induced unscheduled DNA synthesis visualized by fluorescence widefield, confocal and super-resolution microscopy

PubMed Central

Pierzyńska-Mach, Agnieszka; Szczurek, Aleksander; Cella Zanacchi, Francesca; Pennacchietti, Francesca; Drukała, Justyna; Diaspro, Alberto; Cremer, Christoph; Darzynkiewicz, Zbigniew; Dobrucki, Jurek W.

2016-01-01

ABSTRACT Unscheduled DNA synthesis (UDS) is the final stage of the process of repair of DNA lesions induced by UVC. We detected UDS using a DNA precursor, 5-ethynyl-2′-deoxyuridine (EdU). Using wide-field, confocal and super-resolution fluorescence microscopy and normal human fibroblasts, derived from healthy subjects, we demonstrate that the sub-nuclear pattern of UDS detected via incorporation of EdU is different from that when BrdU is used as DNA precursor. EdU incorporation occurs evenly throughout chromatin, as opposed to just a few small and large repair foci detected by BrdU. We attribute this difference to the fact that BrdU antibody is of much larger size than EdU, and its accessibility to the incorporated precursor requires the presence of denatured sections of DNA. It appears that under the standard conditions of immunocytochemical detection of BrdU only fragments of DNA of various length are being denatured. We argue that, compared with BrdU, the UDS pattern visualized by EdU constitutes a more faithful representation of sub-nuclear distribution of the final stage of nucleotide excision repair induced by UVC. Using the optimized integrated EdU detection procedure we also measured the relative amount of the DNA precursor incorporated by cells during UDS following exposure to various doses of UVC. Also described is the high degree of heterogeneity in terms of the UVC-induced EdU incorporation per cell, presumably reflecting various DNA repair efficiencies or differences in the level of endogenous dT competing with EdU within a population of normal human fibroblasts. PMID:27097376

Optimizing disinfection by-product monitoring points in a distribution system using cluster analysis.

PubMed

Delpla, Ianis; Florea, Mihai; Pelletier, Geneviève; Rodriguez, Manuel J

2018-06-04

Trihalomethanes (THMs) and Haloacetic Acids (HAAs) are the main groups detected in drinking water and are consequently strictly regulated. However, the increasing quantity of data for disinfection byproducts (DBPs) produced from research projects and regulatory programs remains largely unexploited, despite a great potential for its use in optimizing drinking water quality monitoring to meet specific objectives. In this work, we developed a procedure to optimize locations and periods for DBPs monitoring based on a set of monitoring scenarios using the cluster analysis technique. The optimization procedure used a robust set of spatio-temporal monitoring results on DBPs (THMs and HAAs) generated from intensive sampling campaigns conducted in a residential sector of a water distribution system. Results shows that cluster analysis allows for the classification of water quality in different groups of THMs and HAAs according to their similarities, and the identification of locations presenting water quality concerns. By using cluster analysis with different monitoring objectives, this work provides a set of monitoring solutions and a comparison between various monitoring scenarios for decision-making purposes. Finally, it was demonstrated that the data from intensive monitoring of free chlorine residual and water temperature as DBP proxy parameters, when processed using cluster analysis, could also help identify the optimal sampling points and periods for regulatory THMs and HAAs monitoring. Copyright © 2018 Elsevier Ltd. All rights reserved.

Improved alignment evaluation and optimization : final report.

DOT National Transportation Integrated Search

2007-09-11

This report outlines the development of an enhanced highway alignment evaluation and optimization : model. A GIS-based software tool is prepared for alignment optimization that uses genetic algorithms for : optimal search. The software is capable of ...

Dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization

NASA Astrophysics Data System (ADS)

Li, Li

2018-03-01

In order to extract target from complex background more quickly and accurately, and to further improve the detection effect of defects, a method of dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization was proposed. Firstly, the method of single-threshold selection based on Arimoto entropy was extended to dual-threshold selection in order to separate the target from the background more accurately. Then intermediate variables in formulae of Arimoto entropy dual-threshold selection was calculated by recursion to eliminate redundant computation effectively and to reduce the amount of calculation. Finally, the local search phase of artificial bee colony algorithm was improved by chaotic sequence based on tent mapping. The fast search for two optimal thresholds was achieved using the improved bee colony optimization algorithm, thus the search could be accelerated obviously. A large number of experimental results show that, compared with the existing segmentation methods such as multi-threshold segmentation method using maximum Shannon entropy, two-dimensional Shannon entropy segmentation method, two-dimensional Tsallis gray entropy segmentation method and multi-threshold segmentation method using reciprocal gray entropy, the proposed method can segment target more quickly and accurately with superior segmentation effect. It proves to be an instant and effective method for image segmentation.

Multi-hop path tracing of mobile robot with multi-range image

NASA Astrophysics Data System (ADS)

Choudhury, Ramakanta; Samal, Chandrakanta; Choudhury, Umakanta

2010-02-01

It is well known that image processing depends heavily upon image representation technique . This paper intends to find out the optimal path of mobile robots for a specified area where obstacles are predefined as well as modified. Here the optimal path is represented by using the Quad tree method. Since there has been rising interest in the use of quad tree, we have tried to use the successive subdivision of images into quadrants from which the quad tree is developed. In the quad tree, obstacles-free area and the partial filled area are represented with different notations. After development of quad tree the algorithm is used to find the optimal path by employing neighbor finding technique, with a view to move the robot from the source to destination. The algorithm, here , permeates through the entire tree, and tries to locate the common ancestor for computation. The computation and the algorithm, aim at easing the ability of the robot to trace the optimal path with the help of adjacencies between the neighboring nodes as well as determining such adjacencies in the horizontal, vertical and diagonal directions. In this paper efforts have been made to determine the movement of the adjacent block in the quad tree and to detect the transition between the blocks equal size and finally generate the result.

Conduct overall test operations and evaluate two Doppler systems to detect, track and measure velocities in aircraft wake vortices

NASA Technical Reports Server (NTRS)

Wilson, D. J.; Krause, M. C.; Craven, C. E.; Edwards, B. B.; Coffey, E. W.; Huang, C. C.; Jetton, J. L.; Morrison, L. K.

1974-01-01

A program plan for system evaluation of the two-dimensional Scanning Laser Doppler System (SLDS) is presented. In order to meet system evaluation and optimization objectives the following tests were conducted: (1) noise tests; (2) wind tests; (3) blower flowfield tests; (4) single unit (1-D) flyby tests; and (5) dual unit (2-D) flyby tests. Test results are reported. The final phase of the program included logistics preparation, equipment interface checkouts, and data processing. It is concluded that the SLDS is capable of accurately tracking aircraft wake vortices from small or large aircraft, and in any type of weather.

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

PubMed Central

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

2014-01-01

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

A reversed-phase compatible thin-layer chromatography autography for the detection of acetylcholinesterase inhibitors.

PubMed

Ramallo, I Ayelen; García, Paula; Furlan, Ricardo L E

2015-11-01

A dual readout autographic assay to detect acetylcholinesterase inhibitors present in complex matrices adsorbed on reversed-phase or normal-phase thin-layer chromatography plates is described. Enzyme gel entrapment with an amphiphilic copolymer was used for assay development. The effects of substrate and enzyme concentrations, pH, incubation time, and incubation temperature on the sensitivity and the detection limit of the assay were evaluated. Experimental design and response surface methodology were used to optimize conditions with a minimum number of experiments. The assay allowed the detection of 0.01% w/w of physostigmine in both a spiked Sonchus oleraceus L. extract chromatographed on normal phase and a spiked Pimenta racemosa (Mill.) J.W. Moore leaf essential oil chromatographed on reversed phase. Finally, the reversed-phase thin-layer chromatography assay was applied to reveal the presence of an inhibitor in the Cymbopogon citratus (DC.) Stapf essential oil. The developed assay is able to detect acetylcholinesterase inhibitors present in complex matrixes that were chromatographed in normal phase or reversed-phase thin-layer chromatography. The detection limit for physostigmine on both normal and reversed phase was of 1×10(-4) μg. The results can be read by a change in color and/or a change in fluorescence. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of a fieldable rugged TATP surface-enhanced Raman spectroscopy sensor

NASA Astrophysics Data System (ADS)

Spencer, Kevin M.; Clauson, Susan L.; Sylvia, James M.

2011-06-01

Surface-enhanced Raman spectroscopy (SERS) has repeatedly been shown to be capable of single molecule detection in laboratory controlled environments. However, superior detection of desired compounds in complex situations requires optimization of factors in addition to sensitivity. For example, SERS sensors are metals with surface roughness in the nm scale. This metallic roughness scale may not adsorb the analyte of interest but instead cause a catalytic reaction unless stabilization is designed into the sensor interface. In addition, the SERS sensor needs to be engineered sensitive only to the desired analyte(s) or a small subset of analytes; detection of every analyte would saturate the sensor and make data interpretation untenable. Finally, the SERS sensor has to be a preferable adsorption site in passive sampling applications, whether vapor or liquid. In this paper, EIC Laboratories will discuss modifications to SERS sensors that increase the likelihood of detection of the analyte of interest. We will then demonstrate data collected for TATP, a compound that rapidly decomposes and is undetected on standard silver SERS sensors. With the modified SERS sensor, ROC curves for room temperature TATP vapor detection, detection of TATP in a non equilibrium vapor environment in 30 s, detection of TATP on a sensor exposed to a ventilation duct, and detection of TATP in the presence of fuel components were all created and will be presented herein.

Multiple burn fuel-optimal orbit transfers: Numerical trajectory computation and neighboring optimal feedback guidance

NASA Technical Reports Server (NTRS)

Chuang, C.-H.; Goodson, Troy D.; Ledsinger, Laura A.

1995-01-01

This report describes current work in the numerical computation of multiple burn, fuel-optimal orbit transfers and presents an analysis of the second variation for extremal multiple burn orbital transfers as well as a discussion of a guidance scheme which may be implemented for such transfers. The discussion of numerical computation focuses on the use of multivariate interpolation to aid the computation in the numerical optimization. The second variation analysis includes the development of the conditions for the examination of both fixed and free final time transfers. Evaluations for fixed final time are presented for extremal one, two, and three burn solutions of the first variation. The free final time problem is considered for an extremal two burn solution. In addition, corresponding changes of the second variation formulation over thrust arcs and coast arcs are included. The guidance scheme discussed is an implicit scheme which implements a neighboring optimal feedback guidance strategy to calculate both thrust direction and thrust on-off times.

Residues of selected antibiotics in the South Moravian Rivers, Czech Republic.

PubMed

Jarova, Katerina; Vavrova, Milada; Koleckarova, Alice

2015-01-01

The aim of this study was to assess the contamination level of aquatic ecosystems of the Oslava and the Jihlava Rivers, and of the Nove Mlyny Water Reservoir, situated in the South Moravian Region (Czech Republic), by residues of selected veterinary pharmaceuticals. We isolated and determined 10 sulfonamide antibiotics in samples of surface water and bottom sediments using optimized analytical methods. A representative number of sampling sites in the entire basin of selected waters were chosen. Samples were collected particularly near the larger cities in order to assess their possible impact to the aquatic ecosystems. Extraction, pre-concentration and purification of samples were performed using optimized methods of solid phase extraction and pressurized solvent extraction. Final identification and quantification were carried out by high-performance liquid chromatography coupled with diode array detector. The concentration of sulfonamides in water samples were all under the limit of detection. Regarding sediment samples, sulfadimidine was found at most sampling sites; its highest values were recorded in the Jihlava River (up to 979.8 µg.kg(-1) dry matter). Other frequently detected sulfonamides were sulfamethoxazole and sulfamerazine. Most other sulfonamides were under the limit of detection or limit of quantification. Monitoring of antibiotic residues in the environment, especially in the aquatic ecosystem, is a current topic due to the growing worldwide use in both human and veterinary medicine. According to obtained results, we document the pollution of selected rivers and water reservoir by particular sulfonamides which basically reflects their application in veterinary medicine.

Automated Breast Ultrasound for Ductal Pattern Reconstruction: Ground Truth File Generation and CADe Evaluation

NASA Astrophysics Data System (ADS)

Manousaki, D.; Panagiotopoulou, A.; Bizimi, V.; Haynes, M. S.; Love, S.; Kallergi, M.

2017-11-01

The purpose of this study was the generation of ground truth files (GTFs) of the breast ducts from 3D images of the Invenia™ Automated Breast Ultrasound System (ABUS) system (GE Healthcare, Little Chalfont, UK) and the application of these GTFs for the optimization of the imaging protocol and the evaluation of a computer aided detection (CADe) algorithm developed for automated duct detection. Six lactating, nursing volunteers were scanned with the ABUS before and right after breastfeeding their infants. An expert in breast ultrasound generated rough outlines of the milk-filled ducts in the transaxial slices of all image volumes and the final GTFs were created by using thresholding and smoothing tools in ImageJ. In addition, a CADe algorithm automatically segmented duct like areas and its results were compared to the expert’s GTFs by estimating true positive fraction (TPF) or % overlap. The CADe output differed significantly from the expert’s but both detected a smaller than expected volume of the ducts due to insufficient contrast (ducts were partially filled with milk), discontinuities, and artifacts. GTFs were used to modify the imaging protocol and improve the CADe method. In conclusion, electronic GTFs provide a valuable tool in the optimization of a tomographic imaging system, the imaging protocol, and the CADe algorithms. Their generation, however, is an extremely time consuming, strenuous process, particularly for multi-slice examinations, and alternatives based on phantoms or simulations are highly desirable.

Fluorescence spectroscopy of trapped molecular ions

NASA Astrophysics Data System (ADS)

Wright, Kenneth Charles

This thesis describes the development of a unique instrument capable of detecting fluorescence emission from large gas phase molecular ions trapped in a three-dimensional quadrupole ion trap. The hypothesis that has formed the basis of this work is the belief that fluorescence spectroscopy can be combined with ion trap mass spectrometry to probe the structure of gas phase molecular ions. The ion trap provides a rarefied environment where fluorescence experiments can be conducted without interference from solvent molecules or impurities. Although fluorescence was not detected during preliminary experiments, two significant experimental challenges associated with detecting the gas phase fluorescence of ions were discovered. First, gas phase ions were vulnerable to photodissociation and low laser powers were necessary to avoid photodissociation. Since fluorescence emission is directly proportional to laser intensity, a lower laser power limits the fluorescence signal. Second, the fluorescence emission was not significantly Stokes shifted from the excitation. The lack of Stokes shift meant the small fluorescence signal must be detected in the presence of a large amount of background scatter generated by the excitation. Initially, this background was seven orders of magnitude higher than the analytical signal ultimately detected. A specially designed fiber optic probe was inserted between the electrodes of the ion trap to stop light scattered off the outside surfaces of the trap from reaching the detector. The inside surfaces of the ion trap were coated black to further reduce the amount of scattered light collected. These innovations helped reduced the background by six orders of magnitude and fluorescence emission from rhodamine-6G was detected. Pulse counting experiments were used to optimize fluorescence detection. The effects of trapping level, laser power, and irradiation time were investigated and optimized. The instrument developed in this work not only allows for the detection of fluorescent photons, but the sensitivity is high enough for the light to be dispersed and an emission spectrum recorded. The emission spectra of rhodamine-6G and 5-carboxyrhodamine-6G ions reported in this thesis represent the first spectra recorded from large molecular ions confined in a quadrupole ion trap. Finally, anti-Stokes fluorescence from rhodamine-6G was also detected.

Wavelet-based Gaussian-mixture hidden Markov model for the detection of multistage seizure dynamics: A proof-of-concept study

PubMed Central

2011-01-01

Background Epilepsy is a common neurological disorder characterized by recurrent electrophysiological activities, known as seizures. Without the appropriate detection strategies, these seizure episodes can dramatically affect the quality of life for those afflicted. The rationale of this study is to develop an unsupervised algorithm for the detection of seizure states so that it may be implemented along with potential intervention strategies. Methods Hidden Markov model (HMM) was developed to interpret the state transitions of the in vitro rat hippocampal slice local field potentials (LFPs) during seizure episodes. It can be used to estimate the probability of state transitions and the corresponding characteristics of each state. Wavelet features were clustered and used to differentiate the electrophysiological characteristics at each corresponding HMM states. Using unsupervised training method, the HMM and the clustering parameters were obtained simultaneously. The HMM states were then assigned to the electrophysiological data using expert guided technique. Minimum redundancy maximum relevance (mRMR) analysis and Akaike Information Criterion (AICc) were applied to reduce the effect of over-fitting. The sensitivity, specificity and optimality index of chronic seizure detection were compared for various HMM topologies. The ability of distinguishing early and late tonic firing patterns prior to chronic seizures were also evaluated. Results Significant improvement in state detection performance was achieved when additional wavelet coefficient rates of change information were used as features. The final HMM topology obtained using mRMR and AICc was able to detect non-ictal (interictal), early and late tonic firing, chronic seizures and postictal activities. A mean sensitivity of 95.7%, mean specificity of 98.9% and optimality index of 0.995 in the detection of chronic seizures was achieved. The detection of early and late tonic firing was validated with experimental intracellular electrical recordings of seizures. Conclusions The HMM implementation of a seizure dynamics detector is an improvement over existing approaches using visual detection and complexity measures. The subjectivity involved in partitioning the observed data prior to training can be eliminated. It can also decipher the probabilities of seizure state transitions using the magnitude and rate of change wavelet information of the LFPs. PMID:21504608

Humans Are Still the Critical Factor in Aviation Security.

PubMed

Krüger, Jenny Kathinka; Suchan, Boris

2015-10-01

In Germany, the German Federal Police assess the performance of aviation security screeners on a regular basis. These so-called "reality tests" are unannounced examinations which aim to investigate whether airport screeners can detect forbidden items in hand luggage or attached to the body. Recent alarming results of such inspections showed clearly that the overall detection rate is in need of improvement. To achieve this, it is important to identify specific factors that influence general screening performance. This especially includes basic cognitive functions like visual screening, alertness, and divided attention, which have come more and more into focus in current fundamental research projects. This brief commentary points out critical factors, contributes background conditions in aviation security screening, and shows possible approaches for enhancement and optimization. Finally, the human aspect is discussed as not only being the weakest factor in security screening, but also one of major importance.

All-Sky Census of Variable Stars from the ATLAS Survey

NASA Astrophysics Data System (ADS)

Heinze, Aren Nathaniel; Tonry, John; Denneau, Larry; Stalder, Brian

2018-01-01

The Asteroid Terrestrial-Impact Last Alert Survey uses two custom-built 0.5 meter telescopes to scan the whole accessible sky down to magnitude 19.5 every two nights, with a cadence optimized to detect small asteroids on their 'final plunge' toward impact with Earth. This cadence is also well suited to the detection of variable stars with a huge range of periods and properties, while ATLAS' use of two filters provides additional scientific depth. From the first two years of ATLAS data we have constructed a catalog of several hundred thousand variable objects with periods from one hour to hundreds of days. These include RR Lyrae stars, Cepheids, eclipsing binaries, spotted stars, ellipsoidal variables, Miras; and other objects both regular and irregular. We describe the construction of this catalog, including our multi-step confirmation process for genuine variables; some big-picture scientific conclusions; and prospects for more detailed results.

Perceptual learning through optimization of attentional weighting: human versus optimal Bayesian learner

NASA Technical Reports Server (NTRS)

Eckstein, Miguel P.; Abbey, Craig K.; Pham, Binh T.; Shimozaki, Steven S.

2004-01-01

Human performance in visual detection, discrimination, identification, and search tasks typically improves with practice. Psychophysical studies suggest that perceptual learning is mediated by an enhancement in the coding of the signal, and physiological studies suggest that it might be related to the plasticity in the weighting or selection of sensory units coding task relevant information (learning through attention optimization). We propose an experimental paradigm (optimal perceptual learning paradigm) to systematically study the dynamics of perceptual learning in humans by allowing comparisons to that of an optimal Bayesian algorithm and a number of suboptimal learning models. We measured improvement in human localization (eight-alternative forced-choice with feedback) performance of a target randomly sampled from four elongated Gaussian targets with different orientations and polarities and kept as a target for a block of four trials. The results suggest that the human perceptual learning can occur within a lapse of four trials (<1 min) but that human learning is slower and incomplete with respect to the optimal algorithm (23.3% reduction in human efficiency from the 1st-to-4th learning trials). The greatest improvement in human performance, occurring from the 1st-to-2nd learning trial, was also present in the optimal observer, and, thus reflects a property inherent to the visual task and not a property particular to the human perceptual learning mechanism. One notable source of human inefficiency is that, unlike the ideal observer, human learning relies more heavily on previous decisions than on the provided feedback, resulting in no human learning on trials following a previous incorrect localization decision. Finally, the proposed theory and paradigm provide a flexible framework for future studies to evaluate the optimality of human learning of other visual cues and/or sensory modalities.

Reactive Collision Avoidance Algorithm

NASA Technical Reports Server (NTRS)

Scharf, Daniel; Acikmese, Behcet; Ploen, Scott; Hadaegh, Fred

2010-01-01

The reactive collision avoidance (RCA) algorithm allows a spacecraft to find a fuel-optimal trajectory for avoiding an arbitrary number of colliding spacecraft in real time while accounting for acceleration limits. In addition to spacecraft, the technology can be used for vehicles that can accelerate in any direction, such as helicopters and submersibles. In contrast to existing, passive algorithms that simultaneously design trajectories for a cluster of vehicles working to achieve a common goal, RCA is implemented onboard spacecraft only when an imminent collision is detected, and then plans a collision avoidance maneuver for only that host vehicle, thus preventing a collision in an off-nominal situation for which passive algorithms cannot. An example scenario for such a situation might be when a spacecraft in the cluster is approaching another one, but enters safe mode and begins to drift. Functionally, the RCA detects colliding spacecraft, plans an evasion trajectory by solving the Evasion Trajectory Problem (ETP), and then recovers after the collision is avoided. A direct optimization approach was used to develop the algorithm so it can run in real time. In this innovation, a parameterized class of avoidance trajectories is specified, and then the optimal trajectory is found by searching over the parameters. The class of trajectories is selected as bang-off-bang as motivated by optimal control theory. That is, an avoiding spacecraft first applies full acceleration in a constant direction, then coasts, and finally applies full acceleration to stop. The parameter optimization problem can be solved offline and stored as a look-up table of values. Using a look-up table allows the algorithm to run in real time. Given a colliding spacecraft, the properties of the collision geometry serve as indices of the look-up table that gives the optimal trajectory. For multiple colliding spacecraft, the set of trajectories that avoid all spacecraft is rapidly searched on-line. The optimal avoidance trajectory is implemented as a receding-horizon model predictive control law. Therefore, at each time step, the optimal avoidance trajectory is found and the first time step of its acceleration is applied. At the next time step of the control computer, the problem is re-solved and the new first time step is again applied. This continual updating allows the RCA algorithm to adapt to a colliding spacecraft that is making erratic course changes.

Thermal and TEC anomalies detection using an intelligent hybrid system around the time of the Saravan, Iran, (Mw = 7.7) earthquake of 16 April 2013

NASA Astrophysics Data System (ADS)

Akhoondzadeh, M.

2014-02-01

A powerful earthquake of Mw = 7.7 struck the Saravan region (28.107° N, 62.053° E) in Iran on 16 April 2013. Up to now nomination of an automated anomaly detection method in a non linear time series of earthquake precursor has been an attractive and challenging task. Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) have revealed strong potentials in accurate time series prediction. This paper presents the first study of an integration of ANN and PSO method in the research of earthquake precursors to detect the unusual variations of the thermal and total electron content (TEC) seismo-ionospheric anomalies induced by the strong earthquake of Saravan. In this study, to overcome the stagnation in local minimum during the ANN training, PSO as an optimization method is used instead of traditional algorithms for training the ANN method. The proposed hybrid method detected a considerable number of anomalies 4 and 8 days preceding the earthquake. Since, in this case study, ionospheric TEC anomalies induced by seismic activity is confused with background fluctuations due to solar activity, a multi-resolution time series processing technique based on wavelet transform has been applied on TEC signal variations. In view of the fact that the accordance in the final results deduced from some robust methods is a convincing indication for the efficiency of the method, therefore the detected thermal and TEC anomalies using the ANN + PSO method were compared to the results with regard to the observed anomalies by implementing the mean, median, Wavelet, Kalman filter, Auto-Regressive Integrated Moving Average (ARIMA), Support Vector Machine (SVM) and Genetic Algorithm (GA) methods. The results indicate that the ANN + PSO method is quite promising and deserves serious attention as a new tool for thermal and TEC seismo anomalies detection.

Integrated Circuits for Rapid Sample Processing and Electrochemical Detection of Biomarkers

NASA Astrophysics Data System (ADS)

Besant, Justin

The trade-off between speed and sensitivity of detection is a fundamental challenge in the design of point-of-care diagnostics. As the relevant molecules in many diseases exist natively at extremely low levels, many gold-standard diagnostic tests are designed with high sensitivity at the expense of long incubations needed to amplify the target analytes. The central aim of this thesis is to design new strategies to detect biologically relevant analytes with both high speed and sensitivity. The response time of a biosensor is limited by the ability of the target analyte to accumulate to detectable levels at the sensor surface. We overcome this limitation by designing a range of integrated devices to optimize the flux of the analyte to the sensor by increasing the effective analyte concentration, shortening the required diffusion distance, and confining the analyte in close proximity to the sensor. We couple these devices with novel ultrasensitive electrochemical transduction strategies to convert rare analytes into a detectable signal. We showcase the clinical utility of these approaches with several applications including cancer diagnosis, bacterial identification, and antibiotic susceptibility profiling. We design and optimize a device to isolate rare cancer cells from the bloodstream with near 100% efficiency and 10 000-fold specificity. We analyse pathogen specific nucleic acids by lysing bacteria in close proximity to an electrochemical sensor and find that this approach has 10-fold higher sensitivity than standard lysis in bulk solution. We design an electronic chip to readout the antibiotic susceptibility profile with an hour-long incubation by concentrating bacteria into nanoliter chambers with integrated electrodes. Finally, we report a strategy for ultrasensitive visual readout of nucleic acids as low as 100 fM within 10 minutes using an amplification cascade. The strategies presented could guide the development of fast, sensitive and low-cost diagnostics for diseases not previously detectable at the point-of-care.

Automated detection of focal cortical dysplasia type II with surface-based magnetic resonance imaging postprocessing and machine learning.

PubMed

Jin, Bo; Krishnan, Balu; Adler, Sophie; Wagstyl, Konrad; Hu, Wenhan; Jones, Stephen; Najm, Imad; Alexopoulos, Andreas; Zhang, Kai; Zhang, Jianguo; Ding, Meiping; Wang, Shuang; Wang, Zhong Irene

2018-05-01

Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In this study, we utilized surface-based MRI morphometry and machine learning for automated lesion detection in a mixed cohort of patients with FCD type II from 3 different epilepsy centers. Sixty-one patients with pharmacoresistant epilepsy and histologically proven FCD type II were included in the study. The patients had been evaluated at 3 different epilepsy centers using 3 different MRI scanners. T1-volumetric sequence was used for postprocessing. A normal database was constructed with 120 healthy controls. We also included 35 healthy test controls and 15 disease test controls with histologically confirmed hippocampal sclerosis to assess specificity. Features were calculated and incorporated into a nonlinear neural network classifier, which was trained to identify lesional cluster. We optimized the threshold of the output probability map from the classifier by performing receiver operating characteristic (ROC) analyses. Success of detection was defined by overlap between the final cluster and the manual labeling. Performance was evaluated using k-fold cross-validation. The threshold of 0.9 showed optimal sensitivity of 73.7% and specificity of 90.0%. The area under the curve for the ROC analysis was 0.75, which suggests a discriminative classifier. Sensitivity and specificity were not significantly different for patients from different centers, suggesting robustness of performance. Correct detection rate was significantly lower in patients with initially normal MRI than patients with unequivocally positive MRI. Subgroup analysis showed the size of the training group and normal control database impacted classifier performance. Automated surface-based MRI morphometry equipped with machine learning showed robust performance across cohorts from different centers and scanners. The proposed method may be a valuable tool to improve FCD detection in presurgical evaluation for patients with pharmacoresistant epilepsy. Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.

Quantitation of zolpidem in biological fluids by electro-driven microextraction combined with HPLC-UV analysis.

PubMed

Yaripour, Saeid; Mohammadi, Ali; Esfanjani, Isa; Walker, Roderick B; Nojavan, Saeed

2018-01-01

In this study, for the first time, an electro-driven microextraction method named electromembrane extraction combined with a simple high performance liquid chromatography and ultraviolet detection was developed and validated for the quantitation of zolpidem in biological samples. Parameters influencing electromembrane extraction were evaluated and optimized. The membrane consisted of 2-ethylhexanol immobilized in the pores of a hollow fiber. As a driving force, a 150 V electric field was applied to facilitate the analyte migration from the sample matrix to an acceptor solution through a supported liquid membrane. The pHs of donor and acceptor solutions were optimized to 6.0 and 2.0, respectively. The enrichment factor was obtained >75 within 15 minutes. The effect of carbon nanotubes (as solid nano-sorbents) on the membrane performance and EME efficiency was evaluated. The method was linear over the range of 10-1000 ng/mL for zolpidem (R 2 >0.9991) with repeatability ( %RSD) between 0.3 % and 7.3 % ( n = 3). The limits of detection and quantitation were 3 and 10 ng/mL, respectively. The sensitivity of HPLC-UV for the determination of zolpidem was enhanced by electromembrane extraction. Finally, the method was employed for the quantitation of zolpidem in biological samples with relative recoveries in the range of 60-79 %.

Quantitation of zolpidem in biological fluids by electro-driven microextraction combined with HPLC-UV analysis

PubMed Central

Yaripour, Saeid; Mohammadi, Ali; Esfanjani, Isa; Walker, Roderick B.; Nojavan, Saeed

2018-01-01

In this study, for the first time, an electro-driven microextraction method named electromembrane extraction combined with a simple high performance liquid chromatography and ultraviolet detection was developed and validated for the quantitation of zolpidem in biological samples. Parameters influencing electromembrane extraction were evaluated and optimized. The membrane consisted of 2-ethylhexanol immobilized in the pores of a hollow fiber. As a driving force, a 150 V electric field was applied to facilitate the analyte migration from the sample matrix to an acceptor solution through a supported liquid membrane. The pHs of donor and acceptor solutions were optimized to 6.0 and 2.0, respectively. The enrichment factor was obtained >75 within 15 minutes. The effect of carbon nanotubes (as solid nano-sorbents) on the membrane performance and EME efficiency was evaluated. The method was linear over the range of 10-1000 ng/mL for zolpidem (R2 >0.9991) with repeatability ( %RSD) between 0.3 % and 7.3 % (n = 3). The limits of detection and quantitation were 3 and 10 ng/mL, respectively. The sensitivity of HPLC-UV for the determination of zolpidem was enhanced by electromembrane extraction. Finally, the method was employed for the quantitation of zolpidem in biological samples with relative recoveries in the range of 60-79 %. PMID:29805344

Fabrication and characterization of a chemically oxidized-nanostructured porous silicon based biosensor implementing orienting protein A.

PubMed

Naveas, Nelson; Hernandez-Montelongo, Jacobo; Pulido, Ruth; Torres-Costa, Vicente; Villanueva-Guerrero, Raúl; Predestinación García Ruiz, Josefa; Manso-Silván, Miguel

2014-03-01

Nanostructured porous silicon (PSi) elicits as a very attractive material for future biosensing systems due to its high surface area, biocompatibility and well-established fabrication methods. In order to engineer its performance as a biosensor transducer platform, the density of immunoglobulins properly immobilized and oriented onto the surface needs to be optimized. In this work we fabricated and characterized a novel biosensing system focusing on the improvement of the biofunctionalization cascade. The system consists on a chemically oxidized PSi platform derivatized with 3-aminopropyltriethoxysilane (APTS) that is coupled to Staphylococcus protein A (SpA). The chemical oxidation has previously demonstrated to enhance the biofunctionalization process and here "by implementing SpA" a molecularly oriented immunosensor is achieved. The biosensor system is characterized in terms of its chemical composition, wettability and optical reflectance. Finally, this system is successfully exploited to develop a biosensor for detecting asymmetric dimethylarginine (ADMA), an endogenous molecule involved in cardiovascular diseases. Therefore, this work is relevant from the point of view of design and optimization of the biomolecular immobilization cascade on PSi surfaces with the added value of contribution to the development of new assays for detecting ADMA with a view on prevention of cardiovascular diseases. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparison of specificity and sensitivity of immunochemical and molecular techniques for determination of Clavibacter michiganensis subsp. michiganensis.

