A relational metric, its application to domain analysis, and an example analysis and model of a remote sensing domain

NASA Technical Reports Server (NTRS)

Mcgreevy, Michael W.

1995-01-01

An objective and quantitative method has been developed for deriving models of complex and specialized spheres of activity (domains) from domain-generated verbal data. The method was developed for analysis of interview transcripts, incident reports, and other text documents whose original source is people who are knowledgeable about, and participate in, the domain in question. To test the method, it is applied here to a report describing a remote sensing project within the scope of the Earth Observing System (EOS). The method has the potential to improve the designs of domain-related computer systems and software by quickly providing developers with explicit and objective models of the domain in a form which is useful for design. Results of the analysis include a network model of the domain, and an object-oriented relational analysis report which describes the nodes and relationships in the network model. Other products include a database of relationships in the domain, and an interactive concordance. The analysis method utilizes a newly developed relational metric, a proximity-weighted frequency of co-occurrence. The metric is applied to relations between the most frequently occurring terms (words or multiword entities) in the domain text, and the terms found within the contexts of these terms. Contextual scope is selectable. Because of the discriminating power of the metric, data reduction from the association matrix to the network is simple. In addition to their value for design. the models produced by the method are also useful for understanding the domains themselves. They can, for example, be interpreted as models of presence in the domain.

21 CFR 133.5 - Methods of analysis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 2 2011-04-01 2011-04-01 false Methods of analysis. 133.5 Section 133.5 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) FOOD FOR HUMAN CONSUMPTION CHEESES AND RELATED CHEESE PRODUCTS General Provisions § 133.5 Methods of analysis. Moisture...

21 CFR 133.5 - Methods of analysis.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 2 2012-04-01 2012-04-01 false Methods of analysis. 133.5 Section 133.5 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) FOOD FOR HUMAN CONSUMPTION CHEESES AND RELATED CHEESE PRODUCTS General Provisions § 133.5 Methods of analysis. Moisture...

21 CFR 133.5 - Methods of analysis.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 2 2013-04-01 2013-04-01 false Methods of analysis. 133.5 Section 133.5 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) FOOD FOR HUMAN CONSUMPTION CHEESES AND RELATED CHEESE PRODUCTS General Provisions § 133.5 Methods of analysis. Moisture...

Simulation Research on Vehicle Active Suspension Controller Based on G1 Method

NASA Astrophysics Data System (ADS)

Li, Gen; Li, Hang; Zhang, Shuaiyang; Luo, Qiuhui

2017-09-01

Based on the order relation analysis method (G1 method), the optimal linear controller of vehicle active suspension is designed. The system of the main and passive suspension of the single wheel vehicle is modeled and the system input signal model is determined. Secondly, the system motion state space equation is established by the kinetic knowledge and the optimal linear controller design is completed with the optimal control theory. The weighting coefficient of the performance index coefficients of the main passive suspension is determined by the relational analysis method. Finally, the model is simulated in Simulink. The simulation results show that: the optimal weight value is determined by using the sequence relation analysis method under the condition of given road conditions, and the vehicle acceleration, suspension stroke and tire motion displacement are optimized to improve the comprehensive performance of the vehicle, and the active control is controlled within the requirements.

Optimisation and validation of a rapid and efficient microemulsion liquid chromatographic (MELC) method for the determination of paracetamol (acetaminophen) content in a suppository formulation.

PubMed

McEvoy, Eamon; Donegan, Sheila; Power, Joe; Altria, Kevin

2007-05-09

A rapid and efficient oil-in-water microemulsion liquid chromatographic method has been optimised and validated for the analysis of paracetamol in a suppository formulation. Excellent linearity, accuracy, precision and assay results were obtained. Lengthy sample pre-treatment/extraction procedures were eliminated due to the solubilising power of the microemulsion and rapid analysis times were achieved. The method was optimised to achieve rapid analysis time and relatively high peak efficiencies. A standard microemulsion composition of 33 g SDS, 66 g butan-1-ol, 8 g n-octane in 1l of 0.05% TFA modified with acetonitrile has been shown to be suitable for the rapid analysis of paracetamol in highly hydrophobic preparations under isocratic conditions. Validated assay results and overall analysis time of the optimised method was compared to British Pharmacopoeia reference methods. Sample preparation and analysis times for the MELC analysis of paracetamol in a suppository were extremely rapid compared to the reference method and similar assay results were achieved. A gradient MELC method using the same microemulsion has been optimised for the resolution of paracetamol and five of its related substances in approximately 7 min.

40 CFR 60.435 - Test methods and procedures.

Code of Federal Regulations, 2013 CFR

2013-07-01

... of any affected facility using solvent-borne ink systems shall determine the VOC content of the raw inks and related coatings used at the affected facility by: (1) Analysis using Method 24A of routine weekly samples of raw ink and related coatings in each respective storage tank; or (2) Analysis using...

40 CFR 60.435 - Test methods and procedures.

Code of Federal Regulations, 2012 CFR

2012-07-01

... of any affected facility using solvent-borne ink systems shall determine the VOC content of the raw inks and related coatings used at the affected facility by: (1) Analysis using Method 24A of routine weekly samples of raw ink and related coatings in each respective storage tank; or (2) Analysis using...

40 CFR 60.435 - Test methods and procedures.

Code of Federal Regulations, 2014 CFR

2014-07-01

... of any affected facility using solvent-borne ink systems shall determine the VOC content of the raw inks and related coatings used at the affected facility by: (1) Analysis using Method 24A of routine weekly samples of raw ink and related coatings in each respective storage tank; or (2) Analysis using...

Comparison of detrending methods for fluctuation analysis in hydrology

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Zhou, Yu; Singh, Vijay P.; Chen, Yongqin David

2011-03-01

SummaryTrends within a hydrologic time series can significantly influence the scaling results of fluctuation analysis, such as rescaled range (RS) analysis and (multifractal) detrended fluctuation analysis (MF-DFA). Therefore, removal of trends is important in the study of scaling properties of the time series. In this study, three detrending methods, including adaptive detrending algorithm (ADA), Fourier-based method, and average removing technique, were evaluated by analyzing numerically generated series and observed streamflow series with obvious relative regular periodic trend. Results indicated that: (1) the Fourier-based detrending method and ADA were similar in detrending practices, and given proper parameters, these two methods can produce similarly satisfactory results; (2) detrended series by Fourier-based detrending method and ADA lose the fluctuation information at larger time scales, and the location of crossover points is heavily impacted by the chosen parameters of these two methods; and (3) the average removing method has an advantage over the other two methods, i.e., the fluctuation information at larger time scales is kept well-an indication of relatively reliable performance in detrending. In addition, the average removing method performed reasonably well in detrending a time series with regular periods or trends. In this sense, the average removing method should be preferred in the study of scaling properties of the hydrometeorolgical series with relative regular periodic trend using MF-DFA.

Static analysis of class invariants in Java programs

NASA Astrophysics Data System (ADS)

Bonilla-Quintero, Lidia Dionisia

2011-12-01

This paper presents a technique for the automatic inference of class invariants from Java bytecode. Class invariants are very important for both compiler optimization and as an aid to programmers in their efforts to reduce the number of software defects. We present the original DC-invariant analysis from Adam Webber, talk about its shortcomings and suggest several different ways to improve it. To apply the DC-invariant analysis to identify DC-invariant assertions, all that one needs is a monotonic method analysis function and a suitable assertion domain. The DC-invariant algorithm is very general; however, the method analysis can be highly tuned to the problem in hand. For example, one could choose shape analysis as the method analysis function and use the DC-invariant analysis to simply extend it to an analysis that would yield class-wide invariants describing the shapes of linked data structures. We have a prototype implementation: a system we refer to as "the analyzer" that infers DC-invariant unary and binary relations and provides them to the user in a human readable format. The analyzer uses those relations to identify unnecessary array bounds checks in Java programs and perform null-reference analysis. It uses Adam Webber's relational constraint technique for the class-invariant binary relations. Early results with the analyzer were very imprecise in the presence of "dirty-called" methods. A dirty-called method is one that is called, either directly or transitively, from any constructor of the class, or from any method of the class at a point at which a disciplined field has been altered. This result was unexpected and forced an extensive search for improved techniques. An important contribution of this paper is the suggestion of several ways to improve the results by changing the way dirty-called methods are handled. The new techniques expand the set of class invariants that can be inferred over Webber's original results. The technique that produces better results uses in-line analysis. Final results are promising: we can infer sound class invariants for full-scale, not just toy applications.

