Radio Galaxy Zoo: Machine learning for radio source host galaxy cross-identification

NASA Astrophysics Data System (ADS)

Alger, M. J.; Banfield, J. K.; Ong, C. S.; Rudnick, L.; Wong, O. I.; Wolf, C.; Andernach, H.; Norris, R. P.; Shabala, S. S.

2018-05-01

We consider the problem of determining the host galaxies of radio sources by cross-identification. This has traditionally been done manually, which will be intractable for wide-area radio surveys like the Evolutionary Map of the Universe (EMU). Automated cross-identification will be critical for these future surveys, and machine learning may provide the tools to develop such methods. We apply a standard approach from computer vision to cross-identification, introducing one possible way of automating this problem, and explore the pros and cons of this approach. We apply our method to the 1.4 GHz Australian Telescope Large Area Survey (ATLAS) observations of the Chandra Deep Field South (CDFS) and the ESO Large Area ISO Survey South 1 (ELAIS-S1) fields by cross-identifying them with the Spitzer Wide-area Infrared Extragalactic (SWIRE) survey. We train our method with two sets of data: expert cross-identifications of CDFS from the initial ATLAS data release and crowdsourced cross-identifications of CDFS from Radio Galaxy Zoo. We found that a simple strategy of cross-identifying a radio component with the nearest galaxy performs comparably to our more complex methods, though our estimated best-case performance is near 100 per cent. ATLAS contains 87 complex radio sources that have been cross-identified by experts, so there are not enough complex examples to learn how to cross-identify them accurately. Much larger datasets are therefore required for training methods like ours. We also show that training our method on Radio Galaxy Zoo cross-identifications gives comparable results to training on expert cross-identifications, demonstrating the value of crowdsourced training data.

Vibro-Acoustic Modulation Based Damage Identification in a Composite Skin-Stiffener Structure

NASA Technical Reports Server (NTRS)

Ooijevaar, T. H.; Loendersloot, R.; Rogge, M. D.; Akkerman, R.; Tinga, T.

2014-01-01

The vibro-acoustic modulation method is applied to a composite skin-stiffener structure to investigate the possibilities to utilize this method for damage identification in terms of detection, localisation and damage quantification. The research comprises a theoretical part and an experimental part. An impact load is applied to the skin-stiffener structure, resulting in a delamination underneath the stiffener. The structure is interrogated with a low frequency pump excitation and a high frequency carrier excitation. The analysis of the response in a frequency band around the carrier frequency is employed to assess the damage identification capabilities and to gain a better understanding of the modulations occurring and the underlying physical phenomena. Though vibro-acoustic is shown to be a sensitive method for damage identification, the complexity of the damage, combined with a high modal density, complicate the understanding of the relation between the physical phenomena and the modulations occurring. more research is recommended to reveal the physics behind the observations.

[Regional atmospheric environment risk source identification and assessment].

PubMed

Zhang, Xiao-Chun; Chen, Wei-Ping; Ma, Chun; Zhan, Shui-Fen; Jiao, Wen-Tao

2012-12-01

Identification and assessment for atmospheric environment risk source plays an important role in regional atmospheric risk assessment and regional atmospheric pollution prevention and control. The likelihood exposure and consequence assessment method (LEC method) and the Delphi method were employed to build a fast and effective method for identification and assessment of regional atmospheric environment risk sources. This method was applied to the case study of a large coal transportation port in North China. The assessment results showed that the risk characteristics and the harm degree of regional atmospheric environment risk source were in line with the actual situation. Fast and effective identification and assessment of risk source has laid an important foundation for the regional atmospheric environmental risk assessment and regional atmospheric pollution prevention and control.

Multiscale global identification of porous structures

NASA Astrophysics Data System (ADS)

Hatłas, Marcin; Beluch, Witold

2018-01-01

The paper is devoted to the evolutionary identification of the material constants of porous structures based on measurements conducted on a macro scale. Numerical homogenization with the RVE concept is used to determine the equivalent properties of a macroscopically homogeneous material. Finite element method software is applied to solve the boundary-value problem in both scales. Global optimization methods in form of evolutionary algorithm are employed to solve the identification task. Modal analysis is performed to collect the data necessary for the identification. A numerical example presenting the effectiveness of proposed attitude is attached.

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry applied to virus identification

PubMed Central

Calderaro, Adriana; Arcangeletti, Maria-Cristina; Rodighiero, Isabella; Buttrini, Mirko; Gorrini, Chiara; Motta, Federica; Germini, Diego; Medici, Maria-Cristina; Chezzi, Carlo; De Conto, Flora

2014-01-01

Virus detection and/or identification traditionally rely on methods based on cell culture, electron microscopy and antigen or nucleic acid detection. These techniques are good, but often expensive and/or time-consuming; furthermore, they not always lead to virus identification at the species and/or type level. In this study, Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) was tested as an innovative tool to identify human polioviruses and to identify specific viral protein biomarkers in infected cells. The results revealed MALDI-TOF MS to be an effective and inexpensive tool for the identification of the three poliovirus serotypes. The method was firstly applied to Sabin reference strains, and then to isolates from different clinical samples, highlighting its value as a time-saving, sensitive and specific technique when compared to the gold standard neutralization assay and casting new light on its possible application to virus detection and/or identification. PMID:25354905

A forward model-based validation of cardiovascular system identification

NASA Technical Reports Server (NTRS)

Mukkamala, R.; Cohen, R. J.

2001-01-01

We present a theoretical evaluation of a cardiovascular system identification method that we previously developed for the analysis of beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure, and instantaneous lung volume. The method provides a dynamical characterization of the important autonomic and mechanical mechanisms responsible for coupling the fluctuations (inverse modeling). To carry out the evaluation, we developed a computational model of the cardiovascular system capable of generating realistic beat-to-beat variability (forward modeling). We applied the method to data generated from the forward model and compared the resulting estimated dynamics with the actual dynamics of the forward model, which were either precisely known or easily determined. We found that the estimated dynamics corresponded to the actual dynamics and that this correspondence was robust to forward model uncertainty. We also demonstrated the sensitivity of the method in detecting small changes in parameters characterizing autonomic function in the forward model. These results provide confidence in the performance of the cardiovascular system identification method when applied to experimental data.

19 CFR 191.14 - Identification of merchandise or articles by accounting method.

Code of Federal Regulations, 2010 CFR

2010-04-01

... applies to identification of merchandise or articles in inventory or storage, as well as identification of... identified as being received into and withdrawn from the same inventory. Even if merchandise or articles are... or articles under this section, subject to the conditions of this section. If any such inventory...

Yeast identification: reassessment of assimilation tests as sole universal identifiers.

PubMed

Spencer, J; Rawling, S; Stratford, M; Steels, H; Novodvorska, M; Archer, D B; Chandra, S

2011-11-01

To assess whether assimilation tests in isolation remain a valid method of identification of yeasts, when applied to a wide range of environmental and spoilage isolates. Seventy-one yeast strains were isolated from a soft drinks factory. These were identified using assimilation tests and by D1/D2 rDNA sequencing. When compared to sequencing, assimilation test identifications (MicroLog™) were 18·3% correct, a further 14·1% correct within the genus and 67·6% were incorrectly identified. The majority of the latter could be attributed to the rise in newly reported yeast species. Assimilation tests alone are unreliable as a universal means of yeast identification, because of numerous new species, variability of strains and increasing coincidence of assimilation profiles. Assimilation tests still have a useful role in the identification of common species, such as the majority of clinical isolates. It is probable, based on these results, that many yeast identifications reported in older literature are incorrect. This emphasizes the crucial need for accurate identification in present and future publications. © 2011 The Authors. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.

System Identification of Mistuned Bladed Disks from Traveling Wave Response Measurements

NASA Technical Reports Server (NTRS)

Feiner, D. M.; Griffin, J. H.; Jones, K. W.; Kenyon, J. A.; Mehmed, O.; Kurkov, A. P.

2003-01-01

A new approach to modal analysis is presented. By applying this technique to bladed disk system identification methods, one can determine the mistuning in a rotor based on its response to a traveling wave excitation. This allows system identification to be performed under rotating conditions, and thus expands the applicability of existing mistuning identification techniques from integrally bladed rotors to conventional bladed disks.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Metamodel-based inverse method for parameter identification: elastic-plastic damage model

NASA Astrophysics Data System (ADS)

Huang, Changwu; El Hami, Abdelkhalak; Radi, Bouchaïb

2017-04-01

This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic-plastic damage model parameter identification. An elastic-plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic-plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.

Decoupling Identification for Serial Two-Link Two-Inertia System

NASA Astrophysics Data System (ADS)

Oaki, Junji; Adachi, Shuichi

The purpose of our study is to develop a precise model by applying the technique of system identification for the model-based control of a nonlinear robot arm, under taking joint-elasticity into consideration. We previously proposed a systematic identification method, called “decoupling identification,” for a “SCARA-type” planar two-link robot arm with elastic joints caused by the Harmonic-drive® reduction gears. The proposed method serves as an extension of the conventional rigid-joint-model-based identification. The robot arm is treated as a serial two-link two-inertia system with nonlinearity. The decoupling identification method using link-accelerometer signals enables the serial two-link two-inertia system to be divided into two linear one-link two-inertia systems. The MATLAB®'s commands for state-space model estimation are utilized in the proposed method. Physical parameters such as motor inertias, link inertias, joint-friction coefficients, and joint-spring coefficients are estimated through the identified one-link two-inertia systems using a gray-box approach. This paper describes accuracy evaluations using the two-link arm for the decoupling identification method under introducing closed-loop-controlled elements and varying amplitude-setup of identification-input. Experimental results show that the identification method also works with closed-loop-controlled elements. Therefore, the identification method is applicable to a “PUMA-type” vertical robot arm under gravity.

Parametric system identification of catamaran for improving controller design

NASA Astrophysics Data System (ADS)

Timpitak, Surasak; Prempraneerach, Pradya; Pengwang, Eakkachai

2018-01-01

This paper presents an estimation of simplified dynamic model for only surge- and yaw- motions of catamaran by using system identification (SI) techniques to determine associated unknown parameters. These methods will enhance the performance of designing processes for the motion control system of Unmanned Surface Vehicle (USV). The simulation results demonstrate an effective way to solve for damping forces and to determine added masses by applying least-square and AutoRegressive Exogenous (ARX) methods. Both methods are then evaluated according to estimated parametric errors from the vehicle’s dynamic model. The ARX method, which yields better estimated accuracy, can then be applied to identify unknown parameters as well as to help improving a controller design of a real unmanned catamaran.

A loop-mediated isothermal amplification method for a differential identification of Taenia tapeworms from human: application to a field survey.

PubMed

Nkouawa, Agathe; Sako, Yasuhito; Li, Tiaoying; Chen, Xingwang; Nakao, Minoru; Yanagida, Tetsuya; Okamoto, Munehiro; Giraudoux, Patrick; Raoul, Francis; Nakaya, Kazuhiro; Xiao, Ning; Qiu, Jiamin; Qiu, Dongchuan; Craig, Philip S; Ito, Akira

2012-12-01

In this study, we applied a loop-mediated isothermal amplification method for identification of human Taenia tapeworms in Tibetan communities in Sichuan, China. Out of 51 proglottids recovered from 35 carriers, 9, 1, and 41 samples were identified as Taenia solium, Taenia asiatica and Taenia saginata, respectively. Same results were obtained afterwards in the laboratory, except one sample. These results demonstrated that the LAMP method enabled rapid identification of parasites in the field surveys, which suggested that this method would contribute to the control of Taenia infections in endemic areas. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Simple and fast multiplex PCR method for detection of species origin in meat products.

PubMed

Izadpanah, Mehrnaz; Mohebali, Nazanin; Elyasi Gorji, Zahra; Farzaneh, Parvaneh; Vakhshiteh, Faezeh; Shahzadeh Fazeli, Seyed Abolhassan

2018-02-01

Identification of animal species is one of the major concerns in food regulatory control and quality assurance system. Different approaches have been used for species identification in animal origin of feedstuff. This study aimed to develop a multiplex PCR approach to detect the origin of meat and meat products. Specific primers were designed based on the conserved region of mitochondrial Cytochrome C Oxidase subunit I ( COX1 ) gene. This method could successfully distinguish the origin of the pig, camel, sheep, donkey, goat, cow, and chicken in one single reaction. Since PCR products derived from each species represent unique molecular weight, the amplified products could be identified by electrophoresis and analyzed based on their size. Due to the synchronized amplification of segments within a single PCR reaction, multiplex PCR is considered to be a simple, fast, and inexpensive technique that can be applied for identification of meat products in food industries. Nowadays, this technique has been considered as a practical method to identify the species origin, which could further applied for animal feedstuffs identification.

Experimental studies of forensic odontology to aid in the identification process

PubMed Central

Saxena, Susmita; Sharma, Preeti; Gupta, Nitin

2010-01-01

The importance of dental identification is on the increase year after year. With the passage of time, the role of forensic odontology has increased as very often teeth and dental restorations are the only means of identification. Forensic odontology has played a key role in identification of persons in mass disasters (aviation, earthquakes, Tsunamis), in crime investigations, in ethnic studies, and in identification of decomposed and disfigured bodies like that of drowned persons, fire victims, and victims of motor vehicle accidents. The various methods employed in forensic odontology include tooth prints, radiographs, photographic study, rugoscopy, cheiloscopy and molecular methods. Investigative methods applied in forensic odontology are reasonably reliable, yet the shortcomings must be accounted for to make it a more meaningful and relevant procedure. This paper gives an overview of the various experimental studies to aid in the identification processes, discussing their feasibilities and limitations in day-to-day practice. PMID:21731343

Moment Method and Pixel-by-Pixel Method: Complementary Mode Identification I. Testing FG Vir-like pulsation modes

NASA Astrophysics Data System (ADS)

Zima, W.; Kolenberg, K.; Briquet, M.; Breger, M.

2004-06-01

We have carried out a Hare-and-Hound test to determine the reliability of the Moment Method (Briquet & Aerts 2003) and the Pixel-by-Pixel Method (Mantegazza 2000) for the identification of pulsation modes in Delta Scuti stars. For this purpose we calculated synthetic line profiles, exhibiting six pulsation modes of low degree and with input parameters initially unknown to us. The aim was to test and increase the quality of the mode identification by applying both methods independently and by using a combined technique. Our results show that, whereas the azimuthal order m and its sign can be fixed by both methods, the degree l is not determined unambiguously. Both identification methods show a better reliability if multiple modes are fitted simultaneously. In particular, the inclination angle is better determined. We have to emphasize that the outcome of this test is only meaningful for stars having pulsational velocities below 0.2 vsini. This is the first part of a series of articles, in which we will test these spectroscopic identification methods.

[Literature review of the influences on error rates when identifying equids with transponder and hot-iron branding].

PubMed

Campe, Amely; Schulz, Sophia; Bohnet, Willa

2016-01-01

Although equids have had to be tagged with a transponder since 2009, breeding associations in Germany disagree as to which method is best suited for identification (with or without hot iron branding). Therefore, the aim of this systematic literature review was to gain an overview of how effective identification is using transponders and hot iron branding and as to which factors influence the success of identification. Existing literature showed that equids can be identified by means of transponders with a probability of 85-100%, whereas symbol brandings could be identified correctly in 78-89%, whole number brandings in 0-87% and single figures in 37-92% of the readings, respectively. The successful reading of microchips can be further optimised by a correctly operated implantation process and thorough training of the applying persons. affect identification with a scanner. The removal of transponders for manipulation purposes is virtually impossible. Influences during the application of branding marks can hardly, if at all, be standardised, but influence the subsequent readability relevantly. Therefore, identification by means of hot branding cannot be considered sufficiently reliable. Impaired quality of identification can be reduced during reading but cannot be counteracted. Based on the existing studies it can be concluded that the transponder method is the best suited of the investigated methods for clearly identifying equids, being forgery-proof and permanent. It is not to be expected that applying hot branding in addition to microchips would optimise the probability of identification relevantly.

Damage identification of a TLP floating wind turbine by meta-heuristic algorithms

NASA Astrophysics Data System (ADS)

Ettefagh, M. M.

2015-12-01

Damage identification of the offshore floating wind turbine by vibration/dynamic signals is one of the important and new research fields in the Structural Health Monitoring (SHM). In this paper a new damage identification method is proposed based on meta-heuristic algorithms using the dynamic response of the TLP (Tension-Leg Platform) floating wind turbine structure. The Genetic Algorithms (GA), Artificial Immune System (AIS), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) are chosen for minimizing the object function, defined properly for damage identification purpose. In addition to studying the capability of mentioned algorithms in correctly identifying the damage, the effect of the response type on the results of identification is studied. Also, the results of proposed damage identification are investigated with considering possible uncertainties of the structure. Finally, for evaluating the proposed method in real condition, a 1/100 scaled experimental setup of TLP Floating Wind Turbine (TLPFWT) is provided in a laboratory scale and the proposed damage identification method is applied to the scaled turbine.

Parameter identification using a creeping-random-search algorithm

NASA Technical Reports Server (NTRS)

Parrish, R. V.

1971-01-01

A creeping-random-search algorithm is applied to different types of problems in the field of parameter identification. The studies are intended to demonstrate that a random-search algorithm can be applied successfully to these various problems, which often cannot be handled by conventional deterministic methods, and, also, to introduce methods that speed convergence to an extremal of the problem under investigation. Six two-parameter identification problems with analytic solutions are solved, and two application problems are discussed in some detail. Results of the study show that a modified version of the basic creeping-random-search algorithm chosen does speed convergence in comparison with the unmodified version. The results also show that the algorithm can successfully solve problems that contain limits on state or control variables, inequality constraints (both independent and dependent, and linear and nonlinear), or stochastic models.

Recent Advances in Mass Spectrometry for the Identification of Neuro-chemicals and their Metabolites in Biofluids.

PubMed

Kailasa, Suresh Kumar; Wu, Hui-Fen

2013-07-01

Recently, mass spectrometric related techniques have been widely applied for the identification and quantification of neurochemicals and their metabolites in biofluids. This article presents an overview of mass spectrometric techniques applied in the detection of neurological substances and their metabolites from biological samples. In addition, the advances of chromatographic methods (LC, GC and CE) coupled with mass spectrometric techniques for analysis of neurochemicals in pharmaceutical and biological samples are also discussed.

Iterative integral parameter identification of a respiratory mechanics model.

PubMed

Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey

2012-07-18

Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.

Effectiveness of CID, HCD, and ETD with FT MS/MS for degradomic-peptidomic analysis: comparison of peptide identification methods

PubMed Central

Shen, Yufeng; Tolić, Nikola; Xie, Fang; Zhao, Rui; Purvine, Samuel O.; Schepmoes, Athena A.; Ronald, J. Moore; Anderson, Gordon A.; Smith, Richard D.

2011-01-01

We report on the effectiveness of CID, HCD, and ETD for LC-FT MS/MS analysis of peptides using a tandem linear ion trap-Orbitrap mass spectrometer. A range of software tools and analysis parameters were employed to explore the use of CID, HCD, and ETD to identify peptides isolated from human blood plasma without the use of specific “enzyme rules”. In the evaluation of an FDR-controlled SEQUEST scoring method, the use of accurate masses for fragments increased the numbers of identified peptides (by ~50%) compared to the use of conventional low accuracy fragment mass information, and CID provided the largest contribution to the identified peptide datasets compared to HCD and ETD. The FDR-controlled Mascot scoring method provided significantly fewer peptide identifications than with SEQUEST (by 1.3–2.3 fold) at the same confidence levels, and CID, HCD, and ETD provided similar contributions to identified peptides. Evaluation of de novo sequencing and the UStags method for more intense fragment ions revealed that HCD afforded more sequence consecutive residues (e.g., ≥7 amino acids) than either CID or ETD. Both the FDR-controlled SEQUEST and Mascot scoring methods provided peptide datasets that were affected by the decoy database and mass tolerances applied (e.g., the identical peptides between the datasets could be limited to ~70%), while the UStags method provided the most consistent peptide datasets (>90% overlap) with extremely low (near zero) numbers of false positive identifications. The m/z ranges in which CID, HCD, and ETD contributed the largest number of peptide identifications were substantially overlapping. This work suggests that the three peptide ion fragmentation methods are complementary, and that maximizing the number of peptide identifications benefits significantly from a careful match with the informatics tools and methods applied. These results also suggest that the decoy strategy may inaccurately estimate identification FDRs. PMID:21678914

Estimating error rates for firearm evidence identifications in forensic science

PubMed Central

Song, John; Vorburger, Theodore V.; Chu, Wei; Yen, James; Soons, Johannes A.; Ott, Daniel B.; Zhang, Nien Fan

2018-01-01

Estimating error rates for firearm evidence identification is a fundamental challenge in forensic science. This paper describes the recently developed congruent matching cells (CMC) method for image comparisons, its application to firearm evidence identification, and its usage and initial tests for error rate estimation. The CMC method divides compared topography images into correlation cells. Four identification parameters are defined for quantifying both the topography similarity of the correlated cell pairs and the pattern congruency of the registered cell locations. A declared match requires a significant number of CMCs, i.e., cell pairs that meet all similarity and congruency requirements. Initial testing on breech face impressions of a set of 40 cartridge cases fired with consecutively manufactured pistol slides showed wide separation between the distributions of CMC numbers observed for known matching and known non-matching image pairs. Another test on 95 cartridge cases from a different set of slides manufactured by the same process also yielded widely separated distributions. The test results were used to develop two statistical models for the probability mass function of CMC correlation scores. The models were applied to develop a framework for estimating cumulative false positive and false negative error rates and individual error rates of declared matches and non-matches for this population of breech face impressions. The prospect for applying the models to large populations and realistic case work is also discussed. The CMC method can provide a statistical foundation for estimating error rates in firearm evidence identifications, thus emulating methods used for forensic identification of DNA evidence. PMID:29331680

Estimating error rates for firearm evidence identifications in forensic science.

PubMed

Song, John; Vorburger, Theodore V; Chu, Wei; Yen, James; Soons, Johannes A; Ott, Daniel B; Zhang, Nien Fan

2018-03-01

Estimating error rates for firearm evidence identification is a fundamental challenge in forensic science. This paper describes the recently developed congruent matching cells (CMC) method for image comparisons, its application to firearm evidence identification, and its usage and initial tests for error rate estimation. The CMC method divides compared topography images into correlation cells. Four identification parameters are defined for quantifying both the topography similarity of the correlated cell pairs and the pattern congruency of the registered cell locations. A declared match requires a significant number of CMCs, i.e., cell pairs that meet all similarity and congruency requirements. Initial testing on breech face impressions of a set of 40 cartridge cases fired with consecutively manufactured pistol slides showed wide separation between the distributions of CMC numbers observed for known matching and known non-matching image pairs. Another test on 95 cartridge cases from a different set of slides manufactured by the same process also yielded widely separated distributions. The test results were used to develop two statistical models for the probability mass function of CMC correlation scores. The models were applied to develop a framework for estimating cumulative false positive and false negative error rates and individual error rates of declared matches and non-matches for this population of breech face impressions. The prospect for applying the models to large populations and realistic case work is also discussed. The CMC method can provide a statistical foundation for estimating error rates in firearm evidence identifications, thus emulating methods used for forensic identification of DNA evidence. Published by Elsevier B.V.

Competitive code-based fast palmprint identification using a set of cover trees

NASA Astrophysics Data System (ADS)

Yue, Feng; Zuo, Wangmeng; Zhang, David; Wang, Kuanquan

2009-06-01

A palmprint identification system recognizes a query palmprint image by searching for its nearest neighbor from among all the templates in a database. When applied on a large-scale identification system, it is often necessary to speed up the nearest-neighbor searching process. We use competitive code, which has very fast feature extraction and matching speed, for palmprint identification. To speed up the identification process, we extend the cover tree method and propose to use a set of cover trees to facilitate the fast and accurate nearest-neighbor searching. We can use the cover tree method because, as we show, the angular distance used in competitive code can be decomposed into a set of metrics. Using the Hong Kong PolyU palmprint database (version 2) and a large-scale palmprint database, our experimental results show that the proposed method searches for nearest neighbors faster than brute force searching.

15 CFR 325.3 - Applying for a certificate of review.

Code of Federal Regulations, 2011 CFR

2011-01-01

... delivery method that provides evidence of receipt. (b) Contents of application. Any person may submit an.... Some information, in particular the identification of goods or services that the applicant exports or... services. (ii) If it is reasonably available, an identification of the goods or services according to the...

Application of Two-Parameter Stabilizing Functions in Solving a Convolution-Type Integral Equation by Regularization Method

NASA Astrophysics Data System (ADS)

Maslakov, M. L.

2018-04-01

This paper examines the solution of convolution-type integral equations of the first kind by applying the Tikhonov regularization method with two-parameter stabilizing functions. The class of stabilizing functions is expanded in order to improve the accuracy of the resulting solution. The features of the problem formulation for identification and adaptive signal correction are described. A method for choosing regularization parameters in problems of identification and adaptive signal correction is suggested.

Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2013-01-01

A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.

Improving substructure identification accuracy of shear structures using virtual control system

NASA Astrophysics Data System (ADS)

Zhang, Dongyu; Yang, Yang; Wang, Tingqiang; Li, Hui

2018-02-01

Substructure identification is a powerful tool to identify the parameters of a complex structure. Previously, the authors developed an inductive substructure identification method for shear structures. The identification error analysis showed that the identification accuracy of this method is significantly influenced by the magnitudes of two key structural responses near a certain frequency; if these responses are unfavorable, the method cannot provide accurate estimation results. In this paper, a novel method is proposed to improve the substructure identification accuracy by introducing a virtual control system (VCS) into the structure. A virtual control system is a self-balanced system, which consists of some control devices and a set of self-balanced forces. The self-balanced forces counterbalance the forces that the control devices apply on the structure. The control devices are combined with the structure to form a controlled structure used to replace the original structure in the substructure identification; and the self-balance forces are treated as known external excitations to the controlled structure. By optimally tuning the VCS’s parameters, the dynamic characteristics of the controlled structure can be changed such that the original structural responses become more favorable for the substructure identification and, thus, the identification accuracy is improved. A numerical example of 6-story shear structure is utilized to verify the effectiveness of the VCS based controlled substructure identification method. Finally, shake table tests are conducted on a 3-story structural model to verify the efficacy of the VCS to enhance the identification accuracy of the structural parameters.

Gain-Scheduled Fault Tolerance Control Under False Identification

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Belcastro, Christine (Technical Monitor)

2006-01-01

An active fault tolerant control (FTC) law is generally sensitive to false identification since the control gain is reconfigured for fault occurrence. In the conventional FTC law design procedure, dynamic variations due to false identification are not considered. In this paper, an FTC synthesis method is developed in order to consider possible variations of closed-loop dynamics under false identification into the control design procedure. An active FTC synthesis problem is formulated into an LMI optimization problem to minimize the upper bound of the induced-L2 norm which can represent the worst-case performance degradation due to false identification. The developed synthesis method is applied for control of the longitudinal motions of FASER (Free-flying Airplane for Subscale Experimental Research). The designed FTC law of the airplane is simulated for pitch angle command tracking under a false identification case.

Methods for Multiloop Identification of Visual and Neuromuscular Pilot Responses.

PubMed

Olivari, Mario; Nieuwenhuizen, Frank M; Venrooij, Joost; Bülthoff, Heinrich H; Pollini, Lorenzo

2015-12-01

In this paper, identification methods are proposed to estimate the neuromuscular and visual responses of a multiloop pilot model. A conventional and widely used technique for simultaneous identification of the neuromuscular and visual systems makes use of cross-spectral density estimates. This paper shows that this technique requires a specific noninterference hypothesis, often implicitly assumed, that may be difficult to meet during actual experimental designs. A mathematical justification of the necessity of the noninterference hypothesis is given. Furthermore, two methods are proposed that do not have the same limitations. The first method is based on autoregressive models with exogenous inputs, whereas the second one combines cross-spectral estimators with interpolation in the frequency domain. The two identification methods are validated by offline simulations and contrasted to the classic method. The results reveal that the classic method fails when the noninterference hypothesis is not fulfilled; on the contrary, the two proposed techniques give reliable estimates. Finally, the three identification methods are applied to experimental data from a closed-loop control task with pilots. The two proposed techniques give comparable estimates, different from those obtained by the classic method. The differences match those found with the simulations. Thus, the two identification methods provide a good alternative to the classic method and make it possible to simultaneously estimate human's neuromuscular and visual responses in cases where the classic method fails.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis.

PubMed

Carnevale Neto, Fausto; Pilon, Alan C; Selegato, Denise M; Freire, Rafael T; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis

PubMed Central

Carnevale Neto, Fausto; Pilon, Alan C.; Selegato, Denise M.; Freire, Rafael T.; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P.; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts. PMID:27747213

Automated colour identification in melanocytic lesions.

PubMed

Sabbaghi, S; Aldeen, M; Garnavi, R; Varigos, G; Doliantis, C; Nicolopoulos, J

2015-08-01

Colour information plays an important role in classifying skin lesion. However, colour identification by dermatologists can be very subjective, leading to cases of misdiagnosis. Therefore, a computer-assisted system for quantitative colour identification is highly desirable for dermatologists to use. Although numerous colour detection systems have been developed, few studies have focused on imitating the human visual perception of colours in melanoma application. In this paper we propose a new methodology based on QuadTree decomposition technique for automatic colour identification in dermoscopy images. Our approach mimics the human perception of lesion colours. The proposed method is trained on a set of 47 images from NIH dataset and applied to a test set of 190 skin lesions obtained from PH2 dataset. The results of our proposed method are compared with a recently reported colour identification method using the same dataset. The effectiveness of our method in detecting colours in dermoscopy images is vindicated by obtaining approximately 93% accuracy when the CIELab1 colour space is used.

RAPD-PCR characterization of lactobacilli isolated from artisanal meat plants and traditional fermented sausages of Veneto region (Italy).

PubMed

Andrighetto, C; Zampese, L; Lombardi, A

2001-07-01

The study was carried out to evaluate the use of randomly amplified polymorphic DNA-polymerase chain reaction (RAPD-PCR) as a method for the identification of lactobacilli isolated from meat products. RAPD-PCR with primers M13 and D8635 was applied to the identification and intraspecific differentiation of 53 lactobacilli isolates originating from traditional fermented sausages and artisanal meat plants of the Veneto region (Italy). Most of the isolates were assigned to the species Lactobacillus sakei and Lact. curvatus; differentiation of groups of strains within the species was also possible. RAPD-PCR could be applied to the identification of lactobacilli species most commonly found in meat products. The method, which is easy and rapid to perform, could be useful for the study of the lactobacilli populations present in fermented sausages, and could help in the selection of candidate strains to use as starter cultures in meat fermentation.

Estimation of hysteretic damping of structures by stochastic subspace identification

NASA Astrophysics Data System (ADS)

Bajrić, Anela; Høgsberg, Jan

2018-05-01

Output-only system identification techniques can estimate modal parameters of structures represented by linear time-invariant systems. However, the extension of the techniques to structures exhibiting non-linear behavior has not received much attention. This paper presents an output-only system identification method suitable for random response of dynamic systems with hysteretic damping. The method applies the concept of Stochastic Subspace Identification (SSI) to estimate the model parameters of a dynamic system with hysteretic damping. The restoring force is represented by the Bouc-Wen model, for which an equivalent linear relaxation model is derived. Hysteretic properties can be encountered in engineering structures exposed to severe cyclic environmental loads, as well as in vibration mitigation devices, such as Magneto-Rheological (MR) dampers. The identification technique incorporates the equivalent linear damper model in the estimation procedure. Synthetic data, representing the random vibrations of systems with hysteresis, validate the estimated system parameters by the presented identification method at low and high-levels of excitation amplitudes.

Comparison of System Identification Techniques for the Hydraulic Manipulator Test Bed (HMTB)

NASA Technical Reports Server (NTRS)

Morris, A. Terry

1996-01-01

In this thesis linear, dynamic, multivariable state-space models for three joints of the ground-based Hydraulic Manipulator Test Bed (HMTB) are identified. HMTB, housed at the NASA Langley Research Center, is a ground-based version of the Dexterous Orbital Servicing System (DOSS), a representative space station manipulator. The dynamic models of the HMTB manipulator will first be estimated by applying nonparametric identification methods to determine each joint's response characteristics using various input excitations. These excitations include sum of sinusoids, pseudorandom binary sequences (PRBS), bipolar ramping pulses, and chirp input signals. Next, two different parametric system identification techniques will be applied to identify the best dynamical description of the joints. The manipulator is localized about a representative space station orbital replacement unit (ORU) task allowing the use of linear system identification methods. Comparisons, observations, and results of both parametric system identification techniques are discussed. The thesis concludes by proposing a model reference control system to aid in astronaut ground tests. This approach would allow the identified models to mimic on-orbit dynamic characteristics of the actual flight manipulator thus providing astronauts with realistic on-orbit responses to perform space station tasks in a ground-based environment.

Application of RNAMlet to surface defect identification of steels

NASA Astrophysics Data System (ADS)

Xu, Ke; Xu, Yang; Zhou, Peng; Wang, Lei

2018-06-01

As three main production lines of steels, continuous casting slabs, hot rolled steel plates and cold rolled steel strips have different surface appearances and are produced at different speeds of their production lines. Therefore, the algorithms for the surface defect identifications of the three steel products have different requirements for real-time and anti-interference. The existing algorithms cannot be adaptively applied to surface defect identification of the three steel products. A new method of adaptive multi-scale geometric analysis named RNAMlet was proposed. The idea of RNAMlet came from the non-symmetry anti-packing pattern representation model (NAM). The image is decomposed into a set of rectangular blocks asymmetrically according to gray value changes of image pixels. Then two-dimensional Haar wavelet transform is applied to all blocks. If the image background is complex, the number of blocks is large, and more details of the image are utilized. If the image background is simple, the number of blocks is small, and less computation time is needed. RNAMlet was tested with image samples of the three steel products, and compared with three classical methods of multi-scale geometric analysis, including Contourlet, Shearlet and Tetrolet. For the image samples with complicated backgrounds, such as continuous casting slabs and hot rolled steel plates, the defect identification rate obtained by RNAMlet was 1% higher than other three methods. For the image samples with simple backgrounds, such as cold rolled steel strips, the computation time of RNAMlet was one-tenth of the other three MGA methods, while the defect identification rates obtained by RNAMlet were higher than the other three methods.

A photometric high-throughput method for identification of electrochemically active bacteria using a WO3 nanocluster probe.

PubMed

Yuan, Shi-Jie; He, Hui; Sheng, Guo-Ping; Chen, Jie-Jie; Tong, Zhong-Hua; Cheng, Yuan-Yuan; Li, Wen-Wei; Lin, Zhi-Qi; Zhang, Feng; Yu, Han-Qing

2013-01-01

Electrochemically active bacteria (EAB) are ubiquitous in environment and have important application in the fields of biogeochemistry, environment, microbiology and bioenergy. However, rapid and sensitive methods for EAB identification and evaluation of their extracellular electron transfer ability are still lacking. Herein we report a novel photometric method for visual detection of EAB by using an electrochromic material, WO(3) nanoclusters, as the probe. This method allowed a rapid identification of EAB within 5 min and a quantitative evaluation of their extracellular electron transfer abilities. In addition, it was also successfully applied for isolation of EAB from environmental samples. Attributed to its rapidness, high reliability, easy operation and low cost, this method has high potential for practical implementation of EAB detection and investigations.

Real-Time Parameter Estimation Method Applied to a MIMO Process and its Comparison with an Offline Identification Method

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

Kaplanoglu, Erkan; Safak, Koray K.; Varol, H. Selcuk

2009-01-12

An experiment based method is proposed for parameter estimation of a class of linear multivariable systems. The method was applied to a pressure-level control process. Experimental time domain input/output data was utilized in a gray-box modeling approach. Prior knowledge of the form of the system transfer function matrix elements is assumed to be known. Continuous-time system transfer function matrix parameters were estimated in real-time by the least-squares method. Simulation results of experimentally determined system transfer function matrix compare very well with the experimental results. For comparison and as an alternative to the proposed real-time estimation method, we also implemented anmore » offline identification method using artificial neural networks and obtained fairly good results. The proposed methods can be implemented conveniently on a desktop PC equipped with a data acquisition board for parameter estimation of moderately complex linear multivariable systems.« less

Real-Time Gas Identification by Analyzing the Transient Response of Capillary-Attached Conductive Gas Sensor

PubMed Central

Bahraminejad, Behzad; Basri, Shahnor; Isa, Maryam; Hambli, Zarida

2010-01-01

In this study, the ability of the Capillary-attached conductive gas sensor (CGS) in real-time gas identification was investigated. The structure of the prototype fabricated CGS is presented. Portions were selected from the beginning of the CGS transient response including the first 11 samples to the first 100 samples. Different feature extraction and classification methods were applied on the selected portions. Validation of methods was evaluated to study the ability of an early portion of the CGS transient response in target gas (TG) identification. Experimental results proved that applying extracted features from an early part of the CGS transient response along with a classifier can distinguish short-chain alcohols from each other perfectly. Decreasing time of exposition in the interaction between target gas and sensing element improved the reliability of the sensor. Classification rate was also improved and time of identification was decreased. Moreover, the results indicated the optimum interval of the early transient response of the CGS for selecting portions to achieve the best classification rates. PMID:22219666

Rapid method for sampling metals for materials identification

NASA Technical Reports Server (NTRS)

Higgins, L. E.

1971-01-01

Nondamaging process similar to electrochemical machining is useful in obtaining metal samples from places inaccessible to conventional sampling methods or where methods would be hazardous or contaminating to specimens. Process applies to industries where metals or metal alloys play a vital role.

OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes

PubMed Central

Li, Li; Stoeckert, Christian J.; Roos, David S.

2003-01-01

The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of “recent” paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome. PMID:12952885

Damage Identification of Piles Based on Vibration Characteristics

PubMed Central

Zhang, Xiaozhong; Yao, Wenjuan; Chen, Bo; Liu, Dewen

2014-01-01

A method of damage identification of piles was established by using vibration characteristics. The approach focused on the application of the element strain energy and sensitive modals. A damage identification equation of piles was deduced using the structural vibration equation. The equation contained three major factors: change rate of element modal strain energy, damage factor of pile, and sensitivity factor of modal damage. The sensitive modals of damage identification were selected by using sensitivity factor of modal damage firstly. Subsequently, the indexes for early-warning of pile damage were established by applying the change rate of strain energy. Then the technology of computational analysis of wavelet transform was used to damage identification for pile. The identification of small damage of pile was completely achieved, including the location of damage and the extent of damage. In the process of identifying the extent of damage of pile, the equation of damage identification was used in many times. Finally, a stadium project was used as an example to demonstrate the effectiveness of the proposed method of damage identification for piles. The correctness and practicability of the proposed method were verified by comparing the results of damage identification with that of low strain test. The research provided a new way for damage identification of piles. PMID:25506062

Identification of bacteria isolated from veterinary clinical specimens using MALDI-TOF MS.

PubMed

Pavlovic, Melanie; Wudy, Corinna; Zeller-Peronnet, Veronique; Maggipinto, Marzena; Zimmermann, Pia; Straubinger, Alix; Iwobi, Azuka; Märtlbauer, Erwin; Busch, Ulrich; Huber, Ingrid

2015-01-01

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has recently emerged as a rapid and accurate identification method for bacterial species. Although it has been successfully applied for the identification of human pathogens, it has so far not been well evaluated for routine identification of veterinary bacterial isolates. This study was performed to compare and evaluate the performance of MALDI-TOF MS based identification of veterinary bacterial isolates with commercially available conventional test systems. Discrepancies of both methods were resolved by sequencing 16S rDNA and, if necessary, the infB gene for Actinobacillus isolates. A total of 375 consecutively isolated veterinary samples were collected. Among the 357 isolates (95.2%) correctly identified at the genus level by MALDI-TOF MS, 338 of them (90.1% of the total isolates) were also correctly identified at the species level. Conventional methods offered correct species identification for 319 isolates (85.1%). MALDI-TOF identification therefore offered more accurate identification of veterinary bacterial isolates. An update of the in-house mass spectra database with additional reference spectra clearly improved the identification results. In conclusion, the presented data suggest that MALDI-TOF MS is an appropriate platform for classification and identification of veterinary bacterial isolates.

Identification Approach to Alleviate Effects of Unmeasured Heat Gains for MIMO Building Thermal Systems

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

Cai, Jie; Kim, Donghun; Braun, James E.

It is important to have practical methods for constructing a good mathematical model for a building's thermal system for energy audits, retrofit analysis and advanced building controls, e.g. model predictive control. Identification approaches based on semi-physical model structures are popular in building science for those purposes. However conventional gray box identification approaches applied to thermal networks would fail when significant unmeasured heat gains present in estimation data. Although this situation is very common and practical, there has been little research to tackle this issue in building science. This paper presents an overall identification approach to alleviate influences of unmeasured disturbances,more » and hence to obtain improved gray-box building models. The approach was applied to an existing open space building and the performance is demonstrated.« less

Modal parameter identification using the log decrement method and band-pass filters

NASA Astrophysics Data System (ADS)

Liao, Yabin; Wells, Valana

2011-10-01

This paper presents a time-domain technique for identifying modal parameters of test specimens based on the log-decrement method. For lightly damped multidegree-of-freedom or continuous systems, the conventional method is usually restricted to identification of fundamental-mode parameters only. Implementation of band-pass filters makes it possible for the proposed technique to extract modal information of higher modes. The method has been applied to a polymethyl methacrylate (PMMA) beam for complex modulus identification in the frequency range 10-1100 Hz. Results compare well with those obtained using the Least Squares method, and with those previously published in literature. Then the accuracy of the proposed method has been further verified by experiments performed on a QuietSteel specimen with very low damping. The method is simple and fast. It can be used for a quick estimation of the modal parameters, or as a complementary approach for validation purposes.

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method

PubMed Central

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters – TCCF, Tθ, Tx and Ty are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images. PMID:26601045

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method.

PubMed

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters - T CCF, T θ, T x and T y are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images.

Comparative analysis of storage conditions and homogenization methods for tick and flea species for identification by MALDI-TOF MS.

PubMed

Nebbak, A; El Hamzaoui, B; Berenger, J-M; Bitam, I; Raoult, D; Almeras, L; Parola, P

2017-12-01

Ticks and fleas are vectors for numerous human and animal pathogens. Controlling them, which is important in combating such diseases, requires accurate identification, to distinguish between vector and non-vector species. Recently, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) was applied to the rapid identification of arthropods. The growth of this promising tool, however, requires guidelines to be established. To this end, standardization protocols were applied to species of Rhipicephalus sanguineus (Ixodida: Ixodidae) Latreille and Ctenocephalides felis felis (Siphonaptera: Pulicidae) Bouché, including the automation of sample homogenization using two homogenizer devices, and varied sample preservation modes for a period of 1-6 months. The MS spectra were then compared with those obtained from manual pestle grinding, the standard homogenization method. Both automated methods generated intense, reproducible MS spectra from fresh specimens. Frozen storage methods appeared to represent the best preservation mode, for up to 6 months, while storage in ethanol is also possible, with some caveats for tick specimens. Carnoy's buffer, however, was shown to be less compatible with MS analysis for the purpose of identifying ticks or fleas. These standard protocols for MALDI-TOF MS arthropod identification should be complemented by additional MS spectrum quality controls, to generalize their use in monitoring arthropods of medical interest. © 2017 The Royal Entomological Society.

Adaptive Modal Identification for Flutter Suppression Control

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Drew, Michael; Swei, Sean S.

2016-01-01

In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.

Initialization of a fractional order identification algorithm applied for Lithium-ion battery modeling in time domain

NASA Astrophysics Data System (ADS)

Nasser Eddine, Achraf; Huard, Benoît; Gabano, Jean-Denis; Poinot, Thierry

2018-06-01

This paper deals with the initialization of a non linear identification algorithm used to accurately estimate the physical parameters of Lithium-ion battery. A Randles electric equivalent circuit is used to describe the internal impedance of the battery. The diffusion phenomenon related to this modeling is presented using a fractional order method. The battery model is thus reformulated into a transfer function which can be identified through Levenberg-Marquardt algorithm to ensure the algorithm's convergence to the physical parameters. An initialization method is proposed in this paper by taking into account previously acquired information about the static and dynamic system behavior. The method is validated using noisy voltage response, while precision of the final identification results is evaluated using Monte-Carlo method.

Development of a Test Facility for Air Revitalization Technology Evaluation

NASA Technical Reports Server (NTRS)

Lu, Sao-Dung; Lin, Amy; Campbell, Melissa; Smith, Frederick

2006-01-01

An active fault tolerant control (FTC) law is generally sensitive to false identification since the control gain is reconfigured for fault occurrence. In the conventional FTC law design procedure, dynamic variations due to false identification are not considered. In this paper, an FTC synthesis method is developed in order to consider possible variations of closed-loop dynamics under false identification into the control design procedure. An active FTC synthesis problem is formulated into an LMI optimization problem to minimize the upper bound of the induced-L2 norm which can represent the worst-case performance degradation due to false identification. The developed synthesis method is applied for control of the longitudinal motions of FASER (Free-flying Airplane for Subscale Experimental Research). The designed FTC law of the airplane is simulated for pitch angle command tracking under a false identification case.

A Support Vector Machine-Based Gender Identification Using Speech Signal

NASA Astrophysics Data System (ADS)

Lee, Kye-Hwan; Kang, Sang-Ick; Kim, Deok-Hwan; Chang, Joon-Hyuk

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

A simplified fractional order impedance model and parameter identification method for lithium-ion batteries

PubMed Central

Yang, Qingxia; Xu, Jun; Cao, Binggang; Li, Xiuqing

2017-01-01

Identification of internal parameters of lithium-ion batteries is a useful tool to evaluate battery performance, and requires an effective model and algorithm. Based on the least square genetic algorithm, a simplified fractional order impedance model for lithium-ion batteries and the corresponding parameter identification method were developed. The simplified model was derived from the analysis of the electrochemical impedance spectroscopy data and the transient response of lithium-ion batteries with different states of charge. In order to identify the parameters of the model, an equivalent tracking system was established, and the method of least square genetic algorithm was applied using the time-domain test data. Experiments and computer simulations were carried out to verify the effectiveness and accuracy of the proposed model and parameter identification method. Compared with a second-order resistance-capacitance (2-RC) model and recursive least squares method, small tracing voltage fluctuations were observed. The maximum battery voltage tracing error for the proposed model and parameter identification method is within 0.5%; this demonstrates the good performance of the model and the efficiency of the least square genetic algorithm to estimate the internal parameters of lithium-ion batteries. PMID:28212405

Identification and assessment of hazardous compounds in drinking water.

PubMed

Fawell, J K; Fielding, M

1985-12-01

The identification of organic chemicals in drinking water and their assessment in terms of potential hazardous effects are two very different but closely associated tasks. In relation to both continuous low-level background contamination and specific, often high-level, contamination due to pollution incidents, the identification of contaminants is a pre-requisite to evaluation of significant hazards. Even in the case of the rapidly developing short-term bio-assays which are applied to water to indicate a potential genotoxic hazard (for example Ames tests), identification of the active chemicals is becoming a major factor in the further assessment of the response. Techniques for the identification of low concentrations of organic chemicals in drinking water have developed remarkably since the early 1970s and methods based upon gas chromatography-mass spectrometry (GC-MS) have revolutionised qualitative analysis of water. Such techniques are limited to "volatile" chemicals and these usually constitute a small fraction of the total organic material in water. However, in recent years there have been promising developments in techniques for "non-volatile" chemicals in water. Such techniques include combined high-performance liquid chromatography-mass spectrometry (HPLC-MS) and a variety of MS methods, involving, for example, field desorption, fast atom bombardment and thermospray ionisation techniques. In the paper identification techniques in general are reviewed and likely future developments outlined. The assessment of hazards associated with chemicals identified in drinking and related waters usually centres upon toxicology - an applied science which involves numerous disciplines. The paper examines the toxicological information needed, the quality and deployment of such information and discusses future research needs. Application of short-term bio-assays to drinking water is a developing area and one which is closely involved with, and to some extent dependent on, powerful methods of identification. Recent developments are discussed.

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

PubMed

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

2014-01-01

A new peak detection method has been developed for rapid selection of peptide and its fragment ion peaks for protein identification using tandem mass spectrometry. The algorithm applies classification of peak intensities present in the defined mass range to determine the noise level. A threshold is then given to select ion peaks according to the determined noise level in each mass range. This algorithm was initially designed for the peak detection of low resolution peptide mass spectra, such as matrix-assisted laser desorption/ionization Time-of-Flight (MALDI-TOF) mass spectra. But it can also be applied to other type of mass spectra. This method has demonstrated obtaining a good rate of number of real ions to noises for even poorly fragmented peptide spectra. The effect of using peak lists generated from this method produces improved protein scores in database search results. The reliability of the protein identifications is increased by finding more peptide identifications. This software tool is freely available at the Mass++ home page (http://www.first-ms3d.jp/english/achievement/software/).

Peptide Peak Detection for Low Resolution MALDI-TOF Mass Spectrometry

PubMed Central

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

2014-01-01

A new peak detection method has been developed for rapid selection of peptide and its fragment ion peaks for protein identification using tandem mass spectrometry. The algorithm applies classification of peak intensities present in the defined mass range to determine the noise level. A threshold is then given to select ion peaks according to the determined noise level in each mass range. This algorithm was initially designed for the peak detection of low resolution peptide mass spectra, such as matrix-assisted laser desorption/ionization Time-of-Flight (MALDI-TOF) mass spectra. But it can also be applied to other type of mass spectra. This method has demonstrated obtaining a good rate of number of real ions to noises for even poorly fragmented peptide spectra. The effect of using peak lists generated from this method produces improved protein scores in database search results. The reliability of the protein identifications is increased by finding more peptide identifications. This software tool is freely available at the Mass++ home page (http://www.first-ms3d.jp/english/achievement/software/). PMID:26819872

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

NASA Astrophysics Data System (ADS)

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

2010-03-01

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

Applications of system identification methods to the prediction of helicopter stability, control and handling characteristics

NASA Technical Reports Server (NTRS)

Padfield, G. D.; Duval, R. K.

1982-01-01

A set of results on rotorcraft system identification is described. Flight measurements collected on an experimental Puma helicopter are reviewed and some notable characteristics highlighted. Following a brief review of previous work in rotorcraft system identification, the results of state estimation and model structure estimation processes applied to the Puma data are presented. The results, which were obtained using NASA developed software, are compared with theoretical predictions of roll, yaw and pitching moment derivatives for a 6 degree of freedom model structure. Anomalies are reported. The theoretical methods used are described. A framework for reduced order modelling is outlined.

Vitamin K

USDA-ARS?s Scientific Manuscript database

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

Identification of Load Categories in Rotor System Based on Vibration Analysis

PubMed Central

Yang, Zhaojian

2017-01-01

Rotating machinery is often subjected to variable loads during operation. Thus, monitoring and identifying different load types is important. Here, five typical load types have been qualitatively studied for a rotor system. A novel load category identification method for rotor system based on vibration signals is proposed. This method is a combination of ensemble empirical mode decomposition (EEMD), energy feature extraction, and back propagation (BP) neural network. A dedicated load identification test bench for rotor system was developed. According to loads characteristics and test conditions, an experimental plan was formulated, and loading tests for five loads were conducted. Corresponding vibration signals of the rotor system were collected for each load condition via eddy current displacement sensor. Signals were reconstructed using EEMD, and then features were extracted followed by energy calculations. Finally, characteristics were input to the BP neural network, to identify different load types. Comparison and analysis of identifying data and test data revealed a general identification rate of 94.54%, achieving high identification accuracy and good robustness. This shows that the proposed method is feasible. Due to reliable and experimentally validated theoretical results, this method can be applied to load identification and fault diagnosis for rotor equipment used in engineering applications. PMID:28726754

Detection and identification of substances using noisy THz signal

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Zakharova, Irina G.; Zagursky, Dmitry Yu.; Varentsova, Svetlana A.

2017-05-01

We discuss an effective method for the detection and identification of substances using a high noisy THz signal. In order to model such a noisy signal, we add to the THz signal transmitted through a pure substance, a noisy THz signal obtained in real conditions at a long distance (more than 3.5 m) from the receiver in air. The insufficiency of the standard THz-TDS method is demonstrated. The method discussed in the paper is based on time-dependent integral correlation criteria calculated using spectral dynamics of medium response. A new type of the integral correlation criterion, which is less dependent on spectral characteristics of the noisy signal under investigation, is used for the substance identification. To demonstrate the possibilities of the integral correlation criteria in real experiment, they are applied for the identification of explosive HMX in the reflection mode. To explain the physical mechanism for the false absorption frequencies appearance in the signal we make a computer simulation using 1D Maxwell's equations and density matrix formalism. We propose also new method for the substance identification by using the THz pulse frequency up-conversion and discuss an application of the cascade mechanism of molecules high energy levels excitation for the substance identification.

Parametric output-only identification of time-varying structures using a kernel recursive extended least squares TARMA approach

NASA Astrophysics Data System (ADS)

Ma, Zhi-Sai; Liu, Li; Zhou, Si-Da; Yu, Lei; Naets, Frank; Heylen, Ward; Desmet, Wim

2018-01-01

The problem of parametric output-only identification of time-varying structures in a recursive manner is considered. A kernelized time-dependent autoregressive moving average (TARMA) model is proposed by expanding the time-varying model parameters onto the basis set of kernel functions in a reproducing kernel Hilbert space. An exponentially weighted kernel recursive extended least squares TARMA identification scheme is proposed, and a sliding-window technique is subsequently applied to fix the computational complexity for each consecutive update, allowing the method to operate online in time-varying environments. The proposed sliding-window exponentially weighted kernel recursive extended least squares TARMA method is employed for the identification of a laboratory time-varying structure consisting of a simply supported beam and a moving mass sliding on it. The proposed method is comparatively assessed against an existing recursive pseudo-linear regression TARMA method via Monte Carlo experiments and shown to be capable of accurately tracking the time-varying dynamics. Furthermore, the comparisons demonstrate the superior achievable accuracy, lower computational complexity and enhanced online identification capability of the proposed kernel recursive extended least squares TARMA approach.

A biochemical protocol for the isolation and identification of current species of Vibrio in seafood.

PubMed

Ottaviani, D; Masini, L; Bacchiocchi, S

2003-01-01

We report a biochemical method for the isolation and identification of the current species of vibrios using just one operative protocol. The method involves an enrichment phase with incubation at 30 degrees C for 8-24 h in alkaline peptone water and an isolation phase on thiosulphate-citrate-salt sucrose agar plates incubating at 30 degrees C for 24 h. Four biochemical tests and Alsina's scheme were performed for genus and species identification, respectively. All biochemical tests were optimized as regards conditions of temperature, time of incubation and media composition. The whole standardized protocol was always able to give a correct identification when applied to 25 reference strains of Vibrio and 134 field isolates. The data demonstrated that the assay method allows an efficient recovery, isolation and identification of current species of Vibrio in seafood obtaining results within 2-7 days. This method based on biochemical tests could be applicable even in basic microbiology laboratories, and can be used simultaneously to isolate and discriminate all clinically relevant species of Vibrio.

Outlier identification in urban soils and its implications for identification of potential contaminated land

NASA Astrophysics Data System (ADS)

Zhang, Chaosheng

2010-05-01

Outliers in urban soil geochemical databases may imply potential contaminated land. Different methodologies which can be easily implemented for the identification of global and spatial outliers were applied for Pb concentrations in urban soils of Galway City in Ireland. Due to its strongly skewed probability feature, a Box-Cox transformation was performed prior to further analyses. The graphic methods of histogram and box-and-whisker plot were effective in identification of global outliers at the original scale of the dataset. Spatial outliers could be identified by a local indicator of spatial association of local Moran's I, cross-validation of kriging, and a geographically weighted regression. The spatial locations of outliers were visualised using a geographical information system. Different methods showed generally consistent results, but differences existed. It is suggested that outliers identified by statistical methods should be confirmed and justified using scientific knowledge before they are properly dealt with.

Development of Amplified 16S Ribosomal DNA Restriction Analysis for Identification of Actinomyces Species and Comparison with Pyrolysis-Mass Spectrometry and Conventional Biochemical Tests

PubMed Central

Hall, Val; O’Neill, G. L.; Magee, J. T.; Duerden, B. I.

1999-01-01

Identification of Actinomyces spp. by conventional phenotypic methods is notoriously difficult and unreliable. Recently, the application of chemotaxonomic and molecular methods has clarified the taxonomy of the group and has led to the recognition of several new species. A practical and discriminatory identification method is now needed for routine identification of clinical isolates. Amplified 16S ribosomal DNA restriction analysis (ARDRA) was applied to reference strains (n = 27) and clinical isolates (n = 36) of Actinomyces spp. and other gram-positive rods. Clinical strains were identified initially to the species level by conventional biochemical tests. However, given the low degree of confidence in conventional methods, the findings obtained by ARDRA were also compared with those obtained by pyrolysis-mass spectrometry. The ARDRA profiles generated by the combination of HaeIII and HpaII endonuclease digestion differentiated all reference strains to the species or subspecies level. The profiles correlated well with the findings obtained by pyrolysis-mass spectrometry and by conventional tests and enabled the identification of 31 of 36 clinical isolates to the species level. ARDRA was shown to be a simple, rapid, cost-effective, and highly discriminatory method for routine identification of Actinomyces spp. of clinical origin. PMID:10364594

IFPTarget: A Customized Virtual Target Identification Method Based on Protein-Ligand Interaction Fingerprinting Analyses.

PubMed

Li, Guo-Bo; Yu, Zhu-Jun; Liu, Sha; Huang, Lu-Yi; Yang, Ling-Ling; Lohans, Christopher T; Yang, Sheng-Yong

2017-07-24

Small-molecule target identification is an important and challenging task for chemical biology and drug discovery. Structure-based virtual target identification has been widely used, which infers and prioritizes potential protein targets for the molecule of interest (MOI) principally via a scoring function. However, current "universal" scoring functions may not always accurately identify targets to which the MOI binds from the retrieved target database, in part due to a lack of consideration of the important binding features for an individual target. Here, we present IFPTarget, a customized virtual target identification method, which uses an interaction fingerprinting (IFP) method for target-specific interaction analyses and a comprehensive index (Cvalue) for target ranking. Evaluation results indicate that the IFP method enables substantially improved binding pose prediction, and Cvalue has an excellent performance in target ranking for the test set. When applied to screen against our established target library that contains 11,863 protein structures covering 2842 unique targets, IFPTarget could retrieve known targets within the top-ranked list and identified new potential targets for chemically diverse drugs. IFPTarget prediction led to the identification of the metallo-β-lactamase VIM-2 as a target for quercetin as validated by enzymatic inhibition assays. This study provides a new in silico target identification tool and will aid future efforts to develop new target-customized methods for target identification.

Robust identification of transcriptional regulatory networks using a Gibbs sampler on outlier sum statistic.

PubMed

Gu, Jinghua; Xuan, Jianhua; Riggins, Rebecca B; Chen, Li; Wang, Yue; Clarke, Robert

2012-08-01

Identification of transcriptional regulatory networks (TRNs) is of significant importance in computational biology for cancer research, providing a critical building block to unravel disease pathways. However, existing methods for TRN identification suffer from the inclusion of excessive 'noise' in microarray data and false-positives in binding data, especially when applied to human tumor-derived cell line studies. More robust methods that can counteract the imperfection of data sources are therefore needed for reliable identification of TRNs in this context. In this article, we propose to establish a link between the quality of one target gene to represent its regulator and the uncertainty of its expression to represent other target genes. Specifically, an outlier sum statistic was used to measure the aggregated evidence for regulation events between target genes and their corresponding transcription factors. A Gibbs sampling method was then developed to estimate the marginal distribution of the outlier sum statistic, hence, to uncover underlying regulatory relationships. To evaluate the effectiveness of our proposed method, we compared its performance with that of an existing sampling-based method using both simulation data and yeast cell cycle data. The experimental results show that our method consistently outperforms the competing method in different settings of signal-to-noise ratio and network topology, indicating its robustness for biological applications. Finally, we applied our method to breast cancer cell line data and demonstrated its ability to extract biologically meaningful regulatory modules related to estrogen signaling and action in breast cancer. The Gibbs sampler MATLAB package is freely available at http://www.cbil.ece.vt.edu/software.htm. xuan@vt.edu Supplementary data are available at Bioinformatics online.

Robust identification of transcriptional regulatory networks using a Gibbs sampler on outlier sum statistic

PubMed Central

Gu, Jinghua; Xuan, Jianhua; Riggins, Rebecca B.; Chen, Li; Wang, Yue; Clarke, Robert

2012-01-01

Motivation: Identification of transcriptional regulatory networks (TRNs) is of significant importance in computational biology for cancer research, providing a critical building block to unravel disease pathways. However, existing methods for TRN identification suffer from the inclusion of excessive ‘noise’ in microarray data and false-positives in binding data, especially when applied to human tumor-derived cell line studies. More robust methods that can counteract the imperfection of data sources are therefore needed for reliable identification of TRNs in this context. Results: In this article, we propose to establish a link between the quality of one target gene to represent its regulator and the uncertainty of its expression to represent other target genes. Specifically, an outlier sum statistic was used to measure the aggregated evidence for regulation events between target genes and their corresponding transcription factors. A Gibbs sampling method was then developed to estimate the marginal distribution of the outlier sum statistic, hence, to uncover underlying regulatory relationships. To evaluate the effectiveness of our proposed method, we compared its performance with that of an existing sampling-based method using both simulation data and yeast cell cycle data. The experimental results show that our method consistently outperforms the competing method in different settings of signal-to-noise ratio and network topology, indicating its robustness for biological applications. Finally, we applied our method to breast cancer cell line data and demonstrated its ability to extract biologically meaningful regulatory modules related to estrogen signaling and action in breast cancer. Availability and implementation: The Gibbs sampler MATLAB package is freely available at http://www.cbil.ece.vt.edu/software.htm. Contact: xuan@vt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22595208

[Application of immunologic methods to the analysis of bio-leaching bacteria].