PubMed

Kokosková, B; Mráz, I; Fousek, J

2010-05-01

Detection of Clavibacter michiganensis subsp. michiganensis (Cmm), causing bacterial canker of tomato, was verified using PTA-ELISA and IFAS with PAbs of Neogen Europe Ltd. (UK), and with published and also laboratory-generated PCR primers from the Cmm tomatinase gene. The specificity of this technique was determined with 15 plant-pathogenic and 4 common, saprophytic bacteria. With IFAS, crossreactions were found for Pantoea dispersa, P. agglomerans and Rahnella aquatilis, and with PTA-ELISA for Curtobacterium flaccumfaciens, Pectobacterium atrosepticum and Dickeya sp. Cross-reactions with subspecies other than michiganensis were also found using both methods. Molecular methods were optimized by verification of annealing temperatures and times for both primers. Conditions were finally adjusted to 30 s at 65 degrees C for Dreier's and 10 s at 69 degrees C for our primer set. After this optimization, both primer pairs produced positive reaction only with Cmm. By means of PTA-ELISA and IFAS, Cmm strains were detected at a concentration up to 10(5) CFU/mL and 10(3) CFU/mL, respectively. The PCR test with bacterial cell suspensions reached a sensitivity of 10(3) CFU/mL with our designed primers and 104 CFU/mL with Dreier's primer pair.

Microwave-assisted extraction at atmospheric pressure coupled to different clean-up methods for the determination of organophosphorus pesticides in olive and avocado oil.

PubMed

Fuentes, Edwar; Báez, María E; Díaz, Juan

2009-12-18

An effective extraction method was devised for the determination of organophosphorus pesticides (OPPs) in olive and avocado oil samples, using atmospheric pressure microwave-assisted liquid-liquid extraction (APMAE) and solid-phase extraction or low-temperature precipitation as clean-up step. A simple glass system equipped with an air-cooled condenser was designed as an extraction vessel. The pesticides were partitioned between acetonitrile and oil solution in hexane. Analytical determinations were carried out by gas chromatography-flame photometric detection and gas chromatography-tandem mass spectrometry, using a triple quadrupole mass analyzer, for confirmation purposes. Several factors influencing the extraction efficiency were investigated and optimized through fractional factorial design and Doehlert design. Under optimal conditions the recovery of pesticides from oil at 0.025 microg g(-1) ranged from 71% to 103%, except for fenthion in avocado oil, with RSDs < or = 13% (n=5). The LOQ for the entire method ranged from 0.004 to 0.015 microg g(-1). Finally, the proposed method was successfully applied to the extraction and determination of the selected pesticides in 20 commercially packed extra virgin olive oils and four commercially packed avocado oils produced in Chile. Detectable residues of different OPPs were observed in 85% of samples.

Thermal analysis in the rat glioma model during directly multipoint injection hyperthermia incorporating magnetic nanoparticles.

PubMed

Liu, Lianke; Ni, Fang; Zhang, Jianchao; Wang, Chunyu; Lu, Xiang; Guo, Zhirui; Yao, Shaowei; Shu, Yongqian; Xu, Ruizhi

2011-12-01

Hyperthermia incorporating magnetic nanoparticles (MNPs) is a hopeful therapy to cancers and steps into clinical tests at present. However, the clinical plan of MNPs deposition in tumors, especially applied for directly multipoint injection hyperthermia (DMIH), and the information of temperature rise in tumors by DMIH is lack of studied. In this paper, we mainly discussed thermal distributions induced by MNPs in the rat brain tumors during DMIH. Due to limited experimental measurement for detecting thermal dose of tumors, and in order to acquire optimized results of temperature distributions clinically needed, we designed the thermal model in which three types of MNPs injection for hyperthermia treatments were simulated. The simulated results showed that MNPs injection plan played an important role in determining thermal distribution, as well as the overall dose of MNPs injected. We found that as injected points enhanced, the difference of temperature in the whole tumor volume decreased. Moreover, from temperature detecting data by Fiber Optic Temperature Sensors (FOTSs) in glioma bearing rats during MNPs hyperthermia, we found the temperature errors by FOTSs reduced as the number of points injected enhanced. Finally, the results showed that the simulations are preferable and the optimized plans of the numbers and spatial positions of MNPs points injected are essential during direct injection hyperthermia.

10th Annual Systems Engineering Conference: Volume 2 Wednesday

DTIC Science & Technology

2007-10-25

intelligently optimize resource performance. Self - Healing Detect hardware/software failures and reconfigure to permit continued operations. Self ...Types Wake Ice WEAPON/PLATFORM ACOUSTICS Self -Noise Radiated Noise Beam Forming Pulse Types Submarines, surface ships, and platform sensors P r o p P r o...Computing Self -Protecting Detect internal/external attacks and protect it’s resources from exploitation. Self -Optimizing Detect sub-optimal behaviors and

Multiple Detector Optimization for Hidden Radiation Source Detection

DTIC Science & Technology

2015-03-26

important in achieving operationally useful methods for optimizing detector emplacement, the 2-D attenuation model approach promises to speed up the...process of hidden source detection significantly. The model focused on detection of the full energy peak of a radiation source. Methods to optimize... radioisotope identification is possible without using a computationally intensive stochastic model such as the Monte Carlo n-Particle (MCNP) code

Organizational Decision Making

DTIC Science & Technology

1975-08-01

the lack of formal techniques typically used by large organizations, digress on the advantages of formal over informal... optimization ; for example one might do a number of optimization calculations, each time using a different measure of effectiveness as the optimized ...final decision. The next level of computer application involves the use of computerized optimization techniques. Optimization

Flocking in Distributed Control and Optimization

DTIC Science & Technology

2015-06-01

AFRL-AFOSR-VA-TR-2015-0309 Flocking in Distributed Control and Optimization Alfredo Garcia UNIVERSITY OF VIRGINIA Final Report 06/01/2015... control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      30-09-2015 2. REPORT TYPE Final Performance 3...DATES COVERED (From - To) 01-04-2012 to 31-03-2015 4. TITLE AND SUBTITLE Flocking in Distributed Control and Optimization 5a.  CONTRACT NUMBER 5b

Development of a HS-SPME-GC/MS protocol assisted by chemometric tools to study herbivore-induced volatiles in Myrcia splendens.

PubMed

Souza Silva, Érica A; Saboia, Giovanni; Jorge, Nina C; Hoffmann, Camila; Dos Santos Isaias, Rosy Mary; Soares, Geraldo L G; Zini, Claudia A

2017-12-01

A headspace solid phase microextraction (HS-SPME) method combined with gas chromatography-mass spectrometry (GC/MS) was developed and optimized for extraction and analysis of volatile organic compounds (VOC) of leaves and galls of Myrcia splendens. Through a process of optimization of main factors affecting HS-SPME efficiency, the coating divivnilbenzene-carboxen-polydimethylsiloxane (DVB/Car/PDMS) was chosen as the optimum extraction phase, not only in terms of extraction efficiency, but also for its broader analyte coverage. Optimum extraction temperature was 30°C, while an extraction time of 15min provided the best compromise between extraction efficiencies of lower and higher molecular weight compounds. The optimized protocol was demonstrated to be capable of sampling plant material with high reproducibility, considering that most classes of analytes met the 20% RSD FDA criterion. The optimized method was employed for the analysis of three classes of M. splendens samples, generating a final list of 65 tentatively identified VOC, including alcohols, aldehydes, esters, ketones, phenol derivatives, as well as mono and sesquiterpenes. Significant differences were evident amongst the volatile profiles obtained from non-galled leaves (NGL) and leaf-folding galls (LFG) of M. splendens. Several differences pertaining to amounts of alcohols and aldehydes were detected between samples, particularly regarding quantities of green leaf volatiles (GLV). Alcohols represented about 14% of compounds detected in gall samples, whereas in non-galled samples, alcohol content was below 5%. Phenolic derived compounds were virtually absent in reference samples, while in non-galled leaves and galls their content ranged around 0.2% and 0.4%, respectively. Likewise, methyl salicylate, a well-known signal of plant distress, amounted for 1.2% of the sample content of galls, whereas it was only present in trace levels in reference samples. Chemometric analysis based on Heatmap associated with Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) provided a suitable tool to differentiate VOC profiles in vegetal material, and could open new perspectives and opportunities in agricultural and ecological studies for the detection and identification of herbivore-induced plant VOC emissions. Copyright © 2017 Elsevier B.V. All rights reserved.

Ionic liquid-based single-drop microextraction followed by liquid chromatography-ultraviolet spectrophotometry detection to determine typical UV filters in surface water samples.

PubMed

Vidal, Lorena; Chisvert, Alberto; Canals, Antonio; Salvador, Amparo

2010-04-15

A user-friendly and inexpensive ionic liquid-based single-drop microextraction (IL-SDME) procedure has been developed to preconcentrate trace amounts of six typical UV filters extensively used in cosmetic products (i.e., 2-hydroxy-4-methoxybenzophenone, isoamyl 4-methoxycinnamate, 3-(4'-methylbenzylidene)camphor, 2-ethylhexyl 2-cyano-3,3-diphenylacrylate, 2-ethylhexyl 4-dimethylaminobenzoate and 2-ethylhexyl 4-methoxycinnamate) from surface water samples prior to analysis by liquid chromatography-ultraviolet spectrophotometry detection (LC-UV). A two-stage multivariate optimization approach was developed by means of a Plackett-Burman design for screening and selecting the significant variables involved in the SDME procedure, which were later optimized by means of a circumscribed central composite design. The studied variables were drop volume, sample volume, agitation speed, ionic strength, extraction time and ethanol quantity. Owing to particularities, ionic liquid type and pH of the sample were optimized separately. Under optimized experimental conditions (i.e., 10 microL of 1-hexyl-3-methylimidazolium hexafluorophosphate, 20 mL of sample containing 1% (v/v) ethanol and NaCl free adjusted to pH 2, 37 min extraction time and 1300 rpm agitation speed) enrichment factors up to ca. 100-fold were obtained depending on the target analyte. The method gave good levels of repeatability with relative standard deviations varying between 2.8 and 8.8% (n=6). Limits of detection were found in the low microg L(-1) range, varying between 0.06 and 3.0 microg L(-1) depending on the target analyte. Recovery studies from different types of surface water samples collected during the winter period, which were analysed and confirmed free of all target analytes, ranged between 92 and 115%, showing that the matrix had a negligible effect upon extraction. Finally, the proposed method was applied to the analysis of different water samples (taken from two beaches, two swimming pools and a river) collected during the summer period. (c) 2009 Elsevier B.V. All rights reserved.

Two neural network algorithms for designing optimal terminal controllers with open final time

NASA Technical Reports Server (NTRS)

Plumer, Edward S.

1992-01-01

Multilayer neural networks, trained by the backpropagation through time algorithm (BPTT), have been used successfully as state-feedback controllers for nonlinear terminal control problems. Current BPTT techniques, however, are not able to deal systematically with open final-time situations such as minimum-time problems. Two approaches which extend BPTT to open final-time problems are presented. In the first, a neural network learns a mapping from initial-state to time-to-go. In the second, the optimal number of steps for each trial run is found using a line-search. Both methods are derived using Lagrange multiplier techniques. This theoretical framework is used to demonstrate that the derived algorithms are direct extensions of forward/backward sweep methods used in N-stage optimal control. The two algorithms are tested on a Zermelo problem and the resulting trajectories compare favorably to optimal control results.

Estimation and detection information trade-off for x-ray system optimization

NASA Astrophysics Data System (ADS)

Cushing, Johnathan B.; Clarkson, Eric W.; Mandava, Sagar; Bilgin, Ali

2016-05-01

X-ray Computed Tomography (CT) systems perform complex imaging tasks to detect and estimate system parameters, such as a baggage imaging system performing threat detection and generating reconstructions. This leads to a desire to optimize both the detection and estimation performance of a system, but most metrics only focus on one of these aspects. When making design choices there is a need for a concise metric which considers both detection and estimation information parameters, and then provides the user with the collection of possible optimal outcomes. In this paper a graphical analysis of Estimation and Detection Information Trade-off (EDIT) will be explored. EDIT produces curves which allow for a decision to be made for system optimization based on design constraints and costs associated with estimation and detection. EDIT analyzes the system in the estimation information and detection information space where the user is free to pick their own method of calculating these measures. The user of EDIT can choose any desired figure of merit for detection information and estimation information then the EDIT curves will provide the collection of optimal outcomes. The paper will first look at two methods of creating EDIT curves. These curves can be calculated using a wide variety of systems and finding the optimal system by maximizing a figure of merit. EDIT could also be found as an upper bound of the information from a collection of system. These two methods allow for the user to choose a method of calculation which best fits the constraints of their actual system.

Cortical membrane potential signature of optimal states for sensory signal detection

PubMed Central

McGinley, Matthew J.; David, Stephen V.; McCormick, David A.

2015-01-01

The neural correlates of optimal states for signal detection task performance are largely unknown. One hypothesis holds that optimal states exhibit tonically depolarized cortical neurons with enhanced spiking activity, such as occur during movement. We recorded membrane potentials of auditory cortical neurons in mice trained on a challenging tone-in-noise detection task while assessing arousal with simultaneous pupillometry and hippocampal recordings. Arousal measures accurately predicted multiple modes of membrane potential activity, including: rhythmic slow oscillations at low arousal, stable hyperpolarization at intermediate arousal, and depolarization during phasic or tonic periods of hyper-arousal. Walking always occurred during hyper-arousal. Optimal signal detection behavior and sound-evoked responses, at both sub-threshold and spiking levels, occurred at intermediate arousal when pre-decision membrane potentials were stably hyperpolarized. These results reveal a cortical physiological signature of the classically-observed inverted-U relationship between task performance and arousal, and that optimal detection exhibits enhanced sensory-evoked responses and reduced background synaptic activity. PMID:26074005

Technology platform development for targeted plasma metabolites in human heart failure.

PubMed

Chan, Cy X'avia; Khan, Anjum A; Choi, Jh Howard; Ng, Cm Dominic; Cadeiras, Martin; Deng, Mario; Ping, Peipei

2013-01-01

Heart failure is a multifactorial disease associated with staggeringly high morbidity and motility. Recently, alterations of multiple metabolites have been implicated in heart failure; however, the lack of an effective technology platform to assess these metabolites has limited our understanding on how they contribute to this disease phenotype. We have successfully developed a new workflow combining specific sample preparation with tandem mass spectrometry that enables us to extract most of the targeted metabolites. 19 metabolites were chosen ascribing to their biological relevance to heart failure, including extracellular matrix remodeling, inflammation, insulin resistance, renal dysfunction, and cardioprotection against ischemic injury. In this report, we systematically engineered, optimized and refined a protocol applicable to human plasma samples; this study contributes to the methodology development with respect to deproteinization, incubation, reconstitution, and detection with mass spectrometry. The deproteinization step was optimized with 20% methanol/ethanol at a plasma:solvent ratio of 1:3. Subsequently, an incubation step was implemented which remarkably enhanced the metabolite signals and the number of metabolite peaks detected by mass spectrometry in both positive and negative modes. With respect to the step of reconstitution, 0.1% formic acid was designated as the reconstitution solvent vs. 6.5 mM ammonium bicarbonate, based on the comparable number of metabolite peaks detected in both solvents, and yet the signal detected in the former was higher. By adapting this finalized protocol, we were able to retrieve 13 out of 19 targeted metabolites from human plasma. We have successfully devised a simple albeit effective workflow for the targeted plasma metabolites relevant to human heart failure. This will be employed in tandem with high throughput liquid chromatography mass spectrometry platform to validate and characterize these potential metabolic biomarkers for diagnostic and therapeutic development of heart failure patients.

Optimization of proximity ligation assay (PLA) for detection of protein interactions and fusion proteins in non-adherent cells: application to pre-B lymphocytes.

PubMed

Debaize, Lydie; Jakobczyk, Hélène; Rio, Anne-Gaëlle; Gandemer, Virginie; Troadec, Marie-Bérengère

2017-01-01

Genetic abnormalities, including chromosomal translocations, are described for many hematological malignancies. From the clinical perspective, detection of chromosomal abnormalities is relevant not only for diagnostic and treatment purposes but also for prognostic risk assessment. From the translational research perspective, the identification of fusion proteins and protein interactions has allowed crucial breakthroughs in understanding the pathogenesis of malignancies and consequently major achievements in targeted therapy. We describe the optimization of the Proximity Ligation Assay (PLA) to ascertain the presence of fusion proteins, and protein interactions in non-adherent pre-B cells. PLA is an innovative method of protein-protein colocalization detection by molecular biology that combines the advantages of microscopy with the advantages of molecular biology precision, enabling detection of protein proximity theoretically ranging from 0 to 40 nm. We propose an optimized PLA procedure. We overcome the issue of maintaining non-adherent hematological cells by traditional cytocentrifugation and optimized buffers, by changing incubation times, and modifying washing steps. Further, we provide convincing negative and positive controls, and demonstrate that optimized PLA procedure is sensitive to total protein level. The optimized PLA procedure allows the detection of fusion proteins and protein interactions on non-adherent cells. The optimized PLA procedure described here can be readily applied to various non-adherent hematological cells, from cell lines to patients' cells. The optimized PLA protocol enables detection of fusion proteins and their subcellular expression, and protein interactions in non-adherent cells. Therefore, the optimized PLA protocol provides a new tool that can be adopted in a wide range of applications in the biological field.

Automated Image Intelligence Adaptive Sensor Management System for High Altitude Long Endurance UAVs in a Dynamic and Anti-Access Area Denial Environment

NASA Astrophysics Data System (ADS)

Kim, Gi Young

The problem we investigate deals with an Image Intelligence (IMINT) sensor allocation schedule for High Altitude Long Endurance UAVs in a dynamic and Anti-Access Area Denial (A2AD) environment. The objective is to maximize the Situational Awareness (SA) of decision makers. The value of SA can be improved in two different ways. First, if a sensor allocated to an Areas of Interest (AOI) detects target activity, then the SA value will be increased. Second, the SA value increases if an AOI is monitored for a certain period of time, regardless of target detections. These values are functions of the sensor allocation time, sensor type and mode. Relatively few studies in the archival literature have been devoted to an analytic, detailed explanation of the target detection process, and AOI monitoring value dynamics. These two values are the fundamental criteria used to choose the most judicious sensor allocation schedule. This research presents mathematical expressions for target detection processes, and shows the monitoring value dynamics. Furthermore, the dynamics of target detection is the result of combined processes between belligerent behavior (target activity) and friendly behavior (sensor allocation). We investigate these combined processes and derive mathematical expressions for simplified cases. These closed form mathematical models can be used for Measures of Effectiveness (MOEs), i.e., target activity detection to evaluate sensor allocation schedules. We also verify these models with discrete event simulations which can also be used to describe more complex systems. We introduce several methodologies to achieve a judicious sensor allocation schedule focusing on the AOI monitoring value. The first methodology is a discrete time integer programming model which provides an optimal solution but is impractical for real world scenarios due to its computation time. Thus, it is necessary to trade off the quality of solution with computation time. The Myopic Greedy Procedure (MGP) is a heuristic which chooses the largest immediate unit time return at each decision epoch. This reduces computation time significantly, but the quality of the solution may be only 95% of optimal (for small size problems). Another alternative is a multi-start random constructive Hybrid Myopic Greedy Procedure (H-MGP), which incorporates stochastic variation in choosing an action at each stage, and repeats it a predetermined number of times (roughly 99.3% of optimal with 1000 repetitions). Finally, the One Stage Look Ahead (OSLA) procedure considers all the 'top choices' at each stage for a temporary time horizon and chooses the best action (roughly 98.8% of optimal with no repetition). Using OSLA procedure, we can have ameliorated solutions within a reasonable computation time. Other important issues discussed in this research are methodologies for the development of input parameters for real world applications.

Parallel Molecular Distributed Detection With Brownian Motion.

PubMed

Rogers, Uri; Koh, Min-Sung

2016-12-01

This paper explores the in vivo distributed detection of an undesired biological agent's (BAs) biomarkers by a group of biological sized nanomachines in an aqueous medium under drift. The term distributed, indicates that the system information relative to the BAs presence is dispersed across the collection of nanomachines, where each nanomachine possesses limited communication, computation, and movement capabilities. Using Brownian motion with drift, a probabilistic detection and optimal data fusion framework, coined molecular distributed detection, will be introduced that combines theory from both molecular communication and distributed detection. Using the optimal data fusion framework as a guide, simulation indicates that a sub-optimal fusion method exists, allowing for a significant reduction in implementation complexity while retaining BA detection accuracy.

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

NASA Astrophysics Data System (ADS)

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

2012-08-01

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

Learning optimal embedded cascades.

PubMed

Saberian, Mohammad Javad; Vasconcelos, Nuno

2012-10-01

The problem of automatic and optimal design of embedded object detector cascades is considered. Two main challenges are identified: optimization of the cascade configuration and optimization of individual cascade stages, so as to achieve the best tradeoff between classification accuracy and speed, under a detection rate constraint. Two novel boosting algorithms are proposed to address these problems. The first, RCBoost, formulates boosting as a constrained optimization problem which is solved with a barrier penalty method. The constraint is the target detection rate, which is met at all iterations of the boosting process. This enables the design of embedded cascades of known configuration without extensive cross validation or heuristics. The second, ECBoost, searches over cascade configurations to achieve the optimal tradeoff between classification risk and speed. The two algorithms are combined into an overall boosting procedure, RCECBoost, which optimizes both the cascade configuration and its stages under a detection rate constraint, in a fully automated manner. Extensive experiments in face, car, pedestrian, and panda detection show that the resulting detectors achieve an accuracy versus speed tradeoff superior to those of previous methods.

Analytical solutions to optimal underactuated spacecraft formation reconfiguration

NASA Astrophysics Data System (ADS)

Huang, Xu; Yan, Ye; Zhou, Yang

2015-11-01

Underactuated systems can generally be defined as systems with fewer number of control inputs than that of the degrees of freedom to be controlled. In this paper, analytical solutions to optimal underactuated spacecraft formation reconfiguration without either the radial or the in-track control are derived. By using a linear dynamical model of underactuated spacecraft formation in circular orbits, controllability analysis is conducted for either underactuated case. Indirect optimization methods based on the minimum principle are then introduced to generate analytical solutions to optimal open-loop underactuated reconfiguration problems. Both fixed and free final conditions constraints are considered for either underactuated case and comparisons between these two final conditions indicate that the optimal control strategies with free final conditions require less control efforts than those with the fixed ones. Meanwhile, closed-loop adaptive sliding mode controllers for both underactuated cases are designed to guarantee optimal trajectory tracking in the presence of unmatched external perturbations, linearization errors, and system uncertainties. The adaptation laws are designed via a Lyapunov-based method to ensure the overall stability of the closed-loop system. The explicit expressions of the terminal convergent regions of each system states have also been obtained. Numerical simulations demonstrate the validity and feasibility of the proposed open-loop and closed-loop control schemes for optimal underactuated spacecraft formation reconfiguration in circular orbits.

Liquid paraffin as new dilution medium for the analysis of high boiling point residual solvents with static headspace-gas chromatography.

PubMed

D'Autry, Ward; Zheng, Chao; Bugalama, John; Wolfs, Kris; Hoogmartens, Jos; Adams, Erwin; Wang, Bochu; Van Schepdael, Ann

2011-07-15

Residual solvents are volatile organic compounds which can be present in pharmaceutical substances. A generic static headspace-gas chromatography analysis method for the identification and control of residual solvents is described in the European Pharmacopoeia. Although this method is proved to be suitable for the majority of samples and residual solvents, the method may lack sensitivity for high boiling point residual solvents such as N,N-dimethylformamide, N,N-dimethylacetamide, dimethyl sulfoxide and benzyl alcohol. In this study, liquid paraffin was investigated as new dilution medium for the analysis of these residual solvents. The headspace-gas chromatography method was developed and optimized taking the official Pharmacopoeia method as a starting point. The optimized method was validated according to ICH criteria. It was found that the detection limits were below 1μg/vial for each compound, indicating a drastically increased sensitivity compared to the Pharmacopoeia method, which failed to detect the compounds at their respective limit concentrations. Linearity was evaluated based on the R(2) values, which were above 0.997 for all compounds, and inspection of residual plots. Instrument and method precision were examined by calculating the relative standard deviations (RSD) of repeated analyses within the linearity and accuracy experiments, respectively. It was found that all RSD values were below 10%. Accuracy was checked by a recovery experiment at three different levels. Mean recovery values were all in the range 95-105%. Finally, the optimized method was applied to residual DMSO analysis in four different Kollicoat(®) sample batches. Copyright © 2011 Elsevier B.V. All rights reserved.

Aminoquinolines as fluorescent labels for hydrophilic interaction liquid chromatography of oligosaccharides.

PubMed

Struwe, Weston B; Rudd, Pauline M

2012-08-01

In this study, we investigated the potential of four different aminoquinoline (AQ) compounds as fluorescent labels for glycan analysis using hydrophilic interaction liquid chromatography (HILIC) and fluorescence detection (FLD). We confirmed the optimal excitation and emission wavelengths of 3-AQ and 6-AQ conjugated to glycan standards using three-dimensional fluorescent spectral scanning. The optimal excitation and emission wavelengths for 6-AQ were confirmed at λ(ex)=355 nm and λ(em)=440 nm. We concluded that the optimal wavelengths for 3-AQ were λ(ex)=355 nm and λ(em)=420 nm, which differed considerably from the wavelengths applied in previous reports. HILIC-FLD chromatograms using experimentally determined wavelengths were similar to 2-aminobenzamide controls, but the peak capacity and resolution differed significantly when published 3-AQ λ(ex/em) values were applied. Furthermore, we found that 5-AQ and 8-AQ labeled maltohexaose did not display any fluorescent properties when used as a carbohydrate tag for HPLC analysis. Finally, we applied experimentally determined wavelengths to 3-AQ labeled N-glycans released from human IgG to illustrate changes in retention time as well as to demonstrate that AQ labeling is applicable to complex sample analysis via exoglycosidase sequencing.

Code Optimization Techniques

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

MAGEE,GLEN I.

Computers transfer data in a number of different ways. Whether through a serial port, a parallel port, over a modem, over an ethernet cable, or internally from a hard disk to memory, some data will be lost. To compensate for that loss, numerous error detection and correction algorithms have been developed. One of the most common error correction codes is the Reed-Solomon code, which is a special subset of BCH (Bose-Chaudhuri-Hocquenghem) linear cyclic block codes. In the AURA project, an unmanned aircraft sends the data it collects back to earth so it can be analyzed during flight and possible flightmore » modifications made. To counter possible data corruption during transmission, the data is encoded using a multi-block Reed-Solomon implementation with a possibly shortened final block. In order to maximize the amount of data transmitted, it was necessary to reduce the computation time of a Reed-Solomon encoding to three percent of the processor's time. To achieve such a reduction, many code optimization techniques were employed. This paper outlines the steps taken to reduce the processing time of a Reed-Solomon encoding and the insight into modern optimization techniques gained from the experience.« less

Simultaneous microemulsion liquid chromatographic analysis of fat-soluble vitamins in pharmaceutical formulations: optimization using genetic algorithm.

PubMed

Momenbeik, Fariborz; Roosta, Mostafa; Nikoukar, Ali Akbar

2010-06-11

An environmentally benign and simple method has been proposed for separation and determination of fat-soluble vitamins using isocratic microemulsion liquid chromatography. Optimization of parameters affecting the separation selectivity and efficiency including surfactant concentration, percent of cosurfactant (1-butanol), and percent of organic oily solvent (diethyl ether), temperature and pH were performed simultaneously using genetic algorithm method. A new software package, MLR-GA, was developed for this purpose. The results indicated that 73.6mM sodium dodecyl sulfate, 13.64% (v/v) 1-butanol, 0.48% (v/v) diethyl ether, column temperature of 32.5 degrees C and 0.02M phosphate buffer of pH 6.99 are the best conditions for separation of fat-soluble vitamins. At the optimized conditions, the calibration plots for the vitamins were obtained and detection limits (1.06-3.69microgmL(-1)), accuracy (recoveries>94.3), precision (RSD<3.96) and linearity (0.01-10mgmL(-1)) were estimated. Finally, the amount of vitamins in multivitamin syrup and a sample of fish oil capsule were determined. The results showed a good agreement with those reported by manufactures. Copyright 2010 Elsevier B.V. All rights reserved.

Optimization of single photon detection model based on GM-APD

NASA Astrophysics Data System (ADS)

Chen, Yu; Yang, Yi; Hao, Peiyu

2017-11-01

One hundred kilometers high precision laser ranging hopes the detector has very strong detection ability for very weak light. At present, Geiger-Mode of Avalanche Photodiode has more use. It has high sensitivity and high photoelectric conversion efficiency. Selecting and designing the detector parameters according to the system index is of great importance to the improvement of photon detection efficiency. Design optimization requires a good model. In this paper, we research the existing Poisson distribution model, and consider the important detector parameters of dark count rate, dead time, quantum efficiency and so on. We improve the optimization of detection model, select the appropriate parameters to achieve optimal photon detection efficiency. The simulation is carried out by using Matlab and compared with the actual test results. The rationality of the model is verified. It has certain reference value in engineering applications.

Constant-Envelope Waveform Design for Optimal Target-Detection and Autocorrelation Performances

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

Sen, Satyabrata

2013-01-01

We propose an algorithm to directly synthesize in time-domain a constant-envelope transmit waveform that achieves the optimal performance in detecting an extended target in the presence of signal-dependent interference. This approach is in contrast to the traditional indirect methods that synthesize the transmit signal following the computation of the optimal energy spectral density. Additionally, we aim to maintain a good autocorrelation property of the designed signal. Therefore, our waveform design technique solves a bi-objective optimization problem in order to simultaneously improve the detection and autocorrelation performances, which are in general conflicting in nature. We demonstrate this compromising characteristics of themore » detection and autocorrelation performances with numerical examples. Furthermore, in the absence of the autocorrelation criterion, our designed signal is shown to achieve a near-optimum detection performance.« less

Multi-Fault Detection of Rolling Element Bearings under Harsh Working Condition Using IMF-Based Adaptive Envelope Order Analysis

PubMed Central

Zhao, Ming; Lin, Jing; Xu, Xiaoqiang; Li, Xuejun

2014-01-01

When operating under harsh condition (e.g., time-varying speed and load, large shocks), the vibration signals of rolling element bearings are always manifested as low signal noise ratio, non-stationary statistical parameters, which cause difficulties for current diagnostic methods. As such, an IMF-based adaptive envelope order analysis (IMF-AEOA) is proposed for bearing fault detection under such conditions. This approach is established through combining the ensemble empirical mode decomposition (EEMD), envelope order tracking and fault sensitive analysis. In this scheme, EEMD provides an effective way to adaptively decompose the raw vibration signal into IMFs with different frequency bands. The envelope order tracking is further employed to transform the envelope of each IMF to angular domain to eliminate the spectral smearing induced by speed variation, which makes the bearing characteristic frequencies more clear and discernible in the envelope order spectrum. Finally, a fault sensitive matrix is established to select the optimal IMF containing the richest diagnostic information for final decision making. The effectiveness of IMF-AEOA is validated by simulated signal and experimental data from locomotive bearings. The result shows that IMF-AEOA could accurately identify both single and multiple faults of bearing even under time-varying rotating speed and large extraneous shocks. PMID:25353982

A structural topological optimization method for multi-displacement constraints and any initial topology configuration

NASA Astrophysics Data System (ADS)

Rong, J. H.; Yi, J. H.

2010-10-01

In density-based topological design, one expects that the final result consists of elements either black (solid material) or white (void), without any grey areas. Moreover, one also expects that the optimal topology can be obtained by starting from any initial topology configuration. An improved structural topological optimization method for multi- displacement constraints is proposed in this paper. In the proposed method, the whole optimization process is divided into two optimization adjustment phases and a phase transferring step. Firstly, an optimization model is built to deal with the varied displacement limits, design space adjustments, and reasonable relations between the element stiffness matrix and mass and its element topology variable. Secondly, a procedure is proposed to solve the optimization problem formulated in the first optimization adjustment phase, by starting with a small design space and advancing to a larger deign space. The design space adjustments are automatic when the design domain needs expansions, in which the convergence of the proposed method will not be affected. The final topology obtained by the proposed procedure in the first optimization phase, can approach to the vicinity of the optimum topology. Then, a heuristic algorithm is given to improve the efficiency and make the designed structural topology black/white in both the phase transferring step and the second optimization adjustment phase. And the optimum topology can finally be obtained by the second phase optimization adjustments. Two examples are presented to show that the topologies obtained by the proposed method are of very good 0/1 design distribution property, and the computational efficiency is enhanced by reducing the element number of the design structural finite model during two optimization adjustment phases. And the examples also show that this method is robust and practicable.

Parallel Monte Carlo Search for Hough Transform

NASA Astrophysics Data System (ADS)

Lopes, Raul H. C.; Franqueira, Virginia N. L.; Reid, Ivan D.; Hobson, Peter R.