DNA-based methods of geochemical prospecting

DOEpatents

Ashby, Matthew [Mill Valley, CA

2011-12-06

The present invention relates to methods for performing surveys of the genetic diversity of a population. The invention also relates to methods for performing genetic analyses of a population. The invention further relates to methods for the creation of databases comprising the survey information and the databases created by these methods. The invention also relates to methods for analyzing the information to correlate the presence of nucleic acid markers with desired parameters in a sample. These methods have application in the fields of geochemical exploration, agriculture, bioremediation, environmental analysis, clinical microbiology, forensic science and medicine.

The Relation between Factor Score Estimates, Image Scores, and Principal Component Scores

ERIC Educational Resources Information Center

Velicer, Wayne F.

1976-01-01

Investigates the relation between factor score estimates, principal component scores, and image scores. The three methods compared are maximum likelihood factor analysis, principal component analysis, and a variant of rescaled image analysis. (RC)

Using the Image Analysis Method for Describing Soil Detachment by a Single Water Drop Impact

PubMed Central

Ryżak, Magdalena; Bieganowski, Andrzej

2012-01-01

The aim of the present work was to develop a method based on image analysis for describing soil detachment caused by the impact of a single water drop. The method consisted of recording tracks made by splashed particles on blotting paper under an optical microscope. The analysis facilitated division of the recorded particle tracks on the paper into drops, “comets” and single particles. Additionally, the following relationships were determined: (i) the distances of splash; (ii) the surface areas of splash tracks into relation to distance; (iii) the surface areas of the solid phase transported over a given distance; and (iv) the ratio of the solid phase to the splash track area in relation to distance. Furthermore, the proposed method allowed estimation of the weight of soil transported by a single water drop splash in relation to the distance of the water drop impact. It was concluded that the method of image analysis of splashed particles facilitated analysing the results at very low water drop energy and generated by single water drops.

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

PubMed

Bigler, Erin D

2015-09-01

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

Optical Coherence Tomography Measurements and Analysis Methods in Optical Coherence Tomography Studies of Diabetic Macular Edema

PubMed Central

Browning, David J.; Glassman, Adam R.; Aiello, Lloyd P.; Bressler, Neil M.; Bressler, Susan; Danis, Ronald P.; Davis, Matthew D.; Ferris, Frederick L.; Huang, Suber S.; Kaiser, Peter K.; Kollman, Craig; Sadda, Srinavas; Scott, Ingrid U.; Qin, Haijing

2009-01-01

Objective To evaluate optical coherence tomography (OCT) measurements and methods of analysis of OCT data in studies of diabetic macular edema (DME). Design Associations of pairs of OCT variables and results of three analysis methods using data from two studies of DME. Participants Two hundred sixty-three subjects from a study of modified Early Treatment of Diabetic Retinopathy Study (mETDRS) versus modified macular grid (MMG) photocoagulation for DME and 96 subjects from a study of diurnal variation of DME. Methods Correlations were calculated for pairs of OCT variables at baseline and for changes in the variables over time. Distribution of OCT measurement changes, predictive factors for OCT measurement changes, and treatment group outcomes were compared when three measures of change in macular thickness were analyzed: absolute change in retinal thickness, relative change in retinal thickness, and relative change in retinal thickening. Main Outcome Measures Concordance of results using different OCT variables and analysis methods. Results Center point thickness correlated highly with central subfield mean thickness (CSMT) at baseline (0.98–0.99). The distributions of changes in CSMT were approximately normally distributed for absolute change in retinal thickness and relative change in retinal thickness, but not for relative change in retinal thickening. The macular thinning in the mETDRS group was significantly greater than in the MMG group when absolute change in retinal thickness was used, but not when relative change in thickness and relative change in thickening were used. Relative change in macular thickening provides unstable data in eyes with mild degrees of baseline thickening, unlike the situation with absolute or relative change in retinal thickness. Conclusions Central subfield mean thickness is the preferred OCT measurement for the central macula because of its higher reproducibility and correlation with other measurements of the central macula. Total macular volume may be preferred when the central macula is less important. Absolute change in retinal thickness is the preferred analysis method in studies involving eyes with mild macular thickening. Relative change in thickening may be preferable when retinal thickening is more severe. PMID:18675696

Structural Analysis of a Consumption-Based Stratification Indicator: Relational Proximity of Household Expenditures

ERIC Educational Resources Information Center

Katz-Gerro, Tally; Talmud, Ilan

2005-01-01

This paper proposes a new analysis of consumption inequality using relational methods, derived from network images of social structure. We combine structural analysis with theoretical concerns in consumer research to propose a relational theory of consumption space, to construct a stratification indicator, and to demonstrate its analytical…

Quality Analysis of Chlorogenic Acid and Hyperoside in Crataegi fructus

PubMed Central

Weon, Jin Bae; Jung, Youn Sik; Ma, Choong Je

2016-01-01

Background: Crataegi fructus is a herbal medicine for strong stomach, sterilization, and alcohol detoxification. Chlorogenic acid and hyperoside are the major compounds in Crataegi fructus. Objective: In this study, we established novel high-performance liquid chromatography (HPLC)-diode array detection analysis method of chlorogenic acid and hyperoside for quality control of Crataegi fructus. Materials and Methods: HPLC analysis was achieved on a reverse-phase C18 column (5 μm, 4.6 mm × 250 mm) using water and acetonitrile as mobile phase with gradient system. The method was validated for linearity, precision, and accuracy. About 31 batches of Crataegi fructus samples collected from Korea and China were analyzed by using HPLC fingerprint of developed HPLC method. Then, the contents of chlorogenic acid and hyperoside were compared for quality evaluation of Crataegi fructus. Results: The results have shown that the average contents (w/w %) of chlorogenic acid and hyperoside in Crataegi fructus collected from Korea were 0.0438% and 0.0416%, respectively, and the average contents (w/w %) of 0.0399% and 0.0325%, respectively. Conclusion: In conclusion, established HPLC analysis method was stable and could provide efficient quality evaluation for monitoring of commercial Crataegi fructus. SUMMARY Quantitative analysis method of chlorogenic acid and hyperoside in Crataegi fructus is developed by high.performance liquid chromatography.(HPLC).diode array detectionEstablished HPLC analysis method is validated with linearity, precision, and accuracyThe developed method was successfully applied for quantitative analysis of Crataegi fructus sample collected from Korea and China. Abbreviations used: HPLC: High-performance liquid chromatography, GC: Gas chromatography, MS: Mass spectrometer, LOD: Limits of detection, LOQ: Limits of quantification, RSD: Relative standard deviation, RRT: Relative retention time, RPA: Relation peak area. PMID:27076744

Power flow as a complement to statistical energy analysis and finite element analysis

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.

1987-01-01

Present methods of analysis of the structural response and the structure-borne transmission of vibrational energy use either finite element (FE) techniques or statistical energy analysis (SEA) methods. The FE methods are a very useful tool at low frequencies where the number of resonances involved in the analysis is rather small. On the other hand SEA methods can predict with acceptable accuracy the response and energy transmission between coupled structures at relatively high frequencies where the structural modal density is high and a statistical approach is the appropriate solution. In the mid-frequency range, a relatively large number of resonances exist which make finite element method too costly. On the other hand SEA methods can only predict an average level form. In this mid-frequency range a possible alternative is to use power flow techniques, where the input and flow of vibrational energy to excited and coupled structural components can be expressed in terms of input and transfer mobilities. This power flow technique can be extended from low to high frequencies and this can be integrated with established FE models at low frequencies and SEA models at high frequencies to form a verification of the method. This method of structural analysis using power flo and mobility methods, and its integration with SEA and FE analysis is applied to the case of two thin beams joined together at right angles.

Low Streamflow Forcasting using Minimum Relative Entropy

NASA Astrophysics Data System (ADS)

Cui, H.; Singh, V. P.

2013-12-01

Minimum relative entropy spectral analysis is derived in this study, and applied to forecast streamflow time series. Proposed method extends the autocorrelation in the manner that the relative entropy of underlying process is minimized so that time series data can be forecasted. Different prior estimation, such as uniform, exponential and Gaussian assumption, is taken to estimate the spectral density depending on the autocorrelation structure. Seasonal and nonseasonal low streamflow series obtained from Colorado River (Texas) under draught condition is successfully forecasted using proposed method. Minimum relative entropy determines spectral of low streamflow series with higher resolution than conventional method. Forecasted streamflow is compared to the prediction using Burg's maximum entropy spectral analysis (MESA) and Configurational entropy. The advantage and disadvantage of each method in forecasting low streamflow is discussed.