PubMed

Coto, O; Fernández, A I; León, T; Rodríguez, D

1994-09-01

Pure cultures of Thiobacillus ferrooxidans and mixed cultures of Thiobacillus ferrooxidans and Leptospirillum ferrooxidans isolated from the Matahambre mine (Cuba) were used to fit immunodiffusion and immunoelectron microscopy to the study of iron oxidizing bacteria. The possibilities, advantages and limits of those techniques have been studied from both the identification and the serological characterization points of view. Finally, the efficiency of these methods was tested by applying them to the identification of microorganisms from acidic waters from the mine.

Identification of active sources inside cavities using the equivalent source method-based free-field recovery technique

NASA Astrophysics Data System (ADS)

Bi, Chuan-Xing; Hu, Ding-Yu; Zhang, Yong-Bin; Jing, Wen-Qian

2015-06-01

In previous studies, an equivalent source method (ESM)-based technique for recovering the free sound field in a noisy environment has been successfully applied to exterior problems. In order to evaluate its performance when applied to a more general noisy environment, that technique is used to identify active sources inside cavities where the sound field is composed of the field radiated by active sources and that reflected by walls. A patch approach with two semi-closed surfaces covering the target active sources is presented to perform the measurements, and the field that would be radiated by these target active sources into free space is extracted from the mixed field by using the proposed technique, which will be further used as the input of nearfield acoustic holography for source identification. Simulation and experimental results validate the effectiveness of the proposed technique for source identification in cavities, and show the feasibility of performing the measurements with a double layer planar array.

Applying Comprehensive Environmental Assessment to Research Planning for Multiwalled Carbon Nanotubes: Refinements to Inform Future Stakeholder Engagement

EPA Science Inventory

We previously described our collective judgment methods to engage expert stakeholders in the Comprehensive Environmental Assessment (CEA) workshop process applied to nano-TiO2 and nano-Ag research planning. We identified several lessons learned in engaging stakeholders to identif...

Development of a rapid and simplified protocol for direct bacterial identification from positive blood cultures by using matrix assisted laser desorption ionization time-of- flight mass spectrometry.

PubMed

Jakovljev, Aleksandra; Bergh, Kåre

2015-11-06

Bloodstream infections represent serious conditions carrying a high mortality and morbidity rate. Rapid identification of microorganisms and prompt institution of adequate antimicrobial therapy is of utmost importance for a successful outcome. Aiming at the development of a rapid, simplified and efficient protocol, we developed and compared two in-house preparatory methods for the direct identification of bacteria from positive blood culture flasks (BD BACTEC FX system) by using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI TOF MS). Both methods employed saponin and distilled water for erythrocyte lysis. In method A the cellular pellet was overlaid with formic acid on the MALDI TOF target plate for protein extraction, whereas in method B the pellet was exposed to formic acid followed by acetonitrile prior to placing on the target plate. Best results were obtained by method A. Direct identification was achieved for 81.9 % and 65.8 % (50.3 % and 26.2 % with scores >2.0) of organisms by method A and method B, respectively. Overall concordance with final identification was 100 % to genus and 97.9 % to species level. By applying a lower cut-off score value, the levels of identification obtained by method A and method B increased to 89.3 % and 77.8 % of organisms (81.9 % and 65.8 % identified with scores >1.7), respectively. Using the lowered score criteria, concordance with final results was obtained for 99.3 % of genus and 96.6 % of species identifications. The reliability of results, rapid performance (approximately 25 min) and applicability of in-house method A have contributed to implementation of this robust and cost-effective method in our laboratory.

Commissioning Cornell OSTs for SRF cavity testing at Jlab

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

Eremeev, Grigory

2011-07-01

Understanding the current quench limitations in SRF cavities is a topic essential for any SRF accelerator that requires high fields. This understanding crucially depends on correct and precise quench identification. Second sound quench detection in superfluid liquid helium with oscillating superleak transducers is a technique recently applied at Cornell University as a fast and versatile method for quench identification in SRF cavities. Having adopted Cornell design, we report in this contribution on our experience with OST for quench identification in different cavities at JLab.

[Identification of Dens Draconis and Os Draconis by XRD method].

PubMed

Chen, Guang-Yun; Wu, Qi-Nan; Shen, Bei; Chen, Rong

2012-04-01

To establish an XRD method for evaluating the quality of Os Draconis and Dens Draconis and applying in judgement of the counterfeit. Dens Draconis, Os Draconis and the counterfeit of Os Draconis were analyzed by XRD. Their diffraction patterns were clustered analysis and evaluated their similarity degree. Established the analytical method of Dens Draconis and Os Draconis basing the features fingerprint information of the 10 common peaks by XRD pattern. Obtained the XRD pattern of the counterfeit of Os Draconis. The similarity degree of separate sources of Dens Draconis was high,while the similarity degree of separate sources of Os Draconis was significant different from each other. This method can be used for identification and evaluation of Os Draconis and Dens Draconis. It also can be used for identification the counterfeit of Os Draconis effectively.

The Use of ATR-FTIR in Conjunction with Thermal Analysis Methods for Efficient Identification of Polymer Samples: A Qualitative Multiinstrument Instrumental Analysis Laboratory Experiment

ERIC Educational Resources Information Center

Dickson-Karn, Nicole M.

2017-01-01

A multi-instrument approach has been applied to the efficient identification of polymers in an upper-division undergraduate instrumental analysis laboratory course. Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) is used in conjunction with differential scanning calorimetry (DSC) to identify 18 polymer samples and…

Utility of Computational Methods to Identify the Apoptosis Machinery in Unicellular Eukaryotes

PubMed Central

Durand, Pierre Marcel; Coetzer, Theresa Louise

2008-01-01

Apoptosis is the phenotypic result of an active, regulated process of self-destruction. Following various cellular insults, apoptosis has been demonstrated in numerous unicellular eukaryotes, but very little is known about the genes and proteins that initiate and execute this process in this group of organisms. A bioinformatic approach presents an array of powerful methods to direct investigators in the identification of the apoptosis machinery in protozoans. In this review, we discuss some of the available computational methods and illustrate how they may be applied using the identification of a Plasmodium falciparum metacaspase gene as an example. PMID:19812769

The anisotropic Hooke's law for cancellous bone and wood.

PubMed

Yang, G; Kabel, J; van Rietbergen, B; Odgaard, A; Huiskes, R; Cowin, S C

A method of data analysis for a set of elastic constant measurements is applied to data bases for wood and cancellous bone. For these materials the identification of the type of elastic symmetry is complicated by the variable composition of the material. The data analysis method permits the identification of the type of elastic symmetry to be accomplished independent of the examination of the variable composition. This method of analysis may be applied to any set of elastic constant measurements, but is illustrated here by application to hardwoods and softwoods, and to an extraordinary data base of cancellous bone elastic constants. The solid volume fraction or bulk density is the compositional variable for the elastic constants of these natural materials. The final results are the solid volume fraction dependent orthotropic Hooke's law for cancellous bone and a bulk density dependent one for hardwoods and softwoods.

[Evaluation of mass spectrometry: MALDI-TOF MS for fast and reliable yeast identification].

PubMed

Relloso, María S; Nievas, Jimena; Fares Taie, Santiago; Farquharson, Victoria; Mujica, María T; Romano, Vanesa; Zarate, Mariela S; Smayevsky, Jorgelina

2015-01-01

The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry technique known as MALDI-TOF MS is a tool used for the identification of clinical pathogens by generating a protein spectrum that is unique for a given species. In this study we assessed the identification of clinical yeast isolates by MALDI-TOF MS in a university hospital from Argentina and compared two procedures for protein extraction: a rapid method and a procedure based on the manufacturer's recommendations. A short protein extraction procedure was applied in 100 isolates and the rate of correct identification at genus and species level was 98.0%. In addition, we analyzed 201 isolates, previously identified by conventional methods, using the methodology recommended by the manufacturer and there was 95.38% coincidence in the identification at species level. MALDI TOF MS showed to be a fast, simple and reliable tool for yeast identification. Copyright © 2014 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

Identifying outliers of non-Gaussian groundwater state data based on ensemble estimation for long-term trends

NASA Astrophysics Data System (ADS)

Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kueyoung; Choung, Sungwook; Chung, Il Moon

2017-05-01

A hydrogeological dataset often includes substantial deviations that need to be inspected. In the present study, three outlier identification methods - the three sigma rule (3σ), inter quantile range (IQR), and median absolute deviation (MAD) - that take advantage of the ensemble regression method are proposed by considering non-Gaussian characteristics of groundwater data. For validation purposes, the performance of the methods is compared using simulated and actual groundwater data with a few hypothetical conditions. In the validations using simulated data, all of the proposed methods reasonably identify outliers at a 5% outlier level; whereas, only the IQR method performs well for identifying outliers at a 30% outlier level. When applying the methods to real groundwater data, the outlier identification performance of the IQR method is found to be superior to the other two methods. However, the IQR method shows limitation by identifying excessive false outliers, which may be overcome by its joint application with other methods (for example, the 3σ rule and MAD methods). The proposed methods can be also applied as potential tools for the detection of future anomalies by model training based on currently available data.

Probability of identification: adulteration of American Ginseng with Asian Ginseng.

PubMed

Harnly, James; Chen, Pei; Harrington, Peter De B

2013-01-01

The AOAC INTERNATIONAL guidelines for validation of botanical identification methods were applied to the detection of Asian Ginseng [Panax ginseng (PG)] as an adulterant for American Ginseng [P. quinquefolius (PQ)] using spectral fingerprints obtained by flow injection mass spectrometry (FIMS). Samples of 100% PQ and 100% PG were physically mixed to provide 90, 80, and 50% PQ. The multivariate FIMS fingerprint data were analyzed using soft independent modeling of class analogy (SIMCA) based on 100% PQ. The Q statistic, a measure of the degree of non-fit of the test samples with the calibration model, was used as the analytical parameter. FIMS was able to discriminate between 100% PQ and 100% PG, and between 100% PQ and 90, 80, and 50% PQ. The probability of identification (POI) curve was estimated based on the SD of 90% PQ. A digital model of adulteration, obtained by mathematically summing the experimentally acquired spectra of 100% PQ and 100% PG in the desired ratios, agreed well with the physical data and provided an easy and more accurate method for constructing the POI curve. Two chemometric modeling methods, SIMCA and fuzzy optimal associative memories, and two classification methods, partial least squares-discriminant analysis and fuzzy rule-building expert systems, were applied to the data. The modeling methods correctly identified the adulterated samples; the classification methods did not.

[The research and application of pretreatment method for matrix-assisted laser desorption ionization-time of flight mass spectrometry identification of filamentous fungi].

PubMed

Huang, Y F; Chang, Z; Bai, J; Zhu, M; Zhang, M X; Wang, M; Zhang, G; Li, X Y; Tong, Y G; Wang, J L; Lu, X X

2017-08-08

Objective: To establish and evaluate the feasibility of a pretreatment method for matrix-assisted laser desorption ionization-time of flight mass spectrometry identification of filamentous fungi developed by the laboratory. Methods: Three hundred and eighty strains of filamentous fungi from January 2014 to December 2016 were recovered and cultured on sabouraud dextrose agar (SDA) plate at 28 ℃ to mature state. Meanwhile, the fungi were cultured in liquid sabouraud medium with a vertical rotation method recommended by Bruker and a horizontal vibration method developed by the laboratory until adequate amount of colonies were observed. For the strains cultured with the three methods, protein was extracted with modified magnetic bead-based extraction method for mass spectrum identification. Results: For 380 fungi strains, it took 3-10 d to culture with SDA culture method, and the ratio of identification of the species and genus was 47% and 81%, respectively; it took 5-7 d to culture with vertical rotation method, and the ratio of identification of the species and genus was 76% and 94%, respectively; it took 1-2 d to culture with horizontal vibration method, and the ratio of identification of the species and genus was 96% and 99%, respectively. For the comparison between horizontal vibration method and SDA culture method comparison, the difference was statistically significant (χ(2)=39.026, P <0.01); for the comparison between horizontal vibration method and vertical rotation method recommended by Bruker, the difference was statistically significant(χ(2)=11.310, P <0.01). Conclusion: The horizontal vibration method and modified magnetic bead-based extraction method developed by the laboratory is superior to the method recommended by Bruker and SDA culture method in terms of the identification capacity for filamentous fungi, which can be applied in clinic.

System Identification and POD Method Applied to Unsteady Aerodynamics

NASA Technical Reports Server (NTRS)

Tang, Deman; Kholodar, Denis; Juang, Jer-Nan; Dowell, Earl H.

2001-01-01

The representation of unsteady aerodynamic flow fields in terms of global aerodynamic modes has proven to be a useful method for reducing the size of the aerodynamic model over those representations that use local variables at discrete grid points in the flow field. Eigenmodes and Proper Orthogonal Decomposition (POD) modes have been used for this purpose with good effect. This suggests that system identification models may also be used to represent the aerodynamic flow field. Implicit in the use of a systems identification technique is the notion that a relative small state space model can be useful in describing a dynamical system. The POD model is first used to show that indeed a reduced order model can be obtained from a much larger numerical aerodynamical model (the vortex lattice method is used for illustrative purposes) and the results from the POD and the system identification methods are then compared. For the example considered, the two methods are shown to give comparable results in terms of accuracy and reduced model size. The advantages and limitations of each approach are briefly discussed. Both appear promising and complementary in their characteristics.

Study of parameter identification using hybrid neural-genetic algorithm in electro-hydraulic servo system

NASA Astrophysics Data System (ADS)

Moon, Byung-Young

2005-12-01

The hybrid neural-genetic multi-model parameter estimation algorithm was demonstrated. This method can be applied to structured system identification of electro-hydraulic servo system. This algorithms consist of a recurrent incremental credit assignment(ICRA) neural network and a genetic algorithm. The ICRA neural network evaluates each member of a generation of model and genetic algorithm produces new generation of model. To evaluate the proposed method, electro-hydraulic servo system was designed and manufactured. The experiment was carried out to figure out the hybrid neural-genetic multi-model parameter estimation algorithm. As a result, the dynamic characteristics were obtained such as the parameters(mass, damping coefficient, bulk modulus, spring coefficient), which minimize total square error. The result of this study can be applied to hydraulic systems in industrial fields.

The application of artificial intelligence for the identification of the maceral groups and mineral components of coal

NASA Astrophysics Data System (ADS)

Mlynarczuk, Mariusz; Skiba, Marta

2017-06-01

The correct and consistent identification of the petrographic properties of coal is an important issue for researchers in the fields of mining and geology. As part of the study described in this paper, investigations concerning the application of artificial intelligence methods for the identification of the aforementioned characteristics were carried out. The methods in question were used to identify the maceral groups of coal, i.e. vitrinite, inertinite, and liptinite. Additionally, an attempt was made to identify some non-organic minerals. The analyses were performed using pattern recognition techniques (NN, kNN), as well as artificial neural network techniques (a multilayer perceptron - MLP). The classification process was carried out using microscopy images of polished sections of coals. A multidimensional feature space was defined, which made it possible to classify the discussed structures automatically, based on the methods of pattern recognition and algorithms of the artificial neural networks. Also, from the study we assessed the impact of the parameters for which the applied methods proved effective upon the final outcome of the classification procedure. The result of the analyses was a high percentage (over 97%) of correct classifications of maceral groups and mineral components. The paper discusses also an attempt to analyze particular macerals of the inertinite group. It was demonstrated that using artificial neural networks to this end makes it possible to classify the macerals properly in over 91% of cases. Thus, it was proved that artificial intelligence methods can be successfully applied for the identification of selected petrographic features of coal.

Analysis of the vortices in the inner flow of reversible pump turbine with the new omega vortex identification method

NASA Astrophysics Data System (ADS)

Zhang, Yu-ning; Liu, Kai-hua; Li, Jin-wei; Xian, Hai-zhen; Du, Xiao-ze

2018-05-01

Reversible pump turbines are widely employed in the pumped hydro energy storage power plants. The frequent shifts among various operational modes for the reversible pump turbines pose various instability problems, e.g., the strong pressure fluctuation, the shaft swing, and the impeller damage. The instability is related to the vortices generated in the channels of the reversible pump turbines in the generating mode. In the present paper, a new omega vortex identification method is applied to the vortex analysis of the reversible pump turbines. The main advantage of the adopted algorithm is that it is physically independent of the selected values for the vortex identification in different working modes. Both weak and strong vortices can be identified by setting the same omega value in the whole passage of the reversible pump turbine. Five typical modes (turbine mode, runaway mode, turbine brake mode, zero-flow-rate mode and reverse pump mode) at several typical guide vane openings are selected for the analysis and comparisons. The differences between various modes and different guide vane openings are compared both qualitatively in terms of the vortex distributions and quantitatively in terms of the areas of the vortices in the reversible pump turbines. Our findings indicate that the new omega method could be successfully applied to the vortex identification in the reversible pump turbines.

[Molecular techniques applied in species identification of Toxocara].

PubMed

Fogt, Renata

2006-01-01

Toxocarosis is still an important and actual problem in human medicine. It can manifest as visceral (VLM), ocular (OLM) or covert (CT) larva migrans syndroms. Complicated life cycle of Toxocara, lack of easy and practical methods of species differentiation of the adult nematode and embarrassing in recognition of the infection in definitive hosts create difficulties in fighting with the infection. Although studies on human toxocarosis have been continued for over 50 years there is no conclusive answer, which of species--T. canis or T. cati constitutes a greater risk of transmission of the nematode to man. Neither blood serological examinations nor microscopic observations of the morphological features of the nematode give the satisfied answer on the question. Since the 90-ths molecular methods were developed for species identification and became useful tools being widely applied in parasitological diagnosis. This paper cover the survey of methods of DNA analyses used for identification of Toxocara species. The review may be helpful for researchers focused on Toxocara and toxocarosis as well as on detection of new species. The following techniques are described: PCR (Polymerase Chain Reaction), RFLP (Restriction Fragment Length Polymorphism), RAPD (Random Amplified Polymorphic DNA) and SSCP (Single Strand Conformation Polymorphism).

Identification of Erwinia species isolated from apples and pears by differential PCR.

PubMed

Gehring, I; Geider, K

2012-04-01

Many pathogenic and epiphytic bacteria isolated from apples and pears belong to the genus Erwinia; these include the species E. amylovora, E. pyrifoliae, E. billingiae, E. persicina, E. rhapontici and E. tasmaniensis. Identification and classification of freshly isolated bacterial species often requires tedious taxonomic procedures. To facilitate routine identification of Erwinia species, we have developed a PCR method based on species-specific oligonucleotides (SSOs) from the sequences of the housekeeping genes recA and gpd. Using species-specific primers that we report here, differentiation was done with conventional PCR (cPCR) and quantitative PCR (qPCR) applying two consecutive primer annealing temperatures. The specificity of the primers depends on terminal Single Nucleotide Polymorphisms (SNPs) that are characteristic for the target species. These PCR assays enabled us to distinguish eight Erwinia species, as well as to identify new Erwinia isolates from plant surfaces. When performed with mixed bacterial cultures, they only detected a single target species. This method is a novel approach to classify strains within the genus Erwinia by PCR and it can be used to confirm other diagnostic data, especially when specific PCR detection methods are not already available. The method may be applied to classify species within other bacterial genera. Copyright © 2012 Elsevier B.V. All rights reserved.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS.

PubMed

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-01-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree. Copyright © 2015 Elsevier B.V. All rights reserved.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS

NASA Astrophysics Data System (ADS)

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-10-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree.

Low-Dimensional Feature Representation for Instrument Identification

NASA Astrophysics Data System (ADS)

Ihara, Mizuki; Maeda, Shin-Ichi; Ikeda, Kazushi; Ishii, Shin

For monophonic music instrument identification, various feature extraction and selection methods have been proposed. One of the issues toward instrument identification is that the same spectrum is not always observed even in the same instrument due to the difference of the recording condition. Therefore, it is important to find non-redundant instrument-specific features that maintain information essential for high-quality instrument identification to apply them to various instrumental music analyses. For such a dimensionality reduction method, the authors propose the utilization of linear projection methods: local Fisher discriminant analysis (LFDA) and LFDA combined with principal component analysis (PCA). After experimentally clarifying that raw power spectra are actually good for instrument classification, the authors reduced the feature dimensionality by LFDA or by PCA followed by LFDA (PCA-LFDA). The reduced features achieved reasonably high identification performance that was comparable or higher than those by the power spectra and those achieved by other existing studies. These results demonstrated that our LFDA and PCA-LFDA can successfully extract low-dimensional instrument features that maintain the characteristic information of the instruments.

Recommendations for Improving Identification and Quantification in Non-Targeted, GC-MS-Based Metabolomic Profiling of Human Plasma

PubMed Central

Wang, Hanghang; Muehlbauer, Michael J.; O’Neal, Sara K.; Newgard, Christopher B.; Hauser, Elizabeth R.; Shah, Svati H.

2017-01-01

The field of metabolomics as applied to human disease and health is rapidly expanding. In recent efforts of metabolomics research, greater emphasis has been placed on quality control and method validation. In this study, we report an experience with quality control and a practical application of method validation. Specifically, we sought to identify and modify steps in gas chromatography-mass spectrometry (GC-MS)-based, non-targeted metabolomic profiling of human plasma that could influence metabolite identification and quantification. Our experimental design included two studies: (1) a limiting-dilution study, which investigated the effects of dilution on analyte identification and quantification; and (2) a concentration-specific study, which compared the optimal plasma extract volume established in the first study with the volume used in the current institutional protocol. We confirmed that contaminants, concentration, repeatability and intermediate precision are major factors influencing metabolite identification and quantification. In addition, we established methods for improved metabolite identification and quantification, which were summarized to provide recommendations for experimental design of GC-MS-based non-targeted profiling of human plasma. PMID:28841195

[Possibility of the species identification using blood stains located on the material evidences and bone fragments with the method of solid phase enzyme immunoassay with "IgG general-EIA-BEST" kit and human immunoglobulin G].

PubMed

Sidorov, V L; Shvetsova, I V; Isakova, I V

2007-01-01

The authors give the comparative analysis of Russian and foreign forensic medical methods of species character identification of the blood from the stains on the material evidences and bone fragments. It is shown that for this purpose it is feasible to apply human immunoglobulin G (IgG) and solid phase enzyme immunoassay (EIA) with the kit "IgG general-EIA-BEST". In comparison with the methods used in Russia this method is more sensitive, convenient for objective registration and computer processing. The results of experiments shown that it is possible to use the kit "IgG general-EIA-BEST" in forensic medicine for the species character identification of the blood from the stains on the material evidences and bone fragments.

Improvement of Automated Identification of the Heart Wall in Echocardiography by Suppressing Clutter Component

NASA Astrophysics Data System (ADS)

Takahashi, Hiroki; Hasegawa, Hideyuki; Kanai, Hiroshi

2013-07-01

For the facilitation of analysis and elimination of the operator dependence in estimating the myocardial function in echocardiography, we have previously developed a method for automated identification of the heart wall. However, there are misclassified regions because the magnitude-squared coherence (MSC) function of echo signals, which is one of the features in the previous method, is sensitively affected by the clutter components such as multiple reflection and off-axis echo from external tissue or the nearby myocardium. The objective of the present study is to improve the performance of automated identification of the heart wall. For this purpose, we proposed a method to suppress the effect of the clutter components on the MSC of echo signals by applying an adaptive moving target indicator (MTI) filter to echo signals. In vivo experimental results showed that the misclassified regions were significantly reduced using our proposed method in the longitudinal axis view of the heart.

One drop chemical derivatization--DESI-MS analysis for metabolite structure identification.

PubMed

Lubin, Arnaud; Cabooter, Deirdre; Augustijns, Patrick; Cuyckens, Filip

2015-07-01

Structural elucidation of metabolites is an important part during the discovery and development process of new pharmaceutical drugs. Liquid Chromatography (LC) in combination with Mass Spectrometry (MS) is usually the technique of choice for structural identification but cannot always provide precise structural identification of the studied metabolite (e.g. site of hydroxylation and site of glucuronidation). In order to identify those metabolites, different approaches are used combined with MS data including nuclear magnetic resonance, hydrogen/deuterium exchange and chemical derivatization followed by LC-MS. Those techniques are often time-consuming and/or require extra sample pre-treatment. In this paper, a fast and easy to set up tool using desorption electrospray ionization-MS for metabolite identification is presented. In the developed method, analytes in solution are simply dried on a glass plate with printed Teflon spots and then a single drop of derivatization mixture is added. Once the spot is dried, the derivatized compound is analyzed. Six classic chemical derivatizations were adjusted to work as a one drop reaction and applied on a list of compounds with relevant functional groups. Subsequently, two successive reactions on a single spot of amoxicillin were tested and the methodology described was successfully applied on an in vitro incubated alprazolam metabolite. All reactions and analyses were performed within an hour and gave useful structural information by derivatizing functional groups, making the method a time-saving and efficient tool for metabolite identification if used in addition or in some cases as an alternative to common methods. Copyright © 2015 John Wiley & Sons, Ltd.

Identification of Species in Tripterygium (Celastraceae) Based on DNA Barcoding.

PubMed

Zhang, Xiaomei; Li, Na; Yao, Yuanyuan; Liang, Xuming; Qu, Xianyou; Liu, Xiang; Zhu, Yingjie; Yang, Dajian; Sun, Wei

2016-11-01

Species of genus Tripterygium (Celastraceae) have attracted much attention owing to their excellent effect on treating autoimmune and inflammatory diseases. However, due to high market demand causing overexploitation, natural populations of genus Tripterygium have rapidly declined. Tripterygium medicinal materials are mainly collected from the wild, making the quality of medicinal materials unstable. Additionally, identification of herbal materials from Tripterygium species and their adulterants is difficult based on morphological characters. Therefore, an accurate, convenient, and stability method is urgently needed. In this wok, we developed a DNA barcoding technique to distinguish T. wilfordii HOOK. f., T. hypoglaucum (LÉVL.) HUTCH, and T. regelii SPRAGUE et TAKEDA and their adulterants based on four uniform and standard DNA regions (internal transcribed spacer 2 (ITS2), matK, rbcL, and psbA-trnH). DNA was extracted from 26 locations of fresh leaves. Phylogenetic tree was constructed with Neighbor-Joining (NJ) method, while barcoding gap was analyzed to assess identification efficiency. Compared with the other DNA barcodes applied individually or in combination, ITS2+psbA-trnH was demonstrated as the optimal barcode. T. hypoglaucum and T. wilfordii can be considered as conspecific, while T. regelii was recognized as a separate species. Furthermore, identification of commercial Tripterygium samples was conducted using BLAST against GenBank and Species Identification System for Traditional Chinese Medicine. Our results indicated that DNA barcoding is a convenient, effective, and stability method to identify and distinguish Tripterygium and its adulterants, and could be applied as the quality control for Tripterygium medicinal preparations and monitoring of the medicinal herb trade in markets.

Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree.

PubMed

Acharya, Tri Dev; Lee, Dong Ha; Yang, In Tae; Lee, Jae Kang

2016-07-12

Water bodies are essential to humans and other forms of life. Identification of water bodies can be useful in various ways, including estimation of water availability, demarcation of flooded regions, change detection, and so on. In past decades, Landsat satellite sensors have been used for land use classification and water body identification. Due to the introduction of a New Operational Land Imager (OLI) sensor on Landsat 8 with a high spectral resolution and improved signal-to-noise ratio, the quality of imagery sensed by Landsat 8 has improved, enabling better characterization of land cover and increased data size. Therefore, it is necessary to explore the most appropriate and practical water identification methods that take advantage of the improved image quality and use the fewest inputs based on the original OLI bands. The objective of the study is to explore the potential of a J48 decision tree (JDT) in identifying water bodies using reflectance bands from Landsat 8 OLI imagery. J48 is an open-source decision tree. The test site for the study is in the Northern Han River Basin, which is located in Gangwon province, Korea. Training data with individual bands were used to develop the JDT model and later applied to the whole study area. The performance of the model was statistically analysed using the kappa statistic and area under the curve (AUC). The results were compared with five other known water identification methods using a confusion matrix and related statistics. Almost all the methods showed high accuracy, and the JDT was successfully applied to the OLI image using only four bands, where the new additional deep blue band of OLI was found to have the third highest information gain. Thus, the JDT can be a good method for water body identification based on images with improved resolution and increased size.

A RAPID DNA EXTRACTION METHOD FOR PCR IDENTIFICATION OF FUNGAL INDOOR AIR CONTAMINANTS

EPA Science Inventory

Following air sampling, fungal DNA needs to be extracted and purified to a state suitable for laboratory use. Our laboratory has developed a simple method of extraction and purification of fungal DNA appropriate for enzymatic manipulation and polymerase chain reaction (PCR) appli...

Outlier identification and visualization for Pb concentrations in urban soils and its implications for identification of potential contaminated land.

PubMed

Zhang, Chaosheng; Tang, Ya; Luo, Lin; Xu, Weilin

2009-11-01

Outliers in urban soil geochemical databases may imply potential contaminated land. Different methodologies which can be easily implemented for the identification of global and spatial outliers were applied for Pb concentrations in urban soils of Galway City in Ireland. Due to its strongly skewed probability feature, a Box-Cox transformation was performed prior to further analyses. The graphic methods of histogram and box-and-whisker plot were effective in identification of global outliers at the original scale of the dataset. Spatial outliers could be identified by a local indicator of spatial association of local Moran's I, cross-validation of kriging, and a geographically weighted regression. The spatial locations of outliers were visualised using a geographical information system. Different methods showed generally consistent results, but differences existed. It is suggested that outliers identified by statistical methods should be confirmed and justified using scientific knowledge before they are properly dealt with.

Data-driven mono-component feature identification via modified nonlocal means and MEWT for mechanical drivetrain fault diagnosis

NASA Astrophysics Data System (ADS)

Pan, Jun; Chen, Jinglong; Zi, Yanyang; Yuan, Jing; Chen, Binqiang; He, Zhengjia

2016-12-01

It is significant to perform condition monitoring and fault diagnosis on rolling mills in steel-making plant to ensure economic benefit. However, timely fault identification of key parts in a complicated industrial system under operating condition is still a challenging task since acquired condition signals are usually multi-modulated and inevitably mixed with strong noise. Therefore, a new data-driven mono-component identification method is proposed in this paper for diagnostic purpose. First, the modified nonlocal means algorithm (NLmeans) is proposed to reduce noise in vibration signals without destroying its original Fourier spectrum structure. During the modified NLmeans, two modifications are investigated and performed to improve denoising effect. Then, the modified empirical wavelet transform (MEWT) is applied on the de-noised signal to adaptively extract empirical mono-component modes. Finally, the modes are analyzed for mechanical fault identification based on Hilbert transform. The results show that the proposed data-driven method owns superior performance during system operation compared with the MEWT method.

High-throughput Identification of Bacteria Repellent Polymers for Medical Devices

PubMed Central

Wu, Mei; Hardman, Ailsa; Lilienkampf, Annamaria; Pernagallo, Salvatore; Blakely, Garry; Swann, David G.; Bradley, Mark; Gallagher, Maurice P.

2016-01-01

Medical devices are often associated with hospital-acquired infections, which place enormous strain on patients and the healthcare system as well as contributing to antimicrobial resistance. One possible avenue for the reduction of device-associated infections is the identification of bacteria-repellent polymer coatings for these devices, which would prevent bacterial binding at the initial attachment step. A method for the identification of such repellent polymers, based on the parallel screening of hundreds of polymers using a microarray, is described here. This high-throughput method resulted in the identification of a range of promising polymers that resisted binding of various clinically relevant bacterial species individually and also as multi-species communities. One polymer, PA13 (poly(methylmethacrylate-co-dimethylacrylamide)), demonstrated significant reduction in attachment of a number of hospital isolates when coated onto two commercially available central venous catheters. The method described could be applied to identify polymers for a wide range of applications in which modification of bacterial attachment is important. PMID:27842360

On convergence and convergence rates for Ivanov and Morozov regularization and application to some parameter identification problems in elliptic PDEs

NASA Astrophysics Data System (ADS)

Kaltenbacher, Barbara; Klassen, Andrej

2018-05-01

In this paper we provide a convergence analysis of some variational methods alternative to the classical Tikhonov regularization, namely Ivanov regularization (also called the method of quasi solutions) with some versions of the discrepancy principle for choosing the regularization parameter, and Morozov regularization (also called the method of the residuals). After motivating nonequivalence with Tikhonov regularization by means of an example, we prove well-definedness of the Ivanov and the Morozov method, convergence in the sense of regularization, as well as convergence rates under variational source conditions. Finally, we apply these results to some linear and nonlinear parameter identification problems in elliptic boundary value problems.

Intensity of regionally applied tastes in relation to administration method: an investigation based on the "taste strips" test.

PubMed

Manzi, Brian; Hummel, Thomas

2014-02-01

To compare various methods to apply regional taste stimuli to the tongue. "Taste strips" are a clinical tool to determine gustatory function. How a patient perceives the chemical environment in the mouth is a result of many factors such as taste bud distribution and interactions between the cranial nerves. To date, there have been few studies describing the different approaches to administer taste strips to maximize taste identification accuracy and intensity. This is a normative value acquisition pilot and single-center study. The investigation involved 30 participants reporting a normal sense of smell and taste (18 women, 12 men, mean age 33 years). The taste test was based on spoon-shaped filter paper strips impregnated with four taste qualities (sweet, sour, salty, and bitter) at concentrations shown to be easily detectable by young healthy subjects. The strips were administered in three methods (held stationary on the tip of the tongue, applied across the tongue, held in the mouth), resulting in a total of 12 trials per participant. Subjects identified the taste from a list of four descriptors, (sweet, sour, salty, bitter) and ranked the intensity on a scale from 0 to 10. Statistical analyses were performed on the accuracy of taste identification and rated intensities. The participants perceived in order of most to least intense: salt, sour, bitter, sweet. Of the four tastes, sour consistently was least accurately identified. Presenting the taste strip inside the closed mouth of the participants produced the least accurate taste identification, whereas moving the taste strip across the tongue led to a significant increase in intensity for the sweet taste. In this study of 30 subjects at the second concentration, optimized accuracy and intensity of taste identification was observed through administration of taste strips laterally across the anterior third of the extended tongue. Further studies are required on more subjects and the additional concentrations prior to determining the ideal taste strip application method.

A photometric mode identification method, including an improved non-adiabatic treatment of the atmosphere

NASA Astrophysics Data System (ADS)

Dupret, M.-A.; De Ridder, J.; De Cat, P.; Aerts, C.; Scuflaire, R.; Noels, A.; Thoul, A.

2003-02-01

We present an improved version of the method of photometric mode identification of Heynderickx et al. (\\cite{hey}). Our new version is based on the inclusion of precise non-adiabatic eigenfunctions determined in the outer stellar atmosphere according to the formalism recently proposed by Dupret et al. (\\cite{dup}). Our improved photometric mode identification technique is therefore no longer dependent on ad hoc parameters for the non-adiabatic effects. It contains the complete physical conditions of the outer atmosphere of the star, provided that rotation does not play a key role. We apply our method to the two slowly pulsating B stars HD 74560 and HD 138764 and to the beta Cephei star EN (16) Lac. Besides identifying the degree l of the pulsating stars, our method is also a tool for improving the knowledge of stellar interiors and atmospheres, by imposing constraints on parameters such as the metallicity and the mixing-length parameter alpha (a procedure we label non-adiabatic asteroseismology). The non-adiabatic eigenfunctions needed for the mode identification are available upon request from the authors.

Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Tolpekin, Valentyn A.; Bijker, Wietske; Stein, Alfred

2011-11-01

Identification of tree crowns from remote sensing requires detailed spectral information and submeter spatial resolution imagery. Traditional pixel-based classification techniques do not fully exploit the spatial and spectral characteristics of remote sensing datasets. We propose a contextual and probabilistic method for detection of tree crowns in urban areas using a Markov random field based super resolution mapping (SRM) approach in very high resolution images. Our method defines an objective energy function in terms of the conditional probabilities of panchromatic and multispectral images and it locally optimizes the labeling of tree crown pixels. Energy and model parameter values are estimated from multiple implementations of SRM in tuning areas and the method is applied in QuickBird images to produce a 0.6 m tree crown map in a city of The Netherlands. The SRM output shows an identification rate of 66% and commission and omission errors in small trees and shrub areas. The method outperforms tree crown identification results obtained with maximum likelihood, support vector machines and SRM at nominal resolution (2.4 m) approaches.

Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

PubMed

Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko

2017-07-01

Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.

Separomics applied to the proteomics and peptidomics of low-abundance proteins: Choice of methods and challenges - A review.

PubMed

Baracat-Pereira, Maria Cristina; de Oliveira Barbosa, Meire; Magalhães, Marcos Jorge; Carrijo, Lanna Clicia; Games, Patrícia Dias; Almeida, Hebréia Oliveira; Sena Netto, José Fabiano; Pereira, Matheus Rodrigues; de Barros, Everaldo Gonçalves

2012-06-01

The enrichment and isolation of proteins are considered limiting steps in proteomic studies. Identification of proteins whose expression is transient, those that are of low-abundance, and of natural peptides not described in databases, is still a great challenge. Plant extracts are in general complex, and contaminants interfere with the identification of proteins involved in important physiological processes, such as plant defense against pathogens. This review discusses the challenges and strategies of separomics applied to the identification of low-abundance proteins and peptides in plants, especially in plants challenged by pathogens. Separomics is described as a group of methodological strategies for the separation of protein molecules for proteomics. Several tools have been used to remove highly abundant proteins from samples and also non-protein contaminants. The use of chromatographic techniques, the partition of the proteome into subproteomes, and an effort to isolate proteins in their native form have allowed the isolation and identification of rare proteins involved in different processes.

Separomics applied to the proteomics and peptidomics of low-abundance proteins: Choice of methods and challenges – A review

PubMed Central

Baracat-Pereira, Maria Cristina; de Oliveira Barbosa, Meire; Magalhães, Marcos Jorge; Carrijo, Lanna Clicia; Games, Patrícia Dias; Almeida, Hebréia Oliveira; Sena Netto, José Fabiano; Pereira, Matheus Rodrigues; de Barros, Everaldo Gonçalves

2012-01-01

The enrichment and isolation of proteins are considered limiting steps in proteomic studies. Identification of proteins whose expression is transient, those that are of low-abundance, and of natural peptides not described in databases, is still a great challenge. Plant extracts are in general complex, and contaminants interfere with the identification of proteins involved in important physiological processes, such as plant defense against pathogens. This review discusses the challenges and strategies of separomics applied to the identification of low-abundance proteins and peptides in plants, especially in plants challenged by pathogens. Separomics is described as a group of methodological strategies for the separation of protein molecules for proteomics. Several tools have been used to remove highly abundant proteins from samples and also non-protein contaminants. The use of chromatographic techniques, the partition of the proteome into subproteomes, and an effort to isolate proteins in their native form have allowed the isolation and identification of rare proteins involved in different processes. PMID:22802713

Domain identification in impedance computed tomography by spline collocation method

NASA Technical Reports Server (NTRS)

Kojima, Fumio

1990-01-01

A method for estimating an unknown domain in elliptic boundary value problems is considered. The problem is formulated as an inverse problem of integral equations of the second kind. A computational method is developed using a splice collocation scheme. The results can be applied to the inverse problem of impedance computed tomography (ICT) for image reconstruction.

Evaluation of the Technical Adequacy of Three Methods for Identifying Specific Learning Disabilities Based on Cognitive Discrepancies

ERIC Educational Resources Information Center

Stuebing, Karla K.; Fletcher, Jack M.; Branum-Martin, Lee; Francis, David J.

2012-01-01

This study used simulation techniques to evaluate the technical adequacy of three methods for the identification of specific learning disabilities via patterns of strengths and weaknesses in cognitive processing. Latent and observed data were generated and the decision-making process of each method was applied to assess concordance in…

Adaptive infinite impulse response system identification using modified-interior search algorithm with Lèvy flight.

PubMed

Kumar, Manjeet; Rawat, Tarun Kumar; Aggarwal, Apoorva

2017-03-01

In this paper, a new meta-heuristic optimization technique, called interior search algorithm (ISA) with Lèvy flight is proposed and applied to determine the optimal parameters of an unknown infinite impulse response (IIR) system for the system identification problem. ISA is based on aesthetics, which is commonly used in interior design and decoration processes. In ISA, composition phase and mirror phase are applied for addressing the nonlinear and multimodal system identification problems. System identification using modified-ISA (M-ISA) based method involves faster convergence, single parameter tuning and does not require derivative information because it uses a stochastic random search using the concepts of Lèvy flight. A proper tuning of control parameter has been performed in order to achieve a balance between intensification and diversification phases. In order to evaluate the performance of the proposed method, mean square error (MSE), computation time and percentage improvement are considered as the performance measure. To validate the performance of M-ISA based method, simulations has been carried out for three benchmarked IIR systems using same order and reduced order system. Genetic algorithm (GA), particle swarm optimization (PSO), cat swarm optimization (CSO), cuckoo search algorithm (CSA), differential evolution using wavelet mutation (DEWM), firefly algorithm (FFA), craziness based particle swarm optimization (CRPSO), harmony search (HS) algorithm, opposition based harmony search (OHS) algorithm, hybrid particle swarm optimization-gravitational search algorithm (HPSO-GSA) and ISA are also used to model the same examples and simulation results are compared. Obtained results confirm the efficiency of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Comprehensive HPTLC Fingerprinting for Quality Control of an Herbal Drug - The Case of Angelica gigas Root.

PubMed

Frommenwiler, Débora Arruda; Kim, Jonghwan; Yook, Chang-Soo; Tran, Thi Thu Trang; Cañigueral, Salvador; Reich, Eike

2018-04-01

The quality of herbal drugs is usually controlled using several tests recommended in a monograph. HPTLC is the method of choice for identification in many pharmacopoeias. If combined with a suitable reference material for comparison, HPTLC can provide information beyond identification and thus may simplify quality control. This paper describes, as a proof of concept, how HPTLC can be applied to define specifications for an herbal reference material and to control the quality of an herbal drug according to these specifications. Based on multiple batches of cultivated Angelica gigas root, a specific HPTLC method for identification was optimized. This method can distinguish 27 related species. It also can detect the presence of mixtures of A. gigas with two other Angelica species traded as "Dang gui" and is suitable as well for quantitative assessment of samples in a test for minimum content of the sum of decursin and decursinol angelate. The new concept of "comprehensive HPTLC fingerprinting" is proposed: HPTLC fingerprints (images), which are used for identification, are converted into peak profiles and the intensities of selected zones are quantitatively compared to those of the corresponding zones of the reference material. Following a collaborative trial involving three laboratories in three countries, the method was applied to check the quality of further candidates for establishing an appropriate reference material. In conclusion, this case demonstrates that a single HPTLC analysis can provide information about identity, purity, and minimum content of markers of an herbal drug. Georg Thieme Verlag KG Stuttgart · New York.

Multi-centre evaluation of mass spectrometric identification of anaerobic bacteria using the VITEK® MS system.

PubMed

Garner, O; Mochon, A; Branda, J; Burnham, C-A; Bythrow, M; Ferraro, M; Ginocchio, C; Jennemann, R; Manji, R; Procop, G W; Richter, S; Rychert, J; Sercia, L; Westblade, L; Lewinski, M

2014-04-01

Accurate and timely identification of anaerobic bacteria is critical to successful treatment. Classic phenotypic methods for identification require long turnaround times and can exhibit poor species level identification. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is an identification method that can provide rapid identification of anaerobes. We present a multi-centre study assessing the clinical performance of the VITEK(®) MS in the identification of anaerobic bacteria. Five different test sites analysed a collection of 651 unique anaerobic isolates comprising 11 different genera. Multiple species were included for several of the genera. Briefly, anaerobic isolates were applied directly to a well of a target plate. Matrix solution (α-cyano-4-hydroxycinnamic acid) was added and allowed to dry. Mass spectra results were generated with the VITEK(®) MS, and the comparative spectral analysis and organism identification were determined using the VITEK(®) MS database 2.0. Results were confirmed by 16S rRNA gene sequencing. Of the 651 isolates analysed, 91.2% (594/651) exhibited the correct species identification. An additional eight isolates were correctly identified to genus level, raising the rate of identification to 92.5%. Genus-level identification consisted of Actinomyces, Bacteroides and Prevotella species. Fusobacterium nucleatum, Actinomyces neuii and Bacteroides uniformis were notable for an increased percentage of no-identification results compared with the other anaerobes tested. VITEK(®) MS identification of clinically relevant anaerobes is highly accurate and represents a dramatic improvement over other phenotypic methods in accuracy and turnaround time. © 2013 The Authors Clinical Microbiology and Infection © 2013 European Society of Clinical Microbiology and Infectious Diseases.

A Galerkin method for the estimation of parameters in hybrid systems governing the vibration of flexible beams with tip bodies

NASA Technical Reports Server (NTRS)

Banks, H. T.; Rosen, I. G.

1985-01-01

An approximation scheme is developed for the identification of hybrid systems describing the transverse vibrations of flexible beams with attached tip bodies. In particular, problems involving the estimation of functional parameters are considered. The identification problem is formulated as a least squares fit to data subject to the coupled system of partial and ordinary differential equations describing the transverse displacement of the beam and the motion of the tip bodies respectively. A cubic spline-based Galerkin method applied to the state equations in weak form and the discretization of the admissible parameter space yield a sequence of approximating finite dimensional identification problems. It is shown that each of the approximating problems admits a solution and that from the resulting sequence of optimal solutions a convergent subsequence can be extracted, the limit of which is a solution to the original identification problem. The approximating identification problems can be solved using standard techniques and readily available software.

Writer identification on historical Glagolitic documents

NASA Astrophysics Data System (ADS)

Fiel, Stefan; Hollaus, Fabian; Gau, Melanie; Sablatnig, Robert

2013-12-01

This work aims at automatically identifying scribes of historical Slavonic manuscripts. The quality of the ancient documents is partially degraded by faded-out ink or varying background. The writer identification method used is based on image features, which are described with Scale Invariant Feature Transform (SIFT) features. A visual vocabulary is used for the description of handwriting characteristics, whereby the features are clustered using a Gaussian Mixture Model and employing the Fisher kernel. The writer identification approach is originally designed for grayscale images of modern handwritings. But contrary to modern documents, the historical manuscripts are partially corrupted by background clutter and water stains. As a result, SIFT features are also found on the background. Since the method shows also good results on binarized images of modern handwritings, the approach was additionally applied on binarized images of the ancient writings. Experiments show that this preprocessing step leads to a significant performance increase: The identification rate on binarized images is 98.9%, compared to an identification rate of 87.6% gained on grayscale images.

Personal Identification of Deceased Persons: An Overview of the Current Methods Based on Physical Appearance.

PubMed

Caplova, Zuzana; Obertova, Zuzana; Gibelli, Daniele M; De Angelis, Danilo; Mazzarelli, Debora; Sforza, Chiarella; Cattaneo, Cristina

2018-05-01

The use of the physical appearance of the deceased has become more important because the available antemortem information for comparisons may consist only of a physical description and photographs. Twenty-one articles dealing with the identification based on the physiognomic features of the human body were selected for review and were divided into four sections: (i) visual recognition, (ii) specific facial/body areas, (iii) biometrics, and (iv) dental superimposition. While opinions about the reliability of the visual recognition differ, the search showed that it has been used in mass disasters, even without testing its objectivity and reliability. Specific facial areas being explored for the identification of dead; however, their practical use is questioned, similarly to soft biometrics. The emerging dental superimposition seems to be the only standardized and successfully applied method for identification so far. More research is needed into a potential use of the individualizing features, considering that postmortem changes and technical difficulties may affect the identification. © 2017 American Academy of Forensic Sciences.

A Developed Spectral Identification Tree for Mineral Mapping using Hyperspectral Data

NASA Astrophysics Data System (ADS)

Gan, Fuping; Wang, Runsheng; Yan, Bokun; Shang, Kun

2016-04-01

The relationship between the spectral features and the composition of minerals are the basis of mineral identification using hyperspectral data. The reflectance spectrum of minerals results from the systematic combination of several modes of interaction between electromagnetic energy and mineral particles in the form of reflection and absorption. Minerals tend to have absorbing features at specific wavelengths with a characteristic shape, which can be used as diagnostic indicators for identification. The spectral identification tree (SIT) method for mineral identification is developed in our research to map minerals accurately and applied in some typical mineral deposits in China. The SIT method is based on the diagnostic absorption features of minerals through comparing and statistically analyzing characteristic spectral data of minerals. We establish several levels of identification rules for the type, group and species of minerals using IF-THEN rule according to the spectral identification criteria so that the developed SIT can be further used to map minerals at different levels of detail from mineral type to mineral species. Identifiable minerals can be grouped into six types: Fe2+-bearing, Fe3+-bearing, Mn2+-bearing, Al-OH-bearing, Mg-OH-bearing and carbonate minerals. Each type can be further divided into several mineral groups. Each group contains several mineral species or specific minerals. A mineral spectral series, therefore, can be constructed as "type-group-species-specific mineral (mineral variety)" for mineral spectral identification. It is noted that the mineral classification is based mainly on spectral reflectance characteristics of minerals which may not be consistent with the classification in mineralogy. We applied the developed SIT method to the datasets acquired at the Eastern Tianshan Mountains of Xinjiang (HyMap data) and the Qulong district of Xizang (Hyperion data). In Xinjiang, the two major classes of Al-OH and Mg-OH minerals were mapped firstly. Then montmorillonite, kaolinite and muscovite were identified in the area of the Al-OH bearing minerals, and chlorite and epidote were identified in the area of the Mg-OH bearing minerals. Muscovite of rich Al and poor Al were further identified in the area of muscovite. In Xizang, Al-rich and Al-poor muscovite, kaolinite, chlorite and malachite were identified using SIT method. In all, the developed SIT method can further reduce the effect of other materials and focus on targeted minerals. In particular, the discrimination accuracy will be improved when the most diagnostic absorption spectral features are used in the developed SIT method.

Identification of flame transfer functions in the presence of intrinsic thermoacoustic feedback and noise

NASA Astrophysics Data System (ADS)

Jaensch, Stefan; Merk, Malte; Emmert, Thomas; Polifke, Wolfgang

2018-05-01

The Large Eddy Simulation/System Identification (LES/SI) approach is a general and efficient numerical method for deducing a Flame Transfer Function (FTF) from the LES of turbulent reacting flow. The method may be summarised as follows: a simulated flame is forced with a broadband excitation signal. The resulting fluctuations of the reference velocity and of the global heat release rate are post-processed via SI techniques in order to estimate a low-order model of the flame dynamics. The FTF is readily deduced from the low-order model. The SI method most frequently applied in aero- and thermo-acoustics has been Wiener-Hopf Inversion (WHI). This method is known to yield biased estimates in situations with feedback, thus it was assumed that non-reflective boundary conditions are required to generate accurate results with the LES/SI approach. Recent research has shown that the FTF is part of the so-called Intrinsic ThermoAcoustic (ITA) feedback loop. Hence, identifying an FTF from a compressible LES is always a closed-loop problem, and consequently one should expect that the WHI would yield biased results. However, several studies proved that WHI results compare favourably with validation data. To resolve this apparent contradiction, a variety of identification methods are compared against each other, including models designed for closed-loop identification. In agreement with theory, we show that the estimate given by WHI does not converge to the actual FTF. Fortunately, the error made is small if excitation amplitudes can be set such that the signal-to-noise ratio is large, but not large enough to trigger nonlinear flame dynamics. Furthermore, we conclude that non-reflective boundary conditions are not essentially necessary to apply the LES/SI approach.

Bacteriophage Amplification-Coupled Detection and Identification of Bacterial Pathogens

NASA Astrophysics Data System (ADS)

Cox, Christopher R.; Voorhees, Kent J.

Current methods of species-specific bacterial detection and identification are complex, time-consuming, and often require expensive specialized equipment and highly trained personnel. Numerous biochemical and genotypic identification methods have been applied to bacterial characterization, but all rely on tedious microbiological culturing practices and/or costly sequencing protocols which render them impractical for deployment as rapid, cost-effective point-of-care or field detection and identification methods. With a view towards addressing these shortcomings, we have exploited the evolutionarily conserved interactions between a bacteriophage (phage) and its bacterial host to develop species-specific detection methods. Phage amplification-coupled matrix assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF-MS) was utilized to rapidly detect phage propagation resulting from species-specific in vitro bacterial infection. This novel signal amplification method allowed for bacterial detection and identification in as little as 2 h, and when combined with disulfide bond reduction methods developed in our laboratory to enhance MALDI-TOF-MS resolution, was observed to lower the limit of detection by several orders of magnitude over conventional spectroscopy and phage typing methods. Phage amplification has been combined with lateral flow immunochromatography (LFI) to develop rapid, easy-to-operate, portable, species-specific point-of-care (POC) detection devices. Prototype LFI detectors have been developed and characterized for Yersinia pestis and Bacillus anthracis, the etiologic agents of plague and anthrax, respectively. Comparable sensitivity and rapidity was observed when phage amplification was adapted to a species-specific handheld LFI detector, thus allowing for rapid, simple, POC bacterial detection and identification while eliminating the need for bacterial culturing or DNA isolation and amplification techniques.

EMQN Best Practice Guidelines for molecular and haematology methods for carrier identification and prenatal diagnosis of the haemoglobinopathies.

PubMed

Traeger-Synodinos, Joanne; Harteveld, Cornelis L; Old, John M; Petrou, Mary; Galanello, Renzo; Giordano, Piero; Angastioniotis, Michael; De la Salle, Barbara; Henderson, Shirley; May, Alison

2015-04-01

Haemoglobinopathies constitute the commonest recessive monogenic disorders worldwide, and the treatment of affected individuals presents a substantial global disease burden. Carrier identification and prenatal diagnosis represent valuable procedures that identify couples at risk for having affected children, so that they can be offered options to have healthy offspring. Molecular diagnosis facilitates prenatal diagnosis and definitive diagnosis of carriers and patients (especially 'atypical' cases who often have complex genotype interactions). However, the haemoglobin disorders are unique among all genetic diseases in that identification of carriers is preferable by haematological (biochemical) tests rather than DNA analysis. These Best Practice guidelines offer an overview of recommended strategies and methods for carrier identification and prenatal diagnosis of haemoglobinopathies, and emphasize the importance of appropriately applying and interpreting haematological tests in supporting the optimum application and evaluation of globin gene DNA analysis.

EMQN Best Practice Guidelines for molecular and haematology methods for carrier identification and prenatal diagnosis of the haemoglobinopathies

PubMed Central

Traeger-Synodinos, Joanne; Harteveld, Cornelis L; Old, John M; Petrou, Mary; Galanello, Renzo; Giordano, Piero; Angastioniotis, Michael; De la Salle, Barbara; Henderson, Shirley; May, Alison

2015-01-01

Haemoglobinopathies constitute the commonest recessive monogenic disorders worldwide, and the treatment of affected individuals presents a substantial global disease burden. Carrier identification and prenatal diagnosis represent valuable procedures that identify couples at risk for having affected children, so that they can be offered options to have healthy offspring. Molecular diagnosis facilitates prenatal diagnosis and definitive diagnosis of carriers and patients (especially ‘atypical' cases who often have complex genotype interactions). However, the haemoglobin disorders are unique among all genetic diseases in that identification of carriers is preferable by haematological (biochemical) tests rather than DNA analysis. These Best Practice guidelines offer an overview of recommended strategies and methods for carrier identification and prenatal diagnosis of haemoglobinopathies, and emphasize the importance of appropriately applying and interpreting haematological tests in supporting the optimum application and evaluation of globin gene DNA analysis. PMID:25052315

[A peak recognition algorithm designed for chromatographic peaks of transformer oil].

PubMed

Ou, Linjun; Cao, Jian

2014-09-01

In the field of the chromatographic peak identification of the transformer oil, the traditional first-order derivative requires slope threshold to achieve peak identification. In terms of its shortcomings of low automation and easy distortion, the first-order derivative method was improved by applying the moving average iterative method and the normalized analysis techniques to identify the peaks. Accurate identification of the chromatographic peaks was realized through using multiple iterations of the moving average of signal curves and square wave curves to determine the optimal value of the normalized peak identification parameters, combined with the absolute peak retention times and peak window. The experimental results show that this algorithm can accurately identify the peaks and is not sensitive to the noise, the chromatographic peak width or the peak shape changes. It has strong adaptability to meet the on-site requirements of online monitoring devices of dissolved gases in transformer oil.

Topic Identification and Categorization of Public Information in Community-Based Social Media

NASA Astrophysics Data System (ADS)

Kusumawardani, RP; Basri, MH

2017-01-01

This paper presents a work on a semi-supervised method for topic identification and classification of short texts in the social media, and its application on tweets containing dialogues in a large community of dwellers in a city, written mostly in Indonesian. These dialogues comprise a wealth of information about the city, shared in real-time. We found that despite the high irregularity of the language used, and the scarcity of suitable linguistic resources, a meaningful identification of topics could be performed by clustering the tweets using the K-Means algorithm. The resulting clusters are found to be robust enough to be the basis of a classification. On three grouping schemes derived from the clusters, we get accuracy of 95.52%, 95.51%, and 96.7 using linear SVMs, reflecting the applicability of applying this method for generating topic identification and classification on such data.

Molecular identification of Malassezia species isolated from dermatitis affections.

PubMed

Affes, M; Ben Salah, S; Makni, F; Sellami, H; Ayadi, A

2009-05-01

The lipophilic yeast of the genus Malassezia are opportunistic microorganisms of the skin microflora but they can be agents of various dermatomycoses. The aim of this study was to perform molecular identification of the commonly isolated Malassezia species from various dermatomycoses in our region. Thirty strains of Malassezia were isolated from different dermatologic affections: pityriasis versicolor (17), dandruff (5), seborrheic dermatitis (4), onyxis (2), folliculitis (1) and blepharitis (1). These species were identified by their morphological features and biochemical characterisation. The molecular identification was achieved by amplification of the internal transcribed spacer region by simple PCR. PCR technique was used for molecular characterisation of four Malassezia species: Malassezia globosa (270 bp), Malassezia furfur (230 bp), Malassezia sympodialis (190 bp) and Malassezia restricta (320 bp). We have detected the association between M. furfur and M. sympodialis in 16% and confirmed presumptive identification in 70% of the cases. The phenotypic identification based on microscopic and physiological method is difficult and time consuming. The application of a simple PCR method provides a sensitive and rapid identification system for Malassezia species, which may be applied in epidemiological surveys and routine practice.

Mobile visual object identification: from SIFT-BoF-RANSAC to Sketchprint

NASA Astrophysics Data System (ADS)

Voloshynovskiy, Sviatoslav; Diephuis, Maurits; Holotyak, Taras

2015-03-01

Mobile object identification based on its visual features find many applications in the interaction with physical objects and security. Discriminative and robust content representation plays a central role in object and content identification. Complex post-processing methods are used to compress descriptors and their geometrical information, aggregate them into more compact and discriminative representations and finally re-rank the results based on the similarity geometries of descriptors. Unfortunately, most of the existing descriptors are not very robust and discriminative once applied to the various contend such as real images, text or noise-like microstructures next to requiring at least 500-1'000 descriptors per image for reliable identification. At the same time, the geometric re-ranking procedures are still too complex to be applied to the numerous candidates obtained from the feature similarity based search only. This restricts that list of candidates to be less than 1'000 which obviously causes a higher probability of miss. In addition, the security and privacy of content representation has become a hot research topic in multimedia and security communities. In this paper, we introduce a new framework for non- local content representation based on SketchPrint descriptors. It extends the properties of local descriptors to a more informative and discriminative, yet geometrically invariant content representation. In particular it allows images to be compactly represented by 100 SketchPrint descriptors without being fully dependent on re-ranking methods. We consider several use cases, applying SketchPrint descriptors to natural images, text documents, packages and micro-structures and compare them with the traditional local descriptors.

A measurement fusion method for nonlinear system identification using a cooperative learning algorithm.

PubMed

Xia, Youshen; Kamel, Mohamed S

2007-06-01

Identification of a general nonlinear noisy system viewed as an estimation of a predictor function is studied in this article. A measurement fusion method for the predictor function estimate is proposed. In the proposed scheme, observed data are first fused by using an optimal fusion technique, and then the optimal fused data are incorporated in a nonlinear function estimator based on a robust least squares support vector machine (LS-SVM). A cooperative learning algorithm is proposed to implement the proposed measurement fusion method. Compared with related identification methods, the proposed method can minimize both the approximation error and the noise error. The performance analysis shows that the proposed optimal measurement fusion function estimate has a smaller mean square error than the LS-SVM function estimate. Moreover, the proposed cooperative learning algorithm can converge globally to the optimal measurement fusion function estimate. Finally, the proposed measurement fusion method is applied to ARMA signal and spatial temporal signal modeling. Experimental results show that the proposed measurement fusion method can provide a more accurate model.