2017-10-01

We investigate the problem of line detection in digital image processing and in special how state of the art algorithms behave in the presence of noise and whether CPU efficiency can be improved by the combination of a Monte Carlo Tree Search, hierarchical space decomposition, and parallel computing. The starting point of the investigation is the method introduced in 1962 by Paul Hough for detecting lines in binary images. Extended in the 1970s to the detection of space forms, what came to be known as Hough Transform (HT) has been proposed, for example, in the context of track fitting in the LHC ATLAS and CMS projects. The Hough Transform transfers the problem of line detection, for example, into one of optimization of the peak in a vote counting process for cells which contain the possible points of candidate lines. The detection algorithm can be computationally expensive both in the demands made upon the processor and on memory. Additionally, it can have a reduced effectiveness in detection in the presence of noise. Our first contribution consists in an evaluation of the use of a variation of the Radon Transform as a form of improving theeffectiveness of line detection in the presence of noise. Then, parallel algorithms for variations of the Hough Transform and the Radon Transform for line detection are introduced. An algorithm for Parallel Monte Carlo Search applied to line detection is also introduced. Their algorithmic complexities are discussed. Finally, implementations on multi-GPU and multicore architectures are discussed.

[Research on the temperature field detection method of hot forging based on long-wavelength infrared spectrum].

PubMed

Zhang, Yu-Cun; Wei, Bin; Fu, Xian-Bin

2014-02-01

A temperature field detection method based on long-wavelength infrared spectrum for hot forging is proposed in the present paper. This method combines primary spectrum pyrometry and three-stage FP-cavity LCTF. By optimizing the solutions of three group nonlinear equations in the mathematical model of temperature detection, the errors are reduced, thus measuring results will be more objective and accurate. Then the system of three-stage FP-cavity LCTF was designed on the principle of crystal birefringence. The system realized rapid selection of any wavelength in a certain wavelength range. It makes the response of the temperature measuring system rapid and accurate. As a result, without the emissivity of hot forging, the method can acquire exact information of temperature field and effectively suppress the background light radiation around the hot forging and ambient light that impact the temperature detection accuracy. Finally, the results of MATLAB showed that the infrared spectroscopy through the three-stage FP-cavity LCTF could meet the requirements of design. And experiments verified the feasibility of temperature measuring method. Compared with traditional single-band thermal infrared imager, the accuracy of measuring result was improved.

Carbon dots based fluorescent sensor for sensitive determination of hydroquinone.

PubMed

Ni, Pengjuan; Dai, Haichao; Li, Zhen; Sun, Yujing; Hu, Jingting; Jiang, Shu; Wang, Yilin; Li, Zhuang

2015-11-01

In this paper, a novel biosensor based on Carbon dots (C-dots) for sensitive detection of hydroquinone (H2Q) is reported. It is interesting to find that the fluorescence of the C-dots could be quenched by H2Q directly. The possible quenching mechanism is proposed, which shows that the quenching effect may be caused by the electron transfer from C-dots to oxidized H2Q-quinone. Based on the above principle, a novel C-dots based fluorescent probe has been successfully applied to detect H2Q. Under the optimal condition, detection limit down to 0.1 μM is obtained, which is far below U.S. Environmental Protection Agency estimated wastewater discharge limit of 0.5 mg/L. Moreover, the proposed method shows high selectivity for H2Q over a number of potential interfering species. Finally, several water samples spiked with H2Q are analyzed utilizing the sensing method with satisfactory recovery. The proposed method is simple with high sensitivity and excellent selectivity, which provides a new approach for the detection of various analytes that can be transformed into quinone. Copyright © 2015 Elsevier B.V. All rights reserved.

Semi-supervised spectral algorithms for community detection in complex networks based on equivalence of clustering methods

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Wang, Bingbo; Yu, Liang

2018-01-01

Community detection is fundamental for revealing the structure-functionality relationship in complex networks, which involves two issues-the quantitative function for community as well as algorithms to discover communities. Despite significant research on either of them, few attempt has been made to establish the connection between the two issues. To attack this problem, a generalized quantification function is proposed for community in weighted networks, which provides a framework that unifies several well-known measures. Then, we prove that the trace optimization of the proposed measure is equivalent with the objective functions of algorithms such as nonnegative matrix factorization, kernel K-means as well as spectral clustering. It serves as the theoretical foundation for designing algorithms for community detection. On the second issue, a semi-supervised spectral clustering algorithm is developed by exploring the equivalence relation via combining the nonnegative matrix factorization and spectral clustering. Different from the traditional semi-supervised algorithms, the partial supervision is integrated into the objective of the spectral algorithm. Finally, through extensive experiments on both artificial and real world networks, we demonstrate that the proposed method improves the accuracy of the traditional spectral algorithms in community detection.

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.

Final report: Compiled MPI. Cost-Effective Exascale Application Development

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

Gropp, William Douglas

2015-12-21

This is the final report on Compiled MPI: Cost-Effective Exascale Application Development, and summarizes the results under this project. The project investigated runtime enviroments that improve the performance of MPI (Message-Passing Interface) programs; work at Illinois in the last period of this project looked at optimizing data access optimizations expressed with MPI datatypes.

Optimization of optical systems.

PubMed

Champagne, E B

1966-11-01

The power signal-to-noise ratios for coherent and noncoherent optical detection are presented, with the expression for noncoherent detection being examined in detail. It is found that for the long range optical system to compete with its microwave counterpart it is necessary to optimize the optical system. The optical system may be optimized by using coherent detection, or noncoherent detection if the signal is the dominate noise factor. A design procedure is presented which, in principle, always allows one to obtain signal shot-noise limited operation with noncoherent detection if pulsed operation is used. The technique should make reasonable extremely long range, high data rate systems of relatively simple design.

The simulation study on optical target laser active detection performance

NASA Astrophysics Data System (ADS)

Li, Ying-chun; Hou, Zhao-fei; Fan, Youchen

2014-12-01

According to the working principle of laser active detection system, the paper establishes the optical target laser active detection simulation system, carry out the simulation study on the detection process and detection performance of the system. For instance, the performance model such as the laser emitting, the laser propagation in the atmosphere, the reflection of optical target, the receiver detection system, the signal processing and recognition. We focus on the analysis and modeling the relationship between the laser emitting angle and defocus amount and "cat eye" effect echo laser in the reflection of optical target. Further, in the paper some performance index such as operating range, SNR and the probability of the system have been simulated. The parameters including laser emitting parameters, the reflection of the optical target and the laser propagation in the atmosphere which make a great influence on the performance of the optical target laser active detection system. Finally, using the object-oriented software design methods, the laser active detection system with the opening type, complete function and operating platform, realizes the process simulation that the detection system detect and recognize the optical target, complete the performance simulation of each subsystem, and generate the data report and the graph. It can make the laser active detection system performance models more intuitive because of the visible simulation process. The simulation data obtained from the system provide a reference to adjust the structure of the system parameters. And it provides theoretical and technical support for the top level design of the optical target laser active detection system and performance index optimization.

Automated recognition of the pericardium contour on processed CT images using genetic algorithms.

PubMed

Rodrigues, É O; Rodrigues, L O; Oliveira, L S N; Conci, A; Liatsis, P

2017-08-01

This work proposes the use of Genetic Algorithms (GA) in tracing and recognizing the pericardium contour of the human heart using Computed Tomography (CT) images. We assume that each slice of the pericardium can be modelled by an ellipse, the parameters of which need to be optimally determined. An optimal ellipse would be one that closely follows the pericardium contour and, consequently, separates appropriately the epicardial and mediastinal fats of the human heart. Tracing and automatically identifying the pericardium contour aids in medical diagnosis. Usually, this process is done manually or not done at all due to the effort required. Besides, detecting the pericardium may improve previously proposed automated methodologies that separate the two types of fat associated to the human heart. Quantification of these fats provides important health risk marker information, as they are associated with the development of certain cardiovascular pathologies. Finally, we conclude that GA offers satisfiable solutions in a feasible amount of processing time. Copyright © 2017 Elsevier Ltd. All rights reserved.

An atomic model of brome mosaic virus using direct electron detection and real-space optimization.

PubMed

Wang, Zhao; Hryc, Corey F; Bammes, Benjamin; Afonine, Pavel V; Jakana, Joanita; Chen, Dong-Hua; Liu, Xiangan; Baker, Matthew L; Kao, Cheng; Ludtke, Steven J; Schmid, Michael F; Adams, Paul D; Chiu, Wah

2014-09-04

Advances in electron cryo-microscopy have enabled structure determination of macromolecules at near-atomic resolution. However, structure determination, even using de novo methods, remains susceptible to model bias and overfitting. Here we describe a complete workflow for data acquisition, image processing, all-atom modelling and validation of brome mosaic virus, an RNA virus. Data were collected with a direct electron detector in integrating mode and an exposure beyond the traditional radiation damage limit. The final density map has a resolution of 3.8 Å as assessed by two independent data sets and maps. We used the map to derive an all-atom model with a newly implemented real-space optimization protocol. The validity of the model was verified by its match with the density map and a previous model from X-ray crystallography, as well as the internal consistency of models from independent maps. This study demonstrates a practical approach to obtain a rigorously validated atomic resolution electron cryo-microscopy structure.

RCrawler: An R package for parallel web crawling and scraping

NASA Astrophysics Data System (ADS)

Khalil, Salim; Fakir, Mohamed

RCrawler is a contributed R package for domain-based web crawling and content scraping. As the first implementation of a parallel web crawler in the R environment, RCrawler can crawl, parse, store pages, extract contents, and produce data that can be directly employed for web content mining applications. However, it is also flexible, and could be adapted to other applications. The main features of RCrawler are multi-threaded crawling, content extraction, and duplicate content detection. In addition, it includes functionalities such as URL and content-type filtering, depth level controlling, and a robot.txt parser. Our crawler has a highly optimized system, and can download a large number of pages per second while being robust against certain crashes and spider traps. In this paper, we describe the design and functionality of RCrawler, and report on our experience of implementing it in an R environment, including different optimizations that handle the limitations of R. Finally, we discuss our experimental results.

Improvement of LOD in Fluorescence Detection with Spectrally Nonuniform Background by Optimization of Emission Filtering.

PubMed

Galievsky, Victor A; Stasheuski, Alexander S; Krylov, Sergey N

2017-10-17

The limit-of-detection (LOD) in analytical instruments with fluorescence detection can be improved by reducing noise of optical background. Efficiently reducing optical background noise in systems with spectrally nonuniform background requires complex optimization of an emission filter-the main element of spectral filtration. Here, we introduce a filter-optimization method, which utilizes an expression for the signal-to-noise ratio (SNR) as a function of (i) all noise components (dark, shot, and flicker), (ii) emission spectrum of the analyte, (iii) emission spectrum of the optical background, and (iv) transmittance spectrum of the emission filter. In essence, the noise components and the emission spectra are determined experimentally and substituted into the expression. This leaves a single variable-the transmittance spectrum of the filter-which is optimized numerically by maximizing SNR. Maximizing SNR provides an accurate way of filter optimization, while a previously used approach based on maximizing a signal-to-background ratio (SBR) is the approximation that can lead to much poorer LOD specifically in detection of fluorescently labeled biomolecules. The proposed filter-optimization method will be an indispensable tool for developing new and improving existing fluorescence-detection systems aiming at ultimately low LOD.

On a New Optimization Approach for the Hydroforming of Defects-Free Tubular Metallic Parts

NASA Astrophysics Data System (ADS)

Caseiro, J. F.; Valente, R. A. F.; Andrade-Campos, A.; Jorge, R. M. Natal

2011-05-01

In the hydroforming of tubular metallic components, process parameters (internal pressure, axial feed and counter-punch position) must be carefully set in order to avoid defects in the final part. If, on one hand, excessive pressure may lead to thinning and bursting during forming, on the other hand insufficient pressure may lead to an inadequate filling of the die. Similarly, an excessive axial feeding may lead to the formation of wrinkles, whilst an inadequate one may cause thinning and, consequentially, bursting. These apparently contradictory targets are virtually impossible to achieve without trial-and-error procedures in industry, unless optimization approaches are formulated and implemented for complex parts. In this sense, an optimization algorithm based on differentialevolutionary techniques is presented here, capable of being applied in the determination of the adequate process parameters for the hydroforming of metallic tubular components of complex geometries. The Hybrid Differential Evolution Particle Swarm Optimization (HDEPSO) algorithm, combining the advantages of a number of well-known distinct optimization strategies, acts along with a general purpose implicit finite element software, and is based on the definition of a wrinkling and thinning indicators. If defects are detected, the algorithm automatically corrects the process parameters and new numerical simulations are performed in real time. In the end, the algorithm proved to be robust and computationally cost-effective, thus providing a valid design tool for the conformation of defects-free components in industry [1].

Near-infrared surface-enhanced fluorescence using silver nanoparticles in solution

NASA Astrophysics Data System (ADS)

Furtaw, Michael D.

Fluorescence spectroscopy is a widely used detection technology in many research and clinical assays. Further improvement to assay sensitivity may enable earlier diagnosis of disease, novel biomarker discovery, and ultimately, improved outcomes of clinical care along with reduction in costs. Near-infrared, surface-enhanced fluorescence (NIR-SEF) is a promising approach to improve assay sensitivity via simultaneous increase in signal with a reduction in background. This dissertation describes research conducted with the overall goal to determine the extent to which fluorescence in solution may be enhanced by altering specific variables involved in the formation of plasmon-active nanostructures of dye-labeled protein and silver nanoparticles in solution, with the intent of providing a simple solution that may be readily adopted by current fluorescence users in the life science research community. First, it is shown that inner-filtering, re-absorption of the emitted photons, can red-shift the optimal fluorophore spectrum away from the resonant frequency of the plasmon-active nanostructure. It is also shown that, under certain conditions, the quality factor may be a better indicator of SEF than the commonly accepted overlap of the fluorophore spectrum with the plasmon resonance of the nanostructure. Next, it is determined that streptavidin is the best choice for carrier protein, among the most commonly used dye-labeled detection antibodies, to enable the largest fluorescence enhancement when labeled with IRDye 800CW and used in combination with silver nanoparticles in solution. It is shown that the relatively small and symmetric geometry of streptavidin enables substantial electromagnetic-field confinement when bound to silver nanoparticles, leading to strong and reproducible enhancement. The role of silver nanoparticle aggregation is demonstrated in a droplet-based microfluidic chip and further optimized in a standard microtiter-plate format. A NIR-SEF technology based on aggregation with optimized salt concentration demonstrates a fluorescence signal enhancement up to 2530-fold while improving the limit-of-detection over 1000-fold. Finally, the NIR-SEF technology is applied to demonstrate 42-fold improvement in sensitivity of the clinically-relevant biomarker, alpha-fetoprotein, along with a 16-fold improvement in limit-of-detection.

Detection capability of a pulsed Ground Penetrating Radar utilizing an oscilloscope and Radargram Fusion Approach for optimal signal quality

NASA Astrophysics Data System (ADS)

Seyfried, Daniel; Schoebel, Joerg

2015-07-01

In scientific research pulsed radars often employ a digital oscilloscope as sampling unit. The sensitivity of an oscilloscope is determined in general by means of the number of digits of its analog-to-digital converter and the selected full scale vertical setting, i.e., the maximal voltage range displayed. Furthermore oversampling or averaging of the input signal may increase the effective number of digits, hence the sensitivity. Especially for Ground Penetrating Radar applications high sensitivity of the radar system is demanded since reflection amplitudes of buried objects are strongly attenuated in ground. Hence, in order to achieve high detection capability this parameter is one of the most crucial ones. In this paper we analyze the detection capability of our pulsed radar system utilizing a Rohde & Schwarz RTO 1024 oscilloscope as sampling unit for Ground Penetrating Radar applications, such as detection of pipes and cables in the ground. Also effects of averaging and low-noise amplification of the received signal prior to sampling are investigated by means of an appropriate laboratory setup. To underline our findings we then present real-world radar measurements performed on our GPR test site, where we have buried pipes and cables of different types and materials in different depths. The results illustrate the requirement for proper choice of the settings of the oscilloscope for optimal data recording. However, as we show, displaying both strong signal contributions due to e.g., antenna cross-talk and direct ground bounce reflection as well as weak reflections from objects buried deeper in ground requires opposing trends for the oscilloscope's settings. We therefore present our Radargram Fusion Approach. By means of this approach multiple radargrams recorded in parallel, each with an individual optimized setting for a certain type of contribution, can be fused in an appropriate way in order to finally achieve a single radargram which displays all contributions occurring originally at different strengths in an equalized and normalized way by means of appropriate digital signal post-processing.

A robust hypothesis test for the sensitive detection of constant speed radiation moving sources

NASA Astrophysics Data System (ADS)

Dumazert, Jonathan; Coulon, Romain; Kondrasovs, Vladimir; Boudergui, Karim; Moline, Yoann; Sannié, Guillaume; Gameiro, Jordan; Normand, Stéphane; Méchin, Laurence

2015-09-01

Radiation Portal Monitors are deployed in linear networks to detect radiological material in motion. As a complement to single and multichannel detection algorithms, inefficient under too low signal-to-noise ratios, temporal correlation algorithms have been introduced. Test hypothesis methods based on empirically estimated mean and variance of the signals delivered by the different channels have shown significant gain in terms of a tradeoff between detection sensitivity and false alarm probability. This paper discloses the concept of a new hypothesis test for temporal correlation detection methods, taking advantage of the Poisson nature of the registered counting signals, and establishes a benchmark between this test and its empirical counterpart. The simulation study validates that in the four relevant configurations of a pedestrian source carrier under respectively high and low count rate radioactive backgrounds, and a vehicle source carrier under the same respectively high and low count rate radioactive backgrounds, the newly introduced hypothesis test ensures a significantly improved compromise between sensitivity and false alarm. It also guarantees that the optimal coverage factor for this compromise remains stable regardless of signal-to-noise ratio variations between 2 and 0.8, therefore allowing the final user to parametrize the test with the sole prior knowledge of background amplitude.

Development of flexible SAW sensors for non-destructive testing of structure

NASA Astrophysics Data System (ADS)

Takpara, R.; Duquennoy, M.; Courtois, C.; Gonon, M.; Ouaftouh, M.; Martic, G.; Rguiti, M.; Jenot, F.; Seronveaux, L.; Pelegris, C.

2016-02-01

In order to accurately examine structures surfaces, it is interesting to use surface SAW (Surface Acoustic Wave). Such waves are well suited for example to detect early emerging cracks or to test the quality of a coating. In addition, when coatings are thin or when emergent cracks are precocious, it is necessary to excite surface waves beyond 10MHz. Finally, when structures are not flat, it makes sense to have flexible or conformable sensors for their characterization. To address this problem, we propose to develop SAW type of interdigital sensors (or IDT for InterDigital Transducer), based on flexible piezoelectric plates. Initially, in order to optimize these sensors, we modeled the behavior of these sensors and identified the optimum characteristic sizes. In particular, the thickness of the piezoelectric plate and the width of the interdigital electrodes have been studied. Secondly, we made composites based on barium titanate foams in order to have flexible piezoelectric plates and to carry out thereafter sensors. Then, we studied several techniques in order to optimize the interdigitated electrodes deposition on this type of material. One of the difficulties concerns the fineness of these electrodes because the ratio between the length (typically several millimeters) and the width (a few tens of micrometers) of electrodes is very high. Finally, mechanical, electrical and acoustical characterizations of the sensors deposited on aluminum substrates were able to show the quality of our achievement.

Testing models of parental investment strategy and offspring size in ants.

PubMed

Gilboa, Smadar; Nonacs, Peter

2006-01-01

Parental investment strategies can be fixed or flexible. A fixed strategy predicts making all offspring a single 'optimal' size. Dynamic models predict flexible strategies with more than one optimal size of offspring. Patterns in the distribution of offspring sizes may thus reveal the investment strategy. Static strategies should produce normal distributions. Dynamic strategies should often result in non-normal distributions. Furthermore, variance in morphological traits should be positively correlated with the length of developmental time the traits are exposed to environmental influences. Finally, the type of deviation from normality (i.e., skewed left or right, or platykurtic) should be correlated with the average offspring size. To test the latter prediction, we used simulations to detect significant departures from normality and categorize distribution types. Data from three species of ants strongly support the predicted patterns for dynamic parental investment. Offspring size distributions are often significantly non-normal. Traits fixed earlier in development, such as head width, are less variable than final body weight. The type of distribution observed correlates with mean female dry weight. The overall support for a dynamic parental investment model has implications for life history theory. Predicted conflicts over parental effort, sex investment ratios, and reproductive skew in cooperative breeders follow from assumptions of static parental investment strategies and omnipresent resource limitations. By contrast, with flexible investment strategies such conflicts can be either absent or maladaptive.

Indirect competitive ELISA based on monoclonal antibody for the detection of 5-hydroxymethyl-2-furfural in milk, compared with HPLC.

PubMed

Guan, Yongguang; Wu, Xinlan; Meng, Hecheng

2013-08-01

In this study, a method for rapid detection of 5-hydroxymethyl-2-furfural (HMF) was investigated. Monoclonal antibody (anti-HMF) was prepared and evaluated by an indirect competitive ELISA (ic-ELISA) format. The optimized standard curve was y=-0.2097x+1.0432 [where x is the logarithm (base 10) of the values of the HMF concentration and y is the absorbance of ic-ELISA results tested at 490 nm] and the linear detection range was 0.008 to 32.768 mg/L. The percentage of cross-reactivity of HMF with 5 major furfural derivatives was less than 2.92%. Finally, the established ic-ELISA format was used to test HMF in milk, and compared with the result obtained by HPLC, which produced an error of about 0.3%. Based on the data in this experiment, we concluded that the established ic-ELISA format was reliable with a high specificity. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Pd-Au@carbon dots nanocomposite: Facile synthesis and application as an ultrasensitive electrochemical biosensor for determination of colitoxin DNA in human serum.

PubMed

Huang, Qitong; Lin, Xiaofeng; Zhu, Jie-Ji; Tong, Qing-Xiao

2017-08-15

In this study, a green and fast method was developed to synthesize high-yield carbon dots (CDs) via one-pot microwave treatment of banana peels without using any other surface passivation agents. Then the as-prepared CDs was used as the reducing agent and stabilizer to synthesize a Pd-Au@CDs nanocomposite by a simple sequential reduction strategy. Finally, Pd-Au@CDs nanocomposite modified glassy carbon electrode (Pd-Au@CDs/GCE) was obtained as a biosensor for target DNA after being immobilized a single-stranded probe DNA by a carboxyl ammonia condensation reaction. Under the optimal conditions, the sensor could detect target DNA concentrations in the range from 5.0×10 -16 to 1.0×10 -1 °molL -1 . The detection limit (LD) was estimated to be 1.82×10 -17 molL -1 , which showed higher sensitivity than other electrochemical biosensors reported. In addition, the DNA sensor was also successfully applied to detect colitoxin DNA in human serum. Copyright © 2017 Elsevier B.V. All rights reserved.

Detailed analysis of complex single molecule FRET data with the software MASH

NASA Astrophysics Data System (ADS)

Hadzic, Mélodie C. A. S.; Kowerko, Danny; Börner, Richard; Zelger-Paulus, Susann; Sigel, Roland K. O.

2016-04-01

The processing and analysis of surface-immobilized single molecule FRET (Förster resonance energy transfer) data follows systematic steps (e.g. single molecule localization, clearance of different sources of noise, selection of the conformational and kinetic model, etc.) that require a solid knowledge in optics, photophysics, signal processing and statistics. The present proceeding aims at standardizing and facilitating procedures for single molecule detection by guiding the reader through an optimization protocol for a particular experimental data set. Relevant features were determined from single molecule movies (SMM) imaging Cy3- and Cy5-labeled Sc.ai5γ group II intron molecules synthetically recreated, to test the performances of four different detection algorithms. Up to 120 different parameterizations per method were routinely evaluated to finally establish an optimum detection procedure. The present protocol is adaptable to any movie displaying surface-immobilized molecules, and can be easily reproduced with our home-written software MASH (multifunctional analysis software for heterogeneous data) and script routines (both available in the download section of www.chem.uzh.ch/rna).

Optimization of vehicle deceleration to reduce occupant injury risks in frontal impact.

PubMed

Mizuno, Koji; Itakura, Takuya; Hirabayashi, Satoko; Tanaka, Eiichi; Ito, Daisuke

2014-01-01

In vehicle frontal impacts, vehicle acceleration has a large effect on occupant loadings and injury risks. In this research, an optimal vehicle crash pulse was determined systematically to reduce injury measures of rear seat occupants by using mathematical simulations. The vehicle crash pulse was optimized based on a vehicle deceleration-deformation diagram under the conditions that the initial velocity and the maximum vehicle deformation were constant. Initially, a spring-mass model was used to understand the fundamental parameters for optimization. In order to investigate the optimization under a more realistic situation, the vehicle crash pulse was also optimized using a multibody model of a Hybrid III dummy seated in the rear seat for the objective functions of chest acceleration and chest deflection. A sled test using a Hybrid III dummy was carried out to confirm the simulation results. Finally, the optimal crash pulses determined from the multibody simulation were applied to a human finite element (FE) model. The optimized crash pulse to minimize the occupant deceleration had a concave shape: a high deceleration in the initial phase, low in the middle phase, and high again in the final phase. This crash pulse shape depended on the occupant restraint stiffness. The optimized crash pulse determined from the multibody simulation was comparable to that from the spring-mass model. From the sled test, it was demonstrated that the optimized crash pulse was effective for the reduction of chest acceleration. The crash pulse was also optimized for the objective function of chest deflection. The optimized crash pulse in the final phase was lower than that obtained for the minimization of chest acceleration. In the FE analysis of the human FE model, the optimized pulse for the objective function of the Hybrid III chest deflection was effective in reducing rib fracture risks. The optimized crash pulse has a concave shape and is dependent on the occupant restraint stiffness and maximum vehicle deformation. The shapes of the optimized crash pulse in the final phase were different for the objective functions of chest acceleration and chest deflection due to the inertial forces of the head and upper extremities. From the human FE model analysis it was found that the optimized crash pulse for the Hybrid III chest deflection can substantially reduce the risk of rib cage fractures. Supplemental materials are available for this article. Go to the publisher's online edition of Traffic Injury Prevention to view the supplemental file.

Spectral anomaly methods for aerial detection using KUT nuisance rejection

NASA Astrophysics Data System (ADS)

Detwiler, R. S.; Pfund, D. M.; Myjak, M. J.; Kulisek, J. A.; Seifert, C. E.

2015-06-01

This work discusses the application and optimization of a spectral anomaly method for the real-time detection of gamma radiation sources from an aerial helicopter platform. Aerial detection presents several key challenges over ground-based detection. For one, larger and more rapid background fluctuations are typical due to higher speeds, larger field of view, and geographically induced background changes. As well, the possible large altitude or stand-off distance variations cause significant steps in background count rate as well as spectral changes due to increased gamma-ray scatter with detection at higher altitudes. The work here details the adaptation and optimization of the PNNL-developed algorithm Nuisance-Rejecting Spectral Comparison Ratios for Anomaly Detection (NSCRAD), a spectral anomaly method previously developed for ground-based applications, for an aerial platform. The algorithm has been optimized for two multi-detector systems; a NaI(Tl)-detector-based system and a CsI detector array. The optimization here details the adaptation of the spectral windows for a particular set of target sources to aerial detection and the tailoring for the specific detectors. As well, the methodology and results for background rejection methods optimized for the aerial gamma-ray detection using Potassium, Uranium and Thorium (KUT) nuisance rejection are shown. Results indicate that use of a realistic KUT nuisance rejection may eliminate metric rises due to background magnitude and spectral steps encountered in aerial detection due to altitude changes and geographically induced steps such as at land-water interfaces.

The Analysis of Fixed Final State Optimal Control in Bilinear System Applied to Bone Marrow by Cell-Cycle Specific (CCS) Chemotherapy

NASA Astrophysics Data System (ADS)

Rainarli, E.; E Dewi, K.

2017-04-01

The research conducted by Fister & Panetta shown an optimal control model of bone marrow cells against Cell Cycle Specific chemotherapy drugs. The model used was a bilinear system model. Fister & Panetta research has proved existence, uniqueness, and characteristics of optimal control (the chemotherapy effect). However, by using this model, the amount of bone marrow at the final time could achieve less than 50 percent from the amount of bone marrow before given treatment. This could harm patients because the lack of bone marrow cells made the number of leukocytes declining and patients will experience leukemia. This research would examine the optimal control of a bilinear system that applied to fixed final state. It will be used to determine the length of optimal time in administering chemotherapy and kept bone marrow cells on the allowed level at the same time. Before simulation conducted, this paper shows that the system could be controlled by using a theory of Lie Algebra. Afterward, it shows the characteristics of optimal control. Based on the simulation, it indicates that strong chemotherapy drug given in a short time frame is the most optimal condition to keep bone marrow cells spine on the allowed level but still could put playing an effective treatment. It gives preference of the weight of treatment for keeping bone marrow cells. The result of chemotherapy’s effect (u) is not able to reach the maximum value. On the other words, it needs to make adjustments of medicine’s dosage to satisfy the final treatment condition e.g. the number of bone marrow cells should be at the allowed level.

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

NASA Astrophysics Data System (ADS)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

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

CNV detection method optimized for high-resolution arrayCGH by normality test.

PubMed

Ahn, Jaegyoon; Yoon, Youngmi; Park, Chihyun; Park, Sanghyun

2012-04-01

High-resolution arrayCGH platform makes it possible to detect small gains and losses which previously could not be measured. However, current CNV detection tools fitted to early low-resolution data are not applicable to larger high-resolution data. When CNV detection tools are applied to high-resolution data, they suffer from high false-positives, which increases validation cost. Existing CNV detection tools also require optimal parameter values. In most cases, obtaining these values is a difficult task. This study developed a CNV detection algorithm that is optimized for high-resolution arrayCGH data. This tool operates up to 1500 times faster than existing tools on a high-resolution arrayCGH of whole human chromosomes which has 42 million probes whose average length is 50 bases, while preserving false positive/negative rates. The algorithm also uses a normality test, thereby removing the need for optimal parameters. To our knowledge, this is the first formulation for CNV detecting problems that results in a near-linear empirical overall complexity for real high-resolution data. Copyright © 2012 Elsevier Ltd. All rights reserved.

Trellis coding with Continuous Phase Modulation (CPM) for satellite-based land-mobile communications

NASA Technical Reports Server (NTRS)

1989-01-01

This volume of the final report summarizes the results of our studies on the satellite-based mobile communications project. It includes: a detailed analysis, design, and simulations of trellis coded, full/partial response CPM signals with/without interleaving over various Rician fading channels; analysis and simulation of computational cutoff rates for coherent, noncoherent, and differential detection of CPM signals; optimization of the complete transmission system; analysis and simulation of power spectrum of the CPM signals; design and development of a class of Doppler frequency shift estimators; design and development of a symbol timing recovery circuit; and breadboard implementation of the transmission system. Studies prove the suitability of the CPM system for mobile communications.

Cerenkov luminescence imaging: physics principles and potential applications in biomedical sciences.

PubMed

Ciarrocchi, Esther; Belcari, Nicola

2017-12-01

Cerenkov luminescence imaging (CLI) is a novel imaging modality to study charged particles with optical methods by detecting the Cerenkov luminescence produced in tissue. This paper first describes the physical processes that govern the production and transport in tissue of Cerenkov luminescence. The detectors used for CLI and their most relevant specifications to optimize the acquisition of the Cerenkov signal are then presented, and CLI is compared with the other optical imaging modalities sharing the same data acquisition and processing methods. Finally, the scientific work related to CLI and the applications for which CLI has been proposed are reviewed. The paper ends with some considerations about further perspectives for this novel imaging modality.

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

DTIC Science & Technology

2010-11-01

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

Research on the algorithm of infrared target detection based on the frame difference and background subtraction method

NASA Astrophysics Data System (ADS)

Liu, Yun; Zhao, Yuejin; Liu, Ming; Dong, Liquan; Hui, Mei; Liu, Xiaohua; Wu, Yijian

2015-09-01

As an important branch of infrared imaging technology, infrared target tracking and detection has a very important scientific value and a wide range of applications in both military and civilian areas. For the infrared image which is characterized by low SNR and serious disturbance of background noise, an innovative and effective target detection algorithm is proposed in this paper, according to the correlation of moving target frame-to-frame and the irrelevance of noise in sequential images based on OpenCV. Firstly, since the temporal differencing and background subtraction are very complementary, we use a combined detection method of frame difference and background subtraction which is based on adaptive background updating. Results indicate that it is simple and can extract the foreground moving target from the video sequence stably. For the background updating mechanism continuously updating each pixel, we can detect the infrared moving target more accurately. It paves the way for eventually realizing real-time infrared target detection and tracking, when transplanting the algorithms on OpenCV to the DSP platform. Afterwards, we use the optimal thresholding arithmetic to segment image. It transforms the gray images to black-white images in order to provide a better condition for the image sequences detection. Finally, according to the relevance of moving objects between different frames and mathematical morphology processing, we can eliminate noise, decrease the area, and smooth region boundaries. Experimental results proves that our algorithm precisely achieve the purpose of rapid detection of small infrared target.