Relativity Concept Inventory: Development, Analysis, and Results

ERIC Educational Resources Information Center

Aslanides, J. S.; Savage, C. M.

2013-01-01

We report on a concept inventory for special relativity: the development process, data analysis methods, and results from an introductory relativity class. The Relativity Concept Inventory tests understanding of relativistic concepts. An unusual feature is confidence testing for each question. This can provide additional information; for example,…

Quantitative Analysis of Ca, Mg, and K in the Roots of Angelica pubescens f. biserrata by Laser-Induced Breakdown Spectroscopy Combined with Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Wang, J.; Shi, M.; Zheng, P.; Xue, Sh.; Peng, R.

2018-03-01

Laser-induced breakdown spectroscopy has been applied for the quantitative analysis of Ca, Mg, and K in the roots of Angelica pubescens Maxim. f. biserrata Shan et Yuan used in traditional Chinese medicine. Ca II 317.993 nm, Mg I 517.268 nm, and K I 769.896 nm spectral lines have been chosen to set up calibration models for the analysis using the external standard and artificial neural network methods. The linear correlation coefficients of the predicted concentrations versus the standard concentrations of six samples determined by the artificial neural network method are 0.9896, 0.9945, and 0.9911 for Ca, Mg, and K, respectively, which are better than for the external standard method. The artificial neural network method also gives better performance comparing with the external standard method for the average and maximum relative errors, average relative standard deviations, and most maximum relative standard deviations of the predicted concentrations of Ca, Mg, and K in the six samples. Finally, it is proved that the artificial neural network method gives better performance compared to the external standard method for the quantitative analysis of Ca, Mg, and K in the roots of Angelica pubescens.

Key Spatial Relations-based Focused Crawling (KSRs-FC) for Borderlands Situation Analysis

NASA Astrophysics Data System (ADS)

Hou, D. Y.; Wu, H.; Chen, J.; Li, R.

2013-11-01

Place names play an important role in Borderlands Situation topics, while current focused crawling methods treat them in the same way as other common keywords, which may lead to the omission of many useful web pages. In the paper, place names in web pages and their spatial relations were firstly discussed. Then, a focused crawling method named KSRs-FC was proposed to deal with the collection of situation information about borderlands. In this method, place names and common keywords were represented separately, and some of the spatial relations related to web pages crawling were used in the relevance calculation between the given topic and web pages. Furthermore, an information collection system for borderlands situation analysis was developed based on KSRs-FC. Finally, F-Score method was adopted to quantitatively evaluate this method by comparing with traditional method. Experimental results showed that the F-Score value of the proposed method increased by 11% compared to traditional method with the same sample data. Obviously, KSRs-FC method can effectively reduce the misjudgement of relevant webpages.

Improved methods of vibration analysis of pretwisted, airfoil blades

NASA Technical Reports Server (NTRS)

Subrahmanyam, K. B.; Kaza, K. R. V.

1984-01-01

Vibration analysis of pretwisted blades of asymmetric airfoil cross section is performed by using two mixed variational approaches. Numerical results obtained from these two methods are compared to those obtained from an improved finite difference method and also to those given by the ordinary finite difference method. The relative merits, convergence properties and accuracies of all four methods are studied and discussed. The effects of asymmetry and pretwist on natural frequencies and mode shapes are investigated. The improved finite difference method is shown to be far superior to the conventional finite difference method in several respects. Close lower bound solutions are provided by the improved finite difference method for untwisted blades with a relatively coarse mesh while the mixed methods have not indicated any specific bound.

Error minimization algorithm for comparative quantitative PCR analysis: Q-Anal.

PubMed

OConnor, William; Runquist, Elizabeth A

2008-07-01

Current methods for comparative quantitative polymerase chain reaction (qPCR) analysis, the threshold and extrapolation methods, either make assumptions about PCR efficiency that require an arbitrary threshold selection process or extrapolate to estimate relative levels of messenger RNA (mRNA) transcripts. Here we describe an algorithm, Q-Anal, that blends elements from current methods to by-pass assumptions regarding PCR efficiency and improve the threshold selection process to minimize error in comparative qPCR analysis. This algorithm uses iterative linear regression to identify the exponential phase for both target and reference amplicons and then selects, by minimizing linear regression error, a fluorescence threshold where efficiencies for both amplicons have been defined. From this defined fluorescence threshold, cycle time (Ct) and the error for both amplicons are calculated and used to determine the expression ratio. Ratios in complementary DNA (cDNA) dilution assays from qPCR data were analyzed by the Q-Anal method and compared with the threshold method and an extrapolation method. Dilution ratios determined by the Q-Anal and threshold methods were 86 to 118% of the expected cDNA ratios, but relative errors for the Q-Anal method were 4 to 10% in comparison with 4 to 34% for the threshold method. In contrast, ratios determined by an extrapolation method were 32 to 242% of the expected cDNA ratios, with relative errors of 67 to 193%. Q-Anal will be a valuable and quick method for minimizing error in comparative qPCR analysis.

Comparing Mycobacterium tuberculosis genomes using genome topology networks.

PubMed

Jiang, Jianping; Gu, Jianlei; Zhang, Liang; Zhang, Chenyi; Deng, Xiao; Dou, Tonghai; Zhao, Guoping; Zhou, Yan

2015-02-14

Over the last decade, emerging research methods, such as comparative genomic analysis and phylogenetic study, have yielded new insights into genotypes and phenotypes of closely related bacterial strains. Several findings have revealed that genomic structural variations (SVs), including gene gain/loss, gene duplication and genome rearrangement, can lead to different phenotypes among strains, and an investigation of genes affected by SVs may extend our knowledge of the relationships between SVs and phenotypes in microbes, especially in pathogenic bacteria. In this work, we introduce a 'Genome Topology Network' (GTN) method based on gene homology and gene locations to analyze genomic SVs and perform phylogenetic analysis. Furthermore, the concept of 'unfixed ortholog' has been proposed, whose members are affected by SVs in genome topology among close species. To improve the precision of 'unfixed ortholog' recognition, a strategy to detect annotation differences and complete gene annotation was applied. To assess the GTN method, a set of thirteen complete M. tuberculosis genomes was analyzed as a case study. GTNs with two different gene homology-assigning methods were built, the Clusters of Orthologous Groups (COG) method and the orthoMCL clustering method, and two phylogenetic trees were constructed accordingly, which may provide additional insights into whole genome-based phylogenetic analysis. We obtained 24 unfixable COG groups, of which most members were related to immunogenicity and drug resistance, such as PPE-repeat proteins (COG5651) and transcriptional regulator TetR gene family members (COG1309). The GTN method has been implemented in PERL and released on our website. The tool can be downloaded from http://homepage.fudan.edu.cn/zhouyan/gtn/ , and allows re-annotating the 'lost' genes among closely related genomes, analyzing genes affected by SVs, and performing phylogenetic analysis. With this tool, many immunogenic-related and drug resistance-related genes were found to be affected by SVs in M. tuberculosis genomes. We believe that the GTN method will be suitable for the exploration of genomic SVs in connection with biological features of bacterial strains, and that GTN-based phylogenetic analysis will provide additional insights into whole genome-based phylogenetic analysis.

Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study

PubMed Central

2014-01-01

Background Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. Methods 126 hypothetical trial scenarios were evaluated (126 000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Results Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Conclusions Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power. PMID:24712304

Methods for High-Order Multi-Scale and Stochastic Problems Analysis, Algorithms, and Applications

DTIC Science & Technology

2016-10-17

finite volume schemes, discontinuous Galerkin finite element method, and related methods, for solving computational fluid dynamics (CFD) problems and...approximation for finite element methods. (3) The development of methods of simulation and analysis for the study of large scale stochastic systems of...laws, finite element method, Bernstein-Bezier finite elements , weakly interacting particle systems, accelerated Monte Carlo, stochastic networks 16

5'to 3' nucleic acid synthesis using 3'-photoremovable protecting group

DOEpatents

Pirrung, Michael C.; Shuey, Steven W.; Bradley, Jean-Claude

1999-01-01

The present invention relates, in general, to a method of synthesizing a nucleic acid, and, in particular, to a method of effecting 5' to 3' nucleic acid synthesis. The method can be used to prepare arrays of oligomers bound to a support via their 5' end. The invention also relates to a method of effecting mutation analysis using such arrays. The invention further relates to compounds and compositions suitable for use in such methods.