A low noise stenography method for medical images with QR encoding of patient information

NASA Astrophysics Data System (ADS)

Patiño-Vanegas, Alberto; Contreras-Ortiz, Sonia H.; Martinez-Santos, Juan C.

2017-03-01

This paper proposes an approach to facilitate the process of individualization of patients from their medical images, without compromising the inherent confidentiality of medical data. The identification of a patient from a medical image is not often the goal of security methods applied to image records. Usually, any identification data is removed from shared records, and security features are applied to determine ownership. We propose a method for embedding a QR-code containing information that can be used to individualize a patient. This is done so that the image to be shared does not differ significantly from the original image. The QR-code is distributed in the image by changing several pixels according to a threshold value based on the average value of adjacent pixels surrounding the point of interest. The results show that the code can be embedded and later fully recovered with minimal changes in the UIQI index - less than 0.1% of different.

Identification of magnetic anomalies based on ground magnetic data analysis using multifractal modeling: a case study in Qoja-Kandi, East Azerbaijan Province, Iran

NASA Astrophysics Data System (ADS)

Mansouri, E.; Feizi, F.; Karbalaei Ramezanali, A. A.

2015-07-01

Ground magnetic anomaly separation using reduction-to-the-pole (RTP) technique and the fractal concentration-area (C-A) method has been applied to the Qoja-Kandi prosepecting area in NW Iran. The geophysical survey that resulted in the ground magnetic data was conducted for magnetic elements exploration. Firstly, RTP technique was applied for recognizing underground magnetic anomalies. RTP anomalies was classified to different populations based on this method. For this reason, drilling points determination with RTP technique was complicated. Next, C-A method was applied on the RTP-Magnetic-Anomalies (RTP-MA) for demonstrating magnetic susceptibility concentration. This identification was appropriate for increasing the resolution of the drilling points determination and decreasing the drilling risk, due to the economic costs of underground prospecting. In this study, the results of C-A Modeling on the RTP-MA are compared with 8 borehole data. The results show there is good correlation between anomalies derived via C-A method and log report of boreholes. Two boreholes were drilled in magnetic susceptibility concentration, based on multifractal modeling data analyses, between 63 533.1 and 66 296 nT. Drilling results show appropriate magnetite thickness with the grades greater than 20 % Fe total. Also, anomalies associated with andesite units host iron mineralization.

The Rebirth of Culture in Microbiology through the Example of Culturomics To Study Human Gut Microbiota

PubMed Central

Lagier, Jean-Christophe; Hugon, Perrine; Khelaifia, Saber; Fournier, Pierre-Edouard; La Scola, Bernard

2015-01-01

SUMMARY Bacterial culture was the first method used to describe the human microbiota, but this method is considered outdated by many researchers. Metagenomics studies have since been applied to clinical microbiology; however, a “dark matter” of prokaryotes, which corresponds to a hole in our knowledge and includes minority bacterial populations, is not elucidated by these studies. By replicating the natural environment, environmental microbiologists were the first to reduce the “great plate count anomaly,” which corresponds to the difference between microscopic and culture counts. The revolution in bacterial identification also allowed rapid progress. 16S rRNA bacterial identification allowed the accurate identification of new species. Mass spectrometry allowed the high-throughput identification of rare species and the detection of new species. By using these methods and by increasing the number of culture conditions, culturomics allowed the extension of the known human gut repertoire to levels equivalent to those of pyrosequencing. Finally, taxonogenomics strategies became an emerging method for describing new species, associating the genome sequence of the bacteria systematically. We provide a comprehensive review on these topics, demonstrating that both empirical and hypothesis-driven approaches will enable a rapid increase in the identification of the human prokaryote repertoire. PMID:25567229

Automated bow shock and radiation belt edge identification methods and their application for Cluster, THEMIS/ARTEMIS and Van Allen Probes data

NASA Astrophysics Data System (ADS)

Facsko, Gabor; Sibeck, David; Balogh, Tamas; Kis, Arpad; Wesztergom, Viktor

2017-04-01

The bow shock and the outer rim of the outer radiation belt are detected automatically by our algorithm developed as a part of the Boundary Layer Identification Code Cluster Active Archive project. The radiation belt positions are determined from energized electron measurements working properly onboard all Cluster spacecraft. For bow shock identification we use magnetometer data and, when available, ion plasma instrument data. In addition, electrostatic wave instrument electron density, spacecraft potential measurements and wake indicator auxiliary data are also used so the events can be identified by all Cluster probes in highly redundant way, as the magnetometer and these instruments are still operational in all spacecraft. The capability and performance of the bow shock identification algorithm were tested using known bow shock crossing determined manually from January 29, 2002 to February 3,. The verification enabled 70% of the bow shock crossings to be identified automatically. The method shows high flexibility and it can be applied to observations from various spacecraft. Now these tools have been applied to Time History of Events and Macroscale Interactions during Substorms (THEMIS)/Acceleration, Reconnection, Turbulence, and Electrodynamics of the Moon's Interaction with the Sun (ARTEMIS) magnetic field, plasma and spacecraft potential observations to identify bow shock crossings; and to Van Allen Probes supra-thermal electron observations to identify the edges of the radiation belt. The outcomes of the algorithms are checked manually and the parameters used to search for bow shock identification are refined.

Water Quality Assessment for Deep-water Channel area of Guangzhou Port based on the Comprehensive Water Quality Identification Index Method

NASA Astrophysics Data System (ADS)

Chen, Yi

2018-03-01

The comprehensive water quality identification index method is able to assess the general water quality situation comprehensively and represent the water quality classification; water environment functional zone achieves pollution level and standard objectively and systematically. This paper selects 3 representative zones along deep-water channel of Guangzhou port and applies comprehensive water quality identification index method to calculate sea water quality monitoring data for different selected zones from year 2006 to 2014, in order to investigate the temporal variation of water quality along deep-water channel of Guangzhou port. The comprehensive water quality level from north to south presents an increased trend, and the water quality of the three zones in 2014 is much better than in 2006. This paper puts forward environmental protection measurements and suggestions for Pearl River Estuary, provides data support and theoretical basis for studied sea area pollution prevention and control.

Full-Field Strain Measurement On Titanium Welds And Local Elasto-Plastic Identification With The Virtual Fields Method

NASA Astrophysics Data System (ADS)

Tattoli, F.; Pierron, F.; Rotinat, R.; Casavola, C.; Pappalettere, C.

2011-01-01

One of the main problems in welding is the microstructural transformation within the area affected by the thermal history. The resulting heterogeneous microstructure within the weld nugget and the heat affected zones is often associated with changes in local material properties. The present work deals with the identification of material parameters governing the elasto—plastic behaviour of the fused and heat affected zones as well as the base material for titanium hybrid welded joints (Ti6Al4V alloy). The material parameters are identified from heterogeneous strain fields with the Virtual Fields Method. This method is based on a relevant use of the principle of virtual work and it has been shown to be useful and much less time consuming than classical finite element model updating approaches applied to similar problems. The paper will present results and discuss the problem of selection of the weld zones for the identification.

Enhancement of Chemical Entity Identification in Text Using Semantic Similarity Validation

PubMed Central

Grego, Tiago; Couto, Francisco M.

2013-01-01

With the amount of chemical data being produced and reported in the literature growing at a fast pace, it is increasingly important to efficiently retrieve this information. To tackle this issue text mining tools have been applied, but despite their good performance they still provide many errors that we believe can be filtered by using semantic similarity. Thus, this paper proposes a novel method that receives the results of chemical entity identification systems, such as Whatizit, and exploits the semantic relationships in ChEBI to measure the similarity between the entities found in the text. The method assigns a single validation score to each entity based on its similarities with the other entities also identified in the text. Then, by using a given threshold, the method selects a set of validated entities and a set of outlier entities. We evaluated our method using the results of two state-of-the-art chemical entity identification tools, three semantic similarity measures and two text window sizes. The method was able to increase precision without filtering a significant number of correctly identified entities. This means that the method can effectively discriminate the correctly identified chemical entities, while discarding a significant number of identification errors. For example, selecting a validation set with 75% of all identified entities, we were able to increase the precision by 28% for one of the chemical entity identification tools (Whatizit), maintaining in that subset 97% the correctly identified entities. Our method can be directly used as an add-on by any state-of-the-art entity identification tool that provides mappings to a database, in order to improve their results. The proposed method is included in a freely accessible web tool at www.lasige.di.fc.ul.pt/webtools/ice/. PMID:23658791

The relation between periods’ identification and noises in hydrologic series data

NASA Astrophysics Data System (ADS)

Sang, Yan-Fang; Wang, Dong; Wu, Ji-Chun; Zhu, Qing-Ping; Wang, Ling

2009-04-01

SummaryIdentification of dominant periods is a typical and important issue in hydrologic series data analysis, since it is the basis of building effective stochastic models, understanding complex hydrologic processes, etc. However it is still a difficult task due to the influence of many interrelated factors, such as noises in hydrologic series data. In this paper, firstly the great influence of noises on periods' identification has been analyzed. Then, based on two conventional methods of hydrologic series analysis: wavelet analysis (WA) and maximum entropy spectral analysis (MESA), a new method of periods' identification of hydrologic series data, main series spectral analysis (MSSA), has been put forward, whose main idea is to identify periods of the main series on the basis of reducing hydrologic noises. Various methods (include fast Fourier transform (FFT), MESA and MSSA) have been applied to both synthetic series and observed hydrologic series. Results show that conventional methods (FFT and MESA) are not as good as expected due to the great influence of noises. However, this influence is not so strong while using the new method MSSA. In addition, by using the new de-noising method proposed in this paper, which is suitable for both normal noises and skew noises, the results are more reasonable, since noises separated from hydrologic series data generally follow skew probability distributions. In conclusion, based on comprehensive analyses, it can be stated that the proposed method MSSA could improve periods' identification by effectively reducing the influence of hydrologic noises.

Global Sensitivity Analysis for Process Identification under Model Uncertainty

NASA Astrophysics Data System (ADS)

Ye, M.; Dai, H.; Walker, A. P.; Shi, L.; Yang, J.

2015-12-01

The environmental system consists of various physical, chemical, and biological processes, and environmental models are always built to simulate these processes and their interactions. For model building, improvement, and validation, it is necessary to identify important processes so that limited resources can be used to better characterize the processes. While global sensitivity analysis has been widely used to identify important processes, the process identification is always based on deterministic process conceptualization that uses a single model for representing a process. However, environmental systems are complex, and it happens often that a single process may be simulated by multiple alternative models. Ignoring the model uncertainty in process identification may lead to biased identification in that identified important processes may not be so in the real world. This study addresses this problem by developing a new method of global sensitivity analysis for process identification. The new method is based on the concept of Sobol sensitivity analysis and model averaging. Similar to the Sobol sensitivity analysis to identify important parameters, our new method evaluates variance change when a process is fixed at its different conceptualizations. The variance considers both parametric and model uncertainty using the method of model averaging. The method is demonstrated using a synthetic study of groundwater modeling that considers recharge process and parameterization process. Each process has two alternative models. Important processes of groundwater flow and transport are evaluated using our new method. The method is mathematically general, and can be applied to a wide range of environmental problems.

Selective structural source identification

NASA Astrophysics Data System (ADS)

Totaro, Nicolas

2018-04-01

In the field of acoustic source reconstruction, the inverse Patch Transfer Function (iPTF) has been recently proposed and has shown satisfactory results whatever the shape of the vibrating surface and whatever the acoustic environment. These two interesting features are due to the virtual acoustic volume concept underlying the iPTF methods. The aim of the present article is to show how this concept of virtual subsystem can be used in structures to reconstruct the applied force distribution. Some virtual boundary conditions can be applied on a part of the structure, called virtual testing structure, to identify the force distribution applied in that zone regardless of the presence of other sources outside the zone under consideration. In the present article, the applicability of the method is only demonstrated on planar structures. However, the final example show how the method can be applied to a complex shape planar structure with point welded stiffeners even in the tested zone. In that case, if the virtual testing structure includes the stiffeners the identified force distribution only exhibits the positions of external applied forces. If the virtual testing structure does not include the stiffeners, the identified force distribution permits to localize the forces due to the coupling between the structure and the stiffeners through the welded points as well as the ones due to the external forces. This is why this approach is considered here as a selective structural source identification method. It is demonstrated that this approach clearly falls in the same framework as the Force Analysis Technique, the Virtual Fields Method or the 2D spatial Fourier transform. Even if this approach has a lot in common with these latters, it has some interesting particularities like its low sensitivity to measurement noise.

An efficient and reliable DNA-based sex identification method for archaeological Pacific salmonid (Oncorhynchus spp.) remains.

PubMed

Royle, Thomas C A; Sakhrani, Dionne; Speller, Camilla F; Butler, Virginia L; Devlin, Robert H; Cannon, Aubrey; Yang, Dongya Y

2018-01-01

Pacific salmonid (Oncorhynchus spp.) remains are routinely recovered from archaeological sites in northwestern North America but typically lack sexually dimorphic features, precluding the sex identification of these remains through morphological approaches. Consequently, little is known about the deep history of the sex-selective salmonid fishing strategies practiced by some of the region's Indigenous peoples. Here, we present a DNA-based method for the sex identification of archaeological Pacific salmonid remains that integrates two PCR assays that each co-amplify fragments of the sexually dimorphic on the Y chromosome (sdY) gene and an internal positive control (Clock1a or D-loop). The first assay co-amplifies a 95 bp fragment of sdY and a 108 bp fragment of the autosomal Clock1a gene, whereas the second assay co-amplifies the same sdY fragment and a 249 bp fragment of the mitochondrial D-loop region. This method's reliability, sensitivity, and efficiency, were evaluated by applying it to 72 modern Pacific salmonids from five species and 75 archaeological remains from six Pacific salmonids. The sex identities assigned to each of the modern samples were concordant with their known phenotypic sex, highlighting the method's reliability. Applications of the method to dilutions of modern DNA samples indicate it can correctly identify the sex of samples with as little as ~39 pg of total genomic DNA. The successful sex identification of 70 of the 75 (93%) archaeological samples further demonstrates the method's sensitivity. The method's reliance on two co-amplifications that preferentially amplify sdY helps validate the sex identities assigned to samples and reduce erroneous identifications caused by allelic dropout and contamination. Furthermore, by sequencing the D-loop fragment used as a positive control, species-level and sex identifications can be simultaneously assigned to samples. Overall, our results indicate the DNA-based method reported in this study is a sensitive and reliable sex identification method for ancient salmonid remains.

Model reference adaptive control (MRAC)-based parameter identification applied to surface-mounted permanent magnet synchronous motor

NASA Astrophysics Data System (ADS)

Zhong, Chongquan; Lin, Yaoyao

2017-11-01

In this work, a model reference adaptive control-based estimated algorithm is proposed for online multi-parameter identification of surface-mounted permanent magnet synchronous machines. By taking the dq-axis equations of a practical motor as the reference model and the dq-axis estimation equations as the adjustable model, a standard model-reference-adaptive-system-based estimator was established. Additionally, the Popov hyperstability principle was used in the design of the adaptive law to guarantee accurate convergence. In order to reduce the oscillation of identification result, this work introduces a first-order low-pass digital filter to improve precision regarding the parameter estimation. The proposed scheme was then applied to an SPM synchronous motor control system without any additional circuits and implemented using a DSP TMS320LF2812. For analysis, the experimental results reveal the effectiveness of the proposed method.

Inter-Industry Wage Differentials and the Gender Wage Gap: An Identification Problem.

ERIC Educational Resources Information Center

Horrace, William C.; Oaxaca, Ronald L.

2001-01-01

States that a method for estimating gender wage gaps by industry yields estimates that vary according to arbitrary choice of omitted reference groups. Suggests alternative methods not susceptible to this problem that can be applied to other contexts, such as racial, union/nonunion, and immigrant/native wage differences. (SK)

Aircraft Flight Envelope Determination using Upset Detection and Physical Modeling Methods

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

Restructurable Controls

NASA Technical Reports Server (NTRS)

Montoya, R. J. (Compiler); Howell, W. E. (Compiler); Bundick, W. T. (Compiler); Ostroff, A. J. (Compiler); Hueschen, R. M. (Compiler); Belcastro, C. M. (Compiler)

1983-01-01

Restructurable control system theory, robust reconfiguration for high reliability and survivability for advanced aircraft, restructurable controls problem definition and research, experimentation, system identification methods applied to aircraft, a self-repairing digital flight control system, and state-of-the-art theory application are addressed.

Empirical performance of the self-controlled case series design: lessons for developing a risk identification and analysis system.

PubMed

Suchard, Marc A; Zorych, Ivan; Simpson, Shawn E; Schuemie, Martijn J; Ryan, Patrick B; Madigan, David

2013-10-01

The self-controlled case series (SCCS) offers potential as an statistical method for risk identification involving medical products from large-scale observational healthcare data. However, analytic design choices remain in encoding the longitudinal health records into the SCCS framework and its risk identification performance across real-world databases is unknown. To evaluate the performance of SCCS and its design choices as a tool for risk identification in observational healthcare data. We examined the risk identification performance of SCCS across five design choices using 399 drug-health outcome pairs in five real observational databases (four administrative claims and one electronic health records). In these databases, the pairs involve 165 positive controls and 234 negative controls. We also consider several synthetic databases with known relative risks between drug-outcome pairs. We evaluate risk identification performance through estimating the area under the receiver-operator characteristics curve (AUC) and bias and coverage probability in the synthetic examples. The SCCS achieves strong predictive performance. Twelve of the twenty health outcome-database scenarios return AUCs >0.75 across all drugs. Including all adverse events instead of just the first per patient and applying a multivariate adjustment for concomitant drug use are the most important design choices. However, the SCCS as applied here returns relative risk point-estimates biased towards the null value of 1 with low coverage probability. The SCCS recently extended to apply a multivariate adjustment for concomitant drug use offers promise as a statistical tool for risk identification in large-scale observational healthcare databases. Poor estimator calibration dampens enthusiasm, but on-going work should correct this short-coming.

Evaluation of the veracity of one work by the artist Di Cavalcanti through non-destructive techniques: XRF, imaging and brush stroke analysis

NASA Astrophysics Data System (ADS)

Kajiya, E. A. M.; Campos, P. H. O. V.; Rizzutto, M. A.; Appoloni, C. R.; Lopes, F.

2014-02-01

This paper presents systematic studies and analysis that contributed to the identification of the forgery of a work by the artist Emiliano Augusto Cavalcanti de Albuquerque e Melo, known as Di Cavalcanti. The use of several areas of expertise such as brush stroke analysis ("pinacologia"), applied physics, and art history resulted in an accurate diagnosis for ascertaining the authenticity of the work entitled "Violeiro" (1950). For this work we used non-destructive methods such as techniques of infrared, ultraviolet, visible and tangential light imaging combined with chemical analysis of the pigments by portable X-Ray Fluorescence (XRF) and graphic gesture analysis. Each applied method of analysis produced specific information that made possible the identification of materials and techniques employed and we concluded that this work is not consistent with patterns characteristic of the artist Di Cavalcanti.

Evaluation of speaker de-identification based on voice gender and age conversion

NASA Astrophysics Data System (ADS)

Přibil, Jiří; Přibilová, Anna; Matoušek, Jindřich

2018-03-01

Two basic tasks are covered in this paper. The first one consists in the design and practical testing of a new method for voice de-identification that changes the apparent age and/or gender of a speaker by multi-segmental frequency scale transformation combined with prosody modification. The second task is aimed at verification of applicability of a classifier based on Gaussian mixture models (GMM) to detect the original Czech and Slovak speakers after applied voice deidentification. The performed experiments confirm functionality of the developed gender and age conversion for all selected types of de-identification which can be objectively evaluated by the GMM-based open-set classifier. The original speaker detection accuracy was compared also for sentences uttered by German and English speakers showing language independence of the proposed method.

Target identification for small bioactive molecules: finding the needle in the haystack.

PubMed

Ziegler, Slava; Pries, Verena; Hedberg, Christian; Waldmann, Herbert

2013-03-04

Identification and confirmation of bioactive small-molecule targets is a crucial, often decisive step both in academic and pharmaceutical research. Through the development and availability of several new experimental techniques, target identification is, in principle, feasible, and the number of successful examples steadily grows. However, a generic methodology that can successfully be applied in the majority of the cases has not yet been established. Herein we summarize current methods for target identification of small molecules, primarily for a chemistry audience but also the biological community, for example, the chemist or biologist attempting to identify the target of a given bioactive compound. We describe the most frequently employed experimental approaches for target identification and provide several representative examples illustrating the state-of-the-art. Among the techniques currently available, protein affinity isolation using suitable small-molecule probes (pulldown) and subsequent mass spectrometric analysis of the isolated proteins appears to be most powerful and most frequently applied. To provide guidance for rapid entry into the field and based on our own experience we propose a typical workflow for target identification, which centers on the application of chemical proteomics as the key step to generate hypotheses for potential target proteins. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Determination of alpha-hydroxy acids in cosmetic products by high-performance liquid chromatography with a narrow-bore column.

PubMed

Nicoletti, I; Corradini, C; Cogliandro, E; Cavazza, A

1999-08-01

This paper reports the results of a study carried out to develop a simple, rapid and sensitive method for the separation, identification and quantitative measurement of alpha-hydroxy acids in commercial cosmetics using high-performance liquid chromatography (HPLC). This method is successfully applied to the simultaneous identification and quantitative determination of glycolic, lactic, malic, tartaric and citric acids employing a reversed phase narrow-bore column under isocratic condition and UV detection. The method is validated by determining the precision of replicate analyses and accuracy by analyzing samples with and without adding know amount of the alpha-hydroxy acids. The procedure is suitable for routine analyses of commercial cosmetics.

Use of system identification techniques for improving airframe finite element models using test data

NASA Technical Reports Server (NTRS)

Hanagud, Sathya V.; Zhou, Weiyu; Craig, James I.; Weston, Neil J.

1991-01-01

A method for using system identification techniques to improve airframe finite element models was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Nondestructive online testing method for friction stir welding using acoustic emission

NASA Astrophysics Data System (ADS)

Levikhina, Anastasiya

2017-12-01

The paper reviews the possibility of applying the method of acoustic emission for online monitoring of the friction stir welding process. It is shown that acoustic emission allows the detection of weld defects and their location in real time. The energy of an acoustic signal and the median frequency are suggested to be used as informative parameters. The method of calculating the median frequency with the use of a short time Fourier transform is applied for the identification of correlations between the defective weld structure and properties of the acoustic emission signals received during welding.

Health condition identification of multi-stage planetary gearboxes using a mRVM-based method

NASA Astrophysics Data System (ADS)

Lei, Yaguo; Liu, Zongyao; Wu, Xionghui; Li, Naipeng; Chen, Wu; Lin, Jing

2015-08-01

Multi-stage planetary gearboxes are widely applied in aerospace, automotive and heavy industries. Their key components, such as gears and bearings, can easily suffer from damage due to tough working environment. Health condition identification of planetary gearboxes aims to prevent accidents and save costs. This paper proposes a method based on multiclass relevance vector machine (mRVM) to identify health condition of multi-stage planetary gearboxes. In this method, a mRVM algorithm is adopted as a classifier, and two features, i.e. accumulative amplitudes of carrier orders (AACO) and energy ratio based on difference spectra (ERDS), are used as the input of the classifier to classify different health conditions of multi-stage planetary gearboxes. To test the proposed method, seven health conditions of a two-stage planetary gearbox are considered and vibration data is acquired from the planetary gearbox under different motor speeds and loading conditions. The results of three tests based on different data show that the proposed method obtains an improved identification performance and robustness compared with the existing method.

A study in the founding of applied behavior analysis through its publications.

PubMed

Morris, Edward K; Altus, Deborah E; Smith, Nathaniel G

2013-01-01

This article reports a study of the founding of applied behavior analysis through its publications. Our methods included hand searches of sources (e.g., journals, reference lists), search terms (i.e., early, applied, behavioral, research, literature), inclusion criteria (e.g., the field's applied dimension), and (d) challenges to their face and content validity. Our results were 36 articles published between 1959 and 1967 that we organized into 4 groups: 12 in 3 programs of research and 24 others. Our discussion addresses (a) limitations in our method (e.g., the completeness of our search), (b) challenges to the validity of our methods and results (e.g., convergent validity), and (c) priority claims about the field's founding. We conclude that the claims are irresolvable because identification of the founding publications depends significantly on methods and because the field's founding was an evolutionary process. We close with suggestions for future research.

A Study in the Founding of Applied Behavior Analysis Through Its Publications

PubMed Central

Morris, Edward K.; Altus, Deborah E.; Smith, Nathaniel G.

2013-01-01

This article reports a study of the founding of applied behavior analysis through its publications. Our methods included hand searches of sources (e.g., journals, reference lists), search terms (i.e., early, applied, behavioral, research, literature), inclusion criteria (e.g., the field's applied dimension), and (d) challenges to their face and content validity. Our results were 36 articles published between 1959 and 1967 that we organized into 4 groups: 12 in 3 programs of research and 24 others. Our discussion addresses (a) limitations in our method (e.g., the completeness of our search), (b) challenges to the validity of our methods and results (e.g., convergent validity), and (c) priority claims about the field's founding. We conclude that the claims are irresolvable because identification of the founding publications depends significantly on methods and because the field's founding was an evolutionary process. We close with suggestions for future research. PMID:25729133

DNA Barcoding of Recently Diverged Species: Relative Performance of Matching Methods

PubMed Central

van Velzen, Robin; Weitschek, Emanuel; Felici, Giovanni; Bakker, Freek T.

2012-01-01

Recently diverged species are challenging for identification, yet they are frequently of special interest scientifically as well as from a regulatory perspective. DNA barcoding has proven instrumental in species identification, especially in insects and vertebrates, but for the identification of recently diverged species it has been reported to be problematic in some cases. Problems are mostly due to incomplete lineage sorting or simply lack of a ‘barcode gap’ and probably related to large effective population size and/or low mutation rate. Our objective was to compare six methods in their ability to correctly identify recently diverged species with DNA barcodes: neighbor joining and parsimony (both tree-based), nearest neighbor and BLAST (similarity-based), and the diagnostic methods DNA-BAR, and BLOG. We analyzed simulated data assuming three different effective population sizes as well as three selected empirical data sets from published studies. Results show, as expected, that success rates are significantly lower for recently diverged species (∼75%) than for older species (∼97%) (P<0.00001). Similarity-based and diagnostic methods significantly outperform tree-based methods, when applied to simulated DNA barcode data (P<0.00001). The diagnostic method BLOG had highest correct query identification rate based on simulated (86.2%) as well as empirical data (93.1%), indicating that it is a consistently better method overall. Another advantage of BLOG is that it offers species-level information that can be used outside the realm of DNA barcoding, for instance in species description or molecular detection assays. Even though we can confirm that identification success based on DNA barcoding is generally high in our data, recently diverged species remain difficult to identify. Nevertheless, our results contribute to improved solutions for their accurate identification. PMID:22272356

DNA barcoding of recently diverged species: relative performance of matching methods.

PubMed

van Velzen, Robin; Weitschek, Emanuel; Felici, Giovanni; Bakker, Freek T

2012-01-01

Recently diverged species are challenging for identification, yet they are frequently of special interest scientifically as well as from a regulatory perspective. DNA barcoding has proven instrumental in species identification, especially in insects and vertebrates, but for the identification of recently diverged species it has been reported to be problematic in some cases. Problems are mostly due to incomplete lineage sorting or simply lack of a 'barcode gap' and probably related to large effective population size and/or low mutation rate. Our objective was to compare six methods in their ability to correctly identify recently diverged species with DNA barcodes: neighbor joining and parsimony (both tree-based), nearest neighbor and BLAST (similarity-based), and the diagnostic methods DNA-BAR, and BLOG. We analyzed simulated data assuming three different effective population sizes as well as three selected empirical data sets from published studies. Results show, as expected, that success rates are significantly lower for recently diverged species (∼75%) than for older species (∼97%) (P<0.00001). Similarity-based and diagnostic methods significantly outperform tree-based methods, when applied to simulated DNA barcode data (P<0.00001). The diagnostic method BLOG had highest correct query identification rate based on simulated (86.2%) as well as empirical data (93.1%), indicating that it is a consistently better method overall. Another advantage of BLOG is that it offers species-level information that can be used outside the realm of DNA barcoding, for instance in species description or molecular detection assays. Even though we can confirm that identification success based on DNA barcoding is generally high in our data, recently diverged species remain difficult to identify. Nevertheless, our results contribute to improved solutions for their accurate identification.

Report of the Federation of European Laboratory Animal Science Associations Working Group on animal identification.

PubMed

Dahlborn, K; Bugnon, P; Nevalainen, T; Raspa, M; Verbost, P; Spangenberg, E

2013-01-01

The primary aim of this report is to assist scientists in selecting more reliable/suitable identification (ID) methods for their studies. This is especially true for genetically altered (GA) animals where individual identification is strictly necessary to link samples, research design and genotype. The aim of this Federation of European Laboratory Animal Science Associations working group was to provide an update of the methods used to identify rodents in different situations and to assess their implications for animal welfare. ID procedures are an indispensable prerequisite for conducting good science but the degree of invasiveness differs between the different methods; therefore, one needs to make a good ethical evaluation of the method chosen. Based on the scientific literature the advantages and disadvantages of various methods have been presented comprehensively and this report is intended as a practical guide for researchers. New upcoming methods have been included next to the traditional techniques. Ideally, an ID method should provide reliable identification, be technically easy to apply and not inflict adverse effects on animals while taking into account the type of research. There is no gold standard method because each situation is unique; however, more studies are needed to better evaluate ID systems and the desirable introduction of new and modern approaches will need to be assessed by detailed scientific evaluation.

Identification of MAPK Substrates Using Quantitative Phosphoproteomics.

PubMed

Zhang, Tong; Schneider, Jacqueline D; Zhu, Ning; Chen, Sixue

2017-01-01

Activation of mitogen-activated protein kinases (MAPKs) under diverse biotic and abiotic factors and identification of an array of downstream MAPK target proteins are hot topics in plant signal transduction. Through interactions with a plethora of substrate proteins, MAPK cascades regulate many physiological processes in the course of plant growth, development, and response to environmental factors. Identification and quantification of potential MAPK substrates are essential, but have been technically challenging. With the recent advancement in phosphoproteomics, here we describe a method that couples metal dioxide for phosphopeptide enrichment with tandem mass tags (TMT) mass spectrometry (MS) for large-scale MAPK substrate identification and quantification. We have applied this method to a transient expression system carrying a wild type (WT) and a constitutive active (CA) version of a MAPK. This combination of genetically engineered MAPKs and phosphoproteomics provides a high-throughput, unbiased analysis of MAPK-triggered phosphorylation changes on the proteome scale. Therefore, it is a robust method for identifying potential MAPK substrates and should be applicable in the study of other kinase cascades in plants as well as in other organisms.

Village Building Identification Based on Ensemble Convolutional Neural Networks

PubMed Central

Guo, Zhiling; Chen, Qi; Xu, Yongwei; Shibasaki, Ryosuke; Shao, Xiaowei

2017-01-01

In this study, we present the Ensemble Convolutional Neural Network (ECNN), an elaborate CNN frame formulated based on ensembling state-of-the-art CNN models, to identify village buildings from open high-resolution remote sensing (HRRS) images. First, to optimize and mine the capability of CNN for village mapping and to ensure compatibility with our classification targets, a few state-of-the-art models were carefully optimized and enhanced based on a series of rigorous analyses and evaluations. Second, rather than directly implementing building identification by using these models, we exploited most of their advantages by ensembling their feature extractor parts into a stronger model called ECNN based on the multiscale feature learning method. Finally, the generated ECNN was applied to a pixel-level classification frame to implement object identification. The proposed method can serve as a viable tool for village building identification with high accuracy and efficiency. The experimental results obtained from the test area in Savannakhet province, Laos, prove that the proposed ECNN model significantly outperforms existing methods, improving overall accuracy from 96.64% to 99.26%, and kappa from 0.57 to 0.86. PMID:29084154

Molecular analysis of single oocyst of Eimeria by whole genome amplification (WGA) based nested PCR.

PubMed

Wang, Yunzhou; Tao, Geru; Cui, Yujuan; Lv, Qiyao; Xie, Li; Li, Yuan; Suo, Xun; Qin, Yinghe; Xiao, Lihua; Liu, Xianyong

2014-09-01

PCR-based molecular tools are widely used for the identification and characterization of protozoa. Here we report the molecular analysis of Eimeria species using combined methods of whole genome amplification (WGA) and nested PCR. Single oocyst of Eimeria stiedai or Eimeriamedia was directly used for random amplification of the genomic DNA with either primer extension preamplification (PEP) or multiple displacement amplification (MDA), and then the WGA product was used as template in nested PCR with species-specific primers for ITS-1, 18S rDNA and 23S rDNA of E. stiedai and E. media. WGA-based PCR was successful for the amplification of these genes from single oocyst. For the species identification of single oocyst isolated from mixed E. stiedai or E. media, the results from WGA-based PCR were exactly in accordance with those from morphological identification, suggesting the availability of this method in molecular analysis of eimerian parasites at the single oocyst level. WGA-based PCR method can also be applied for the identification and genetic characterization of other protists. Copyright © 2014 Elsevier Inc. All rights reserved.

Force Enhancement Packages for Countering Nuclear Threats in the 2022-2027 Time Frame

DTIC Science & Technology

2015-09-01

characterization methods . • Apply proper radioisotope identification techniques. c. A one-week CNT operations exercise at Fort Belvoir, Virginia. Team members...on experiments to seek better methods , holding active teaching until later. The team expects that better methods would involve collection using...conduct more effective wide-area searches than those commonly employed by civil law enforcement agencies. The IDA team suggests that better methods

Differential equations as a tool for community identification.

PubMed

Krawczyk, Małgorzata J

2008-06-01

We consider the task of identification of a cluster structure in random networks. The results of two methods are presented: (i) the Newman algorithm [M. E. J. Newman and M. Girvan, Phys. Rev. E 69, 026113 (2004)]; and (ii) our method based on differential equations. A series of computer experiments is performed to check if in applying these methods we are able to determine the structure of the network. The trial networks consist initially of well-defined clusters and are disturbed by introducing noise into their connectivity matrices. Further, we show that an improvement of the previous version of our method is possible by an appropriate choice of the threshold parameter beta . With this change, the results obtained by the two methods above are similar, and our method works better, for all the computer experiments we have done.

Infective Endocarditis: Identification of Catalase-Negative, Gram-Positive Cocci from Blood Cultures by Partial 16S rRNA Gene Analysis and by Vitek 2 Examination.

PubMed

Abdul-Redha, Rawaa Jalil; Kemp, Michael; Bangsborg, Jette M; Arpi, Magnus; Christensen, Jens Jørgen

2010-01-01

Streptococci, enterococci and Streptococcus-like bacteria are frequent etiologic agents of infective endocarditis and correct species identification can be a laboratory challenge. Viridans streptococci (VS) not seldomly cause contamination of blood cultures. Vitek 2 and partial sequencing of the 16S rRNA gene were applied in order to compare the results of both methods. STRAINS ORIGINATED FROM TWO GROUPS OF PATIENTS: 149 strains from patients with infective endocarditis and 181 strains assessed as blood culture contaminants. Of the 330 strains, based on partial 16S rRNA gene sequencing results, 251 (76%) were VS strains, 10 (3%) were pyogenic streptococcal strains, 54 (16%) were E. faecalis strains and 15 (5%) strains belonged to a group of miscellaneous catalase-negative, Gram-positive cocci. Among VS strains, respectively, 220 (87,6%) and 31 (12,3%) obtained agreeing and non-agreeing identifications with the two methods with respect to allocation to the same VS group. Non-agreeing species identification mostly occurred among strains in the contaminant group, while for endocarditis strains notably fewer disagreeing results were observed.Only 67 of 150 strains in the mitis group strains obtained identical species identifications by the two methods. Most VS strains belonging to the groups of salivarius, anginosus, and mutans obtained agreeing species identifications with the two methods, while this only was the case for 13 of the 21 bovis strains. Pyogenic strains (n=10), Enterococcus faecalis strains (n=54) and a miscellaneous group of catalase-negative, Gram-positive cocci (n=15) seemed well identified by both methods, except that disagreements in identifications in the miscellaneous group of strains occurred for 6 of 15 strains.

Diagnostic Value of the Impairment of Olfaction in Parkinson's Disease

PubMed Central

Casjens, Swaantje; Eckert, Angelika; Woitalla, Dirk; Ellrichmann, Gisa; Turewicz, Michael; Stephan, Christian; Eisenacher, Martin; May, Caroline; Meyer, Helmut E.; Brüning, Thomas; Pesch, Beate

2013-01-01

Background Olfactory impairment is increasingly recognized as an early symptom in the development of Parkinson's disease. Testing olfactory function is a non-invasive method but can be time-consuming which restricts its application in clinical settings and epidemiological studies. Here, we investigate odor identification as a supportive diagnostic tool for Parkinson's disease and estimate the performance of odor subsets to allow a more rapid testing of olfactory impairment. Methodology/Principal Findings Odor identification was assessed with 16 Sniffin' sticks in 148 Parkinson patients and 148 healthy controls. Risks of olfactory impairment were estimated with proportional odds models. Random forests were applied to classify Parkinson and non-Parkinson patients. Parkinson patients were rarely normosmic (identification of more than 12 odors; 16.8%) and identified on average seven odors whereas the reference group identified 12 odors and showed a higher prevalence of normosmy (31.1%). Parkinson patients with rigidity dominance had a twofold greater prevalence of olfactory impairment. Disease severity was associated with impairment of odor identification (per score point of the Hoehn and Yahr rating OR 1.87, 95% CI 1.26–2.77). Age-related impairment of olfaction showed a steeper gradient in Parkinson patients. Coffee, peppermint, and anise showed the largest difference in odor identification between Parkinson patients and controls. Random forests estimated a misclassification rate of 22.4% when comparing Parkinson patients with healthy controls using all 16 odors. A similar rate (23.8%) was observed when only the three aforementioned odors were applied. Conclusions/Significance Our findings indicate that testing odor identification can be a supportive diagnostic tool for Parkinson's disease. The application of only three odors performed well in discriminating Parkinson patients from controls, which can facilitate a wider application of this method as a point-of-care test. PMID:23696904

Modal parameter identification based on combining transmissibility functions and blind source separation techniques

NASA Astrophysics Data System (ADS)

Araújo, Iván Gómez; Sánchez, Jesús Antonio García; Andersen, Palle

2018-05-01

Transmissibility-based operational modal analysis is a recent and alternative approach used to identify the modal parameters of structures under operational conditions. This approach is advantageous compared with traditional operational modal analysis because it does not make any assumptions about the excitation spectrum (i.e., white noise with a flat spectrum). However, common methodologies do not include a procedure to extract closely spaced modes with low signal-to-noise ratios. This issue is relevant when considering that engineering structures generally have closely spaced modes and that their measured responses present high levels of noise. Therefore, to overcome these problems, a new combined method for modal parameter identification is proposed in this work. The proposed method combines blind source separation (BSS) techniques and transmissibility-based methods. Here, BSS techniques were used to recover source signals, and transmissibility-based methods were applied to estimate modal information from the recovered source signals. To achieve this combination, a new method to define a transmissibility function was proposed. The suggested transmissibility function is based on the relationship between the power spectral density (PSD) of mixed signals and the PSD of signals from a single source. The numerical responses of a truss structure with high levels of added noise and very closely spaced modes were processed using the proposed combined method to evaluate its ability to identify modal parameters in these conditions. Colored and white noise excitations were used for the numerical example. The proposed combined method was also used to evaluate the modal parameters of an experimental test on a structure containing closely spaced modes. The results showed that the proposed combined method is capable of identifying very closely spaced modes in the presence of noise and, thus, may be potentially applied to improve the identification of damping ratios.

Numerical Methods of Parameter Identification for Problems Arising in Elasticity.

DTIC Science & Technology

1982-06-01

Theorem 2.21 remains essentially unchanged by the inclusion of this new term . We now turn to a concrete realization of the approximate identification...cost if it had been accomplished under contract or if it had been done in-house in terms of manpower and/or dollars? ( ) a. MAN-YEARS ( ) b. $ 4...eigenfunction) state approximations were applied to a class of hyperbolic and parabolic equations, and also used in [7 ], where spline-based state

Support vector machine based classification of fast Fourier transform spectroscopy of proteins

NASA Astrophysics Data System (ADS)

Lazarevic, Aleksandar; Pokrajac, Dragoljub; Marcano, Aristides; Melikechi, Noureddine

2009-02-01

Fast Fourier transform spectroscopy has proved to be a powerful method for study of the secondary structure of proteins since peak positions and their relative amplitude are affected by the number of hydrogen bridges that sustain this secondary structure. However, to our best knowledge, the method has not been used yet for identification of proteins within a complex matrix like a blood sample. The principal reason is the apparent similarity of protein infrared spectra with actual differences usually masked by the solvent contribution and other interactions. In this paper, we propose a novel machine learning based method that uses protein spectra for classification and identification of such proteins within a given sample. The proposed method uses principal component analysis (PCA) to identify most important linear combinations of original spectral components and then employs support vector machine (SVM) classification model applied on such identified combinations to categorize proteins into one of given groups. Our experiments have been performed on the set of four different proteins, namely: Bovine Serum Albumin, Leptin, Insulin-like Growth Factor 2 and Osteopontin. Our proposed method of applying principal component analysis along with support vector machines exhibits excellent classification accuracy when identifying proteins using their infrared spectra.

Identification of driving network of cellular differentiation from single sample time course gene expression data

NASA Astrophysics Data System (ADS)

Chen, Ye; Wolanyk, Nathaniel; Ilker, Tunc; Gao, Shouguo; Wang, Xujing

Methods developed based on bifurcation theory have demonstrated their potential in driving network identification for complex human diseases, including the work by Chen, et al. Recently bifurcation theory has been successfully applied to model cellular differentiation. However, there one often faces a technical challenge in driving network prediction: time course cellular differentiation study often only contains one sample at each time point, while driving network prediction typically require multiple samples at each time point to infer the variation and interaction structures of candidate genes for the driving network. In this study, we investigate several methods to identify both the critical time point and the driving network through examination of how each time point affects the autocorrelation and phase locking. We apply these methods to a high-throughput sequencing (RNA-Seq) dataset of 42 subsets of thymocytes and mature peripheral T cells at multiple time points during their differentiation (GSE48138 from GEO). We compare the predicted driving genes with known transcription regulators of cellular differentiation. We will discuss the advantages and limitations of our proposed methods, as well as potential further improvements of our methods.

Identification of an EMS-induced causal mutation in a gene required for boron-mediated root development by low-coverage genome re-sequencing in Arabidopsis

PubMed Central

Tabata, Ryo; Kamiya, Takehiro; Shigenobu, Shuji; Yamaguchi, Katsushi; Yamada, Masashi; Hasebe, Mitsuyasu; Fujiwara, Toru; Sawa, Shinichiro

2013-01-01

Next-generation sequencing (NGS) technologies enable the rapid production of an enormous quantity of sequence data. These powerful new technologies allow the identification of mutations by whole-genome sequencing. However, most reported NGS-based mapping methods, which are based on bulked segregant analysis, are costly and laborious. To address these limitations, we designed a versatile NGS-based mapping method that consists of a combination of low- to medium-coverage multiplex SOLiD (Sequencing by Oligonucleotide Ligation and Detection) and classical genetic rough mapping. Using only low to medium coverage reduces the SOLiD sequencing costs and, since just 10 to 20 mutant F2 plants are required for rough mapping, the operation is simple enough to handle in a laboratory with limited space and funding. As a proof of principle, we successfully applied this method to identify the CTR1, which is involved in boron-mediated root development, from among a population of high boron requiring Arabidopsis thaliana mutants. Our work demonstrates that this NGS-based mapping method is a moderately priced and versatile method that can readily be applied to other model organisms. PMID:23104114

Application of culture-dependent and culture-independent methods for the identification of Lactobacillus kefiranofaciens in microbial consortia present in kefir grains.

PubMed

Hamet, Maria Fernanda; Londero, Alejandra; Medrano, Micaela; Vercammen, Elisabeth; Van Hoorde, Koenraad; Garrote, Graciela L; Huys, Geert; Vandamme, Peter; Abraham, Analía G

2013-12-01

The biological and technological characteristics of kefiran as well as its importance in grain integrity led us to analyze the microbial kefir grain consortium with focus on Lactobacillus kefiranofaciens. The presence of L. kefiranofaciens in the nine kefir grains studied was demonstrated by denaturing gradient gel electrophoresis. By culture dependent methods applying a methodology focused on the search of this species, 22 isolates with typical morphology were obtained and identified applying a combination of SDS-PAGE of whole cell proteins, (GTG)5-PCR and sequence analysis of the housekeeping gene encoding the α-subunit of bacterial phenylalanyl-tRNA synthase (pheS). This polyphasic approach allowed the reliable identification of 11 L. kefiranofaciens, 5 Lactobacillus paracasei, 4 Lactobacillus kefiri and 2 Lactobacillus parakefiri isolates. Isolated L. kefiranofaciens strains produced polysaccharide in strain-dependent concentrations and EPS produced by them also differed in the degree of polymerization. The isolation and accurate identification of L. kefiranofaciens is relevant taking into account the important role of this microorganism in the grain ecosystem as well as its potential application as starter in food fermentations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Using a binaural biomimetic array to identify bottom objects ensonified by echolocating dolphins

USGS Publications Warehouse

Heiweg, D.A.; Moore, P.W.; Martin, S.W.; Dankiewicz, L.A.

2006-01-01

The development of a unique dolphin biomimetic sonar produced data that were used to study signal processing methods for object identification. Echoes from four metallic objects proud on the bottom, and a substrate-only condition, were generated by bottlenose dolphins trained to ensonify the targets in very shallow water. Using the two-element ('binaural') receive array, object echo spectra were collected and submitted for identification to four neural network architectures. Identification accuracy was evaluated over two receive array configurations, and five signal processing schemes. The four neural networks included backpropagation, learning vector quantization, genetic learning and probabilistic network architectures. The processing schemes included four methods that capitalized on the binaural data, plus a monaural benchmark process. All the schemes resulted in above-chance identification accuracy when applied to learning vector quantization and backpropagation. Beam-forming or concatenation of spectra from both receive elements outperformed the monaural benchmark, with higher sensitivity and lower bias. Ultimately, best object identification performance was achieved by the learning vector quantization network supplied with beam-formed data. The advantages of multi-element signal processing for object identification are clearly demonstrated in this development of a first-ever dolphin biomimetic sonar. ?? 2006 IOP Publishing Ltd.

Reliability of System Identification Techniques to Assess Standing Balance in Healthy Elderly

PubMed Central

Maier, Andrea B.; Aarts, Ronald G. K. M.; van Gerven, Joop M. A.; Arendzen, J. Hans; Schouten, Alfred C.; Meskers, Carel G. M.; van der Kooij, Herman

2016-01-01

Objectives System identification techniques have the potential to assess the contribution of the underlying systems involved in standing balance by applying well-known disturbances. We investigated the reliability of standing balance parameters obtained with multivariate closed loop system identification techniques. Methods In twelve healthy elderly balance tests were performed twice a day during three days. Body sway was measured during two minutes of standing with eyes closed and the Balance test Room (BalRoom) was used to apply four disturbances simultaneously: two sensory disturbances, to the proprioceptive and the visual system, and two mechanical disturbances applied at the leg and trunk segment. Using system identification techniques, sensitivity functions of the sensory disturbances and the neuromuscular controller were estimated. Based on the generalizability theory (G theory), systematic errors and sources of variability were assessed using linear mixed models and reliability was assessed by computing indexes of dependability (ID), standard error of measurement (SEM) and minimal detectable change (MDC). Results A systematic error was found between the first and second trial in the sensitivity functions. No systematic error was found in the neuromuscular controller and body sway. The reliability of 15 of 25 parameters and body sway were moderate to excellent when the results of two trials on three days were averaged. To reach an excellent reliability on one day in 7 out of 25 parameters, it was predicted that at least seven trials must be averaged. Conclusion This study shows that system identification techniques are a promising method to assess the underlying systems involved in standing balance in elderly. However, most of the parameters do not appear to be reliable unless a large number of trials are collected across multiple days. To reach an excellent reliability in one third of the parameters, a training session for participants is needed and at least seven trials of two minutes must be performed on one day. PMID:26953694

A NEW SW-846 METHOD: MICRO-LIQUID CHROMATOGRAPHY-ELECTROSPRAY/ION TRAP MASS SPECTROMETRY AS APPLIED TO THE DETECTION AND IDENTIFICATION OF ORGANOTINS - METHOD 8323

EPA Science Inventory

There is a growing body of evidence that humans and other animals (terrestrial and marine) are being exposed continually to potentially harmful species of organotins. One possible route of environmental exposure in the U.S. to organotins (specifically dibutyltin and triphenyltin)...

Line identification studies using traditional techniques and wavelength coincidence statistics

NASA Technical Reports Server (NTRS)

Cowley, Charles R.; Adelman, Saul J.

1990-01-01

Traditional line identification techniques result in the assignment of individual lines to an atomic or ionic species. These methods may be supplemented by wavelength coincidence statistics (WCS). The strength and weakness of these methods are discussed using spectra of a number of normal and peculiar B and A stars that have been studied independently by both methods. The present results support the overall findings of some earlier studies. WCS would be most useful in a first survey, before traditional methods have been applied. WCS can quickly make a global search for all species and in this way may enable identifications of an unexpected spectrum that could easily be omitted entirely from a traditional study. This is illustrated by O I. WCS is a subject to well known weakness of any statistical technique, for example, a predictable number of spurious results are to be expected. The danger of small number statistics are illustrated. WCS is at its best relative to traditional methods in finding a line-rich atomic species that is only weakly present in a complicated stellar spectrum.

Testing efficacy of distance and tree-based methods for DNA barcoding of grasses (Poaceae tribe Poeae) in Australia

PubMed Central

Walsh, Neville G.; Cantrill, David J.; Holmes, Gareth D.; Murphy, Daniel J.

2017-01-01

In Australia, Poaceae tribe Poeae are represented by 19 genera and 99 species, including economically and environmentally important native and introduced pasture grasses [e.g. Poa (Tussock-grasses) and Lolium (Ryegrasses)]. We used this tribe, which are well characterised in regards to morphological diversity and evolutionary relationships, to test the efficacy of DNA barcoding methods. A reference library was generated that included 93.9% of species in Australia (408 individuals, x¯ = 3.7 individuals per species). Molecular data were generated for official plant barcoding markers (rbcL, matK) and the nuclear ribosomal internal transcribed spacer (ITS) region. We investigated accuracy of specimen identifications using distance- (nearest neighbour, best-close match, and threshold identification) and tree-based (maximum likelihood, Bayesian inference) methods and applied species discovery methods (automatic barcode gap discovery, Poisson tree processes) based on molecular data to assess congruence with recognised species. Across all methods, success rate for specimen identification of genera was high (87.5–99.5%) and of species was low (25.6–44.6%). Distance- and tree-based methods were equally ineffective in providing accurate identifications for specimens to species rank (26.1–44.6% and 25.6–31.3%, respectively). The ITS marker achieved the highest success rate for specimen identification at both generic and species ranks across the majority of methods. For distance-based analyses the best-close match method provided the greatest accuracy for identification of individuals with a high percentage of “correct” (97.6%) and a low percentage of “incorrect” (0.3%) generic identifications, based on the ITS marker. For tribe Poeae, and likely for other grass lineages, sequence data in the standard DNA barcode markers are not variable enough for accurate identification of specimens to species rank. For recently diverged grass species similar challenges are encountered in the application of genetic and morphological data to species delimitations, with taxonomic signal limited by extensive infra-specific variation and shared polymorphisms among species in both data types. PMID:29084279

Testing efficacy of distance and tree-based methods for DNA barcoding of grasses (Poaceae tribe Poeae) in Australia.

PubMed

Birch, Joanne L; Walsh, Neville G; Cantrill, David J; Holmes, Gareth D; Murphy, Daniel J

2017-01-01

In Australia, Poaceae tribe Poeae are represented by 19 genera and 99 species, including economically and environmentally important native and introduced pasture grasses [e.g. Poa (Tussock-grasses) and Lolium (Ryegrasses)]. We used this tribe, which are well characterised in regards to morphological diversity and evolutionary relationships, to test the efficacy of DNA barcoding methods. A reference library was generated that included 93.9% of species in Australia (408 individuals, [Formula: see text] = 3.7 individuals per species). Molecular data were generated for official plant barcoding markers (rbcL, matK) and the nuclear ribosomal internal transcribed spacer (ITS) region. We investigated accuracy of specimen identifications using distance- (nearest neighbour, best-close match, and threshold identification) and tree-based (maximum likelihood, Bayesian inference) methods and applied species discovery methods (automatic barcode gap discovery, Poisson tree processes) based on molecular data to assess congruence with recognised species. Across all methods, success rate for specimen identification of genera was high (87.5-99.5%) and of species was low (25.6-44.6%). Distance- and tree-based methods were equally ineffective in providing accurate identifications for specimens to species rank (26.1-44.6% and 25.6-31.3%, respectively). The ITS marker achieved the highest success rate for specimen identification at both generic and species ranks across the majority of methods. For distance-based analyses the best-close match method provided the greatest accuracy for identification of individuals with a high percentage of "correct" (97.6%) and a low percentage of "incorrect" (0.3%) generic identifications, based on the ITS marker. For tribe Poeae, and likely for other grass lineages, sequence data in the standard DNA barcode markers are not variable enough for accurate identification of specimens to species rank. For recently diverged grass species similar challenges are encountered in the application of genetic and morphological data to species delimitations, with taxonomic signal limited by extensive infra-specific variation and shared polymorphisms among species in both data types.

Literature Reference for Cryptosporidium spp. (Applied and Environmental Microbiology. 2007. 73(13): 4218–4225)

EPA Pesticide Factsheets

Procedures are described for analysis of drinking water samples and may be adapted for assessment of solid, particulate, aerosol, and liquid samples. The method uses real-time PCR for identification of Cryptosporidium spp.

Optimization and Development of a Human Scent Collection Method

DTIC Science & Technology

2007-06-04

19. Schoon, G. A. A., Scent Identification Lineups by Dogs (Canis familiaris): Experimental Design and Forensic Application. Applied Animal...Parker, Lloyd R., Morgan, Stephen L., Deming, Stanley N., Sequential Simplex Optimization. Chemometrics Series, ed. S.D. Brown. 1991, Boca Raton

A Novel Degradation Identification Method for Wind Turbine Pitch System

NASA Astrophysics Data System (ADS)

Guo, Hui-Dong

2018-04-01

It’s difficult for traditional threshold value method to identify degradation of operating equipment accurately. An novel degradation evaluation method suitable for wind turbine condition maintenance strategy implementation was proposed in this paper. Based on the analysis of typical variable-speed pitch-to-feather control principle and monitoring parameters for pitch system, a multi input multi output (MIMO) regression model was applied to pitch system, where wind speed, power generation regarding as input parameters, wheel rotation speed, pitch angle and motor driving currency for three blades as output parameters. Then, the difference between the on-line measurement and the calculated value from the MIMO regression model applying least square support vector machines (LSSVM) method was defined as the Observed Vector of the system. The Gaussian mixture model (GMM) was applied to fitting the distribution of the multi dimension Observed Vectors. Applying the model established, the Degradation Index was calculated using the SCADA data of a wind turbine damaged its pitch bearing retainer and rolling body, which illustrated the feasibility of the provided method.

Pollutant source identification model for water pollution incidents in small straight rivers based on genetic algorithm

NASA Astrophysics Data System (ADS)

Zhang, Shou-ping; Xin, Xiao-kang

2017-07-01

Identification of pollutant sources for river pollution incidents is an important and difficult task in the emergency rescue, and an intelligent optimization method can effectively compensate for the weakness of traditional methods. An intelligent model for pollutant source identification has been established using the basic genetic algorithm (BGA) as an optimization search tool and applying an analytic solution formula of one-dimensional unsteady water quality equation to construct the objective function. Experimental tests show that the identification model is effective and efficient: the model can accurately figure out the pollutant amounts or positions no matter single pollution source or multiple sources. Especially when the population size of BGA is set as 10, the computing results are sound agree with analytic results for a single source amount and position identification, the relative errors are no more than 5 %. For cases of multi-point sources and multi-variable, there are some errors in computing results for the reasons that there exist many possible combinations of the pollution sources. But, with the help of previous experience to narrow the search scope, the relative errors of the identification results are less than 5 %, which proves the established source identification model can be used to direct emergency responses.

[Identification characters of leaf morphological and venation pattern of Houttuynia cordata with its confused herb Gymnotheca chinensis].

PubMed

Lu, Hai-Lin; Guo, Min; Liao, Yue-Kui; Huang, Ding-Ying; Huang, Chun-Ni; Wu, Xiao-Chen; He, Bao-Zuo

2012-11-01

To study the identification characters of Houttuynia cordata and its confused herb Gymnotheca chinensis and establish an identification method. LMVP (leaf morphological-venation pattern for identification Chinese herbs), and QAERM (quantitatively analyze and evaluate reliability for the method of identification Chinese herbs) were applied for the study. Both venations were brochidodromous-acrodromous and arising from the mid-petiole or the upper section of petiole. The main characteristic of the leaf of Houttuynia cordata: surface with small gray-white stoma protuberances; Ligulate process of stipule-petiole sheath were clear; Primary veins 7 or 5; The innermost pair of primary vein closed up the top of the sinus at blade base or above sinus, and the section of closed vein was straight; Emitted a smell of fish when fresh leaf was kneaded into pieces. The main feature of the leaf of Gymnotheca chinensis: no small gray-white stoma protuberances; Ligulate process of stipule-petiole sheath were not clear; Primary veins 5; The innermost pair of primary vein closed into the sinus at blade base, and the section of closed vein was slightly curve; No smell of fish. With the mentioned key differences, the both plants could be successfully identified from each other. The accuracy of identification results (AC) was 100%, the repeatability of identification results: agreement rate for observation (ARO) was 100% and Kappa value was 1.00. The established method is simple, rapid, economic and reliable.

System-wide identification of wild-type SUMO-2 conjugation sites

PubMed Central

Hendriks, Ivo A.; D'Souza, Rochelle C.; Chang, Jer-Gung; Mann, Matthias; Vertegaal, Alfred C. O.

2015-01-01

SUMOylation is a reversible post-translational modification (PTM) regulating all nuclear processes. Identification of SUMOylation sites by mass spectrometry (MS) has been hampered by bulky tryptic fragments, which thus far necessitated the use of mutated SUMO. Here we present a SUMO-specific protease-based methodology which circumvents this problem, dubbed Protease-Reliant Identification of SUMO Modification (PRISM). PRISM allows for detection of SUMOylated proteins as well as identification of specific sites of SUMOylation while using wild-type SUMO. The method is generic and could be widely applied to study lysine PTMs. We employ PRISM in combination with high-resolution MS to identify SUMOylation sites from HeLa cells under standard growth conditions and in response to heat shock. We identified 751 wild-type SUMOylation sites on endogenous proteins, including 200 dynamic SUMO sites in response to heat shock. Thus, we have developed a method capable of quantitatively studying wild-type mammalian SUMO at the site-specific and system-wide level. PMID:26073453

Comparison of μ-ATR-FTIR spectroscopy and py-GCMS as identification tools for microplastic particles and fibers isolated from river sediments.

PubMed

Käppler, Andrea; Fischer, Marten; Scholz-Böttcher, Barbara M; Oberbeckmann, Sonja; Labrenz, Matthias; Fischer, Dieter; Eichhorn, Klaus-Jochen; Voit, Brigitte

2018-06-16

In recent years, many studies on the analysis of microplastics (MP) in environmental samples have been published. These studies are hardly comparable due to different sampling, sample preparation, as well as identification and quantification techniques. Here, MP identification is one of the crucial pitfalls. Visual identification approaches using morphological criteria alone often lead to significant errors, being especially true for MP fibers. Reliable, chemical structure-based identification methods are indispensable. In this context, the frequently used vibrational spectroscopic techniques but also thermoanalytical methods are established. However, no critical comparison of these fundamentally different approaches has ever been carried out with regard to analyzing MP in environmental samples. In this blind study, we investigated 27 single MP particles and fibers of unknown material isolated from river sediments. Successively micro-attenuated total reflection Fourier transform infrared spectroscopy (μ-ATR-FTIR) and pyrolysis gas chromatography-mass spectrometry (py-GCMS) in combination with thermochemolysis were applied. Both methods differentiated between plastic vs. non-plastic in the same way in 26 cases, with 19 particles and fibers (22 after re-evaluation) identified as the same polymer type. To illustrate the different approaches and emphasize the complementarity of their information content, we exemplarily provide a detailed comparison of four particles and three fibers and a critical discussion of advantages and disadvantages of both methods.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

Comparison of outlier identification methods in hospital surgical quality improvement programs.