Multi-epitope proteins for improved serological detection of Trypanosoma cruzi infection and Chagas Disease.

PubMed

Duthie, Malcolm S; Guderian, Jeffery A; Vallur, Aarthy C; Misquith, Ayesha; Liang, Hong; Mohamath, Raodoh; Luquetti, Alejandro O; Carter, Darrick; Tavares, Suelene N B; Reed, Steven G

2016-03-01

We previously reported that tandem repeat (TR) proteins from Trypanosoma cruzi could serve as targets of the antibody response and be useful as diagnostic indicators. To optimize reagents for detecting T. cruzi infection we evaluated individual TR proteins and identified several that were recognized by the majority of Chagas patient's sera collected from individuals form Brazil. We then produced novel, recombinant fusion proteins to combine the reactive TR proteins into a single diagnostic product. Direct comparison of the antibody response of serum samples that were readily detected by the established fusion antigen used in commercial detection of Chagas disease, TcF, revealed strong responses to TcF43 and TcF26 proteins. While the TcF43 and TcF26 antigens enhanced detection and strength of signal, they did not compromise the specificity of detection compared to that obtained with TcF. Finally, it was apparent by testing against a panel of 84 serum samples assembled on the basis of moderate or weak reactivity against TcF (mostly signal:noise <5) that TcF43 and TcF26 could more strongly detected by many of the sera that had low TcF antibody levels. Taken together, these data indicate that TcF43 and TcF26 could be used to enhance the detection of T. cruzi infection as well as supporting a diagnosis of Chagas disease. Copyright © 2016 Elsevier Inc. All rights reserved.

A novel rapid and reproducible flow cytometric method for optimization of transfection efficiency in cells

PubMed Central

Homann, Stefanie; Hofmann, Christian; Gorin, Aleksandr M.; Nguyen, Huy Cong Xuan; Huynh, Diana; Hamid, Phillip; Maithel, Neil; Yacoubian, Vahe; Mu, Wenli; Kossyvakis, Athanasios; Sen Roy, Shubhendu; Yang, Otto Orlean

2017-01-01

Transfection is one of the most frequently used techniques in molecular biology that is also applicable for gene therapy studies in humans. One of the biggest challenges to investigate the protein function and interaction in gene therapy studies is to have reliable monospecific detection reagents, particularly antibodies, for all human gene products. Thus, a reliable method that can optimize transfection efficiency based on not only expression of the target protein of interest but also the uptake of the nucleic acid plasmid, can be an important tool in molecular biology. Here, we present a simple, rapid and robust flow cytometric method that can be used as a tool to optimize transfection efficiency at the single cell level while overcoming limitations of prior established methods that quantify transfection efficiency. By using optimized ratios of transfection reagent and a nucleic acid (DNA or RNA) vector directly labeled with a fluorochrome, this method can be used as a tool to simultaneously quantify cellular toxicity of different transfection reagents, the amount of nucleic acid plasmid that cells have taken up during transfection as well as the amount of the encoded expressed protein. Finally, we demonstrate that this method is reproducible, can be standardized and can reliably and rapidly quantify transfection efficiency, reducing assay costs and increasing throughput while increasing data robustness. PMID:28863132

Chiral micellar electrokinetic chromatography (CMEKC)-atmospheric pressure photoionization of benzoin derivatives using mixed molecular micelles

PubMed Central

He, Jun; Shamsi, Shahab A.

2012-01-01

In the present work we report, for the first time, the successful on-line coupling of chiral micellar electrokinetic chromatography (CMEKC) to atmospheric pressure photo-ionization mass spectrometry (APPI-MS). Four structurally similar neutral test solutes (e.g., benzoin derivatives) were successfully ionized by APPI-MS. The mass spectra in the positive ion mode showed that the protonated molecular ions of benzoins are not the most abundant fragment ions. Simultaneous enantioseparation by CMEKC and on-line APPI-MS detection of four photoinitiators: hydrobenzoin (HBNZ), benzoin (BNZ), benzoin methyl ether (BME), benzoin ethyl ether (BEE), were achieved using an optimized molar ratio of mixed molecular micelle of two polymeric chiral surfactants (polysodium N-undecenoxy carbonyl-L-leucinate and polysodium N-undecenoyl-L,L-leucylvalinate). The CMEKC conditions, such as voltage, chiral polymeric surfactant concentration, buffer pH, and BGE concentration, were optimized using a multivariate central composite design (CCD). The sheath liquid composition (involving % v/v methanol, dopant concentration, electrolyte additive concentration, and flow rate) and spray chamber parameters (drying gas flow rate, drying gas temperature, and vaporizer temperature) were also optimized with CCD. Models built based on the CCD results and response surface method was used to analyze the interactions between factors and their effects on the responses. The final overall optimum conditions for CMEKC-APPI-MS were also predicted and found in agreement with the experimentally optimized parameters. PMID:21500208

Application of Failure Mode and Effect Analysis (FMEA), cause and effect analysis, and Pareto diagram in conjunction with HACCP to a corn curl manufacturing plant.

PubMed

Varzakas, Theodoros H; Arvanitoyannis, Ioannis S

2007-01-01

The Failure Mode and Effect Analysis (FMEA) model has been applied for the risk assessment of corn curl manufacturing. A tentative approach of FMEA application to the snacks industry was attempted in an effort to exclude the presence of GMOs in the final product. This is of crucial importance both from the ethics and the legislation (Regulations EC 1829/2003; EC 1830/2003; Directive EC 18/2001) point of view. The Preliminary Hazard Analysis and the Fault Tree Analysis were used to analyze and predict the occurring failure modes in a food chain system (corn curls processing plant), based on the functions, characteristics, and/or interactions of the ingredients or the processes, upon which the system depends. Critical Control points have been identified and implemented in the cause and effect diagram (also known as Ishikawa, tree diagram, and the fishbone diagram). Finally, Pareto diagrams were employed towards the optimization of GMOs detection potential of FMEA.

Salt disproportionation: A material science perspective.

PubMed

Thakral, Naveen K; Kelly, Ron C

2017-03-30

While screening the counter-ions for salt selection for an active pharmaceutical substance, there is often an uncertainty about disproportionation of the salt and hence physical stability of the final product formulation to provide adequate shelf life. Several examples of disproportionation reactions are reviewed to explain the concepts of pHmax, microenvironmental pH, and buffering capacity of excipients and APIs to gain mechanistic understanding of disproportionation reaction. Miscellaneous factors responsible for disproportionation are examined. In addition to the dissolution failure due to the formation of less soluble unionized form, various implications of the disproportionation are evaluated with specific examples. During lead optimization and early stages of development, when only a limited amount of material is available, use of predictive tools like mathematical models and model free kinetics to rank order the various counter-ions are discussed in detail. Finally, analytical methods and mitigation strategies are discussed to prevent the disproportionation by detecting it during early stages of drug development. Copyright © 2017 Elsevier B.V. All rights reserved.

Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-01-01

To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

Optimization of Contrast Detection Power with Probabilistic Behavioral Information

PubMed Central

Cordes, Dietmar; Herzmann, Grit; Nandy, Rajesh; Curran, Tim

2012-01-01

Recent progress in the experimental design for event-related fMRI experiments made it possible to find the optimal stimulus sequence for maximum contrast detection power using a genetic algorithm. In this study, a novel algorithm is proposed for optimization of contrast detection power by including probabilistic behavioral information, based on pilot data, in the genetic algorithm. As a particular application, a recognition memory task is studied and the design matrix optimized for contrasts involving the familiarity of individual items (pictures of objects) and the recollection of qualitative information associated with the items (left/right orientation). Optimization of contrast efficiency is a complicated issue whenever subjects’ responses are not deterministic but probabilistic. Contrast efficiencies are not predictable unless behavioral responses are included in the design optimization. However, available software for design optimization does not include options for probabilistic behavioral constraints. If the anticipated behavioral responses are included in the optimization algorithm, the design is optimal for the assumed behavioral responses, and the resulting contrast efficiency is greater than what either a block design or a random design can achieve. Furthermore, improvements of contrast detection power depend strongly on the behavioral probabilities, the perceived randomness, and the contrast of interest. The present genetic algorithm can be applied to any case in which fMRI contrasts are dependent on probabilistic responses that can be estimated from pilot data. PMID:22326984

Weak fault detection and health degradation monitoring using customized standard multiwavelets

NASA Astrophysics Data System (ADS)

Yuan, Jing; Wang, Yu; Peng, Yizhen; Wei, Chenjun

2017-09-01

Due to the nonobvious symptoms contaminated by a large amount of background noise, it is challenging to beforehand detect and predictively monitor the weak faults for machinery security assurance. Multiwavelets can act as adaptive non-stationary signal processing tools, potentially viable for weak fault diagnosis. However, the signal-based multiwavelets suffer from such problems as the imperfect properties missing the crucial orthogonality, the decomposition distortion impossibly reflecting the relationships between the faults and signatures, the single objective optimization and independence for fault prognostic. Thus, customized standard multiwavelets are proposed for weak fault detection and health degradation monitoring, especially the weak fault signature quantitative identification. First, the flexible standard multiwavelets are designed using the construction method derived from scalar wavelets, seizing the desired properties for accurate detection of weak faults and avoiding the distortion issue for feature quantitative identification. Second, the multi-objective optimization combined three dimensionless indicators of the normalized energy entropy, normalized singular entropy and kurtosis index is introduced to the evaluation criterions, and benefits for selecting the potential best basis functions for weak faults without the influence of the variable working condition. Third, an ensemble health indicator fused by the kurtosis index, impulse index and clearance index of the original signal along with the normalized energy entropy and normalized singular entropy by the customized standard multiwavelets is achieved using Mahalanobis distance to continuously monitor the health condition and track the performance degradation. Finally, three experimental case studies are implemented to demonstrate the feasibility and effectiveness of the proposed method. The results show that the proposed method can quantitatively identify the fault signature of a slight rub on the inner race of a locomotive bearing, effectively detect and locate the potential failure from a complicated epicyclic gear train and successfully reveal the fault development and performance degradation of a test bearing in the lifetime.

Second generation multiple reaction monitoring assays for enhanced detection of ultra-low abundance Mycobacterium tuberculosis peptides in human serum.

PubMed

Mehaffy, Carolina; Dobos, Karen M; Nahid, Payam; Kruh-Garcia, Nicole A

2017-01-01

Mycobacterium tuberculosis (Mtb) is the causative agent of Tuberculosis (TB), the number one cause of death due to an infectious disease. TB diagnosis is performed by microscopy, culture or PCR amplification of bacterial DNA, all of which require patient sputum or the biopsy of infected tissue. Detection of mycobacterial products in serum, as biomarkers of diagnosis or disease status would provide an improvement over current methods. Due to the low-abundance of mycobacterial products in serum, we have explored exosome enrichment to improve sensitivity. Mtb resides intracellularly where its secreted proteins have been shown to be packaged into host exosomes and released into the bloodstream. Exosomes can be readily purified assuring an enrichment of mycobacterial analytes from the complex mix of host serum proteins. Multiple reaction monitoring assays were optimized for the enhanced detection of 41 Mtb peptides in exosomes purified from the serum of individuals with TB. Exosomes isolated from the serum of healthy individuals was used to create and validate a unique data analysis algorithm and identify filters to reduce the rate of false positives, attributed to host m / z interference. The final optimized method was tested in 40 exosome samples from TB positive patients. Our enhanced methods provide limit of detection and quantification averaging in the low femtomolar range for detection of mycobacterial products in serum. At least one mycobacterial peptide was identified in 92.5% of the TB positive patients. Four peptides from the Mtb proteins, Cfp2, Mpt32, Mpt64 and BfrB, show normalized total peak areas significantly higher in individuals with active TB as compared to healthy controls; three of the peptides from these proteins have not previously been associated with serum exosomes from individuals with active TB disease. Some of the detected peptides were significantly associated with specific geographical locations, highlighting potential markers that can be linked to the Mtb strains circulating within each given region. An enhanced MRM method to detect ultra-low abundance Mtb peptides in human serum exosomes is demonstrated, highlighting the potential of this methodology for TB diagnostic biomarker development.

A Bernoulli Gaussian Watermark for Detecting Integrity Attacks in Control Systems

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

Weerakkody, Sean; Ozel, Omur; Sinopoli, Bruno

We examine the merit of Bernoulli packet drops in actively detecting integrity attacks on control systems. The aim is to detect an adversary who delivers fake sensor measurements to a system operator in order to conceal their effect on the plant. Physical watermarks, or noisy additive Gaussian inputs, have been previously used to detect several classes of integrity attacks in control systems. In this paper, we consider the analysis and design of Gaussian physical watermarks in the presence of packet drops at the control input. On one hand, this enables analysis in a more general network setting. On the othermore » hand, we observe that in certain cases, Bernoulli packet drops can improve detection performance relative to a purely Gaussian watermark. This motivates the joint design of a Bernoulli-Gaussian watermark which incorporates both an additive Gaussian input and a Bernoulli drop process. We characterize the effect of such a watermark on system performance as well as attack detectability in two separate design scenarios. Here, we consider a correlation detector for attack recognition. We then propose efficiently solvable optimization problems to intelligently select parameters of the Gaussian input and the Bernoulli drop process while addressing security and performance trade-offs. Finally, we provide numerical results which illustrate that a watermark with packet drops can indeed outperform a Gaussian watermark.« less

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Gold nanoparticle-based enzyme-linked antibody-aptamer sandwich assay for detection of Salmonella Typhimurium.

PubMed

Wu, Wenhe; Li, Jun; Pan, Dun; Li, Jiang; Song, Shiping; Rong, Mingge; Li, Zixi; Gao, Jimin; Lu, Jianxin

2014-10-08

Enzyme-linked immunosorbent assay (ELISA) provides a convenient means for the detection of Salmonella enterica serovar Typhimurium (STM), which is important for rapid diagnosis of foodborne pathogens. However, conventional ELISA is limited by antibody-antigen immunoreactions and suffers from poor sensitivity and tedious sample pretreatment. Therefore, development of novel ELISA remains challenging. Herein, we designed a comprehensive strategy for rapid, sensitive, and quantitative detection of STM with high specificity by gold nanoparticle-based enzyme-linked antibody-aptamer sandwich (nano-ELAAS) method. STM was captured and preconcentrated from samples with aptamer-modified magnetic particles, followed by binding with detector antibodies. Then nanoprobes carrying a large amount of reporter antibodies and horseradish peroxidase molecules were used for colorimetric signal amplification. Under the optimized reaction conditions, the nano-ELAAS assay had a quantitative detection range from 1 × 10(3) to 1 × 10(8) CFU mL(-1), a limit of detection of 1 × 10(3) CFU mL(-1), and a selectivity of >10-fold for STM in samples containing other bacteria at higher concentration with an assay time less than 3 h. In addition, the developed nanoprobes were improved in terms of detection range and/or sensitivity when compared with two commercial enzyme-labeled antibody signal reporters. Finally, the nano-ELAAS method was demonstrated to work well in milk samples, a common source of STM contamination.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits.

PubMed

Fu, Liya; Wang, You-Gan

2011-02-15

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which clearly demonstrates the advantages of the rank regression models.

Application of dispersive liquid-liquid microextraction for the preconcentration of eight parabens in real samples and their determination by high-performance liquid chromatography.

PubMed

Shen, Xiong; Liang, Jian; Zheng, Luxia; Lv, Qianzhou; Wang, Hong

2017-11-01

A simple and sensitive method for the simultaneous determination of eight parabens in human plasma and urine samples was developed. The samples were preconcentrated using dispersive liquid-liquid microextraction based on the solidification of floating organic drops and determined by high-performance liquid chromatography with ultraviolet detection. The influence of variables affecting the extraction efficiency was investigated and optimized using Placket-Burman design and Box-Behnken design. The optimized values were: 58 μL of 1-decanol (as extraction solvent), 0.65 mL methanol (as disperser solvent), 1.5% w/v NaCl in 5.0 mL of sample solution, pH 10.6, and 4.0 min centrifugation at 4000 rpm. The extract was injected into the high-performance liquid chromatography system for analysis. Under the optimum conditions, the linear ranges for eight parabens in plasma and urine were 1.0-1000 ng/mL, with correlation coefficients above 0.994. The limit of detection was 0.2-0.4 and 0.1-0.4 ng/mL for plasma and urine samples, respectively. Relative recoveries were between 80.3 and 110.7%, while relative standard deviations were less than 5.4%. Finally, the method was applied to analyze the parabens in 98 patients of primary breast cancer. Results showed that parabens existed widely, at least one paraben detected in 96.9% (95/98) of plasma samples and 98.0% (96/98) of urine samples. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Root Exploit Detection and Features Optimization: Mobile Device and Blockchain Based Medical Data Management.

PubMed

Firdaus, Ahmad; Anuar, Nor Badrul; Razak, Mohd Faizal Ab; Hashem, Ibrahim Abaker Targio; Bachok, Syafiq; Sangaiah, Arun Kumar

2018-05-04

The increasing demand for Android mobile devices and blockchain has motivated malware creators to develop mobile malware to compromise the blockchain. Although the blockchain is secure, attackers have managed to gain access into the blockchain as legal users, thereby comprising important and crucial information. Examples of mobile malware include root exploit, botnets, and Trojans and root exploit is one of the most dangerous malware. It compromises the operating system kernel in order to gain root privileges which are then used by attackers to bypass the security mechanisms, to gain complete control of the operating system, to install other possible types of malware to the devices, and finally, to steal victims' private keys linked to the blockchain. For the purpose of maximizing the security of the blockchain-based medical data management (BMDM), it is crucial to investigate the novel features and approaches contained in root exploit malware. This study proposes to use the bio-inspired method of practical swarm optimization (PSO) which automatically select the exclusive features that contain the novel android debug bridge (ADB). This study also adopts boosting (adaboost, realadaboost, logitboost, and multiboost) to enhance the machine learning prediction that detects unknown root exploit, and scrutinized three categories of features including (1) system command, (2) directory path and (3) code-based. The evaluation gathered from this study suggests a marked accuracy value of 93% with Logitboost in the simulation. Logitboost also helped to predicted all the root exploit samples in our developed system, the root exploit detection system (RODS).

An Improved Pathological Brain Detection System Based on Two-Dimensional PCA and Evolutionary Extreme Learning Machine.

PubMed

Nayak, Deepak Ranjan; Dash, Ratnakar; Majhi, Banshidhar

2017-12-07

Pathological brain detection has made notable stride in the past years, as a consequence many pathological brain detection systems (PBDSs) have been proposed. But, the accuracy of these systems still needs significant improvement in order to meet the necessity of real world diagnostic situations. In this paper, an efficient PBDS based on MR images is proposed that markedly improves the recent results. The proposed system makes use of contrast limited adaptive histogram equalization (CLAHE) to enhance the quality of the input MR images. Thereafter, two-dimensional PCA (2DPCA) strategy is employed to extract the features and subsequently, a PCA+LDA approach is used to generate a compact and discriminative feature set. Finally, a new learning algorithm called MDE-ELM is suggested that combines modified differential evolution (MDE) and extreme learning machine (ELM) for segregation of MR images as pathological or healthy. The MDE is utilized to optimize the input weights and hidden biases of single-hidden-layer feed-forward neural networks (SLFN), whereas an analytical method is used for determining the output weights. The proposed algorithm performs optimization based on both the root mean squared error (RMSE) and norm of the output weights of SLFNs. The suggested scheme is benchmarked on three standard datasets and the results are compared against other competent schemes. The experimental outcomes show that the proposed scheme offers superior results compared to its counterparts. Further, it has been noticed that the proposed MDE-ELM classifier obtains better accuracy with compact network architecture than conventional algorithms.

[Magnetic solid phase extraction combined with gas chromatography-flame photometric detection for the determination of organophosphorus pesticides in juice samples].

PubMed

Huang, Qian; He, Man; Chen, Beibei; Hu, Bin

2014-10-01

A novel method for the determination of organophosphorous pesticides (OPPs) in fresh juice samples was developed. Fe3O4 @ P (St-co-MAA) magnetic microparticles were synthesized and modified with styrene (St) and methacrylic acid (MAA) by coating St and MAA on magnetic particles and characterized by a series of techniques. The results indicated that Fe3 O4 magnetic nanoparticles (MNPs) have been successfully modified with St and MAA. Based on the prepared FeO4 @ P (St-co-MAA) magnetic microparticles, a novel method of magnetic solid phase extraction (MSPE)-gas chromatography (GC)-flame photometric detection (FPD) was developed for the determination of OPPs. The extraction/desorption conditions of MSPE were optimized, and the analytical performance was evaluated under the optimal conditions. The limits of detection (LODs, S/N = 3) for target OPPs were in the range of 0.013-0.305 μg/L with the RSDs (n = 7) ranging from 3.1% to 8.8%. The enrichment factors varied from 406 to 951. The linear ranges were over three orders of magnitudes (R2 > 0.99) and the reproducibilities were 7.4%-14.5% (n = 5). Finally, the proposed MSPE-GC-FPD method was successfully applied to the analysis of the five OPPs in fresh tomato and strawberry juice samples, with the recoveries of target OPPs in the range of 85.4%-118.9% for the spiked samples. The proposed MSPE-GC-FPD method is featured with low cost, fast separation and high enrichment factor.

Final screening round of the NELSON lung cancer screening trial: the effect of a 2.5-year screening interval.

PubMed

Yousaf-Khan, Uraujh; van der Aalst, Carlijn; de Jong, Pim A; Heuvelmans, Marjolein; Scholten, Ernst; Lammers, Jan-Willem; van Ooijen, Peter; Nackaerts, Kristiaan; Weenink, Carla; Groen, Harry; Vliegenthart, Rozemarijn; Ten Haaf, Kevin; Oudkerk, Matthijs; de Koning, Harry

2017-01-01

In the USA annual lung cancer screening is recommended. However, the optimal screening strategy (eg, screening interval, screening rounds) is unknown. This study provides results of the fourth screening round after a 2.5-year interval in the Dutch-Belgian Lung Cancer Screening trial (NELSON). Europe's largest, sufficiently powered randomised lung cancer screening trial was designed to determine whether low-dose CT screening reduces lung cancer mortality by ≥25% compared with no screening after 10 years of follow-up. The screening arm (n=7915) received screening at baseline, after 1 year, 2 years and 2.5 years. Performance of the NELSON screening strategy in the final fourth round was evaluated. Comparisons were made between lung cancers detected in the first three rounds, in the final round and during the 2.5-year interval. In round 4, 46 cancers were screen-detected and there were 28 interval cancers between the third and fourth screenings. Compared with the second round screening (1-year interval), in round 4 a higher proportion of stage IIIb/IV cancers (17.3% vs 6.8%, p=0.02) and higher proportions of squamous-cell, bronchoalveolar and small-cell carcinomas (p=0.001) were detected. Compared with a 2-year interval, the 2.5-year interval showed a higher non-significant stage distribution (stage IIIb/IV 17.3% vs 5.2%, p=0.10). Additionally, more interval cancers manifested in the 2.5-year interval than in the intervals of previous rounds (28 vs 5 and 28 vs 19). A 2.5-year interval reduced the effect of screening: the interval cancer rate was higher compared with the 1-year and 2-year intervals, and proportion of advanced disease stage in the final round was higher compared with the previous rounds. ISRCTN63545820. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Detecting Outliers in Marathon Data by Means of the Andrews Plot

NASA Astrophysics Data System (ADS)

Stehlík, Milan; Wald, Helmut; Bielik, Viktor; Petrovič, Juraj

2011-09-01

For an optimal race performance, it is important, that the runner keeps steady pace during most of the time of the competition. First time runners or athletes without many competitions often experience an "blow out" after a few kilometers of the race. This could happen, because of strong emotional experiences or low control of running intensity. Competition pace of half marathon of the middle level recreational athletes is approximately 10 sec quicker than their training pace. If an athlete runs the first third of race (7 km) at a pace that is 20 sec quicker than is his capacity (trainability), he would experience an "blow out" in the last third of the race. This would be reflected by reducing the running intensity and inability to keep steady pace in the last kilometers of the race and in the final time as well. In sports science, there are many diagnostic methods ([3], [2], [6]) that are used for prediction of optimal race pace tempo and final time. Otherwise there is lacking practical evidence of diagnostics methods and its use in the field (competition, race). One of the conditions that needs to be carried out is that athletes have not only similar final times, but it is important that they keep constant pace as much as possible during whole race. For this reason it is very important to find outliers. Our experimental group consisted of 20 recreational trained athletes (mean age 32,6 years±8,9). Before the race the athletes were instructed to run on the basis of their subjective feeling and previous experience. The data (running pace of each kilometer, average and maximal heart rate of each kilometer) were collected by GPS-enabled personal trainer Forerunner 305.

Three-Dimensional Viscous Alternating Direction Implicit Algorithm and Strategies for Shape Optimization

NASA Technical Reports Server (NTRS)

Pandya, Mohagna J.; Baysal, Oktay

1997-01-01

A gradient-based shape optimization based on quasi-analytical sensitivities has been extended for practical three-dimensional aerodynamic applications. The flow analysis has been rendered by a fully implicit, finite-volume formulation of the Euler and Thin-Layer Navier-Stokes (TLNS) equations. Initially, the viscous laminar flow analysis for a wing has been compared with an independent computational fluid dynamics (CFD) code which has been extensively validated. The new procedure has been demonstrated in the design of a cranked arrow wing at Mach 2.4 with coarse- and fine-grid based computations performed with Euler and TLNS equations. The influence of the initial constraints on the geometry and aerodynamics of the optimized shape has been explored. Various final shapes generated for an identical initial problem formulation but with different optimization path options (coarse or fine grid, Euler or TLNS), have been aerodynamically evaluated via a common fine-grid TLNS-based analysis. The initial constraint conditions show significant bearing on the optimization results. Also, the results demonstrate that to produce an aerodynamically efficient design, it is imperative to include the viscous physics in the optimization procedure with the proper resolution. Based upon the present results, to better utilize the scarce computational resources, it is recommended that, a number of viscous coarse grid cases using either a preconditioned bi-conjugate gradient (PbCG) or an alternating-direction-implicit (ADI) method, should initially be employed to improve the optimization problem definition, the design space and initial shape. Optimized shapes should subsequently be analyzed using a high fidelity (viscous with fine-grid resolution) flow analysis to evaluate their true performance potential. Finally, a viscous fine-grid-based shape optimization should be conducted, using an ADI method, to accurately obtain the final optimized shape.

An iterative approach to optimize change classification in SAR time series data

NASA Astrophysics Data System (ADS)

Boldt, Markus; Thiele, Antje; Schulz, Karsten; Hinz, Stefan

2016-10-01

The detection of changes using remote sensing imagery has become a broad field of research with many approaches for many different applications. Besides the simple detection of changes between at least two images acquired at different times, analyses which aim on the change type or category are at least equally important. In this study, an approach for a semi-automatic classification of change segments is presented. A sparse dataset is considered to ensure the fast and simple applicability for practical issues. The dataset is given by 15 high resolution (HR) TerraSAR-X (TSX) amplitude images acquired over a time period of one year (11/2013 to 11/2014). The scenery contains the airport of Stuttgart (GER) and its surroundings, including urban, rural, and suburban areas. Time series imagery offers the advantage of analyzing the change frequency of selected areas. In this study, the focus is set on the analysis of small-sized high frequently changing regions like parking areas, construction sites and collecting points consisting of high activity (HA) change objects. For each HA change object, suitable features are extracted and a k-means clustering is applied as the categorization step. Resulting clusters are finally compared to a previously introduced knowledge-based class catalogue, which is modified until an optimal class description results. In other words, the subjective understanding of the scenery semantics is optimized by the data given reality. Doing so, an even sparsely dataset containing only amplitude imagery can be evaluated without requiring comprehensive training datasets. Falsely defined classes might be rejected. Furthermore, classes which were defined too coarsely might be divided into sub-classes. Consequently, classes which were initially defined too narrowly might be merged. An optimal classification results when the combination of previously defined key indicators (e.g., number of clusters per class) reaches an optimum.

Electromembrane extraction of gonadotropin-releasing hormone agonists from plasma and wastewater samples.

PubMed

Nojavan, Saeed; Bidarmanesh, Tina; Mohammadi, Ali; Yaripour, Saeid

2016-03-01

In the present study, for the first time electromembrane extraction followed by high performance liquid chromatography coupled with ultraviolet detection was optimized and validated for quantification of four gonadotropin-releasing hormone agonist anticancer peptides (alarelin, leuprolide, buserelin and triptorelin) in biological and aqueous samples. The parameters influencing electromigration were investigated and optimized. The membrane consists 95% of 1-octanol and 5% di-(2-ethylhexyl)-phosphate immobilized in the pores of a hollow fiber. A 20 V electrical field was applied to make the analytes migrate from sample solution with pH 7.0, through the supported liquid membrane into an acidic acceptor solution with pH 1.0 which was located inside the lumen of hollow fiber. Extraction recoveries in the range of 49 and 71% within 15 min extraction time were obtained in different biological matrices which resulted in preconcentration factors in the range of 82-118 and satisfactory repeatability (7.1 < RSD% < 19.8). The method offers good linearity (2.0-1000 ng/mL) with estimation of regression coefficient higher than 0.998. The procedure allows very low detection and quantitation limits of 0.2 and 0.6 ng/mL, respectively. Finally, it was applied to determination and quantification of peptides in human plasma and wastewater samples and satisfactory results were yielded. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Numerical and experimental analysis of high frequency acoustic microscopy and infrared reflectance system for early detection of melanoma

NASA Astrophysics Data System (ADS)

Karagiannis, Georgios; Apostolidis, Georgios; Georgoulias, Panagiotis

2016-03-01

Melanoma is a very malicious type of cancer as it metastasizes early and hence its late diagnosis leads to death. Consequently, early diagnosis of melanoma and its removal is considered the most effective way of treatment. We present a design of a high frequency acoustic microscopy and infrared reflectance system for the early detection of melanoma. Specifically, the identification of morphological changes related to carcinogenesis is required. In this work, we simulate of the propagation of the ultrasonic waves of the order of 100 MHz as well as of electromagnetic waves of the order of 100 THz in melanoma structures targeting to the estimation and optimization of the basic characteristics of the systems. The simulation results of the acoustic microscopy subsystem aim to provide information such as the geometry of the transducer, the center frequency of operation, the focal length where the power transmittance is optimum and the spot size in focal length. As far as the infrared is concerned the optimal frequency range and the spot illumination size of the external probe is provided. This information is next used to assemble a properly designed system which is applied to melanoma phantoms as well as real skin lesions. Finally, the measurement data are visualized to reveal the information of the experimented structures, proving noteworthy accuracy.

A dispersive liquid-liquid micellar microextraction for the determination of pharmaceutical compounds in wastewaters using ultra-high-performace liquid chromatography with DAD detection.

PubMed

Montesdeoca-Esponda, Sarah; Mahugo-Santana, Cristina; Sosa-Ferrera, Zoraida; Santana-Rodríguez, José Juan

2015-03-01

A dispersive liquid-liquid micellar microextraction (DLLMME) method coupled with ultra-high-performance liquid chromatography (UHPLC) using Diode Array Detector (DAD) detector was developed for the analysis of five pharmaceutical compounds of different nature in wastewaters. A micellar solution of a surfactant, polidocanol, as extraction solvent (100 μL) and chloroform as dispersive solvent (200 μL) were used to extract and preconcentrate the target analytes. Samples were heated above critical temperature and the cloudy solution was centrifuged. After removing the chloroform, the reduced volume of surfactant was then injected in the UHPLC system. In order to obtain high extraction efficiency, the parameters affecting the liquid-phase microextraction, such as time and temperature extraction, ionic strength and surfactant and organic solvent volume, were optimized using an experimental design. Under the optimized conditions, this procedure allows enrichment factors of up to 47-fold. The detection limit of the method ranged from 0.1 to 2.0 µg/L for the different pharmaceuticals. Relative standard deviations were <26% for all compounds. The procedure was applied to samples from final effluent collected from wastewater treatment plants in Las Palmas de Gran Canaria (Spain), and two compounds were measured at 67 and 113 µg/L in one of them. Copyright © 2014 John Wiley & Sons, Ltd.

Sensitive determination of estrogens in environmental waters treated with polymeric ionic liquid-based stir cake sorptive extraction and liquid chromatographic analysis.