Eigensystem analysis of classical relaxation techniques with applications to multigrid analysis

NASA Technical Reports Server (NTRS)

Lomax, Harvard; Maksymiuk, Catherine

1987-01-01

Classical relaxation techniques are related to numerical methods for solution of ordinary differential equations. Eigensystems for Point-Jacobi, Gauss-Seidel, and SOR methods are presented. Solution techniques such as eigenvector annihilation, eigensystem mixing, and multigrid methods are examined with regard to the eigenstructure.

Databases for rRNA gene profiling of microbial communities

DOEpatents

Ashby, Matthew

2013-07-02

The present invention relates to methods for performing surveys of the genetic diversity of a population. The invention also relates to methods for performing genetic analyses of a population. The invention further relates to methods for the creation of databases comprising the survey information and the databases created by these methods. The invention also relates to methods for analyzing the information to correlate the presence of nucleic acid markers with desired parameters in a sample. These methods have application in the fields of geochemical exploration, agriculture, bioremediation, environmental analysis, clinical microbiology, forensic science and medicine.

Diffraction as a Method of Critical Policy Analysis

ERIC Educational Resources Information Center

Ulmer, Jasmine B.

2016-01-01

Recent developments in critical policy analysis have occurred alongside the new materialisms in qualitative research. These lines of scholarship have unfolded along two separate, but related, tracks. In particular, the new materialist method of "diffraction" aligns with many elements of critical policy analysis. Both involve critical…

A Relational Metric, Its Application to Domain Analysis, and an Example Analysis and Model of a Remote Sensing Domain

DOT National Transportation Integrated Search

1995-07-01

An objective and quantitative method has been developed for deriving models of complex and specialized spheres of activity (domains) from domain-generated verbal data. The method was developed for analysis of interview transcripts, incident reports, ...

An X-ray diffraction method for semiquantitative mineralogical analysis of Chilean nitrate ore

USGS Publications Warehouse

Jackson, J.C.; Ericksent, G.E.

1997-01-01

Computer analysis of X-ray diffraction (XRD) data provides a simple method for determining the semiquantitative mineralogical composition of naturally occurring mixtures of saline minerals. The method herein described was adapted from a computer program for the study of mixtures of naturally occurring clay minerals. The program evaluates the relative intensities of selected diagnostic peaks for the minerals in a given mixture, and then calculates the relative concentrations of these minerals. The method requires precise calibration of XRD data for the minerals to be studied and selection of diffraction peaks that minimize inter-compound interferences. The calculated relative abundances are sufficiently accurate for direct comparison with bulk chemical analyses of naturally occurring saline mineral assemblages.

An x-ray diffraction method for semiquantitative mineralogical analysis of chilean nitrate ore

USGS Publications Warehouse

John, C.; George, J.; Ericksen, E.

1997-01-01

Computer analysis of X-ray diffraction (XRD) data provides a simple method for determining the semiquantitative mineralogical composition of naturally occurring mixtures of saline minerals. The method herein described was adapted from a computer program for the study of mixtures of naturally occurring clay minerals. The program evaluates the relative intensities of selected diagnostic peaks for the minerals in a given mixture, and then calculates the relative concentrations of these minerals. The method requires precise calibration of XRD data for the minerals to be studied and selection of diffraction peaks that minimize inter-compound interferences. The calculated relative abundances are sufficiently accurate for direct comparison with bulk chemical analyses of naturally occurring saline mineral assemblages.

Use-related risk analysis for medical devices based on improved FMEA.

PubMed

Liu, Long; Shuai, Ma; Wang, Zhu; Li, Ping

2012-01-01

In order to effectively analyze and control use-related risk of medical devices, quantitative methodologies must be applied. Failure Mode and Effects Analysis (FMEA) is a proactive technique for error detection and risk reduction. In this article, an improved FMEA based on Fuzzy Mathematics and Grey Relational Theory is developed to better carry out user-related risk analysis for medical devices. As an example, the analysis process using this improved FMEA method for a certain medical device (C-arm X-ray machine) is described.

Extending methods: using Bourdieu's field analysis to further investigate taste

NASA Astrophysics Data System (ADS)

Schindel Dimick, Alexandra

2015-06-01

In this commentary on Per Anderhag, Per-Olof Wickman and Karim Hamza's article Signs of taste for science, I consider how their study is situated within the concern for the role of science education in the social and cultural production of inequality. Their article provides a finely detailed methodology for analyzing the constitution of taste within science education classrooms. Nevertheless, because the authors' socially situated methodology draws upon Bourdieu's theories, it seems equally important to extend these methods to consider how and why students make particular distinctions within a relational context—a key aspect of Bourdieu's theory of cultural production. By situating the constitution of taste within Bourdieu's field analysis, researchers can explore the ways in which students' tastes and social positionings are established and transformed through time, space, place, and their ability to navigate the field. I describe the process of field analysis in relation to the authors' paper and suggest that combining the authors' methods with a field analysis can provide a strong methodological and analytical framework in which theory and methods combine to create a detailed understanding of students' interest in relation to their context.

Mixing Qualitative and Quantitative Methods: Insights into Design and Analysis Issues

ERIC Educational Resources Information Center

Lieber, Eli

2009-01-01

This article describes and discusses issues related to research design and data analysis in the mixing of qualitative and quantitative methods. It is increasingly desirable to use multiple methods in research, but questions arise as to how best to design and analyze the data generated by mixed methods projects. I offer a conceptualization for such…

Chromatographic fingerprint analysis of yohimbe bark and related dietary supplements using UHPLC/UV/MS.

PubMed

Sun, Jianghao; Chen, Pei

2012-03-05

A practical ultra high-performance liquid chromatography (UHPLC) method was developed for fingerprint analysis of and determination of yohimbine in yohimbe barks and related dietary supplements. Good separation was achieved using a Waters Acquity BEH C(18) column with gradient elution using 0.1% (v/v) aqueous ammonium hydroxide and 0.1% ammonium hydroxide in methanol as the mobile phases. The study is the first reported chromatographic method that separates corynanthine from yohimbine in yohimbe bark extract. The chromatographic fingerprint analysis was applied to the analysis of 18 yohimbe commercial dietary supplement samples. Quantitation of yohimbine, the traditional method for analysis of yohimbe barks, were also performed to evaluate the results of the fingerprint analysis. Wide variability was observed in fingerprints and yohimbine content among yohimbe dietary supplement samples. For most of the dietary supplements, the yohimbine content was not consistent with the label claims. Copyright © 2011. Published by Elsevier B.V.

21 CFR 133.5 - Methods of analysis.

Code of Federal Regulations, 2014 CFR

2014-04-01

... CONSUMPTION CHEESES AND RELATED CHEESE PRODUCTS General Provisions § 133.5 Methods of analysis. Moisture...: http://www.archives.gov/federal_register/code_of_federal_regulations/ibr_locations.html): (a) Moisture content—section 16.233 “Method I (52)—Official Final Action”, under the heading “Moisture”. (b) Milkfat...

Optical coherence tomography measurements and analysis methods in optical coherence tomography studies of diabetic macular edema.

PubMed

Browning, David J; Glassman, Adam R; Aiello, Lloyd P; Bressler, Neil M; Bressler, Susan B; Danis, Ronald P; Davis, Matthew D; Ferris, Frederick L; Huang, Suber S; Kaiser, Peter K; Kollman, Craig; Sadda, Srinavas; Scott, Ingrid U; Qin, Haijing

2008-08-01

To evaluate optical coherence tomography (OCT) measurements and methods of analysis of OCT data in studies of diabetic macular edema (DME). Associations of pairs of OCT variables and results of 3 analysis methods using data from 2 studies of DME. Two hundred sixty-three subjects from a study of modified Early Treatment of Diabetic Retinopathy Study (mETDRS) versus modified macular grid (MMG) photocoagulation for DME and 96 subjects from a study of diurnal variation of DME. Correlations were calculated for pairs of OCT variables at baseline and for changes in the variables over time. Distribution of OCT measurement changes, predictive factors for OCT measurement changes, and treatment group outcomes were compared when 3 measures of change in macular thickness were analyzed: absolute change in retinal thickness, relative change in retinal thickness, and relative change in retinal thickening. Concordance of results using different OCT variables and analysis methods. Center point thickness correlated highly with central subfield mean thickness (CSMT) at baseline (0.98-0.99). The distributions of changes in CSMT were approximately normally distributed for absolute change in retinal thickness and relative change in retinal thickness, but not for relative change in retinal thickening. Macular thinning in the mETDRS group was significantly greater than in the MMG group when absolute change in retinal thickness was used, but not when relative change in thickness and relative change in thickening were used. Relative change in macular thickening provides unstable data in eyes with mild degrees of baseline thickening, unlike the situation with absolute or relative change in retinal thickness. Central subfield mean thickness is the preferred OCT measurement for the central macula because of its higher reproducibility and correlation with other measurements of the central macula. Total macular volume may be preferred when the central macula is less important. Absolute change in retinal thickness is the preferred analysis method in studies involving eyes with mild macular thickening. Relative change in thickening may be preferable when retinal thickening is more severe.