PubMed

Bilimoria, Karl Y; Cohen, Mark E; Merkow, Ryan P; Wang, Xue; Bentrem, David J; Ingraham, Angela M; Richards, Karen; Hall, Bruce L; Ko, Clifford Y

2010-10-01

Surgeons and hospitals are being increasingly assessed by third parties regarding surgical quality and outcomes, and much of this information is reported publicly. Our objective was to compare various methods used to classify hospitals as outliers in established surgical quality assessment programs by applying each approach to a single data set. Using American College of Surgeons National Surgical Quality Improvement Program data (7/2008-6/2009), hospital risk-adjusted 30-day morbidity and mortality were assessed for general surgery at 231 hospitals (cases = 217,630) and for colorectal surgery at 109 hospitals (cases = 17,251). The number of outliers (poor performers) identified using different methods and criteria were compared. The overall morbidity was 10.3% for general surgery and 25.3% for colorectal surgery. The mortality was 1.6% for general surgery and 4.0% for colorectal surgery. Programs used different methods (logistic regression, hierarchical modeling, partitioning) and criteria (P < 0.01, P < 0.05, P < 0.10) to identify outliers. Depending on outlier identification methods and criteria employed, when each approach was applied to this single dataset, the number of outliers ranged from 7 to 57 hospitals for general surgery morbidity, 1 to 57 hospitals for general surgery mortality, 4 to 27 hospitals for colorectal morbidity, and 0 to 27 hospitals for colorectal mortality. There was considerable variation in the number of outliers identified using different detection approaches. Quality programs seem to be utilizing outlier identification methods contrary to what might be expected, thus they should justify their methodology based on the intent of the program (i.e., quality improvement vs. reimbursement). Surgeons and hospitals should be aware of variability in methods used to assess their performance as these outlier designations will likely have referral and reimbursement consequences.

Use of system identification techniques for improving airframe finite element models using test data

NASA Technical Reports Server (NTRS)

Hanagud, Sathya V.; Zhou, Weiyu; Craig, James I.; Weston, Neil J.

1993-01-01

A method for using system identification techniques to improve airframe finite element models using test data was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in the total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all of the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Force Enhancement Packages for Countering Nuclear Threats in the 2022-2027 Time Frame: Final Report

DTIC Science & Technology

2015-09-01

survey, and area characterization methods . • Apply proper radioisotope identification techniques. A-10 c. A one-week CNT operations exercise at Fort...focus on experiments to seek better iv methods , holding active teaching until later. The team expects that better methods would involve collection... methods likely will involve collection by multiple ISR sensors and on-the-ground investigators, with only limited use of radiation detectors. The

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

NASA Technical Reports Server (NTRS)

Pelletier, R. E.; Griffin, R. H.

1985-01-01

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

An adaptive optimal control for smart structures based on the subspace tracking identification technique

NASA Astrophysics Data System (ADS)

Ripamonti, Francesco; Resta, Ferruccio; Borroni, Massimo; Cazzulani, Gabriele

2014-04-01

A new method for the real-time identification of mechanical system modal parameters is used in order to design different adaptive control logics aiming to reduce the vibrations in a carbon fiber plate smart structure. It is instrumented with three piezoelectric actuators, three accelerometers and three strain gauges. The real-time identification is based on a recursive subspace tracking algorithm whose outputs are elaborated by an ARMA model. A statistical approach is finally applied to choose the modal parameter correct values. These are given in input to model-based control logics such as a gain scheduling and an adaptive LQR control.

Identification of new meteorite, Mihonoseki (L), from broken fragments in Japan

NASA Technical Reports Server (NTRS)

Miura, Y.; Noma, Y.

1993-01-01

New meteorite of Mihonoseki fallen in Shimane-ken was identified by fine broken pieces by using an energy-dispersive scanning electron microprobe analyzer. It shows fusion-crust (i.e. Fe-Si melt), meteoritic minerals (kamacite, taenite, troilite, amorphous plagioclase etc.) and chrondrule with clear glassy rim. Mineralogical, and petrological data of several fine grains suggest that broken fragments of Mihonoseki are L3/4 chondritic meteorite which is the first identification in a Japanese fallen meteorite. The prompt identification method of meteorite-fragments will be applied to the next lunar, Martian and asteroid explorations, as well as meteorite falls on the terrestrial surface.

Identification of cutting force coefficients in machining process considering cutter vibration

NASA Astrophysics Data System (ADS)

Yao, Qi; Luo, Ming; Zhang, Dinghua; Wu, Baohai

2018-03-01

Among current cutting force models, cutting force coefficients still are the foundation of predicting calculation combined with consideration of geometry engagement variation, equipment characteristics, material properties and so on. Attached with unimpeachable significance, the traditional and some novel identification methods of cutting force coefficient are still faced with trouble, including repeated onerous work, over ideal measuring condition, variation of value due to material divergence, interference from measuring units. To utilize the large amount of data from real manufacturing section, enlarge data sources and enrich cutting data base for former prediction task, a novel identification method is proposed by considering stiffness properties of the cutter-holder-spindle system in this paper. According to previously proposed studies, the direct result of cutter vibration is the form of dynamic undeformed chip thickness. This fluctuation is considered in two stages of this investigation. Firstly, a cutting force model combined with cutter vibration is established in detailed way. Then, on the foundation of modeling, a novel identification method is developed, in which the dynamic undeformed chip thickness could be obtained by using collected data. In a carefully designed experiment procedure, the reliability of model is validated by comparing predicted and measured results. Under different cutting condition and cutter stiffness, data is collected for the justification of identification method. The results showed divergence in calculated coefficients is acceptable confirming the possibility of accomplishing targets by applying this new method. In discussion, the potential directions of improvement are proposed.

DNA identification of human remains in Disaster Victim Identification (DVI): An efficient sampling method for muscle, bone, bone marrow and teeth.

PubMed

de Boer, Hans H; Maat, George J R; Kadarmo, D Aji; Widodo, Putut T; Kloosterman, Ate D; Kal, Arnoud J

2018-06-04

In disaster victim identification (DVI), DNA profiling is considered to be one of the most reliable and efficient means to identify bodies or separated body parts. This requires a post mortem DNA sample, and an ante mortem DNA sample of the presumed victim or their biological relative(s). Usually the collection of an adequate ante mortem sample is technically simple, but the acquisition of a good quality post mortem sample under unfavourable DVI circumstances is complicated due to the variable degree of preservation of the human remains and the high risk of DNA (cross) contamination. This paper provides the community with an efficient method to collect post-mortem DNA samples from muscle, bone, bone marrow and teeth, with a minimal risk of contamination. Our method has been applied in a recent, challenging DVI operation (i.e. the identification of the 298 victims of the MH17 airplane crash in 2014). 98,2% of the collected PM samples provided the DVI team with highly informative DNA genotyping results without the risk of contamination and consequent mistyping the victim's DNA. Moreover, the method is easy, cheap and quick. This paper provides the DVI community with a step-wise instructions with recommendations for the type of tissue to be sampled and the site of excision (preferably the upper leg). Although initially designed for DVI purposes, the method is also suited for the identification of individual victims. Copyright © 2018 Elsevier B.V. All rights reserved.

Motion estimation of subcellular structures from fluorescence microscopy images.

PubMed

Vallmitjana, A; Civera-Tregon, A; Hoenicka, J; Palau, F; Benitez, R

2017-07-01

We present an automatic image processing framework to study moving intracellular structures from live cell fluorescence microscopy. The system includes the identification of static and dynamic structures from time-lapse images using data clustering as well as the identification of the trajectory of moving objects with a probabilistic tracking algorithm. The method has been successfully applied to study mitochondrial movement in neurons. The approach provides excellent performance under different experimental conditions and is robust to common sources of noise including experimental, molecular and biological fluctuations.

Prospective performance evaluation of selected common virtual screening tools. Case study: Cyclooxygenase (COX) 1 and 2.

PubMed

Kaserer, Teresa; Temml, Veronika; Kutil, Zsofia; Vanek, Tomas; Landa, Premysl; Schuster, Daniela

2015-01-01

Computational methods can be applied in drug development for the identification of novel lead candidates, but also for the prediction of pharmacokinetic properties and potential adverse effects, thereby aiding to prioritize and identify the most promising compounds. In principle, several techniques are available for this purpose, however, which one is the most suitable for a specific research objective still requires further investigation. Within this study, the performance of several programs, representing common virtual screening methods, was compared in a prospective manner. First, we selected top-ranked virtual screening hits from the three methods pharmacophore modeling, shape-based modeling, and docking. For comparison, these hits were then additionally predicted by external pharmacophore- and 2D similarity-based bioactivity profiling tools. Subsequently, the biological activities of the selected hits were assessed in vitro, which allowed for evaluating and comparing the prospective performance of the applied tools. Although all methods performed well, considerable differences were observed concerning hit rates, true positive and true negative hits, and hitlist composition. Our results suggest that a rational selection of the applied method represents a powerful strategy to maximize the success of a research project, tightly linked to its aims. We employed cyclooxygenase as application example, however, the focus of this study lied on highlighting the differences in the virtual screening tool performances and not in the identification of novel COX-inhibitors. Copyright © 2015 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

Potential of DNA barcoding for detecting quarantine fungi.

PubMed

Gao, Ruifang; Zhang, Guiming

2013-11-01

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

Semi-quantitative MALDI-TOF for antimicrobial susceptibility testing in Staphylococcus aureus.

PubMed

Maxson, Tucker; Taylor-Howell, Cheryl L; Minogue, Timothy D

2017-01-01

Antibiotic resistant bacterial infections are a significant problem in the healthcare setting, in many cases requiring the rapid administration of appropriate and effective antibiotic therapy. Diagnostic assays capable of quickly and accurately determining the pathogen resistance profile are therefore crucial to initiate or modify care. Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) is a standard method for species identification in many clinical microbiology laboratories and is well positioned to be applied towards antimicrobial susceptibility testing. One recently reported approach utilizes semi-quantitative MALDI-TOF MS for growth rate analysis to provide a resistance profile independent of resistance mechanism. This method was previously successfully applied to Gram-negative pathogens and mycobacteria; here, we evaluated this method with the Gram-positive pathogen Staphylococcus aureus. Specifically, we used 35 strains of S. aureus and four antibiotics to optimize and test the assay, resulting in an overall accuracy rate of 95%. Application of the optimized assay also successfully determined susceptibility from mock blood cultures, allowing both species identification and resistance determination for all four antibiotics within 3 hours of blood culture positivity.

DNA-BASED METHODS FOR MONITORING INVASIVE SPECIES: A REVIEW AND PROSPECTUS

EPA Science Inventory

The recent explosion of interest in DNA-based tools for species identification has prompted widespread speculation on the future availability of inexpensive, rapid and accurate means of identifying specimens and assessing biodiversity. One applied field that may benefit dramatic...

Forensic Odontology: Automatic Identification of Persons Comparing Antemortem and Postmortem Panoramic Radiographs Using Computer Vision.

PubMed

Heinrich, Andreas; Güttler, Felix; Wendt, Sebastian; Schenkl, Sebastian; Hubig, Michael; Wagner, Rebecca; Mall, Gita; Teichgräber, Ulf

2018-06-18

 In forensic odontology the comparison between antemortem and postmortem panoramic radiographs (PRs) is a reliable method for person identification. The purpose of this study was to improve and automate identification of unknown people by comparison between antemortem and postmortem PR using computer vision.  The study includes 43 467 PRs from 24 545 patients (46 % females/54 % males). All PRs were filtered and evaluated with Matlab R2014b including the toolboxes image processing and computer vision system. The matching process used the SURF feature to find the corresponding points between two PRs (unknown person and database entry) out of the whole database.  From 40 randomly selected persons, 34 persons (85 %) could be reliably identified by corresponding PR matching points between an already existing scan in the database and the most recent PR. The systematic matching yielded a maximum of 259 points for a successful identification between two different PRs of the same person and a maximum of 12 corresponding matching points for other non-identical persons in the database. Hence 12 matching points are the threshold for reliable assignment.  Operating with an automatic PR system and computer vision could be a successful and reliable tool for identification purposes. The applied method distinguishes itself by virtue of its fast and reliable identification of persons by PR. This Identification method is suitable even if dental characteristics were removed or added in the past. The system seems to be robust for large amounts of data.   · Computer vision allows an automated antemortem and postmortem comparison of panoramic radiographs (PRs) for person identification.. · The present method is able to find identical matching partners among huge datasets (big data) in a short computing time.. · The identification method is suitable even if dental characteristics were removed or added.. · Heinrich A, Güttler F, Wendt S et al. Forensic Odontology: Automatic Identification of Persons Comparing Antemortem and Postmortem Panoramic Radiographs Using Computer Vision. Fortschr Röntgenstr 2018; DOI: 10.1055/a-0632-4744. © Georg Thieme Verlag KG Stuttgart · New York.

A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems.

PubMed

Kazemi, Mahdi; Arefi, Mohammad Mehdi

2017-03-01

In this paper, an online identification algorithm is presented for nonlinear systems in the presence of output colored noise. The proposed method is based on extended recursive least squares (ERLS) algorithm, where the identified system is in polynomial Wiener form. To this end, an unknown intermediate signal is estimated by using an inner iterative algorithm. The iterative recursive algorithm adaptively modifies the vector of parameters of the presented Wiener model when the system parameters vary. In addition, to increase the robustness of the proposed method against variations, a robust RLS algorithm is applied to the model. Simulation results are provided to show the effectiveness of the proposed approach. Results confirm that the proposed method has fast convergence rate with robust characteristics, which increases the efficiency of the proposed model and identification approach. For instance, the FIT criterion will be achieved 92% in CSTR process where about 400 data is used. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A New High-Throughput Approach to Genotype Ancient Human Gastrointestinal Parasites.

PubMed

Côté, Nathalie M L; Daligault, Julien; Pruvost, Mélanie; Bennett, E Andrew; Gorgé, Olivier; Guimaraes, Silvia; Capelli, Nicolas; Le Bailly, Matthieu; Geigl, Eva-Maria; Grange, Thierry

2016-01-01

Human gastrointestinal parasites are good indicators for hygienic conditions and health status of past and present individuals and communities. While microscopic analysis of eggs in sediments of archeological sites often allows their taxonomic identification, this method is rarely effective at the species level, and requires both the survival of intact eggs and their proper identification. Genotyping via PCR-based approaches has the potential to achieve a precise species-level taxonomic determination. However, so far it has mostly been applied to individual eggs isolated from archeological samples. To increase the throughput and taxonomic accuracy, as well as reduce costs of genotyping methods, we adapted a PCR-based approach coupled with next-generation sequencing to perform precise taxonomic identification of parasitic helminths directly from archeological sediments. Our study of twenty-five 100 to 7,200 year-old archeological samples proved this to be a powerful, reliable and efficient approach for species determination even in the absence of preserved eggs, either as a stand-alone method or as a complement to microscopic studies.

Summary of research in applied mathematics, numerical analysis, and computer sciences

NASA Technical Reports Server (NTRS)

1986-01-01

The major categories of current ICASE research programs addressed include: numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; control and parameter identification problems, with emphasis on effective numerical methods; computational problems in engineering and physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and computer systems and software, especially vector and parallel computers.

Hierarchical relaxation methods for multispectral pixel classification as applied to target identification

NASA Astrophysics Data System (ADS)

Cohen, E. A., Jr.

1985-02-01

This report provides insights into the approaches toward image modeling as applied to target detection. The approach is that of examining the energy in prescribed wave-bands which emanate from a target and correlating the emissions. Typically, one might be looking at two or three infrared bands, possibly together with several visual bands. The target is segmented, using both first and second order modeling, into a set of interesting components and these components are correlated so as to enhance the classification process. A Markov-type model is used to provide an a priori assessment of the spatial relationships among critical parts of the target, and a stochastic model using the output of an initial probabilistic labeling is invoked. The tradeoff between this stochastic model and the Markov model is then optimized to yield a best labeling for identification purposes. In an identification of friend or foe (IFF) context, this methodology could be of interest, for it provides the ingredients for such a higher level of understanding.

The Effect of Achievement Test Selection on Identification of Learning Disabilities within a Patterns of Strengths and Weaknesses Framework

PubMed Central

Miciak, Jeremy; Taylor, Pat; Denton, Carolyn A.; Fletcher, Jack M.

2014-01-01

Purpose Few empirical investigations have evaluated learning disabilities (LD) identification methods based on a pattern of cognitive strengths and weaknesses (PSW). This study investigated the reliability of LD classification decisions of the concordance/discordance method (C/DM) across different psychoeducational assessment batteries. Methods C/DM criteria were applied to assessment data from 177 second grade students based on two psychoeducational assessment batteries. The achievement tests were different, but were highly correlated and measured the same latent construct. Resulting LD identifications were then evaluated for agreement across batteries on LD status and the academic domain of eligibility. Results The two batteries identified a similar number of participants as having LD (80 and 74). However, indices of agreement for classification decisions were low (kappa = .29), especially for percent positive agreement (62%). The two batteries demonstrated agreement on the academic domain of eligibility for only 25 participants. Conclusions Cognitive discrepancy frameworks for LD identification are inherently unstable because of imperfect reliability and validity at the observed level. Methods premised on identifying a PSW profile may never achieve high reliability because of these underlying psychometric factors. An alternative is to directly assess academic skills to identify students in need of intervention. PMID:25243467

An application of the geophysical methods and ALS DTM for the identification of the geological structure in the Kraśnik region - Lublin Upland, Poland

NASA Astrophysics Data System (ADS)

Kamiński, Mirosław

2017-11-01

The purpose of the study was the assessment of the viability of selected geophysical methods and the Airborne Laser Scanning (ALS) for the identification and interpretation of the geological structure. The studied area is covered with a dense forest. For this reason, the ALS numerical terrain model was applied for the analysis of the topography. Three geophysical methods were used: gravimetric, in the form of a semi-detailed gravimetric photograph, Vertical Electrical Sounding (VES), and Electrical Resistivity Tomography (ERT). The numerical terrain model enabled the identification of Jurassic limestone outcrops and interpretation of the directions of the faults network. The geological interpretation of the digitally processed gravimetric data enabled the determination of the spatial orientation of the synclines and anticlines axes and of the course directions of main faults. Vertical Electrical Sounding carried along the section line perpendicular to the Gościeradów anticline axis enabled the interpretation of the lithology of this structure and identification of its complex tectonic structure. The shallow geophysical surveys using the ERT method enabled the estimation of the thickness of Quaternary formations deposited unconformably on the highly eroded Jurassic limestone outcrop. The lithology of Quaternary, Cretaceous and Jurassic rocks was also interpreted.

Single-step inline hydroxyapatite enrichment facilitates identification and quantitation of phosphopeptides from mass-limited proteomes with MudPIT

PubMed Central

Fonslow, Bryan R.; Niessen, Sherry M.; Singh, Meha; Wong, Catherine C.; Xu, Tao; Carvalho, Paulo C.; Choi, Jeong; Park, Sung Kyu; Yates, John R.

2012-01-01

Herein we report the characterization and optimization of single-step inline enrichment of phosphopeptides directly from small amounts of whole cell and tissue lysates (100 – 500 μg) using a hydroxyapatite (HAP) microcolumn and Multidimensional Protein Identification Technology (MudPIT). In comparison to a triplicate HILIC-IMAC phosphopeptide enrichment study, ~80% of the phosphopeptides identified using HAP-MudPIT were unique. Similarly, analysis of the consensus phosphorylation motifs between the two enrichment methods illustrates the complementarity of calcium-and iron-based enrichment methods and the higher sensitivity and selectivity of HAP-MudPIT for acidic motifs. We demonstrate how the identification of more multiply phosphorylated peptides from HAP-MudPIT can be used to quantify phosphorylation cooperativity. Through optimization of HAP-MudPIT on a whole cell lysate we routinely achieved identification and quantification of ca. 1000 phosphopeptides from a ~1 hr enrichment and 12 hr MudPIT analysis on small quantities of material. Finally, we applied this optimized method to identify phosphorylation sites from a mass-limited mouse brain region, the amygdala (200 – 500 μg), identifying up to 4000 phosphopeptides per run. PMID:22509746

Advances in identification and validation of protein targets of natural products without chemical modification.

PubMed

Chang, J; Kim, Y; Kwon, H J

2016-05-04

Covering: up to February 2016Identification of the target proteins of natural products is pivotal to understanding the mechanisms of action to develop natural products for use as molecular probes and potential therapeutic drugs. Affinity chromatography of immobilized natural products has been conventionally used to identify target proteins, and has yielded good results. However, this method has limitations, in that labeling or tagging for immobilization and affinity purification often result in reduced or altered activity of the natural product. New strategies have recently been developed and applied to identify the target proteins of natural products and synthetic small molecules without chemical modification of the natural product. These direct and indirect methods for target identification of label-free natural products include drug affinity responsive target stability (DARTS), stability of proteins from rates of oxidation (SPROX), cellular thermal shift assay (CETSA), thermal proteome profiling (TPP), and bioinformatics-based analysis of connectivity. This review focuses on and reports case studies of the latest advances in target protein identification methods for label-free natural products. The integration of newly developed technologies will provide new insights and highlight the value of natural products for use as biological probes and new drug candidates.

Free-decay time-domain modal identification for large space structures

NASA Technical Reports Server (NTRS)

Kim, Hyoung M.; Vanhorn, David A.; Doiron, Harold H.

1992-01-01

Concept definition studies for the Modal Identification Experiment (MIE), a proposed space flight experiment for the Space Station Freedom (SSF), have demonstrated advantages and compatibility of free-decay time-domain modal identification techniques with the on-orbit operational constraints of large space structures. Since practical experience with modal identification using actual free-decay responses of large space structures is very limited, several numerical and test data reduction studies were conducted. Major issues and solutions were addressed, including closely-spaced modes, wide frequency range of interest, data acquisition errors, sampling delay, excitation limitations, nonlinearities, and unknown disturbances during free-decay data acquisition. The data processing strategies developed in these studies were applied to numerical simulations of the MIE, test data from a deployable truss, and launch vehicle flight data. Results of these studies indicate free-decay time-domain modal identification methods can provide accurate modal parameters necessary to characterize the structural dynamics of large space structures.

TEMPORAL VARIABILITY OF ENTEROCOCCI SPECIES IN STREAMS IMPACTED BY CATTLE FECAL CONTAMINATION

EPA Science Inventory

Temporal variability in the gastrointestinal flora of animals impacting water resources with fecal material can be one of the factors producing low source identification rates when applying microbial source tracking (MST) methods. Our objective is to identify and compare the temp...

Mapping functional connectivity

Treesearch

Peter Vogt; Joseph R. Ferrari; Todd R. Lookingbill; Robert H. Gardner; Kurt H. Riitters; Katarzyna Ostapowicz

2009-01-01

An objective and reliable assessment of wildlife movement is important in theoretical and applied ecology. The identification and mapping of landscape elements that may enhance functional connectivity is usually a subjective process based on visual interpretations of species movement patterns. New methods based on mathematical morphology provide a generic, flexible,...

40 CFR 796.2750 - Sediment and soil adsorption isotherm.

Code of Federal Regulations, 2014 CFR

2014-07-01

... are highly reproducible. The test provides excellent quantitative data readily amenable to statistical... combination of methods suitable for the identification and quantitative detection of the parent test chemical... quantitative analysis of the parent chemical. (3) Amount of parent test chemical applied, the amount recovered...

40 CFR 796.2750 - Sediment and soil adsorption isotherm.

Code of Federal Regulations, 2013 CFR

2013-07-01

... highly reproducible. The test provides excellent quantitative data readily amenable to statistical... combination of methods suitable for the identification and quantitative detection of the parent test chemical... quantitative analysis of the parent chemical. (3) Amount of parent test chemical applied, the amount recovered...

40 CFR 796.2750 - Sediment and soil adsorption isotherm.

Code of Federal Regulations, 2012 CFR

2012-07-01

... highly reproducible. The test provides excellent quantitative data readily amenable to statistical... combination of methods suitable for the identification and quantitative detection of the parent test chemical... quantitative analysis of the parent chemical. (3) Amount of parent test chemical applied, the amount recovered...

Rapid diagnostic tests apply for pediatric infections at outpatient clinic setting.

PubMed

Ushijima, Hiroshi; Thongprachum, Aksara; Tran, Dinh Nguyen; Fujimoto, Tsuguto; Hanaoka, Nozomu; Okitsu, Shoko; Takanashi, Sayaka; Mizuguchi, Masashi; Hayakawa, Satoshi

2015-01-01

Early identification of the etiology of infection is beneficial. Most infections are treated as outpatients. However, facilities for rapid diagnosis are not available in clinic settings. We applied Immunochromatography (IC) and Loop-mediated Isothermal Amplification (LAMP) methods to rapidly diagnose pathogens among 31 children with respiratory infection and 12 with gastroenteritis at a clinic in Saitama prefecture, Japan. Pathogens were then screened by multiplex conventional and real-time PCRs and bacterial culture. Respiratory pathogens were found in 64.5%. Despite the narrow spectrum, rapid tests identified pathogens in 28.6% of cases with a high agreement rate of 89.3% with PCR. Gastroenteritis pathogens were found in 66.7%. E. coli was positive in 3 cases and all were negative for verotoxin by LAMP. The agreement rate of IC and PCR assay was high, 100%. IC and LAMP are reliable and suitable methods in limited-resource settings for early pathogenic identification, which will help appropriate management, avoid unnecessary intervention, and cost saving.

Digital Signal Processing Based on a Clustering Algorithm for Ir/Au TES Microcalorimeter

NASA Astrophysics Data System (ADS)

Zen, N.; Kunieda, Y.; Takahashi, H.; Hiramoto, K.; Nakazawa, M.; Fukuda, D.; Ukibe, M.; Ohkubo, M.

2006-02-01

In recent years, cryogenic microcalorimeters using their superconducting transition edge have been under development for possible application to the research for astronomical X-ray observations. To improve the energy resolution of superconducting transition edge sensors (TES), several correction methods have been developed. Among them, a clustering method based on digital signal processing has recently been proposed. In this paper, we applied the clustering method to Ir/Au bilayer TES. This method resulted in almost a 10% improvement in the energy resolution. Conversely, from the point of view of imaging X-ray spectroscopy, we applied the clustering method to pixellated Ir/Au-TES devices. We will thus show how a clustering method which sorts signals by their shapes is also useful for position identification

Improved CEEMDAN-wavelet transform de-noising method and its application in well logging noise reduction

NASA Astrophysics Data System (ADS)

Zhang, Jingxia; Guo, Yinghai; Shen, Yulin; Zhao, Difei; Li, Mi

2018-06-01

The use of geophysical logging data to identify lithology is an important groundwork in logging interpretation. Inevitably, noise is mixed in during data collection due to the equipment and other external factors and this will affect the further lithological identification and other logging interpretation. Therefore, to get a more accurate lithological identification it is necessary to adopt de-noising methods. In this study, a new de-noising method, namely improved complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)-wavelet transform, is proposed, which integrates the superiorities of improved CEEMDAN and wavelet transform. Improved CEEMDAN, an effective self-adaptive multi-scale analysis method, is used to decompose non-stationary signals as the logging data to obtain the intrinsic mode function (IMF) of N different scales and one residual. Moreover, one self-adaptive scale selection method is used to determine the reconstruction scale k. Simultaneously, given the possible frequency aliasing problem between adjacent IMFs, a wavelet transform threshold de-noising method is used to reduce the noise of the (k-1)th IMF. Subsequently, the de-noised logging data are reconstructed by the de-noised (k-1)th IMF and the remaining low-frequency IMFs and the residual. Finally, empirical mode decomposition, improved CEEMDAN, wavelet transform and the proposed method are applied for analysis of the simulation and the actual data. Results show diverse performance of these de-noising methods with regard to accuracy for lithological identification. Compared with the other methods, the proposed method has the best self-adaptability and accuracy in lithological identification.

Superestructuras en el universo: caracterización e identificación en el catálgo SDSS-DR7

NASA Astrophysics Data System (ADS)

Luparello, H. E.; Lares, M.; García Lambas, D.; Padilla, N.

Superclusters are the largest gravitationally bound systems in the Universe. These structures are not presently virialized, so the application of theoreti- cal arguments in their identification is not straightforward. Luparello et al., (2011) present an identification method and establish the values of the pa- rameters in order to ensure that superstructures in the present Universe will evolve into virialized structures. In this work we define and characterize the largest structures in the Universe, in the framework of the cosmological model CDM. We briefly describe the Future Virialized Structures (FVS) identification method applied to the seventh data release of the Sloan Dig- ital Sky Survey (SDSS-DR7, Abazajian et al., 2009) in the redshift range 0.04 < z < 0.12 and present the main properties of the FVS catalogue. FULL TEXT IN SPANISH

Application of SERS spectroscopy to the identification of (3,4-methylenedioxy)amphetamine in forensic samples utilizing matrix stabilized silver halides.

PubMed

Sägmüller, B; Schwarze, B; Brehm, G; Schneider, S

2001-11-01

A method based on surface-enhanced Raman scattering (SERS) spectroscopy was developed to meet the need for the reliable and rapid identification of illicit drugs such as the 'designer drug' XTC, preferably to increase the security of legal certificates. A matrix stabilized silver halide dispersion on a microtiter plate is used as the SERS-active substrate, providing an easy to use system for sample preparation and probing by means of a Raman microscope. The potential of the method is demonstrated by applying it to the identification of the psychoactive ingredients of drug containing tablets which were confiscated by the local police at techno-music events. The samples of interest were 26 different brands of XTC tablets and several pieces of evidence (powders) containing amphetamine. For reference, we show SERS and Raman spectra of pristine amphetamine, methamphetamine, 3,4-methylenedioxyamphetamine, 3,4-methylenedioxymethamphetamine (MDMA) and 3,4-methylenedioxyethamphetamine.

Space-Based Identification of Archaeological Illegal Excavations and a New Automatic Method for Looting Feature Extraction in Desert Areas

NASA Astrophysics Data System (ADS)

Lasaponara, Rosa; Masini, Nicola

2018-06-01

The identification and quantification of disturbance of archaeological sites has been generally approached by visual inspection of optical aerial or satellite pictures. In this paper, we briefly summarize the state of the art of the traditionally satellite-based approaches for looting identification and propose a new automatic method for archaeological looting feature extraction approach (ALFEA). It is based on three steps: the enhancement using spatial autocorrelation, unsupervised classification, and segmentation. ALFEA has been applied to Google Earth images of two test areas, selected in desert environs in Syria (Dura Europos), and in Peru (Cahuachi-Nasca). The reliability of ALFEA was assessed through field surveys in Peru and visual inspection for the Syrian case study. Results from the evaluation procedure showed satisfactory performance from both of the two analysed test cases with a rate of success higher than 90%.

Rapid label-free identification of Klebsiella pneumoniae antibiotic resistant strains by the drop-coating deposition surface-enhanced Raman scattering method

NASA Astrophysics Data System (ADS)

Cheong, Youjin; Kim, Young Jin; Kang, Heeyoon; Choi, Samjin; Lee, Hee Joo

2017-08-01

Although many methodologies have been developed to identify unknown bacteria, bacterial identification in clinical microbiology remains a complex and time-consuming procedure. To address this problem, we developed a label-free method for rapidly identifying clinically relevant multilocus sequencing typing-verified quinolone-resistant Klebsiella pneumoniae strains. We also applied the method to identify three strains from colony samples, ATCC70063 (control), ST11 and ST15; these are the prevalent quinolone-resistant K. pneumoniae strains in East Asia. The colonies were identified using a drop-coating deposition surface-enhanced Raman scattering (DCD-SERS) procedure coupled with a multivariate statistical method. Our workflow exhibited an enhancement factor of 11.3 × 106 to Raman intensities, high reproducibility (relative standard deviation of 7.4%), and a sensitive limit of detection (100 pM rhodamine 6G), with a correlation coefficient of 0.98. All quinolone-resistant K. pneumoniae strains showed similar spectral Raman shifts (high correlations) regardless of bacterial type, as well as different Raman vibrational modes compared to Escherichia coli strains. Our proposed DCD-SERS procedure coupled with the multivariate statistics-based identification method achieved excellent performance in discriminating similar microbes from one another and also in subtyping of K. pneumoniae strains. Therefore, our label-free DCD-SERS procedure coupled with the computational decision supporting method is a potentially useful method for the rapid identification of clinically relevant K. pneumoniae strains.

Evaluation of three sample preparation methods for the direct identification of bacteria in positive blood cultures by MALDI-TOF.

PubMed

Tanner, Hannah; Evans, Jason T; Gossain, Savita; Hussain, Abid

2017-01-18

Patient mortality is significantly reduced by rapid identification of bacteria from sterile sites. MALDI-TOF can identify bacteria directly from positive blood cultures and multiple sample preparation methods are available. We evaluated three sample preparation methods and two MALDI-TOF score cut-off values. Positive blood culture bottles with organisms present in Gram stains were prospectively analysed by MALDI-TOF. Three lysis reagents (Saponin, SDS, and SepsiTyper lysis bufer) were applied to each positive culture followed by centrifugation, washing and protein extraction steps. Methods were compared using the McNemar test and 16S rDNA sequencing was used to assess discordant results. In 144 monomicrobial cultures, using ≥2.000 as the cut-off value, species level identifications were obtained from 69/144 (48%) samples using Saponin, 86/144 (60%) using SDS, and 91/144 (63%) using SepsiTyper. The difference between SDS and SepsiTyper was not statistically significant (P = 0.228). Differences between Saponin and the other two reagents were significant (P < 0.01). Using ≥1.700 plus top three results matching as the cut-off value, species level identifications were obtained from 100/144 (69%) samples using Saponin, 103/144 (72%) using SDS, and 106/144 (74%) using SepsiTyper and there was no statistical difference between the methods. No true discordances between culture and direct MALDI-TOF identification were observed in monomicrobial cultures. In 32 polymicrobial cultures, MALDI-TOF identified one organism in 34-75% of samples depending on the method. This study demonstrates two inexpensive in-house detergent lysis methods are non-inferior to a commercial kit for analysis of positive blood cultures by direct MALDI-TOF in a clinical diagnostic microbiology laboratory.

Improved bacterial identification directly from urine samples with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

PubMed

Kitagawa, Koichi; Shigemura, Katsumi; Onuma, Ken-Ichiro; Nishida, Masako; Fujiwara, Mayu; Kobayashi, Saori; Yamasaki, Mika; Nakamura, Tatsuya; Yamamichi, Fukashi; Shirakawa, Toshiro; Tokimatsu, Issei; Fujisawa, Masato

2018-03-01

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) contributes to rapid identification of pathogens in the clinic but has not yet performed especially well for Gram-positive cocci (GPC) causing complicated urinary tract infection (UTI). The goal of this study was to investigate the possible clinical use of MALDI-TOF MS as a rapid method for bacterial identification directly from urine in complicated UTI. MALDI-TOF MS was applied to urine samples gathered from 142 suspected complicated UTI patients in 2015-2017. We modified the standard procedure (Method 1) for sample preparation by adding an initial 10 minutes of ultrasonication followed by centrifugation at 500 g for 1 minutes to remove debris such as epithelial cells and leukocytes from the urine (Method 2). In 133 urine culture-positive bacteria, the rate of corresponded with urine culture in GPC by MALDI-TOF MS in urine with standard sample preparation (Method 1) was 16.7%, but the modified sample preparation (Method 2) significantly improved that rate to 52.2% (P=.045). Method 2 also improved the identification accuracy for Gram-negative rods (GNR) from 77.1% to 94.2% (P=.022). The modified Method 2 significantly improved the average MALDI score from 1.408±0.153 to 2.166±0.045 (P=.000) for GPC and slightly improved the score from 2.107±0.061 to 2.164±0.037 for GNR. The modified sample preparation for MALDI-TOF MS can improve identification accuracy for complicated UTI causative bacteria. This simple modification offers a rapid and accurate routine diagnosis for UTI, and may possibly be a substitute for urine cultures. © 2017 Wiley Periodicals, Inc.

Fundamental Rotorcraft Acoustic Modeling From Experiments (FRAME)

NASA Technical Reports Server (NTRS)

Greenwood, Eric

2011-01-01

A new methodology is developed for the construction of helicopter source noise models for use in mission planning tools from experimental measurements of helicopter external noise radiation. The models are constructed by employing a parameter identification method to an assumed analytical model of the rotor harmonic noise sources. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. The method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor harmonic noise, allowing accurate estimates of the dominant rotorcraft noise sources to be made for operating conditions based on a small number of measurements taken at different operating conditions. The ability of this method to estimate changes in noise radiation due to changes in ambient conditions is also demonstrated.

A Galerkin discretisation-based identification for parameters in nonlinear mechanical systems

NASA Astrophysics Data System (ADS)

Liu, Zuolin; Xu, Jian

2018-04-01

In the paper, a new parameter identification method is proposed for mechanical systems. Based on the idea of Galerkin finite-element method, the displacement over time history is approximated by piecewise linear functions, and the second-order terms in model equation are eliminated by integrating by parts. In this way, the lost function of integration form is derived. Being different with the existing methods, the lost function actually is a quadratic sum of integration over the whole time history. Then for linear or nonlinear systems, the optimisation of the lost function can be applied with traditional least-squares algorithm or the iterative one, respectively. Such method could be used to effectively identify parameters in linear and arbitrary nonlinear mechanical systems. Simulation results show that even under the condition of sparse data or low sampling frequency, this method could still guarantee high accuracy in identifying linear and nonlinear parameters.

Development of sampling method and chromatographic analysis of volatile organic compounds emitted from human skin.

PubMed

Grabowska-Polanowska, Beata; Miarka, Przemysław; Skowron, Monika; Sułowicz, Joanna; Wojtyna, Katarzyna; Moskal, Karolina; Śliwka, Ireneusz

2017-10-01

The studies on volatile organic compounds emitted from skin are an interest for chemists, biologists and physicians due to their role in development of different scientific areas, including medical diagnostics, forensic medicine and the perfume design. This paper presents a proposal of two sampling methods applied to skin odor collection: the first one uses a bag of cellulose film, the second one, using cellulose sachets filled with active carbon. Volatile organic compounds were adsorbed on carbon sorbent, removed via thermal desorption and analyzed using gas chromatograph with mass spectrometer. The first sampling method allowed identification of more compounds (52) comparing to the second one (30). Quantitative analyses for acetone, butanal, pentanal and hexanal were done. The skin odor sampling method using a bag of cellulose film, allowed the identification of many more compounds when compared with the method using a sachet filled with active carbon.

Evaluating current automatic de-identification methods with Veteran's health administration clinical documents.

PubMed

Ferrández, Oscar; South, Brett R; Shen, Shuying; Friedlin, F Jeffrey; Samore, Matthew H; Meystre, Stéphane M

2012-07-27

The increased use and adoption of Electronic Health Records (EHR) causes a tremendous growth in digital information useful for clinicians, researchers and many other operational purposes. However, this information is rich in Protected Health Information (PHI), which severely restricts its access and possible uses. A number of investigators have developed methods for automatically de-identifying EHR documents by removing PHI, as specified in the Health Insurance Portability and Accountability Act "Safe Harbor" method.This study focuses on the evaluation of existing automated text de-identification methods and tools, as applied to Veterans Health Administration (VHA) clinical documents, to assess which methods perform better with each category of PHI found in our clinical notes; and when new methods are needed to improve performance. We installed and evaluated five text de-identification systems "out-of-the-box" using a corpus of VHA clinical documents. The systems based on machine learning methods were trained with the 2006 i2b2 de-identification corpora and evaluated with our VHA corpus, and also evaluated with a ten-fold cross-validation experiment using our VHA corpus. We counted exact, partial, and fully contained matches with reference annotations, considering each PHI type separately, or only one unique 'PHI' category. Performance of the systems was assessed using recall (equivalent to sensitivity) and precision (equivalent to positive predictive value) metrics, as well as the F(2)-measure. Overall, systems based on rules and pattern matching achieved better recall, and precision was always better with systems based on machine learning approaches. The highest "out-of-the-box" F(2)-measure was 67% for partial matches; the best precision and recall were 95% and 78%, respectively. Finally, the ten-fold cross validation experiment allowed for an increase of the F(2)-measure to 79% with partial matches. The "out-of-the-box" evaluation of text de-identification systems provided us with compelling insight about the best methods for de-identification of VHA clinical documents. The errors analysis demonstrated an important need for customization to PHI formats specific to VHA documents. This study informed the planning and development of a "best-of-breed" automatic de-identification application for VHA clinical text.

Application of econometric and ecology analysis methods in physics software

NASA Astrophysics Data System (ADS)

Han, Min Cheol; Hoff, Gabriela; Kim, Chan Hyeong; Kim, Sung Hun; Grazia Pia, Maria; Ronchieri, Elisabetta; Saracco, Paolo

2017-10-01

Some data analysis methods typically used in econometric studies and in ecology have been evaluated and applied in physics software environments. They concern the evolution of observables through objective identification of change points and trends, and measurements of inequality, diversity and evenness across a data set. Within each analysis area, various statistical tests and measures have been examined. This conference paper summarizes a brief overview of some of these methods.

Investigation of High-Angle-of-Attack Maneuver-Limiting Factors. Part 1. Analysis and Simulation

DTIC Science & Technology

1980-12-01

useful, are not so satisfying or in- structive as the more positive identification of causal factors offered by the methods developed in Reference 5...same methods be applied to additional high-performance fighter aircraft having widely differing high AOA handling characteristics to see if further...predictions and the nonlinear model results were resolved. The second task involved development of methods , criteria, and an associated pilot rating scale, for

Identification of Dekkera bruxellensis (Brettanomyces) from Wine by Fluorescence In Situ Hybridization Using Peptide Nucleic Acid Probes

PubMed Central

Stender, Henrik; Kurtzman, Cletus; Hyldig-Nielsen, Jens J.; Sørensen, Ditte; Broomer, Adam; Oliveira, Kenneth; Perry-O'Keefe, Heather; Sage, Andrew; Young, Barbara; Coull, James

2001-01-01

A new fluorescence in situ hybridization method using peptide nucleic acid (PNA) probes for identification of Brettanomyces is described. The test is based on fluorescein-labeled PNA probes targeting a species-specific sequence of the rRNA of Dekkera bruxellensis. The PNA probes were applied to smears of colonies, and results were interpreted by fluorescence microscopy. The results obtained from testing 127 different yeast strains, including 78 Brettanomyces isolates from wine, show that the spoilage organism Brettanomyces belongs to the species D. bruxellensis and that the new method is able to identify Brettanomyces (D. bruxellensis) with 100% sensitivity and 100% specificity. PMID:11157265

Unsteady hovering wake parameters identified from dynamic model tests, part 1

NASA Technical Reports Server (NTRS)

Hohenemser, K. H.; Crews, S. T.

1977-01-01

The development of a 4-bladed model rotor is reported that can be excited with a simple eccentric mechanism in progressing and regressing modes with either harmonic or transient inputs. Parameter identification methods were applied to the problem of extracting parameters for linear perturbation models, including rotor dynamic inflow effects, from the measured blade flapping responses to transient pitch stirring excitations. These perturbation models were then used to predict blade flapping response to other pitch stirring transient inputs, and rotor wake and blade flapping responses to harmonic inputs. The viability and utility of using parameter identification methods for extracting the perturbation models from transients are demonstrated through these combined analytical and experimental studies.

Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method

PubMed Central

Arias, Carlos Roberto; Yeh, Hsiang-Yuan; Soo, Von-Wun

2012-01-01

Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF). The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well. PMID:22654636

Terahertz detection and identification of defects in layered polymer composites and composite coatings

NASA Astrophysics Data System (ADS)

Lopato, Przemyslaw; Chady, Tomasz

2013-03-01

Modern industry makes more and more extensive use of various composite materials. In this paper, for the purposes of various composite materials evaluation, the terahertz imaging method is presented. Basalt fibre-reinforced composites and polymeric anticorrosion coatings are considered. Basalt fibre composites are the innovative materials that are being increasingly used in modern industry. The paper also briefly introduces a specific type of complex coating of steel applied in the industry (e.g. oil or chemical). Two methods of defects detection in the mentioned structures are presented. The first method is based on a system identification, whereas the second one is on the estimation of time-domain signal parameters. Finally, the results achieved during terahertz inspection of coatings are compared with those obtained using active thermography.

Comments on Frequency Swept Rotating Input Perturbation Techniques and Identification of the Fluid Force Models in Rotor/bearing/seal Systems and Fluid Handling Machines

NASA Technical Reports Server (NTRS)

Muszynska, Agnes; Bently, Donald E.

1991-01-01

Perturbation techniques used for identification of rotating system dynamic characteristics are described. A comparison between two periodic frequency-swept perturbation methods applied in identification of fluid forces of rotating machines is presented. The description of the fluid force model identified by inputting circular periodic frequency-swept force is given. This model is based on the existence and strength of the circumferential flow, most often generated by the shaft rotation. The application of the fluid force model in rotor dynamic analysis is presented. It is shown that the rotor stability is an entire rotating system property. Some areas for further research are discussed.

Dynamic biometric identification from multiple views using the GLBP-TOP method.

PubMed

Wang, Yu; Shen, Xuanjing; Chen, Haipeng; Zhai, Yujie

2014-01-01

To realize effective and rapid dynamic biometric identification with low computational complexity, a video-based facial texture program that extracts local binary patterns from three orthogonal planes in the frequency domain of the Gabor transform (GLBP-TOP) was proposed. Firstly, each normalized face was transformed by Gabor wavelet to get the enhanced Gabor magnitude map, and then the LBP-TOP operator was applied to the maps to extract video texture. Finally, weighted Chi square statistics based on the Fisher Criterion were used to realize the identification. The proposed algorithm was proved effective through the biometric experiments using the Honda/UCSD database, and was robust against changes of illumination and expressions.

Identification of Uranium Minerals in Natural U-Bearing Rocks Using Infrared Reflectance Spectroscopy.

PubMed

Beiswenger, Toya N; Gallagher, Neal B; Myers, Tanya L; Szecsody, James E; Tonkyn, Russell G; Su, Yin-Fong; Sweet, Lucas E; Lewallen, Tricia A; Johnson, Timothy J

2018-02-01

The identification of minerals, including uranium-bearing species, is often a labor-intensive process using X-ray diffraction (XRD), fluorescence, or other solid-phase or wet chemical techniques. While handheld XRD and fluorescence instruments can aid in field applications, handheld infrared (IR) reflectance spectrometers can now also be used in industrial or field environments, with rapid, nondestructive identification possible via analysis of the solid's reflectance spectrum providing information not found in other techniques. In this paper, we report the use of laboratory methods that measure the IR hemispherical reflectance of solids using an integrating sphere and have applied it to the identification of mineral mixtures (i.e., rocks), with widely varying percentages of uranium mineral content. We then apply classical least squares (CLS) and multivariate curve resolution (MCR) methods to better discriminate the minerals (along with two pure uranium chemicals U 3 O 8 and UO 2 ) against many common natural and anthropogenic background materials (e.g., silica sand, asphalt, calcite, K-feldspar) with good success. Ground truth as to mineral content was attained primarily by XRD. Identification is facile and specific, both for samples that are pure or are partially composed of uranium (e.g., boltwoodite, tyuyamunite, etc.) or non-uranium minerals. The characteristic IR bands generate unique (or class-specific) bands, typically arising from similar chemical moieties or functional groups in the minerals: uranyls, phosphates, silicates, etc. In some cases, the chemical groups that provide spectral discrimination in the longwave IR reflectance by generating upward-going (reststrahlen) bands can provide discrimination in the midwave and shortwave IR via downward-going absorption features, i.e., weaker overtone or combination bands arising from the same chemical moieties.

A hybrid system identification methodology for wireless structural health monitoring systems based on dynamic substructuring

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-04-01

System identification has been employed in numerous structural health monitoring (SHM) applications. Traditional system identification methods usually rely on centralized processing of structural response data to extract information on structural parameters. However, in wireless SHM systems the centralized processing of structural response data introduces a significant communication bottleneck. Exploiting the merits of decentralization and on-board processing power of wireless SHM systems, many system identification methods have been successfully implemented in wireless sensor networks. While several system identification approaches for wireless SHM systems have been proposed, little attention has been paid to obtaining information on the physical parameters (e.g. stiffness, damping) of the monitored structure. This paper presents a hybrid system identification methodology suitable for wireless sensor networks based on the principles of component mode synthesis (dynamic substructuring). A numerical model of the monitored structure is embedded into the wireless sensor nodes in a distributed manner, i.e. the entire model is segmented into sub-models, each embedded into one sensor node corresponding to the substructure the sensor node is assigned to. The parameters of each sub-model are estimated by extracting local mode shapes and by applying the equations of the Craig-Bampton method on dynamic substructuring. The proposed methodology is validated in a laboratory test conducted on a four-story frame structure to demonstrate the ability of the methodology to yield accurate estimates of stiffness parameters. Finally, the test results are discussed and an outlook on future research directions is provided.

Novel, improved sample preparation for rapid, direct identification from positive blood cultures using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry.

PubMed

Schubert, Sören; Weinert, Kirsten; Wagner, Chris; Gunzl, Beatrix; Wieser, Andreas; Maier, Thomas; Kostrzewa, Markus

2011-11-01

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is widely used for rapid and reliable identification of bacteria and yeast grown on agar plates. Moreover, MALDI-TOF MS also holds promise for bacterial identification from blood culture (BC) broths in hospital laboratories. The most important technical step for the identification of bacteria from positive BCs by MALDI-TOF MS is sample preparation to remove blood cells and host proteins. We present a method for novel, rapid sample preparation using differential lysis of blood cells. We demonstrate the efficacy and ease of use of this sample preparation and subsequent MALDI-TOF MS identification, applying it to a total of 500 aerobic and anaerobic BCs reported to be positive by a Bactec 9240 system. In 86.5% of all BCs, the microorganism species were correctly identified. Moreover, in 18/27 mixed cultures at least one isolate was correctly identified. A novel method that adjusts the score value for MALDI-TOF MS results is proposed, further improving the proportion of correctly identified samples. The results of the present study show that the MALDI-TOF MS-based method allows rapid (<20 minutes) bacterial identification directly from positive BCs and with high accuracy. Copyright © 2011 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Evaluation of MALDI-TOF mass spectrometry and Sepsityper Kit™ for the direct identification of organisms from sterile body fluids in a Canadian pediatric hospital.

PubMed

Tadros, Manal; Petrich, Astrid

2013-01-01

Matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) can be used to identify bacteria directly from positive blood and sterile fluid cultures. The authors evaluated a commercially available kit - the Sepsityper Kit (Bruker Daltonik, Germany) - and MALDI-TOF MS for the rapid identification of organisms from 80 flagged positive blood culture broths, of which 73 (91.2%) were blood culture specimens and seven (8.7%) were cerebrospinal fluid specimens, in comparison with conventional identification methods. Correct identification to the genus and species levels was obtained in 75 of 80 (93.8%) and 39 of 50 (78%) blood culture broths, respectively. Applying the blood culture analysis module, a newly developed software tool, improved the species identification of Gram-negative organisms from 94.7% to 100% and of Gram-positive organisms from 66.7% to 70%. MALDI-TOF MS is a promising tool for the direct identification of organisms cultured from sterile sites.

Rapid identification of bacteria from positive blood culture bottles by use of matrix-assisted laser desorption-ionization time of flight mass spectrometry fingerprinting.

PubMed

Christner, Martin; Rohde, Holger; Wolters, Manuel; Sobottka, Ingo; Wegscheider, Karl; Aepfelbacher, Martin

2010-05-01

Early and adequate antimicrobial therapy has been shown to improve the clinical outcome in bloodstream infections (BSI). To provide rapid pathogen identification for targeted treatment, we applied matrix-assisted laser desorption-ionization time of flight (MALDI-TOF) mass spectrometry fingerprinting to bacteria directly recovered from blood culture bottles. A total of 304 aerobic and anaerobic blood cultures, reported positive by a Bactec 9240 system, were subjected in parallel to differential centrifugation with subsequent mass spectrometry fingerprinting and reference identification using established microbiological methods. A representative spectrum of bloodstream pathogens was recovered from 277 samples that grew a single bacterial isolate. Species identification by direct mass spectrometry fingerprinting matched reference identification in 95% of these samples and worked equally well for aerobic and anaerobic culture bottles. Application of commonly used score cutoffs to classify the fingerprinting results led to an identification rate of 87%. Mismatching mostly resulted from insufficient bacterial numbers and preferentially occurred with Gram-positive samples. The respective spectra showed low concordance to database references and were effectively rejected by score thresholds. Spiking experiments and examination of the respective study samples even suggested applicability of the method to mixed cultures. With turnaround times around 100 min, the approach allowed for reliable pathogen identification at the day of blood culture positivity, providing treatment-relevant information within the critical phase of septic illness.

Identification of impact force acting on composite laminated plates using the radiated sound measured with microphones

NASA Astrophysics Data System (ADS)

Atobe, Satoshi; Nonami, Shunsuke; Hu, Ning; Fukunaga, Hisao

2017-09-01

Foreign object impact events are serious threats to composite laminates because impact damage leads to significant degradation of the mechanical properties of the structure. Identification of the location and force history of the impact that was applied to the structure can provide useful information for assessing the structural integrity. This study proposes a method for identifying impact forces acting on CFRP (carbon fiber reinforced plastic) laminated plates on the basis of the sound radiated from the impacted structure. Identification of the impact location and force history is performed using the sound pressure measured with microphones. To devise a method for identifying the impact location from the difference in the arrival times of the sound wave detected with the microphones, the propagation path of the sound wave from the impacted point to the sensor is examined. For the identification of the force history, an experimentally constructed transfer matrix is employed to relate the force history to the corresponding sound pressure. To verify the validity of the proposed method, impact tests are conducted by using a CFRP cross-ply laminate as the specimen, and an impulse hammer as the impactor. The experimental results confirm the validity of the present method for identifying the impact location from the arrival time of the sound wave detected with the microphones. Moreover, the results of force history identification show the feasibility of identifying the force history accurately from the measured sound pressure using the experimental transfer matrix.

Multi-level slug tests in highly permeable formations: 2. Hydraulic conductivity identification, method verification, and field applications

USGS Publications Warehouse

Zlotnik, V.A.; McGuire, V.L.

1998-01-01

Using the developed theory and modified Springer-Gelhar (SG) model, an identification method is proposed for estimating hydraulic conductivity from multi-level slug tests. The computerized algorithm calculates hydraulic conductivity from both monotonic and oscillatory well responses obtained using a double-packer system. Field verification of the method was performed at a specially designed fully penetrating well of 0.1-m diameter with a 10-m screen in a sand and gravel alluvial aquifer (MSEA site, Shelton, Nebraska). During well installation, disturbed core samples were collected every 0.6 m using a split-spoon sampler. Vertical profiles of hydraulic conductivity were produced on the basis of grain-size analysis of the disturbed core samples. These results closely correlate with the vertical profile of horizontal hydraulic conductivity obtained by interpreting multi-level slug test responses using the modified SG model. The identification method was applied to interpret the response from 474 slug tests in 156 locations at the MSEA site. More than 60% of responses were oscillatory. The method produced a good match to experimental data for both oscillatory and monotonic responses using an automated curve matching procedure. The proposed method allowed us to drastically increase the efficiency of each well used for aquifer characterization and to process massive arrays of field data. Recommendations generalizing this experience to massive application of the proposed method are developed.Using the developed theory and modified Springer-Gelhar (SG) model, an identification method is proposed for estimating hydraulic conductivity from multi-level slug tests. The computerized algorithm calculates hydraulic conductivity from both monotonic and oscillatory well responses obtained using a double-packer system. Field verification of the method was performed at a specially designed fully penetrating well of 0.1-m diameter with a 10-m screen in a sand and gravel alluvial aquifer (MSEA site, Shelton, Nebraska). During well installation, disturbed core samples were collected every 0.6 m using a split-spoon sampler. Vertical profiles of hydraulic conductivity were produced on the basis of grain-size analysis of the disturbed core samples. These results closely correlate with the vertical profile of horizontal hydraulic conductivity obtained by interpreting multi-level slug test responses using the modified SG model. The identification method was applied to interpret the response from 474 slug tests in 156 locations at the MSEA site. More than 60% of responses were oscillatory. The method produced a good match to experimental data for both oscillatory and monotonic responses using an automated curve matching procedure. The proposed method allowed us to drastically increase the efficiency of each well used for aquifer characterization and to process massive arrays of field data. Recommendations generalizing this experience to massive application of the proposed method are developed.

36 CFR 1237.28 - What special concerns apply to digital photographs?

Code of Federal Regulations, 2012 CFR

2012-07-01

... defects, evaluate the accuracy of finding aids, and verify file header information and file name integrity... sampling methods or more comprehensive verification systems (e.g., checksum programs), to evaluate image.... For permanent or unscheduled images descriptive elements must include: (1) An identification number...

36 CFR § 1237.28 - What special concerns apply to digital photographs?

Code of Federal Regulations, 2013 CFR

2013-07-01

... defects, evaluate the accuracy of finding aids, and verify file header information and file name integrity... sampling methods or more comprehensive verification systems (e.g., checksum programs), to evaluate image.... For permanent or unscheduled images descriptive elements must include: (1) An identification number...

36 CFR 1237.28 - What special concerns apply to digital photographs?

Code of Federal Regulations, 2014 CFR

2014-07-01

... defects, evaluate the accuracy of finding aids, and verify file header information and file name integrity... sampling methods or more comprehensive verification systems (e.g., checksum programs), to evaluate image.... For permanent or unscheduled images descriptive elements must include: (1) An identification number...

36 CFR 1237.28 - What special concerns apply to digital photographs?

Code of Federal Regulations, 2010 CFR

2010-07-01

... defects, evaluate the accuracy of finding aids, and verify file header information and file name integrity... sampling methods or more comprehensive verification systems (e.g., checksum programs), to evaluate image.... For permanent or unscheduled images descriptive elements must include: (1) An identification number...

36 CFR 1237.28 - What special concerns apply to digital photographs?

Code of Federal Regulations, 2011 CFR

2011-07-01

... defects, evaluate the accuracy of finding aids, and verify file header information and file name integrity... sampling methods or more comprehensive verification systems (e.g., checksum programs), to evaluate image.... For permanent or unscheduled images descriptive elements must include: (1) An identification number...

SPECIATION OF ORGANICS IN WATER WITH RAMAN SPECTROSCOPY: UTILITY OF IONIC STRENGTH VARIATION

EPA Science Inventory

We have developed and are applying an experimental and mathematical method for describing the micro-speciation of complex organic contaminants in aqueous media. For our case, micro-speciation can be defined as qualitative and quantitative identification of all discrete forms of ...

IDENTIFICATION OF CHICKEN-SPECIFIC FECAL MICROBIAL SEQUENCES USING A METAGENOMIC APPROACH

EPA Science Inventory

In this study, we applied a genome fragment enrichment (GFE) method to select for genomic regions that differ between different fecal metagenomes. Competitive DNA hybridizations were performed between chicken fecal DNA and pig fecal DNA (C-P) and between chicken fecal DNA and an ...

Semi-supervised word polarity identification in resource-lean languages.

PubMed

Dehdarbehbahani, Iman; Shakery, Azadeh; Faili, Heshaam

2014-10-01

Sentiment words, as fundamental constitutive parts of subjective sentences, have a substantial effect on analysis of opinions, emotions and beliefs. Most of the proposed methods for identifying the semantic orientations of words exploit rich linguistic resources such as WordNet, subjectivity corpora, or polarity tagged words. Shortage of such linguistic resources in resource-lean languages affects the performance of word polarity identification in these languages. In this paper, we present a method which exploits a language with rich subjectivity analysis resources (English) to identify the polarity of words in a resource-lean foreign language. The English WordNet and a sparse foreign WordNet infrastructure are used to create a heterogeneous, multilingual and weighted semantic network. To identify the semantic orientation of foreign words, a random walk based method is applied to the semantic network along with a set of automatically weighted English positive and negative seeds. In a post-processing phase, synonym and antonym relations in the foreign WordNet are used to filter the random walk results. Our experiments on English and Persian languages show that the proposed method can outperform state-of-the-art word polarity identification methods in both languages. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identification and characterization of earthquake clusters: a comparative analysis for selected sequences in Italy

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2017-04-01

Identification and statistical characterization of seismic clusters may provide useful insights about the features of seismic energy release and their relation to physical properties of the crust within a given region. Moreover, a number of studies based on spatio-temporal analysis of main-shocks occurrence require preliminary declustering of the earthquake catalogs. Since various methods, relying on different physical/statistical assumptions, may lead to diverse classifications of earthquakes into main events and related events, we aim to investigate the classification differences among different declustering techniques. Accordingly, a formal selection and comparative analysis of earthquake clusters is carried out for the most relevant earthquakes in North-Eastern Italy, as reported in the local OGS-CRS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. The comparison is then extended to selected earthquake sequences associated with a different seismotectonic setting, namely to events that occurred in the region struck by the recent Central Italy destructive earthquakes, making use of INGV data. Various techniques, ranging from classical space-time windows methods to ad hoc manual identification of aftershocks, are applied for detection of earthquake clusters. In particular, a statistical method based on nearest-neighbor distances of events in space-time-energy domain, is considered. Results from clusters identification by the nearest-neighbor method turn out quite robust with respect to the time span of the input catalogue, as well as to minimum magnitude cutoff. The identified clusters for the largest events reported in North-Eastern Italy since 1977 are well consistent with those reported in earlier studies, which were aimed at detailed manual aftershocks identification. The study shows that the data-driven approach, based on the nearest-neighbor distances, can be satisfactorily applied to decompose the seismic catalog into background seismicity and individual sequences of earthquake clusters, also in areas characterized by moderate seismic activity, where the standard declustering techniques may turn out rather gross approximations. With these results acquired, the main statistical features of seismic clusters are explored, including complex interdependence of related events, with the aim to characterize the space-time patterns of earthquakes occurrence in North-Eastern Italy and capture their basic differences with Central Italy sequences.