PubMed

Chen, Lei; Mei, Meng; Huang, Xiaojia; Yuan, Dongxing

2016-05-15

A simple, sensitive and environmentally friendly method using polymeric ionic liquid-based stir cake sorptive extraction followed by high performance liquid chromatography with diode array detection (HPLC/DAD) has been developed for efficient quantification of six selected estrogens in environmental waters. To extract trace estrogens effectively, a poly (1-ally-3-vinylimidazolium chloride-co-ethylene dimethacrylate) monolithic cake was prepared and used as the sorbent of stir cake sorptive extraction (SCSE). The effects of preparation conditions of sorbent and extraction parameters of SCSE for estrogens were investigated and optimized. Under optimal conditions, the developed method showed satisfactory analytical performance for targeted analytes. Low limits of detection (S/N=3) and quantification limits (S/N=10) were achieved within the range of 0.024-0.057 µg/L and 0.08-0.19 µg/L, respectively. Good linearity of method was obtained for analytes with the correlation coefficients (R(2)) above 0.99. At the same time, satisfactory method repeatability and reproducibility was achieved in terms of intra- and inter-day precisions, respectively. Finally, the established SCSE-HPLC/DAD method was successfully applied for the determination of estrogens in different environmental water samples. Recoveries obtained for the determination of estrogens in spiked samples ranged from 71.2% to 108%, with RSDs below 10% in all cases. Copyright © 2016 Elsevier B.V. All rights reserved.

Multivariate Approach for Alzheimer's Disease Detection Using Stationary Wavelet Entropy and Predator-Prey Particle Swarm Optimization.

PubMed

Zhang, Yudong; Wang, Shuihua; Sui, Yuxiu; Yang, Ming; Liu, Bin; Cheng, Hong; Sun, Junding; Jia, Wenjuan; Phillips, Preetha; Gorriz, Juan Manuel

2017-07-17

The number of patients with Alzheimer's disease is increasing rapidly every year. Scholars often use computer vision and machine learning methods to develop an automatic diagnosis system. In this study, we developed a novel machine learning system that can make diagnoses automatically from brain magnetic resonance images. First, the brain imaging was processed, including skull stripping and spatial normalization. Second, one axial slice was selected from the volumetric image, and stationary wavelet entropy (SWE) was done to extract the texture features. Third, a single-hidden-layer neural network was used as the classifier. Finally, a predator-prey particle swarm optimization was proposed to train the weights and biases of the classifier. Our method used 4-level decomposition and yielded 13 SWE features. The classification yielded an overall accuracy of 92.73±1.03%, a sensitivity of 92.69±1.29%, and a specificity of 92.78±1.51%. The area under the curve is 0.95±0.02. Additionally, this method only cost 0.88 s to identify a subject in online stage, after its volumetric image is preprocessed. In terms of classification performance, our method performs better than 10 state-of-the-art approaches and the performance of human observers. Therefore, this proposed method is effective in the detection of Alzheimer's disease.

Simultaneous enantioselective determination of six pesticides in aqueous environmental samples by chiral liquid chromatography with tandem mass spectrometry.

PubMed

Zhao, Pengfei; Lei, Shuo; Xing, Mingming; Xiong, Shihang; Guo, Xingjie

2018-03-01

A robust and sensitive method was developed for the enantiomeric analysis of six chiral pesticides (including metalaxyl, epoxiconazole, myclobutanil, hexaconazole, napropamide, and isocarbophos) in aquatic environmental samples. The optimized chromatographic conditions for the quantification of all the 12 enantiomers were performed with Chiralcel OD-RH column using mobile phase consisting of 0.1% aqueous formic acid and acetonitrile operated under reversed-phase conditions and then analyzed using liquid chromatography with tandem mass spectrometry. Twelve enantiomers were detected in multiple reaction monitoring mode. Solid-phase extraction and dispersive liquid-liquid microextraction were employed in this study. Response surface methodology was applied to assist in the dispersive liquid-liquid microextraction optimization. Under the optimum conditions, recoveries of pesticides enantiomers varied from 83.0 to 103.2% at two spiked levels with relative standard deviation less than 11.5%. The concentration factors were up to 1000 times. Method detection and quantification limits varied from 0.11 to 0.48 ng/L and from 0.46 to 1.49 ng/L, respectively. Finally, this method was used to determination of the enantiomers composition of the six pesticides in environmental aqueous matrices, which will help better understand the behavior of individual enantiomer and make accurate risk assessment to ecosystems. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Fault Tolerance Mechanism for On-Road Sensor Networks

PubMed Central

Feng, Lei; Guo, Shaoyong; Sun, Jialu; Yu, Peng; Li, Wenjing

2016-01-01

On-Road Sensor Networks (ORSNs) play an important role in capturing traffic flow data for predicting short-term traffic patterns, driving assistance and self-driving vehicles. However, this kind of network is prone to large-scale communication failure if a few sensors physically fail. In this paper, to ensure that the network works normally, an effective fault-tolerance mechanism for ORSNs which mainly consists of backup on-road sensor deployment, redundant cluster head deployment and an adaptive failure detection and recovery method is proposed. Firstly, based on the N − x principle and the sensors’ failure rate, this paper formulates the backup sensor deployment problem in the form of a two-objective optimization, which explains the trade-off between the cost and fault resumption. In consideration of improving the network resilience further, this paper introduces a redundant cluster head deployment model according to the coverage constraint. Then a common solving method combining integer-continuing and sequential quadratic programming is explored to determine the optimal location of these two deployment problems. Moreover, an Adaptive Detection and Resume (ADR) protocol is deigned to recover the system communication through route and cluster adjustment if there is a backup on-road sensor mismatch. The final experiments show that our proposed mechanism can achieve an average 90% recovery rate and reduce the average number of failed sensors at most by 35.7%. PMID:27918483

Application of a cholesterol stationary phase in the analysis of phosphorothioate oligonucleotides by means of ion pair chromatography coupled with tandem mass spectrometry.

PubMed

Studzińska, Sylwia; Krzemińska, Katarzyna; Szumski, Michał; Buszewski, Bogusław

2016-07-01

The main aim of this study was the investigation of the influence of several ion pair reagents towards both the retention and the mass spectrometry sensitivity of phosphorothioate oligonucleotides. A cholesterol stationary phase was applied for the first time in the analysis of this group of compounds. The mobile phase composition was modified by changing the concentration and the type of amines and acetates or 1,1,1,3,3,3-hexafluoroisopropanol. It has been shown that the increase of amines concentration results in the retention factor increase for each oligonucleotide, on each adsorbent. The only exception was the mobile phase composed of triethylamine and 1,1,1,3,3,3-hexafluoroisopropanol. This is a consequence of interactions taking place between a cholesterol molecule and an alcohol. This effect was convenient when the mass spectrometry detection was applied, since it allowed an increase in the sensitivity. Moreover, optimization of the mobile phase composition and its impact on the efficiency of ionization process and on the sensitivity in mass spectrometry were also presented. The optimization of this new method, based on cholesterol stationary phase coupled with mass spectrometry detection, was finally applied for the determination of phosphorothioate oligonucleotides impurity in a real sample. Copyright © 2016 Elsevier B.V. All rights reserved.

Singular-Arc Time-Optimal Trajectory of Aircraft in Two-Dimensional Wind Field

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2006-01-01

This paper presents a study of a minimum time-to-climb trajectory analysis for aircraft flying in a two-dimensional altitude dependent wind field. The time optimal control problem possesses a singular control structure when the lift coefficient is taken as a control variable. A singular arc analysis is performed to obtain an optimal control solution on the singular arc. Using a time-scale separation with the flight path angle treated as a fast state, the dimensionality of the optimal control solution is reduced by eliminating the lift coefficient control. A further singular arc analysis is used to decompose the original optimal control solution into the flight path angle solution and a trajectory solution as a function of the airspeed and altitude. The optimal control solutions for the initial and final climb segments are computed using a shooting method with known starting values on the singular arc The numerical results of the shooting method show that the optimal flight path angle on the initial and final climb segments are constant. The analytical approach provides a rapid means for analyzing a time optimal trajectory for aircraft performance.

Optimal Detection of Global Warming using Temperature Profiles

NASA Technical Reports Server (NTRS)

Leroy, Stephen S.

1997-01-01

Optimal fingerprinting is applied to estimate the amount of time it would take to detect warming by increased concentrations of carbon dioxide in monthly averages of temperature profiles over the Indian Ocean.

Model-Based Design of Tree WSNs for Decentralized Detection.

PubMed

Tantawy, Ashraf; Koutsoukos, Xenofon; Biswas, Gautam

2015-08-20

The classical decentralized detection problem of finding the optimal decision rules at the sensor and fusion center, as well as variants that introduce physical channel impairments have been studied extensively in the literature. The deployment of WSNs in decentralized detection applications brings new challenges to the field. Protocols for different communication layers have to be co-designed to optimize the detection performance. In this paper, we consider the communication network design problem for a tree WSN. We pursue a system-level approach where a complete model for the system is developed that captures the interactions between different layers, as well as different sensor quality measures. For network optimization, we propose a hierarchical optimization algorithm that lends itself to the tree structure, requiring only local network information. The proposed design approach shows superior performance over several contentionless and contention-based network design approaches.

Impulsive time-free transfers between halo orbits

NASA Astrophysics Data System (ADS)

Hiday, L. A.; Howell, K. C.

1992-08-01

A methodology is developed to design optimal time-free impulsive transfers between three-dimensional halo orbits in the vicinity of the interior L1 libration point of the sun-earth/moon barycenter system. The transfer trajectories are optimal in the sense that the total characteristics velocity required to implement the transfer exhibits a local minimum. Criteria are established whereby the implementation of a coast in the initial orbit, a coast in the final orbit, or dual coasts accomplishes a reduction in fuel expenditure. The optimality of a reference two-impulse transfer can be determined by examining the slope at the endpoints of a plot of the magnitude of the primer vector on the reference trajectory. If the initial and final slopes of the primer magnitude are zero, the transfer trajectory is optimal; otherwise, the execution of coasts is warranted. The optimal time of flight on the time-free transfer, and consequently, the departure and arrival locations on the halo orbits are determined by the unconstrained minimization of a function of two variables using a multivariable search technique. Results indicate that the cost can be substantially diminished by the allowance for coasts in the initial and final libration-point orbits.

Impulsive Time-Free Transfers Between Halo Orbits

NASA Astrophysics Data System (ADS)

Hiday-Johnston, L. A.; Howell, K. C.

1996-12-01

A methodology is developed to design optimal time-free impulsive transfers between three-dimensional halo orbits in the vicinity of the interior L 1 libration point of the Sun-Earth/Moon barycenter system. The transfer trajectories are optimal in the sense that the total characteristic velocity required to implement the transfer exhibits a local minimum. Criteria are established whereby the implementation of a coast in the initial orbit, a coast in the final orbit, or dual coasts accomplishes a reduction in fuel expenditure. The optimality of a reference two-impulse transfer can be determined by examining the slope at the endpoints of a plot of the magnitude of the primer vector on the reference trajectory. If the initial and final slopes of the primer magnitude are zero, the transfer trajectory is optimal; otherwise, the execution of coasts is warranted. The optimal time of flight on the time-free transfer, and consequently, the departure and arrival locations on the halo orbits are determined by the unconstrained minimization of a function of two variables using a multivariable search technique. Results indicate that the cost can be substantially diminished by the allowance for coasts in the initial and final libration-point orbits.

Comparison of conventional and sensor-based electronic stethoscopes in detecting cardiac murmurs of dogs.

PubMed

Vörös, K; Bonnevie, A; Reiczigel, J

2012-04-24

Cardiac auscultation is one of the most important parts of the cardiological examination traditionally performed with acoustic stethoscopes. The aim of this study was to compare the sensitivities and the diagnostic capabilities of traditional and electronic stethoscopes in detecting canine heart murmurs. The study was performed on 21 dogs referred for cardiologic examination with suspected heart murmurs. Six out of these dogs had cardiac murmurs bilaterally. Cardiac auscultation was performed independently by a final-year veterinary student (AB=I1) and by an experienced clinician (KV=I2), both using a traditional and a Welch Allyn Meditron electronic sensor-based stethoscope. Final diagnoses were established by echocardiography and by digital phonocardiography. Correct detection of a murmur was made by I1 with a traditional stethoscope in 20/27 (74.0%) of the suspected murmurs (p=0.30, kappa[κ] =0.2) and with the electronic stethoscope in 26/27 (96.3%), respectively (p=0.0013, κ=0.75). I2 correctly detected the murmurs with the traditional stethoscope in 25/27 (92.6%) cases (p=0.0013, κ=0.75) and with the electronic stethoscope in all 27/27 (100%) cases (p=0.00012, κ=1). Agreements of murmur intensity gradings between traditional and electronic stethoscopes were highly significant (I1: p=6.9´10⁻⁸; κ=0.79), (I2: p=5.2´10⁻¹¹; κ=0.92). When grading the murmurs with the traditional stethoscope, there was a significant agreement between I1 and I2 (p=2.9´10⁻⁷; κ=0.79), being even higher with the electronic stethoscope (p=1.1´10⁻¹¹; κ=0.92). The electronic stethoscope was more sensitive than the traditional one in detecting and grading cardiac murmurs being especially useful for I1 with less experience. However, it can be suggested to use a traditional and an electronic stethoscopes simultaneously to optimally utilize their advantages.

Towards radiation hard converter material for SiC-based fast neutron detectors

NASA Astrophysics Data System (ADS)

Tripathi, S.; Upadhyay, C.; Nagaraj, C. P.; Venkatesan, A.; Devan, K.

2018-05-01

In the present work, Geant4 Monte-Carlo simulations have been carried out to study the neutron detection efficiency of the various neutron to other charge particle (recoil proton) converter materials. The converter material is placed over Silicon Carbide (SiC) in Fast Neutron detectors (FNDs) to achieve higher neutron detection efficiency as compared to bare SiC FNDs. Hydrogenous converter material such as High-Density Polyethylene (HDPE) is preferred over other converter materials due to the virtue of its high elastic scattering reaction cross-section for fast neutron detection at room temperature. Upon interaction with fast neutrons, hydrogenous converter material generates recoil protons which liberate e-hole pairs in the active region of SiC detector to provide a detector signal. The neutron detection efficiency offered by HDPE converter is compared with several other hydrogenous materials viz., 1) Lithium Hydride (LiH), 2) Perylene, 3) PTCDA . It is found that, HDPE, though providing highest efficiency among various studied materials, cannot withstand high temperature and harsh radiation environment. On the other hand, perylene and PTCDA can sustain harsh environments, but yields low efficiency. The analysis carried out reveals that LiH is a better material for neutron to other charge particle conversion with competent efficiency and desired radiation hardness. Further, the thickness of LiH has also been optimized for various mono-energetic neutron beams and Am-Be neutron source generating a neutron fluence of 109 neutrons/cm2. The optimized thickness of LiH converter for fast neutron detection is found to be ~ 500 μm. However, the estimated efficiency for fast neutron detection is only 0.1%, which is deemed to be inadequate for reliable detection of neutrons. A sensitivity study has also been done investigating the gamma background effect on the neutron detection efficiency for various energy threshold of Low-Level Discriminator (LLD). The detection efficiency of a stacked structure concept has been explored by juxtaposing several converter-detector layers to improve the efficiency of LiH-SiC-based FNDs . It is observed that approximately tenfold efficiency improvement has been achieved—0.93% for ten layers stacked configuration vis-à-vis 0.1% of single converter-detector layer configuration. Finally, stacked detectors have also been simulated for different converter thicknesses to attain the efficiency as high as ~ 3.25% with the help of 50 stacked layers.

Magnetoresistive immunosensor for the detection of Escherichia coli O157:H7 including a microfluidic network.

PubMed

Mujika, M; Arana, S; Castaño, E; Tijero, M; Vilares, R; Ruano-López, J M; Cruz, A; Sainz, L; Berganza, J

2009-01-01

A hand held device has been designed for the immunomagnetic detection and quantification of the pathogen Escherichia coli O157:H7 in food and clinical samples. In this work, a technology to manufacture a Lab on a Chip that integrates a 3D microfluidic network with a microfabricated biosensor has been developed. With this aim, the sensing film optimization, the design of the microfluidic circuitry, the development of the biological protocols involved in the measurements and, finally, the packaging needed to carry out the assays in a safe and straightforward way have been completed. The biosensor is designed to be capable to detect and quantify small magnetic field variations caused by the presence of superparamagnetic beads bound to the antigens previously immobilized on the sensor surface via an antibody-antigen reaction. The giant magnetoresistive multilayer structure implemented as sensing film consists of 20[Cu(5.10nm)/Co(2.47 nm)] with a magnetoresistance of 3.20% at 235Oe and a sensitivity up to 0.06 Omega/Oe between 150Oe and 230Oe. Silicon nitride has been selected as optimum sensor surface coating due to its suitability for antibody immobilization. In order to guide the biological samples towards the sensing area, a microfluidic network made of SU-8 photoresist has been included. Finally, a novel packaging design has been fabricated employing 3D stereolithographic techniques. The microchannels are connected to the outside using standard tubing. Hence, this packaging allows an easy replacement of the used devices.

Factorial-design optimization of gas chromatographic analysis of tetrabrominated to decabrominated diphenyl ethers. Application to domestic dust.

PubMed

Regueiro, Jorge; Llompart, Maria; Garcia-Jares, Carmen; Cela, Rafael

2007-07-01

Gas chromatographic analysis of polybrominated diphenyl ethers (PBDEs) has been evaluated in an attempt to achieve better control of the separation process, especially for highly substituted congeners. Use of a narrow-bore capillary column enabled adequate determination of tetra, penta, hexa, hepta, octa, nona and decaBDE congeners in only one chromatographic run while maintaining resolution power similar to that of conventional columns. A micro electron-capture detector (GC-microECD) was used. Chromatographic conditions were optimized by multifactorial experimental design, with the objective of obtaining not only high sensitivity but also good precision. In this way two different approaches to maximizing response and minimizing variability were tested, and are fully discussed. These optimum chromatographic conditions were then used to determine PBDEs extracted from domestic dust samples by microwave-assisted solvent extraction (MASE). Quantitative recovery (90-108%) was achieved for all the PBDEs and method precision (RSD < 13%) was satisfactory. Accuracy was tested by use of the standard reference material SRM 2585, and sub-ng g(-1) limits of detection were obtained for all compounds except BDE-209 (1.44 ng g(-1)). Finally, several samples of house dust were analysed by use of the proposed method and all the target PBDEs were detected in all the samples. BDE-209 was the predominant congener. Amounts varied from 58 to 1615 ng g(-1) and the average contribution to the total PBDE burden of 52%. The main congeners of the octaBDE mixture (BDE-183, BDE-197, BDE-207 and BDE-196) also made an important contribution (29%) to the total. These are the first data about the presence of these compounds in European house-dust samples. Finally, the sum of the main congeners in the pentaBDE commercial mixture (BDE-47, BDE-99, and BDE-100) contributed 14% to the total. Figure Polybrominated diphenyl ethers in House Dust.

Microwave synthesis of gibberellin acid 3 magnetic molecularly imprinted polymer beads for the trace analysis of gibberellin acids in plant samples by liquid chromatography-mass spectrometry detection.

PubMed

Zhang, Zhuomin; Tan, Wei; Hu, Yuling; Li, Gongke; Zan, Song

2012-02-21

In this study, novel GA3 magnetic molecularly imprinted polymer (mag-MIP) beads were synthesized by a microwave irradiation method, and the beads were applied for the trace analysis of gibberellin acids (GAs) in plant samples including rice and cucumber coupled with high performance liquid chromatography-mass spectrometry (HPLC-MS). The microwave synthetic procedure was optimized in detail. In particular, the interaction between GA3 and functional monomers was further studied for the selection of the optimal functional monomers during synthesis. It can be seen that the interaction between GA3 and acrylamide (AM) finally selected was stronger than that between GA3 and other functional monomers. GA3 mag-MIP beads were characterized by a series of physical tests. GA3 mag-MIP beads had a porous and homogeneous surface morphology with stable chemical, thermal and magnetic properties. Moreover, GA3 mag-MIP beads demonstrated selective and specific absorption behavior for the target compounds during unsaturated extraction, which resulted in a higher extraction capacity (∼708.4 pmol for GA3) and selectivity than GA3 mag-non-imprinted polymer beads. Finally, an analytical method of GA3 mag-AM-MIP bead extraction coupled with HPLC-MS detection was established and applied for the determination of trace GA1, GA3, GA4 and GA7 in rice and cucumber samples. It was satisfactory that GA4 could be actually found to be 121.5 ± 1.4 μg kg(-1) in real rice samples by this novel analytical method. The recoveries of spiked rice and cucumber samples were found to be 76.0-109.1% and 79.9-93.6% with RSDs of 2.8-8.8% and 3.1-7.7% (n = 3), respectively. The proposed method is efficient and applicable for the trace analysis of GAs in complicated plant samples.

Application of loop-mediated isothermal amplification assay in the detection of herpesvirus of turkey (FC 126 strain) from chicken samples in Nigeria

PubMed Central

Adedeji, A. J.; Abdu, P. A.; Luka, P. D.; Owoade, A. A.; Joannis, T. M.

2017-01-01

Aim: This study was designed to optimize and apply the use of loop-mediated isothermal amplification (LAMP) as an alternative to conventional polymerase chain reaction (PCR) for the detection of herpesvirus of turkeys (HVT) (FC 126 strain) in vaccinated and non-vaccinated poultry in Nigeria. Materials and Methods: HVT positive control (vaccine) was used for optimization of LAMP using six primers that target the HVT070 gene sequence of the virus. These primers can differentiate HVT, a Marek’s disease virus (MDV) serotype 3 from MDV serotypes 1 and 2. Samples were collected from clinical cases of Marek’s disease (MD) in chickens, processed and subjected to LAMP and PCR. Results: LAMP assay for HVT was optimized. HVT was detected in 60% (3/5) and 100% (5/5) of the samples analyzed by PCR and LAMP, respectively. HVT was detected in the feathers, liver, skin, and spleen with average DNA purity of 3.05-4.52 μg DNA/mg (A260/A280) using LAMP. Conventional PCR detected HVT in two vaccinated and one unvaccinated chicken samples, while LAMP detected HVT in two vaccinated and three unvaccinated corresponding chicken samples. However, LAMP was a faster and simpler technique to carry out than PCR. Conclusion: LAMP assay for the detection of HVT was optimized. LAMP and PCR detected HVT in clinical samples collected. LAMP assay can be a very good alternative to PCR for detection of HVT and other viruses. This is the first report of the use of LAMP for the detection of viruses of veterinary importance in Nigeria. LAMP should be optimized as a diagnostic and research tool for investigation of poultry diseases such as MD in Nigeria. PMID:29263603

High Grazing Angle Sea-Clutter Literature Review

DTIC Science & Technology

2013-03-01

Optimal and sub-optimal detection .................................................................... 37 7.3 Polarimetry ... polarimetry for target detection from high grazing angles. UNCLASSIFIED DSTO-GD-0736 UNCLASSIFIED 36 7.1 Parametric modelling There have not been...relationships were also found to be intrinsically related to Gaussian detection counterparts. 7.3 Polarimetry Early studies by Stacy et al. [45, 46] and

Optimal detection and control strategies for invasive species management

Treesearch

Shefali V. Mehta; Robert G. Haight; Frances R. Homans; Stephen Polasky; Robert C. Venette

2007-01-01

The increasing economic and environmental losses caused by non-native invasive species amplify the value of identifying and implementing optimal management options to prevent, detect, and control invasive species. Previous literature has focused largely on preventing introductions of invasive species and post-detection control activities; few have addressed the role of...

Optimal Attack Strategies Subject to Detection Constraints Against Cyber-Physical Systems

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

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

This paper studies an attacker against a cyberphysical system (CPS) whose goal is to move the state of a CPS to a target state while ensuring that his or her probability of being detected does not exceed a given bound. The attacker’s probability of being detected is related to the nonnegative bias induced by his or her attack on the CPS’s detection statistic. We formulate a linear quadratic cost function that captures the attacker’s control goal and establish constraints on the induced bias that reflect the attacker’s detection-avoidance objectives. When the attacker is constrained to be detected at the false-alarmmore » rate of the detector, we show that the optimal attack strategy reduces to a linear feedback of the attacker’s state estimate. In the case that the attacker’s bias is upper bounded by a positive constant, we provide two algorithms – an optimal algorithm and a sub-optimal, less computationally intensive algorithm – to find suitable attack sequences. Lastly, we illustrate our attack strategies in numerical examples based on a remotely-controlled helicopter under attack.« less

Optimal Attack Strategies Subject to Detection Constraints Against Cyber-Physical Systems

DOE PAGES

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

2017-03-31

This paper studies an attacker against a cyberphysical system (CPS) whose goal is to move the state of a CPS to a target state while ensuring that his or her probability of being detected does not exceed a given bound. The attacker’s probability of being detected is related to the nonnegative bias induced by his or her attack on the CPS’s detection statistic. We formulate a linear quadratic cost function that captures the attacker’s control goal and establish constraints on the induced bias that reflect the attacker’s detection-avoidance objectives. When the attacker is constrained to be detected at the false-alarmmore » rate of the detector, we show that the optimal attack strategy reduces to a linear feedback of the attacker’s state estimate. In the case that the attacker’s bias is upper bounded by a positive constant, we provide two algorithms – an optimal algorithm and a sub-optimal, less computationally intensive algorithm – to find suitable attack sequences. Lastly, we illustrate our attack strategies in numerical examples based on a remotely-controlled helicopter under attack.« less

Development of Rapid Detection and Genetic Characterization of Salmonella in Poultry Breeder Feeds

PubMed Central

Jarquin, Robin; Hanning, Irene; Ahn, Soohyoun; Ricke, Steven C.

2009-01-01

Salmonella is a leading cause of foodborne illness in the United States, with poultry and poultry products being a primary source of infection to humans. Poultry may carry some Salmonella serovars without any signs or symptoms of disease and without causing any adverse effects to the health of the bird. Salmonella may be introduced to a flock by multiple environmental sources, but poultry feed is suspected to be a leading source. Detecting Salmonella in feed can be challenging because low levels of the bacteria may not be recovered using traditional culturing techniques. Numerous detection methodologies have been examined over the years for quantifying Salmonella in feeds and many have proven to be effective for Salmonella isolation and detection in a variety of feeds. However, given the potential need for increased detection sensitivity, molecular detection technologies may the best candidate for developing rapid sensitive methods for identifying small numbers of Salmonella in the background of large volumes of feed. Several studies have been done using polymerase chain reaction (PCR) assays and commercial kits to detect Salmonella spp. in a wide variety of feed sources. In addition, DNA array technology has recently been utilized to track the dissemination of a specific Salmonella serotype in feed mills. This review will discuss the processing of feeds and potential points in the process that may introduce Salmonella contamination to the feed. Detection methods currently used and the need for advances in these methods also will be discussed. Finally, implementation of rapid detection for optimizing control methods to prevent and remove any Salmonella contamination of feeds will be considered. PMID:22346699

Comparison of methods for the detection of coliphages in recreational water at two California, United States beaches.

PubMed

Rodríguez, Roberto A; Love, David C; Stewart, Jill R; Tajuba, Julianne; Knee, Jacqueline; Dickerson, Jerold W; Webster, Laura F; Sobsey, Mark D

2012-04-01

Methods for detection of two fecal indicator viruses, F+ and somatic coliphages, were evaluated for application to recreational marine water. Marine water samples were collected during the summer of 2007 in Southern California, United States from transects along Avalon Beach (n=186 samples) and Doheny Beach (n=101 samples). Coliphage detection methods included EPA method 1601 - two-step enrichment (ENR), EPA method 1602 - single agar layer (SAL), and variations of ENR. Variations included comparison of two incubation times (overnight and 5-h incubation) and two final detection steps (lysis zone assay and a rapid latex agglutination assay). A greater number of samples were positive for somatic and F+ coliphages by ENR than by SAL (p<0.01). The standard ENR with overnight incubation and detection by lysis zone assay was the most sensitive method for the detection of F+ and somatic coliphages from marine water, although the method takes up to three days to obtain results. A rapid 5-h enrichment version of ENR also performed well, with more positive samples than SAL, and could be performed in roughly 24h. Latex agglutination-based detection methods require the least amount of time to perform, although the sensitivity was less than lysis zone-based detection methods. Rapid culture-based enrichment of coliphages in marine water may be possible by further optimizing culture-based methods for saline water conditions to generate higher viral titers than currently available, as well as increasing the sensitivity of latex agglutination detection methods. Copyright © 2012 Elsevier B.V. All rights reserved.

Optimization of an enhanced ceramic micro-filter for concentrating E.coli in water

NASA Astrophysics Data System (ADS)

Zhang, Yushan; Guo, Tianyi; Xu, Changqing; Hong, Lingcheng

2017-02-01

Recently lower limit of detection (LOD) is necessary for rapid bacteria detection and analysis applications in clinical practices and daily life. A critical pre-conditioning step for these applications is bacterial concentration, especially for low level of pathogens. Sample volume can be largely reduced with an efficient pre-concentration process. Some approaches such as hollow-fiber ultra-filtration and electrokinetic technique have been applied to bacterial concentration. Since none of these methods can provide a concentrating method with a stable recovery efficiency, bacterial concentration still remains challenging Ceramic micro- filter can be used to concentrate the bacteria but the cross flow system keeps the bacteria in suspension. Similar harvesting bacteria using ultra-filtration showed an average recovery efficiency of 43% [1] and other studies achieved recovery rates greater than 50% [2]. In this study, an enhanced ceramic micro-filter with 0.14 μm pore size was proposed and demonstrated to optimize the concentration of E.coli. A high recovery rate (mean value >90%) and a high volumetric concentration ratio (>100) were achieved. Known quantities (104 to 106 CFU/ml) of E.coli cells were spiked to different amounts of phosphate buffered saline (0.1 to 1 L), and then concentrated to a final retentate of 5 ml to 10 ml. An average recovery efficiency of 95.3% with a standard deviation of 5.6% was achieved when the volumetric con- centration ratio was 10. No significant recovery rate loss was indicated when the volumetric concentration ratio reached up to 100. The effects of multiple parameters on E.coli recovery rate were also studied. The obtained results indicated that the optimized ceramic micro- filtration system can successfully concentrate E.coli cells in water with an average recovery rate of 90.8%.

A bio-inspired structural health monitoring system based on ambient vibration

NASA Astrophysics Data System (ADS)

Lin, Tzu-Kang; Kiremidjian, Anne; Lei, Chi-Yang

2010-11-01

A structural health monitoring (SHM) system based on naïve Bayesian (NB) damage classification and DNA-like expression data was developed in this research. Adapted from the deoxyribonucleic acid (DNA) array concept in molecular biology, the proposed structural health monitoring system is constructed utilizing a double-tier regression process to extract the expression array from the structural time history recorded during external excitations. The extracted array is symbolized as the various genes of the structure from the viewpoint of molecular biology and reflects the possible damage conditions prevalent in the structure. A scaled down, six-story steel building mounted on the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark. The structural response at different damage levels and locations under ambient vibration was collected to support the database for the proposed SHM system. To improve the precision of detection in practical applications, the system was enhanced by an optimization process using the likelihood selection method. The obtained array representing the DNA array of the health condition of the structure was first evaluated and ranked. A total of 12 groups of expression arrays were regenerated from a combination of four damage conditions. To keep the length of the array unchanged, the best 16 coefficients from every expression array were selected to form the optimized SHM system. Test results from the ambient vibrations showed that the detection accuracy of the structural damage could be greatly enhanced by the optimized expression array, when compared to the original system. Practical verification also demonstrated that a rapid and reliable result could be given by the final system within 1 min. The proposed system implements the idea of transplanting the DNA array concept from molecular biology into the field of SHM.

Development of polymerase chain reaction-based diagnostic tests for detection of Malsoor virus & adenovirus isolated from Rousettus species of bats in Maharashtra, India.

PubMed

Shete, Anita M; Yadav, Pragya; Kumar, Vimal; Nikam, Tushar; Mehershahi, Kurosh; Kokate, Prasad; Patil, Deepak; Mourya, Devendra T

2017-01-01

Bats are recognized as important reservoirs for emerging infectious disease and some unknown viral diseases. Two novel viruses, Malsoor virus (family Bunyaviridae, genus, Phlebovirus) and a novel adenovirus (AdV) (family, Adenoviridae genus, Mastadenovirus), were identified from Rousettus bats in the Maharashtra State of India. This study was done to develop and optimize real time reverse transcription - polymerase chain reaction (RT-PCR) assays for Malsoor virus and real time and nested PCR for adenovirus from Rousettus bats. For rapid and accurate screening of Malsoor virus and adenovirus a nested polymerase chain reaction and TaqMan-based real-time PCR were developed. Highly conserved region of nucleoprotein gene of phleboviruses and polymerase gene sequence from the Indian bat AdV isolate polyprotein gene were selected respectively for diagnostic assay development of Malsoor virus and AdV. Sensitivity and specificity of assays were calculated and optimized assays were used to screen bat samples. Molecular diagnostic assays were developed for screening of Malsoor virus and AdV and those were found to be specific. Based on the experiments performed with different parameters, nested PCR was found to be more sensitive than real-time PCR; however, for rapid screening, real-time PCR can be used and further nested PCR can be used for final confirmation or in those laboratories where real-time facility/expertise is not existing. This study reports the development and optimization of nested RT-PCR and a TaqMan-based real-time PCR for Malsoor virus and AdV. The diagnostic assays can be used for rapid detection of these novel viruses to understand their prevalence among bat population.