5[prime] to 3[prime] nucleic acid synthesis using 3[prime]-photoremovable protecting group

DOEpatents

Pirrung, M.C.; Shuey, S.W.; Bradley, J.C.

1999-06-01

The present invention relates, in general, to a method of synthesizing a nucleic acid, and, in particular, to a method of effecting 5[prime] to 3[prime] nucleic acid synthesis. The method can be used to prepare arrays of oligomers bound to a support via their 5[prime] end. The invention also relates to a method of effecting mutation analysis using such arrays. The invention further relates to compounds and compositions suitable for use in such methods.

An advanced probabilistic structural analysis method for implicit performance functions

NASA Technical Reports Server (NTRS)

Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

1989-01-01

In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

Skeletal Mechanism Generation of Surrogate Jet Fuels for Aeropropulsion Modeling

NASA Astrophysics Data System (ADS)

Sung, Chih-Jen; Niemeyer, Kyle E.

2010-05-01

A novel implementation for the skeletal reduction of large detailed reaction mechanisms using the directed relation graph with error propagation and sensitivity analysis (DRGEPSA) is developed and presented with skeletal reductions of two important hydrocarbon components, n-heptane and n-decane, relevant to surrogate jet fuel development. DRGEPSA integrates two previously developed methods, directed relation graph-aided sensitivity analysis (DRGASA) and directed relation graph with error propagation (DRGEP), by first applying DRGEP to efficiently remove many unimportant species prior to sensitivity analysis to further remove unimportant species, producing an optimally small skeletal mechanism for a given error limit. It is illustrated that the combination of the DRGEP and DRGASA methods allows the DRGEPSA approach to overcome the weaknesses of each previous method, specifically that DRGEP cannot identify all unimportant species and that DRGASA shields unimportant species from removal.

The power-proportion method for intracranial volume correction in volumetric imaging analysis.

PubMed

Liu, Dawei; Johnson, Hans J; Long, Jeffrey D; Magnotta, Vincent A; Paulsen, Jane S

2014-01-01

In volumetric brain imaging analysis, volumes of brain structures are typically assumed to be proportional or linearly related to intracranial volume (ICV). However, evidence abounds that many brain structures have power law relationships with ICV. To take this relationship into account in volumetric imaging analysis, we propose a power law based method-the power-proportion method-for ICV correction. The performance of the new method is demonstrated using data from the PREDICT-HD study.

Probabilistic structural analysis by extremum methods

NASA Technical Reports Server (NTRS)

Nafday, Avinash M.

1990-01-01

The objective is to demonstrate discrete extremum methods of structural analysis as a tool for structural system reliability evaluation. Specifically, linear and multiobjective linear programming models for analysis of rigid plastic frames under proportional and multiparametric loadings, respectively, are considered. Kinematic and static approaches for analysis form a primal-dual pair in each of these models and have a polyhedral format. Duality relations link extreme points and hyperplanes of these polyhedra and lead naturally to dual methods for system reliability evaluation.

[Research on the reliability and validity of postural workload assessment method and the relation to work-related musculoskeletal disorders of workers].

PubMed

Qin, D L; Jin, X N; Wang, S J; Wang, J J; Mamat, N; Wang, F J; Wang, Y; Shen, Z A; Sheng, L G; Forsman, M; Yang, L Y; Wang, S; Zhang, Z B; He, L H

2018-06-18

To form a new assessment method to evaluate postural workload comprehensively analyzing the dynamic and static postural workload for workers during their work process to analyze the reliability and validity, and to study the relation between workers' postural workload and work-related musculoskeletal disorders (WMSDs). In the study, 844 workers from electronic and railway vehicle manufacturing factories were selected as subjects investigated by using the China Musculoskeletal Questionnaire (CMQ) to form the postural workload comprehensive assessment method. The Cronbach's α, cluster analysis and factor analysis were used to assess the reliability and validity of the new assessment method. Non-conditional Logistic regression was used to analyze the relation between workers' postural workload and WMSDs. Reliability of the assessment method for postural workload: internal consistency analysis results showed that Cronbach's α was 0.934 and the results of split-half reliability indicated that Spearman-Brown coefficient was 0.881 and the correlation coefficient between the first part and the second was 0.787. Validity of the assessment method for postural workload: the results of cluster analysis indicated that square Euclidean distance between dynamic and static postural workload assessment in the same part or work posture was the shortest. The results of factor analysis showed that 2 components were extracted and the cumulative percentage of variance achieved 65.604%. The postural workload score of the different occupational workers showed significant difference (P<0.05) by covariance analysis. The results of nonconditional Logistic regression indicated that alcohol intake (OR=2.141, 95%CI 1.337-3.428) and obesity (OR=3.408, 95%CI 1.629-7.130) were risk factors for WMSDs. The risk for WMSDs would rise as workers' postural workload rose (OR=1.035, 95%CI 1.022-1.048). There was significant different risk for WMSDs in the different groups of workers distinguished by work type, gender and age. Female workers exhibited a higher prevalence for WMSDs (OR=2.626, 95%CI 1.414-4.879) and workers between 30-40 years of age (OR=1.909, 95%CI 1.237-2.946) as compared with those under 30. This method for comprehensively assessing postural workload is reliable and effective when used in assembling workers, and there is certain relation between the postural workload and WMSDs.

A review of machine learning in obesity.

PubMed

DeGregory, K W; Kuiper, P; DeSilvio, T; Pleuss, J D; Miller, R; Roginski, J W; Fisher, C B; Harness, D; Viswanath, S; Heymsfield, S B; Dungan, I; Thomas, D M

2018-05-01

Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine learning provides sophisticated and elegant tools to describe, classify and predict obesity-related risks and outcomes. Here, we review machine learning methods that predict and/or classify such as linear and logistic regression, artificial neural networks, deep learning and decision tree analysis. We also review methods that describe and characterize data such as cluster analysis, principal component analysis, network science and topological data analysis. We introduce each method with a high-level overview followed by examples of successful applications. The algorithms were then applied to National Health and Nutrition Examination Survey to demonstrate methodology, utility and outcomes. The strengths and limitations of each method were also evaluated. This summary of machine learning algorithms provides a unique overview of the state of data analysis applied specifically to obesity. © 2018 World Obesity Federation.

Device and method for enhanced collection and assay of chemicals with high surface area ceramic

DOEpatents

Addleman, Raymond S.; Li, Xiaohong Shari; Chouyyok, Wilaiwan; Cinson, Anthony D.; Bays, John T.; Wallace, Krys

2016-02-16

A method and device for enhanced capture of target analytes is disclosed. This invention relates to collection of chemicals for separations and analysis. More specifically, this invention relates to a solid phase microextraction (SPME) device having better capability for chemical collection and analysis. This includes better physical stability, capacity for chemical collection, flexible surface chemistry and high affinity for target analyte.

Content Analysis of Curriculum-Related Studies in Turkey between 2000 and 2014

ERIC Educational Resources Information Center

Aksan, Elif; Baki, Adnan

2017-01-01

This study aims to carry out a content analysis determining the general framework of studies related to curriculum. For this purpose, 154 curriculum-related studies carried out in Turkey between 2000 and 2014 were examined in terms of year, sample, method, data collection technique, purpose, and result. The most studies related to curriculum were…

Computer Graphics-aided systems analysis: application to well completion design

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

Detamore, J.E.; Sarma, M.P.

1985-03-01

The development of an engineering tool (in the form of a computer model) for solving design and analysis problems related with oil and gas well production operations is discussed. The development of the method is based on integrating the concepts of ''Systems Analysis'' with the techniques of ''Computer Graphics''. The concepts behind the method are very general in nature. This paper, however, illustrates the application of the method in solving gas well completion design problems. The use of the method will save time and improve the efficiency of such design and analysis problems. The method can be extended to othermore » design and analysis aspects of oil and gas wells.« less

Is a multivariate consensus representation of genetic relationships among populations always meaningful?