Identification of magnetic anomalies based on ground magnetic data analysis using multifractal modelling: a case study in Qoja-Kandi, East Azerbaijan Province, Iran

NASA Astrophysics Data System (ADS)

Mansouri, E.; Feizi, F.; Karbalaei Ramezanali, A. A.

2015-10-01

Ground magnetic anomaly separation using the reduction-to-the-pole (RTP) technique and the fractal concentration-area (C-A) method has been applied to the Qoja-Kandi prospecting area in northwestern Iran. The geophysical survey resulting in the ground magnetic data was conducted for magnetic element exploration. Firstly, the RTP technique was applied to recognize underground magnetic anomalies. RTP anomalies were classified into different populations based on the current method. For this reason, drilling point area determination by the RTP technique was complicated for magnetic anomalies, which are in the center and north of the studied area. Next, the C-A method was applied to the RTP magnetic anomalies (RTP-MA) to demonstrate magnetic susceptibility concentrations. This identification was appropriate for increasing the resolution of the drilling point area determination and decreasing the drilling risk issue, due to the economic costs of underground prospecting. In this study, the results of C-A modelling on the RTP-MA are compared with 8 borehole data. The results show that there is a good correlation between anomalies derived via the C-A method and the log report of boreholes. Two boreholes were drilled in magnetic susceptibility concentrations, based on multifractal modelling data analyses, between 63 533.1 and 66 296 nT. Drilling results showed appropriate magnetite thickness with grades greater than 20 % Fe. The total associated with anomalies containing andesite units hosts iron mineralization.

Methods to recognize work-related cancer in workplaces, the general population, and by experts in the clinic, a Norwegian experience

PubMed Central

2011-01-01

Background In most countries, the numbers of work-related cancer identified are much lower than are the estimated total burden of cancer caused by exposure at work. Therefore, there is a great need to use all available practical as well as epidemiological methods for identification as well as to develop new methods of recognizing cases of work-related cancers. Methods Primarily based on practical experiences from Norway, methods to identify cases of possible work-related cancers in the general population and at workplaces as well as methods to recognize more specific cases after referral to specialized clinics are reviewed in this publication. Results Countries applying a number of the available methods to detect work-related cancer reach a reporting rate of 60 such cases per million, while other countries that do not employ such methods hardly identify any cases. As most subjects previously exposed to cancer causing agents and substances at work are gradually recruited out of work, methods should be versatile for identification of cases in the general population, as well as at work. Conclusions Even in countries using a number of the available methods for identification, only a limited fraction of the real number of work-related cancer are notified to the labour inspectorate. Clinicians should be familiar with the methods and do the best to identify work-related cancer to serve prevention. PMID:21899752

Application of physical parameter identification to finite-element models

NASA Technical Reports Server (NTRS)

Bronowicki, Allen J.; Lukich, Michael S.; Kuritz, Steven P.

1987-01-01

The time domain parameter identification method described previously is applied to TRW's Large Space Structure Truss Experiment. Only control sensors and actuators are employed in the test procedure. The fit of the linear structural model to the test data is improved by more than an order of magnitude using a physically reasonable parameter set. The electro-magnetic control actuators are found to contribute significant damping due to a combination of eddy current and back electro-motive force (EMF) effects. Uncertainties in both estimated physical parameters and modal behavior variables are given.

Rapid Identification of Sequences for Orphan Enzymes to Power Accurate Protein Annotation

PubMed Central

Ojha, Sunil; Watson, Douglas S.; Bomar, Martha G.; Galande, Amit K.; Shearer, Alexander G.

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the “back catalog” of enzymology – “orphan enzymes,” those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme “back catalog” is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology’s “back catalog” another powerful tool to drive accurate genome annotation. PMID:24386392

Rapid identification of sequences for orphan enzymes to power accurate protein annotation.

PubMed

Ramkissoon, Kevin R; Miller, Jennifer K; Ojha, Sunil; Watson, Douglas S; Bomar, Martha G; Galande, Amit K; Shearer, Alexander G

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the "back catalog" of enzymology--"orphan enzymes," those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme "back catalog" is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology's "back catalog" another powerful tool to drive accurate genome annotation.

Development of SCAR (sequence-characterized amplified region) markers as a complementary tool for identification of ginger (Zingiber officinale Roscoe) from crude drugs and multicomponent formulations.

PubMed

Chavan, Preeti; Warude, Dnyaneshwar; Joshi, Kalpana; Patwardhan, Bhushan

2008-05-01

Zingiber officinale Roscoe (common or culinary ginger) is an official drug in Ayurvedic, Indian herbal, Chinese, Japanese, African and British Pharmacopoeias. The objective of the present study was to develop DNA-based markers that can be applied for the identification and differentiation of the commercially important plant Z. officinale Roscoe from the closely related species Zingiber zerumbet (pinecone, bitter or 'shampoo' ginger) and Zingiber cassumunar [cassumunar or plai (Thai) ginger]. The rhizomes of the other two Zingiber species used in the present study are morphologically similar to that of Z. officinale Roscoe and can be used as its adulterants or contaminants. Various methods, including macroscopy, microscopy and chemoprofiling, have been reported for the quality control of crude ginger and its products. These methods are reported to have limitations in distinguishing Z. officinale from closely related species. Hence, newer complementary methods for correct identification of ginger are useful. In the present study, RAPD (random amplification of polymorphic DNA) analysis was used to identify putative species-specific amplicons for Z. officinale. These were further cloned and sequenced to develop SCAR (sequence-characterized amplified region) markers. The developed SCAR markers were tested in several non-Zingiber species commonly used in ginger-containing formulations. One of the markers, P3, was found to be specific for Z. officinale and was successfully applied for detection of Z. officinale from Trikatu, a multicomponent formulation.

Rigid body mode identification of the PAH-2 helicopter using the eigensystem realization algorithm

NASA Technical Reports Server (NTRS)

Schenk, Axel; Pappa, Richard S.

1992-01-01

The rigid body modes of the PAH-2 'Tiger' helicopter were identified using the Eigensystem Realization Algorithm (ERA). This work complements ground vibration tests performed using DLR's traditional phase resonance technique and the ISSPA (Identification of Structural System Parameters) method. Rigid body modal parameters are important for ground resonance prediction. Time-domain data for ERA were obtained by inverse Fourier transformation of frequency response functions measured with stepped-sine excitation. Mode purity (based on the Phase Resonance Criterion) was generally equal to or greater than corresponding results obtained in the ground vibration tests. All identified natural frequencies and mode shapes correlate well with corresponding ground vibration test results. The modal identification approach discussed in this report has become increasingly attractive in recent years due to the steadily declining cost and increased performance of scientific computers. As illustrated in this application, modern time-domain methods can be successfully applied to data acquired using DLR's existing test equipment. Some suggestions are made for future applications of time domain modal identification in this manner.

The Use of DNA Barcoding in Identification and Conservation of Rosewood (Dalbergia spp.)

PubMed Central

Hartvig, Ida; Czako, Mihaly; Kjær, Erik Dahl; Nielsen, Lene Rostgaard; Theilade, Ida

2015-01-01

The genus Dalbergia contains many valuable timber species threatened by illegal logging and deforestation, but knowledge on distributions and threats is often limited and accurate species identification difficult. The aim of this study was to apply DNA barcoding methods to support conservation efforts of Dalbergia species in Indochina. We used the recommended rbcL, matK and ITS barcoding markers on 95 samples covering 31 species of Dalbergia, and tested their discrimination ability with both traditional distance-based as well as different model-based machine learning methods. We specifically tested whether the markers could be used to solve taxonomic confusion concerning the timber species Dalbergia oliveri, and to identify the CITES-listed Dalbergia cochinchinensis. We also applied the barcoding markers to 14 samples of unknown identity. In general, we found that the barcoding markers discriminated among Dalbergia species with high accuracy. We found that ITS yielded the single highest discrimination rate (100%), but due to difficulties in obtaining high-quality sequences from degraded material, the better overall choice for Dalbergia seems to be the standard rbcL+matK barcode, as this yielded discrimination rates close to 90% and amplified well. The distance-based method TaxonDNA showed the highest identification rates overall, although a more complete specimen sampling is needed to conclude on the best analytic method. We found strong support for a monophyletic Dalbergia oliveri and encourage that this name is used consistently in Indochina. The CITES-listed Dalbergia cochinchinensis was successfully identified, and a species-specific assay can be developed from the data generated in this study for the identification of illegally traded timber. We suggest that the use of DNA barcoding is integrated into the work flow during floristic studies and at national herbaria in the region, as this could significantly increase the number of identified specimens and improve knowledge about species distributions. PMID:26375850

Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram

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

Anant, K.S.

1997-06-01

In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective mathematical tool for the analysis of transient signals. The two key signal processing applications of the wavelet transform, namely feature identification and representation (i.e., compression), are shown by solving important problems involving the seismogram and the electrocardiogram. The seismic feature identification problem involved locating in time the P and S phase arrivals. Locating these arrivals accurately (particularly the S phase) has been a constant issue in seismic signal processing. In Chapter 3, I show that the wavelet transform can be used to locate both the Pmore » as well as the S phase using only information from single station three-component seismograms. This is accomplished by using the basis function (wave-let) of the wavelet transform as a matching filter and by processing information across scales of the wavelet domain decomposition. The `pick` time results are quite promising as compared to analyst picks. The representation application involved the compression of the electrocardiogram which is a recording of the electrical activity of the heart. Compression of the electrocardiogram is an important problem in biomedical signal processing due to transmission and storage limitations. In Chapter 4, I develop an electrocardiogram compression method that applies vector quantization to the wavelet transform coefficients. The best compression results were obtained by using orthogonal wavelets, due to their ability to represent a signal efficiently. Throughout this thesis the importance of choosing wavelets based on the problem at hand is stressed. In Chapter 5, I introduce a wavelet design method that uses linear prediction in order to design wavelets that are geared to the signal or feature being analyzed. The use of these designed wavelets in a test feature identification application led to positive results. The methods developed in this thesis; the feature identification methods of Chapter 3, the compression methods of Chapter 4, as well as the wavelet design methods of Chapter 5, are general enough to be easily applied to other transient signals.« less

APHASIC CHILDREN, IDENTIFICATION AND EDUCATION BY THE ASSOCIATION METHOD.

ERIC Educational Resources Information Center

MCGINNIS, MILDRED A.

THIS BOOK IS DESIGNED TO DEFINE APHASIA AND ITS CHARACTERISTICS, TO PRESENT A PROCEDURE FOR TEACHING LANGUAGE TO APHASIC CHILDREN, AND TO APPLY THIS PROCEDURE TO ELEMENTARY SCHOOL SUBJECTS. OTHER HANDICAPPING CONDITIONS WHICH COMPLICATE THE DIAGNOSIS OF APHASIA ARE PRESENTED BY MEANS OF CASE STUDIES. CHARACTERISTICS OF TWO TYPES OF…

A Performance-Based Method of Student Evaluation

ERIC Educational Resources Information Center

Nelson, G. E.; And Others

1976-01-01

The Problem Oriented Medical Record (which allows practical definition of the behavioral terms thoroughness, reliability, sound analytical sense, and efficiency as they apply to the identification and management of patient problems) provides a vehicle to use in performance based type evaluation. A test-run use of the record is reported. (JT)

TEMPORAL AND SPATIAL VARIABILITY OF FECAL INDICATOR BACTERIA: IMPLICATIONS FOR THE APPLICATION OF MST METHODOLOGIES TO DIFFERENTIATE SOURCES OF FECAL CONTAMINATION

EPA Science Inventory

Temporal variability in the gastrointestinal flora of animals impacting water resources with fecal material can be one of the factors producing low source identification rates when applying microbial source tracking (MST) methods. Understanding how bacterial species and genotype...

A novel approach to identifying regulatory motifs in distantly related genomes

PubMed Central

Van Hellemont, Ruth; Monsieurs, Pieter; Thijs, Gert; De Moor, Bart; Van de Peer, Yves; Marchal, Kathleen

2005-01-01

Although proven successful in the identification of regulatory motifs, phylogenetic footprinting methods still show some shortcomings. To assess these difficulties, most apparent when applying phylogenetic footprinting to distantly related organisms, we developed a two-step procedure that combines the advantages of sequence alignment and motif detection approaches. The results on well-studied benchmark datasets indicate that the presented method outperforms other methods when the sequences become either too long or too heterogeneous in size. PMID:16420672

Identification of moving sinusoidal wave loads for sensor structural configuration by finite element inverse method

NASA Astrophysics Data System (ADS)

Zhang, B.; Yu, S.

2018-03-01

In this paper, a beam structure of composite materials with elastic foundation supports is established as the sensor model, which propagates moving sinusoidal wave loads. The inverse Finite Element Method (iFEM) is applied for reconstructing moving wave loads which are compared with true wave loads. The conclusion shows that iFEM is accurate and robust in the determination of wave propagation. This helps to seek a suitable new wave sensor method.

Identification of Enzyme Genes Using Chemical Structure Alignments of Substrate-Product Pairs.

PubMed

Moriya, Yuki; Yamada, Takuji; Okuda, Shujiro; Nakagawa, Zenichi; Kotera, Masaaki; Tokimatsu, Toshiaki; Kanehisa, Minoru; Goto, Susumu

2016-03-28

Although there are several databases that contain data on many metabolites and reactions in biochemical pathways, there is still a big gap in the numbers between experimentally identified enzymes and metabolites. It is supposed that many catalytic enzyme genes are still unknown. Although there are previous studies that estimate the number of candidate enzyme genes, these studies required some additional information aside from the structures of metabolites such as gene expression and order in the genome. In this study, we developed a novel method to identify a candidate enzyme gene of a reaction using the chemical structures of the substrate-product pair (reactant pair). The proposed method is based on a search for similar reactant pairs in a reference database and offers ortholog groups that possibly mediate the given reaction. We applied the proposed method to two experimentally validated reactions. As a result, we confirmed that the histidine transaminase was correctly identified. Although our method could not directly identify the asparagine oxo-acid transaminase, we successfully found the paralog gene most similar to the correct enzyme gene. We also applied our method to infer candidate enzyme genes in the mesaconate pathway. The advantage of our method lies in the prediction of possible genes for orphan enzyme reactions where any associated gene sequences are not determined yet. We believe that this approach will facilitate experimental identification of genes for orphan enzymes.

The application of a biometric identification technique for linking community and hospital data in rural Ghana

PubMed Central

Odei-Lartey, Eliezer Ofori; Boateng, Dennis; Danso, Samuel; Kwarteng, Anthony; Abokyi, Livesy; Amenga-Etego, Seeba; Gyaase, Stephaney; Asante, Kwaku Poku; Owusu-Agyei, Seth

2016-01-01

Background The reliability of counts for estimating population dynamics and disease burdens in communities depends on the availability of a common unique identifier for matching general population data with health facility data. Biometric data has been explored as a feasible common identifier between the health data and sociocultural data of resident members in rural communities within the Kintampo Health and Demographic Surveillance System located in the central part of Ghana. Objective Our goal was to assess the feasibility of using fingerprint identification to link community data and hospital data in a rural African setting. Design A combination of biometrics and other personal identification techniques were used to identify individual's resident within a surveillance population seeking care in two district hospitals. Visits from resident individuals were successfully recorded and categorized by the success of the techniques applied during identification. The successes of visits that involved identification by fingerprint were further examined by age. Results A total of 27,662 hospital visits were linked to resident individuals. Over 85% of those visits were successfully identified using at least one identification method. Over 65% were successfully identified and linked using their fingerprints. Supervisory support from the hospital administration was critical in integrating this identification system into its routine activities. No concerns were expressed by community members about the fingerprint registration and identification processes. Conclusions Fingerprint identification should be combined with other methods to be feasible in identifying community members in African rural settings. This can be enhanced in communities with some basic Demographic Surveillance System or census information. PMID:26993473

The application of a biometric identification technique for linking community and hospital data in rural Ghana.

PubMed

Odei-Lartey, Eliezer Ofori; Boateng, Dennis; Danso, Samuel; Kwarteng, Anthony; Abokyi, Livesy; Amenga-Etego, Seeba; Gyaase, Stephaney; Asante, Kwaku Poku; Owusu-Agyei, Seth

2016-01-01

The reliability of counts for estimating population dynamics and disease burdens in communities depends on the availability of a common unique identifier for matching general population data with health facility data. Biometric data has been explored as a feasible common identifier between the health data and sociocultural data of resident members in rural communities within the Kintampo Health and Demographic Surveillance System located in the central part of Ghana. Our goal was to assess the feasibility of using fingerprint identification to link community data and hospital data in a rural African setting. A combination of biometrics and other personal identification techniques were used to identify individual's resident within a surveillance population seeking care in two district hospitals. Visits from resident individuals were successfully recorded and categorized by the success of the techniques applied during identification. The successes of visits that involved identification by fingerprint were further examined by age. A total of 27,662 hospital visits were linked to resident individuals. Over 85% of those visits were successfully identified using at least one identification method. Over 65% were successfully identified and linked using their fingerprints. Supervisory support from the hospital administration was critical in integrating this identification system into its routine activities. No concerns were expressed by community members about the fingerprint registration and identification processes. Fingerprint identification should be combined with other methods to be feasible in identifying community members in African rural settings. This can be enhanced in communities with some basic Demographic Surveillance System or census information.

[Identification of spill oil species based on low concentration synchronous fluorescence spectra and RBF neural network].

PubMed

Liu, Qian-qian; Wang, Chun-yan; Shi, Xiao-feng; Li, Wen-dong; Luan, Xiao-ning; Hou, Shi-lin; Zhang, Jin-liang; Zheng, Rong-er

2012-04-01

In this paper, a new method was developed to differentiate the spill oil samples. The synchronous fluorescence spectra in the lower nonlinear concentration range of 10(-2) - 10(-1) g x L(-1) were collected to get training data base. Radial basis function artificial neural network (RBF-ANN) was used to identify the samples sets, along with principal component analysis (PCA) as the feature extraction method. The recognition rate of the closely-related oil source samples is 92%. All the results demonstrated that the proposed method could identify the crude oil samples effectively by just one synchronous spectrum of the spill oil sample. The method was supposed to be very suitable to the real-time spill oil identification, and can also be easily applied to the oil logging and the analysis of other multi-PAHs or multi-fluorescent mixtures.

A Spacecraft Electrical Characteristics Multi-Label Classification Method Based on Off-Line FCM Clustering and On-Line WPSVM

PubMed Central

Li, Ke; Liu, Yi; Wang, Quanxin; Wu, Yalei; Song, Shimin; Sun, Yi; Liu, Tengchong; Wang, Jun; Li, Yang; Du, Shaoyi

2015-01-01

This paper proposes a novel multi-label classification method for resolving the spacecraft electrical characteristics problems which involve many unlabeled test data processing, high-dimensional features, long computing time and identification of slow rate. Firstly, both the fuzzy c-means (FCM) offline clustering and the principal component feature extraction algorithms are applied for the feature selection process. Secondly, the approximate weighted proximal support vector machine (WPSVM) online classification algorithms is used to reduce the feature dimension and further improve the rate of recognition for electrical characteristics spacecraft. Finally, the data capture contribution method by using thresholds is proposed to guarantee the validity and consistency of the data selection. The experimental results indicate that the method proposed can obtain better data features of the spacecraft electrical characteristics, improve the accuracy of identification and shorten the computing time effectively. PMID:26544549

Identification of dust source regions and dust emission trends across North Africa and the Middle East using MISR satellite observations

NASA Astrophysics Data System (ADS)

Yu, Y.; Kalashnikova, O. V.; Garay, M. J.; Notaro, M.

2017-12-01

Global arid and semi-arid regions supply 1100 to 5000 Tg of Aeolian dust to the atmosphere each year, primarily from North Africa and secondarily from the Middle East. Previous dust source identification methods, based on either remotely-sensed aerosol optical depth (AOD) or dust activity, yield distinct dust source maps, largely due to the limitations in each method and remote-sensing product. Here we apply a novel motion-based method for dust source identification. Dust plume thickness and motion vectors from Multi-angle Imaging SpectroRadiometer (MISR) Cloud Motion Vector Product (CMVP) are examined to identify the regions with high frequency of fast moving-dust plumes, by season. According to MISR CMVP, Bodele depression is the most important dust source across North Africa, consistent with previous studies. Seasonal variability of dust emission across the North Africa is largely driven by climatology of wind and precipitation, featuring the influence of Sharav Cyclone and western African monsoon. In the Middle East, Iraq, Kuwait, and eastern Saudi Arabia are identified as dust source regions, especially during summer months, when the Middle Eastern Shamal wind is active. Furthermore, dust emission trend at each dust source are diagnosed from the motion-based dust source dataset. Increase in dust emission from the Fertile Crescent, Sahel, and eastern African dust sources are identified from MISR CMVP, implying potential contribution from these dust sources to the upward trend in AOD and dust AOD over the Middle East in the 21st century. By comparing with various dust source identification studies, we conclude that the motion-based identification of dust sources is an encouraging alternative and compliment to the AOD-only source identification method.

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

PubMed

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

2014-12-01

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

Methods and Apparatus for Reducing Multipath Signal Error Using Deconvolution

NASA Technical Reports Server (NTRS)

Kumar, Rajendra (Inventor); Lau, Kenneth H. (Inventor)

1999-01-01

A deconvolution approach to adaptive signal processing has been applied to the elimination of signal multipath errors as embodied in one preferred embodiment in a global positioning system receiver. The method and receiver of the present invention estimates then compensates for multipath effects in a comprehensive manner. Application of deconvolution, along with other adaptive identification and estimation techniques, results in completely novel GPS (Global Positioning System) receiver architecture.

A hybrid technique for speech segregation and classification using a sophisticated deep neural network

PubMed Central

Nawaz, Tabassam; Mehmood, Zahid; Rashid, Muhammad; Habib, Hafiz Adnan

2018-01-01

Recent research on speech segregation and music fingerprinting has led to improvements in speech segregation and music identification algorithms. Speech and music segregation generally involves the identification of music followed by speech segregation. However, music segregation becomes a challenging task in the presence of noise. This paper proposes a novel method of speech segregation for unlabelled stationary noisy audio signals using the deep belief network (DBN) model. The proposed method successfully segregates a music signal from noisy audio streams. A recurrent neural network (RNN)-based hidden layer segregation model is applied to remove stationary noise. Dictionary-based fisher algorithms are employed for speech classification. The proposed method is tested on three datasets (TIMIT, MIR-1K, and MusicBrainz), and the results indicate the robustness of proposed method for speech segregation. The qualitative and quantitative analysis carried out on three datasets demonstrate the efficiency of the proposed method compared to the state-of-the-art speech segregation and classification-based methods. PMID:29558485

[FMEA applied to the radiotherapy patient care process].

PubMed

Meyrieux, C; Garcia, R; Pourel, N; Mège, A; Bodez, V

2012-10-01

Failure modes and effects analysis (FMEA), is a risk analysis method used at the Radiotherapy Department of Institute Sainte-Catherine as part of a strategy seeking to continuously improve the quality and security of treatments. The method comprises several steps: definition of main processes; for each of them, description for every step of prescription, treatment preparation, treatment application; identification of the possible risks, their consequences, their origins; research of existing safety elements which may avoid these risks; grading of risks to assign a criticality score resulting in a numerical organisation of the risks. Finally, the impact of proposed corrective actions was then estimated by a new grading round. For each process studied, a detailed map of the risks was obtained, facilitating the identification of priority actions to be undertaken. For example, we obtain five steps in patient treatment planning with an unacceptable level of risk, 62 a level of moderate risk and 31 an acceptable level of risk. The FMEA method, used in the industrial domain and applied here to health care, is an effective tool for the management of risks in patient care. However, the time and training requirements necessary to implement this method should not be underestimated. Copyright © 2012 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

The study of using earth tide response of groundwater level and rainfall recharge to identify groundwater aquifer

NASA Astrophysics Data System (ADS)

Huang, W. J.; Hsu, C. H.; Chang, L. C.; Chiang, C. J.; Wang, Y. S.; Lu, W. C.

2017-12-01

Hydrogeological framework is the most important basis for groundwater analysis and simulation. Conventionally, the core drill is a most commonly adopted skill to acquire the core's data with the help of other research methods to artificially determine the result. Now, with the established groundwater station network, there are a lot of groundwater level information available. Groundwater level is an integrated presentation of the hydrogeological framework and the external pumping and recharge system. Therefore, how to identify the hydrogeological framework from a large number of groundwater level data is an important subject. In this study, the frequency analysis method and rainfall recharge mechanism were used to identify the aquifer where the groundwater level's response frequency and amplitude react to the earth tide. As the earth tide change originates from the gravity caused by the paths of sun and moon, it leads to soil stress and strain changes, which further affects the groundwater level. The scale of groundwater level's change varies with the influence of aquifer pressure systems such as confined or unconfined aquifers. This method has been applied to the identification of aquifers in the Cho-Shui River Alluvial Fan. The results of the identification are compared to the records of core drill and they both are quite consistent. It is shown that the identification methods developed in this study can considerably contribute to the identification of hydrogeological framework.

Development of a PCR-RFLP method based on the transcription elongation factor 1-α gene to differentiate Fusarium graminearum from other species within the Fusarium graminearum species complex.

PubMed

Garmendia, Gabriela; Umpierrez-Failache, Mariana; Ward, Todd J; Vero, Silvana

2018-04-01

Fusarium head blight (FHB) is a destructive disease of cereals crops worldwide and a major food safety concern due to grain contamination with trichothecenes and other mycotoxins. Fusarium graminearum, a member of the Fusarium graminearum species complex (FGSC) is the dominant FHB pathogen in many parts of the world. However, a number of other Fusarium species, including other members of the FGSC, may also be present for example in Argentina, New Zealand, Ethiopia, Nepal, Unites States in cereals such as wheat and barley. Proper species identification is critical to research aimed at improving disease and mycotoxin control programs. Identification of Fusarium species is are often unreliable by traditional, as many species are morphologically cryptic. DNA sequence-based methods offer a reliable means of species identification, but can be expensive when applied to the analyses of population samples. To facilitate identification of the major causative agent of FHB, this work describes an easy and inexpensive method to differentiate F. graminearum from the remaining species within the FGSC and from the other common Fusarium species causing FHB in cereals. The developed method is based on a PCR-RFLP of the transcription elongation factor (TEF 1-α) gene using the restriction enzyme BsaHI. Copyright © 2017 Elsevier Ltd. All rights reserved.

Time series modeling of human operator dynamics in manual control tasks

NASA Technical Reports Server (NTRS)

Biezad, D. J.; Schmidt, D. K.

1984-01-01

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency responses of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that has not been previously modeled to demonstrate the strengths of the method.

Time Series Modeling of Human Operator Dynamics in Manual Control Tasks

NASA Technical Reports Server (NTRS)

Biezad, D. J.; Schmidt, D. K.

1984-01-01

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency response of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that was previously modeled to demonstrate the strengths of the method.

Superpixel segmentation and pigment identification of colored relics based on visible spectral image.

PubMed

Li, Junfeng; Wan, Xiaoxia

2018-01-15

To enrich the contents of digital archive and to guide the copy and restoration of colored relics, non-invasive methods for extraction of painting boundary and identification of pigment composition are proposed in this study based on the visible spectral images of colored relics. Superpixel concept is applied for the first time to the field of oversegmentation of visible spectral images and implemented on the visible spectral images of colored relics to extract their painting boundary. Since different pigments are characterized by their own spectrum and the same kind of pigment has the similar geometric profile in spectrum, an automatic identification method is established by comparing the proximity between the geometric profiles of the unknown spectrum from each superpixel and the pre-known spectrum from a deliberately prepared database. The methods are validated using the visible spectral images of the ancient wall paintings in Mogao Grottoes. By the way, the visible spectral images are captured by a multispectral imaging system consisting of two broadband filters and a RGB camera with high spatial resolution. Copyright © 2017 Elsevier B.V. All rights reserved.

New Possibilities of Substance Identification Based on THz Time Domain Spectroscopy Using a Cascade Mechanism of High Energy Level Excitation

PubMed Central

Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Zakharova, Irina G.; Zagursky, Dmitry Yu.

2017-01-01

Using an experiment with thin paper layers and computer simulation, we demonstrate the principal limitations of standard Time Domain Spectroscopy (TDS) based on using a broadband THz pulse for the detection and identification of a substance placed inside a disordered structure. We demonstrate the spectrum broadening of both transmitted and reflected pulses due to the cascade mechanism of the high energy level excitation considering, for example, a three-energy level medium. The pulse spectrum in the range of high frequencies remains undisturbed in the presence of a disordered structure. To avoid false absorption frequencies detection, we apply the spectral dynamics analysis method (SDA-method) together with certain integral correlation criteria (ICC). PMID:29186849

A review of output-only structural mode identification literature employing blind source separation methods

NASA Astrophysics Data System (ADS)

Sadhu, A.; Narasimhan, S.; Antoni, J.

2017-09-01

Output-only modal identification has seen significant activity in recent years, especially in large-scale structures where controlled input force generation is often difficult to achieve. This has led to the development of new system identification methods which do not require controlled input. They often work satisfactorily if they satisfy some general assumptions - not overly restrictive - regarding the stochasticity of the input. Hundreds of papers covering a wide range of applications appear every year related to the extraction of modal properties from output measurement data in more than two dozen mechanical, aerospace and civil engineering journals. In little more than a decade, concepts of blind source separation (BSS) from the field of acoustic signal processing have been adopted by several researchers and shown that they can be attractive tools to undertake output-only modal identification. Originally intended to separate distinct audio sources from a mixture of recordings, mathematical equivalence to problems in linear structural dynamics have since been firmly established. This has enabled many of the developments in the field of BSS to be modified and applied to output-only modal identification problems. This paper reviews over hundred articles related to the application of BSS and their variants to output-only modal identification. The main contribution of the paper is to present a literature review of the papers which have appeared on the subject. While a brief treatment of the basic ideas are presented where relevant, a comprehensive and critical explanation of their contents is not attempted. Specific issues related to output-only modal identification and the relative advantages and limitations of BSS methods both from theoretical and application standpoints are discussed. Gap areas requiring additional work are also summarized and the paper concludes with possible future trends in this area.

Identification of pesticide varieties by detecting characteristics of Chlorella pyrenoidosa using Visible/Near infrared hyperspectral imaging and Raman microspectroscopy technology.

PubMed

Shao, Yongni; Li, Yuan; Jiang, Linjun; Pan, Jian; He, Yong; Dou, Xiaoming

2016-11-01

The main goal of this research is to examine the feasibility of applying Visible/Near-infrared hyperspectral imaging (Vis/NIR-HSI) and Raman microspectroscopy technology for non-destructive identification of pesticide varieties (glyphosate and butachlor). Both mentioned technologies were explored to investigate how internal elements or characteristics of Chlorella pyrenoidosa change when pesticides are applied, and in the meantime, to identify varieties of the pesticides during this procedure. Successive projections algorithm (SPA) was introduced to our study to identify seven most effective wavelengths. With those wavelengths suggested by SPA, a model of the linear discriminant analysis (LDA) was established to classify the pesticide varieties, and the correct classification rate of the SPA-LDA model reached as high as 100%. For the Raman technique, a few partial least squares discriminant analysis models were established with different preprocessing methods from which we also identified one processing approach that achieved the most optimal result. The sensitive wavelengths (SWs) which are related to algae's pigment were chosen, and a model of LDA was established with the correct identification reached a high level of 90.0%. The results showed that both Vis/NIR-HSI and Raman microspectroscopy techniques are capable to identify pesticide varieties in an indirect but effective way, and SPA is an effective wavelength extracting method. The SWs corresponding to microalgae pigments, which were influenced by pesticides, could also help to characterize different pesticide varieties and benefit the variety identification. Copyright © 2016 Elsevier Ltd. All rights reserved.

Particle identification algorithms for the PANDA Endcap Disc DIRC

NASA Astrophysics Data System (ADS)

Schmidt, M.; Ali, A.; Belias, A.; Dzhygadlo, R.; Gerhardt, A.; Götzen, K.; Kalicy, G.; Krebs, M.; Lehmann, D.; Nerling, F.; Patsyuk, M.; Peters, K.; Schepers, G.; Schmitt, L.; Schwarz, C.; Schwiening, J.; Traxler, M.; Böhm, M.; Eyrich, W.; Lehmann, A.; Pfaffinger, M.; Uhlig, F.; Düren, M.; Etzelmüller, E.; Föhl, K.; Hayrapetyan, A.; Kreutzfeld, K.; Merle, O.; Rieke, J.; Wasem, T.; Achenbach, P.; Cardinali, M.; Hoek, M.; Lauth, W.; Schlimme, S.; Sfienti, C.; Thiel, M.

2017-12-01

The Endcap Disc DIRC has been developed to provide an excellent particle identification for the future PANDA experiment by separating pions and kaons up to a momentum of 4 GeV/c with a separation power of 3 standard deviations in the polar angle region from 5o to 22o. This goal will be achieved using dedicated particle identification algorithms based on likelihood methods and will be applied in an offline analysis and online event filtering. This paper evaluates the resulting PID performance using Monte-Carlo simulations to study basic single track PID as well as the analysis of complex physics channels. The online reconstruction algorithm has been tested with a Virtex4 FGPA card and optimized regarding the resulting constraints.

Expansion of Microbial Forensics

PubMed Central

Schmedes, Sarah E.; Sajantila, Antti

2016-01-01

Microbial forensics has been defined as the discipline of applying scientific methods to the analysis of evidence related to bioterrorism, biocrimes, hoaxes, or the accidental release of a biological agent or toxin for attribution purposes. Over the past 15 years, technology, particularly massively parallel sequencing, and bioinformatics advances now allow the characterization of microorganisms for a variety of human forensic applications, such as human identification, body fluid characterization, postmortem interval estimation, and biocrimes involving tracking of infectious agents. Thus, microbial forensics should be more broadly described as the discipline of applying scientific methods to the analysis of microbial evidence in criminal and civil cases for investigative purposes. PMID:26912746

Perceptron ensemble of graph-based positive-unlabeled learning for disease gene identification.

PubMed

Jowkar, Gholam-Hossein; Mansoori, Eghbal G

2016-10-01

Identification of disease genes, using computational methods, is an important issue in biomedical and bioinformatics research. According to observations that diseases with the same or similar phenotype have the same biological characteristics, researchers have tried to identify genes by using machine learning tools. In recent attempts, some semi-supervised learning methods, called positive-unlabeled learning, is used for disease gene identification. In this paper, we present a Perceptron ensemble of graph-based positive-unlabeled learning (PEGPUL) on three types of biological attributes: gene ontologies, protein domains and protein-protein interaction networks. In our method, a reliable set of positive and negative genes are extracted using co-training schema. Then, the similarity graph of genes is built using metric learning by concentrating on multi-rank-walk method to perform inference from labeled genes. At last, a Perceptron ensemble is learned from three weighted classifiers: multilevel support vector machine, k-nearest neighbor and decision tree. The main contributions of this paper are: (i) incorporating the statistical properties of gene data through choosing proper metrics, (ii) statistical evaluation of biological features, and (iii) noise robustness characteristic of PEGPUL via using multilevel schema. In order to assess PEGPUL, we have applied it on 12950 disease genes with 949 positive genes from six class of diseases and 12001 unlabeled genes. Compared with some popular disease gene identification methods, the experimental results show that PEGPUL has reasonable performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spectral algorithm for non-destructive damage localisation: Application to an ancient masonry arch model

NASA Astrophysics Data System (ADS)

Masciotta, Maria-Giovanna; Ramos, Luís F.; Lourenço, Paulo B.; Vasta, Marcello

2017-02-01

Structural monitoring and vibration-based damage identification methods are fundamental tools for condition assessment and early-stage damage identification, especially when dealing with the conservation of historical constructions and the maintenance of strategic civil structures. However, although the substantial advances in the field, several issues must still be addressed to broaden the application range of such tools and to assert their reliability. This study deals with the experimental validation of a novel method for non-destructive damage identification purposes. This method is based on the use of spectral output signals and has been recently validated by the authors through a numerical simulation. After a brief insight into the basic principles of the proposed approach, the spectral-based technique is applied to identify the experimental damage induced on a masonry arch through statically increasing loading. Once the direct and cross spectral density functions of the nodal response processes are estimated, the system's output power spectrum matrix is built and decomposed in eigenvalues and eigenvectors. The present study points out how the extracted spectral eigenparameters contribute to the damage analysis allowing to detect the occurrence of damage and to locate the target points where the cracks appear during the experimental tests. The sensitivity of the spectral formulation to the level of noise in the modal data is investigated and discussed. As a final evaluation criterion, the results from the spectrum-driven method are compared with the ones obtained from existing non-model based damage identification methods.

Identification of suitable sites for mountain ginseng cultivation using GIS and geo-temperature.

PubMed

Kang, Hag Mo; Choi, Soo Im; Kim, Hyun

2016-01-01

This study was conducted to explore an accurate site identification technique using a geographic information system (GIS) and geo-temperature (gT) for locating suitable sites for growing cultivated mountain ginseng (CMG; Panax ginseng), which is highly sensitive to the environmental conditions in which it grows. The study site was Jinan-gun, South Korea. The spatial resolution for geographic data was set at 10 m × 10 m, and the temperatures for various climatic factors influencing CMG growth were calculated by averaging the 3-year temperatures obtained from the automatic weather stations of the Korea Meteorological Administration. Identification of suitable sites for CMG cultivation was undertaken using both a conventional method and a new method, in which the gT was added as one of the most important factors for crop cultivation. The results yielded by the 2 methods were then compared. When the gT was added as an additional factor (new method), the proportion of suitable sites identified decreased by 0.4 % compared with the conventional method. However, the proportion matching real CMG cultivation sites increased by 3.5 %. Moreover, only 68.2 % corresponded with suitable sites identified using the conventional factors; i.e., 31.8 % were newly detected suitable sites. The accuracy of GIS-based identification of suitable CMG cultivation sites improved by applying the temperature factor (i.e., gT) in addition to the conventionally used factors.

Study on Urban Heat Island Intensity Level Identification Based on an Improved Restricted Boltzmann Machine.

PubMed

Zhang, Yang; Jiang, Ping; Zhang, Hongyan; Cheng, Peng

2018-01-23

Thermal infrared remote sensing has become one of the main technology methods used for urban heat island research. When applying urban land surface temperature inversion of the thermal infrared band, problems with intensity level division arise because the method is subjective. However, this method is one of the few that performs heat island intensity level identification. This paper will build an intensity level identifier for an urban heat island, by using weak supervision and thought-based learning in an improved, restricted Boltzmann machine (RBM) model. The identifier automatically initializes the annotation and optimizes the model parameters sequentially until the target identifier is completed. The algorithm needs very little information about the weak labeling of the target training sample and generates an urban heat island intensity spatial distribution map. This study can provide reliable decision-making support for urban ecological planning and effective protection of urban ecological security. The experimental results showed the following: (1) The heat island effect in Wuhan is existent and intense. Heat island areas are widely distributed. The largest heat island area is in Wuhan, followed by the sub-green island. The total area encompassed by heat island and strong island levels accounts for 54.16% of the land in Wuhan. (2) Partially based on improved RBM identification, this method meets the research demands of determining the spatial distribution characteristics of the internal heat island effect; its identification accuracy is superior to that of comparable methods.

Study on Urban Heat Island Intensity Level Identification Based on an Improved Restricted Boltzmann Machine

PubMed Central

Jiang, Ping; Zhang, Hongyan; Cheng, Peng

2018-01-01

Thermal infrared remote sensing has become one of the main technology methods used for urban heat island research. When applying urban land surface temperature inversion of the thermal infrared band, problems with intensity level division arise because the method is subjective. However, this method is one of the few that performs heat island intensity level identification. This paper will build an intensity level identifier for an urban heat island, by using weak supervision and thought-based learning in an improved, restricted Boltzmann machine (RBM) model. The identifier automatically initializes the annotation and optimizes the model parameters sequentially until the target identifier is completed. The algorithm needs very little information about the weak labeling of the target training sample and generates an urban heat island intensity spatial distribution map. This study can provide reliable decision-making support for urban ecological planning and effective protection of urban ecological security. The experimental results showed the following: (1) The heat island effect in Wuhan is existent and intense. Heat island areas are widely distributed. The largest heat island area is in Wuhan, followed by the sub-green island. The total area encompassed by heat island and strong island levels accounts for 54.16% of the land in Wuhan. (2) Partially based on improved RBM identification, this method meets the research demands of determining the spatial distribution characteristics of the internal heat island effect; its identification accuracy is superior to that of comparable methods. PMID:29360786

Application of permanents of square matrices for DNA identification in multiple-fatality cases

PubMed Central

2013-01-01

Background DNA profiling is essential for individual identification. In forensic medicine, the likelihood ratio (LR) is commonly used to identify individuals. The LR is calculated by comparing two hypotheses for the sample DNA: that the sample DNA is identical or related to a reference DNA, and that it is randomly sampled from a population. For multiple-fatality cases, however, identification should be considered as an assignment problem, and a particular sample and reference pair should therefore be compared with other possibilities conditional on the entire dataset. Results We developed a new method to compute the probability via permanents of square matrices of nonnegative entries. As the exact permanent is known as a #P-complete problem, we applied the Huber–Law algorithm to approximate the permanents. We performed a computer simulation to evaluate the performance of our method via receiver operating characteristic curve analysis compared with LR under the assumption of a closed incident. Differences between the two methods were well demonstrated when references provided neither obligate alleles nor impossible alleles. The new method exhibited higher sensitivity (0.188 vs. 0.055) at a threshold value of 0.999, at which specificity was 1, and it exhibited higher area under a receiver operating characteristic curve (0.990 vs. 0.959, P = 9.6E-15). Conclusions Our method therefore offers a solution for a computationally intensive assignment problem and may be a viable alternative to LR-based identification for closed-incident multiple-fatality cases. PMID:23962363

FAMIAS - A userfriendly new software tool for the mode identification of photometric and spectroscopic times series

NASA Astrophysics Data System (ADS)

Zima, W.

2008-12-01

FAMIAS (Frequency Analysis and Mode Identification for AsteroSeismology) is a collection of state-of-the-art software tools for the analysis of photometric and spectroscopic time series data. It is one of the deliverables of the Work Package NA5: Asteroseismology of the European Coordination Action in Helio- and Asteroseismology (HELAS1 ). Two main sets of tools are incorporated in FAMIAS. The first set allows to search for pe- riodicities in the data using Fourier and non-linear least-squares fitting algorithms. The other set allows to carry out a mode identification for the detected pulsation frequencies to deter- mine their pulsational quantum numbers, the harmonic degree, ℓ, and the azimuthal order, m. For the spectroscopic mode identification, the Fourier parameter fit method and the moment method are available. The photometric mode identification is based on pre-computed grids of atmospheric parameters and non-adiabatic observables, and uses the method of amplitude ratios and phase differences in different filters. The types of stars to which FAMIAS is appli- cable are main-sequence pulsators hotter than the Sun. This includes the Gamma Dor stars, Delta Sct stars, the slowly pulsating B stars and the Beta Cep stars - basically all pulsating main-sequence stars, for which empirical mode identification is required to successfully carry out asteroseismology. The complete manual for FAMIAS is published in a special issue of Communications in Asteroseismology, Vol 155. The homepage of FAMIAS2 provides the possibility to download the software and to read the on-line documentation.

Impact force identification for composite helicopter blades using minimal sensing

NASA Astrophysics Data System (ADS)

Budde, Carson N.

In this research a method for online impact identification using minimal sensors is developed for rotor hubs with composite blades. Modal impact data and the corresponding responses are recorded at several locations to develop a frequency response function model for each composite blade on the rotor hub. The frequency response model for each blade is used to develop an impact identification algorithm which can be used to identify the location and magnitude of impacts. Impacts are applied in two experimental setups, including a four-blade spin test rig and a cantilevered full-sized composite blade. The impacts are estimated to have been applied at the correct location 92.3% of the time for static fiberglass blades, 97.4% of the time for static carbon fiber blades and 99.2% of the time for a full sized-static blade. The estimated location is assessed further and determined to have been estimated in the correct chord position 96.1% of the time for static fiberglass, 100% of the time for carbon fiber blades and 99.2% of the time for the full-sized blades. Projectile impacts are also applied statically and during rotation to the carbon fiber blades on the spin test rig at 57 and 83 RPM. The applied impacts can be located to the correct position 63.9%, 41.7% and 33.3% for the 0, 57 and 83 RPM speeds, respectively, while the correct chord location is estimated 100% of the time. The impact identification algorithm also estimates the force of an impact with an average percent difference of 4.64, 2.61 and 1.00 for static fiberglass, full sized, and carbon fiber blades, respectively. Using a load cell and work equations, the force of impact for a projectile fired from a dynamic firing setup is estimated at about 400 N. The average force measured for applied projectile impacts to the carbon fiber blades, rotating at 0, 57 and 83 RPM, is 368.8, 373.7 and 432.4 N, respectively.

A network approach for identifying and delimiting biogeographical regions.

PubMed

Vilhena, Daril A; Antonelli, Alexandre

2015-04-24

Biogeographical regions (geographically distinct assemblages of species and communities) constitute a cornerstone for ecology, biogeography, evolution and conservation biology. Species turnover measures are often used to quantify spatial biodiversity patterns, but algorithms based on similarity can be sensitive to common sampling biases in species distribution data. Here we apply a community detection approach from network theory that incorporates complex, higher-order presence-absence patterns. We demonstrate the performance of the method by applying it to all amphibian species in the world (c. 6,100 species), all vascular plant species of the USA (c. 17,600) and a hypothetical data set containing a zone of biotic transition. In comparison with current methods, our approach tackles the challenges posed by transition zones and succeeds in retrieving a larger number of commonly recognized biogeographical regions. This method can be applied to generate objective, data-derived identification and delimitation of the world's biogeographical regions.

Optimized System Identification

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Longman, Richard W.

1999-01-01

In system identification, one usually cares most about finding a model whose outputs are as close as possible to the true system outputs when the same input is applied to both. However, most system identification algorithms do not minimize this output error. Often they minimize model equation error instead, as in typical least-squares fits using a finite-difference model, and it is seen here that this distinction is significant. Here, we develop a set of system identification algorithms that minimize output error for multi-input/multi-output and multi-input/single-output systems. This is done with sequential quadratic programming iterations on the nonlinear least-squares problems, with an eigendecomposition to handle indefinite second partials. This optimization minimizes a nonlinear function of many variables, and hence can converge to local minima. To handle this problem, we start the iterations from the OKID (Observer/Kalman Identification) algorithm result. Not only has OKID proved very effective in practice, it minimizes an output error of an observer which has the property that as the data set gets large, it converges to minimizing the criterion of interest here. Hence, it is a particularly good starting point for the nonlinear iterations here. Examples show that the methods developed here eliminate the bias that is often observed using any system identification methods of either over-estimating or under-estimating the damping of vibration modes in lightly damped structures.

In situ Identification of Labile Precursor Compounds and their Short-lived Intermediates in Plants using in vivo Nanospray High-resolution Mass Spectrometry.

PubMed

Chang, Qing; Peng, Yue'e; Shi, Bin; Dan, Conghui; Yang, Yijun; Shuai, Qin

2016-05-01

Many secondary metabolites in plants are labile compounds which under environmental stress, are difficult to detect and track due to the lack of rapid in situ identification techniques, making plant metabolomics research difficult. Therefore, developing a reliable analytical method for rapid in situ identification of labile compounds and their short-lived intermediates in plants is of great importance. To develop under atmospheric pressure, a rapid in situ method for effective identification of labile compounds and their short-lived intermediates in fresh plants. An in vivo nanospray high-resolution mass spectrometry (HR-MS) method was used for rapid capture of labile compounds and their short-lived intermediates in plants. A quartz capillary was partially inserted into fresh plant tissues, and the liquid flowed out through the capillary tube owing to the capillary effect. A high direct current (d.c.) voltage was applied to the plant to generate a spray of charged droplets from the tip of the capillary carrying bioactive molecules toward the inlet of mass spectrometer for full-scan and MS/MS analysis. Many labile compounds and short-lived intermediates were identified via this method: including glucosinolates and their short-lived intermediates (existing for only 10 s) in Raphanus sativus roots, alliin and its conversion intermediate (existing for 20 s) in Allium sativum and labile precursor compound chlorogenic acid in Malus pumila Mill. The method is an effective approach for in situ identification of internal labile compounds and their short-lived intermediates in fresh plants and it can be used as an auxiliary tool to explore the degradation mechanisms of new labile plant compounds. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

On-site identification of meat species in processed foods by a rapid real-time polymerase chain reaction system.

PubMed

Furutani, Shunsuke; Hagihara, Yoshihisa; Nagai, Hidenori

2017-09-01

Correct labeling of foods is critical for consumers who wish to avoid a specific meat species for religious or cultural reasons. Therefore, gene-based point-of-care food analysis by real-time Polymerase Chain Reaction (PCR) is expected to contribute to the quality control in the food industry. In this study, we perform rapid identification of meat species by our portable rapid real-time PCR system, following a very simple DNA extraction method. Applying these techniques, we correctly identified beef, pork, chicken, rabbit, horse, and mutton in processed foods in 20min. Our system was sensitive enough to detect the interfusion of about 0.1% chicken egg-derived DNA in a processed food sample. Our rapid real-time PCR system is expected to contribute to the quality control in food industries because it can be applied for the identification of meat species, and future applications can expand its functionality to the detection of genetically modified organisms or mutations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of two matrix-assisted laser desorption ionization-time of flight mass spectrometry methods with conventional phenotypic identification for routine identification of bacteria to the species level.

PubMed

Cherkaoui, Abdessalam; Hibbs, Jonathan; Emonet, Stéphane; Tangomo, Manuela; Girard, Myriam; Francois, Patrice; Schrenzel, Jacques

2010-04-01

Bacterial identification relies primarily on culture-based methodologies requiring 24 h for isolation and an additional 24 to 48 h for species identification. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is an emerging technology newly applied to the problem of bacterial species identification. We evaluated two MALDI-TOF MS systems with 720 consecutively isolated bacterial colonies under routine clinical laboratory conditions. Isolates were analyzed in parallel on both devices, using the manufacturers' default recommendations. We compared MS with conventional biochemical test system identifications. Discordant results were resolved with "gold standard" 16S rRNA gene sequencing. The first MS system (Bruker) gave high-confidence identifications for 680 isolates, of which 674 (99.1%) were correct; the second MS system (Shimadzu) gave high-confidence identifications for 639 isolates, of which 635 (99.4%) were correct. Had MS been used for initial testing and biochemical identification used only in the absence of high-confidence MS identifications, the laboratory would have saved approximately US$5 per isolate in marginal costs and reduced average turnaround time by more than an 8-h shift, with no loss in accuracy. Our data suggest that implementation of MS as a first test strategy for one-step species identification would improve timeliness and reduce isolate identification costs in clinical bacteriology laboratories now.

Research in applied mathematics, numerical analysis, and computer science

NASA Technical Reports Server (NTRS)

1984-01-01

Research conducted at the Institute for Computer Applications in Science and Engineering (ICASE) in applied mathematics, numerical analysis, and computer science is summarized and abstracts of published reports are presented. The major categories of the ICASE research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers.

Identification of functional modules that correlate with phenotypic difference: the influence of network topology

PubMed Central

2010-01-01

One of the important challenges to post-genomic biology is relating observed phenotypic alterations to the underlying collective alterations in genes. Current inferential methods, however, invariably omit large bodies of information on the relationships between genes. We present a method that takes account of such information - expressed in terms of the topology of a correlation network - and we apply the method in the context of current procedures for gene set enrichment analysis. PMID:20187943

A comparison of heuristic and model-based clustering methods for dietary pattern analysis.

PubMed

Greve, Benjamin; Pigeot, Iris; Huybrechts, Inge; Pala, Valeria; Börnhorst, Claudia

2016-02-01

Cluster analysis is widely applied to identify dietary patterns. A new method based on Gaussian mixture models (GMM) seems to be more flexible compared with the commonly applied k-means and Ward's method. In the present paper, these clustering approaches are compared to find the most appropriate one for clustering dietary data. The clustering methods were applied to simulated data sets with different cluster structures to compare their performance knowing the true cluster membership of observations. Furthermore, the three methods were applied to FFQ data assessed in 1791 children participating in the IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants) Study to explore their performance in practice. The GMM outperformed the other methods in the simulation study in 72 % up to 100 % of cases, depending on the simulated cluster structure. Comparing the computationally less complex k-means and Ward's methods, the performance of k-means was better in 64-100 % of cases. Applied to real data, all methods identified three similar dietary patterns which may be roughly characterized as a 'non-processed' cluster with a high consumption of fruits, vegetables and wholemeal bread, a 'balanced' cluster with only slight preferences of single foods and a 'junk food' cluster. The simulation study suggests that clustering via GMM should be preferred due to its higher flexibility regarding cluster volume, shape and orientation. The k-means seems to be a good alternative, being easier to use while giving similar results when applied to real data.

Multi-resolution analysis for ear recognition using wavelet features

NASA Astrophysics Data System (ADS)

Shoaib, M.; Basit, A.; Faye, I.

2016-11-01

Security is very important and in order to avoid any physical contact, identification of human when they are moving is necessary. Ear biometric is one of the methods by which a person can be identified using surveillance cameras. Various techniques have been proposed to increase the ear based recognition systems. In this work, a feature extraction method for human ear recognition based on wavelet transforms is proposed. The proposed features are approximation coefficients and specific details of level two after applying various types of wavelet transforms. Different wavelet transforms are applied to find the suitable wavelet. Minimum Euclidean distance is used as a matching criterion. Results achieved by the proposed method are promising and can be used in real time ear recognition system.

Fish species identification using PCR-RFLP analysis and lab-on-a-chip capillary electrophoresis: application to detect white fish species in food products and an interlaboratory study.

PubMed

Dooley, John J; Sage, Helen D; Clarke, Marie-Anne L; Brown, Helen M; Garrett, Stephen D

2005-05-04

Identification of 10 white fish species associated with U.K. food products was achieved using PCR-RFLP of the mitochondrial cytochrome b gene. Use of lab-on-a-chip capillary electrophoresis for end-point analysis enabled accurate sizing of DNA fragments and identification of fish species at a level of 5% (w/w) in a fish admixture. One restriction enzyme, DdeI, allowed discrimination of eight species. When combined with NlaIII and HaeIII, specific profiles for all 10 species were generated. The method was applied to a range of products and subjected to an interlaboratory study carried out by five U.K. food control laboratories. One hundred percent correct identification of single species samples and six of nine admixture samples was achieved by all laboratories. The results indicated that fish species identification could be carried out using a database of PCR-RFLP profiles without the need for reference materials.

A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

NASA Astrophysics Data System (ADS)

Lee, Dong-Sup; Cho, Dae-Seung; Kim, Kookhyun; Jeon, Jae-Jin; Jung, Woo-Jin; Kang, Myeng-Hwan; Kim, Jae-Ho

2015-01-01

Independent Component Analysis (ICA), one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: instability and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to validate the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.

Quantitative Index and Abnormal Alarm Strategy Using Sensor-Dependent Vibration Data for Blade Crack Identification in Centrifugal Booster Fans

PubMed Central

Chen, Jinglong; Sun, Hailiang; Wang, Shuai; He, Zhengjia

2016-01-01

Centrifugal booster fans are important equipment used to recover blast furnace gas (BFG) for generating electricity, but blade crack faults (BCFs) in centrifugal booster fans can lead to unscheduled breakdowns and potentially serious accidents, so in this work quantitative fault identification and an abnormal alarm strategy based on acquired historical sensor-dependent vibration data is proposed for implementing condition-based maintenance for this type of equipment. Firstly, three group dependent sensors are installed to acquire running condition data. Then a discrete spectrum interpolation method and short time Fourier transform (STFT) are applied to preliminarily identify the running data in the sensor-dependent vibration data. As a result a quantitative identification and abnormal alarm strategy based on compound indexes including the largest Lyapunov exponent and relative energy ratio at the second harmonic frequency component is proposed. Then for validation the proposed blade crack quantitative identification and abnormality alarm strategy is applied to analyze acquired experimental data for centrifugal booster fans and it has successfully identified incipient blade crack faults. In addition, the related mathematical modelling work is also introduced to investigate the effects of mistuning and cracks on the vibration features of centrifugal impellers and to explore effective techniques for crack detection. PMID:27171083

Applications of surface metrology in firearm identification

NASA Astrophysics Data System (ADS)

Zheng, X.; Soons, J.; Vorburger, T. V.; Song, J.; Renegar, T.; Thompson, R.

2014-01-01

Surface metrology is commonly used to characterize functional engineering surfaces. The technologies developed offer opportunities to improve forensic toolmark identification. Toolmarks are created when a hard surface, the tool, comes into contact with a softer surface and causes plastic deformation. Toolmarks are commonly found on fired bullets and cartridge cases. Trained firearms examiners use these toolmarks to link an evidence bullet or cartridge case to a specific firearm, which can lead to a criminal conviction. Currently, identification is typically based on qualitative visual comparison by a trained examiner using a comparison microscope. In 2009, a report by the National Academies called this method into question. Amongst other issues, they questioned the objectivity of visual toolmark identification by firearms examiners. The National Academies recommended the development of objective toolmark identification criteria and confidence limits. The National Institute of Standards and Technology (NIST) have applied its experience in surface metrology to develop objective identification criteria, measurement methods, and reference artefacts for toolmark identification. NIST developed the Standard Reference Material SRM 2460 standard bullet and SRM 2461 standard cartridge case to facilitate quality control and traceability of identifications performed in crime laboratories. Objectivity is improved through measurement of surface topography and application of unambiguous surface similarity metrics, such as the maximum value (ACCFMAX) of the areal cross correlation function. Case studies were performed on consecutively manufactured tools, such as gun barrels and breech faces, to demonstrate that, even in this worst case scenario, all the tested tools imparted unique surface topographies that were identifiable. These studies provide scientific support for toolmark evidence admissibility in criminal court cases.

Talent identification and recruitment in youth soccer: Recruiter's perceptions of the key attributes for player recruitment.

PubMed

Larkin, Paul; O'Connor, Donna

2017-01-01

Using the modified Delphi method, we aimed to understand the attributes youth coaches and recruiters perceive as important when identifying skilled youth performance at the entry level of representative soccer in Australia (i.e., Under 13 years). Furthermore, we also aimed to describe the current methods youth coaches and recruiters use to assess and identify these attributes in youth players. Australian regional youth technical directors and coaches (n = 20) completed a three stage process, including an initial interview and two subsequent questionnaires, whereby attributes and qualities associated with talent identification were rated and justified according to the importance for youth player performance and talent identification. Results indicate a hierarchy of attributes recruiters perceive as important for Under 13 soccer performance, including technical (i.e., first touch, striking the ball, one-versus-one ability, and technical ability under pressure), tactical (i.e., decision-making ability) and psychological attributes (i.e., coachability and positive attitude). In addition, the findings indicated attributes and qualities not emphasised within the talent identification process including, physiological, anthropometrical, sociological and several psychological attributes. It is suggested talent recruiters apply a holistic multidisciplinary approach to talent identification, with the current findings potentially providing initial evidence to suggest recruiters do consider numerous attributes when selecting and identifying youth players.

Talent identification and recruitment in youth soccer: Recruiter’s perceptions of the key attributes for player recruitment

PubMed Central

2017-01-01

Using the modified Delphi method, we aimed to understand the attributes youth coaches and recruiters perceive as important when identifying skilled youth performance at the entry level of representative soccer in Australia (i.e., Under 13 years). Furthermore, we also aimed to describe the current methods youth coaches and recruiters use to assess and identify these attributes in youth players. Australian regional youth technical directors and coaches (n = 20) completed a three stage process, including an initial interview and two subsequent questionnaires, whereby attributes and qualities associated with talent identification were rated and justified according to the importance for youth player performance and talent identification. Results indicate a hierarchy of attributes recruiters perceive as important for Under 13 soccer performance, including technical (i.e., first touch, striking the ball, one-versus-one ability, and technical ability under pressure), tactical (i.e., decision-making ability) and psychological attributes (i.e., coachability and positive attitude). In addition, the findings indicated attributes and qualities not emphasised within the talent identification process including, physiological, anthropometrical, sociological and several psychological attributes. It is suggested talent recruiters apply a holistic multidisciplinary approach to talent identification, with the current findings potentially providing initial evidence to suggest recruiters do consider numerous attributes when selecting and identifying youth players. PMID:28419175

Orientation and mobility training for partially-sighted older adults using an identification cane: a systematic review

PubMed Central

Ballemans, Judith; Kempen, Gertrudis IJM; Zijlstra, GA Rixt

2011-01-01

Objective: This study aimed to provide an overview of the development, content, feasibility, and effectiveness of existing orientation and mobility training programmes in the use of the identification cane. Data sources: A systematic bibliographic database search in PubMed, PsychInfo, ERIC, CINAHL and the Cochrane Library was performed, in combination with the expert consultation (n = 42; orientation and mobility experts), and hand-searching of reference lists. Review methods: Selection criteria included a description of the development, the content, the feasibility, or the effectiveness of orientation and mobility training in the use of the identification cane. Two reviewers independently agreed on eligibility and methodological quality. A narrative/qualitative data analysis method was applied to extract data from obtained documents. Results: The sensitive database search and hand-searching of reference lists revealed 248 potentially relevant abstracts. None met the eligibility criteria. Expert consultation resulted in the inclusion of six documents in which the information presented on the orientation and mobility training in the use of the identification cane was incomplete and of low methodological quality. Conclusion: Our review of the literature showed a lack of well-described protocols and studies on orientation and mobility training in identification cane use. PMID:21795405

Comparison of Real-Time PCR and Conventional Biochemical Methods for Identification of Staphylococcus lugdunensis▿

PubMed Central

Pinsky, Benjamin A.; Samson, Divinia; Ghafghaichi, Laleh; Baron, Ellen J.; Banaei, Niaz

2009-01-01

Staphylococcus lugdunensis is an aggressive, virulent member of the coagulase-negative staphylococci (CoNS) that is responsible for severe, rapidly progressive skin and soft tissue infections and native valve endocarditis. To facilitate prompt identification and appropriate therapy, we describe here a rapid and robust multiplex real-time PCR assay that is able to definitively distinguish S. lugdunensis from other staphylococci. Using melting curve analysis, the assay also identifies Staphylococcus aureus and CoNS other than S. lugdunensis and determines MecA-dependent resistance to methicillin (meticillin). When applied to a panel of well-characterized staphylococcal reference strains, as well as 165 clinical isolates previously identified by conventional methods, the assay was both sensitive and specific for S. lugdunensis, correctly identifying the reference strain and all 47 S. lugdunensis isolates without inappropriate amplification of other staphylococci. Furthermore, rapid biochemical identification using the WEE-TAB system to detect ornithine decarboxylase activity was found to be unsuitable as an alternative to PCR identification, displaying just 31% sensitivity and 77% specificity when tested on a subset (90 isolates) of the clinical strains. We therefore propose that this simple, accurate PCR approach will allow for the routine and timely identification of S. lugdunensis in the clinical microbiology laboratory. PMID:19741081

School District Resources and Identification of Children With Autistic Disorder

PubMed Central

Palmer, Raymond F.; Blanchard, Stephen; Jean, Carlos R.; Mandell, David S.