Development and application of carbon nanotubes assisted electromembrane extraction (CNTs/EME) for the determination of buprenorphine as a model of basic drugs from urine samples.

PubMed

Hasheminasab, Kobra Sadat; Fakhari, Ali Reza

2013-03-12

In this work carbon nanotubes assisted electromembrane extraction (CNTs/EME) coupled with capillary electrophoresis (CE) and ultraviolet (UV) detection was developed for the determination of buprenorphine as a model of basic drugs from urine samples. Carbon nanotubes reinforced hollow fiber was used in this research. Here the CNTs serve as a sorbent and provide an additional pathway for solute transport. The presence of CNTs in the hollow fiber wall increased the effective surface area and the overall partition coefficient on the membrane; and lead to an enhancement in the analyte transport. For investigating the influence of the presence of CNTs in the SLM on the extraction efficiency, a comparative study was carried out between EME and CNTs/EME methods. Optimization of the variables affecting these methods was carried out in order to achieve the best extraction efficiency. Optimal extractions were accomplished with NPOE as the SLM, with 200V as the driving force, and with pH 2.0 in the donor and pH 1.0 in the acceptor solutions with the whole assembly agitated at 750rpm after 25min and 15min for EME and CNTs/EME, respectively. Under the optimized conditions, in comparison with the conventional EME method, CNTs/EME provided higher extraction efficiencies in shorter time. This method provided lower limit of detection (1ngmL(-1)), higher preconcentration factor (185) and higher recovery (92). Finally, the applicability of this method was evaluated by the extraction and determination of buprenorphine in patients' urine samples. Copyright © 2013 Elsevier B.V. All rights reserved.

Automated Cloud Observation for Ground Telescope Optimization

NASA Astrophysics Data System (ADS)

Lane, B.; Jeffries, M. W., Jr.; Therien, W.; Nguyen, H.

As the number of man-made objects placed in space each year increases with advancements in commercial, academic and industry, the number of objects required to be detected, tracked, and characterized continues to grow at an exponential rate. Commercial companies, such as ExoAnalytic Solutions, have deployed ground based sensors to maintain track custody of these objects. For the ExoAnalytic Global Telescope Network (EGTN), observation of such objects are collected at the rate of over 10 million unique observations per month (as of September 2017). Currently, the EGTN does not optimally collect data on nights with significant cloud levels. However, a majority of these nights prove to be partially cloudy providing clear portions in the sky for EGTN sensors to observe. It proves useful for a telescope to utilize these clear areas to continue resident space object (RSO) observation. By dynamically updating the tasking with the varying cloud positions, the number of observations could potentially increase dramatically due to increased persistence, cadence, and revisit. This paper will discuss the recent algorithms being implemented within the EGTN, including the motivation, need, and general design. The use of automated image processing as well as various edge detection methods, including Canny, Sobel, and Marching Squares, on real-time large FOV images of the sky enhance the tasking and scheduling of a ground based telescope is discussed in Section 2. Implementations of these algorithms on single and expanding to multiple telescopes, will be explored. Results of applying these algorithms to the EGTN in real-time and comparison to non-optimized EGTN tasking is presented in Section 3. Finally, in Section 4 we explore future work in applying these throughout the EGTN as well as other optical telescopes.

Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape Stems

PubMed Central

Kong, Wenwen; Zhang, Chu; Huang, Weihao

2018-01-01

Hyperspectral imaging covering the spectral range of 384–1034 nm combined with chemometric methods was used to detect Sclerotinia sclerotiorum (SS) on oilseed rape stems by two sample sets (60 healthy and 60 infected stems for each set). Second derivative spectra and PCA loadings were used to select the optimal wavelengths. Discriminant models were built and compared to detect SS on oilseed rape stems, including partial least squares-discriminant analysis, radial basis function neural network, support vector machine and extreme learning machine. The discriminant models using full spectra and optimal wavelengths showed good performance with classification accuracies of over 80% for the calibration and prediction set. Comparing all developed models, the optimal classification accuracies of the calibration and prediction set were over 90%. The similarity of selected optimal wavelengths also indicated the feasibility of using hyperspectral imaging to detect SS on oilseed rape stems. The results indicated that hyperspectral imaging could be used as a fast, non-destructive and reliable technique to detect plant diseases on stems. PMID:29300315

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.

Symbiotic Optimization of Behavior

DTIC Science & Technology

2015-05-01

SYMBIOTIC OPTIMIZATION OF BEHAVIOR UNIVERSITY OF WASHINGTON MAY 2015 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED...2014 4. TITLE AND SUBTITLE SYMBIOTIC OPTIMIZATION OF BEHAVIOR 5a. CONTRACT NUMBER FA8750-12-1-0304 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT

Algorithm for solving of two-level hierarchical minimax program control problem of final state the regional socio-economic system in the presence of risks

NASA Astrophysics Data System (ADS)

Shorikov, A. F.

2017-10-01

In this paper we study the problem of optimization of guaranteed result for program control by the final state of regional social and economic system in the presence of risks. For this problem we propose a mathematical model in the form of two-level hierarchical minimax program control problem of the final state of this process with incomplete information. For solving of its problem we constructed the common algorithm that has a form of a recurrent procedure of solving a linear programming and a finite optimization problems.

Finite element approximation of an optimal control problem for the von Karman equations

NASA Technical Reports Server (NTRS)

Hou, L. Steven; Turner, James C.

1994-01-01

This paper is concerned with optimal control problems for the von Karman equations with distributed controls. We first show that optimal solutions exist. We then show that Lagrange multipliers may be used to enforce the constraints and derive an optimality system from which optimal states and controls may be deduced. Finally we define finite element approximations of solutions for the optimality system and derive error estimates for the approximations.

Development of a lithium fluoride zinc sulfide based neutron multiplicity counter

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

Cowles, Christian; Behling, Spencer; Baldez, Phoenix

Here, the feasibility of a full-scale lithium fluoride zinc sulfide (LiF/ZnS) based neutron multiplicity counter has been demonstrated. The counter was constructed of modular neutron detecting stacks that each contain five sheets of LiF/ZnS interleaved between six sheets of wavelength shifting plastic with a photomultiplier tube on each end. Twelve such detector stacks were placed around a sample chamber in a square arrangement with lithiated high-density polyethylene blocks in the corners to reflect high-energy neutrons and capture low-energy neutrons. The final system design was optimized via modeling and small-scale test. Measuring neutrons from a 252Cf source, the counter achieved amore » 36% neutron detection efficiency (ϵϵ) and an View the MathML source11.7μs neutron die-away time (ττ) for a doubles figure-of-merit (ϵ 2/τ) of 109. This is the highest doubles figure-of-merit measured to-date for a 3He-free neutron multiplicity counter.« less

Multisensor-based real-time quality monitoring by means of feature extraction, selection and modeling for Al alloy in arc welding

NASA Astrophysics Data System (ADS)

Zhang, Zhifen; Chen, Huabin; Xu, Yanling; Zhong, Jiyong; Lv, Na; Chen, Shanben

2015-08-01

Multisensory data fusion-based online welding quality monitoring has gained increasing attention in intelligent welding process. This paper mainly focuses on the automatic detection of typical welding defect for Al alloy in gas tungsten arc welding (GTAW) by means of analzing arc spectrum, sound and voltage signal. Based on the developed algorithms in time and frequency domain, 41 feature parameters were successively extracted from these signals to characterize the welding process and seam quality. Then, the proposed feature selection approach, i.e., hybrid fisher-based filter and wrapper was successfully utilized to evaluate the sensitivity of each feature and reduce the feature dimensions. Finally, the optimal feature subset with 19 features was selected to obtain the highest accuracy, i.e., 94.72% using established classification model. This study provides a guideline for feature extraction, selection and dynamic modeling based on heterogeneous multisensory data to achieve a reliable online defect detection system in arc welding.

Development of a lithium fluoride zinc sulfide based neutron multiplicity counter

NASA Astrophysics Data System (ADS)

Cowles, Christian; Behling, Spencer; Baldez, Phoenix; Folsom, Micah; Kouzes, Richard; Kukharev, Vladislav; Lintereur, Azaree; Robinson, Sean; Siciliano, Edward; Stave, Sean; Valdez, Patrick

2018-04-01

The feasibility of a full-scale lithium fluoride zinc sulfide (LiF/ZnS) based neutron multiplicity counter has been demonstrated. The counter was constructed of modular neutron detecting stacks that each contain five sheets of LiF/ZnS interleaved between six sheets of wavelength shifting plastic with a photomultiplier tube on each end. Twelve such detector stacks were placed around a sample chamber in a square arrangement with lithiated high-density polyethylene blocks in the corners to reflect high-energy neutrons and capture low-energy neutrons. The final system design was optimized via modeling and small-scale test. Measuring neutrons from a 252Cf source, the counter achieved a 36% neutron detection efficiency (ɛ) and an 11 . 7 μs neutron die-away time (τ) for a doubles figure-of-merit (ɛ2 / τ) of 109. This is the highest doubles figure-of-merit measured to-date for a 3He-free neutron multiplicity counter.

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

NASA Astrophysics Data System (ADS)

Shi, Aiye; Gao, Guirong; Shen, Shaohong

2016-12-01

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

Recent advances in integrated photonic sensors.

PubMed

Passaro, Vittorio M N; de Tullio, Corrado; Troia, Benedetto; La Notte, Mario; Giannoccaro, Giovanni; De Leonardis, Francesco

2012-11-09

Nowadays, optical devices and circuits are becoming fundamental components in several application fields such as medicine, biotechnology, automotive, aerospace, food quality control, chemistry, to name a few. In this context, we propose a complete review on integrated photonic sensors, with specific attention to materials, technologies, architectures and optical sensing principles. To this aim, sensing principles commonly used in optical detection are presented, focusing on sensor performance features such as sensitivity, selectivity and rangeability. Since photonic sensors provide substantial benefits regarding compatibility with CMOS technology and integration on chips characterized by micrometric footprints, design and optimization strategies of photonic devices are widely discussed for sensing applications. In addition, several numerical methods employed in photonic circuits and devices, simulations and design are presented, focusing on their advantages and drawbacks. Finally, recent developments in the field of photonic sensing are reviewed, considering advanced photonic sensor architectures based on linear and non-linear optical effects and to be employed in chemical/biochemical sensing, angular velocity and electric field detection.

Recent Advances in Integrated Photonic Sensors

PubMed Central

Passaro, Vittorio M. N.; de Tullio, Corrado; Troia, Benedetto; La Notte, Mario; Giannoccaro, Giovanni; De Leonardis, Francesco

2012-01-01

Nowadays, optical devices and circuits are becoming fundamental components in several application fields such as medicine, biotechnology, automotive, aerospace, food quality control, chemistry, to name a few. In this context, we propose a complete review on integrated photonic sensors, with specific attention to materials, technologies, architectures and optical sensing principles. To this aim, sensing principles commonly used in optical detection are presented, focusing on sensor performance features such as sensitivity, selectivity and rangeability. Since photonic sensors provide substantial benefits regarding compatibility with CMOS technology and integration on chips characterized by micrometric footprints, design and optimization strategies of photonic devices are widely discussed for sensing applications. In addition, several numerical methods employed in photonic circuits and devices, simulations and design are presented, focusing on their advantages and drawbacks. Finally, recent developments in the field of photonic sensing are reviewed, considering advanced photonic sensor architectures based on linear and non-linear optical effects and to be employed in chemical/biochemical sensing, angular velocity and electric field detection. PMID:23202223

Development of a lithium fluoride zinc sulfide based neutron multiplicity counter

DOE PAGES

Cowles, Christian; Behling, Spencer; Baldez, Phoenix; ...

2018-01-12

Here, the feasibility of a full-scale lithium fluoride zinc sulfide (LiF/ZnS) based neutron multiplicity counter has been demonstrated. The counter was constructed of modular neutron detecting stacks that each contain five sheets of LiF/ZnS interleaved between six sheets of wavelength shifting plastic with a photomultiplier tube on each end. Twelve such detector stacks were placed around a sample chamber in a square arrangement with lithiated high-density polyethylene blocks in the corners to reflect high-energy neutrons and capture low-energy neutrons. The final system design was optimized via modeling and small-scale test. Measuring neutrons from a 252Cf source, the counter achieved amore » 36% neutron detection efficiency (ϵϵ) and an View the MathML source11.7μs neutron die-away time (ττ) for a doubles figure-of-merit (ϵ 2/τ) of 109. This is the highest doubles figure-of-merit measured to-date for a 3He-free neutron multiplicity counter.« less

All-Optical Cantilever-Enhanced Photoacoustic Spectroscopy in the Open Environment

NASA Astrophysics Data System (ADS)

Wei, Wei; Zhu, Yong; Lin, Cheng; Tian, Li; Xu, Zhuwen; Nong, Jinpeng

2015-06-01

A novel all-optical cantilever-enhanced photoacoustic spectroscopy technique for trace gas detection in the open environment is proposed. A cantilever is set off-beam to "listen to" the photoacoustic signal, and an improved quadrature-point stabilization Fabry-Perot demodulation unit is used to pick up the vibration signal of the acoustic transducer instead of a complicated Michelson interferometer. The structure parameters of the cantilever are optimized to make the sensing system work more stably and reliably using a finite element method, which is then fabricated by surface micro-machining technology. Finally, related experiments are carried out to detect the absorption of water vapor at one atmosphere in the open environment. It was found that the normalized noise-equivalent absorption coefficient obtained by a traditional Fabry-Perot demodulation unit is , while that by a quadrature- point stabilization Fabry-Perot demodulation unit is , which indicates that the sensitivity is increased by a factor of 3.1 using improved cantilever-enhanced photoacoustic spectroscopy.

A simple, remote, video based breathing monitor.

PubMed

Regev, Nir; Wulich, Dov

2017-07-01

Breathing monitors have become the all-important cornerstone of a wide variety of commercial and personal safety applications, ranging from elderly care to baby monitoring. Many such monitors exist in the market, some, with vital signs monitoring capabilities, but none remote. This paper presents a simple, yet efficient, real time method of extracting the subject's breathing sinus rhythm. Points of interest are detected on the subject's body, and the corresponding optical flow is estimated and tracked using the well known Lucas-Kanade algorithm on a frame by frame basis. A generalized likelihood ratio test is then utilized on each of the many interest points to detect which is moving in harmonic fashion. Finally, a spectral estimation algorithm based on Pisarenko harmonic decomposition tracks the harmonic frequency in real time, and a fusion maximum likelihood algorithm optimally estimates the breathing rate using all points considered. The results show a maximal error of 1 BPM between the true breathing rate and the algorithm's calculated rate, based on experiments on two babies and three adults.

Detection of esophageal cancer cell by photoelectrochemical Cu2O/ZnO biosensor (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hsu, Chao-Hsin; Chu, Cheng-Hsun; Chen, Weichung; Wu, I.-Chen; Wu, Ming Tsang; Kuo, Chie-Tong; Tsiang, Raymond Chien-Chao; Wang, Hsiang-Chen

2016-03-01

We have demonstrated a Cu2O/ZnO nanorods (NRs) array p-n heterostructures photoelectrochemical biosensor. The electrodeposition of Cu2O at pH 12 acquired the preferably (111) lattice planes, resulting in the largest interfacial electric field between Cu2O and ZnO, which finally led to the highest separation efficiency of photogenerated charge carriers. High verticality ZnO nanorods by seed layer and thermal annealing assist the hydrothermal growth. The optimized Cu2O/ZnO NRs array p-n heterostructures exhibited enhanced PEC performance, such as elevated photocurrent and photoconversion efficiency, as well as excellent sensing performance for the sensitive detection of four strains of different races and different degree of cancer cell which made the device self-powered. We got spectral response characteristics and operating wavelength range of biosensor, and to verify the biological characteristics of cancer cells wafer react with different stages of cancer characterized by a cancer measured reaction experiment.

Fall Risk Assessment and Early-Warning for Toddler Behaviors at Home

PubMed Central

Yang, Mau-Tsuen; Chuang, Min-Wen

2013-01-01

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second. PMID:24335727

Segmentation and classification of road markings using MLS data

NASA Astrophysics Data System (ADS)

Soilán, Mario; Riveiro, Belén; Martínez-Sánchez, Joaquín; Arias, Pedro

2017-01-01

Traffic signs are one of the most important safety elements in a road network. Particularly, road markings provide information about the limits and direction of each road lane, or warn the drivers about potential danger. The optimal condition of road markings contributes to a better road safety. Mobile Laser Scanning technology can be used for infrastructure inspection and specifically for traffic sign detection and inventory. This paper presents a methodology for the detection and semantic characterization of the most common road markings, namely pedestrian crossings and arrows. The 3D point cloud data acquired by a LYNX Mobile Mapper system is filtered in order to isolate reflective points in the road, and each single element is hierarchically classified using Neural Networks. State of the art results are obtained for the extraction and classification of the markings, with F-scores of 94% and 96% respectively. Finally, data from classified markings are exported to a GIS layer and maintenance criteria based on the aforementioned data are proposed.

Double resonance long period fiber grating for detection of E. coli in trace concentration by choosing a proper bacteriophage

NASA Astrophysics Data System (ADS)

Chiniforooshan, Y.; Celebanska, A.; Janik, M.; Mikulic, P.; Haddad, F.; Perreault, J.; Bock, W. J.

2017-04-01

There is a critical need of a fast, specific and reliable assay for biological species. To address this need, long period fiber gratings (LPFG) among other fiber optic sensors can be used because of their high sensitivity to changes in surrounding medium. In this work we fabricated and used two over-etched LPFGs. One of them was covered with T4 Phage and the other was covered with MS2 phage that both specifically bind with Escherichia coli (E. coli) bacteria. This bacterium is a major cause of the food contaminations and outbreaks. We showed achieving a highest sensitivity region of the LPFG and the way to fine tune to that region by over-etching the grating. Finally, using the highly sensitive LPFG platform we could detect E. coli at concentrations as low as 100 colony forming units (CFU), by covering the LPFG with an optimized bio-functionalization of the fiber surface with MS2 bacteriophage.

Laser Ultrasound Spectroscopy Scanning for 3D Printed Parts

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

Brennan, Guendalyn Kendra

One of the challenges of additive manufacturing is quality control due to the possibility of unseen flaws in the final product. The current methods of inspection are lacking in detail, too slow for practical use, or unable to validate internal structure. This report examines the use of laser ultrasound spectroscopy in layer by layer scans of 3D printed parts as they are created. The result is fast and detailed quality control. An additional advantage of this method is the ability to cancel a print as soon as a defect is detected, therefore saving materials and time. This technique, though simplemore » in concept, has been a challenge to implement. I discuss tweaking the 3D printer configuration, and finding the optimal settings for laser scanning small parts made of ABS plastic, as well as the limits of how small of a detail the laser can detect. These settings include the frequency of the ultrasonic transducer, the speed of the laser, and the distance from the laser to the part.« less

Fault Diagnosis for Centre Wear Fault of Roll Grinder Based on a Resonance Demodulation Scheme

NASA Astrophysics Data System (ADS)

Wang, Liming; Shao, Yimin; Yin, Lei; Yuan, Yilin; Liu, Jing

2017-05-01

Roll grinder is one of the important parts in the rolling machinery, and the grinding precision of roll surface has direct influence on the surface quality of steel strip. However, during the grinding process, the centre bears the gravity of the roll and alternating stress. Therefore, wear or spalling faults are easily observed on the centre, which will lead to an anomalous vibration of the roll grinder. In this study, a resonance demodulation scheme is proposed to detect the centre wear fault of roll grinder. Firstly, fast kurtogram method is employed to help select the sub-band filter parameters for optimal resonance demodulation. Further, the envelope spectrum are derived based on the filtered signal. Finally, two health indicators are designed to conduct the fault diagnosis for centre wear fault. The proposed scheme is assessed by analysing experimental data from a roll grinder of twenty-high rolling mill. The results show that the proposed scheme can effectively detect the centre wear fault of the roll grinder.

Learning directed acyclic graphs from large-scale genomics data.

PubMed

Nikolay, Fabio; Pesavento, Marius; Kritikos, George; Typas, Nassos

2017-09-20

In this paper, we consider the problem of learning the genetic interaction map, i.e., the topology of a directed acyclic graph (DAG) of genetic interactions from noisy double-knockout (DK) data. Based on a set of well-established biological interaction models, we detect and classify the interactions between genes. We propose a novel linear integer optimization program called the Genetic-Interactions-Detector (GENIE) to identify the complex biological dependencies among genes and to compute the DAG topology that matches the DK measurements best. Furthermore, we extend the GENIE program by incorporating genetic interaction profile (GI-profile) data to further enhance the detection performance. In addition, we propose a sequential scalability technique for large sets of genes under study, in order to provide statistically significant results for real measurement data. Finally, we show via numeric simulations that the GENIE program and the GI-profile data extended GENIE (GI-GENIE) program clearly outperform the conventional techniques and present real data results for our proposed sequential scalability technique.

Implementation of a close range photogrammetric system for 3D reconstruction of a scoliotic torso

NASA Astrophysics Data System (ADS)

Detchev, Ivan Denislavov

Scoliosis is a deformity of the human spine most commonly encountered with children. After being detected, periodic examinations via x-rays are traditionally used to measure its progression. However, due to the increased risk of cancer, a non-invasive and radiation-free scoliosis detection and progression monitoring methodology is needed. Quantifying the scoliotic deformity through the torso surface is a valid alternative, because of its high correlation with the internal spine curvature. This work proposes a low-cost multi-camera photogrammetric system for semi-automated 3D reconstruction of a torso surface with sub-millimetre level accuracy. The thesis describes the system design and calibration for optimal accuracy. It also covers the methodology behind the reconstruction and registration procedures. The experimental results include the complete reconstruction of a scoliotic torso mannequin. The final accuracy is evaluated through the goodness of fit between the reconstructed surface and a more accurate set of points measured by a coordinate measuring machine.

Fall risk assessment and early-warning for toddler behaviors at home.

PubMed

Yang, Mau-Tsuen; Chuang, Min-Wen

2013-12-10

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second.

Interleaved segment correction achieves higher improvement factors in using genetic algorithm to optimize light focusing through scattering media

NASA Astrophysics Data System (ADS)

Li, Runze; Peng, Tong; Liang, Yansheng; Yang, Yanlong; Yao, Baoli; Yu, Xianghua; Min, Junwei; Lei, Ming; Yan, Shaohui; Zhang, Chunmin; Ye, Tong

2017-10-01

Focusing and imaging through scattering media has been proved possible with high resolution wavefront shaping. A completely scrambled scattering field can be corrected by applying a correction phase mask on a phase only spatial light modulator (SLM) and thereby the focusing quality can be improved. The correction phase is often found by global searching algorithms, among which Genetic Algorithm (GA) stands out for its parallel optimization process and high performance in noisy environment. However, the convergence of GA slows down gradually with the progression of optimization, causing the improvement factor of optimization to reach a plateau eventually. In this report, we propose an interleaved segment correction (ISC) method that can significantly boost the improvement factor with the same number of iterations comparing with the conventional all segment correction method. In the ISC method, all the phase segments are divided into a number of interleaved groups; GA optimization procedures are performed individually and sequentially among each group of segments. The final correction phase mask is formed by applying correction phases of all interleaved groups together on the SLM. The ISC method has been proved significantly useful in practice because of its ability to achieve better improvement factors when noise is present in the system. We have also demonstrated that the imaging quality is improved as better correction phases are found and applied on the SLM. Additionally, the ISC method lowers the demand of dynamic ranges of detection devices. The proposed method holds potential in applications, such as high-resolution imaging in deep tissue.

Optimization and evaluation of a method to detect adenoviruses in river water

EPA Pesticide Factsheets

This dataset includes the recoveries of spiked adenovirus through various stages of experimental optimization procedures. This dataset is associated with the following publication:McMinn , B., A. Korajkic, and A. Grimm. Optimization and evaluation of a method to detect adenoviruses in river water. JOURNAL OF VIROLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA, 231(1): 8-13, (2016).

Online optimal obstacle avoidance for rotary-wing autonomous unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kang, Keeryun

This thesis presents an integrated framework for online obstacle avoidance of rotary-wing unmanned aerial vehicles (UAVs), which can provide UAVs an obstacle field navigation capability in a partially or completely unknown obstacle-rich environment. The framework is composed of a LIDAR interface, a local obstacle grid generation, a receding horizon (RH) trajectory optimizer, a global shortest path search algorithm, and a climb rate limit detection logic. The key feature of the framework is the use of an optimization-based trajectory generation in which the obstacle avoidance problem is formulated as a nonlinear trajectory optimization problem with state and input constraints over the finite range of the sensor. This local trajectory optimization is combined with a global path search algorithm which provides a useful initial guess to the nonlinear optimization solver. Optimization is the natural process of finding the best trajectory that is dynamically feasible, safe within the vehicle's flight envelope, and collision-free at the same time. The optimal trajectory is continuously updated in real time by the numerical optimization solver, Nonlinear Trajectory Generation (NTG), which is a direct solver based on the spline approximation of trajectory for dynamically flat systems. In fact, the overall approach of this thesis to finding the optimal trajectory is similar to the model predictive control (MPC) or the receding horizon control (RHC), except that this thesis followed a two-layer design; thus, the optimal solution works as a guidance command to be followed by the controller of the vehicle. The framework is implemented in a real-time simulation environment, the Georgia Tech UAV Simulation Tool (GUST), and integrated in the onboard software of the rotary-wing UAV test-bed at Georgia Tech. Initially, the 2D vertical avoidance capability of real obstacles was tested in flight. The flight test evaluations were extended to the benchmark tests for 3D avoidance capability over the virtual obstacles, and finally it was demonstrated on real obstacles located at the McKenna MOUT site in Fort Benning, Georgia. Simulations and flight test evaluations demonstrate the feasibility of the developed framework for UAV applications involving low-altitude flight in an urban area.

Fabrication of paper-based analytical devices optimized by central composite design.

PubMed

Hamedpour, Vahid; Leardi, Riccardo; Suzuki, Koji; Citterio, Daniel

2018-04-30

In this work, an application of a design of experiments approach for the optimization of an isoniazid assay on a single-area inkjet-printed paper-based analytical device (PAD) is described. For this purpose, a central composite design was used for evaluation of the effect of device geometry and amount of assay reagents on the efficiency of the proposed device. The factors of interest were printed length, width, and sampling volume as factors related to device geometry, and amounts of the assay reagents polyvinyl alcohol (PVA), NH4OH, and AgNO3. Deposition of the assay reagents was performed by a thermal inkjet printer. The colorimetric assay mechanism of this device is based on the chemical interaction of isoniazid, ammonium hydroxide, and PVA with silver ions to induce the formation of yellow silver nanoparticles (AgNPs). The in situ-formed AgNPs can be easily detected by the naked eye or with a simple flat-bed scanner. Under optimal conditions, the calibration curve was linear in the isoniazid concentration range 0.03-10 mmol L-1 with a relative standard deviation of 3.4% (n = 5 for determination of 1.0 mmol L-1). Finally, the application of the proposed device for isoniazid determination in pharmaceutical preparations produced satisfactory results.

[The optimizing design and experiment for a MOEMS micro-mirror spectrometer].

PubMed

Mo, Xiang-xia; Wen, Zhi-yu; Zhang, Zhi-hai; Guo, Yuan-jun

2011-12-01

A MOEMS micro-mirror spectrometer, which uses micro-mirror as a light switch so that spectrum can be detected by a single detector, has the advantages of transforming DC into AC, applying Hadamard transform optics without additional template, high pixel resolution and low cost. In this spectrometer, the vital problem is the conflict between the scales of slit and the light intensity. Hence, in order to improve the resolution of this spectrometer, the present paper gives the analysis of the new effects caused by micro structure, and optimal values of the key factors. Firstly, the effects of diffraction limitation, spatial sample rate and curved slit image on the resolution of the spectrum were proposed. Then, the results were simulated; the key values were tested on the micro mirror spectrometer. Finally, taking all these three effects into account, this micro system was optimized. With a scale of 70 mm x 130 mm, decreasing the height of the image at the plane of micro mirror can not diminish the influence of curved slit image in the spectrum; under the demand of spatial sample rate, the resolution must be twice over the pixel resolution; only if the width of the slit is 1.818 microm and the pixel resolution is 2.2786 microm can the spectrometer have the best performance.

CEC-atmospheric pressure ionization MS of pesticides using a surfactant-bound monolithic column.

PubMed

Gu, Congying; Shamsi, Shahab A

2010-04-01

A surfactant bound poly (11-acrylaminoundecanoic acid-ethylene dimethacrylate) monolithic column was simply prepared by in situ co-polymerization of 11-acrylaminoundecanoic acid and ethylene dimethacrylate with 1-propanol, 1,4-butanediol and water as porogens in 100 microm id fused-silica capillary in one step. This column was used in CEC-atmospheric pressure photoionization (APPI)-MS system for separation and detection of N-methylcarbamates pesticides. Numerous parameters are optimized for CEC-APPI-MS. After evaluation of the mobile phase composition, sheath liquid composition and the monolithic capillary outlet position, a fractional factorial design was selected as a screening procedure to identify factors of ionization source parameters, such as sheath liquid flow rate, drying gas flow rate, drying gas temperature, nebulizing gas pressure, vaporizer temperature and capillary voltage, which significantly influence APPI-MS sensitivity. A face-centered central composite design was further utilized to optimize the most significant parameters and predict the best sensitivity. Under optimized conditions, S/Ns around 78 were achieved for an injection of 100 ng/mL of each pesticide. Finally, this CEC-APPI-MS method was successfully applied to the analysis of nine N-methylcarbamates in spiked apple juice sample after solid phase extraction with recoveries in the range of 65-109%.

Capillary Electrophoresis Analysis of Organic Amines and Amino Acids in Saline and Acidic Samples Using the Mars Organic Analyzer

NASA Astrophysics Data System (ADS)

Stockton, Amanda M.; Chiesl, Thomas N.; Lowenstein, Tim K.; Amashukeli, Xenia; Grunthaner, Frank; Mathies, Richard A.

2009-11-01

The Mars Organic Analyzer (MOA) has enabled the sensitive detection of amino acid and amine biomarkers in laboratory standards and in a variety of field sample tests. However, the MOA is challenged when samples are extremely acidic and saline or contain polyvalent cations. Here, we have optimized the MOA analysis, sample labeling, and sample dilution buffers to handle such challenging samples more robustly. Higher ionic strength buffer systems with pKa values near pH 9 were developed to provide better buffering capacity and salt tolerance. The addition of ethylaminediaminetetraacetic acid (EDTA) ameliorates the negative effects of multivalent cations. The optimized protocol utilizes a 75 mM borate buffer (pH 9.5) for Pacific Blue labeling of amines and amino acids. After labeling, 50 mM (final concentration) EDTA is added to samples containing divalent cations to ameliorate their effects. This optimized protocol was used to successfully analyze amino acids in a saturated brine sample from Saline Valley, California, and a subcritical water extract of a highly acidic sample from the Río Tinto, Spain. This work expands the analytical capabilities of the MOA and increases its sensitivity and robustness for samples from extraterrestrial environments that may exhibit pH and salt extremes as well as metal ions.

Optimality in mono- and multisensory map formation.

PubMed

Bürck, Moritz; Friedel, Paul; Sichert, Andreas B; Vossen, Christine; van Hemmen, J Leo

2010-07-01

In the struggle for survival in a complex and dynamic environment, nature has developed a multitude of sophisticated sensory systems. In order to exploit the information provided by these sensory systems, higher vertebrates reconstruct the spatio-temporal environment from each of the sensory systems they have at their disposal. That is, for each modality the animal computes a neuronal representation of the outside world, a monosensory neuronal map. Here we present a universal framework that allows to calculate the specific layout of the involved neuronal network by means of a general mathematical principle, viz., stochastic optimality. In order to illustrate the use of this theoretical framework, we provide a step-by-step tutorial of how to apply our model. In so doing, we present a spatial and a temporal example of optimal stimulus reconstruction which underline the advantages of our approach. That is, given a known physical signal transmission and rudimental knowledge of the detection process, our approach allows to estimate the possible performance and to predict neuronal properties of biological sensory systems. Finally, information from different sensory modalities has to be integrated so as to gain a unified perception of reality for further processing, e.g., for distinct motor commands. We briefly discuss concepts of multimodal interaction and how a multimodal space can evolve by alignment of monosensory maps.

Capillary electrophoresis analysis of organic amines and amino acids in saline and acidic samples using the Mars organic analyzer.