PubMed Central

Moazami-Goudarzi, K; Laloë, D

2002-01-01

To determine the relationships among closely related populations or species, two methods are commonly used in the literature: phylogenetic reconstruction or multivariate analysis. The aim of this article is to assess the reliability of multivariate analysis. We describe a method that is based on principal component analysis and Mantel correlations, using a two-step process: The first step consists of a single-marker analysis and the second step tests if each marker reveals the same typology concerning population differentiation. We conclude that if single markers are not congruent, the compromise structure is not meaningful. Our model is not based on any particular mutation process and it can be applied to most of the commonly used genetic markers. This method is also useful to determine the contribution of each marker to the typology of populations. We test whether our method is efficient with two real data sets based on microsatellite markers. Our analysis suggests that for closely related populations, it is not always possible to accept the hypothesis that an increase in the number of markers will increase the reliability of the typology analysis. PMID:12242255

Multi-response optimization of T300/epoxy prepreg tape-wound cylinder by grey relational analysis coupled with the response surface method

NASA Astrophysics Data System (ADS)

Kang, Chao; Shi, Yaoyao; He, Xiaodong; Yu, Tao; Deng, Bo; Zhang, Hongji; Sun, Pengcheng; Zhang, Wenbin

2017-09-01

This study investigates the multi-objective optimization of quality characteristics for a T300/epoxy prepreg tape-wound cylinder. The method integrates the Taguchi method, grey relational analysis (GRA) and response surface methodology, and is adopted to improve tensile strength and reduce residual stress. In the winding process, the main process parameters involving winding tension, pressure, temperature and speed are selected to evaluate the parametric influences on tensile strength and residual stress. Experiments are conducted using the Box-Behnken design. Based on principal component analysis, the grey relational grades are properly established to convert multi-responses into an individual objective problem. Then the response surface method is used to build a second-order model of grey relational grade and predict the optimum parameters. The predictive accuracy of the developed model is proved by two test experiments with a low prediction error of less than 7%. The following process parameters, namely winding tension 124.29 N, pressure 2000 N, temperature 40 °C and speed 10.65 rpm, have the highest grey relational grade and give better quality characteristics in terms of tensile strength and residual stress. The confirmation experiment shows that better results are obtained with GRA improved by the proposed method than with ordinary GRA. The proposed method is proved to be feasible and can be applied to optimize the multi-objective problem in the filament winding process.

High accuracy method for the application of isotope dilution to gas chromatography/mass spectrometric analysis of gases.

PubMed

Milton, Martin J T; Wang, Jian

2003-01-01

A new isotope dilution mass spectrometry (IDMS) method for high-accuracy quantitative analysis of gases has been developed and validated by the analysis of standard mixtures of carbon dioxide in nitrogen. The method does not require certified isotopic reference materials and does not require direct measurements of the highly enriched spike. The relative uncertainty of the method is shown to be 0.2%. Reproduced with the permission of Her Majesty's Stationery Office. Copyright Crown copyright 2003.

High-pressure liquid chromatography analysis of antibiotic susceptibility disks.

PubMed Central

Hagel, R B; Waysek, E H; Cort, W M

1979-01-01

The analysis of antibiotic susceptibility disks by high-pressure liquid chromatography (HPLC) was investigated. Methods are presented for the potency determination of mecillinam, ampicillin, carbenicillin, and cephalothin alone and in various combinations. Good agreement between HPLC and microbiological data is observed for potency determinations with recoveries of greater than 95%. Relative standard deviations of lower than 2% are recorded for each HPLC method. HPLC methods offer improved accuracy and greater precision when compared to the standard microbiological methods of analysis for susceptibility disks. PMID:507793

RO1 Funding for Mixed Methods Research: Lessons learned from the Mixed-Method Analysis of Japanese Depression Project

PubMed Central

Arnault, Denise Saint; Fetters, Michael D.

2013-01-01

Mixed methods research has made significant in-roads in the effort to examine complex health related phenomenon. However, little has been published on the funding of mixed methods research projects. This paper addresses that gap by presenting an example of an NIMH funded project using a mixed methods QUAL-QUAN triangulation design entitled “The Mixed-Method Analysis of Japanese Depression.” We present the Cultural Determinants of Health Seeking model that framed the study, the specific aims, the quantitative and qualitative data sources informing the study, and overview of the mixing of the two studies. Finally, we examine reviewer's comments and our insights related to writing mixed method proposal successful for achieving RO1 level funding. PMID:25419196

Achieving cost-neutrality with long-acting reversible contraceptive methods.

PubMed

Trussell, James; Hassan, Fareen; Lowin, Julia; Law, Amy; Filonenko, Anna

2015-01-01

This analysis aimed to estimate the average annual cost of available reversible contraceptive methods in the United States. In line with literature suggesting long-acting reversible contraceptive (LARC) methods become increasingly cost-saving with extended duration of use, it aimed to also quantify minimum duration of use required for LARC methods to achieve cost-neutrality relative to other reversible contraceptive methods while taking into consideration discontinuation. A three-state economic model was developed to estimate relative costs of no method (chance), four short-acting reversible (SARC) methods (oral contraceptive, ring, patch and injection) and three LARC methods [implant, copper intrauterine device (IUD) and levonorgestrel intrauterine system (LNG-IUS) 20 mcg/24 h (total content 52 mg)]. The analysis was conducted over a 5-year time horizon in 1000 women aged 20-29 years. Method-specific failure and discontinuation rates were based on published literature. Costs associated with drug acquisition, administration and failure (defined as an unintended pregnancy) were considered. Key model outputs were annual average cost per method and minimum duration of LARC method usage to achieve cost-savings compared to SARC methods. The two least expensive methods were copper IUD ($304 per women, per year) and LNG-IUS 20 mcg/24 h ($308). Cost of SARC methods ranged between $432 (injection) and $730 (patch), per women, per year. A minimum of 2.1 years of LARC usage would result in cost-savings compared to SARC usage. This analysis finds that even if LARC methods are not used for their full durations of efficacy, they become cost-saving relative to SARC methods within 3 years of use. Previous economic arguments in support of using LARC methods have been criticized for not considering that LARC methods are not always used for their full duration of efficacy. This study calculated that cost-savings from LARC methods relative to SARC methods, with discontinuation rates considered, can be realized within 3 years. Copyright © 2014 Elsevier Inc. All rights reserved.

[Extraction of evoked related potentials by using the combination of independent component analysis and wavelet analysis].

PubMed

Zou, Ling; Chen, Shuyue; Sun, Yuqiang; Ma, Zhenghua

2010-08-01

In this paper we present a new method of combining Independent Component Analysis (ICA) and Wavelet de-noising algorithm to extract Evoked Related Potentials (ERPs). First, the extended Infomax-ICA algorithm is used to analyze EEG signals and obtain the independent components (Ics); Then, the Wave Shrink (WS) method is applied to the demixed Ics as an intermediate step; the EEG data were rebuilt by using the inverse ICA based on the new Ics; the ERPs were extracted by using de-noised EEG data after being averaged several trials. The experimental results showed that the combined method and ICA method could remove eye artifacts and muscle artifacts mixed in the ERPs, while the combined method could retain the brain neural activity mixed in the noise Ics and could extract the weak ERPs efficiently from strong background artifacts.

Probabilistic Structural Analysis Theory Development

NASA Technical Reports Server (NTRS)

Burnside, O. H.

1985-01-01

The objective of the Probabilistic Structural Analysis Methods (PSAM) project is to develop analysis techniques and computer programs for predicting the probabilistic response of critical structural components for current and future space propulsion systems. This technology will play a central role in establishing system performance and durability. The first year's technical activity is concentrating on probabilistic finite element formulation strategy and code development. Work is also in progress to survey critical materials and space shuttle mian engine components. The probabilistic finite element computer program NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) is being developed. The final probabilistic code will have, in the general case, the capability of performing nonlinear dynamic of stochastic structures. It is the goal of the approximate methods effort to increase problem solving efficiency relative to finite element methods by using energy methods to generate trial solutions which satisfy the structural boundary conditions. These approximate methods will be less computer intensive relative to the finite element approach.

Relative Displacement Method for Track-Structure Interaction

PubMed Central

Ramos, Óscar Ramón; Pantaleón, Marcos J.