2005-01-01

Objectives. We estimated the effect of community and school district resources on the identification of children with autistic disorder. Methods. Latent growth curve regression models were applied to school district–level data from one large state. Results. The rate of identification of autistic disorder increased on average by 1.0 child per 10000 per year (P<.001), with statistically significant district variation. After adjustment for district and community characteristics, each increase in decile of school revenue was associated with an increase of 0.16 per 10000 children identified with autistic disorder. The proportion of economically disadvantaged children per district was inversely associated with autistic disorder cases. Conclusions. District revenue was associated with higher proportions of children identified with autistic disorder at baseline and increasing rates of identification when measured longitudinally. Economically disadvantaged communities may need assistance to identify children with autistic spectrum disorders and other developmental delays that require attention. PMID:15623872

The Identification and Quantification of Suberin Monomers of Root and Tuber Periderm from Potato (Solanum tuberosum) as Fatty Acyl tert-Butyldimethylsilyl Derivatives.

PubMed

Company-Arumí, Dolors; Figueras, Mercè; Salvadó, Victoria; Molinas, Marisa; Serra, Olga; Anticó, Enriqueta

2016-11-01

Protective plant lipophilic barriers such as suberin and cutin, with their associated waxes, are complex fatty acyl derived polyesters. Their precise chemical composition is valuable to understand the specific role of each compound to the physiological function of the barrier. To develop a method for the compositional analysis of suberin and associated waxes by gas chromatography (GC) coupled to ion trap-mass spectrometry (IT-MS) using N-(tert-butyldimethylsilyl)-N-methyl-trifluoroacetamide (MTBSTFA) as sylilating reagent, and apply it to compare the suberin of the root and tuber periderm of potato (Solanum tuberosum). Waxes and suberin monomers from root and periderm were extracted subsequently using organic solvents and by methanolysis, and subjected to MTBSTFA derivatisation. GC analyses of periderm extracts were used to optimise the chromatographic method and the compound identification. Quantitative data was obtained using external calibration curves. The method was fully validated and applied for suberin composition analyses of roots and periderm. Wax and suberin compounds were successfully separated and compound identification was based on the specific (M-57) and non-specific ions in mass spectra. The use of calibration curves built with different external standards provided quantitative accurate data and showed that suberin from root contains shorter chained fatty acyl derivatives and a relative predominance of α,ω-alkanedioic acids compared to that of the periderm. We present a method for the analysis of suberin and their associated waxes based on MTBSTFA derivatisation. Moreover, the characteristic root suberin composition may be the adaptive response to its specific regulation of permeability to water and gases. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

PubMed

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

2014-03-01

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

Use of PCR analysis for identification of species and genus of Septoria on grain crops

USDA-ARS?s Scientific Manuscript database

Research on methods for molecular-genetic testing of the Septoria pathogens of wheat was initiated. Two species of septoria were studied: Septoria tritici Rob. et Desm., and Stagonospora nodorum [Berk] Castellani and E.G. Germano. Different protocols for extraction of DNA were applied; the best meth...

Classification of Chemical Substances Using Particulate Representations of Matter: An Analysis of Student Thinking

ERIC Educational Resources Information Center

Stains, Marilyne; Talanquer, Vicente

2007-01-01

We applied a mixed-method research design to investigate the patterns of reasoning used by novice undergraduate chemistry students to classify chemical substances as elements, compounds, or mixtures based on their particulate representations. We were interested in the identification of the representational features that students use to build a…

Identification of Genetic Loci Underlying the Phenotypic Constructs of Autism Spectrum Disorders

ERIC Educational Resources Information Center

Liu, Xiao-Qing; Georgiades, Stelios; Duku, Eric; Thompson, Ann; Devlin, Bernie; Cook, Edwin H.; Wijsman, Ellen M.; Paterson, Andrew D.; Szatmari, Peter

2011-01-01

Objective: To investigate the underlying phenotypic constructs in autism spectrum disorders (ASD) and to identify genetic loci that are linked to these empirically derived factors. Method: Exploratory factor analysis was applied to two datasets with 28 selected Autism Diagnostic Interview-Revised (ADI-R) algorithm items. The first dataset was from…

Application of the remote-sensing communication model to a time-sensitive wildfire remote-sensing system

Treesearch

Christopher D. Lippitt; Douglas A. Stow; Philip J. Riggan

2016-01-01

Remote sensing for hazard response requires a priori identification of sensor, transmission, processing, and distribution methods to permit the extraction of relevant information in timescales sufficient to allow managers to make a given time-sensitive decision. This study applies and demonstrates the utility of the Remote Sensing Communication...

Molecular identification of Gd A- and Gd B- G6PD deficient variants by ARMS-PCR in a Tunisian population.

PubMed

Haloui, Sabrine; Laouini, Naouel; Sahli, Chaima Abdelhafidh; Daboubi, Rim; Becher, Mariem; Jouini, Latifa; Kazdaghli, Kalthoum; Tinsa, Faten; Cherif, Semia; Khemiri, Monia; Fredj, Sondess Hadj; Othmani, Rim; Ouali, Faida; Siala, Hajer; Toumi, Nour El Houda; Barsaoui, Sihem; Bibi, Amina; Messaoud, Taieb

2016-01-01

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is the most common enzymopathy. More than 200 mutations in the G6PD gene have been described. In Tunisia, the A-African and the B-Mediterranean mutations predominate the mutational spectrum. The purpose of this study was to apply the amplification refractory mutation system (ARMS-PCR) to the identification of Gd A+, Gd A- and Gd B- variants in a cohort of deficient individuals and to establish a phenotype/genotype association. 90 subjects were screened for enzymatic deficiency by spectrophotometric assay. The molecular analyses were performed in a group of 50 unrelated patients. Of the 54 altered chromosomes examined, 60% had the Gd A- mutation, 18% showed the Gd B- mutation and in 20% of cases, no mutations have been identified. The ARMS-PCR showed complete concordance with the endonuclease cleavage reference method and agreed perfectly with previous Tunisian studies where Gd A- and Gd B- were the most encountered. Also, similarities in spectrum mutations with North African and Mediterranean countries suggest gene migration from Africa to Europe through Spain. In conclusion, ARMS has been introduced in this study for common G6PD alleles identification in Tunisia. It gives some advantages compared to the traditional endonuclease digestion method since it is more convenient and timesaving and also offers the possibility to be applied in mass screening surveys.

Identification of unusual events in multi-channel bridge monitoring data

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr; Brownjohn, James Mark William; Moyo, Pilate

2004-03-01

Continuously operating instrumented structural health monitoring (SHM) systems are becoming a practical alternative to replace visual inspection for assessment of condition and soundness of civil infrastructure such as bridges. However, converting large amounts of data from an SHM system into usable information is a great challenge to which special signal processing techniques must be applied. This study is devoted to identification of abrupt, anomalous and potentially onerous events in the time histories of static, hourly sampled strains recorded by a multi-sensor SHM system installed in a major bridge structure and operating continuously for a long time. Such events may result, among other causes, from sudden settlement of foundation, ground movement, excessive traffic load or failure of post-tensioning cables. A method of outlier detection in multivariate data has been applied to the problem of finding and localising sudden events in the strain data. For sharp discrimination of abrupt strain changes from slowly varying ones wavelet transform has been used. The proposed method has been successfully tested using known events recorded during construction of the bridge, and later effectively used for detection of anomalous post-construction events.

Method for non-referential defect characterization using fractal encoding and active contours

DOEpatents

Gleason, Shaun S [Knoxville, TN; Sari-Sarraf, Hamed [Lubbock, TX

2007-05-15

A method for identification of anomalous structures, such as defects, includes the steps of providing a digital image and applying fractal encoding to identify a location of at least one anomalous portion of the image. The method does not require a reference image to identify the location of the anomalous portion. The method can further include the step of initializing an active contour based on the location information obtained from the fractal encoding step and deforming an active contour to enhance the boundary delineation of the anomalous portion.

Modal identification of structures by a novel approach based on FDD-wavelet method

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2014-02-01

An important application of system identification in structural dynamics is the determination of natural frequencies, mode shapes and damping ratios during operation which can then be used for calibrating numerical models. In this paper, the combination of two advanced methods of Operational Modal Analysis (OMA) called Frequency Domain Decomposition (FDD) and Continuous Wavelet Transform (CWT) based on novel cyclic averaging of correlation functions (CACF) technique are used for identification of dynamic properties. By using this technique, the autocorrelation of averaged correlation functions is used instead of original signals. Integration of FDD and CWT methods is used to overcome their deficiency and take advantage of the unique capabilities of these methods. The FDD method is able to accurately estimate the natural frequencies and mode shapes of structures in the frequency domain. On the other hand, the CWT method is in the time-frequency domain for decomposition of a signal at different frequencies and determines the damping coefficients. In this paper, a new formulation applied to the wavelet transform of the averaged correlation function of an ambient response is proposed. This application causes to accurate estimation of damping ratios from weak (noise) or strong (earthquake) vibrations and long or short duration record. For this purpose, the modified Morlet wavelet having two free parameters is used. The optimum values of these two parameters are obtained by employing a technique which minimizes the entropy of the wavelet coefficients matrix. The capabilities of the novel FDD-Wavelet method in the system identification of various dynamic systems with regular or irregular distribution of mass and stiffness are illustrated. This combined approach is superior to classic methods and yields results that agree well with the exact solutions of the numerical models.

Extending birthday paradox theory to estimate the number of tags in RFID systems.

PubMed

Shakiba, Masoud; Singh, Mandeep Jit; Sundararajan, Elankovan; Zavvari, Azam; Islam, Mohammad Tariqul

2014-01-01

The main objective of Radio Frequency Identification systems is to provide fast identification for tagged objects. However, there is always a chance of collision, when tags transmit their data to the reader simultaneously. Collision is a time-consuming event that reduces the performance of RFID systems. Consequently, several anti-collision algorithms have been proposed in the literature. Dynamic Framed Slotted ALOHA (DFSA) is one of the most popular of these algorithms. DFSA dynamically modifies the frame size based on the number of tags. Since the real number of tags is unknown, it needs to be estimated. Therefore, an accurate tag estimation method has an important role in increasing the efficiency and overall performance of the tag identification process. In this paper, we propose a novel estimation technique for DFSA anti-collision algorithms that applies birthday paradox theory to estimate the number of tags accurately. The analytical discussion and simulation results prove that the proposed method increases the accuracy of tag estimation and, consequently, outperforms previous schemes.

Identification of complex stiffness tensor from waveform reconstruction

NASA Astrophysics Data System (ADS)

Leymarie, N.; Aristégui, C.; Audoin, B.; Baste, S.

2002-03-01

An inverse method is proposed in order to determine the viscoelastic properties of composite-material plates from the plane-wave transmitted acoustic field. Analytical formulations of both the plate transmission coefficient and its first and second derivatives are established, and included in a two-step inversion scheme. Two objective functions to be minimized are then designed by considering the well-known maximum-likelihood principle and by using an analytic signal formulation. Through these innovative objective functions, the robustness of the inversion process against high level of noise in waveforms is improved and the method can be applied to a very thin specimen. The suitability of the inversion process for viscoelastic property identification is demonstrated using simulated data for composite materials with different anisotropy and damping degrees. A study of the effect of the rheologic model choice on the elastic property identification emphasizes the relevance of using a phenomenological description considering viscosity. Experimental characterizations show then the good reliability of the proposed approach. Difficulties arise experimentally for particular anisotropic media.

Identification tibia and fibula bone fracture location using scanline algorithm

NASA Astrophysics Data System (ADS)

Muchtar, M. A.; Simanjuntak, S. E.; Rahmat, R. F.; Mawengkang, H.; Zarlis, M.; Sitompul, O. S.; Winanto, I. D.; Andayani, U.; Syahputra, M. F.; Siregar, I.; Nasution, T. H.

2018-03-01

Fracture is a condition that there is a damage in the continuity of the bone, usually caused by stress, trauma or weak bones. The tibia and fibula are two separated-long bones in the lower leg, closely linked at the knee and ankle. Tibia/fibula fracture often happen when there is too much force applied to the bone that it can withstand. One of the way to identify the location of tibia/fibula fracture is to read X-ray image manually. Visual examination requires more time and allows for errors in identification due to the noise in image. In addition, reading X-ray needs highlighting background to make the objects in X-ray image appear more clearly. Therefore, a method is required to help radiologist to identify the location of tibia/fibula fracture. We propose some image-processing techniques for processing cruris image and Scan line algorithm for the identification of fracture location. The result shows that our proposed method is able to identify it and reach up to 87.5% of accuracy.

Extending Birthday Paradox Theory to Estimate the Number of Tags in RFID Systems

PubMed Central

Shakiba, Masoud; Singh, Mandeep Jit; Sundararajan, Elankovan; Zavvari, Azam; Islam, Mohammad Tariqul

2014-01-01

The main objective of Radio Frequency Identification systems is to provide fast identification for tagged objects. However, there is always a chance of collision, when tags transmit their data to the reader simultaneously. Collision is a time-consuming event that reduces the performance of RFID systems. Consequently, several anti-collision algorithms have been proposed in the literature. Dynamic Framed Slotted ALOHA (DFSA) is one of the most popular of these algorithms. DFSA dynamically modifies the frame size based on the number of tags. Since the real number of tags is unknown, it needs to be estimated. Therefore, an accurate tag estimation method has an important role in increasing the efficiency and overall performance of the tag identification process. In this paper, we propose a novel estimation technique for DFSA anti-collision algorithms that applies birthday paradox theory to estimate the number of tags accurately. The analytical discussion and simulation results prove that the proposed method increases the accuracy of tag estimation and, consequently, outperforms previous schemes. PMID:24752285

Rapid identification of oral Actinomyces species cultivated from subgingival biofilm by MALDI-TOF-MS

PubMed Central

Stingu, Catalina S.; Borgmann, Toralf; Rodloff, Arne C.; Vielkind, Paul; Jentsch, Holger; Schellenberger, Wolfgang; Eschrich, Klaus

2015-01-01

Background Actinomyces are a common part of the residential flora of the human intestinal tract, genitourinary system and skin. Isolation and identification of Actinomyces by conventional methods is often difficult and time consuming. In recent years, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) has become a rapid and simple method to identify bacteria. Objective The present study evaluated a new in-house algorithm using MALDI-TOF-MS for rapid identification of different species of oral Actinomyces cultivated from subgingival biofilm. Design Eleven reference strains and 674 clinical strains were used in this study. All the strains were preliminarily identified using biochemical methods and then subjected to MALDI-TOF-MS analysis using both similarity-based analysis and classification methods (support vector machine [SVM]). The genotype of the reference strains and of 232 clinical strains was identified by sequence analysis of the 16S ribosomal RNA (rRNA). Results The sequence analysis of the 16S rRNA gene of all references strains confirmed their previous identification. The MALDI-TOF-MS spectra obtained from the reference strains and the other clinical strains undoubtedly identified as Actinomyces by 16S rRNA sequencing were used to create the mass spectra reference database. Already a visual inspection of the mass spectra of different species reveals both similarities and differences. However, the differences between them are not large enough to allow a reliable differentiation by similarity analysis. Therefore, classification methods were applied as an alternative approach for differentiation and identification of Actinomyces at the species level. A cross-validation of the reference database representing 14 Actinomyces species yielded correct results for all species which were represented by more than two strains in the database. Conclusions Our results suggest that a combination of MALDI-TOF-MS with powerful classification algorithms, such as SVMs, provide a useful tool for the differentiation and identification of oral Actinomyces. PMID:25597306

[Bacterial identification methods in the microbiology laboratory].

PubMed

Bou, Germán; Fernández-Olmos, Ana; García, Celia; Sáez-Nieto, Juan Antonio; Valdezate, Sylvia

2011-10-01

In order to identify the agent responsible of the infectious process and understanding the pathogenic/pathological implications, clinical course, and to implement an effective antimicrobial therapy, a mainstay in the practice of clinical microbiology is the allocation of species to a microbial isolation. In daily routine practice microbiology laboratory phenotypic techniques are applied to achieve this goal. However, they have some limitations that are seen more clearly for some kinds of microorganism. Molecular methods can circumvent some of these limitations, although its implementation is not universal. This is due to higher costs and the level of expertise required for thei implementation, so molecular methods are often centralized in reference laboratories and centers. Recently, proteomics-based methods made an important breakthrough in the field of diagnostic microbiology and will undoubtedly have a major impact on the future organization of the microbiology services. This paper is a short review of the most noteworthy aspects of the three bacterial identification methods described above used in microbiology laboratories. Copyright © 2011 Elsevier España, S.L. All rights reserved.

Real-time identification of vehicle motion-modes using neural networks

NASA Astrophysics Data System (ADS)

Wang, Lifu; Zhang, Nong; Du, Haiping

2015-01-01

A four-wheel ground vehicle has three body-dominated motion-modes, that is, bounce, roll, and pitch motion-modes. Real-time identification of these motion-modes can make vehicle suspensions, in particular, active suspensions, target on the dominant motion-mode and apply appropriate control strategies to improve its performance with less power consumption. Recently, a motion-mode energy method (MEM) was developed to identify the vehicle body motion-modes. However, this method requires the measurement of full vehicle states and road inputs, which are not always available in practice. This paper proposes an alternative approach to identify vehicle primary motion-modes with acceptable accuracy by employing neural networks (NNs). The effectiveness of the trained NNs is verified on a 10-DOF full-car model under various types of excitation inputs. The results confirm that the proposed method is effective in determining vehicle primary motion-modes with comparable accuracy to the MEM method. Experimental data is further used to validate the proposed method.

[The application of X-ray imaging in forensic medicine].

PubMed

Kučerová, Stěpánka; Safr, Miroslav; Ublová, Michaela; Urbanová, Petra; Hejna, Petr

2014-07-01

X-ray is the most common, basic and essential imaging method used in forensic medicine. It serves to display and localize the foreign objects in the body and helps to detect various traumatic and pathological changes. X-ray imaging is valuable in anthropological assessment of an individual. X-ray allows non-invasive evaluation of important findings before the autopsy and thus selection of the optimal strategy for dissection. Basic indications for postmortem X-ray imaging in forensic medicine include gunshot and explosive fatalities (identification and localization of projectiles or other components of ammunition, visualization of secondary missiles), sharp force injuries (air embolism, identification of the weapon) and motor vehicle related deaths. The method is also helpful for complex injury evaluation in abused victims or in persons where abuse is suspected. Finally, X-ray imaging still remains the gold standard method for identification of unknown deceased. With time modern imaging methods, especially computed tomography and magnetic resonance imaging, are more and more applied in forensic medicine. Their application extends possibilities of the visualization the bony structures toward a more detailed imaging of soft tissues and internal organs. The application of modern imaging methods in postmortem body investigation is known as digital or virtual autopsy. At present digital postmortem imaging is considered as a bloodless alternative to the conventional autopsy.

Gene identification in the congenital disorders of glycosylation type I by whole-exome sequencing.

PubMed

Timal, Sharita; Hoischen, Alexander; Lehle, Ludwig; Adamowicz, Maciej; Huijben, Karin; Sykut-Cegielska, Jolanta; Paprocka, Justyna; Jamroz, Ewa; van Spronsen, Francjan J; Körner, Christian; Gilissen, Christian; Rodenburg, Richard J; Eidhof, Ilse; Van den Heuvel, Lambert; Thiel, Christian; Wevers, Ron A; Morava, Eva; Veltman, Joris; Lefeber, Dirk J

2012-10-01

Congenital disorders of glycosylation type I (CDG-I) form a growing group of recessive neurometabolic diseases. Identification of disease genes is compromised by the enormous heterogeneity in clinical symptoms and the large number of potential genes involved. Until now, gene identification included the sequential application of biochemical methods in blood samples and fibroblasts. In genetically unsolved cases, homozygosity mapping has been applied in consanguineous families. Altogether, this time-consuming diagnostic strategy led to the identification of defects in 17 different CDG-I genes. Here, we applied whole-exome sequencing (WES) in combination with the knowledge of the protein N-glycosylation pathway for gene identification in our remaining group of six unsolved CDG-I patients from unrelated non-consanguineous families. Exome variants were prioritized based on a list of 76 potential CDG-I candidate genes, leading to the rapid identification of one known and two novel CDG-I gene defects. These included the first X-linked CDG-I due to a de novo mutation in ALG13, and compound heterozygous mutations in DPAGT1, together the first two steps in dolichol-PP-glycan assembly, and mutations in PGM1 in two cases, involved in nucleotide sugar biosynthesis. The pathogenicity of the mutations was confirmed by showing the deficient activity of the corresponding enzymes in patient fibroblasts. Combined with these results, the gene defect has been identified in 98% of our CDG-I patients. Our results implicate the potential of WES to unravel disease genes in the CDG-I in newly diagnosed singleton families.

FT-IR spectroscopy as a tool for rapid identification and intra-species characterization of airborne filamentous fungi.

PubMed

Fischer, Guido; Braun, Silvia; Thissen, Ralf; Dott, Wolfgang

2006-01-01

Identification of microfungi is time-consuming due to cultivation and microscopic examination and can be influenced by the interpretation of the macro- and micro-morphological characters observed. Fungal conidia contain mycotoxins that may be present in bioaerosols and thus the capacity for production of mycotoxins (and allergens) needs to be investigated to create a basis for reliable risk assessment in environmental and occupational hygiene. The present investigation aimed to create a simple but sophisticated method for the preparation of samples and the identification of airborne fungi by FT-IR spectroscopy. The method was suited to reproducibly differentiate Aspergillus and Penicillium species on the generic, the species, and the strain level. There are strong indications that strains of one taxon differing in metabolite production can be reliably distinguished by FT-IR spectroscopy (e.g. Aspergillus parasiticus). On the other hand, species from different taxa being similar in secondary metabolite production showed comparably higher similarities. The results obtained here can serve as a basis for the development of a database for species identification and strain characterization of microfungi. The method presented here will improve and facilitate the risk assessment in case of bioaerosol exposure, as strains with different physiological properties (e.g. toxic, non-toxic) could be differentiated. Moreover, it has the potential to significantly improve the identification of microfungi in various fields of applied microbiological research, e.g. high throughput screening in view of specific physiological properties, biodiversity studies, inventories in environmental microbiology, and quality control measures.

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

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

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

2010-02-28

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

Validation of automatic landmark identification for atlas-based segmentation for radiation treatment planning of the head-and-neck region

NASA Astrophysics Data System (ADS)

Leavens, Claudia; Vik, Torbjørn; Schulz, Heinrich; Allaire, Stéphane; Kim, John; Dawson, Laura; O'Sullivan, Brian; Breen, Stephen; Jaffray, David; Pekar, Vladimir

2008-03-01

Manual contouring of target volumes and organs at risk in radiation therapy is extremely time-consuming, in particular for treating the head-and-neck area, where a single patient treatment plan can take several hours to contour. As radiation treatment delivery moves towards adaptive treatment, the need for more efficient segmentation techniques will increase. We are developing a method for automatic model-based segmentation of the head and neck. This process can be broken down into three main steps: i) automatic landmark identification in the image dataset of interest, ii) automatic landmark-based initialization of deformable surface models to the patient image dataset, and iii) adaptation of the deformable models to the patient-specific anatomical boundaries of interest. In this paper, we focus on the validation of the first step of this method, quantifying the results of our automatic landmark identification method. We use an image atlas formed by applying thin-plate spline (TPS) interpolation to ten atlas datasets, using 27 manually identified landmarks in each atlas/training dataset. The principal variation modes returned by principal component analysis (PCA) of the landmark positions were used by an automatic registration algorithm, which sought the corresponding landmarks in the clinical dataset of interest using a controlled random search algorithm. Applying a run time of 60 seconds to the random search, a root mean square (rms) distance to the ground-truth landmark position of 9.5 +/- 0.6 mm was calculated for the identified landmarks. Automatic segmentation of the brain, mandible and brain stem, using the detected landmarks, is demonstrated.

A Pragmatic Smoothing Method for Improving the Quality of the Results in Atomic Spectroscopy

NASA Astrophysics Data System (ADS)

Bennun, Leonardo

2017-07-01

A new smoothing method for the improvement on the identification and quantification of spectral functions based on the previous knowledge of the signals that are expected to be quantified, is presented. These signals are used as weighted coefficients in the smoothing algorithm. This smoothing method was conceived to be applied in atomic and nuclear spectroscopies preferably to these techniques where net counts are proportional to acquisition time, such as particle induced X-ray emission (PIXE) and other X-ray fluorescence spectroscopic methods, etc. This algorithm, when properly applied, does not distort the form nor the intensity of the signal, so it is well suited for all kind of spectroscopic techniques. This method is extremely effective at reducing high-frequency noise in the signal much more efficient than a single rectangular smooth of the same width. As all of smoothing techniques, the proposed method improves the precision of the results, but in this case we found also a systematic improvement on the accuracy of the results. We still have to evaluate the improvement on the quality of the results when this method is applied over real experimental results. We expect better characterization of the net area quantification of the peaks, and smaller Detection and Quantification Limits. We have applied this method to signals that obey Poisson statistics, but with the same ideas and criteria, it could be applied to time series. In a general case, when this algorithm is applied over experimental results, also it would be required that the sought characteristic functions, required for this weighted smoothing method, should be obtained from a system with strong stability. If the sought signals are not perfectly clean, this method should be carefully applied

Identification of multiply charged proteins and amino acid clusters by liquid nitrogen assisted spray ionization mass spectrometry.

PubMed

Kumar Kailasa, Suresh; Hasan, Nazim; Wu, Hui-Fen

2012-08-15

The development of liquid nitrogen assisted spray ionization mass spectrometry (LNASI MS) for the analysis of multiply charged proteins (insulin, ubiquitin, cytochrome c, α-lactalbumin, myoglobin and BSA), peptides (glutathione, HW6, angiotensin-II and valinomycin) and amino acid (arginine) clusters is described. The charged droplets are formed by liquid nitrogen assisted sample spray through a stainless steel nebulizer and transported into mass analyzer for the identification of multiply charged protein ions. The effects of acids and modifier volumes for the efficient ionization of the above analytes in LNASI MS were carefully investigated. Multiply charged proteins and amino acid clusters were effectively identified by LNASI MS. The present approach can effectively detect the multiply charged states of cytochrome c at 400 nM. A comparison between LNASI and ESI, CSI, SSI and V-EASI methods on instrumental conditions, applied temperature and observed charge states for the multiply charged proteins, shows that the LNASI method produces the good quality spectra of amino acid clusters at ambient conditions without applied any electric field and heat. To date, we believe that the LNASI method is the most simple, low cost and provided an alternative paradigm for production of multiply charged ions by LNASI MS, just as ESI-like ions yet no need for applying any electrical field and it could be operated at low temperature for generation of highly charged protein/peptide ions. Copyright © 2012 Elsevier B.V. All rights reserved.

Modified multiplex PCR for identification of Bacillus Calmette-Guérin substrain Tokyo among clinical isolates.

PubMed

Seki, Masaaki; Sato, Akimasa; Honda, Ikuro; Yamazaki, Toshio; Yano, Ikuya; Koyama, Akira; Toida, Ichiro

2005-05-02

When an adverse reaction occurs and a mycobacterial species is isolated from a person vaccinated with Bacillus Calmette-Guérin (BCG) or a patient receiving BCG immunotherapy, it is essential to identify whether the isolate is BCG or another mycobacterial species. However, differentiation of BCG from other members of Mycobacterium tuberculosis complex has been very difficult. Using several specific primer-pairs, Bedwell et al. [Bedwell J, Kairo SK, Behr MA, Bygraves JA. Identification of substrains of BCG vaccine using multiplex PCR. Vaccine 2001; 19: 2146-51] recently reported that they could distinguish BCG substrains. We modified their method to improve differentiation of Tokyo 172 from other members of the M. tuberculosis complex, and examined whether this modified method could be applied to clinical isolates. Our method clearly identified BCG substrain (BCG Tokyo 172) among clinical isolates and easily distinguished between M. tuberculosis and wild-type Mycobacterium bovis.

Mapping the distribution of materials in hyperspectral data using the USGS Material Identification and Characterization Algorithm (MICA)

USGS Publications Warehouse

Kokaly, R.F.; King, T.V.V.; Hoefen, T.M.

2011-01-01

Identifying materials by measuring and analyzing their reflectance spectra has been an important method in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow scientists to detect materials and map their distributions across the landscape. With new satellite-borne hyperspectral sensors planned for the future, for example, HYSPIRI (HYPerspectral InfraRed Imager), robust methods are needed to fully exploit the information content of hyperspectral remote sensing data. A method of identifying and mapping materials using spectral-feature based analysis of reflectance data in an expert-system framework called MICA (Material Identification and Characterization Algorithm) is described in this paper. The core concepts and calculations of MICA are presented. A MICA command file has been developed and applied to map minerals in the full-country coverage of the 2007 Afghanistan HyMap hyperspectral data. ?? 2011 IEEE.

Automated method for identification and artery-venous classification of vessel trees in retinal vessel networks.

PubMed

Joshi, Vinayak S; Reinhardt, Joseph M; Garvin, Mona K; Abramoff, Michael D

2014-01-01

The separation of the retinal vessel network into distinct arterial and venous vessel trees is of high interest. We propose an automated method for identification and separation of retinal vessel trees in a retinal color image by converting a vessel segmentation image into a vessel segment map and identifying the individual vessel trees by graph search. Orientation, width, and intensity of each vessel segment are utilized to find the optimal graph of vessel segments. The separated vessel trees are labeled as primary vessel or branches. We utilize the separated vessel trees for arterial-venous (AV) classification, based on the color properties of the vessels in each tree graph. We applied our approach to a dataset of 50 fundus images from 50 subjects. The proposed method resulted in an accuracy of 91.44% correctly classified vessel pixels as either artery or vein. The accuracy of correctly classified major vessel segments was 96.42%.

On the electrophysiology of aesthetic processing.

PubMed

Jacobsen, Thomas

2013-01-01

One important method that can be applied for gaining an understanding of the underpinning of aesthetics in the brain is that of electrophysiology. Cognitive electrophysiology, in particular, allows the identification of components in a mental processing architecture. The present chapter reviews findings in the neurocognitive psychology of aesthetics, or neuroaesthetics, that have been obtained with the method of event-related brain potentials, as derived from the human electroencephalogram. The cognitive-perceptual bases as well as affective substages of aesthetic processing have been investigated and those are described here. The event-related potential method allows for the identification of mental processing modes in cognitive and aesthetic processing. It also provides an assessment of the mental chronometry of cognitive and affective stages in aesthetic appreciation. As the work described here shows, distinct processes in the brain are engaged in aesthetic judgments. © 2013 Elsevier B.V. All rights reserved.

Application of DNA-based methods in forensic entomology.

PubMed

Wells, Jeffrey D; Stevens, Jamie R

2008-01-01

A forensic entomological investigation can benefit from a variety of widely practiced molecular genotyping methods. The most commonly used is DNA-based specimen identification. Other applications include the identification of insect gut contents and the characterization of the population genetic structure of a forensically important insect species. The proper application of these procedures demands that the analyst be technically expert. However, one must also be aware of the extensive list of standards and expectations that many legal systems have developed for forensic DNA analysis. We summarize the DNA techniques that are currently used in, or have been proposed for, forensic entomology and review established genetic analyses from other scientific fields that address questions similar to those in forensic entomology. We describe how accepted standards for forensic DNA practice and method validation are likely to apply to insect evidence used in a death or other forensic entomological investigation.

Intravital assessment of myelin molecular order with polarimetric multiphoton microscopy

NASA Astrophysics Data System (ADS)

Turcotte, Raphaël; Rutledge, Danette J.; Bélanger, Erik; Dill, Dorothy; Macklin, Wendy B.; Côté, Daniel C.

2016-08-01

Myelin plays an essential role in the nervous system and its disruption in diseases such as multiple sclerosis may lead to neuronal death, thus causing irreversible functional impairments. Understanding myelin biology is therefore of fundamental and clinical importance, but no tools currently exist to describe the fine spatial organization of myelin sheaths in vivo. Here we demonstrate intravital quantification of the myelin molecular structure using a microscopy method based on polarization-resolved coherent Raman scattering. Developmental myelination was imaged noninvasively in live zebrafish. Longitudinal imaging of individual axons revealed changes in myelin organization beyond the diffraction limit. Applied to promyelination drug screening, the method uniquely enabled the identification of focal myelin regions with differential architectures. These observations indicate that the study of myelin biology and the identification of therapeutic compounds will largely benefit from a method to quantify the myelin molecular organization in vivo.

Identification and characterization of chlorogenic acids, chlorogenic acid glycosides and flavonoids from Lonicera henryi L. (Caprifoliaceae) leaves by LC-MSn.

PubMed

Jaiswal, Rakesh; Müller, Heiko; Müller, Anja; Karar, Mohamed Gamaleldin Elsadig; Kuhnert, Nikolai

2014-12-01

The chlorogenic acids, chlorogenic acid glycosides and flavonoids of the leaves of Lonicera henryi L. (Caprifoliaceae) were investigated qualitatively by liquid chromatography tandem mass spectrometry. Thirty-one chlorogenic acids and their glycosides were detected and characterized to their regioisomeric level on the basis of their unique fragmentation pattern in the negative ion mode tandem MS spectra. All of them were extracted for the first time from this source and thirteen of them were not reported previously in nature. For the positive identification of chlorogenic acid glycosides by LC-MS(n), multiple reaction monitoring and targeted MS(n) experiments were performed. We have developed an LC-MS(n) method for the systematic identification of chlorogenic acid glycosides and were also able to discriminate between chlorogenic acids and their isobaric glycosides. It was also possible to discriminate between 5-O-(3'-O-caffeoyl glucosyl)quinic acid and 5-O-(4'-O-caffeoyl glucosyl)quinic acid by LC-MS(n). This method can be applied for the rapid and positive identification of chlorogenic acids and their glycosides in plant materials, food and beverages. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identification of Stenotrophomonas maltophilia strains isolated from environmental and clinical samples: a rapid and efficient procedure.

PubMed

Pinot, C; Deredjian, A; Nazaret, S; Brothier, E; Cournoyer, B; Segonds, C; Favre-Bonté, S

2011-11-01

Aim of the study is to identify accurately Stenotrophomonas maltophilia isolates recovered from environmental and clinical samples. Recovery of Sten. maltophilia-like isolates from soil samples using the vancomycin, imipenem, amphotericin B (VIA) selective agar medium enabled distinction of various morphotype colonies. A set of soil and clinical isolates was tested for species identification using different methods. 16S rDNA analyses showed the dark green with a blue halo morphotype to be typical Sten. maltophilia strains. The API-20NE, Vitek-2 and Biolog phenotypic analyses typically used for the identification of clinical isolates did not perform well on these soil isolates. The species-specific PCR screening targeting Sten. maltophilia 23S rDNA and the multiplex smeD/ggpS PCR, differentiating Sten. maltophilia from Stenotrophomonas rhizophila, were tested for improvement of these identification schemes. The latter multiplex PCR identified all isolates tested in this study, whatever be their origin. Isolation on VIA medium and confirmation of Sten. maltophilia species membership by smeD PCR is proposed to identify environmental and clinical isolates of Sten. maltophilia. The proposed approach enables isolation and identification of Sten. maltophilia from different environments in an easy and rapid way. This approach will be useful to accurately manage studies on the abundance and distribution of Sten. maltophilia in hospital and nonhospital environments. © 2011 The Authors. Journal of Applied Microbiology © 2011 The Society for Applied Microbiology.

Computational inverse methods of heat source in fatigue damage problems

NASA Astrophysics Data System (ADS)

Chen, Aizhou; Li, Yuan; Yan, Bo

2018-04-01

Fatigue dissipation energy is the research focus in field of fatigue damage at present. It is a new idea to solve the problem of calculating fatigue dissipation energy by introducing inverse method of heat source into parameter identification of fatigue dissipation energy model. This paper introduces the research advances on computational inverse method of heat source and regularization technique to solve inverse problem, as well as the existing heat source solution method in fatigue process, prospects inverse method of heat source applying in fatigue damage field, lays the foundation for further improving the effectiveness of fatigue dissipation energy rapid prediction.

Identification of the population density of a species model with nonlocal diffusion and nonlinear reaction

NASA Astrophysics Data System (ADS)

Tuan, Nguyen Huy; Van Au, Vo; Khoa, Vo Anh; Lesnic, Daniel

2017-05-01

The identification of the population density of a logistic equation backwards in time associated with nonlocal diffusion and nonlinear reaction, motivated by biology and ecology fields, is investigated. The diffusion depends on an integral average of the population density whilst the reaction term is a global or local Lipschitz function of the population density. After discussing the ill-posedness of the problem, we apply the quasi-reversibility method to construct stable approximation problems. It is shown that the regularized solutions stemming from such method not only depend continuously on the final data, but also strongly converge to the exact solution in L 2-norm. New error estimates together with stability results are obtained. Furthermore, numerical examples are provided to illustrate the theoretical results.

Recent Methods for Purification and Structure Determination of Oligonucleotides.

PubMed

Zhang, Qiulong; Lv, Huanhuan; Wang, Lili; Chen, Man; Li, Fangfei; Liang, Chao; Yu, Yuanyuan; Jiang, Feng; Lu, Aiping; Zhang, Ge

2016-12-18

Aptamers are single-stranded DNA or RNA oligonucleotides that can interact with target molecules through specific three-dimensional structures. The excellent features, such as high specificity and affinity for target proteins, small size, chemical stability, low immunogenicity, facile chemical synthesis, versatility in structural design and engineering, and accessible for site-specific modifications with functional moieties, make aptamers attractive molecules in the fields of clinical diagnostics and biopharmaceutical therapeutics. However, difficulties in purification and structural identification of aptamers remain a major impediment to their broad clinical application. In this mini-review, we present the recently attractive developments regarding the purification and identification of aptamers. We also discuss the advantages, limitations, and prospects for the major methods applied in purifying and identifying aptamers, which could facilitate the application of aptamers.

Determination of benzimidazoles in meat samples by capillary zone electrophoresis tandem mass spectrometry following dispersive liquid-liquid microextraction.

PubMed

Tejada-Casado, Carmen; Moreno-González, David; Lara, Francisco J; García-Campaña, Ana M; Del Olmo-Iruela, Monsalud

2017-03-24

A novel method based on capillary zone electrophoresis-tandem mass spectrometry has been proposed and validated for the identification and simultaneous quantification of twelve benzimidazoles in meat samples. Electrophoretic separation was carried out using 500mM formic acid (pH 2.2) as background electrolyte and applying a voltage of 25kV at 25°C. In order to improve the sensitivity, stacking mode injection was applied, using as injection solvent a mixture of 30:70 acetonitrile/water at 50mbar for 75s. Sensitivity enhancement factors from 74 to 317 were obtained under these conditions. Detection using an ion trap as analyzer, operating in multiple reactions monitoring mode was employed. The main MS/MS parameters as well as the composition of the sheath liquid and other electrospray variables were optimized in order to obtain the highest sensitivity and precision in conjunction with an unequivocal identification. The method was applied to poultry and pork muscle samples. The deproteinization of samples and extraction of benzimidazoles was carried out with acetonitrile. MgSO 4 and NaCl were added as salting-out agents. Subsequently, dispersive liquid-liquid microextraction was applied as clean up procedure. The organic layer (acetonitrile, used as dispersant) containing the benzimidazoles was mixed with the extractant (chloroform) and both were injected in water, producing a cloudy solution. Recoveries for fortified samples were higher than 70%, with relative standard deviations lower than 16% were obtained in all cases. The limits of detection were below 3μgkg -1 , demonstrating the applicability of this fast, simple, and environmentally friendly method. Copyright © 2017 Elsevier B.V. All rights reserved.

The development of small-scale mechanization means positioning algorithm using radio frequency identification technology in industrial plants

NASA Astrophysics Data System (ADS)

Astafiev, A.; Orlov, A.; Privezencev, D.

2018-01-01

The article is devoted to the development of technology and software for the construction of positioning and control systems for small mechanization in industrial plants based on radio frequency identification methods, which will be the basis for creating highly efficient intelligent systems for controlling the product movement in industrial enterprises. The main standards that are applied in the field of product movement control automation and radio frequency identification are considered. The article reviews modern publications and automation systems for the control of product movement developed by domestic and foreign manufacturers. It describes the developed algorithm for positioning of small-scale mechanization means in an industrial enterprise. Experimental studies in laboratory and production conditions have been conducted and described in the article.

Emerging and Future Applications of Matrix-Assisted Laser Desorption Ionization Time-of-Flight (MALDI-TOF) Mass Spectrometry in the Clinical Microbiology Laboratory: A Report of the Association for Molecular Pathology.

PubMed

Doern, Christopher D; Butler-Wu, Susan M

2016-11-01

The performance of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MS) for routine bacterial and yeast identification as well as direct-from-blood culture bottle identification has been thoroughly evaluated in the peer-reviewed literature. Microbiologists are now moving beyond these methods to apply MS to other areas of the diagnostic process. This review discusses the emergence of advanced matrix-assisted laser desorption ionization time-of-flight MS applications, including the identification of filamentous fungi and mycobacteria and the current and future state of antimicrobial resistance testing. Copyright © 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Multi-ball and one-ball geolocation

NASA Astrophysics Data System (ADS)

Nelson, D. J.; Townsend, J. L.

2017-05-01

We present analysis methods that may be used to geolocate emitters using one or more moving receivers. While some of the methods we present may apply to a broader class of signals, our primary interest is locating and tracking ships from short pulsed transmissions, such as the maritime Automatic Identification System (AIS.) The AIS signal is difficult to process and track since the pulse duration is only 25 milliseconds, and the pulses may only be transmitted every six to ten seconds. In this article, we address several problems including accurate TDOA and FDOA estimation methods that do not require searching a two dimensional surface such as the cross-ambiguity surface. As an example, we apply these methods to identify and process AIS pulses from a single emitter, making it possible to geolocate the AIS signal using a single moving receiver.

System Identification Applied to Dynamic CFD Simulation and Wind Tunnel Data

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.; Klein, Vladislav; Frink, Neal T.; Vicroy, Dan D.

2011-01-01

Demanding aerodynamic modeling requirements for military and civilian aircraft have provided impetus for researchers to improve computational and experimental techniques. Model validation is a key component for these research endeavors so this study is an initial effort to extend conventional time history comparisons by comparing model parameter estimates and their standard errors using system identification methods. An aerodynamic model of an aircraft performing one-degree-of-freedom roll oscillatory motion about its body axes is developed. The model includes linear aerodynamics and deficiency function parameters characterizing an unsteady effect. For estimation of unknown parameters two techniques, harmonic analysis and two-step linear regression, were applied to roll-oscillatory wind tunnel data and to computational fluid dynamics (CFD) simulated data. The model used for this study is a highly swept wing unmanned aerial combat vehicle. Differences in response prediction, parameters estimates, and standard errors are compared and discussed

Vacuum Arc Vapor Deposition Method and Apparatus for Applying Identification Symbols to Substrates

NASA Technical Reports Server (NTRS)

Schramm, Harry F. (Inventor); Roxby, Donald L. (Inventor); Weeks, Jack L. (Inventor)

2002-01-01

An apparatus for applying permanent markings onto products using a Vacuum Arc Vapor Deposition (VAVD) marker by accelerating atoms or molecules from a vaporization source onto a substrate to form human and/or machine-readable part identification marking that can be detected optically or via a sensing device like x-ray, thermal imaging, ultrasound, magneto-optic, micro-power impulse radar, capacitance, or other similar sensing means. The apparatus includes a housing with a nozzle having a marking end. A chamber having an electrode, a vacuum port and a charge is located within the housing. The charge is activated by the electrode in a vacuum environment and deposited onto a substrate at the marking end of the nozzle. The apparatus may be a hand-held device or be disconnected from the handle and mounted to a robot or fixed station.

Rational identification of aggregation hotspots based on secondary structure and amino acid hydrophobicity.

PubMed

Matsui, Daisuke; Nakano, Shogo; Dadashipour, Mohammad; Asano, Yasuhisa

2017-08-25

Insolubility of proteins expressed in the Escherichia coli expression system hinders the progress of both basic and applied research. Insoluble proteins contain residues that decrease their solubility (aggregation hotspots). Mutating these hotspots to optimal amino acids is expected to improve protein solubility. To date, however, the identification of these hotspots has proven difficult. In this study, using a combination of approaches involving directed evolution and primary sequence analysis, we found two rules to help inductively identify hotspots: the α-helix rule, which focuses on the hydrophobicity of amino acids in the α-helix structure, and the hydropathy contradiction rule, which focuses on the difference in hydrophobicity relative to the corresponding amino acid in the consensus protein. By properly applying these two rules, we succeeded in improving the probability that expressed proteins would be soluble. Our methods should facilitate research on various insoluble proteins that were previously difficult to study due to their low solubility.

Identification and quantification of homologous series of compound in complex mixtures: autocovariance study of GC/MS chromatograms.

PubMed

Pietrogrande, Maria Chiara; Zampolli, Maria Grazia; Dondi, Francesco

2006-04-15

The paper describes a method for determining homologous classes of compounds in a multicomponent complex chromatogram obtained under programming elution conditions. The method is based on the computation of the autocovariance function of the experimental chromatogram (EACVF). The EACVF plot, if properly interpreted, can be regarded as a "class chromatogram" i.e., a virtual chromatogram formed by peaks whose positions and heights allow identification and quantification of the different homologous series, even if they are embedded in a random complex chromatogram. Theoretical models were developed to describe complex chromatograms displaying random retention pattern, ordered sequences or a combination of them. On the basis of theoretical autocovariance function, the properties of the chromatogram can be experimentally evaluated, under well-defined conditions: in particular, the two components of the chromatogram, ordered and random, can be identified. Moreover, the total number of single components (SCs) and the separated number of the SCs belonging to the random and ordered components can be determined, when the two components display the same concentration. If the mixture contains several homologous series with common frequency and different phase values, the number and identity of the different homologous series as well as the number of SCs belonging to each of them can be evaluated. Moreover, the power of the EACVF method can be magnified by applying it to the single ion monitoring (SIM) signals to selectively detect specific compound classes in order to identify the different homologous series. By this way, a full "decoding" of the complex multicomponent chromatogram is achieved. The method was validated on synthetic mixtures containing known amount of SCs belonging to homologous series of hydrocarbon, alcohols, ketones, and aromatic compounds in addition to other not structurally related SCs. The method was applied to both the total ion monitoring (TIC) and the SIM signals, to describe step by step the essence of the procedure. Moreover, the systematic use of both SIM and TIC can simplify the decoding procedure of complex chromatograms by singling out only specific compound classes or by confirming the identification of the different homologous series. The method was further applied to a sample containing unknown number of compounds and homologous series (a petroleum benzin, bp 140-160 degrees C): the results obtained were meaningful in terms of both the identified number of components and identified homologous series.

Time-varying singular value decomposition for periodic transient identification in bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Shangbin; Lu, Siliang; He, Qingbo; Kong, Fanrang

2016-09-01

For rotating machines, the defective faults of bearings generally are represented as periodic transient impulses in acquired signals. The extraction of transient features from signals has been a key issue for fault diagnosis. However, the background noise reduces identification performance of periodic faults in practice. This paper proposes a time-varying singular value decomposition (TSVD) method to enhance the identification of periodic faults. The proposed method is inspired by the sliding window method. By applying singular value decomposition (SVD) to the signal under a sliding window, we can obtain a time-varying singular value matrix (TSVM). Each column in the TSVM is occupied by the singular values of the corresponding sliding window, and each row represents the intrinsic structure of the raw signal, namely time-singular-value-sequence (TSVS). Theoretical and experimental analyses show that the frequency of TSVS is exactly twice that of the corresponding intrinsic structure. Moreover, the signal-to-noise ratio (SNR) of TSVS is improved significantly in comparison with the raw signal. The proposed method takes advantages of the TSVS in noise suppression and feature extraction to enhance fault frequency for diagnosis. The effectiveness of the TSVD is verified by means of simulation studies and applications to diagnosis of bearing faults. Results indicate that the proposed method is superior to traditional methods for bearing fault diagnosis.

Optimization for Peptide Sample Preparation for Urine Peptidomics

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

Sigdel, Tara K.; Nicora, Carrie D.; Hsieh, Szu-Chuan

2014-02-25

Analysis of native or endogenous peptides in biofluids can provide valuable insights into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for non-invasive monitoring of human diseases. The non-invasive nature of urine collection and the abundance of peptides in the urine makes analysis by high-throughput ‘peptidomics’ methods , an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regards to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements that it hampers both the identification of peptides andmore » the depth of the peptidomics read when utilizing LC-MS based peptidome analysis. We report on a novel adaptation of the standard solid phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS based peptidomics in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. Expense and time requirements were comparable for both SPE and mSPE, but more interfering contaminants from the urine matrix were evident in the SPE preparations (e.g., clogging of the LC-MS columns, yellowish background coloration of prepared samples due to retained urobilin, lower peptide yields) when compared to the mSPE method. When we compared data from technical replicates of 4 runs, the mSPE method provided significantly improved efficiencies for the preparation of samples from urine (e.g., mSPE peptide identification 82% versus 18% with SPE; p = 8.92E-05). Additionally, peptide identifications, when applying the mSPE method, highlighted the biology of differential activation of urine peptidases during acute renal transplant rejection with distinct laddering of specific peptides, which was obscured for most proteins when utilizing the conventional SPE method. In conclusion, the mSPE method was found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis due to the optimized sample clean up that provided improved experimental inference from the confidently identified peptides.« less

A Subspace Approach to the Structural Decomposition and Identification of Ankle Joint Dynamic Stiffness.

PubMed

Jalaleddini, Kian; Tehrani, Ehsan Sobhani; Kearney, Robert E

2017-06-01

The purpose of this paper is to present a structural decomposition subspace (SDSS) method for decomposition of the joint torque to intrinsic, reflexive, and voluntary torques and identification of joint dynamic stiffness. First, it formulates a novel state-space representation for the joint dynamic stiffness modeled by a parallel-cascade structure with a concise parameter set that provides a direct link between the state-space representation matrices and the parallel-cascade parameters. Second, it presents a subspace method for the identification of the new state-space model that involves two steps: 1) the decomposition of the intrinsic and reflex pathways and 2) the identification of an impulse response model of the intrinsic pathway and a Hammerstein model of the reflex pathway. Extensive simulation studies demonstrate that SDSS has significant performance advantages over some other methods. Thus, SDSS was more robust under high noise conditions, converging where others failed; it was more accurate, giving estimates with lower bias and random errors. The method also worked well in practice and yielded high-quality estimates of intrinsic and reflex stiffnesses when applied to experimental data at three muscle activation levels. The simulation and experimental results demonstrate that SDSS accurately decomposes the intrinsic and reflex torques and provides accurate estimates of physiologically meaningful parameters. SDSS will be a valuable tool for studying joint stiffness under functionally important conditions. It has important clinical implications for the diagnosis, assessment, objective quantification, and monitoring of neuromuscular diseases that change the muscle tone.

Expansion of Microbial Forensics.

PubMed

Schmedes, Sarah E; Sajantila, Antti; Budowle, Bruce

2016-08-01

Microbial forensics has been defined as the discipline of applying scientific methods to the analysis of evidence related to bioterrorism, biocrimes, hoaxes, or the accidental release of a biological agent or toxin for attribution purposes. Over the past 15 years, technology, particularly massively parallel sequencing, and bioinformatics advances now allow the characterization of microorganisms for a variety of human forensic applications, such as human identification, body fluid characterization, postmortem interval estimation, and biocrimes involving tracking of infectious agents. Thus, microbial forensics should be more broadly described as the discipline of applying scientific methods to the analysis of microbial evidence in criminal and civil cases for investigative purposes. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Prior knowledge guided active modules identification: an integrated multi-objective approach.

PubMed

Chen, Weiqi; Liu, Jing; He, Shan

2017-03-14

Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or disease states. A prior information guided active module identification approach is proposed to detect modules that are both active and enriched by prior knowledge. We formulate the active module identification problem as a multi-objective optimisation problem, which consists two conflicting objective functions of maximising the coverage of known biological pathways and the activity of the active module simultaneously. Network is constructed from protein-protein interaction database. A beta-uniform-mixture model is used to estimate the distribution of p-values and generate scores for activity measurement from microarray data. A multi-objective evolutionary algorithm is used to search for Pareto optimal solutions. We also incorporate a novel constraints based on algebraic connectivity to ensure the connectedness of the identified active modules. Application of proposed algorithm on a small yeast molecular network shows that it can identify modules with high activities and with more cross-talk nodes between related functional groups. The Pareto solutions generated by the algorithm provides solutions with different trade-off between prior knowledge and novel information from data. The approach is then applied on microarray data from diclofenac-treated yeast cells to build network and identify modules to elucidate the molecular mechanisms of diclofenac toxicity and resistance. Gene ontology analysis is applied to the identified modules for biological interpretation. Integrating knowledge of functional groups into the identification of active module is an effective method and provides a flexible control of balance between pure data-driven method and prior information guidance.

Two new computational methods for universal DNA barcoding: a benchmark using barcode sequences of bacteria, archaea, animals, fungi, and land plants.

PubMed

Tanabe, Akifumi S; Toju, Hirokazu

2013-01-01

Taxonomic identification of biological specimens based on DNA sequence information (a.k.a. DNA barcoding) is becoming increasingly common in biodiversity science. Although several methods have been proposed, many of them are not universally applicable due to the need for prerequisite phylogenetic/machine-learning analyses, the need for huge computational resources, or the lack of a firm theoretical background. Here, we propose two new computational methods of DNA barcoding and show a benchmark for bacterial/archeal 16S, animal COX1, fungal internal transcribed spacer, and three plant chloroplast (rbcL, matK, and trnH-psbA) barcode loci that can be used to compare the performance of existing and new methods. The benchmark was performed under two alternative situations: query sequences were available in the corresponding reference sequence databases in one, but were not available in the other. In the former situation, the commonly used "1-nearest-neighbor" (1-NN) method, which assigns the taxonomic information of the most similar sequences in a reference database (i.e., BLAST-top-hit reference sequence) to a query, displays the highest rate and highest precision of successful taxonomic identification. However, in the latter situation, the 1-NN method produced extremely high rates of misidentification for all the barcode loci examined. In contrast, one of our new methods, the query-centric auto-k-nearest-neighbor (QCauto) method, consistently produced low rates of misidentification for all the loci examined in both situations. These results indicate that the 1-NN method is most suitable if the reference sequences of all potentially observable species are available in databases; otherwise, the QCauto method returns the most reliable identification results. The benchmark results also indicated that the taxon coverage of reference sequences is far from complete for genus or species level identification in all the barcode loci examined. Therefore, we need to accelerate the registration of reference barcode sequences to apply high-throughput DNA barcoding to genus or species level identification in biodiversity research.

Two New Computational Methods for Universal DNA Barcoding: A Benchmark Using Barcode Sequences of Bacteria, Archaea, Animals, Fungi, and Land Plants

PubMed Central

Tanabe, Akifumi S.; Toju, Hirokazu

2013-01-01

Taxonomic identification of biological specimens based on DNA sequence information (a.k.a. DNA barcoding) is becoming increasingly common in biodiversity science. Although several methods have been proposed, many of them are not universally applicable due to the need for prerequisite phylogenetic/machine-learning analyses, the need for huge computational resources, or the lack of a firm theoretical background. Here, we propose two new computational methods of DNA barcoding and show a benchmark for bacterial/archeal 16S, animal COX1, fungal internal transcribed spacer, and three plant chloroplast (rbcL, matK, and trnH-psbA) barcode loci that can be used to compare the performance of existing and new methods. The benchmark was performed under two alternative situations: query sequences were available in the corresponding reference sequence databases in one, but were not available in the other. In the former situation, the commonly used “1-nearest-neighbor” (1-NN) method, which assigns the taxonomic information of the most similar sequences in a reference database (i.e., BLAST-top-hit reference sequence) to a query, displays the highest rate and highest precision of successful taxonomic identification. However, in the latter situation, the 1-NN method produced extremely high rates of misidentification for all the barcode loci examined. In contrast, one of our new methods, the query-centric auto-k-nearest-neighbor (QCauto) method, consistently produced low rates of misidentification for all the loci examined in both situations. These results indicate that the 1-NN method is most suitable if the reference sequences of all potentially observable species are available in databases; otherwise, the QCauto method returns the most reliable identification results. The benchmark results also indicated that the taxon coverage of reference sequences is far from complete for genus or species level identification in all the barcode loci examined. Therefore, we need to accelerate the registration of reference barcode sequences to apply high-throughput DNA barcoding to genus or species level identification in biodiversity research. PMID:24204702

A unified framework for evaluating the risk of re-identification of text de-identification tools.

PubMed

Scaiano, Martin; Middleton, Grant; Arbuckle, Luk; Kolhatkar, Varada; Peyton, Liam; Dowling, Moira; Gipson, Debbie S; El Emam, Khaled

2016-10-01

It has become regular practice to de-identify unstructured medical text for use in research using automatic methods, the goal of which is to remove patient identifying information to minimize re-identification risk. The metrics commonly used to determine if these systems are performing well do not accurately reflect the risk of a patient being re-identified. We therefore developed a framework for measuring the risk of re-identification associated with textual data releases. We apply the proposed evaluation framework to a data set from the University of Michigan Medical School. Our risk assessment results are then compared with those that would be obtained using a typical contemporary micro-average evaluation of recall in order to illustrate the difference between the proposed evaluation framework and the current baseline method. We demonstrate how this framework compares against common measures of the re-identification risk associated with an automated text de-identification process. For the probability of re-identification using our evaluation framework we obtained a mean value for direct identifiers of 0.0074 and a mean value for quasi-identifiers of 0.0022. The 95% confidence interval for these estimates were below the relevant thresholds. The threshold for direct identifier risk was based on previously used approaches in the literature. The threshold for quasi-identifiers was determined based on the context of the data release following commonly used de-identification criteria for structured data. Our framework attempts to correct for poorly distributed evaluation corpora, accounts for the data release context, and avoids the often optimistic assumptions that are made using the more traditional evaluation approach. It therefore provides a more realistic estimate of the true probability of re-identification. This framework should be used as a basis for computing re-identification risk in order to more realistically evaluate future text de-identification tools. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Performance enhancement for audio-visual speaker identification using dynamic facial muscle model.

PubMed

Asadpour, Vahid; Towhidkhah, Farzad; Homayounpour, Mohammad Mehdi

2006-10-01

Science of human identification using physiological characteristics or biometry has been of great concern in security systems. However, robust multimodal identification systems based on audio-visual information has not been thoroughly investigated yet. Therefore, the aim of this work to propose a model-based feature extraction method which employs physiological characteristics of facial muscles producing lip movements. This approach adopts the intrinsic properties of muscles such as viscosity, elasticity, and mass which are extracted from the dynamic lip model. These parameters are exclusively dependent on the neuro-muscular properties of speaker; consequently, imitation of valid speakers could be reduced to a large extent. These parameters are applied to a hidden Markov model (HMM) audio-visual identification system. In this work, a combination of audio and video features has been employed by adopting a multistream pseudo-synchronized HMM training method. Noise robust audio features such as Mel-frequency cepstral coefficients (MFCC), spectral subtraction (SS), and relative spectra perceptual linear prediction (J-RASTA-PLP) have been used to evaluate the performance of the multimodal system once efficient audio feature extraction methods have been utilized. The superior performance of the proposed system is demonstrated on a large multispeaker database of continuously spoken digits, along with a sentence that is phonetically rich. To evaluate the robustness of algorithms, some experiments were performed on genetically identical twins. Furthermore, changes in speaker voice were simulated with drug inhalation tests. In 3 dB signal to noise ratio (SNR), the dynamic muscle model improved the identification rate of the audio-visual system from 91 to 98%. Results on identical twins revealed that there was an apparent improvement on the performance for the dynamic muscle model-based system, in which the identification rate of the audio-visual system was enhanced from 87 to 96%.