PubMed

Stockton, Amanda M; Chiesl, Thomas N; Lowenstein, Tim K; Amashukeli, Xenia; Grunthaner, Frank; Mathies, Richard A

2009-11-01

The Mars Organic Analyzer (MOA) has enabled the sensitive detection of amino acid and amine biomarkers in laboratory standards and in a variety of field sample tests. However, the MOA is challenged when samples are extremely acidic and saline or contain polyvalent cations. Here, we have optimized the MOA analysis, sample labeling, and sample dilution buffers to handle such challenging samples more robustly. Higher ionic strength buffer systems with pK(a) values near pH 9 were developed to provide better buffering capacity and salt tolerance. The addition of ethylaminediaminetetraacetic acid (EDTA) ameliorates the negative effects of multivalent cations. The optimized protocol utilizes a 75 mM borate buffer (pH 9.5) for Pacific Blue labeling of amines and amino acids. After labeling, 50 mM (final concentration) EDTA is added to samples containing divalent cations to ameliorate their effects. This optimized protocol was used to successfully analyze amino acids in a saturated brine sample from Saline Valley, California, and a subcritical water extract of a highly acidic sample from the Río Tinto, Spain. This work expands the analytical capabilities of the MOA and increases its sensitivity and robustness for samples from extraterrestrial environments that may exhibit pH and salt extremes as well as metal ions.

Vehicle license plate recognition in dense fog based on improved atmospheric scattering model

NASA Astrophysics Data System (ADS)

Tang, Chunming; Lin, Jun; Chen, Chunkai; Dong, Yancheng

2018-04-01

An effective method based on improved atmospheric scattering model is proposed in this paper to handle the problem of the vehicle license plate location and recognition in dense fog. Dense fog detection is performed firstly by the top-hat transformation and the vertical edge detection, and the moving vehicle image is separated from the traffic video image. After the vehicle image is decomposed into two layers: structure and texture layers, the glow layer is separated from the structure layer to get the background layer. Followed by performing the mean-pooling and the bicubic interpolation algorithm, the atmospheric light map of the background layer can be predicted, meanwhile the transmission of the background layer is estimated through the grayed glow layer, whose gray value is altered by linear mapping. Then, according to the improved atmospheric scattering model, the final restored image can be obtained by fusing the restored background layer and the optimized texture layer. License plate location is performed secondly by a series of morphological operations, connected domain analysis and various validations. Characters extraction is achieved according to the projection. Finally, an offline trained pattern classifier of hybrid discriminative restricted boltzmann machines (HDRBM) is applied to recognize the characters. Experimental results on thorough data sets are reported to demonstrate that the proposed method can achieve high recognition accuracy and works robustly in the dense fog traffic environment during 24h or one day.

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.

Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm.

PubMed

Wang, Xingmei; Liu, Shu; Liu, Zhipeng

2017-01-01

This paper proposes a combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm to detect underwater objects in sonar images. Specifically, for the first time, the problem of inappropriate filtering degree parameter which commonly occurs in non-local spatial information and seriously affects the denoising performance in sonar images, was solved with the method utilizing a novel filtering degree parameter. Then, a quantum-inspired shuffled frog leaping algorithm based on new search mechanism (QSFLA-NSM) is proposed to precisely and quickly detect sonar images. Each frog individual is directly encoded by real numbers, which can greatly simplify the evolution process of the quantum-inspired shuffled frog leaping algorithm (QSFLA). Meanwhile, a fitness function combining intra-class difference with inter-class difference is adopted to evaluate frog positions more accurately. On this basis, recurring to an analysis of the quantum-behaved particle swarm optimization (QPSO) and the shuffled frog leaping algorithm (SFLA), a new search mechanism is developed to improve the searching ability and detection accuracy. At the same time, the time complexity is further reduced. Finally, the results of comparative experiments using the original sonar images, the UCI data sets and the benchmark functions demonstrate the effectiveness and adaptability of the proposed method.

Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm

PubMed Central

Liu, Zhipeng

2017-01-01

This paper proposes a combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm to detect underwater objects in sonar images. Specifically, for the first time, the problem of inappropriate filtering degree parameter which commonly occurs in non-local spatial information and seriously affects the denoising performance in sonar images, was solved with the method utilizing a novel filtering degree parameter. Then, a quantum-inspired shuffled frog leaping algorithm based on new search mechanism (QSFLA-NSM) is proposed to precisely and quickly detect sonar images. Each frog individual is directly encoded by real numbers, which can greatly simplify the evolution process of the quantum-inspired shuffled frog leaping algorithm (QSFLA). Meanwhile, a fitness function combining intra-class difference with inter-class difference is adopted to evaluate frog positions more accurately. On this basis, recurring to an analysis of the quantum-behaved particle swarm optimization (QPSO) and the shuffled frog leaping algorithm (SFLA), a new search mechanism is developed to improve the searching ability and detection accuracy. At the same time, the time complexity is further reduced. Finally, the results of comparative experiments using the original sonar images, the UCI data sets and the benchmark functions demonstrate the effectiveness and adaptability of the proposed method. PMID:28542266

Improving space debris detection in GEO ring using image deconvolution

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

The development of a MIP-optosensor for the detection of monoamine naphthalenes in drinking water.

PubMed

Valero-Navarro, Angel; Salinas-Castillo, Alfonso; Fernández-Sánchez, Jorge F; Segura-Carretero, Antonio; Mallavia, Ricardo; Fernández-Gutiérrez, Alberto

2009-03-15

To enhance the advantages of fluorescent flow-through sensing for drinking water we have designed a novel sensing matrix based on molecularly imprinted polymers (MIPs). The synergic combination of a tailor-made MIP recognition with a selective room temperature fluorescence detection is a novel concept for optosensing devices and is assessed here for the simple and selective determination of pollutants in water. We describe a simple approach to preparing synthetic receptors for monoamine naphthalene compounds (MA-NCs) using non-covalent molecular imprinting techniques and naphthalene as template. We examine in detail the binding characteristics of the imprinted polymer and describe the flow-through sensor of MA-NCs by solid-surface fluorescence. Its detection limits for recognizing 1-naphthylamine (1-NA) and 2-naphthylamine (2-NA) separately are 26 ngmL(-1) and 50 ngmL(-1), respectively, and it also determines 1-NA and 2-NA simultaneously with a detection limit of 45 ngmL(-1). All the instrumental, chemical and flow variables were carefully optimized and an interference study was carried out to demonstrate its applicability and selectivity. Finally, we applied it to the analysis of 1-NA and 2-NA in tap and mineral waters, obtaining a 98% average recovery rate.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Simulation Of A Photofission-Based Cargo Interrogation System

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

King, Michael; Gozani, Tsahi; Stevenson, John

A comprehensive model has been developed to characterize and optimize the detection of Bremsstrahlung x-ray induced fission signatures from nuclear materials hidden in cargo containers. An effective active interrogation system should not only induce a large number of fission events but also efficiently detect their signatures. The proposed scanning system utilizes a 9-MV commercially available linear accelerator and the detection of strong fission signals i.e. delayed gamma rays and prompt neutrons. Because the scanning system is complex and the cargo containers are large and often highly attenuating, the simulation method segments the model into several physical steps, representing each changemore » of radiation particle. Each approximation is carried-out separately, resulting in a major reduction in computational time and a significant improvement in tally statistics. The model investigates the effect on the fission rate and detection rate by various cargo types, densities and distributions. Hydrogenous and metallic cargos, homogeneous and heterogeneous, as well as various locations of the nuclear material inside the cargo container were studied. We will show that for the photofission-based interrogation system simulation, the final results are not only in good agreement with a full, single-step simulation but also with experimental results, further validating the full-system simulation.« less

Model-Based Design of Tree WSNs for Decentralized Detection †

PubMed Central

Tantawy, Ashraf; Koutsoukos, Xenofon; Biswas, Gautam

2015-01-01

The classical decentralized detection problem of finding the optimal decision rules at the sensor and fusion center, as well as variants that introduce physical channel impairments have been studied extensively in the literature. The deployment of WSNs in decentralized detection applications brings new challenges to the field. Protocols for different communication layers have to be co-designed to optimize the detection performance. In this paper, we consider the communication network design problem for a tree WSN. We pursue a system-level approach where a complete model for the system is developed that captures the interactions between different layers, as well as different sensor quality measures. For network optimization, we propose a hierarchical optimization algorithm that lends itself to the tree structure, requiring only local network information. The proposed design approach shows superior performance over several contentionless and contention-based network design approaches. PMID:26307989

Topology-optimized metasurfaces: impact of initial geometric layout.

PubMed

Yang, Jianji; Fan, Jonathan A

2017-08-15

Topology optimization is a powerful iterative inverse design technique in metasurface engineering and can transform an initial layout into a high-performance device. With this method, devices are optimized within a local design phase space, making the identification of suitable initial geometries essential. In this Letter, we examine the impact of initial geometric layout on the performance of large-angle (75 deg) topology-optimized metagrating deflectors. We find that when conventional metasurface designs based on dielectric nanoposts are used as initial layouts for topology optimization, the final devices have efficiencies around 65%. In contrast, when random initial layouts are used, the final devices have ultra-high efficiencies that can reach 94%. Our numerical experiments suggest that device topologies based on conventional metasurface designs may not be suitable to produce ultra-high-efficiency, large-angle metasurfaces. Rather, initial geometric layouts with non-trivial topologies and shapes are required.

Optimal control theory determination of feasible return-to-launch-site aborts for the HL-20 Personnel Launch System vehicle

NASA Technical Reports Server (NTRS)

Dutton, Kevin E.

1994-01-01

The personnel launch system (PLS) being studied by NASA is a system to complement the space shuttle and provide alternative access to space. The PLS consists of a manned spacecraft launched by an expendable launch vehicle (ELV). A candidate for the manned spacecraft is the HL-20 lifting body. In the event of an ELV malfunction during the initial portion of the ascent trajectory, the HL-20 will separate from the rocket and perform an unpowered return to launch site (RTLS) abort. This work details an investigation, using optimal control theory, of the RTLS abort scenario. The objective of the optimization was to maximize final altitude. With final altitude as the cost function, the feasibility of an RTLS abort at different times during the ascent was determined. The method of differential inclusions was used to determine the optimal state trajectories, and the optimal controls were then calculated from the optimal states and state rates.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Detection of Zaire ebolavirus in swine: Assay development and optimization.

PubMed

Pickering, B S; Collignon, B; Smith, G; Marszal, P; Kobinger, G; Weingartl, H M

2018-02-01

Ebolaviruses (family Filoviridae, order Mononegavirales) cause often fatal, haemorrhagic fever in primates including humans. Pigs have been identified as a species susceptible to Reston ebolavirus (RESTV) infection, with indicated transmission to humans in the Philippines; however, their role during Ebola outbreaks in Africa needs to be clarified. To perform surveillance studies, detection of ebolavirus requires a prerequisite validation of viral RNA and antibody detection methods in swine samples. These diagnostic tests also need to be suitable for deployment to low-level containment laboratories. In this study, we developed a set of tests for detection of antibodies against Zaire ebolavirus (EBOV) in swine. Recombinant EBOV nucleoprotein was produced using a baculovirus expression system for indirect ELISA development. Evaluation of this assay was performed using laboratory and field samples, achieving a diagnostic specificity of 99%. Importantly, the indirect ELISA was able to detect antibodies to EBOV at 7 dpi, 3 days earlier than virus neutralization tests (VNT). The format of the VNT in this work was modified to a microtitre plaque reduction neutralization assay (miPRNT) complemented with immunostaining to provide a more rapid and highly specific assay. Finally, a confirmatory immunoblot assay was generated to supplement the indirect ELISA results. © 2017 Her Majesty the Queen in Right of Canada Reproduced with the permission of the Minister of Health and Agriculture, Canadian Food Inspection Agency.

Detection of Ochratoxin a Using Molecular Beacons and Real-Time PCR Thermal Cycler

PubMed Central

Sanzani, Simona Marianna; Reverberi, Massimo; Fanelli, Corrado; Ippolito, Antonio

2015-01-01

We developed a simple and cheap assay for quantitatively detecting ochratoxin A (OTA) in wine. A DNA aptamer available in literature was used as recognition probe in its molecular beacon form, i.e., with a fluorescence-quenching pair at the stem ends. Our aptabeacon could adopt a conformation allowing OTA binding, causing a fluorescence rise due to the increased distance between fluorophore and quencher. We used real-time PCR equipment for capturing the signal. With this assay, under optimized conditions, the entire process can be completed within 1 h. In addition, the proposed system exhibited a good selectivity for OTA against other mycotoxins (ochratoxin B and aflatoxin M1) and limited interference from aflatoxin B1 and patulin. A wide linear detection range (0.2–2000 µM) was achieved, with LOD = 13 nM, r = 0.9952, and R2 = 0.9904. The aptabeacon was also applied to detect OTA in red wine spiked with the same dilution series. A linear correlation with a LOD = 19 nM, r = 0.9843, and R2 = 0.9708 was observed, with recoveries in the range 63%–105%. Intra- and inter-day assays confirmed its reproducibility. The proposed biosensor, although still being finalized, might significantly facilitate the quantitative detection of OTA in wine samples, thus improving their quality control from a food safety perspective. PMID:25760080

Microfluidic paper-based analytical device for particulate metals.

PubMed

Mentele, Mallory M; Cunningham, Josephine; Koehler, Kirsten; Volckens, John; Henry, Charles S

2012-05-15

A microfluidic paper-based analytical device (μPAD) fabricated by wax printing was designed to assess occupational exposure to metal-containing aerosols. This method employs rapid digestion of particulate metals using microliters of acid added directly to a punch taken from an air sampling filter. Punches were then placed on a μPAD, and digested metals were transported to detection reservoirs upon addition of water. These reservoirs contained reagents for colorimetric detection of Fe, Cu, and Ni. Dried buffer components were used to set the optimal pH in each detection reservoir, while precomplexation agents were deposited in the channels between the sample and detection zones to minimize interferences from competing metals. Metal concentrations were quantified from color intensity images using a scanner in conjunction with image processing software. Reproducible, log-linear calibration curves were generated for each metal, with method detection limits ranging from 1.0 to 1.5 μg for each metal (i.e., total mass present on the μPAD). Finally, a standard incineration ash sample was aerosolized, collected on filters, and analyzed for the three metals of interest. Analysis of this collected aerosol sample using a μPAD showed good correlation with known amounts of the metals present in the sample. This technology can provide rapid assessment of particulate metal concentrations at or below current regulatory limits and at dramatically reduced cost.

Ligation with Nucleic Acid Sequence–Based Amplification

PubMed Central

Ong, Carmichael; Tai, Warren; Sarma, Aartik; Opal, Steven M.; Artenstein, Andrew W.; Tripathi, Anubhav

2012-01-01

This work presents a novel method for detecting nucleic acid targets using a ligation step along with an isothermal, exponential amplification step. We use an engineered ssDNA with two variable regions on the ends, allowing us to design the probe for optimal reaction kinetics and primer binding. This two-part probe is ligated by T4 DNA Ligase only when both parts bind adjacently to the target. The assay demonstrates that the expected 72-nt RNA product appears only when the synthetic target, T4 ligase, and both probe fragments are present during the ligation step. An extraneous 38-nt RNA product also appears due to linear amplification of unligated probe (P3), but its presence does not cause a false-positive result. In addition, 40 mmol/L KCl in the final amplification mix was found to be optimal. It was also found that increasing P5 in excess of P3 helped with ligation and reduced the extraneous 38-nt RNA product. The assay was also tested with a single nucleotide polymorphism target, changing one base at the ligation site. The assay was able to yield a negative signal despite only a single-base change. Finally, using P3 and P5 with longer binding sites results in increased overall sensitivity of the reaction, showing that increasing ligation efficiency can improve the assay overall. We believe that this method can be used effectively for a number of diagnostic assays. PMID:22449695

Optimizing Probability of Detection Point Estimate Demonstration

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

2017-01-01

Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-18231and associated mh18232POD software gives most common methods of POD analysis. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. The paper provides discussion on optimizing probability of detection (POD) demonstration experiments using Point Estimate Method. POD Point estimate method is used by NASA for qualifying special NDE procedures. The point estimate method uses binomial distribution for probability density. Normally, a set of 29 flaws of same size within some tolerance are used in the demonstration. The optimization is performed to provide acceptable value for probability of passing demonstration (PPD) and achieving acceptable value for probability of false (POF) calls while keeping the flaw sizes in the set as small as possible.

Supersonic Aerodynamic Design Improvements of an Arrow-Wing HSCT Configuration Using Nonlinear Point Design Methods

NASA Technical Reports Server (NTRS)

Unger, Eric R.; Hager, James O.; Agrawal, Shreekant

1999-01-01

This paper is a discussion of the supersonic nonlinear point design optimization efforts at McDonnell Douglas Aerospace under the High-Speed Research (HSR) program. The baseline for these optimization efforts has been the M2.4-7A configuration which represents an arrow-wing technology for the High-Speed Civil Transport (HSCT). Optimization work on this configuration began in early 1994 and continued into 1996. Initial work focused on optimization of the wing camber and twist on a wing/body configuration and reductions of 3.5 drag counts (Euler) were realized. The next phase of the optimization effort included fuselage camber along with the wing and a drag reduction of 5.0 counts was achieved. Including the effects of the nacelles and diverters into the optimization problem became the next focus where a reduction of 6.6 counts (Euler W/B/N/D) was eventually realized. The final two phases of the effort included a large set of constraints designed to make the final optimized configuration more realistic and they were successful albeit with a loss of performance.

Maximizing the Biochemical Resolving Power of Fluorescence Microscopy

PubMed Central

Esposito, Alessandro; Popleteeva, Marina; Venkitaraman, Ashok R.

2013-01-01

Most recent advances in fluorescence microscopy have focused on achieving spatial resolutions below the diffraction limit. However, the inherent capability of fluorescence microscopy to non-invasively resolve different biochemical or physical environments in biological samples has not yet been formally described, because an adequate and general theoretical framework is lacking. Here, we develop a mathematical characterization of the biochemical resolution in fluorescence detection with Fisher information analysis. To improve the precision and the resolution of quantitative imaging methods, we demonstrate strategies for the optimization of fluorescence lifetime, fluorescence anisotropy and hyperspectral detection, as well as different multi-dimensional techniques. We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information in fluorescence detection. These strategies enable the optimal use of the information content available within the limited photon-budget typically available in fluorescence microscopy. This theoretical foundation leads to a generalized strategy for the optimization of multi-dimensional optical detection, and demonstrates how the parallel detection of all properties of fluorescence can maximize the biochemical resolving power of fluorescence microscopy, an approach we term Hyper Dimensional Imaging Microscopy (HDIM). Our work provides a theoretical framework for the description of the biochemical resolution in fluorescence microscopy, irrespective of spatial resolution, and for the development of a new class of microscopes that exploit multi-parametric detection systems. PMID:24204821

A Multi-Scale Settlement Matching Algorithm Based on ARG

NASA Astrophysics Data System (ADS)

Yue, Han; Zhu, Xinyan; Chen, Di; Liu, Lingjia

2016-06-01

Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.

Compact SOI optimized slot microring coupled phase-shifted Bragg grating resonator for sensing

NASA Astrophysics Data System (ADS)

Zhao, Chao Ying; Zhang, Lei; Zhang, Cheng Mei

2018-05-01

We propose a novel sensor structure composed of a slot microring and a phase-shifted sidewall Bragg gratings in a slot waveguide. We first present a theoretical analysis of transmission by using the transfer matrix. Then, the mode-field distributions of transmission spectrum obtained from 3D simulations based on FDTD method demonstrates that our sensor exhibit theoretical sensitivity of 297 . 13 nm / RIU, a minimum detection limit of 1 . 1 × 10-4 RIU, the maximum extinction ratio of 20 dB, the quality factor of 2 × 103 and a compact dimension-theoretical structure of 15 μm × 8 . 5 μm. Finally, the sensor's performance is simulated for NaCl solution.

Array automated assembly task, phase 2. Low cost silicon solar array project

NASA Technical Reports Server (NTRS)

Rhee, S. S.; Jones, G. T.; Allison, K. T.

1978-01-01

Several modifications instituted in the wafer surface preparation process served to significantly reduce the process cost to 1.55 cents per peak watt in 1975 cents. Performance verification tests of a laser scanning system showed a limited capability to detect hidden cracks or defects, but with potential equipment modifications this cost effective system could be rendered suitable for applications. Installation of electroless nickel plating system was completed along with an optimization of the wafer plating process. The solder coating and flux removal process verification test was completed. An optimum temperature range of 500-550 C was found to produce uniform solder coating with the restriction that a modified dipping procedure is utilized. Finally, the construction of the spray-on dopant equipment was completed.

Distributed Sensing and Processing for Multi-Camera Networks

NASA Astrophysics Data System (ADS)

Sankaranarayanan, Aswin C.; Chellappa, Rama; Baraniuk, Richard G.

Sensor networks with large numbers of cameras are becoming increasingly prevalent in a wide range of applications, including video conferencing, motion capture, surveillance, and clinical diagnostics. In this chapter, we identify some of the fundamental challenges in designing such systems: robust statistical inference, computationally efficiency, and opportunistic and parsimonious sensing. We show that the geometric constraints induced by the imaging process are extremely useful for identifying and designing optimal estimators for object detection and tracking tasks. We also derive pipelined and parallelized implementations of popular tools used for statistical inference in non-linear systems, of which multi-camera systems are examples. Finally, we highlight the use of the emerging theory of compressive sensing in reducing the amount of data sensed and communicated by a camera network.

Overview of field gamma spectrometries based on Si-photomultiplier

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Design optimization of rear uprights for UniMAP Automotive Racing Team Formula SAE racing car

NASA Astrophysics Data System (ADS)

Azmeer, M.; Basha, M. H.; Hamid, M. F.; Rahman, M. T. A.; Hashim, M. S. M.

2017-10-01

In an automobile, the rear upright are used to provide a physical mounting and links the suspension arms to the hub and wheel assembly. In this work, static structural and shape optimization analysis for rear upright for UniMAP’s Formula SAE racing car had been done using ANSYS software with the objective to reduce weight while maintaining the structural strength of the vehicle upright. During the shape optimization process, the component undergoes 25%, 50% and 75 % weight reduction in order to find the best optimal shape of the upright. The final design of the upright is developed considering the weight reduction, structural integrity and the manufacturability. The final design achieved 21 % weight reduction and is able to withstand several loads.

Final Report: Pilot Region-Based Optimization Program for Fund-Lead Sites, EPA Region III

EPA Pesticide Factsheets

This report describes a pilot study for a Region-based optimization program, implemented by a Regional Optimization Evaluation Team (ROET) that was conducted in U.S. EPA Region III at Fund-lead sites with pump-and-treat (P&T) systems.

Study on the Simultaneously Quantitative Detection for β-Lactoglobulin and Lactoferrin of Cow Milk by Using Protein Chip Technique.

PubMed

Yin, Ji Yong; Huo, Jun Sheng; Ma, Xin Xin; Sun, Jing; Huang, Jian

2017-12-01

To research a protein chip method which can simultaneously quantitative detect β-Lactoglobulin (β-L) and Lactoferrin (Lf) at one time. Protein chip printer was used to print both anti-β-L antibodies and anti-Lf antibodies on each block of protein chip. And then an improved sandwich detection method was applied while the other two detecting antibodies for the two antigens were added in the block after they were mixed. The detection conditions of the quantitative detection for simultaneous measurement of β-L and Lf with protein chip were optimized and evaluated. Based on these detected conditions, two standard curves of the two proteins were simultaneously established on one protein chip. Finally, the new detection method was evaluated by using the analysis of precision and accuracy. By comparison experiment, mouse monoclonal antibodies of the two antigens were chosen as the printing probe. The concentrations of β-L and Lf probes were 0.5 mg/mL and 0.5 mg/mL, respectively, while the titers of detection antibodies both of β-L and Lf were 1:2,000. Intra- and inter-assay variability was between 4.88% and 38.33% for all tests. The regression coefficients of protein chip comparing with ELISA for β-L and Lf were better than 0.734, and both of the two regression coefficients were statistically significant (r = 0.734, t = 2.644, P = 0.038; and r = 0.774, t = 2.998, P = 0.024). A protein chip method of simultaneously quantitative detection for β-L and Lf has been established and this method is worthy in further application. Copyright © 2017 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.

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.

Multiresidue analysis of endocrine-disrupting compounds and perfluorinated sulfates and carboxylic acids in sediments by ultra-high-performance liquid chromatography-tandem mass spectrometry.

PubMed

Cavaliere, Chiara; Capriotti, Anna Laura; Ferraris, Francesca; Foglia, Patrizia; Samperi, Roberto; Ventura, Salvatore; Laganà, Aldo

2016-03-18

A multiresidue analytical method for the determination of 11 perfluorinated compounds and 22 endocrine-disrupting compounds (ECDs) including 13 natural and synthetic estrogens (free and conjugated forms), 2 alkylphenols, 1 plasticiser, 2 UV-filters, 1 antimicrobial, and 2 organophosphorus compounds in sediments has been developed. Ultrasound-assisted extraction followed by solid phase extraction (SPE) with graphitized carbon black (GCB) cartridge as clean-up step were used. The extraction process yield was optimized in terms of solvent composition. Then, a 3(2) experimental design was used to optimize solvent volume and sonication time by response surface methodology, which simplifies the optimization procedure. The final extract was analyzed by ultra-high performance liquid chromatography coupled with tandem mass spectrometry. The optimized sample preparation method is simple and robust, and allows recovery of ECDs belonging to different classes in a complex matrix such as sediment. The use of GCB for SPE allowed to obtain with a single clean-up procedure excellent recoveries ranging between 75 and 110% (relative standard deviation <16%). The developed methodology has been successfully applied to the analysis of ECDs in sediments from different rivers and lakes of the Lazio Region (Italy). These analyses have shown the ubiquitous presence of chloro-substituted organophosphorus flame retardants and bisphenol A, while other analyzed compounds were occasionally found at concentration between the limit of detection and quantification. Copyright © 2016 Elsevier B.V. All rights reserved.

Critical evaluation of distillation procedure for the determination of methylmercury in soil samples.

PubMed

Perez, Pablo A; Hintelman, Holger; Quiroz, Waldo; Bravo, Manuel A

2017-11-01

In the present work, the efficiency of distillation process for extracting monomethylmercury (MMHg) from soil samples was studied and optimized using an experimental design methodology. The influence of soil composition on MMHg extraction was evaluated by testing of four soil samples with different geochemical characteristics. Optimization suggested that the acid concentration and the duration of the distillation process were most significant and the most favorable conditions, established as a compromise for the studied soils, were determined to be a 70 min distillation using an 0.2 M acid. Corresponding limits of detection (LOD) and quantification (LOQ) were 0.21 and 0.7 pg absolute, respectively. The optimized methodology was applied with satisfactory results to soil samples and was compared to a reference methodology based on isotopic dilution analysis followed by gas chromatography-inductively coupled plasma mass spectrometry (IDA-GC-ICP-MS). Using the optimized conditions, recoveries ranged from 82 to 98%, which is an increase of 9-34% relative to the previously used standard operating procedure. Finally, the validated methodology was applied to quantify MMHg in soils collected from different sites impacted by coal fired power plants in the north-central zone of Chile, measuring MMHg concentrations ranging from 0.091 to 2.8 ng g -1 . These data are to the best of our knowledge the first MMHg measurements reported for Chile. Copyright © 2017 Elsevier Ltd. All rights reserved.

Learning-based 3D surface optimization from medical image reconstruction

NASA Astrophysics Data System (ADS)

Wei, Mingqiang; Wang, Jun; Guo, Xianglin; Wu, Huisi; Xie, Haoran; Wang, Fu Lee; Qin, Jing

2018-04-01

Mesh optimization has been studied from the graphical point of view: It often focuses on 3D surfaces obtained by optical and laser scanners. This is despite the fact that isosurfaced meshes of medical image reconstruction suffer from both staircases and noise: Isotropic filters lead to shape distortion, while anisotropic ones maintain pseudo-features. We present a data-driven method for automatically removing these medical artifacts while not introducing additional ones. We consider mesh optimization as a combination of vertex filtering and facet filtering in two stages: Offline training and runtime optimization. In specific, we first detect staircases based on the scanning direction of CT/MRI scanners, and design a staircase-sensitive Laplacian filter (vertex-based) to remove them; and then design a unilateral filtered facet normal descriptor (uFND) for measuring the geometry features around each facet of a given mesh, and learn the regression functions from a set of medical meshes and their high-resolution reference counterparts for mapping the uFNDs to the facet normals of the reference meshes (facet-based). At runtime, we first perform staircase-sensitive Laplacian filter on an input MC (Marching Cubes) mesh, and then filter the mesh facet normal field using the learned regression functions, and finally deform it to match the new normal field for obtaining a compact approximation of the high-resolution reference model. Tests show that our algorithm achieves higher quality results than previous approaches regarding surface smoothness and surface accuracy.

Chiral micellar electrokinetic chromatography-atmospheric pressure photoionization of benzoin derivatives using mixed molecular micelles.

PubMed

He, Jun; Shamsi, Shahab A

2011-05-01

In the present work we report, for the first time, the successful on-line coupling of chiral MEKC (CMEKC) to atmospheric pressure photoionization MS (APPI-MS). Four structurally similar neutral test solutes (e.g. benzoin (BNZ) derivatives) were successfully ionized by APPI-MS. The mass spectra in the positive ion mode showed that the protonated molecular ions of BNZs are not the most abundant fragment ions. Simultaneous enantioseparation by CMEKC and on-line APPI-MS detection of four photoinitiators, hydrobenzoin, BNZ, benzoin methyl ether, benzoin ethyl ether, were achieved using an optimized molar ratio of mixed molecular micelle of two polymeric chiral surfactants (polysodium N-undecenoxy carbonyl-L-leucinate and polysodium N-undecenoyl-L,L-leucylvalinate). The CMEKC conditions, such as voltage, chiral polymeric surfactant concentration, buffer pH, and BGE concentration, were optimized using a multivariate central composite design (CCD). The sheath liquid composition (involving %v/v methanol, dopant concentration, electrolyte additive concentration, and flow rate) and spray chamber parameters (drying gas flow rate, drying gas temperature, and vaporizer temperature) were also optimized with CCD. Models built based on the CCD results and response surface method were used to analyze the interactions between factors and their effects on the responses. The final overall optimum conditions for CMEKC-APPI-MS were also predicted and found in agreement with the experimentally optimized parameters. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design of helicopter rotor blades for optimum dynamic characteristics

NASA Technical Reports Server (NTRS)

Peters, D. A.; Ko, T.; Korn, A.; Rossow, M. P.

1984-01-01

The optimal design of helicopter rotor blades is addressed. The forced response of an initial (i.e., non-optimized) blade to those of a final (optimized) blade are compared. Response of starting design and optimal designs for varying forcing frequencies, blade response to harmonics of rotor speed, and derivation of mass and stiffness matrices or functions of natural frequencies are discussed.

Graphene quantum dot as a green and facile sensor for free chlorine in drinking water.

PubMed

Dong, Yongqiang; Li, Geli; Zhou, Nana; Wang, Ruixue; Chi, Yuwu; Chen, Guonan

2012-10-02

Free chlorine was found to be able to destroy the passivated surface of the graphene quantum dots (GQDs) obtained by pyrolyzing citric acid, resulting in significant quenching of their fluorescence (FL) signal. After optimizing some experimental conditions (including response time, concentration of GQDs, and pH value of solution), a green and facile sensing system has been developed for the detection of free residual chlorine in water based on FL quenching of GQDs. The sensing system exhibits many advantages, such as short response time, excellent selectivity, wide linear response range, and high sensitivity. The linear response range of free chlorine (R(2) = 0.992) was from 0.05 to 10 μM. The detection limit (S/N = 3) was as low as 0.05 μM, which is much lower than that of the most widely used N-N-diethyl-p-phenylenediamine (DPD) colorimetric method. This sensing system was finally used to detect free residual chlorine in local tap water samples. The result agreed well with that by the DPD colorimetric method, suggesting the potential application of this new, green, sensitive, and facile sensing system in drinking water quality monitoring.

Electrochemical detection of dopamine based on pre-concentration by graphene nanosheets.

PubMed

Bagherzadeh, Mojtaba; Heydari, Maryam

2013-10-21

Herein, graphene nanosheets (GNS) were synthesized, by a green and facile method based on reduction by glucose, and characterized. Afterwards, a carbon paste electrode (CPE) was modified with GNS by casting and drying GNS on top of the CPE (CPE/GNS). The behavior of the CPE/GNS towards dopamine (DA) and ascorbic acid (AA) was investigated by electrochemical methods and the obtained results showed that the CPE/GNS had adsorbed only DA. Based on this behavior, the DA molecules were pre-concentrated on top of the CPE/GNS, followed by stripping in DA free solution. Subsequent to experimental and instrumental optimization, a calibration curve from 2.0 × 10(-6) to 1.0 × 10(-3) M DA, r(2) = 0.99 (±0.01), with detection limit (DL) = 8.5 × 10(-7) M DA, sensitivity = 15.4 (±0.94) μA, and RSD = 6.1 was observed in the presence of 1.0 × 10(-3) M AA. Finally, the performance of the CPE/GNS was successfully tested in a pharmaceutical sample. This work provides a promising strategy for DA detection in the presence of biological interferences, e.g. AA, with high sensitivity and simple characteristics.