2014-01-01

The track-structure interaction effects are usually analysed with conventional FEM programs, where it is difficult to implement the complex track-structure connection behaviour, which is nonlinear, elastic-plastic and depends on the vertical load. The authors developed an alternative analysis method, which they call the relative displacement method. It is based on the calculation of deformation states in single DOF element models that satisfy the boundary conditions. For its solution, an iterative optimisation algorithm is used. This method can be implemented in any programming language or analysis software. A comparison with ABAQUS calculations shows a very good result correlation and compliance with the standard's specifications. PMID:24634610

Optimization of Parameter Ranges for Composite Tape Winding Process Based on Sensitivity Analysis

NASA Astrophysics Data System (ADS)

Yu, Tao; Shi, Yaoyao; He, Xiaodong; Kang, Chao; Deng, Bo; Song, Shibo

2017-08-01

This study is focus on the parameters sensitivity of winding process for composite prepreg tape. The methods of multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis are proposed. The polynomial empirical model of interlaminar shear strength is established by response surface experimental method. Using this model, the relative sensitivity of key process parameters including temperature, tension, pressure and velocity is calculated, while the single-parameter sensitivity curves are obtained. According to the analysis of sensitivity curves, the stability and instability range of each parameter are recognized. Finally, the optimization method of winding process parameters is developed. The analysis results show that the optimized ranges of the process parameters for interlaminar shear strength are: temperature within [100 °C, 150 °C], tension within [275 N, 387 N], pressure within [800 N, 1500 N], and velocity within [0.2 m/s, 0.4 m/s], respectively.

A Century of Enzyme Kinetic Analysis, 1913 to 2013

PubMed Central

Johnson, Kenneth A.

2013-01-01

This review traces the history and logical progression of methods for quantitative analysis of enzyme kinetics from the 1913 Michaelis and Menten paper to the application of modern computational methods today. Following a brief review of methods for fitting steady state kinetic data, modern methods are highlighted for fitting full progress curve kinetics based upon numerical integration of rate equations, including a re-analysis of the original Michaelis-Menten full time course kinetic data. Finally, several illustrations of modern transient state kinetic methods of analysis are shown which enable the elucidation of reactions occurring at the active sites of enzymes in order to relate structure and function. PMID:23850893

Estimation of Environment-Related Properties of Chemicals for Design of Sustainable Processes: Development of Group-Contribution+ (GC+) Property Models and Uncertainty Analysis

EPA Science Inventory

The aim of this work is to develop group-contribution+ (GC+) method (combined group-contribution (GC) method and atom connectivity index (CI) method) based property models to provide reliable estimations of environment-related properties of organic chemicals together with uncert...

Shape design sensitivity analysis and optimal design of structural systems

NASA Technical Reports Server (NTRS)

Choi, Kyung K.

1987-01-01

The material derivative concept of continuum mechanics and an adjoint variable method of design sensitivity analysis are used to relate variations in structural shape to measures of structural performance. A domain method of shape design sensitivity analysis is used to best utilize the basic character of the finite element method that gives accurate information not on the boundary but in the domain. Implementation of shape design sensitivty analysis using finite element computer codes is discussed. Recent numerical results are used to demonstrate the accuracy obtainable using the method. Result of design sensitivity analysis is used to carry out design optimization of a built-up structure.

Achieving cost-neutrality with long-acting reversible contraceptive methods⋆

PubMed Central

Trussell, James; Hassan, Fareen; Lowin, Julia; Law, Amy; Filonenko, Anna

2014-01-01

Objectives This analysis aimed to estimate the average annual cost of available reversible contraceptive methods in the United States. In line with literature suggesting long-acting reversible contraceptive (LARC) methods become increasingly cost-saving with extended duration of use, it aimed to also quantify minimum duration of use required for LARC methods to achieve cost-neutrality relative to other reversible contraceptive methods while taking into consideration discontinuation. Study design A three-state economic model was developed to estimate relative costs of no method (chance), four short-acting reversible (SARC) methods (oral contraceptive, ring, patch and injection) and three LARC methods [implant, copper intrauterine device (IUD) and levonorgestrel intrauterine system (LNG-IUS) 20 mcg/24 h (total content 52 mg)]. The analysis was conducted over a 5-year time horizon in 1000 women aged 20–29 years. Method-specific failure and discontinuation rates were based on published literature. Costs associated with drug acquisition, administration and failure (defined as an unintended pregnancy) were considered. Key model outputs were annual average cost per method and minimum duration of LARC method usage to achieve cost-savings compared to SARC methods. Results The two least expensive methods were copper IUD ($304 per women, per year) and LNG-IUS 20 mcg/24 h ($308). Cost of SARC methods ranged between $432 (injection) and $730 (patch), per women, per year. A minimum of 2.1 years of LARC usage would result in cost-savings compared to SARC usage. Conclusions This analysis finds that even if LARC methods are not used for their full durations of efficacy, they become cost-saving relative to SARC methods within 3 years of use. Implications Previous economic arguments in support of using LARC methods have been criticized for not considering that LARC methods are not always used for their full duration of efficacy. This study calculated that cost-savings from LARC methods relative to SARC methods, with discontinuation rates considered, can be realized within 3 years. PMID:25282161

Research on criticality analysis method of CNC machine tools components under fault rate correlation

NASA Astrophysics Data System (ADS)

Gui-xiang, Shen; Xian-zhuo, Zhao; Zhang, Ying-zhi; Chen-yu, Han

2018-02-01

In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.

Use of Latent Profile Analysis in Studies of Gifted Students

ERIC Educational Resources Information Center

Mammadov, Sakhavat; Ward, Thomas J.; Cross, Jennifer Riedl; Cross, Tracy L.

2016-01-01

To date, in gifted education and related fields various conventional factor analytic and clustering techniques have been used extensively for investigation of the underlying structure of data. Latent profile analysis is a relatively new method in the field. In this article, we provide an introduction to latent profile analysis for gifted education…

Benefit-risk analysis : a brief review and proposed quantitative approaches.

PubMed

Holden, William L

2003-01-01

Given the current status of benefit-risk analysis as a largely qualitative method, two techniques for a quantitative synthesis of a drug's benefit and risk are proposed to allow a more objective approach. The recommended methods, relative-value adjusted number-needed-to-treat (RV-NNT) and its extension, minimum clinical efficacy (MCE) analysis, rely upon efficacy or effectiveness data, adverse event data and utility data from patients, describing their preferences for an outcome given potential risks. These methods, using hypothetical data for rheumatoid arthritis drugs, demonstrate that quantitative distinctions can be made between drugs which would better inform clinicians, drug regulators and patients about a drug's benefit-risk profile. If the number of patients needed to treat is less than the relative-value adjusted number-needed-to-harm in an RV-NNT analysis, patients are willing to undergo treatment with the experimental drug to derive a certain benefit knowing that they may be at risk for any of a series of potential adverse events. Similarly, the results of an MCE analysis allow for determining the worth of a new treatment relative to an older one, given not only the potential risks of adverse events and benefits that may be gained, but also by taking into account the risk of disease without any treatment. Quantitative methods of benefit-risk analysis have a place in the evaluative armamentarium of pharmacovigilance, especially those that incorporate patients' perspectives.

Expected number of asbestos-related lung cancers in the Netherlands in the next two decades: a comparison of methods.