"Learning to Work" in Small Businesses: Learning and Training for Young Adults with Learning Disabilities

ERIC Educational Resources Information Center

Ruggeri-Stevens, Geoff; Goodwin, Susan

2007-01-01

Purpose: The paper alerts small business employers to new dictates of the Disability Discrimination Act (2005) as it applies to learning disabilities. Then the "Learning to Work" project featured in the paper offers small business employers a set of approaches and methods for the identification of a learning-disabled young adult…

Accuracy of a Rationally Derived Method for Identifying Treatment Failure in Children and Adolescents

ERIC Educational Resources Information Center

Bishop, Matthew J.; Bybee, Taige S.; Lambert, Michael J.; Burlingame, Gary M.; Wells, M. Gawain; Poppleton, Landon E.

2005-01-01

Psychotherapy outcome can be enhanced by early identification of potential treatment failures before they leave treatment. In adults, compelling data are emerging that provide evidence that an early warning system that identifies potential treatment failures can be developed and applied to enhance outcome. The present study reports an analysis of…

Non-Destructive Measurement Methods (Neutron-, X-ray Radiography, Vibration Diagnostics and Ultrasound) in the Inspection of Helicopter Rotor Blades

DTIC Science & Technology

2005-04-01

the radiography gauging. In addition to the Statistical Energy Analysis (SEA) measurement a small exciter table (BK4810) and impedance head (BK 8000... Statistical Energy Analysis ; 7th Conf. on Vehicle System Dynamics, Identification and Anomalies (VSDIA2000), 6-8 Nov. 2000 Budapest, Proc. pp. 491-493... Energy Analysis (SEA) and Ultrasound Test. (UT) were concurrently applied. These methods collect accessory information on the objects under inspection

Constrained maximum likelihood modal parameter identification applied to structural dynamics

NASA Astrophysics Data System (ADS)

El-Kafafy, Mahmoud; Peeters, Bart; Guillaume, Patrick; De Troyer, Tim

2016-05-01

A new modal parameter estimation method to directly establish modal models of structural dynamic systems satisfying two physically motivated constraints will be presented. The constraints imposed in the identified modal model are the reciprocity of the frequency response functions (FRFs) and the estimation of normal (real) modes. The motivation behind the first constraint (i.e. reciprocity) comes from the fact that modal analysis theory shows that the FRF matrix and therefore the residue matrices are symmetric for non-gyroscopic, non-circulatory, and passive mechanical systems. In other words, such types of systems are expected to obey Maxwell-Betti's reciprocity principle. The second constraint (i.e. real mode shapes) is motivated by the fact that analytical models of structures are assumed to either be undamped or proportional damped. Therefore, normal (real) modes are needed for comparison with these analytical models. The work done in this paper is a further development of a recently introduced modal parameter identification method called ML-MM that enables us to establish modal model that satisfies such motivated constraints. The proposed constrained ML-MM method is applied to two real experimental datasets measured on fully trimmed cars. This type of data is still considered as a significant challenge in modal analysis. The results clearly demonstrate the applicability of the method to real structures with significant non-proportional damping and high modal densities.

Improved identification of primary biological aerosol particles using single-particle mass spectrometry

DOE PAGES

Zawadowicz, Maria A.; Froyd, Karl D.; Murphy, Daniel M.; ...

2017-06-16

Measurements of primary biological aerosol particles (PBAP), especially at altitudes relevant to cloud formation, are scarce. Single-particle mass spectrometry (SPMS) has been used to probe aerosol chemical composition from ground and aircraft for over 20 years. Here we develop a method for identifying bioaerosols (PBAP and particles containing fragments of PBAP as part of an internal mixture) using SPMS. Here, we show that identification of bioaerosol using SPMS is complicated because phosphorus-bearing mineral dust and phosphorus-rich combustion by-products such as fly ash produce mass spectra with peaks similar to those typically used as markers for bioaerosol. We have developed a methodologymore » to differentiate and identify bioaerosol using machine learning statistical techniques applied to mass spectra of known particle types. This improved method provides far fewer false positives compared to approaches reported in the literature. The new method was then applied to two sets of ambient data collected at Storm Peak Laboratory and a forested site in Central Valley, California to show that 0.04–2 % of particles in the 200–3000 nm aerodynamic diameter range were identified as bioaerosol. In addition, 36–56 % of particles identified as biological also contained spectral features consistent with mineral dust, suggesting internal dust–biological mixtures.« less

Improved identification of primary biological aerosol particles using single-particle mass spectrometry

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

Zawadowicz, Maria A.; Froyd, Karl D.; Murphy, Daniel M.

Measurements of primary biological aerosol particles (PBAP), especially at altitudes relevant to cloud formation, are scarce. Single-particle mass spectrometry (SPMS) has been used to probe aerosol chemical composition from ground and aircraft for over 20 years. Here we develop a method for identifying bioaerosols (PBAP and particles containing fragments of PBAP as part of an internal mixture) using SPMS. Here, we show that identification of bioaerosol using SPMS is complicated because phosphorus-bearing mineral dust and phosphorus-rich combustion by-products such as fly ash produce mass spectra with peaks similar to those typically used as markers for bioaerosol. We have developed a methodologymore » to differentiate and identify bioaerosol using machine learning statistical techniques applied to mass spectra of known particle types. This improved method provides far fewer false positives compared to approaches reported in the literature. The new method was then applied to two sets of ambient data collected at Storm Peak Laboratory and a forested site in Central Valley, California to show that 0.04–2 % of particles in the 200–3000 nm aerodynamic diameter range were identified as bioaerosol. In addition, 36–56 % of particles identified as biological also contained spectral features consistent with mineral dust, suggesting internal dust–biological mixtures.« less

Improved identification of primary biological aerosol particles using single-particle mass spectrometry

NASA Astrophysics Data System (ADS)

Zawadowicz, Maria A.; Froyd, Karl D.; Murphy, Daniel M.; Cziczo, Daniel J.

2017-06-01

Measurements of primary biological aerosol particles (PBAP), especially at altitudes relevant to cloud formation, are scarce. Single-particle mass spectrometry (SPMS) has been used to probe aerosol chemical composition from ground and aircraft for over 20 years. Here we develop a method for identifying bioaerosols (PBAP and particles containing fragments of PBAP as part of an internal mixture) using SPMS. We show that identification of bioaerosol using SPMS is complicated because phosphorus-bearing mineral dust and phosphorus-rich combustion by-products such as fly ash produce mass spectra with peaks similar to those typically used as markers for bioaerosol. We have developed a methodology to differentiate and identify bioaerosol using machine learning statistical techniques applied to mass spectra of known particle types. This improved method provides far fewer false positives compared to approaches reported in the literature. The new method was then applied to two sets of ambient data collected at Storm Peak Laboratory and a forested site in Central Valley, California to show that 0.04-2 % of particles in the 200-3000 nm aerodynamic diameter range were identified as bioaerosol. In addition, 36-56 % of particles identified as biological also contained spectral features consistent with mineral dust, suggesting internal dust-biological mixtures.

Comparaison de méthodes d'identification des paramètres d'une machine asynchrone

NASA Astrophysics Data System (ADS)

Bellaaj-Mrabet, N.; Jelassi, K.

1998-07-01

Interests, in Genetic Algorithms (G.A.) expands rapidly. This paper consists initially to apply G.A. for identifying induction motor parameters. Next, we compare the performances with classical methods like Maximum Likelihood and classical electrotechnical methods. These methods are applied on three induction motors of different powers to compare results following a set of criteria. Les algorithmes génétiques sont des méthodes adaptatives de plus en plus utilisée pour la résolution de certains problèmes d'optimisation. Le présent travail consiste d'une part, à mettre en œuvre un A.G sur des problèmes d'identification des machines électriques, et d'autre part à comparer ses performances avec les méthodes classiques tels que la méthode du maximum de vraisemblance et la méthode électrotechnique basée sur des essais à vides et en court-circuit. Ces méthodes sont appliquées sur des machines asynchrones de différentes puissances. Les résultats obtenus sont comparés selon certains critères, permettant de conclure sur la validité et la performance de chaque méthode.

Monitoring leachables from single-use bioreactor bags for mammalian cell culture by dispersive liquid-liquid microextraction followed by ultra high performance liquid chromatography quadrupole time of flight mass spectrometry.

PubMed

Dorival-García, N; Bones, J

2017-08-25

A method for the identification of leachables in chemically defined media for CHO cell culture using dispersive liquid-liquid microextraction (DLLME) and UHPLC-MS is described. A Box-Behnken design of experiments (DoE) approach was applied to obtain the optimum extraction conditions of the target analytes. Performance of DLLME as extraction technique was studied by comparison of two commercial chemically defined media for CHO cell culture. General extraction conditions for any group of leachables, regardless of their specific chemical functionalities can be applied and similar optimum conditions were obtained with the two media. Extraction efficiency and matrix effects were determined. The method was validated using matrix-matched standard calibration followed by recovery assays with spiked samples. Finally, cell culture media was incubated in 7 single use bioreactors (SUBs) from different vendors and analysed. TBPP was not detected in any of the samples, whereas DtBP and TBPP-ox were found in all samples, with bDtBPP detected in six SUBs. This method can be used for early identification of non-satisfactory SUB films for cultivation of CHO cell lines for biopharmaceutical production. Copyright © 2017 Elsevier B.V. All rights reserved.

Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification.

PubMed

Andreatta, Massimo; Karosiene, Edita; Rasmussen, Michael; Stryhn, Anette; Buus, Søren; Nielsen, Morten

2015-11-01

A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented on the cell surface where it can be recognized by T helper lymphocytes. NetMHCIIpan is a state-of-the-art method for the quantitative prediction of peptide binding to any human or mouse MHC class II molecule of known sequence. In this paper, we describe an updated version of the method with improved peptide binding register identification. Binding register prediction is concerned with determining the minimal core region of nine residues directly in contact with the MHC binding cleft, a crucial piece of information both for the identification and design of CD4(+) T cell antigens. When applied to a set of 51 crystal structures of peptide-MHC complexes with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped to the epitope binding core. NetMHCIIpan is publicly available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.1 .

Personal Verification/Identification via Analysis of the Peripheral ECG Leads: Influence of the Personal Health Status on the Accuracy

PubMed Central

Bortolan, Giovanni

2015-01-01

Traditional means for identity validation (PIN codes, passwords), and physiological and behavioral biometric characteristics (fingerprint, iris, and speech) are susceptible to hacker attacks and/or falsification. This paper presents a method for person verification/identification based on correlation of present-to-previous limb ECG leads: I (r I), II (r II), calculated from them first principal ECG component (r PCA), linear and nonlinear combinations between r I, r II, and r PCA. For the verification task, the one-to-one scenario is applied and threshold values for r I, r II, and r PCA and their combinations are derived. The identification task supposes one-to-many scenario and the tested subject is identified according to the maximal correlation with a previously recorded ECG in a database. The population based ECG-ILSA database of 540 patients (147 healthy subjects, 175 patients with cardiac diseases, and 218 with hypertension) has been considered. In addition a common reference PTB dataset (14 healthy individuals) with short time interval between the two acquisitions has been taken into account. The results on ECG-ILSA database were satisfactory with healthy people, and there was not a significant decrease in nonhealthy patients, demonstrating the robustness of the proposed method. With PTB database, the method provides an identification accuracy of 92.9% and a verification sensitivity and specificity of 100% and 89.9%. PMID:26568954

Robust polygon recognition method with similarity invariants applied to star identification

NASA Astrophysics Data System (ADS)

Hernández, E. Antonio; Alonso, Miguel A.; Chávez, Edgar; Covarrubias, David H.; Conte, Roberto

2017-02-01

In the star identification process the goal is to recognize a star by using the celestial bodies in its vicinity as context. An additional requirement is to avoid having to perform an exhaustive scan of the star database. In this paper we present a novel approach to star identification using similarity invariants. More specifically, the proposed algorithm defines a polygon for each star, using the neighboring celestial bodies in the field of view as vertices. The mapping is insensitive to similarity transformation; that is, the image of the polygon under the transformation is not affected by rotation, scaling or translations. Each polygon is associated with an essentially unique complex number. We perform an exhaustive experimental validation of the proposed algorithm using synthetic data generated from the star catalog with uniformly-distributed positional noise introduced to each star. The star identification method that we present is proven to be robust, achieving a recognition rate of 99.68% when noise levels of up to ± 424 μ radians are introduced to the location of the stars. In our tests the proposed algorithm proves that if a polygon match is found, it always corresponds to the star under analysis; no mismatches are found. In its present form our method cannot identify polygons in cases where there exist missing or false stars in the analyzed images, in those situations it only indicates that no match was found.

Personal Verification/Identification via Analysis of the Peripheral ECG Leads: Influence of the Personal Health Status on the Accuracy.

PubMed

Jekova, Irena; Bortolan, Giovanni

2015-01-01

Traditional means for identity validation (PIN codes, passwords), and physiological and behavioral biometric characteristics (fingerprint, iris, and speech) are susceptible to hacker attacks and/or falsification. This paper presents a method for person verification/identification based on correlation of present-to-previous limb ECG leads: I (r I), II (r II), calculated from them first principal ECG component (r PCA), linear and nonlinear combinations between r I, r II, and r PCA. For the verification task, the one-to-one scenario is applied and threshold values for r I, r II, and r PCA and their combinations are derived. The identification task supposes one-to-many scenario and the tested subject is identified according to the maximal correlation with a previously recorded ECG in a database. The population based ECG-ILSA database of 540 patients (147 healthy subjects, 175 patients with cardiac diseases, and 218 with hypertension) has been considered. In addition a common reference PTB dataset (14 healthy individuals) with short time interval between the two acquisitions has been taken into account. The results on ECG-ILSA database were satisfactory with healthy people, and there was not a significant decrease in nonhealthy patients, demonstrating the robustness of the proposed method. With PTB database, the method provides an identification accuracy of 92.9% and a verification sensitivity and specificity of 100% and 89.9%.

Vector soup: high-throughput identification of Neotropical phlebotomine sand flies using metabarcoding.

PubMed

Kocher, Arthur; Gantier, Jean-Charles; Gaborit, Pascal; Zinger, Lucie; Holota, Helene; Valiere, Sophie; Dusfour, Isabelle; Girod, Romain; Bañuls, Anne-Laure; Murienne, Jerome

2017-03-01

Phlebotomine sand flies are haematophagous dipterans of primary medical importance. They represent the only proven vectors of leishmaniasis worldwide and are involved in the transmission of various other pathogens. Studying the ecology of sand flies is crucial to understand the epidemiology of leishmaniasis and further control this disease. A major limitation in this regard is that traditional morphological-based methods for sand fly species identifications are time-consuming and require taxonomic expertise. DNA metabarcoding holds great promise in overcoming this issue by allowing the identification of multiple species from a single bulk sample. Here, we assessed the reliability of a short insect metabarcode located in the mitochondrial 16S rRNA for the identification of Neotropical sand flies, and constructed a reference database for 40 species found in French Guiana. Then, we conducted a metabarcoding experiment on sand flies mixtures of known content and showed that the method allows an accurate identification of specimens in pools. Finally, we applied metabarcoding to field samples caught in a 1-ha forest plot in French Guiana. Besides providing reliable molecular data for species-level assignations of phlebotomine sand flies, our study proves the efficiency of metabarcoding based on the mitochondrial 16S rRNA for studying sand fly diversity from bulk samples. The application of this high-throughput identification procedure to field samples can provide great opportunities for vector monitoring and eco-epidemiological studies. © 2016 John Wiley & Sons Ltd.

Machinery running state identification based on discriminant semi-supervised local tangent space alignment for feature fusion and extraction

NASA Astrophysics Data System (ADS)

Su, Zuqiang; Xiao, Hong; Zhang, Yi; Tang, Baoping; Jiang, Yonghua

2017-04-01

Extraction of sensitive features is a challenging but key task in data-driven machinery running state identification. Aimed at solving this problem, a method for machinery running state identification that applies discriminant semi-supervised local tangent space alignment (DSS-LTSA) for feature fusion and extraction is proposed. Firstly, in order to extract more distinct features, the vibration signals are decomposed by wavelet packet decomposition WPD, and a mixed-domain feature set consisted of statistical features, autoregressive (AR) model coefficients, instantaneous amplitude Shannon entropy and WPD energy spectrum is extracted to comprehensively characterize the properties of machinery running state(s). Then, the mixed-dimension feature set is inputted into DSS-LTSA for feature fusion and extraction to eliminate redundant information and interference noise. The proposed DSS-LTSA can extract intrinsic structure information of both labeled and unlabeled state samples, and as a result the over-fitting problem of supervised manifold learning and blindness problem of unsupervised manifold learning are overcome. Simultaneously, class discrimination information is integrated within the dimension reduction process in a semi-supervised manner to improve sensitivity of the extracted fusion features. Lastly, the extracted fusion features are inputted into a pattern recognition algorithm to achieve the running state identification. The effectiveness of the proposed method is verified by a running state identification case in a gearbox, and the results confirm the improved accuracy of the running state identification.

Bioassay selection, experimental design and quality control/assurance for use in effluent assessment and control.

PubMed

Johnson, Ian; Hutchings, Matt; Benstead, Rachel; Thain, John; Whitehouse, Paul

2004-07-01

In the UK Direct Toxicity Assessment Programme, carried out in 1998-2000, a series of internationally recognised short-term toxicity test methods for algae, invertebrates and fishes, and rapid methods (ECLOX and Microtox) were used extensively. Abbreviated versions of conventional tests (algal growth inhibition tests, Daphnia magna immobilisation test and the oyster embryo-larval development test) were valuable for toxicity screening of effluent discharges and the identification of causes and sources of toxicity. Rapid methods based on chemiluminescence and bioluminescence were not generally useful in this programme, but may have a role where the rapid test has been shown to be an acceptable surrogate for a standardised test method. A range of quality assurance and control measures were identified. Requirements for quality control/assurance are most stringent when deriving data for characterising the toxic hazards of effluents and monitoring compliance against a toxicity reduction target. Lower quality control/assurance requirements can be applied to discharge screening and the identification of causes and sources of toxicity.

Study of Commercially Available Lobelia chinensis Products Using Bar-HRM Technology.

PubMed

Sun, Wei; Yan, Song; Li, Jingjian; Xiong, Chao; Shi, Yuhua; Wu, Lan; Xiang, Li; Deng, Bo; Ma, Wei; Chen, Shilin

2017-01-01

There is an unmet need for herbal medicine identification using a fast, sensitive, and easy-to-use method that does not require complex infrastructure and well-trained technicians. For instance, the detection of adulterants in Lobelia chinensis herbal product has been challenging, since current detection technologies are not effective due to their own limits. High Resolution Melting (HRM) has emerged as a powerful new technology for clinical diagnosis, research in the food industry and in plant molecular biology, and this method has already highlighted the complexity of species identification. In this study, we developed a method of species specific detection of L. chinensis using HRM analysis combined with internal transcribed spacer 2. We then applied this method to commercial products purporting to contain L . chinensis . Our results demonstrated that HRM can differentiate L. chinensis from six common adulterants. HRM was proven to be a fast and accurate technique for testing the authenticity of L. chinensis in herbal products. Based on these results, a HRM approach for herbal authentication is provided.

Gene expression complex networks: synthesis, identification, and analysis.

PubMed

Lopes, Fabrício M; Cesar, Roberto M; Costa, Luciano Da F

2011-10-01

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdös-Rényi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabási-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree variation, decreasing its network recovery rate with the increase of . The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Using SSR-HRM to Identify Closely Related Species in Herbal Medicine Products: A Case Study on Licorice.

PubMed

Li, Jingjian; Xiong, Chao; He, Xia; Lu, Zhaocen; Zhang, Xin; Chen, Xiaoyang; Sun, Wei

2018-01-01

Traditional herbal medicines have played important roles in the ways of life of people around the world since ancient times. Despite the advanced medical technology of the modern world, herbal medicines are still used as popular alternatives to synthetic drugs. Due to the increasing demand for herbal medicines, plant species identification has become an important tool to prevent substitution and adulteration. Here we propose a method for biological assessment of the quality of prescribed species in the Chinese Pharmacopoeia by use of high resolution melting (HRM) analysis of microsatellite loci. We tested this method on licorice, a traditional herbal medicine with a long history. Results showed that nine simple sequence repeat (SSR) markers produced distinct melting curve profiles for the five licorice species investigated using HRM analysis. These results were validated by capillary electrophoresis. We applied this protocol to commercially available licorice products, thus enabling the consistent identification of 11 labels with non-declared Glycyrrhiza species. This novel strategy may thus facilitate DNA barcoding as a method of identification of closely related species in herbal medicine products. Based on this study, a brief operating procedure for using the SSR-HRM protocol for herbal authentication is provided.

Using SSR-HRM to Identify Closely Related Species in Herbal Medicine Products: A Case Study on Licorice

PubMed Central

Li, Jingjian; Xiong, Chao; He, Xia; Lu, Zhaocen; Zhang, Xin; Chen, Xiaoyang; Sun, Wei

2018-01-01

Traditional herbal medicines have played important roles in the ways of life of people around the world since ancient times. Despite the advanced medical technology of the modern world, herbal medicines are still used as popular alternatives to synthetic drugs. Due to the increasing demand for herbal medicines, plant species identification has become an important tool to prevent substitution and adulteration. Here we propose a method for biological assessment of the quality of prescribed species in the Chinese Pharmacopoeia by use of high resolution melting (HRM) analysis of microsatellite loci. We tested this method on licorice, a traditional herbal medicine with a long history. Results showed that nine simple sequence repeat (SSR) markers produced distinct melting curve profiles for the five licorice species investigated using HRM analysis. These results were validated by capillary electrophoresis. We applied this protocol to commercially available licorice products, thus enabling the consistent identification of 11 labels with non-declared Glycyrrhiza species. This novel strategy may thus facilitate DNA barcoding as a method of identification of closely related species in herbal medicine products. Based on this study, a brief operating procedure for using the SSR-HRM protocol for herbal authentication is provided. PMID:29740326

Biometric sample extraction using Mahalanobis distance in Cardioid based graph using electrocardiogram signals.

PubMed

Sidek, Khairul; Khali, Ibrahim

2012-01-01

In this paper, a person identification mechanism implemented with Cardioid based graph using electrocardiogram (ECG) is presented. Cardioid based graph has given a reasonably good classification accuracy in terms of differentiating between individuals. However, the current feature extraction method using Euclidean distance could be further improved by using Mahalanobis distance measurement producing extracted coefficients which takes into account the correlations of the data set. Identification is then done by applying these extracted features to Radial Basis Function Network. A total of 30 ECG data from MITBIH Normal Sinus Rhythm database (NSRDB) and MITBIH Arrhythmia database (MITDB) were used for development and evaluation purposes. Our experimentation results suggest that the proposed feature extraction method has significantly increased the classification performance of subjects in both databases with accuracy from 97.50% to 99.80% in NSRDB and 96.50% to 99.40% in MITDB. High sensitivity, specificity and positive predictive value of 99.17%, 99.91% and 99.23% for NSRDB and 99.30%, 99.90% and 99.40% for MITDB also validates the proposed method. This result also indicates that the right feature extraction technique plays a vital role in determining the persistency of the classification accuracy for Cardioid based person identification mechanism.

[Microbiological analysis of red octopus in fishing ports of Campeche, Mexico].

PubMed

Estrella-Gómez, Neyi; Escalante-Réndiz, Diana; González-Burgos, Araceli; Sosa-Cordero, Delta; Rojas-Herrera, Rafael

2016-08-01

In this work we studied the microbiological quality of the red octopus given its important economic and social impact on the region South-Southeast of Mexico. Samples were taken in different areas of capture of the species and analyzed with biochemical tests described in the Mexican official standards, identifying strains belonging to the genus Vibrio, Salmonella and faecal coliforms, and E. coli O157: H7. We used the BAx System for the identification of microorganisms through their bacterial DNA. The results obtained in biochemical and molecular methods were confirmed. Bland-Altman statistical method pointed out that both techniques can be used interchangeably. McNemar test showed that both methods have the same efficacy for the identification of pathogens (value X2=0.5 ρ=0.4795). The microbiological quality of the octopus in the South-Southeast region of Mexico is deficient due to the presence of pathogenic intestinal flora that might represent an epidemiological risk. The indexes established by the regulations suggest the need to apply effective and rapid identification technologies, such as the BAx System.This alternative method of analysis can contribute to the implementation of effective strategies that allow compliance with the minimal sanitary specifications during the processing of fishing products, thus strengthening the control systems to decrease the risks of epidemiological outbreaks in the region.

A physics-based fractional order model and state of energy estimation for lithium ion batteries. Part II: Parameter identification and state of energy estimation for LiFePO4 battery

NASA Astrophysics Data System (ADS)

Li, Xiaoyu; Pan, Ke; Fan, Guodong; Lu, Rengui; Zhu, Chunbo; Rizzoni, Giorgio; Canova, Marcello

2017-11-01

State of energy (SOE) is an important index for the electrochemical energy storage system in electric vehicles. In this paper, a robust state of energy estimation method in combination with a physical model parameter identification method is proposed to achieve accurate battery state estimation at different operating conditions and different aging stages. A physics-based fractional order model with variable solid-state diffusivity (FOM-VSSD) is used to characterize the dynamic performance of a LiFePO4/graphite battery. In order to update the model parameter automatically at different aging stages, a multi-step model parameter identification method based on the lexicographic optimization is especially designed for the electric vehicle operating conditions. As the battery available energy changes with different applied load current profiles, the relationship between the remaining energy loss and the state of charge, the average current as well as the average squared current is modeled. The SOE with different operating conditions and different aging stages are estimated based on an adaptive fractional order extended Kalman filter (AFEKF). Validation results show that the overall SOE estimation error is within ±5%. The proposed method is suitable for the electric vehicle online applications.

Validation of a LC-fluorescence method for determination of free captopril in human plasma, using a pre-column derivatization reaction with monobromobimane.

PubMed

Tache, Florentin; Farca, Alexandru; Medvedovici, Andrei; David, Victor

2002-05-15

Both derivatization of free captopril in human plasma samples using monobromobimane as fluorescent label and the corresponding HPLC-fluorescence detection (FLD) method were validated. Calibration curve for the fluorescent captopril derivative in plasma samples is linear in the ppb-ppm range with a detection limit of 4 ppb and an identification limit of 10 ppb (P%: 90; nu > or = 5). These methods were successfully applied on bioequivalence studies carried out on some marketed pharmaceutical formulations.

Modelling the firing pattern of bullfrog vestibular neurons responding to naturalistic stimuli

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

1999-01-01

We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.

Master Logic Diagram: method for hazard and initiating event identification in process plants.

PubMed

Papazoglou, I A; Aneziris, O N

2003-02-28

Master Logic Diagram (MLD), a method for identifying events initiating accidents in chemical installations, is presented. MLD is a logic diagram that resembles a fault tree but without the formal mathematical properties of the latter. MLD starts with a Top Event "Loss of Containment" and decomposes it into simpler contributing events. A generic MLD has been developed which may be applied to all chemical installations storing toxic and/or flammable substances. The method is exemplified through its application to an ammonia storage facility.

Identification of stochastic interactions in nonlinear models of structural mechanics

NASA Astrophysics Data System (ADS)

Kala, Zdeněk

2017-07-01

In the paper, the polynomial approximation is presented by which the Sobol sensitivity analysis can be evaluated with all sensitivity indices. The nonlinear FEM model is approximated. The input area is mapped using simulations runs of Latin Hypercube Sampling method. The domain of the approximation polynomial is chosen so that it were possible to apply large number of simulation runs of Latin Hypercube Sampling method. The method presented also makes possible to evaluate higher-order sensitivity indices, which could not be identified in case of nonlinear FEM.

Bayesian Exploratory Factor Analysis

PubMed Central

Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi

2014-01-01

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517

INSTRUMENTS AND METHODS OF INVESTIGATION: Spectral and spectral-frequency methods of investigating atmosphereless bodies of the Solar system

NASA Astrophysics Data System (ADS)

Busarev, Vladimir V.; Prokof'eva-Mikhailovskaya, Valentina V.; Bochkov, Valerii V.

2007-06-01

A method of reflectance spectrophotometry of atmosphereless bodies of the Solar system, its specificity, and the means of eliminating basic spectral noise are considered. As a development, joining the method of reflectance spectrophotometry with the frequency analysis of observational data series is proposed. The combined spectral-frequency method allows identification of formations with distinctive spectral features, and estimations of their sizes and distribution on the surface of atmospherelss celestial bodies. As applied to investigations of asteroids 21 Lutetia and 4 Vesta, the spectral frequency method has given us the possibility of obtaining fundamentally new information about minor planets.

Exploring MALDI-TOF MS approach for a rapid identification of Mycobacterium avium ssp. paratuberculosis field isolates.

PubMed

Ricchi, M; Mazzarelli, A; Piscini, A; Di Caro, A; Cannas, A; Leo, S; Russo, S; Arrigoni, N

2017-03-01

The aim of the study was to explore the suitability of matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) for a rapid and correct identification of Mycobacterium avium ssp. paratuberculosis (MAP) field isolates. MALDI-TOF MS approach is becoming one of the most popular tests for the identification of intact bacterial cells which has been shown to be fast and reliable. For this purpose, 36 MAP field isolates were analysed through MALDI-TOF MS and the spectra compared with two different databases: one provided by the vendor of the system employed (Biotyper ver. 3·0; Bruker Daltonics) and a homemade database containing spectra from both tuberculous and nontuberculous Mycobacteria. Moreover, principal component analysis procedure was employed to confirm the ability of MALDI-TOF MS to discriminate between very closely related subspecies. Our results suggest MAP can be differentiated from other Mycobacterium species, both when the species are very close (M. intracellulare) and when belonging to different subspecies (M. avium ssp. avium and M. avium ssp. silvaticum). The procedure applied is fast, easy to perform, and achieves an earlier accurate species identification of MAP and nontuberculous Mycobacteria in comparison to other procedures. The gold standard test for the diagnosis of paratuberculosis is still isolation of MAP by cultural methods, but additional assays, such as qPCR and subculturing for determination of mycobactin dependency are required to confirm its identification. We have provided here evidence pertaining to the usefulness of MALDI-TOF MS approach for a rapid identification of this mycobacterium among other members of M. avium complex. © 2016 The Society for Applied Microbiology.

Identification of "insoluble" red dyewoods by high performance liquid chromatography-photodiode array detection (HPLC-PDA) fingerprinting.

PubMed

Surowiec, Izabella; Nowik, Witold; Trojanowicz, Marek

2004-02-01

The paper describes a high performance liquid chromatography-UV/Vis spectrometry detection analytical approach to the identification of some redwood species of historical importance in textile dyeing. The group of extracted dyestuffs considered as "insoluble" because of their non-aqueous or alkaline extraction conditions is present in the wood of the Pterocarpus family and Baphia nitida species. First, the crude extracts of tinctorial and related species and their chromatographic fingerprints were studied. This part of work shows that some species not yet mentioned in the literature have potential dyeing properties. Subsequent experiments performed on the redwood cargo of a 200-year-old archaeological shipwreck allowed identification of the water-logged wood species. Furthermore, the different methods of dyestuff extraction used for dyeing according to traditional recipes and their impact on analytical results were studied. They show that standard recovery obtained by acid hydrolysis of dyestuff from dyed yarns is inadequate. Hence, alternative solvent-based procedures were proposed. The identification of species in textile threads then becomes possible. The applied approach was validated by analysis of dyed reference yarns with some indications of crude material extraction mode. The employed method of analysis seems to be useful for "insoluble" wood species identification in cultural heritage artifacts as well as for phytochemical purposes, despite the fact that very few detected color compounds were chemically identified.

Comparative analysis of Gram's stain, PNA-FISH and Sepsityper with MALDI-TOF MS for the identification of yeast direct from positive blood cultures.

PubMed

Gorton, Rebecca L; Ramnarain, P; Barker, K; Stone, N; Rattenbury, S; McHugh, T D; Kibbler, C C

2014-10-01

Fungaemia diagnosis could be improved by reducing the time to identification of yeast from blood cultures. This study aimed to evaluate three rapid methods for the identification of yeast direct from blood cultures; Gram's stain analysis, the AdvanDX Peptide Nucleic Acid in Situ Hybridisation Yeast Traffic Light system (PNA-FISH YTL) and Bruker Sepsityper alongside matrix-assisted laser desorption ionisation time of flight mass spectrometry (MALDI-TOF MS). Fifty blood cultures spiked with a known single yeast strain were analysed by blinded operators experienced in each method. Identifications were compared with MALDI-TOF MS CHROMagar Candida culture and ITS rRNA sequence-based identifications. On first attempt, success rates of 96% (48/50) and 76% (36/50) were achieved using PNA-FISH YTL and Gram's stain respectively. MALDI-TOF MS demonstrated a success rate of 56% (28/50) when applying manufacturer's species log score thresholds and 76% (38/50) using in-house parameters, including lowering the species log score threshold to >1.5. In conclusion, PNA-FISH YTL demonstrated a high success rate successfully identifying yeast commonly encountered in fungaemia. Sepsityper(™) with MALDI-TOF MS was accurate but increased sensitivity is required. Due to the misidentification of commonly encountered yeast Gram's stain analysis demonstrated limited utility in this setting. © 2014 Blackwell Verlag GmbH.

Direct PCR of indigenous and invasive mosquito species: a time- and cost-effective technique of mosquito barcoding.

PubMed

Werblow, A; Flechl, E; Klimpel, S; Zittra, C; Lebl, K; Kieser, K; Laciny, A; Silbermayr, K; Melaun, C; Fuehrer, H-P

2016-03-01

Millions of people die each year as a result of pathogens transmitted by mosquitoes. However, the morphological identification of mosquito species can be difficult even for experts. The identification of morphologically indistinguishable species, such as members of the Anopheles maculipennis complex (Diptera: Culicidae), and possible hybrids, such as Culex pipiens pipiens/Culex pipiens molestus (Diptera: Culicidae), presents a major problem. In addition, the detection and discrimination of newly introduced species can be challenging, particularly to researchers without previous experience. Because of their medical importance, the clear identification of all relevant mosquito species is essential. Using the direct polymerase chain reaction (PCR) method described here, DNA amplification without prior DNA extraction is possible and thus species identification after sequencing can be achieved. Different amounts of tissue (leg, head; larvae or adult) as well as different storage conditions (dry, ethanol, -20 and -80 °C) and storage times were successfully applied and showed positive results after amplification and gel electrophoresis. Overall, 28 different indigenous and non-indigenous mosquito species were analysed using a gene fragment of the COX1 gene for species differentiation and identification by sequencing this 658-bp fragment. Compared with standard PCR, this method is time- and cost-effective and could thus improve existing surveillance and control programmes. © 2015 The Authors. Medical and Veterinary Entomology published by John Wiley & Sons Ltd on behalf of Royal Entomological Society.

Developing a multimodal biometric authentication system using soft computing methods.

PubMed

Malcangi, Mario

2015-01-01

Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability. This chapter describes the embedded implementation of a multi-biometric (voiceprint and fingerprint) multimodal identification system based on hard computing methods (DSP) for feature extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.

SpeCond: a method to detect condition-specific gene expression

PubMed Central

2011-01-01

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

Identification of the origin of faecal contamination in estuarine oysters using Bacteroidales and F-specific RNA bacteriophage markers.

PubMed

Mieszkin, S; Caprais, M P; Le Mennec, C; Le Goff, M; Edge, T A; Gourmelon, M

2013-09-01

The aim of this study was to identify the origin of faecal pollution impacting the Elorn estuary (Brittany, France) by applying microbial source tracking (MST) markers in both oysters and estuarine waters. The MST markers used were as follows: (i) human-, ruminant- and pig-associated Bacteroidales markers by real-time PCR and (ii) human genogroup II and animal genogroup I of F-specific RNA bacteriophages (FRNAPH) by culture/genotyping and by direct real-time reverse-transcriptase PCR. The higher occurrence of the human genogroup II of F-specific RNA bacteriophages using a culture/genotyping method, and human-associated Bacteroidales marker by real-time PCR, allowed the identification of human faecal contamination as the predominant source of contamination in oysters (total of 18 oyster batches tested) and waters (total of 24 water samples tested). The importance of using the intravalvular liquids instead of digestive tissues, when applying host-associated Bacteroidales markers in oysters, was also revealed. This study has shown that the application of a MST toolbox of diverse bacterial and viral methods can provide multiple lines of evidence to identify the predominant source of faecal contamination in shellfish from an estuarine environment. Application of this MST toolbox is a useful approach to understand the origin of faecal contamination in shellfish harvesting areas in an estuarine setting. © 2013 The Society for Applied Microbiology.

Hazard identification by methods of animal-based toxicology.

PubMed

Barlow, S M; Greig, J B; Bridges, J W; Carere, A; Carpy, A J M; Galli, C L; Kleiner, J; Knudsen, I; Koëter, H B W M; Levy, L S; Madsen, C; Mayer, S; Narbonne, J-F; Pfannkuch, F; Prodanchuk, M G; Smith, M R; Steinberg, P

2002-01-01

This paper is one of several prepared under the project "Food Safety In Europe: Risk Assessment of Chemicals in Food and Diet" (FOSIE), a European Commission Concerted Action Programme, organised by the International Life Sciences Institute, Europe (ILSI). The aim of the FOSIE project is to review the current state of the science of risk assessment of chemicals in food and diet, by consideration of the four stages of risk assessment, that is, hazard identification, hazard characterisation, exposure assessment and risk characterisation. The contribution of animal-based methods in toxicology to hazard identification of chemicals in food and diet is discussed. The importance of first applying existing technical and chemical knowledge to the design of safety testing programs for food chemicals is emphasised. There is consideration of the presently available and commonly used toxicity testing approaches and methodologies, including acute and repeated dose toxicity, reproductive and developmental toxicity, neurotoxicity, genotoxicity, carcinogenicity, immunotoxicity and food allergy. They are considered from the perspective of whether they are appropriate for assessing food chemicals and whether they are adequate to detect currently known or anticipated hazards from food. Gaps in knowledge and future research needs are identified; research on these could lead to improvements in the methods of hazard identification for food chemicals. The potential impact of some emerging techniques and toxicological issues on hazard identification for food chemicals, such as new measurement techniques, the use of transgenic animals, assessment of hormone balance and the possibilities for conducting studies in which common human diseases have been modelled, is also considered.

Species identification in forensic samples using the SPInDel approach: A GHEP-ISFG inter-laboratory collaborative exercise.

PubMed

Alves, Cíntia; Pereira, Rui; Prieto, Lourdes; Aler, Mercedes; Amaral, Cesar R L; Arévalo, Cristina; Berardi, Gabriela; Di Rocco, Florencia; Caputo, Mariela; Carmona, Cristian Hernandez; Catelli, Laura; Costa, Heloísa Afonso; Coufalova, Pavla; Furfuro, Sandra; García, Óscar; Gaviria, Anibal; Goios, Ana; Gómez, Juan José Builes; Hernández, Alexis; Hernández, Eva Del Carmen Betancor; Miranda, Luís; Parra, David; Pedrosa, Susana; Porto, Maria João Anjos; Rebelo, Maria de Lurdes; Spirito, Matteo; Torres, María Del Carmen Villalobos; Amorim, António; Pereira, Filipe

2017-05-01

DNA is a powerful tool available for forensic investigations requiring identification of species. However, it is necessary to develop and validate methods able to produce results in degraded and or low quality DNA samples with the high standards obligatory in forensic research. Here, we describe a voluntary collaborative exercise to test the recently developed Species Identification by Insertions/Deletions (SPInDel) method. The SPInDel kit allows the identification of species by the generation of numeric profiles combining the lengths of six mitochondrial ribosomal RNA (rRNA) gene regions amplified in a single reaction followed by capillary electrophoresis. The exercise was organized during 2014 by a Working Commission of the Spanish and Portuguese-Speaking Working Group of the International Society for Forensic Genetics (GHEP-ISFG), created in 2013. The 24 participating laboratories from 10 countries were asked to identify the species in 11 DNA samples from previous GHEP-ISFG proficiency tests using a SPInDel primer mix and control samples of the 10 target species. A computer software was also provided to the participants to assist the analyses of the results. All samples were correctly identified by 22 of the 24 laboratories, including samples with low amounts of DNA (hair shafts) and mixtures of saliva and blood. Correct species identifications were obtained in 238 of the 241 (98.8%) reported SPInDel profiles. Two laboratories were responsible for the three cases of misclassifications. The SPInDel was efficient in the identification of species in mixtures considering that only a single laboratory failed to detect a mixture in one sample. This result suggests that SPInDel is a valid method for mixture analyses without the need for DNA sequencing, with the advantage of identifying more than one species in a single reaction. The low frequency of wrong (5.0%) and missing (2.1%) alleles did not interfere with the correct species identification, which demonstrated the advantage of using a method based on the analysis of multiple loci. Overall, the SPInDel method was easily implemented by laboratories using different genotyping platforms, the interpretation of results was straightforward and the SPInDel software was used without any problems. The results of this collaborative exercise indicate that the SPInDel method can be applied successfully in forensic casework investigations. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1997-01-01

This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Theodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modern three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.

Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1997-01-01

This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Tbeodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modem three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.

Kennard-Stone combined with least square support vector machine method for noncontact discriminating human blood species

NASA Astrophysics Data System (ADS)

Zhang, Linna; Li, Gang; Sun, Meixiu; Li, Hongxiao; Wang, Zhennan; Li, Yingxin; Lin, Ling

2017-11-01

Identifying whole bloods to be either human or nonhuman is an important responsibility for import-export ports and inspection and quarantine departments. Analytical methods and DNA testing methods are usually destructive. Previous studies demonstrated that visible diffuse reflectance spectroscopy method can realize noncontact human and nonhuman blood discrimination. An appropriate method for calibration set selection was very important for a robust quantitative model. In this paper, Random Selection (RS) method and Kennard-Stone (KS) method was applied in selecting samples for calibration set. Moreover, proper stoichiometry method can be greatly beneficial for improving the performance of classification model or quantification model. Partial Least Square Discrimination Analysis (PLSDA) method was commonly used in identification of blood species with spectroscopy methods. Least Square Support Vector Machine (LSSVM) was proved to be perfect for discrimination analysis. In this research, PLSDA method and LSSVM method was used for human blood discrimination. Compared with the results of PLSDA method, this method could enhance the performance of identified models. The overall results convinced that LSSVM method was more feasible for identifying human and animal blood species, and sufficiently demonstrated LSSVM method was a reliable and robust method for human blood identification, and can be more effective and accurate.

Behavioral biometrics for verification and recognition of malicious software agents

NASA Astrophysics Data System (ADS)

Yampolskiy, Roman V.; Govindaraju, Venu

2008-04-01

Homeland security requires technologies capable of positive and reliable identification of humans for law enforcement, government, and commercial applications. As artificially intelligent agents improve in their abilities and become a part of our everyday life, the possibility of using such programs for undermining homeland security increases. Virtual assistants, shopping bots, and game playing programs are used daily by millions of people. We propose applying statistical behavior modeling techniques developed by us for recognition of humans to the identification and verification of intelligent and potentially malicious software agents. Our experimental results demonstrate feasibility of such methods for both artificial agent verification and even for recognition purposes.

Identification of Direct Protein Targets of Small Molecules

PubMed Central

2010-01-01

Small-molecule target identification is a vital and daunting task for the chemical biology community as well as for researchers interested in applying the power of chemical genetics to impact biology and medicine. To overcome this “target ID” bottleneck, new technologies are being developed that analyze protein–drug interactions, such as drug affinity responsive target stability (DARTS), which aims to discover the direct binding targets (and off targets) of small molecules on a proteome scale without requiring chemical modification of the compound. Here, we review the DARTS method, discuss why it works, and provide new perspectives for future development in this area. PMID:21077692

The development of scientific identification theory to conduct operation research in education management

NASA Astrophysics Data System (ADS)

Hardhienata, S.

2017-01-01

Operations research is a general method used in the study and optimization of a system through modeling of the system. In the field of education, especially in education management, operations research has not been widely used. This paper gives an exposition of ideas about how operations research can be used to conduct research and optimization in the field of education management by developing SITOREM (Scientific Identification Theory for Operation Research in Education Management). To clarify the intent of the idea, an example of applying SITOREM to enhance the professional commitment of lecturers associated with achieving the vision of university will be described.

Mark-resight abundance estimation under incomplete identification of marked individuals

USGS Publications Warehouse

McClintock, Brett T.; Hill, Jason M.; Fritz, Lowell; Chumbley, Kathryn; Luxa, Katie; Diefenbach, Duane R.

2014-01-01

Often less expensive and less invasive than conventional mark–recapture, so-called 'mark-resight' methods are popular in the estimation of population abundance. These methods are most often applied when a subset of the population of interest is marked (naturally or artificially), and non-invasive sighting data can be simultaneously collected for both marked and unmarked individuals. However, it can often be difficult to identify marked individuals with certainty during resighting surveys, and incomplete identification of marked individuals is potentially a major source of bias in mark-resight abundance estimators. Previously proposed solutions are ad hoc and will tend to underperform unless marked individual identification rates are relatively high (>90%) or individual sighting heterogeneity is negligible.Based on a complete data likelihood, we present an approach that properly accounts for uncertainty in marked individual detection histories when incomplete identifications occur. The models allow for individual heterogeneity in detection, sampling with (e.g. Poisson) or without (e.g. Bernoulli) replacement, and an unknown number of marked individuals. Using a custom Markov chain Monte Carlo algorithm to facilitate Bayesian inference, we demonstrate these models using two example data sets and investigate their properties via simulation experiments.We estimate abundance for grassland sparrow populations in Pennsylvania, USA when sampling was conducted with replacement and the number of marked individuals was either known or unknown. To increase marked individual identification probabilities, extensive territory mapping was used to assign incomplete identifications to individuals based on location. Despite marked individual identification probabilities as low as 67% in the absence of this territorial mapping procedure, we generally found little return (or need) for this time-consuming investment when using our proposed approach. We also estimate rookery abundance from Alaskan Steller sea lion counts when sampling was conducted without replacement, the number of marked individuals was unknown, and individual heterogeneity was suspected as non-negligible.In terms of estimator performance, our simulation experiments and examples demonstrated advantages of our proposed approach over previous methods, particularly when marked individual identification probabilities are low and individual heterogeneity levels are high. Our methodology can also reduce field effort requirements for marked individual identification, thus, allowing potential investment into additional marking events or resighting surveys.

Prospects and Problems for Identification of Poisonous Plants in China using DNA Barcodes.

PubMed

Xie, Lei; Wang, Ying Wei; Guan, Shan Yue; Xie, Li Jing; Long, Xin; Sun, Cheng Ye

2014-10-01

Poisonous plants are a deadly threat to public health in China. The traditional clinical diagnosis of the toxic plants is inefficient, fallible, and dependent upon experts. In this study, we tested the performance of DNA barcodes for identification of the most threatening poisonous plants in China. Seventy-four accessions of 27 toxic plant species in 22 genera and 17 families were sampled and three DNA barcodes (matK, rbcL, and ITS) were amplified, sequenced and tested. Three methods, Blast, pairwise global alignment (PWG) distance, and Tree-Building were tested for discrimination power. The primer universality of all the three markers was high. Except in the case of ITS for Hemerocallis minor, the three barcodes were successfully generated from all the selected species. Among the three methods applied, Blast showed the lowest discrimination rate, whereas PWG Distance and Tree-Building methods were equally effective. The ITS barcode showed highest discrimination rates using the PWG Distance and Tree-Building methods. When the barcodes were combined, discrimination rates were increased for the Blast method. DNA barcoding technique provides us a fast tool for clinical identification of poisonous plants in China. We suggest matK, rbcL, ITS used in combination as DNA barcodes for authentication of poisonous plants. Copyright © 2014 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.

Rapid Identification of Microorganisms from Positive Blood Culture by MALDI-TOF MS After Short-Term Incubation on Solid Medium.

PubMed

Curtoni, Antonio; Cipriani, Raffaella; Marra, Elisa Simona; Barbui, Anna Maria; Cavallo, Rossana; Costa, Cristina

2017-01-01

Matrix-assisted laser-desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) is a useful tool for rapid identification of microorganisms. Unfortunately, its direct application to positive blood culture is still lacking standardized procedures. In this study, we evaluated an easy- and rapid-to-perform protocol for MALDI-TOF MS direct identification of microorganisms from positive blood culture after a short-term incubation on solid medium. This protocol was used to evaluate direct identification of microorganisms from 162 positive monomicrobial blood cultures; at different incubation times (3, 5, 24 h), MALDI-TOF MS assay was performed from the growing microorganism patina. Overall, MALDI-TOF MS concordance with conventional methods at species level was 60.5, 80.2, and 93.8% at 3, 5, and 24 h, respectively. Considering only bacteria, the identification performances at species level were 64.1, 85.0, and 94.1% at 3, 5, and 24 h, respectively. This protocol applied to a commercially available MS typing system may represent, a fast and powerful diagnostic tool for pathogen direct identification and for a promptly and pathogen-driven antimicrobial therapy in selected cases.

Wavelet neural networks: a practical guide.

PubMed

Alexandridis, Antonios K; Zapranis, Achilleas D

2013-06-01

Wavelet networks (WNs) are a new class of networks which have been used with great success in a wide range of applications. However a general accepted framework for applying WNs is missing from the literature. In this study, we present a complete statistical model identification framework in order to apply WNs in various applications. The following subjects were thoroughly examined: the structure of a WN, training methods, initialization algorithms, variable significance and variable selection algorithms, model selection methods and finally methods to construct confidence and prediction intervals. In addition the complexity of each algorithm is discussed. Our proposed framework was tested in two simulated cases, in one chaotic time series described by the Mackey-Glass equation and in three real datasets described by daily temperatures in Berlin, daily wind speeds in New York and breast cancer classification. Our results have shown that the proposed algorithms produce stable and robust results indicating that our proposed framework can be applied in various applications. Copyright © 2013 Elsevier Ltd. All rights reserved.

41 CFR 102-34.190 - What special requirements apply to exempted motor vehicles using District of Columbia or State...

Code of Federal Regulations, 2014 CFR

2014-01-01

... Registering Motor Vehicles Identification Exemptions § 102-34.190 What special requirements apply to exempted... and motor vehicle identification. The agency head must provide the name and signature of that official... requirements apply to exempted motor vehicles using District of Columbia or State license plates? 102-34.190...

41 CFR 102-34.190 - What special requirements apply to exempted motor vehicles using District of Columbia or State...

Code of Federal Regulations, 2010 CFR

2010-07-01

... Registering Motor Vehicles Identification Exemptions § 102-34.190 What special requirements apply to exempted... and motor vehicle identification. The agency head must provide the name and signature of that official... requirements apply to exempted motor vehicles using District of Columbia or State license plates? 102-34.190...

41 CFR 102-34.190 - What special requirements apply to exempted motor vehicles using District of Columbia or State...

Code of Federal Regulations, 2011 CFR

2011-01-01

... Registering Motor Vehicles Identification Exemptions § 102-34.190 What special requirements apply to exempted... and motor vehicle identification. The agency head must provide the name and signature of that official... requirements apply to exempted motor vehicles using District of Columbia or State license plates? 102-34.190...

41 CFR 102-34.190 - What special requirements apply to exempted motor vehicles using District of Columbia or State...

Code of Federal Regulations, 2012 CFR

2012-01-01

... Registering Motor Vehicles Identification Exemptions § 102-34.190 What special requirements apply to exempted... and motor vehicle identification. The agency head must provide the name and signature of that official... requirements apply to exempted motor vehicles using District of Columbia or State license plates? 102-34.190...

41 CFR 102-34.190 - What special requirements apply to exempted motor vehicles using District of Columbia or State...

Code of Federal Regulations, 2013 CFR

2013-07-01

... Registering Motor Vehicles Identification Exemptions § 102-34.190 What special requirements apply to exempted... and motor vehicle identification. The agency head must provide the name and signature of that official... requirements apply to exempted motor vehicles using District of Columbia or State license plates? 102-34.190...

SCI Identification (SCIDNT) program user's guide. [maximum likelihood method for linear rotorcraft models

NASA Technical Reports Server (NTRS)

1979-01-01

The computer program Linear SCIDNT which evaluates rotorcraft stability and control coefficients from flight or wind tunnel test data is described. It implements the maximum likelihood method to maximize the likelihood function of the parameters based on measured input/output time histories. Linear SCIDNT may be applied to systems modeled by linear constant-coefficient differential equations. This restriction in scope allows the application of several analytical results which simplify the computation and improve its efficiency over the general nonlinear case.

Machine Learning Methods for Production Cases Analysis

NASA Astrophysics Data System (ADS)

Mokrova, Nataliya V.; Mokrov, Alexander M.; Safonova, Alexandra V.; Vishnyakov, Igor V.

2018-03-01

Approach to analysis of events occurring during the production process were proposed. Described machine learning system is able to solve classification tasks related to production control and hazard identification at an early stage. Descriptors of the internal production network data were used for training and testing of applied models. k-Nearest Neighbors and Random forest methods were used to illustrate and analyze proposed solution. The quality of the developed classifiers was estimated using standard statistical metrics, such as precision, recall and accuracy.

Positron lifetime beam for defect studies in thin epitaxial semiconductor structures

NASA Astrophysics Data System (ADS)

Laakso, A.; Saarinen, K.; Hautojärvi, P.

2001-12-01

Positron annihilation spectroscopies are methods for direct identification of vacancy-type defects by measuring positron lifetime and Doppler broadening of annihilation radiation and providing information about open volume, concentration and atoms surrounding the defect. Both these techniques are easily applied to bulk samples. Only the Doppler broadening spectroscopy can be employed in thin epitaxial samples by utilizing low-energy positron beams. Here we describe the positron lifetime beam which will provide us with a method to measure lifetime in thin semiconductor layers.

Determination of the ruminant origin of bone particles using fluorescence in situ hybridization (FISH)

PubMed Central

Lecrenier, M. C.; Ledoux, Q.; Berben, G.; Fumière, O.; Saegerman, C.; Baeten, V.; Veys, P.

2014-01-01

Molecular biology techniques such as PCR constitute powerful tools for the determination of the taxonomic origin of bones. DNA degradation and contamination by exogenous DNA, however, jeopardise bone identification. Despite the vast array of techniques used to decontaminate bone fragments, the isolation and determination of bone DNA content are still problematic. Within the framework of the eradication of transmissible spongiform encephalopathies (including BSE, commonly known as “mad cow disease”), a fluorescence in situ hybridization (FISH) protocol was developed. Results from the described study showed that this method can be applied directly to bones without a demineralisation step and that it allows the identification of bovine and ruminant bones even after severe processing. The results also showed that the method is independent of exogenous contamination and that it is therefore entirely appropriate for this application. PMID:25034259

Determination of the ruminant origin of bone particles using fluorescence in situ hybridization (FISH).

PubMed

Lecrenier, M C; Ledoux, Q; Berben, G; Fumière, O; Saegerman, C; Baeten, V; Veys, P

2014-07-17

Molecular biology techniques such as PCR constitute powerful tools for the determination of the taxonomic origin of bones. DNA degradation and contamination by exogenous DNA, however, jeopardise bone identification. Despite the vast array of techniques used to decontaminate bone fragments, the isolation and determination of bone DNA content are still problematic. Within the framework of the eradication of transmissible spongiform encephalopathies (including BSE, commonly known as "mad cow disease"), a fluorescence in situ hybridization (FISH) protocol was developed. Results from the described study showed that this method can be applied directly to bones without a demineralisation step and that it allows the identification of bovine and ruminant bones even after severe processing. The results also showed that the method is independent of exogenous contamination and that it is therefore entirely appropriate for this application.

Research on numerical algorithms for large space structures

NASA Technical Reports Server (NTRS)

Denman, E. D.

1982-01-01

Numerical algorithms for large space structures were investigated with particular emphasis on decoupling method for analysis and design. Numerous aspects of the analysis of large systems ranging from the algebraic theory to lambda matrices to identification algorithms were considered. A general treatment of the algebraic theory of lambda matrices is presented and the theory is applied to second order lambda matrices.

Tandem Affinity Purification of Protein Complexes from Eukaryotic Cells.

PubMed

Ma, Zheng; Fung, Victor; D'Orso, Iván

2017-01-26

The purification of active protein-protein and protein-nucleic acid complexes is crucial for the characterization of enzymatic activities and de novo identification of novel subunits and post-translational modifications. Bacterial systems allow for the expression and purification of a wide variety of single polypeptides and protein complexes. However, this system does not enable the purification of protein subunits that contain post-translational modifications (e.g., phosphorylation and acetylation), and the identification of novel regulatory subunits that are only present/expressed in the eukaryotic system. Here, we provide a detailed description of a novel, robust, and efficient tandem affinity purification (TAP) method using STREP- and FLAG-tagged proteins that facilitates the purification of protein complexes with transiently or stably expressed epitope-tagged proteins from eukaryotic cells. This protocol can be applied to characterize protein complex functionality, to discover post-translational modifications on complex subunits, and to identify novel regulatory complex components by mass spectrometry. Notably, this TAP method can be applied to study protein complexes formed by eukaryotic or pathogenic (viral and bacterial) components, thus yielding a wide array of downstream experimental opportunities. We propose that researchers working with protein complexes could utilize this approach in many different ways.

A model-based approach to wildland fire reconstruction using sediment charcoal records

USGS Publications Warehouse

Itter, Malcolm S.; Finley, Andrew O.; Hooten, Mevin B.; Higuera, Philip E.; Marlon, Jennifer R.; Kelly, Ryan; McLachlan, Jason S.

2017-01-01

Lake sediment charcoal records are used in paleoecological analyses to reconstruct fire history, including the identification of past wildland fires. One challenge of applying sediment charcoal records to infer fire history is the separation of charcoal associated with local fire occurrence and charcoal originating from regional fire activity. Despite a variety of methods to identify local fires from sediment charcoal records, an integrated statistical framework for fire reconstruction is lacking. We develop a Bayesian point process model to estimate the probability of fire associated with charcoal counts from individual-lake sediments and estimate mean fire return intervals. A multivariate extension of the model combines records from multiple lakes to reduce uncertainty in local fire identification and estimate a regional mean fire return interval. The univariate and multivariate models are applied to 13 lakes in the Yukon Flats region of Alaska. Both models resulted in similar mean fire return intervals (100–350 years) with reduced uncertainty under the multivariate model due to improved estimation of regional charcoal deposition. The point process model offers an integrated statistical framework for paleofire reconstruction and extends existing methods to infer regional fire history from multiple lake records with uncertainty following directly from posterior distributions.

Identification of unusual events in multichannel bridge monitoring data using wavelet transform and outlier analysis

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr; Brownjohn, James M. W.; Moyo, Pilate

2003-08-01

Continuously operating instrumented structural health monitoring (SHM) systems are becoming a practical alternative to replace visual inspection for assessment of condition and soundness of civil infrastructure. However, converting large amount of data from an SHM system into usable information is a great challenge to which special signal processing techniques must be applied. This study is devoted to identification of abrupt, anomalous and potentially onerous events in the time histories of static, hourly sampled strains recorded by a multi-sensor SHM system installed in a major bridge structure in Singapore and operating continuously for a long time. Such events may result, among other causes, from sudden settlement of foundation, ground movement, excessive traffic load or failure of post-tensioning cables. A method of outlier detection in multivariate data has been applied to the problem of finding and localizing sudden events in the strain data. For sharp discrimination of abrupt strain changes from slowly varying ones wavelet transform has been used. The proposed method has been successfully tested using known events recorded during construction of the bridge, and later effectively used for detection of anomalous post-construction events.

Real-time radionuclide identification in γ-emitter mixtures based on spiking neural network.

PubMed

Bobin, C; Bichler, O; Lourenço, V; Thiam, C; Thévenin, M

2016-03-01

Portal radiation monitors dedicated to the prevention of illegal traffic of nuclear materials at international borders need to deliver as fast as possible a radionuclide identification of a potential radiological threat. Spectrometry techniques applied to identify the radionuclides contributing to γ-emitter mixtures are usually performed using off-line spectrum analysis. As an alternative to these usual methods, a real-time processing based on an artificial neural network and Bayes' rule is proposed for fast radionuclide identification. The validation of this real-time approach was carried out using γ-emitter spectra ((241)Am, (133)Ba, (207)Bi, (60)Co, (137)Cs) obtained with a high-efficiency well-type NaI(Tl). The first tests showed that the proposed algorithm enables a fast identification of each γ-emitting radionuclide using the information given by the whole spectrum. Based on an iterative process, the on-line analysis only needs low-statistics spectra without energy calibration to identify the nature of a radiological threat. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products

NASA Technical Reports Server (NTRS)

Radkevich, Alexander; Khlopenkov, Konstantin; Rutan, David; Kato, Seiji

2013-01-01

Identification of clear-sky snow and ice is an important step in the production of cryosphere radiation budget products, which are used in the derivation of long-term data series for climate research. In this paper, a new method of clear-sky snow/ice identification for Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. The algorithm's goal is to enhance the identification of snow and ice within the Clouds and the Earth's Radiant Energy System (CERES) data after application of the standard CERES scene identification scheme. The input of the algorithm uses spectral radiances from five MODIS bands and surface skin temperature available in the CERES Single Scanner Footprint (SSF) product. The algorithm produces a cryosphere rating from an aggregated test: a higher rating corresponds to a more certain identification of the clear-sky snow/ice-covered scene. Empirical analysis of regions of interest representing distinctive targets such as snow, ice, ice and water clouds, open waters, and snow-free land selected from a number of MODIS images shows that the cryosphere rating of snow/ice targets falls into 95% confidence intervals lying above the same confidence intervals of all other targets. This enables recognition of clear-sky cryosphere by using a single threshold applied to the rating, which makes this technique different from traditional branching techniques based on multiple thresholds. Limited tests show that the established threshold clearly separates the cryosphere rating values computed for the cryosphere from those computed for noncryosphere scenes, whereas individual tests applied consequently cannot reliably identify the cryosphere for complex scenes.