Exploring Sampling in the Detection of Multicategory EEG Signals

PubMed Central

Siuly, Siuly; Kabir, Enamul; Wang, Hua; Zhang, Yanchun

2015-01-01

The paper presents a structure based on samplings and machine leaning techniques for the detection of multicategory EEG signals where random sampling (RS) and optimal allocation sampling (OS) are explored. In the proposed framework, before using the RS and OS scheme, the entire EEG signals of each class are partitioned into several groups based on a particular time period. The RS and OS schemes are used in order to have representative observations from each group of each category of EEG data. Then all of the selected samples by the RS from the groups of each category are combined in a one set named RS set. In the similar way, for the OS scheme, an OS set is obtained. Then eleven statistical features are extracted from the RS and OS set, separately. Finally this study employs three well-known classifiers: k-nearest neighbor (k-NN), multinomial logistic regression with a ridge estimator (MLR), and support vector machine (SVM) to evaluate the performance for the RS and OS feature set. The experimental outcomes demonstrate that the RS scheme well represents the EEG signals and the k-NN with the RS is the optimum choice for detection of multicategory EEG signals. PMID:25977705

Nanomaterial-Based Electrochemical Immunosensors for Clinically Significant Biomarkers

PubMed Central

Ronkainen, Niina J.; Okon, Stanley L.

2014-01-01

Nanotechnology has played a crucial role in the development of biosensors over the past decade. The development, testing, optimization, and validation of new biosensors has become a highly interdisciplinary effort involving experts in chemistry, biology, physics, engineering, and medicine. The sensitivity, the specificity and the reproducibility of biosensors have improved tremendously as a result of incorporating nanomaterials in their design. In general, nanomaterials-based electrochemical immunosensors amplify the sensitivity by facilitating greater loading of the larger sensing surface with biorecognition molecules as well as improving the electrochemical properties of the transducer. The most common types of nanomaterials and their properties will be described. In addition, the utilization of nanomaterials in immunosensors for biomarker detection will be discussed since these biosensors have enormous potential for a myriad of clinical uses. Electrochemical immunosensors provide a specific and simple analytical alternative as evidenced by their brief analysis times, inexpensive instrumentation, lower assay cost as well as good portability and amenability to miniaturization. The role nanomaterials play in biosensors, their ability to improve detection capabilities in low concentration analytes yielding clinically useful data and their impact on other biosensor performance properties will be discussed. Finally, the most common types of electroanalytical detection methods will be briefly touched upon. PMID:28788700

Solid-state voltammetry-based electrochemical immunosensor for Escherichia coli using graphene oxide-Ag nanoparticle composites as labels.

PubMed

Jiang, Xiaochun; Chen, Kun; Wang, Jing; Shao, Kang; Fu, Tao; Shao, Feng; Lu, Donglian; Liang, Jiangong; Foda, M Frahat; Han, Heyou

2013-06-21

A new electrochemical immunosensor based on solid-state voltammetry was fabricated for the detection of Escherichia coli (E. coli) by using graphene oxide-Ag nanoparticle composites (P-GO-Ag) as labels. To construct the platform, Au nanoparticles (AuNPs) were first self-assembled on an Au electrode surface through cysteamine and served as an effective matrix for antibody (Ab) attachment. Under a sandwich-type immunoassay format, the analyte and the probe (P-GO-Ag-Ab) were successively captured onto the immunosensor. Finally, the bonded AgNPs were detected through a solid-state redox process in 0.2 M of KCl solution. Combining the advantages of the high-loading capability of graphene oxide with promoted electron-transfer rate of AuNPs, this immunosensor produced a 26.92-fold signal enhancement compared with the unamplified protocol. Under the optimal conditions, the immunosensor exhibited a wide linear dependence on the logarithm of the concentration of E. coli ranging from 50 to 1.0 × 10(6) cfu mL(-1) with a detection limit of 10 cfu mL(-1). Moreover, as a practical application, the proposed immunosensor was used to monitor E. coli in lake water with satisfactory results.

Simultaneous determination of sucralose and related compounds by high-performance liquid chromatography with evaporative light scattering detection.

PubMed

Yan, Wenwu; Wang, Nani; Zhang, Peimin; Zhang, Jiajie; Wu, Shuchao; Zhu, Yan

2016-08-01

Sucralose is widely used in food and beverages as sweetener. Current synthesis approaches typically provide sucralose products with varying levels of related chlorinated carbohydrates which can affect the taste and flavor-modifying properties of sucralose. Quantification of related compounds in sucralose is often hampered by the lack of commercially available standards. In this work, nine related compounds were purified (purity>97%) and identified by liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR), then a rapid and simple HPLC coupled with evaporative light scattering detection (ELSD) method has been developed for the simultaneous determination of sucralose and related compounds. Under optimized conditions, the method showed good linearity in the range of 2-600μgmL(-1) with determination coefficients R(2)⩾0.9990. Moreover, low limits of detection in the range of 0.5-2.0μgmL(-1) and good repeatability (RSD<3%, n=6) were obtained. Recoveries were from 96.8% to 101.2%. Finally, the method has been successfully applied to sucralose quality control and purification process monitoring. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimization of information content in a mass spectrometry based flow-chemistry system by investigating different ionization approaches.

PubMed

Martha, Cornelius T; Hoogendoorn, Jan-Carel; Irth, Hubertus; Niessen, Wilfried M A

2011-05-15

Current development in catalyst discovery includes combinatorial synthesis methods for the rapid generation of compound libraries combined with high-throughput performance-screening methods to determine the associated activities. Of these novel methodologies, mass spectrometry (MS) based flow chemistry methods are especially attractive due to the ability to combine sensitive detection of the formed reaction product with identification of introduced catalyst complexes. Recently, such a mass spectrometry based continuous-flow reaction detection system was utilized to screen silver-adducted ferrocenyl bidentate catalyst complexes for activity in a multicomponent synthesis of a substituted 2-imidazoline. Here, we determine the merits of different ionization approaches by studying the combination of sensitive detection of product formation in the continuous-flow system with the ability to simultaneous characterize the introduced [ferrocenyl bidentate+Ag](+) catalyst complexes. To this end, we study the ionization characteristics of electrospray ionization (ESI), atmospheric-pressure chemical ionization (APCI), no-discharge APCI, dual ESI/APCI, and dual APCI/no-discharge APCI. Finally, we investigated the application potential of the different ionization approaches by the investigation of ferrocenyl bidentate catalyst complex responses in different solvents. Copyright © 2011 Elsevier B.V. All rights reserved.

Christmas-tree Derived Amplification Immuno-strategy for Sensitive Visual Detection of Vibrio parahaemolyticus Based on Gold Label Silver Stain Technology.

PubMed

Song, Xinxin; Wu, Yanjie; Wu, Lin; Hu, Yufang; Li, Wenrou; Guo, Zhiyong; Su, Xiurong; Jiang, Xiaohua

2017-01-01

A developed Christmas-tree derived immunosensor based on a gold label silver stain (GLSS) technique was fabricated for a highly sensitive analysis of Vibrio parahaemolyticu (VP). In this strategy, captured VP antibody (cAb) was immobilized on a solid substrate; then, the VPs were sequentially tagged with a signal probe by incubating the assay with a detection VP antibody (dAb) conjugated gold nanoparticles (AuNPs)-labeled graphite-like carbon nitride (g-C 3 N 4 ). Finally, the attached signal probe could harvest a visible signal by the silver meal deposition, and then followed by homebrew Matlab 6.0 as a grey value acquisition. In addition, the overall design of the biosensor was established in abundant AuNPs and g-C 3 N 4 with a two-dimensional structure, affording a bulb-decorated Christmas-tree model. Moreover, with the optimized conditions, the detection limit of the as-proposed biosensor is as low as 10 2 CFU (Colony-Forming Units) mL -1 , exhibiting an increase of two orders of magnitude compared with the traditional immune-gold method. Additionally, the developed visible immunosensor was also successfully applied to the analysis of complicated samples.

Optimized small molecule antibody labeling efficiency through continuous flow centrifugal diafiltration.

PubMed

Cappione, Amedeo; Mabuchi, Masaharu; Briggs, David; Nadler, Timothy

2015-04-01

Protein immuno-detection encompasses a broad range of analytical methodologies, including western blotting, flow cytometry, and microscope-based applications. These assays which detect, quantify, and/or localize expression for one or more proteins in complex biological samples, are reliant upon fluorescent or enzyme-tagged target-specific antibodies. While small molecule labeling kits are available with a range of detection moieties, the workflow is hampered by a requirement for multiple dialysis-based buffer exchange steps that are both time-consuming and subject to sample loss. In a previous study, we briefly described an alternative method for small-scale protein labeling with small molecule dyes whereby all phases of the conjugation workflow could be performed in a single centrifugal diafiltration device. Here, we expand on this foundational work addressing functionality of the device at each step in the workflow (sample cleanup, labeling, unbound dye removal, and buffer exchange/concentration) and the implications for optimizing labeling efficiency. When compared to other common buffer exchange methodologies, centrifugal diafiltration offered superior performance as measured by four key parameters (process time, desalting capacity, protein recovery, retain functional integrity). Originally designed for resin-based affinity purification, the device also provides a platform for up-front antibody purification or albumin carrier removal. Most significantly, by exploiting the rapid kinetics of NHS-based labeling reactions, the process of continuous diafiltration minimizes reaction time and long exposure to excess dye, guaranteeing maximal target labeling while limiting the risks associated with over-labeling. Overall, the device offers a simplified workflow with reduced processing time and hands-on requirements, without sacrificing labeling efficiency, final yield, or conjugate performance. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of online, continuous heavy metals detection and monitoring sensors based on microfluidic plasma reactors

NASA Astrophysics Data System (ADS)

Abdul-Majeed, Wameath Sh

This research is dedicated to develop a fully integrated system for heavy metals determination in water samples based on micro fluidic plasma atomizers. Several configurations of dielectric barrier discharge (DBD) atomizer are designed, fabricated and tested toward this target. Finally, a combination of annular and rectangular DBD atomizers has been utilized to develop a scheme for heavy metals determination. The present thesis has combined both theoretical and experimental investigations to fulfil the requirements. Several mathematical studies are implemented to explore the optimal design parameters for best system performance. On the other hand, expanded experimental explorations are conducted to assess the proposed operational approaches. The experiments were designed according to a central composite rotatable design; hence, an empirical model has been produced for each studied case. Moreover, several statistical approaches are adopted to analyse the system performance and to deduce the optimal operational parameters.. The introduction of the examined analyte to the plasma atomizer has been achieved by applying chemical schemes, where the element in the sample has been derivitized by using different kinds of reducing agents to produce vapour species (e.g. hydrides) for a group of nine elements examined in this research individually and simultaneously. Moreover, other derivatization schemes based on photochemical vapour generation assisted by ultrasound irradiation are also investigated. Generally speaking, the detection limits achieved in this research for the examined set of elements (by applying hydroborate scheme) are found to be acceptable in accordance with the standard limits in drinking water. The results of copper compared with the data from other technologies in the literature, showed a competitive detection limit obtained from applying the developed scheme, with an advantage of conducting simultaneous, fully automated, insitu, online- real time analysis as well as a possibility of connecting the proposed device to control loops..

Discovery of a novel calcium-sensitive fluorescent probe for α-ketoglutarate.

PubMed

Gan, Lin-Lin; Chen, Lin-Hai; Nan, Fa-Jun

2017-12-01

α-Ketoglutarate (α-KG), a pivotal metabolite in energy metabolism, has been implicated in nonalcoholic fatty liver disease (NAFLD) and several cancers. It is recently proposed that plasma α-KG is a surrogate biomarker of NAFLD. Here, we report the development of a novel "turn-on" chemosensor for α-KG that contains a coumarin moiety as a fluorophore. Using benzothiazole-coumarin (BTC) as inspiration, we designed a probe for calcium ion recognition that possesses a unique fluorophore compared with previously reported probes for α-KG measurement. This chemosensor is based on the specific Schiff base reaction and the calcium ion recognition property of the widely used calcium indicator BTC. The probe was synthesized, and a series of parallel experiments were conducted to optimize the chemical recognition process. Compared to the initial weak fluorescence, a remarkable 7.6-fold enhancement in fluorescence intensity (I/I 0 at 495 nm) was observed for the conditions in which the probe (1 μmol/L), α-KG (50 μmol/L), and Ca 2+ (100 μmol/L) were incubated at 30 °C in EtOH. The probe displayed good selectivity for α-KG even in an environment with an abundance of amino acids and other interfering species such as glutaric acid. We determined that the quantitative detection range of α-KG in EtOH was between 5 and 50 μmol/L. Finally, probe in serum loaded with α-KG (10 mmol/L) showed a 7.4-fold fluorescence enhancement. In summary, a novel probe for detecting the biomarker α-KG through a typical Schiff base reaction has been discovered. With further optimization, this probe may be a good alternative for detecting the physiological metabolite α-KG.

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Saliency-Guided Change Detection of Remotely Sensed Images Using Random Forest

NASA Astrophysics Data System (ADS)

Feng, W.; Sui, H.; Chen, X.

2018-04-01

Studies based on object-based image analysis (OBIA) representing the paradigm shift in change detection (CD) have achieved remarkable progress in the last decade. Their aim has been developing more intelligent interpretation analysis methods in the future. The prediction effect and performance stability of random forest (RF), as a new kind of machine learning algorithm, are better than many single predictors and integrated forecasting method. In this paper, we present a novel CD approach for high-resolution remote sensing images, which incorporates visual saliency and RF. First, highly homogeneous and compact image super-pixels are generated using super-pixel segmentation, and the optimal segmentation result is obtained through image superimposition and principal component analysis (PCA). Second, saliency detection is used to guide the search of interest regions in the initial difference image obtained via the improved robust change vector analysis (RCVA) algorithm. The salient regions within the difference image that correspond to the binarized saliency map are extracted, and the regions are subject to the fuzzy c-means (FCM) clustering to obtain the pixel-level pre-classification result, which can be used as a prerequisite for superpixel-based analysis. Third, on the basis of the optimal segmentation and pixel-level pre-classification results, different super-pixel change possibilities are calculated. Furthermore, the changed and unchanged super-pixels that serve as the training samples are automatically selected. The spectral features and Gabor features of each super-pixel are extracted. Finally, superpixel-based CD is implemented by applying RF based on these samples. Experimental results on Ziyuan 3 (ZY3) multi-spectral images show that the proposed method outperforms the compared methods in the accuracy of CD, and also confirm the feasibility and effectiveness of the proposed approach.

Application of modified hollow fiber liquid phase microextraction in conjunction with chromatography-electron capture detection for quantification of acrylamide in waste water samples at ultra-trace levels.

PubMed

Sobhi, Hamid Reza; Ghambarian, Mahnaz; Behbahani, Mohammad; Esrafili, Ali

2017-03-03

Herein, a simple and sensitive method was successfully developed for the extraction and quantification of acrylamide in water samples. Initially, acrylamide was derivatized through a bromination process. Subsequently, a modified hollow-fiber liquid-phase microextraction was applied for the extraction of the brominated acrylamide from a 10-ml portion of an aqueous sample. Briefly, in this method, the derivatized acrylamide (2,3-dibromopropionamide) was extracted from the aqueous sample into a thin layer of an organic solvent sustained in pores of a porous hollow fiber. Then, it was back-extracted using a small volume of organic acceptor solution (acetonitril, 25μl) located inside the lumen of the hollow fiber followed by gas chromatography-electron capture detection (GC-ECD). The optimal conditions were examined for the extraction of the analyte such as: the organic solvent: dihexyl ether+10% tri-n-octyl phosphine oxide; stirring rate: 750rpm; no salt addition and 30min extraction time. These optimal extraction conditions allowed excellent enrichment factor values for the method. Enrichment factor, detection limit (S/N=3) and dynamic linear range of 60, 2ngL -1 and 50-1000ngL -1 to be determined for the analyte. The relative standard deviations (RSD%) representing precision of the method were in the range of 2.2-5.8 based on the average of three measurements. Accuracy of the method was tested by the relative recovery experiments on spiked samples, with results ranging from 93 to 108%. Finally, the method proved to be simple, rapid, and cost-effective for routine screen of acrylamide-contaminated highly-complicated untreated waste water samples. Copyright © 2017 Elsevier B.V. All rights reserved.

The performance of matched-field track-before-detect methods using shallow-water Pacific data.

PubMed

Tantum, Stacy L; Nolte, Loren W; Krolik, Jeffrey L; Harmanci, Kerem

2002-07-01

Matched-field track-before-detect processing, which extends the concept of matched-field processing to include modeling of the source dynamics, has recently emerged as a promising approach for maintaining the track of a moving source. In this paper, optimal Bayesian and minimum variance beamforming track-before-detect algorithms which incorporate a priori knowledge of the source dynamics in addition to the underlying uncertainties in the ocean environment are presented. A Markov model is utilized for the source motion as a means of capturing the stochastic nature of the source dynamics without assuming uniform motion. In addition, the relationship between optimal Bayesian track-before-detect processing and minimum variance track-before-detect beamforming is examined, revealing how an optimal tracking philosophy may be used to guide the modification of existing beamforming techniques to incorporate track-before-detect capabilities. Further, the benefits of implementing an optimal approach over conventional methods are illustrated through application of these methods to shallow-water Pacific data collected as part of the SWellEX-1 experiment. The results show that incorporating Markovian dynamics for the source motion provides marked improvement in the ability to maintain target track without the use of a uniform velocity hypothesis.

Superconducting Magnetometry for Cardiovascular Studies and AN Application of Adaptive Filtering.

NASA Astrophysics Data System (ADS)

Leifer, Mark Curtis

Sensitive magnetic detectors utilizing Superconducting Quantum Interference Devices (SQUID's) have been developed and used for studying the cardiovascular system. The theory of magnetic detection of cardiac currents is discussed, and new experimental data supporting the validity of the theory is presented. Measurements on both humans and dogs, in both healthy and diseased states, are presented using the new technique, which is termed vector magnetocardiography. In the next section, a new type of superconducting magnetometer with a room temperature pickup is analyzed, and techniques for optimizing its sensitivity to low-frequency sub-microamp currents are presented. Performance of the actual device displays significantly improved sensitivity in this frequency range, and the ability to measure currents in intact, in vivo biological fibers. The final section reviews the theoretical operation of a digital self-optimizing filter, and presents a four-channel software implementation of the system. The application of the adaptive filter to enhancement of geomagnetic signals for earthquake forecasting is discussed, and the adaptive filter is shown to outperform existing techniques in suppressing noise from geomagnetic records.

Process control systems: integrated for future process technologies

NASA Astrophysics Data System (ADS)

Botros, Youssry; Hajj, Hazem M.

2003-06-01

Process Control Systems (PCS) are becoming more crucial to the success of Integrated Circuit makers due to their direct impact on product quality, cost, and Fab output. The primary objective of PCS is to minimize variability by detecting and correcting non optimal performance. Current PCS implementations are considered disparate, where each PCS application is designed, deployed and supported separately. Each implementation targets a specific area of control such as equipment performance, wafer manufacturing, and process health monitoring. With Intel entering the nanometer technology era, tighter process specifications are required for higher yields and lower cost. This requires areas of control to be tightly coupled and integrated to achieve the optimal performance. This requirement can be achieved via consistent design and deployment of the integrated PCS. PCS integration will result in several benefits such as leveraging commonalities, avoiding redundancy, and facilitating sharing between implementations. This paper will address PCS implementations and focus on benefits and requirements of the integrated PCS. Intel integrated PCS Architecture will be then presented and its components will be briefly discussed. Finally, industry direction and efforts to standardize PCS interfaces that enable PCS integration will be presented.

Effects of dwell time of excitation waveform on meniscus movements for a tubular piezoelectric print-head: experiments and model

NASA Astrophysics Data System (ADS)

Chang, Jiaqing; Liu, Yaxin; Huang, Bo

2017-07-01

In inkjet applications, it is normal to search for an optimal drive waveform when dispensing a fresh fluid or adjusting a newly fabricated print-head. To test trial waveforms with different dwell times, a camera and a strobe light were used to image the protruding or retracting liquid tongues without ejecting any droplets. An edge detection method was used to calculate the lengths of the liquid tongues to draw the meniscus movement curves. The meniscus movement is determined by the time-domain response of the acoustic pressure at the nozzle of the print-head. Starting at the inverse piezoelectric effect, a mathematical model which considers the liquid viscosity in acoustic propagation is constructed to study the acoustic pressure response at the nozzle of the print-head. The liquid viscosity retards the propagation speed and dampens the harmonic amplitude. The pressure response, which is the combined effect of the acoustic pressures generated during the rising time and the falling time and after their propagations and reflections, explains the meniscus movements well. Finally, the optimal dwell time for droplet ejections is discussed.

Modeling-based design and assessment of an acousto-optic guided high-intensity focused ultrasound system

PubMed Central

Adams, Matthew T.; Cleveland, Robin O.; Roy, Ronald A.

2017-01-01

Abstract. Real-time acousto-optic (AO) sensing has been shown to noninvasively detect changes in ex vivo tissue optical properties during high-intensity focused ultrasound (HIFU) exposures. The technique is particularly appropriate for monitoring noncavitating lesions that offer minimal acoustic contrast. A numerical model is presented for an AO-guided HIFU system with an illumination wavelength of 1064 nm and an acoustic frequency of 1.1 MHz. To confirm the model’s accuracy, it is compared to previously published experimental data gathered during AO-guided HIFU in chicken breast. The model is used to determine an optimal design for an AO-guided HIFU system, to assess its robustness, and to predict its efficacy for the ablation of large volumes. It was found that a through transmission geometry results in the best performance, and an optical wavelength around 800 nm was optimal as it provided sufficient contrast with low absorption. Finally, it was shown that the strategy employed while treating large volumes with AO guidance has a major impact on the resulting necrotic volume and symmetry. PMID:28114454

Identifying protein complexes based on brainstorming strategy.

PubMed

Shen, Xianjun; Zhou, Jin; Yi, Li; Hu, Xiaohua; He, Tingting; Yang, Jincai

2016-11-01

Protein complexes comprising of interacting proteins in protein-protein interaction network (PPI network) play a central role in driving biological processes within cells. Recently, more and more swarm intelligence based algorithms to detect protein complexes have been emerging, which have become the research hotspot in proteomics field. In this paper, we propose a novel algorithm for identifying protein complexes based on brainstorming strategy (IPC-BSS), which is integrated into the main idea of swarm intelligence optimization and the improved K-means algorithm. Distance between the nodes in PPI network is defined by combining the network topology and gene ontology (GO) information. Inspired by human brainstorming process, IPC-BSS algorithm firstly selects the clustering center nodes, and then they are separately consolidated with the other nodes with short distance to form initial clusters. Finally, we put forward two ways of updating the initial clusters to search optimal results. Experimental results show that our IPC-BSS algorithm outperforms the other classic algorithms on yeast and human PPI networks, and it obtains many predicted protein complexes with biological significance. Copyright © 2016 Elsevier Inc. All rights reserved.

Current advances in mathematical modeling of anti-cancer drug penetration into tumor tissues.

PubMed

Kim, Munju; Gillies, Robert J; Rejniak, Katarzyna A

2013-11-18

Delivery of anti-cancer drugs to tumor tissues, including their interstitial transport and cellular uptake, is a complex process involving various biochemical, mechanical, and biophysical factors. Mathematical modeling provides a means through which to understand this complexity better, as well as to examine interactions between contributing components in a systematic way via computational simulations and quantitative analyses. In this review, we present the current state of mathematical modeling approaches that address phenomena related to drug delivery. We describe how various types of models were used to predict spatio-temporal distributions of drugs within the tumor tissue, to simulate different ways to overcome barriers to drug transport, or to optimize treatment schedules. Finally, we discuss how integration of mathematical modeling with experimental or clinical data can provide better tools to understand the drug delivery process, in particular to examine the specific tissue- or compound-related factors that limit drug penetration through tumors. Such tools will be important in designing new chemotherapy targets and optimal treatment strategies, as well as in developing non-invasive diagnosis to monitor treatment response and detect tumor recurrence.

Sensitive and selective determination of Cu2+ at D-penicillamine functionalized nano-cellulose modified pencil graphite electrode

NASA Astrophysics Data System (ADS)

Taheri, M.; Ahour, F.; Keshipour, S.

2018-06-01

A novel electrochemical sensor based on D-penicillamine anchored nano-cellulose (DPA-NC) modified pencil graphite electrode was fabricated and used for highly selective and sensitive determination of copper (II) ions in the picomolar concentration by square wave adsorptive stripping voltammetric (SWV) method. The modified electrode showed better and increased SWV response compared to the bare and NC modified electrodes which may be related to the porous structure of modifier along with formation of complex between Cu2+ ions and nitrogen or oxygen containing groups in DPA-NC. Optimization of various experimental parameters influence the performance of the sensor, were investigated. Under optimized condition, DPA-NC modified electrode was used for the analysis of Cu2+ in the concentration range from 0.2 to 50 pM, and a lower detection limit of 0.048 pM with good stability, repeatability, and selectivity. Finally, the practical applicability of DPA-NC-PGE was confirmed via measuring trace amount of Cu (II) in tap and river water samples.

Application of response surface methodology for determination of methyl red in water samples by spectrophotometry method.

PubMed

Khodadoust, Saeid; Ghaedi, Mehrorang

2014-12-10

In this study a rapid and effective method (dispersive liquid-liquid microextraction (DLLME)) was developed for extraction of methyl red (MR) prior to its determination by UV-Vis spectrophotometry. Influence variables on DLLME such as volume of chloroform (as extractant solvent) and methanol (as dispersive solvent), pH and ionic strength and extraction time were investigated. Then significant variables were optimized by using a Box-Behnken design (BBD) and desirability function (DF). The optimized conditions (100μL of chloroform, 1.3mL of ethanol, pH 4 and 4% (w/v) NaCl) resulted in a linear calibration graph in the range of 0.015-10.0mgmL(-1) of MR in initial solution with R(2)=0.995 (n=5). The limits of detection (LOD) and limit of quantification (LOQ) were 0.005 and 0.015mgmL(-1), respectively. Finally, the DLLME method was applied for determination of MR in different water samples with relative standard deviation (RSD) less than 5% (n=5). Copyright © 2014 Elsevier B.V. All rights reserved.

New CNT/poly(brilliant green) and CNT/poly(3,4-ethylenedioxythiophene) based electrochemical enzyme biosensors.

PubMed

Barsan, Madalina M; Pifferi, Valentina; Falciola, Luigi; Brett, Christopher M A

2016-07-13

A combination of the electroactive polymer poly(brilliant green) (PBG) or conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) with carbon nanotubes to obtain CNT/PBG and CNT/PEDOT modified carbon film electrodes (CFE) has been investigated as a new biosensor platform, incorporating the enzymes glucose oxidase (GOx) as test enzyme, alcohol oxidase (AlcOx) or alcohol dehydrogenase (AlcDH). The sensing parameters were optimized for all biosensors based on CNT/PBG/CFE, CNT/PEDOT/CFE platforms. Under optimized conditions, both GOx biosensors exhibited very similar sensitivities, while in the case of AlcOx and AlcDH biosensors, AlcOx/CNT/PBG/CFE was found to give a higher sensitivity and lower detection limit. The influence of dissolved O2 on oxidase-biosensor performance was investigated and was shown to be different for each enzyme. Comparisons were made with similar reported biosensors, showing the advantages of the new biosensors, and excellent selectivity against potential interferents was successfully demonstrated. Finally, alcohol biosensors were successfully used for the determination of ethanol in alcoholic beverages. Copyright © 2016 Elsevier B.V. All rights reserved.

Towards the identification of alkaline phosphatase binding ligands in Li-Dan-Hua-Shi pills: A Box-Behnken design optimized affinity selection approach tandem with UHPLC-Q-TOF/MS analysis.

PubMed

Tao, Yi; Huang, Surun; Gu, Xianghui; Li, Weidong; Cai, Baochang

2018-05-30

Alkaline phosphatase conjugated magnetic microspheres were synthesized via amide reaction, and employed as an effective adsorbent in affinity selection of binding ligands followed by UHPLC-Q-TOF/MS analysis. The analytical validity of the developed approach was evaluated under optimized conditions and the following figures of merit were obtained: linearity, 0.01-0.5 g L -1 with good determination coefficients (R 2  = 0.9992); limits of detection (LODs), 0.003 g L -1 ; and limits of quantitation (LOQ), 0.01 g L -1 . The precision (RSD%) of the proposed affinity selection approach was studied based on intra-day (0.8%) and inter-day (1.3%) precisions. Finally, the adsorbent was successfully applied to identification of binding ligands in Li-Dan-Hua-Shi pills and good recoveries were obtained in the range from 96.9 to 99.4% (RSDs 1.6-3.0%). Copyright © 2018 Elsevier B.V. All rights reserved.

Enhanced MALDI-TOF MS Analysis of Phosphopeptides Using an Optimized DHAP/DAHC Matrix

PubMed Central

Hou, Junjie; Xie, Zhensheng; Xue, Peng; Cui, Ziyou; Chen, Xiulan; Li, Jing; Cai, Tanxi; Wu, Peng; Yang, Fuquan

2010-01-01

Selecting an appropriate matrix solution is one of the most effective means of increasing the ionization efficiency of phosphopeptides in matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). In this study, we systematically assessed matrix combinations of 2, 6-dihydroxyacetophenone (DHAP) and diammonium hydrogen citrate (DAHC), and demonstrated that the low ratio DHAP/DAHC matrix was more effective in enhancing the ionization of phosphopeptides. Low femtomole level of phosphopeptides from the tryptic digests of α-casein and β-casein was readily detected by MALDI-TOF-MS in both positive and negative ion mode without desalination or phosphopeptide enrichment. Compared with the DHB/PA matrix, the optimized DHAP/DAHC matrix yielded superior sample homogeneity and higher phosphopeptide measurement sensitivity, particularly when multiple phosphorylated peptides were assessed. Finally, the DHAP/DAHC matrix was applied to identify phosphorylation sites from α-casein and β-casein and to characterize two phosphorylation sites from the human histone H1 treated with Cyclin-Dependent Kinase-1 (CDK1) by MALDI-TOF/TOF MS. PMID:20339515

Surface Roughness Optimization Using Taguchi Method of High Speed End Milling For Hardened Steel D2

NASA Astrophysics Data System (ADS)

Hazza Faizi Al-Hazza, Muataz; Ibrahim, Nur Asmawiyah bt; Adesta, Erry T. Y.; Khan, Ahsan Ali; Abdullah Sidek, Atiah Bt.

2017-03-01

The main challenge for any manufacturer is to achieve higher quality of their final products with maintains minimum machining time. In this research final surface roughness analysed and optimized with maximum 0.3 mm flank wear length. The experiment was investigated the effect of cutting speed, feed rate and depth of cut on the final surface roughness using D2 as a work piece hardened to 52-56 HRC, and coated carbide as cutting tool with higher cutting speed 120-240 mm/min. The experiment has been conducted using L9 design of Taguchi collection. The results have been analysed using JMP software.

Optic disc detection using ant colony optimization

NASA Astrophysics Data System (ADS)

Dias, Marcy A.; Monteiro, Fernando C.

2012-09-01

The retinal fundus images are used in the treatment and diagnosis of several eye diseases, such as diabetic retinopathy and glaucoma. This paper proposes a new method to detect the optic disc (OD) automatically, due to the fact that the knowledge of the OD location is essential to the automatic analysis of retinal images. Ant Colony Optimization (ACO) is an optimization algorithm inspired by the foraging behaviour of some ant species that has been applied in image processing for edge detection. Recently, the ACO was used in fundus images to detect edges, and therefore, to segment the OD and other anatomical retinal structures. We present an algorithm for the detection of OD in the retina which takes advantage of the Gabor wavelet transform, entropy and ACO algorithm. Forty images of the retina from DRIVE database were used to evaluate the performance of our method.

Heat Sink Design and Optimization

DTIC Science & Technology

2015-12-01

HEAT SINK DESIGN AND OPTIMIZATION I...REPORT DATE (DD-MM-YYYY) December 2015 2. REPORT TYPE Final 3. DATES COVERED (From – To) 4. TITLE AND SUBTITLE HEAT SINK DESIGN AND OPTIMIZATION...distribution is unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Heat sinks are devices that are used to enhance heat dissipation

LDRD Final Report: Global Optimization for Engineering Science Problems

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

HART,WILLIAM E.

1999-12-01

For a wide variety of scientific and engineering problems the desired solution corresponds to an optimal set of objective function parameters, where the objective function measures a solution's quality. The main goal of the LDRD ''Global Optimization for Engineering Science Problems'' was the development of new robust and efficient optimization algorithms that can be used to find globally optimal solutions to complex optimization problems. This SAND report summarizes the technical accomplishments of this LDRD, discusses lessons learned and describes open research issues.