SANIST: optimization of a technology for compound identification based on the European Union directive with applications in forensic, pharmaceutical and food analyses.

PubMed

Cristoni, Simone; Dusi, Guglielmo; Brambilla, Paolo; Albini, Adriana; Conti, Matteo; Brambilla, Maura; Bruno, Antonino; Di Gaudio, Francesca; Ferlin, Luca; Tazzari, Valeria; Mengozzi, Silvia; Barera, Simone; Sialer, Carlos; Trenti, Tommaso; Cantu, Marco; Rossi Bernardi, Luigi; Noonan, Douglas M

2017-01-01

Electrospray Ionization and collision induced dissociation tandem mass spectrometry are usually employed to obtain compound identification through a mass spectra match. Different algorithms have been developed for this purpose (for example the nist match algorithm). These approaches compare the tandem mass spectra of the unknown analyte with the tandem mass spectra spectra of known compounds inserted in a database. The compounds are usually identified on the basis of spectral match value associated with a probability of recognition. However, this approach is not usually applied to multiple reaction monitoring transition spectra achieved by means of triple quadrupole apparatus, mainly due to the lack of a transition spectra database. The Surface Activated Chemical Ionization-Electrospray-NIST Bayesian model database search (SANIST) platform has been recently developed for new potential metabolite biomarker discovery, to confirm their identity and to use them for clinical and diagnostic applications. Here, we present an improved version of the SANIST platform that extends its application to forensic, pharmaceutical, and food analysis studies, where the compound identification rules are strict. The European Union (EU) has set directives for compound identification (EU directive 2002/657/EC). We have applied the SANIST method to identification of 11-nor-9-carboxytetrahydro-cannabinol in urine samples (an example of a forensic application), circulating levels of the immunosuppressive drug tacrolimus in blood (an example of a pharmaceutical application) and glyphosate in fruit juice (an example of a food analysis application) that meet the EU directive requirements. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Highly efficient classification and identification of human pathogenic bacteria by MALDI-TOF MS.

PubMed

Hsieh, Sen-Yung; Tseng, Chiao-Li; Lee, Yun-Shien; Kuo, An-Jing; Sun, Chien-Feng; Lin, Yen-Hsiu; Chen, Jen-Kun

2008-02-01

Accurate and rapid identification of pathogenic microorganisms is of critical importance in disease treatment and public health. Conventional work flows are time-consuming, and procedures are multifaceted. MS can be an alternative but is limited by low efficiency for amino acid sequencing as well as low reproducibility for spectrum fingerprinting. We systematically analyzed the feasibility of applying MS for rapid and accurate bacterial identification. Directly applying bacterial colonies without further protein extraction to MALDI-TOF MS analysis revealed rich peak contents and high reproducibility. The MS spectra derived from 57 isolates comprising six human pathogenic bacterial species were analyzed using both unsupervised hierarchical clustering and supervised model construction via the Genetic Algorithm. Hierarchical clustering analysis categorized the spectra into six groups precisely corresponding to the six bacterial species. Precise classification was also maintained in an independently prepared set of bacteria even when the numbers of m/z values were reduced to six. In parallel, classification models were constructed via Genetic Algorithm analysis. A model containing 18 m/z values accurately classified independently prepared bacteria and identified those species originally not used for model construction. Moreover bacteria fewer than 10(4) cells and different species in bacterial mixtures were identified using the classification model approach. In conclusion, the application of MALDI-TOF MS in combination with a suitable model construction provides a highly accurate method for bacterial classification and identification. The approach can identify bacteria with low abundance even in mixed flora, suggesting that a rapid and accurate bacterial identification using MS techniques even before culture can be attained in the near future.

An Improved In-house MALDI-TOF MS Protocol for Direct Cost-Effective Identification of Pathogens from Blood Cultures.

PubMed

Zhou, Menglan; Yang, Qiwen; Kudinha, Timothy; Sun, Liying; Zhang, Rui; Liu, Chang; Yu, Shuying; Xiao, Meng; Kong, Fanrong; Zhao, Yupei; Xu, Ying-Chun

2017-01-01

Background: Bloodstream infection is a major cause of morbidity and mortality in hospitalized patients worldwide. Delays in the identification of microorganisms often leads to a poor prognosis. The application of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) directly to blood culture (BC) broth can potentially identify bloodstream infections earlier, and facilitate timely management. Methods: We developed an "in-house" (IH) protocol for direct MALDI-TOF MS based identification of organisms in positive BCs. The IH protocol was initially evaluated and improved with spiked BC samples, and its performance was compared with the commercial Sepsityper™ kit using both traditional and modified cut-off values. We then studied in parallel the performance of the IH protocol and the colony MS identifications in positive clinical BC samples using only modified cut-off values. All discrepancies were investigated by "gold standard" of gene sequencing. Results: In 54 spiked BC samples, the IH method showed comparable results with Sepsityper™ after applying modified cut-off values. Specifically, accurate species and genus level identification was achieved in 88.7 and 3.9% of all the clinical monomicrobial BCs (284/301, 94.4%), respectively. The IH protocol exhibited superior performance for Gram negative bacteria than for Gram positive bacteria (92.8 vs. 82.4%). For anaerobes and yeasts, accurate species identification was achieved in 80.0 and 90.0% of the cases, respectively. For polymicrobial cultures (17/301, 5.6%), MALDI-TOF MS correctly identified a single species present in all the polymicrobial BCs under the Standard mode, while using the MIXED method, two species were correctly identified in 52.9% of the samples. Comparisons based on BC bottle type, showed that the BACTEC™ Lytic/10 Anaerobic/F culture vials performed the best. Conclusion: Our study provides a novel and effective sample preparation method for MALDI-TOF MS direct identification of pathogens from positive BC vials, with a lower cost ($1.5 vs. $ 7) albeit a slightly more laborious extracting process (an extra 15 min) compared with Sepsityper™ kit.

Identification of New Cocrystal Systems with Stoichiometric Diversity of Salicylic Acid Using Thermal Methods.

PubMed

Zhou, Zhengzheng; Chan, Hok Man; Sung, Herman H-Y; Tong, Henry H Y; Zheng, Ying

2016-04-01

The purpose of this work was to develop thermal methods to identify cocrystal systems with stoichiometric diversity. Differential scanning calorimetry (DSC) and hot stage microscopy (HSM) have been applied to study the stoichiometric diversity phenomenon on cocrystal systems of the model compound salicylic acid (SA) with different coformers (CCFs). The DSC method was particularly useful in the identification of cocrystal re-crystallization, especially to improve the temperature resolution using a slower heating rate. HSM was implemented as a complementary protocol to confirm the DSC results. The crystal structures were elucidated by single-crystal X-ray diffraction (SXRD). Two new cocrystal systems consisting of salicylic acid-benzamide (SA-BZD, 1:1, 1:2) and salicylic acid-isonicotinamide (SA-ISN, 1:1, 2:1) have been identified in the present work. The chemical structures of the newly discovered cocrystals SA-BZD (1:2) and SA-ISN (2:1) have been elucidated using X-ray single crystal and powder diffraction methods. The developed thermal methods could rapidly identify cocrystal systems with stoichiometric diversity, with the potential to discover new pharmaceutical cocrystals in the future.

Extended Kalman filtering for the detection of damage in linear mechanical structures

NASA Astrophysics Data System (ADS)

Liu, X.; Escamilla-Ambrosio, P. J.; Lieven, N. A. J.

2009-09-01

This paper addresses the problem of assessing the location and extent of damage in a vibrating structure by means of vibration measurements. Frequency domain identification methods (e.g. finite element model updating) have been widely used in this area while time domain methods such as the extended Kalman filter (EKF) method, are more sparsely represented. The difficulty of applying EKF in mechanical system damage identification and localisation lies in: the high computational cost, the dependence of estimation results on the initial estimation error covariance matrix P(0), the initial value of parameters to be estimated, and on the statistics of measurement noise R and process noise Q. To resolve these problems in the EKF, a multiple model adaptive estimator consisting of a bank of EKF in modal domain was designed, each filter in the bank is based on different P(0). The algorithm was iterated by using the weighted global iteration method. A fuzzy logic model was incorporated in each filter to estimate the variance of the measurement noise R. The application of the method is illustrated by simulated and real examples.

An automated method of quantifying ferrite microstructures using electron backscatter diffraction (EBSD) data.

PubMed

Shrestha, Sachin L; Breen, Andrew J; Trimby, Patrick; Proust, Gwénaëlle; Ringer, Simon P; Cairney, Julie M

2014-02-01

The identification and quantification of the different ferrite microconstituents in steels has long been a major challenge for metallurgists. Manual point counting from images obtained by optical and scanning electron microscopy (SEM) is commonly used for this purpose. While classification systems exist, the complexity of steel microstructures means that identifying and quantifying these phases is still a great challenge. Moreover, point counting is extremely tedious, time consuming, and subject to operator bias. This paper presents a new automated identification and quantification technique for the characterisation of complex ferrite microstructures by electron backscatter diffraction (EBSD). This technique takes advantage of the fact that different classes of ferrite exhibit preferential grain boundary misorientations, aspect ratios and mean misorientation, all of which can be detected using current EBSD software. These characteristics are set as criteria for identification and linked to grain size to determine the area fractions. The results of this method were evaluated by comparing the new automated technique with point counting results. The technique could easily be applied to a range of other steel microstructures. © 2013 Published by Elsevier B.V.

Identification of eggs from different production systems based on hyperspectra and CS-SVM.

PubMed

Sun, J; Cong, S L; Mao, H P; Zhou, X; Wu, X H; Zhang, X D

2017-06-01

1. To identify the origin of table eggs more accurately, a method based on hyperspectral imaging technology was studied. 2. The hyperspectral data of 200 samples of intensive and extensive eggs were collected. Standard normalised variables combined with a Savitzky-Golay were used to eliminate noise, then stepwise regression (SWR) was used for feature selection. Grid search algorithm (GS), genetic search algorithm (GA), particle swarm optimisation algorithm (PSO) and cuckoo search algorithm (CS) were applied by support vector machine (SVM) methods to establish an SVM identification model with the optimal parameters. The full spectrum data and the data after feature selection were the input of the model, while egg category was the output. 3. The SWR-CS-SVM model performed better than the other models, including SWR-GS-SVM, SWR-GA-SVM, SWR-PSO-SVM and others based on full spectral data. The training and test classification accuracy of the SWR-CS-SVM model were respectively 99.3% and 96%. 4. SWR-CS-SVM proved effective for identifying egg varieties and could also be useful for the non-destructive identification of other types of egg.

Identification of multivariable nonlinear systems in the presence of colored noises using iterative hierarchical least squares algorithm.

PubMed

Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam

2014-07-01

This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Multiplex-PCR As a Rapid and Sensitive Method for Identification of Meat Species in Halal-Meat Products.

PubMed

Alikord, Mahsa; Keramat, Javad; Kadivar, Mahdi; Momtaz, Hassan; Eshtiaghi, Mohammad N; Homayouni-Rad, Aziz

2017-01-01

Species identification and authentication in meat products are important subjects for ensuring the health of consumers. The multiplex-PCR amplification and species- specific primer set were used for the identification of horse, donkey, pig and other ruminants in raw and processed meat products. Oligonucleotid primers were designed and patented for amplification of species-specific mitochondrial DNA sequences of each species and samples were prepared from binary meat mixtures. The results showed that meat species were accurately determined in all combinations by multiplex-PCR, and the sensitivity of this method was 0.001 ng, rendering this technique open to and suitable for use in industrial meat products. It is concluded that more fraud is seen in lower percentage industrial meat products than in higher percentage ones. There was also more fraud found in processed products than in raw ones. This rapid and useful test is recommended for quality control firms for applying more rigorous controls over industrial meat products, for the benefit of target consumers. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A volumetric pulmonary CT segmentation method with applications in emphysema assessment

NASA Astrophysics Data System (ADS)

Silva, José Silvestre; Silva, Augusto; Santos, Beatriz S.

2006-03-01

A segmentation method is a mandatory pre-processing step in many automated or semi-automated analysis tasks such as region identification and densitometric analysis, or even for 3D visualization purposes. In this work we present a fully automated volumetric pulmonary segmentation algorithm based on intensity discrimination and morphologic procedures. Our method first identifies the trachea as well as primary bronchi and then the pulmonary region is identified by applying a threshold and morphologic operations. When both lungs are in contact, additional procedures are performed to obtain two separated lung volumes. To evaluate the performance of the method, we compared contours extracted from 3D lung surfaces with reference contours, using several figures of merit. Results show that the worst case generally occurs at the middle sections of high resolution CT exams, due the presence of aerial and vascular structures. Nevertheless, the average error is inferior to the average error associated with radiologist inter-observer variability, which suggests that our method produces lung contours similar to those drawn by radiologists. The information created by our segmentation algorithm is used by an identification and representation method in pulmonary emphysema that also classifies emphysema according to its severity degree. Two clinically proved thresholds are applied which identify regions with severe emphysema, and with highly severe emphysema. Based on this thresholding strategy, an application for volumetric emphysema assessment was developed offering new display paradigms concerning the visualization of classification results. This framework is easily extendable to accommodate other classifiers namely those related with texture based segmentation as it is often the case with interstitial diseases.

Distinguishing time-delayed causal interactions using convergent cross mapping

PubMed Central

Ye, Hao; Deyle, Ethan R.; Gilarranz, Luis J.; Sugihara, George

2015-01-01

An important problem across many scientific fields is the identification of causal effects from observational data alone. Recent methods (convergent cross mapping, CCM) have made substantial progress on this problem by applying the idea of nonlinear attractor reconstruction to time series data. Here, we expand upon the technique of CCM by explicitly considering time lags. Applying this extended method to representative examples (model simulations, a laboratory predator-prey experiment, temperature and greenhouse gas reconstructions from the Vostok ice core, and long-term ecological time series collected in the Southern California Bight), we demonstrate the ability to identify different time-delayed interactions, distinguish between synchrony induced by strong unidirectional-forcing and true bidirectional causality, and resolve transitive causal chains. PMID:26435402

Identification of material constants for piezoelectric transformers by three-dimensional, finite-element method and a design-sensitivity method.

PubMed

Joo, Hyun-Woo; Lee, Chang-Hwan; Rho, Jong-Seok; Jung, Hyun-Kyo

2003-08-01

In this paper, an inversion scheme for piezoelectric constants of piezoelectric transformers is proposed. The impedance of piezoelectric transducers is calculated using a three-dimensional finite element method. The validity of this is confirmed experimentally. The effects of material coefficients on piezoelectric transformers are investigated numerically. Six material coefficient variables for piezoelectric transformers were selected, and a design sensitivity method was adopted as an inversion scheme. The validity of the proposed method was confirmed by step-up ratio calculations. The proposed method is applied to the analysis of a sample piezoelectric transformer, and its resonance characteristics are obtained by numerically combined equivalent circuit method.

Research on filter’s parameter selection based on PROMETHEE method

NASA Astrophysics Data System (ADS)

Zhu, Hui-min; Wang, Hang-yu; Sun, Shi-yan

2018-03-01

The selection of filter’s parameters in target recognition was studied in this paper. The PROMETHEE method was applied to the optimization problem of Gabor filter parameters decision, the correspondence model of the elemental relation between two methods was established. The author took the identification of military target as an example, problem about the filter’s parameter decision was simulated and calculated by PROMETHEE. The result showed that using PROMETHEE method for the selection of filter’s parameters was more scientific. The human disturbance caused by the experts method and empirical method could be avoided by this way. The method can provide reference for the parameter configuration scheme decision of the filter.

Compressive sensing method for recognizing cat-eye effect targets.

PubMed

Li, Li; Li, Hui; Dang, Ersheng; Liu, Bo

2013-10-01

This paper proposes a cat-eye effect target recognition method with compressive sensing (CS) and presents a recognition method (sample processing before reconstruction based on compressed sensing, or SPCS) for image processing. In this method, the linear projections of original image sequences are applied to remove dynamic background distractions and extract cat-eye effect targets. Furthermore, the corresponding imaging mechanism for acquiring active and passive image sequences is put forward. This method uses fewer images to recognize cat-eye effect targets, reduces data storage, and translates the traditional target identification, based on original image processing, into measurement vectors processing. The experimental results show that the SPCS method is feasible and superior to the shape-frequency dual criteria method.

An novel identification method of the environmental risk sources for surface water pollution accidents in chemical industrial parks.

PubMed

Peng, Jianfeng; Song, Yonghui; Yuan, Peng; Xiao, Shuhu; Han, Lu

2013-07-01

The chemical industry is a major source of various pollution accidents. Improving the management level of risk sources for pollution accidents has become an urgent demand for most industrialized countries. In pollution accidents, the released chemicals harm the receptors to some extent depending on their sensitivity or susceptibility. Therefore, identifying the potential risk sources from such a large number of chemical enterprises has become pressingly urgent. Based on the simulation of the whole accident process, a novel and expandable identification method for risk sources causing water pollution accidents is presented. The newly developed approach, by analyzing and stimulating the whole process of a pollution accident between sources and receptors, can be applied to identify risk sources, especially on the nationwide scale. Three major types of losses, such as social, economic and ecological losses, were normalized, analyzed and used for overall consequence modeling. A specific case study area, located in a chemical industry park (CIP) along the Yangtze River in Jiangsu Province, China, was selected to test the potential of the identification method. The results showed that there were four risk sources for pollution accidents in this CIP. Aniline leakage in the HS Chemical Plant would lead to the most serious impact on the surrounding water environment. This potential accident would severely damage the ecosystem up to 3.8 km downstream of Yangtze River, and lead to pollution over a distance stretching to 73.7 km downstream. The proposed method is easily extended to the nationwide identification of potential risk sources.

Mass spectrometric profiling of flavonoid glycoconjugates possessing isomeric aglycones.

PubMed

Abrankó, László; Szilvássy, Blanka

2015-01-01

In fields such as food and nutrition science or plant physiology, interest in untargeted profiling of flavonoids continues to expand. The group of flavonoids encompasses several thousands of chemically distinguishable compounds, among which are a number of isobaric compounds with the same elemental composition. Thus, the mass spectrometric identification of these compounds is challenging, especially when reference standards are not available to support their identification. Many different types of isomers of flavonoid glycoconjugates are known, i.e. compounds that differ in their glycosylation position, glycan sequence or type of interglycosidic linkage. This work focuses on the mass spectrometric identification of flavonoid glycoconjugate isomers possessing the same glycan mass and differing only in their aglycone core. A non-targeted HPLC-ESI-MS/MS profiling method using a triple quadrupole MS is presented herein, which utilizes in-source fragmentation and a pseudo-MS(3) approach for the selective analysis of flavonoid glycoconjugates with isomeric/isobaric aglycones. A selective MRM-based identification of the in-source formed isobaric aglycone fragments was established. Additionally, utilizing the precursor scanning capability of the employed triple quadrupole instrument, the developed method enabled the determination of the molecular weight of the studied intact flavonoid glycoconjugate. The versatility of the method was proven with various types of flavonoid aglycones, i.e. anthocyanins, flavonols, flavones, flavanones and isoflavones, along with their representative glycoconjugates. The developed method was also successfully applied to a commercially available sour cherry sample, in which 16 different glycoconjugates of pelargonidin, genistein, cyanidin, kaempferol and quercetin could be tentatively identified, including a number of compounds containing isomeric/isobaric aglycones. Copyright © 2015 John Wiley & Sons, Ltd.

Identification of five highly priced tuna species by quantitative real-time polymerase chain reaction.

PubMed

Liu, Shasha; Xu, Kunhua; Wu, Zhigang; Xie, Xiao; Feng, Junli

2016-09-01

Tunas are economically important fishery worldwide, and are often used for commercial processed production. For effective fishery management and protection of consumers' rights, it is important to develop a molecular method to identify species in canned tuna products rapidly and reliably. Here, we have developed a duplex quantitative real-time PCR (qPCR) for identification of five highly priced tuna species (Thunnus maccoyii, Thunnus obesus, Thunnus albacares, Thunnus alalunga and Katsuwonus pelamis) from processed as well as fresh fish. After amplification and sequencing of seven genetic markers commonly used for species identification, 16S rDNA and control region (CR) of mitochondrial DNA were selected as the reference gene markers for genus Thunnus and tuna species identification, respectively. Subsequently, a 73 bp fragment of 16S rDNA and 85-99 bp fragment of CR were simultaneously amplified from each target species by qPCR. The qPCR efficiency of each reaction was calculated according to the standard curves, and the method was validated by amplification DNA extracted from single or mixed tuna specimen. The developed duplex qPCR system was applied to authenticate species of 14 commercial tuna products successfully, which demonstrated it was really a useful and academic technique to identify highly priced tuna species.

ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data.

PubMed

Oluwadare, Oluwatosin; Cheng, Jianlin

2017-11-14

With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-C technique can generate genome-wide chromosomal interaction (contact) data, which can be used to investigate the higher-level organization of chromosomes, such as Topologically Associated Domains (TAD), i.e., locally packed chromosome regions bounded together by intra chromosomal contacts. The identification of the TADs for a genome is useful for studying gene regulation, genomic interaction, and genome function. Here, we formulate the TAD identification problem as an unsupervised machine learning (clustering) problem, and develop a new TAD identification method called ClusterTAD. We introduce a novel method to represent chromosomal contacts as features to be used by the clustering algorithm. Our results show that ClusterTAD can accurately predict the TADs on a simulated Hi-C data. Our method is also largely complementary and consistent with existing methods on the real Hi-C datasets of two mouse cells. The validation with the chromatin immunoprecipitation (ChIP) sequencing (ChIP-Seq) data shows that the domain boundaries identified by ClusterTAD have a high enrichment of CTCF binding sites, promoter-related marks, and enhancer-related histone modifications. As ClusterTAD is based on a proven clustering approach, it opens a new avenue to apply a large array of clustering methods developed in the machine learning field to the TAD identification problem. The source code, the results, and the TADs generated for the simulated and real Hi-C datasets are available here: https://github.com/BDM-Lab/ClusterTAD .

Identification of the traditional methods of newborn mothers regarding jaundice in Turkey.

PubMed

Aydin, Diler; Karaca Ciftci, Esra; Karatas, Hulya

2014-02-01

To detect traditional methods applied for the treatment of newborn jaundice by mothers in Turkey. Traditional methods are generally used in our society. Instead of using medical services, people often use already-known traditional methods to treat the disease. In such cases, the prognosis of the disease generally becomes worse, the treatment period longer and healthcare costs higher, and more medicine is used. A cross-sectional descriptive study. The participants of this study were 229 mothers with newborn babies aged 0-28 days in one university hospital and one public children's hospital in Sanliurfa. The study was conducted between March and May 2012. In this research, the Beliefs and Traditional Methods of Mothers for Jaundice Questionnaire, which was formed by searching the relevant literature, is used as a data collection tool. The data are evaluated by percentage distributions. Mothers apply conventional practices in cases of health problems such as jaundice, and application of these methods is important to mothers. Moreover, mothers reported applying hazardous conventional methods in cases of neonatal jaundice, such as cutting the area between the baby's eyebrows with a blade, cutting the back of the ear and the body and burning the body, which are not applied in different cultures. Education regarding the effects of conventional methods being applied in families should be provided, and the results of this study should serve to guide further studies in assessing the effects of such education. This approach can support beneficial practices involving individual care and prevent the negative health effects of hazardous practices. © 2013 John Wiley & Sons Ltd.

Division of methods for counting helminths' eggs and the problem of efficiency of these methods.

PubMed

Jaromin-Gleń, Katarzyna; Kłapeć, Teresa; Łagód, Grzegorz; Karamon, Jacek; Malicki, Jacek; Skowrońska, Agata; Bieganowski, Andrzej

2017-03-21

From the sanitary and epidemiological aspects, information concerning the developmental forms of intestinal parasites, especially the eggs of helminths present in our environment in: water, soil, sandpits, sewage sludge, crops watered with wastewater are very important. The methods described in the relevant literature may be classified in various ways, primarily according to the methodology of the preparation of samples from environmental matrices prepared for analysis, and the sole methods of counting and chambers/instruments used for this purpose. In addition, there is a possibility to perform the classification of the research methods analyzed from the aspect of the method and time of identification of the individuals counted, or the necessity for staining them. Standard methods for identification of helminths' eggs from environmental matrices are usually characterized by low efficiency, i.e. from 30% to approximately 80%. The efficiency of the method applied may be measured in a dual way, either by using the method of internal standard or the 'Split/Spike' method. While measuring simultaneously in an examined object the efficiency of the method and the number of eggs, the 'actual' number of eggs may be calculated by multiplying the obtained value of the discovered eggs of helminths by inverse efficiency.

Lipidomics as an important key for the identification of beer-spoilage bacteria.

PubMed

Řezanka, T; Matoulková, D; Benada, O; Sigler, K

2015-06-01

Electrospray ionization-tandem mass spectrometry (ESI-MS/MS) was used for characterizing intact plasmalogen phospholipid molecules in beer-spoilage bacteria. Identification of intact plasmalogens was carried out using collision-induced dissociation and the presence of suitable marker molecular species, both qualitative and quantitative, was determined in samples containing the anaerobic bacteria Megasphaera and Pectinatus. Using selected ion monitoring (SIM), this method had a limit of detection at 1 pg for the standard, i.e. 1-(1Z-octadecenyl)-2-oleoyl-sn-glycero-3-phosphoethanolamine and be linear in the range of four orders of magnitude from 2 pg to 20 ng. This technique was applied to intact plasmalogen extracts from the samples of contaminated and uncontaminated beer without derivatization and resulted in the identification of contamination of beer by Megasphaera and Pectinatus bacteria. The limit of detection was about 830 cells of anaerobic bacteria, i.e. bacteria containing natural cyclopropane plasmalogenes (c-p-19:0/15:0), which is the majority plasmalogen located in both Megasphaera and Pectinatus. The SIM ESI-MS method has been shown to be useful for the analysis of low concentration of plasmalogens in all biological samples, which were contaminated with anaerobic bacteria, e.g. juice, not only in beer. Significance and impact of the study: Electrospray ionization-tandem mass spectrometry (ESI-MS/MS) using collision-induced dissociation was used to characterize intact plasmalogen phospholipid molecules in beer-spoilage anaerobic bacteria Megasphaera and Pectinatus. Using selected ion monitoring (SIM), this method has a detection limit of 1 pg for the standard 1-(1Z-octadecenyl)-2-oleoyl-sn-glycero-3-phosphoethanolamine and is linear within four orders of magnitude (2 pg to 20 ng). The limit of detection was about 830 cells of bacteria containing natural cyclopropane plasmalogen (c-p-19:0/15:0). SIM ESI-MS method is useful for analyzing low concentrations of plasmalogens in biological samples contaminated with anaerobic bacteria, e.g. beer or juice. © 2015 The Society for Applied Microbiology.

Identification of provenance rocks based on EPMA analyses of heavy minerals

NASA Astrophysics Data System (ADS)

Shimizu, M.; Sano, N.; Ueki, T.; Yonaga, Y.; Yasue, K. I.; Masakazu, N.

2017-12-01

Information on mountain building is significant in the field of geological disposal of high-level radioactive waste, because this affects long-term stability in groundwater flow system. Provenance analysis is one of effective approaches for understanding building process of mountains. Chemical compositions of heavy minerals, as well as their chronological data, can be an index for identification of provenance rocks. The accurate identification requires the measurement of as many grains as possible. In order to achieve an efficient provenance analysis, we developed a method for quick identification of heavy minerals using an Electron Probe Micro Analyzer (EPMA). In this method, heavy mineral grains extracted from a sample were aligned on a glass slide and mounted in a resin. Concentration of 28 elements was measured for 300-500 grains per sample using EPMA. To measure as many grains as possible, we prioritized swiftness of measurement over precision, configuring measurement time of about 3.5 minutes for each grain. Identification of heavy minerals was based on their chemical composition. We developed a Microsoft® Excel® spread sheet input criteria of mineral identification using a typical range of chemical compositions for each mineral. The grains of <80 wt.% or >110 wt.% total were rejected. The criteria of mineral identification were revised through the comparison between mineral identification by optical microscopy and chemical compositions of grains classified as "unknown minerals". Provenance rocks can be identified based on abundance ratio of identified minerals. If no significant difference of the abundance ratio was found among source rocks, chemical composition of specific minerals was used as another index. This method was applied to the sediments of some regions in Japan where provenance rocks had lithological variations but similar formation ages. Consequently, the provenance rocks were identified based on chemical compositions of heavy minerals resistant to weathering, such as zircon and ilmenite.This study was carried out under a contract with Ministry of Economy, Trade and Industry of Japan as part of its R&D supporting program for developing geological disposal technology.

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

PubMed

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

2014-12-07

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

Complex networks repair strategies: Dynamic models

NASA Astrophysics Data System (ADS)

Fu, Chaoqi; Wang, Ying; Gao, Yangjun; Wang, Xiaoyang

2017-09-01

Network repair strategies are tactical methods that restore the efficiency of damaged networks; however, unreasonable repair strategies not only waste resources, they are also ineffective for network recovery. Most extant research on network repair focuses on static networks, but results and findings on static networks cannot be applied to evolutionary dynamic networks because, in dynamic models, complex network repair has completely different characteristics. For instance, repaired nodes face more severe challenges, and require strategic repair methods in order to have a significant effect. In this study, we propose the Shell Repair Strategy (SRS) to minimize the risk of secondary node failures due to the cascading effect. Our proposed method includes the identification of a set of vital nodes that have a significant impact on network repair and defense. Our identification of these vital nodes reduces the number of switching nodes that face the risk of secondary failures during the dynamic repair process. This is positively correlated with the size of the average degree 〈 k 〉 and enhances network invulnerability.

Identification of hemoglobin variants by top-down mass spectrometry using selected diagnostic product ions.

PubMed

Coelho Graça, Didia; Hartmer, Ralf; Jabs, Wolfgang; Beris, Photis; Clerici, Lorella; Stoermer, Carsten; Samii, Kaveh; Hochstrasser, Denis; Tsybin, Yury O; Scherl, Alexander; Lescuyer, Pierre

2015-04-01

Hemoglobin disorder diagnosis is a complex procedure combining several analytical steps. Due to the lack of specificity of the currently used protein analysis methods, the identification of uncommon hemoglobin variants (proteoforms) can become a hard task to accomplish. The aim of this work was to develop a mass spectrometry-based approach to quickly identify mutated protein sequences within globin chain variants. To reach this goal, a top-down electron transfer dissociation mass spectrometry method was developed for hemoglobin β chain analysis. A diagnostic product ion list was established with a color code strategy allowing to quickly and specifically localize a mutation in the hemoglobin β chain sequence. The method was applied to the analysis of rare hemoglobin β chain variants and an (A)γ-β fusion protein. The results showed that the developed data analysis process allows fast and reliable interpretation of top-down electron transfer dissociation mass spectra by nonexpert users in the clinical area.

Can we recognize horses by their ocular biometric traits using deep convolutional neural networks?

NASA Astrophysics Data System (ADS)

Trokielewicz, Mateusz; Szadkowski, Mateusz

2017-08-01

This paper aims at determining the viability of horse recognition by the means of ocular biometrics and deep convolutional neural networks (deep CNNs). Fast and accurate identification of race horses before racing is crucial for ensuring that exactly the horses that were declared are participating, using methods that are non-invasive and friendly to these delicate animals. As typical iris recognition methods require lot of fine-tuning of the method parameters and high-quality data, CNNs seem like a natural candidate to be applied for recognition thanks to their potentially excellent abilities in describing texture, combined with ease of implementation in an end-to-end manner. Also, with such approach we can easily utilize both iris and periocular features without constructing complicated algorithms for each. We thus present a simple CNN classifier, able to correctly identify almost 80% of the samples in an identification scenario, and give equal error rate (EER) of less than 10% in a verification scenario.

Discovering latent commercial networks from online financial news articles

NASA Astrophysics Data System (ADS)

Xia, Yunqing; Su, Weifeng; Lau, Raymond Y. K.; Liu, Yi

2013-08-01

Unlike most online social networks where explicit links among individual users are defined, the relations among commercial entities (e.g. firms) may not be explicitly declared in commercial Web sites. One main contribution of this article is the development of a novel computational model for the discovery of the latent relations among commercial entities from online financial news. More specifically, a CRF model which can exploit both structural and contextual features is applied to commercial entity recognition. In addition, a point-wise mutual information (PMI)-based unsupervised learning method is developed for commercial relation identification. To evaluate the effectiveness of the proposed computational methods, a prototype system called CoNet has been developed. Based on the financial news articles crawled from Google finance, the CoNet system achieves average F-scores of 0.681 and 0.754 in commercial entity recognition and commercial relation identification, respectively. Our experimental results confirm that the proposed shallow natural language processing methods are effective for the discovery of latent commercial networks from online financial news.

Input reconstruction of chaos sensors.

PubMed

Yu, Dongchuan; Liu, Fang; Lai, Pik-Yin

2008-06-01

Although the sensitivity of sensors can be significantly enhanced using chaotic dynamics due to its extremely sensitive dependence on initial conditions and parameters, how to reconstruct the measured signal from the distorted sensor response becomes challenging. In this paper we suggest an effective method to reconstruct the measured signal from the distorted (chaotic) response of chaos sensors. This measurement signal reconstruction method applies the neural network techniques for system structure identification and therefore does not require the precise information of the sensor's dynamics. We discuss also how to improve the robustness of reconstruction. Some examples are presented to illustrate the measurement signal reconstruction method suggested.

PDNAsite: Identification of DNA-binding Site from Protein Sequence by Incorporating Spatial and Sequence Context

PubMed Central

Zhou, Jiyun; Xu, Ruifeng; He, Yulan; Lu, Qin; Wang, Hongpeng; Kong, Bing

2016-01-01

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community. PMID:27282833

Automated Segmentation of High-Resolution Photospheric Images of Active Regions

NASA Astrophysics Data System (ADS)

Yang, Meng; Tian, Yu; Rao, Changhui

2018-02-01

Due to the development of ground-based, large-aperture solar telescopes with adaptive optics (AO) resulting in increasing resolving ability, more accurate sunspot identifications and characterizations are required. In this article, we have developed a set of automated segmentation methods for high-resolution solar photospheric images. Firstly, a local-intensity-clustering level-set method is applied to roughly separate solar granulation and sunspots. Then reinitialization-free level-set evolution is adopted to adjust the boundaries of the photospheric patch; an adaptive intensity threshold is used to discriminate between umbra and penumbra; light bridges are selected according to their regional properties from candidates produced by morphological operations. The proposed method is applied to the solar high-resolution TiO 705.7-nm images taken by the 151-element AO system and Ground-Layer Adaptive Optics prototype system at the 1-m New Vacuum Solar Telescope of the Yunnan Observatory. Experimental results show that the method achieves satisfactory robustness and efficiency with low computational cost on high-resolution images. The method could also be applied to full-disk images, and the calculated sunspot areas correlate well with the data given by the National Oceanic and Atmospheric Administration (NOAA).

Real-time PCR detection of Didemnum perlucidum (Monniot, 1983) and Didemnum vexillum (Kott, 2002) in an applied routine marine biosecurity context.

PubMed

Simpson, Tiffany J S; Dias, P Joana; Snow, Michael; Muñoz, Julieta; Berry, Tina

2017-05-01

Prevention and early detection are well recognized as the best strategies for minimizing the risks posed by nonindigenous species (NIS) that have the potential to become marine pests. Central to this is the ability to rapidly and accurately identify the presence of NIS, often from complex environmental samples like biofouling and ballast water. Molecular tools have been increasingly applied to assist with the identification of NIS and can prove particularly useful for taxonomically difficult groups like ascidians. In this study, we have developed real-time PCR assays suited to the specific identification of the ascidians Didemnum perlucidum and Didemnum vexillum. Despite being recognized as important global pests, this is the first time specific molecular detection methods have been developed that can support the early identification and detection of these species from a broad range of environmental sample types. These fast, robust and high-throughput assays represent powerful tools for routine marine biosecurity surveillance, as detection and confirmation of the early presence of species could assist in the timely establishment of emergency responses and control strategies. This study applied the developed assays to confirm the ability to detect Didemnid eDNA in water samples. While previous work has focused on detection of marine larvae from water samples, the development of real-time PCR assays specifically aimed at detecting eDNA of sessile invertebrate species in the marine environment represents a world first and a significant step forwards in applied marine biosecurity surveillance. Demonstrated success in the detection of D. perlucidum eDNA from water samples at sites where it could not be visually identified suggests value in incorporating such assays into biosecurity survey designs targeting Didemnid species. © 2016 John Wiley & Sons Ltd.

Applications of aerospace technology to petroleum exploration. Volume 1: Efforts and results

NASA Technical Reports Server (NTRS)

Jaffe, L. D.

1976-01-01

The feasibility of applying aerospace techniques to help solve significant problems in petroleum exploration is studied. Through contacts with petroleum industry and petroleum service industry, important petroleum exploration problems were identified. For each problem, areas of aerospace technology that might aid in its solution were also identified where possible. Topics selected for investigation include: seismic reflection systems; down-hole acoustic techniques; identification of geological analogies; drilling methods; remote geological sensing; and sea floor imaging and mapping. Specific areas of aerospace technology are applied to 21 concepts formulated from the topics of concern.

Event identification by acoustic signature recognition

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

Dress, W.B.; Kercel, S.W.

1995-07-01

Many events of interest to the security commnnity produce acoustic emissions that are, in principle, identifiable as to cause. Some obvious examples are gunshots, breaking glass, takeoffs and landings of small aircraft, vehicular engine noises, footsteps (high frequencies when on gravel, very low frequencies. when on soil), and voices (whispers to shouts). We are investigating wavelet-based methods to extract unique features of such events for classification and identification. We also discuss methods of classification and pattern recognition specifically tailored for acoustic signatures obtained by wavelet analysis. The paper is divided into three parts: completed work, work in progress, and futuremore » applications. The completed phase has led to the successful recognition of aircraft types on landing and takeoff. Both small aircraft (twin-engine turboprop) and large (commercial airliners) were included in the study. The project considered the design of a small, field-deployable, inexpensive device. The techniques developed during the aircraft identification phase were then adapted to a multispectral electromagnetic interference monitoring device now deployed in a nuclear power plant. This is a general-purpose wavelet analysis engine, spanning 14 octaves, and can be adapted for other specific tasks. Work in progress is focused on applying the methods previously developed to speaker identification. Some of the problems to be overcome include recognition of sounds as voice patterns and as distinct from possible background noises (e.g., music), as well as identification of the speaker from a short-duration voice sample. A generalization of the completed work and the work in progress is a device capable of classifying any number of acoustic events-particularly quasi-stationary events such as engine noises and voices and singular events such as gunshots and breaking glass. We will show examples of both kinds of events and discuss their recognition likelihood.« less

Identification of Forensically Important Calliphoridae and Sarcophagidae Species Collected in Korea Using SNaPshot Multiplex System Targeting the Cytochrome c Oxidase Subunit I Gene

PubMed Central

Park, Ji Hye

2018-01-01

Estimation of postmortem interval (PMI) is paramount in modern forensic investigation. After the disappearance of the early postmortem phenomena conventionally used to estimate PMI, entomologic evidence provides important indicators for PMI estimation. The age of the oldest fly larvae or pupae can be estimated to pinpoint the time of oviposition, which is considered the minimum PMI (PMImin). The development rate of insects is usually temperature dependent and species specific. Therefore, species identification is mandatory for PMImin estimation using entomological evidence. The classical morphological identification method cannot be applied when specimens are damaged or have not yet matured. To overcome this limitation, some investigators employ molecular identification using mitochondrial cytochrome c oxidase subunit I (COI) nucleotide sequences. The molecular identification method commonly uses Sanger's nucleotide sequencing and molecular phylogeny, which are complex and time consuming and constitute another obstacle for forensic investigators. In this study, instead of using conventional Sanger's nucleotide sequencing, single-nucleotide polymorphisms (SNPs) in the COI gene region, which are unique between fly species, were selected and targeted for single-base extension (SBE) technology. These SNPs were genotyped using a SNaPshot® kit. Eleven Calliphoridae and seven Sarcophagidae species were covered. To validate this genotyping, fly DNA samples (103 adults, 84 larvae, and 4 pupae) previously confirmed by DNA barcoding were used. This method worked quickly with minimal DNA, providing a potential alternative to conventional DNA barcoding. Consisting of only a few simple electropherogram peaks, the results were more straightforward compared with those of the conventional DNA barcoding produced by Sanger's nucleotide sequencing. PMID:29682531

The Old Brain, the New Mirror: Matching Teaching and Learning Styles in Foreign Language Class (Based on Neuro-Linguistic Programming).

ERIC Educational Resources Information Center

Knowles, John K.

The process of matching teaching materials and methods to the student's learning style and ability level in foreign language classes is explored. The Neuro-Linguistic Programming (NLP) model offers a diagnostic process for the identification of style. This process can be applied to the language learning setting as a way of presenting material to…

Plan View Pattern Control for Steel Plates through Constrained Locally Weighted Regression

NASA Astrophysics Data System (ADS)

Shigemori, Hiroyasu; Nambu, Koji; Nagao, Ryo; Araki, Tadashi; Mizushima, Narihito; Kano, Manabu; Hasebe, Shinji

A technique for performing parameter identification in a locally weighted regression model using foresight information on the physical properties of the object of interest as constraints was proposed. This method was applied to plan view pattern control of steel plates, and a reduction of shape nonconformity (crop) at the plate head end was confirmed by computer simulation based on real operation data.

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

DTIC Science & Technology

2006-08-01

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

Separation and Identification of a Mixture of Group 6 Transition-Metal Carbonyl Compounds Using GC-MS in the General Chemistry Curriculum

ERIC Educational Resources Information Center

Fong, Lawrence K.

2004-01-01

Students in the general chemistry course are advised to scrutinize data obtained by gas chromatograph (GC) for segregation, and mass spectroscopy (MS) for recognizing combination of group 6 transition-metal carbonyl compounds. The GC-MS method arouses students' interest, as it can be applied to real-world situations, such as the routine…

Identification of Large Space Structures on Orbit

DTIC Science & Technology

1986-09-01

requires only the eigenvector corresponding to the eigenvector 93 .:. ,S --- k’.’ L derivative being calculated. However, a set of linear algebraic ...Journal of Guidance, Control and Dynamics. 204. Noble, B. and J. W. Daniel, Applied Linear Algebra , Prentice-Hall, Inc., 1977. 205. Nurre, G. S., R. S...4.2.1. Linear Relationships . . . . . . . . . . 114 4.2.2. Nonlinear Relationships . . . . . . . . . 120 4.3. Series Expansion Methods

Identifying clouds over the Pierre Auger Observatory using infrared satellite data

NASA Astrophysics Data System (ADS)

Abreu, P.; Aglietta, M.; Ahlers, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allekotte, I.; Allen, J.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Alves Batista, R.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antičić, T.; Aramo, C.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Badescu, A. M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Baughman, B.; Bäuml, J.; Baus, C.; Beatty, J. J.; Becker, K. H.; Bellétoile, A.; Bellido, J. A.; BenZvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brancus, I.; Brogueira, P.; Brown, W. C.; Buchholz, P.; Bueno, A.; Buroker, L.; Burton, R. E.; Buscemi, M.; Caballero-Mora, K. S.; Caccianiga, B.; Caccianiga, L.; Caramete, L.; Caruso, R.; Castellina, A.; Cataldi, G.; Cazon, L.; Cester, R.; Cheng, S. H.; Chiavassa, A.; Chinellato, J. A.; Chirinos, J.; Chudoba, J.; Cilmo, M.; Clay, R. W.; Cocciolo, G.; Colalillo, R.; Collica, L.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coutu, S.; Covault, C. E.; Criss, A.; Cronin, J.; Curutiu, A.; Dallier, R.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; De Domenico, M.; de Jong, S. J.; De La Vega, G.; de Mello, W. J. M.; de Mello Neto, J. R. T.; De Mitri, I.; de Souza, V.; de Vries, K. D.; del Peral, L.; Deligny, O.; Dembinski, H.; Dhital, N.; Di Giulio, C.; Diaz, J. C.; Díaz Castro, M. L.; Diep, P. N.; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Facal San Luis, P.; Falcke, H.; Fang, K.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fick, B.; Figueira, J. M.; Filevich, A.; Filipčič, A.; Fliescher, S.; Fox, B. D.; Fracchiolla, C. E.; Fraenkel, E. D.; Fratu, O.; Fröhlich, U.; Fuchs, B.; Gaior, R.; Gamarra, R. F.; Gambetta, S.; García, B.; Garcia Roca, S. T.; Garcia-Gamez, D.; Garcia-Pinto, D.; Garilli, G.; Gascon Bravo, A.; Gemmeke, H.; Ghia, P. L.; Giller, M.; Gitto, J.; Glaser, C.; Glass, H.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gómez Vitale, P. F.; Gonçalves, P.; Gonzalez, J. G.; Gookin, B.; Gorgi, A.; Gorham, P.; Gouffon, P.; Grebe, S.; Griffith, N.; Grillo, A. F.; Grubb, T. D.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Hollon, N.; Holmes, V. C.; Homola, P.; Hörandel, J. R.; Horvath, P.; Hrabovský, M.; Huber, D.; Huege, T.; Insolia, A.; Jansen, S.; Jarne, C.; Jiraskova, S.; Josebachuili, M.; Kadija, K.; Kampert, K. H.; Karhan, P.; Kasper, P.; Katkov, I.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Krause, R.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; LaHurd, D.; Latronico, L.; Lauer, R.; Lauscher, M.; Lautridou, P.; Le Coz, S.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lu, L.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Malacari, M.; Maldera, S.; Maller, J.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, J.; Marin, V.; Mariş, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martinez, H.; Martínez Bravo, O.; Martraire, D.; Masías Meza, J. J.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurel, D.; Maurizio, D.; Mayotte, E.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Messina, S.; Meyhandan, R.; Mićanović, S.; Micheletti, M. I.; Middendorf, L.; Minaya, I. A.; Miramonti, L.; Mitrica, B.; Molina-Bueno, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, J. C.; Mostafá, M.; Moura, C. A.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, J.; Nhung, P. T.; Niechciol, M.; Niemietz, L.; Nierstenhoefer, N.; Niggemann, T.; Nitz, D.; Nosek, D.; Nožka, L.; Oehlschläger, J.; Olinto, A.; Oliveira, M.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parra, A.; Pastor, S.; Paul, T.; Pech, M.; Peķala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrolini, A.; Petrov, Y.; Pfendner, C.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Ponce, V. H.; Pontz, M.; Porcelli, A.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rizi, V.; Roberts, J.; Rodrigues de Carvalho, W.; Rodriguez Cabo, I.; Rodriguez Fernandez, G.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-d'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Rühle, C.; Saffi, S. J.; Saftoiu, A.; Salamida, F.; Salazar, H.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schröder, F. G.; Schulz, J.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Sima, O.; Śmiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Srivastava, Y. N.; Stanič, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Straub, M.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tapia, A.; Tartare, M.; Taşcău, O.; Tcaciuc, R.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tkaczyk, W.; Todero Peixoto, C. J.; Toma, G.; Tomankova, L.; Tomé, B.; Tonachini, A.; Torralba Elipe, G.; Torres Machado, D.; Travnicek, P.; Tridapalli, D. B.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van Aar, G.; van den Berg, A. M.; van Velzen, S.; van Vliet, A.; Varela, E.; Vargas Cárdenas, B.; Varner, G.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Werner, F.; Westerhoff, S.; Whelan, B. J.; Widom, A.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Wundheiler, B.; Yamamoto, T.; Yapici, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano Garcia, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Zhou, J.; Zhu, Y.; Zimbres Silva, M.; Ziolkowski, M.

2013-12-01

We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ˜2.4 km by ˜5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

Identifying clouds over the Pierre Auger Observatory using infrared satellite data

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

Abreu, Pedro; et al.,

2013-12-01

We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km^2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ~2.4 km by ~5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

Method to integrate clinical guidelines into the electronic health record (EHR) by applying the archetypes approach.

PubMed

Garcia, Diego; Moro, Claudia Maria Cabral; Cicogna, Paulo Eduardo; Carvalho, Deborah Ribeiro

2013-01-01

Clinical guidelines are documents that assist healthcare professionals, facilitating and standardizing diagnosis, management, and treatment in specific areas. Computerized guidelines as decision support systems (DSS) attempt to increase the performance of tasks and facilitate the use of guidelines. Most DSS are not integrated into the electronic health record (EHR), ordering some degree of rework especially related to data collection. This study's objective was to present a method for integrating clinical guidelines into the EHR. The study developed first a way to identify data and rules contained in the guidelines, and then incorporate rules into an archetype-based EHR. The proposed method tested was anemia treatment in the Chronic Kidney Disease Guideline. The phases of the method are: data and rules identification; archetypes elaboration; rules definition and inclusion in inference engine; and DSS-EHR integration and validation. The main feature of the proposed method is that it is generic and can be applied toany type of guideline.

Raman spectroscopic differentiation of beef and horse meat using a 671 nm microsystem diode laser

NASA Astrophysics Data System (ADS)

Ebrahim, Halah Al; Sowoidnich, Kay; Kronfeldt, Heinz-Detlef

2013-11-01

A non-invasive Raman spectroscopic approach for meat species identification and quality detection was successfully demonstrated for the two closely related species beef and horse. Fresh beef and horse muscles were cut and ice-stored at 5 °C, and time-dependent Raman measurements were performed daily up to 12 days postmortem. Applying a 671 nm microsystem diode laser and a laser power of 50 mW, spectra were recorded with integration times of 1-4 s. A pronounced offset of the Raman spectra was observed between horse and beef, with high fluorescence background for horse compared to beef for all days of storage. Principal components analysis was applied for data evaluation revealing a clear distinction between beef and horse meat which can be attributed to differences in the myoglobin content of both species. Furthermore, separations according to aging and spoilage for the two species could be identified simultaneously. Therefore, Raman spectroscopy might be an efficient test method for meat species identification in combination with spoilage detection.

Facial identification in very low-resolution images simulating prosthetic vision.

PubMed

Chang, M H; Kim, H S; Shin, J H; Park, K S

2012-08-01

Familiar facial identification is important to blind or visually impaired patients and can be achieved using a retinal prosthesis. Nevertheless, there are limitations in delivering the facial images with a resolution sufficient to distinguish facial features, such as eyes and nose, through multichannel electrode arrays used in current visual prostheses. This study verifies the feasibility of familiar facial identification under low-resolution prosthetic vision and proposes an edge-enhancement method to deliver more visual information that is of higher quality. We first generated a contrast-enhanced image and an edge image by applying the Sobel edge detector and blocked each of them by averaging. Then, we subtracted the blocked edge image from the blocked contrast-enhanced image and produced a pixelized image imitating an array of phosphenes. Before subtraction, every gray value of the edge images was weighted as 50% (mode 2), 75% (mode 3) and 100% (mode 4). In mode 1, the facial image was blocked and pixelized with no further processing. The most successful identification was achieved with mode 3 at every resolution in terms of identification index, which covers both accuracy and correct response time. We also found that the subjects recognized a distinctive face especially more accurately and faster than the other given facial images even under low-resolution prosthetic vision. Every subject could identify familiar faces even in very low-resolution images. And the proposed edge-enhancement method seemed to contribute to intermediate-stage visual prostheses.

Parameter identification for nonlinear aerodynamic systems

NASA Technical Reports Server (NTRS)

Pearson, Allan E.

1990-01-01

Parameter identification for nonlinear aerodynamic systems is examined. It is presumed that the underlying model can be arranged into an input/output (I/O) differential operator equation of a generic form. The algorithm estimation is especially efficient since the equation error can be integrated exactly given any I/O pair to obtain an algebraic function of the parameters. The algorithm for parameter identification was extended to the order determination problem for linear differential system. The degeneracy in a least squares estimate caused by feedback was addressed. A method of frequency analysis for determining the transfer function G(j omega) from transient I/O data was formulated using complex valued Fourier based modulating functions in contrast with the trigonometric modulating functions for the parameter estimation problem. A simulation result of applying the algorithm is given under noise-free conditions for a system with a low pass transfer function.

DNA based identification of medicinal materials in Chinese patent medicines

NASA Astrophysics Data System (ADS)

Chen, Rong; Dong, Juan; Cui, Xin; Wang, Wei; Yasmeen, Afshan; Deng, Yun; Zeng, Xiaomao; Tang, Zhuo

2012-12-01

Chinese patent medicines (CPM) are highly processed and easy to use Traditional Chinese Medicine (TCM). The market for CPM in China alone is tens of billions US dollars annually and some of the CPM are also used as dietary supplements for health augmentation in the western countries. But concerns continue to be raised about the legality, safety and efficacy of many popular CPM. Here we report a pioneer work of applying molecular biotechnology to the identification of CPM, particularly well refined oral liquids and injections. What's more, this PCR based method can also be developed to an easy to use and cost-effective visual chip by taking advantage of G-quadruplex based Hybridization Chain Reaction. This study demonstrates that DNA identification of specific Medicinal materials is an efficient and cost-effective way to audit highly processed CPM and will assist in monitoring their quality and legality.

Bacterial Volatile Discovery using Solid Phase Microextraction and Comprehensive Two-Dimensional Gas Chromatography–Time-of-Flight Mass Spectrometry

PubMed Central

Bean, Heather D.; Dimandja, Jean-Marie D.; Hill, Jane E.

2014-01-01

Bacteria produce unique volatile mixtures that could be used to identify infectious agents to the species, and possibly the strain level. However, due to the immense variety of human pathogens, and the close relatedness of some of these bacteria, the robust identification of the bacterium based on its volatile metabolome is likely to require a large number of volatile compounds for each species. We applied comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (GC×GC-TOFMS) to the identification of the headspace volatiles of P. aeruginosa PA14 grown for 24 h in lysogeny broth. This is the first reported use of GC×GC-TOFMS for the characterization of bacterial headspace volatiles. The analytical purity that is afforded by this chromatographic method facilitated the identification of 28 new P. aeruginosa-derived volatiles, nearly doubling the list of volatiles for this species. PMID:22727751

Identification and Discrimination of Brands of Fuels by Gas Chromatography and Neural Networks Algorithm in Forensic Research

PubMed Central

Ugena, L.; Moncayo, S.; Manzoor, S.; Rosales, D.

2016-01-01

The detection of adulteration of fuels and its use in criminal scenes like arson has a high interest in forensic investigations. In this work, a method based on gas chromatography (GC) and neural networks (NN) has been developed and applied to the identification and discrimination of brands of fuels such as gasoline and diesel without the necessity to determine the composition of the samples. The study included five main brands of fuels from Spain, collected from fifteen different local petrol stations. The methodology allowed the identification of the gasoline and diesel brands with a high accuracy close to 100%, without any false positives or false negatives. A success rate of three blind samples was obtained as 73.3%, 80%, and 100%, respectively. The results obtained demonstrate the potential of this methodology to help in resolving criminal situations. PMID:27375919

Application of amplified ribosomal DNA restriction analysis in identification of Acinetobacter baumannii from a tertiary teaching hospital, Malaysia.

PubMed

Kong, B H; Hanifah, Y A; Yusof, M Y; Thong, K L

2011-12-01

Acinetobacter baumannii, genomic species 3 and 13TU are being increasingly reported as the most important Acinetobacter species that cause infections in hospitalized patients. These Acinetobacter species are grouped in the Acinetobacter calcoaceticus- Acinetobacter baumannii (Acb) complex. Differentiation of the species in the Acb-complex is limited by phenotypic methods. Therefore, in this study, amplified ribosomal DNA restriction analysis (ARDRA) was applied to confirm the identity A. baumannii strains as well as to differentiate between the subspecies. One hundred and eighty-five strains from Intensive Care Unit, Universiti Malaya Medical Center (UMMC) were successfully identified as A. baumannii by ARDRA. Acinetobacter genomic species 13TU and 15TU were identified in 3 and 1 strains, respectively. ARDRA provides an accurate, rapid and definitive approach towards the identification of the species level in the genus Acinetobacter. This paper reports the first application ARDRA in genospecies identification of Acinetobacter in Malaysia.

Expert system for identification of simultaneous and sequential reactor fuel failures with gas tagging

DOEpatents

Gross, Kenny C.

1994-01-01

Failure of a fuel element in a nuclear reactor core is determined by a gas tagging failure detection system and method. Failures are catalogued and characterized after the event so that samples of the reactor's cover gas are taken at regular intervals and analyzed by mass spectroscopy. Employing a first set of systematic heuristic rules which are applied in a transformed node space allows the number of node combinations which must be processed within a barycentric algorithm to be substantially reduced. A second set of heuristic rules treats the tag nodes of the most recent one or two leakers as "background" gases, further reducing the number of trial node combinations. Lastly, a "fuzzy" set theory formalism minimizes experimental uncertainties in the identification of the most likely volumes of tag gases. This approach allows for the identification of virtually any number of sequential leaks and up to five simultaneous gas leaks from fuel elements.

Talent identification and promotion programmes of Olympic athletes.

PubMed

Vaeyens, Roel; Güllich, Arne; Warr, Chelsea R; Philippaerts, Renaat

2009-11-01

The start of a new Olympic cycle offers a fresh chance for individuals and nations to excel at the highest level in sport. Most countries attempt to develop systematic structures to identify gifted athletes and to promote their development in a certain sport. However, forecasting years in advance the next generation of sporting experts and stimulating their development remains problematic. In this article, we discuss issues related to the identification and preparation of Olympic athletes. We provide field-based data suggesting that an earlier onset and a higher volume of discipline-specific training and competition, and an extended involvement in institutional talent promotion programmes, during adolescence need not necessarily be associated with greater success in senior international elite sport. Next, we consider some of the promising methods that have been (recently) presented in the literature and applied in the field. Finally, implications for talent identification and promotion and directions for future research are highlighted.

System identification of dynamic closed-loop control of total peripheral resistance by arterial and cardiopulmonary baroreceptors

NASA Astrophysics Data System (ADS)

Nikolai Aljuri, A.; Bursac, Nenad; Marini, Robert; Cohen, Richard J.

2001-08-01

Prolonged exposure to microgravity in space flight missions (days) impairs the mechanisms responsible for defense of arterial blood pressure (ABP) and cardiac output (CO) against orthostatic stress in the post-flight period. The mechanisms responsible for the observed orthostatic intolerance are not yet completely understood. Additionally, effective counter measures to attenuate this pathophysiological response are not available. The aim of this study was to investigate the ability of our proposed system identification method to predict closed-loop dynamic changes in TPR induced by changes in mean arterial pressure (MAP) and right atrial pressure (RAP). For this purpose we designed and employed a novel experimental animal model for the examination of arterial and cardiopulmonary baroreceptors in the dynamic closed-loop control of total peripheral resistance (TPR), and applied system identification to the analysis of beat-to-beat fluctuations in the measured signals.

Identification of Nonlinear Micron-Level Mechanics for a Precision Deployable Joint

NASA Technical Reports Server (NTRS)

Bullock, S. J.; Peterson, L. D.

1994-01-01

The experimental identification of micron-level nonlinear joint mechanics and dynamics for a pin-clevis joint used in a precision, adaptive, deployable space structure are investigated. The force-state mapping method is used to identify the behavior of the joint under a preload. The results of applying a single tension-compression cycle to the joint under a tensile preload are presented. The observed micron-level behavior is highly nonlinear and involves all six rigid body motion degrees-of-freedom of the joint. it is also suggests that at micron levels of motion modelling of the joint mechanics and dynamics must include the interactions between all internal components, such as the pin, bushings, and the joint node.

Intergration of system identification and robust controller designs for flexible structures in space

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Lew, Jiann-Shiun

1990-01-01

An approach is developed using experimental data to identify a reduced-order model and its model error for a robust controller design. There are three steps involved in the approach. First, an approximately balanced model is identified using the Eigensystem Realization Algorithm, which is an identification algorithm. Second, the model error is calculated and described in frequency domain in terms of the H(infinity) norm. Third, a pole placement technique in combination with a H(infinity) control method is applied to design a controller for the considered system. A set experimental data from an existing setup, namely the Mini-Mast system, is used to illustrate and verify the approach.

Bayesian Modeling for Identification and Estimation of the Learning Effects of Pointing Tasks

NASA Astrophysics Data System (ADS)

Kyo, Koki

Recently, in the field of human-computer interaction, a model containing the systematic factor and human factor has been proposed to evaluate the performance of the input devices of a computer. This is called the SH-model. In this paper, in order to extend the range of application of the SH-model, we propose some new models based on the Box-Cox transformation and apply a Bayesian modeling method for identification and estimation of the learning effects of pointing tasks. We consider the parameters describing the learning effect as random variables and introduce smoothness priors for them. Illustrative results show that the newly-proposed models work well.