PubMed

Van der Bij, Sjoukje; Vermeulen, Roel C H; Portengen, Lützen; Moons, Karel G M; Koffijberg, Hendrik

2016-05-01

Exposure to asbestos fibres increases the risk of mesothelioma and lung cancer. Although the vast majority of mesothelioma cases are caused by asbestos exposure, the number of asbestos-related lung cancers is less clear. This number cannot be determined directly as lung cancer causes are not clinically distinguishable but may be estimated using varying modelling methods. We applied three different modelling methods to the Dutch population supplemented with uncertainty ranges (UR) due to uncertainty in model input values. The first method estimated asbestos-related lung cancer cases directly from observed and predicted mesothelioma cases in an age-period-cohort analysis. The second method used evidence on the fraction of lung cancer cases attributable (population attributable risk (PAR)) to asbestos exposure. The third method incorporated risk estimates and population exposure estimates to perform a life table analysis. The three methods varied substantially in incorporated evidence. Moreover, the estimated number of asbestos-related lung cancer cases in the Netherlands between 2011 and 2030 depended crucially on the actual method applied, as the mesothelioma method predicts 17 500 expected cases (UR 7000-57 000), the PAR method predicts 12 150 cases (UR 6700-19 000), and the life table analysis predicts 6800 cases (UR 6800-33 850). The three different methods described resulted in absolute estimates varying by a factor of ∼2.5. These results show that accurate estimation of the impact of asbestos exposure on the lung cancer burden remains a challenge. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

The QAP weighted network analysis method and its application in international services trade

NASA Astrophysics Data System (ADS)

Xu, Helian; Cheng, Long

2016-04-01

Based on QAP (Quadratic Assignment Procedure) correlation and complex network theory, this paper puts forward a new method named QAP Weighted Network Analysis Method. The core idea of the method is to analyze influences among relations in a social or economic group by building a QAP weighted network of networks of relations. In the QAP weighted network, a node depicts a relation and an undirect edge exists between any pair of nodes if there is significant correlation between relations. As an application of the QAP weighted network, we study international services trade by using the QAP weighted network, in which nodes depict 10 kinds of services trade relations. After the analysis of international services trade by QAP weighted network, and by using distance indicators, hierarchy tree and minimum spanning tree, the conclusion shows that: Firstly, significant correlation exists in all services trade, and the development of any one service trade will stimulate the other nine. Secondly, as the economic globalization goes deeper, correlations in all services trade have been strengthened continually, and clustering effects exist in those services trade. Thirdly, transportation services trade, computer and information services trade and communication services trade have the most influence and are at the core in all services trade.

Domain fusion analysis by applying relational algebra to protein sequence and domain databases

PubMed Central

Truong, Kevin; Ikura, Mitsuhiko

2003-01-01

Background Domain fusion analysis is a useful method to predict functionally linked proteins that may be involved in direct protein-protein interactions or in the same metabolic or signaling pathway. As separate domain databases like BLOCKS, PROSITE, Pfam, SMART, PRINTS-S, ProDom, TIGRFAMs, and amalgamated domain databases like InterPro continue to grow in size and quality, a computational method to perform domain fusion analysis that leverages on these efforts will become increasingly powerful. Results This paper proposes a computational method employing relational algebra to find domain fusions in protein sequence databases. The feasibility of this method was illustrated on the SWISS-PROT+TrEMBL sequence database using domain predictions from the Pfam HMM (hidden Markov model) database. We identified 235 and 189 putative functionally linked protein partners in H. sapiens and S. cerevisiae, respectively. From scientific literature, we were able to confirm many of these functional linkages, while the remainder offer testable experimental hypothesis. Results can be viewed at . Conclusion As the analysis can be computed quickly on any relational database that supports standard SQL (structured query language), it can be dynamically updated along with the sequence and domain databases, thereby improving the quality of predictions over time. PMID:12734020

Method of assessing a lipid-related health risk based on ion mobility analysis of lipoproteins

DOEpatents

Benner, W. Henry; Krauss, Ronald M.; Blanche, Patricia J.

2010-12-14

A medical diagnostic method and instrumentation system for analyzing noncovalently bonded agglomerated biological particles is described. The method and system comprises: a method of preparation for the biological particles; an electrospray generator; an alpha particle radiation source; a differential mobility analyzer; a particle counter; and data acquisition and analysis means. The medical device is useful for the assessment of human diseases, such as cardiac disease risk and hyperlipidemia, by rapid quantitative analysis of lipoprotein fraction densities. Initially, purification procedures are described to reduce an initial blood sample to an analytical input to the instrument. The measured sizes from the analytical sample are correlated with densities, resulting in a spectrum of lipoprotein densities. The lipoprotein density distribution can then be used to characterize cardiac and other lipid-related health risks.

The Five Star Method: A Relational Dream Work Methodology

ERIC Educational Resources Information Center

Sparrow, Gregory Scott; Thurston, Mark

2010-01-01

This article presents a systematic method of dream work called the Five Star Method. Based on cocreative dream theory, which views the dream as the product of the interaction between dreamer and dream, this creative intervention shifts the principal focus in dream analysis from the interpretation of static imagery to the analysis of the dreamer's…

A Cost-Effectiveness/Benefit Analysis Model for Postsecondary Vocational Programs. Technical Report.

ERIC Educational Resources Information Center

Kim, Jin Eun

A cost-effectiveness/benefit analysis is defined as a technique for measuring the outputs of existing and new programs in relation to their specified program objectives, against the costs of those programs. In terms of its specific use, the technique is conceptualized as a systems analysis method, an evaluation method, and a planning tool for…

Using Citation Analysis Methods to Assess the Influence of Science, Technology, Engineering, and Mathematics Education Evaluations

ERIC Educational Resources Information Center

Greenseid, Lija O.; Lawrenz, Frances

2011-01-01

This study explores the use of citation analysis methods to assess the influence of program evaluations conducted within the area of science, technology, engineering, and mathematics (STEM) education. Citation analysis is widely used within scientific research communities to measure the relative influence of scientific research enterprises and/or…

An improved method for bivariate meta-analysis when within-study correlations are unknown.

PubMed

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the sample size is relatively small, we recommend the use of the robust method under the working independence assumption. We illustrate the proposed method through 2 meta-analyses. Copyright © 2017 John Wiley & Sons, Ltd.

Singularity in structural optimization

NASA Technical Reports Server (NTRS)

Patnaik, S. N.; Guptill, J. D.; Berke, L.

1993-01-01

The conditions under which global and local singularities may arise in structural optimization are examined. Examples of these singularities are presented, and a framework is given within which the singularities can be recognized. It is shown, in particular, that singularities can be identified through the analysis of stress-displacement relations together with compatibility conditions or the displacement-stress relations derived by the integrated force method of structural analysis. Methods of eliminating the effects of singularities are suggested and illustrated numerically.

Elemental analysis by IBA and NAA — A critical comparison

NASA Astrophysics Data System (ADS)

Watterson, J. I. W.

1988-12-01

In this review neutron activation analysis (NAA) and ion beam analysis (IBA) have been compared in the context of the entire field of analytical science using the discipline of scientometrics, as developed by Braun and Lyon. This perspective on the relative achievements of the two methods is modified by considering and comparing their particular attributes and characteristics, particularly in relation to their differing degree of maturity. This assessment shows that NAA, as the more mature method, is the most widely applied nuclear technique, but the special capabilities of IBA give it the ability to provide information about surface composition and elemental distribution that is unique, while it is still relatively immature and it is not yet possible to define its ultimate role with any confidence.

Systems and methods for sample analysis

DOEpatents

Cooks, Robert Graham; Li, Guangtao; Li, Xin; Ouyang, Zheng

2015-01-13

The invention generally relates to systems and methods for sample analysis. In certain embodiments, the invention provides a system for analyzing a sample that includes a probe including a material connected to a high voltage source, a device for generating a heated gas, and a mass analyzer.

A Collaborative Evaluation of LC-MS/MS Based Methods for BMAA Analysis: Soluble Bound BMAA Found to Be an Important Fraction.

PubMed

Faassen, Elisabeth J; Antoniou, Maria G; Beekman-Lukassen, Wendy; Blahova, Lucie; Chernova, Ekaterina; Christophoridis, Christophoros; Combes, Audrey; Edwards, Christine; Fastner, Jutta; Harmsen, Joop; Hiskia, Anastasia; Ilag, Leopold L; Kaloudis, Triantafyllos; Lopicic, Srdjan; Lürling, Miquel; Mazur-Marzec, Hanna; Meriluoto, Jussi; Porojan, Cristina; Viner-Mozzini, Yehudit; Zguna, Nadezda

2016-02-29

Exposure to β-N-methylamino-l-alanine (BMAA) might be linked to the incidence of amyotrophic lateral sclerosis, Alzheimer's disease and Parkinson's disease. Analytical chemistry plays a crucial role in determining human BMAA exposure and the associated health risk, but the performance of various analytical methods currently employed is rarely compared. A CYANOCOST initiated workshop was organized aimed at training scientists in BMAA analysis, creating mutual understanding and paving the way towards interlaboratory comparison exercises. During this workshop, we tested different methods (extraction followed by derivatization and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) analysis, or directly followed by LC-MS/MS analysis) for trueness and intermediate precision. We adapted three workup methods for the underivatized analysis of animal, brain and cyanobacterial samples. Based on recovery of the internal standard D₃BMAA, the underivatized methods were accurate (mean recovery 80%) and precise (mean relative standard deviation 10%), except for the cyanobacterium Leptolyngbya. However, total BMAA concentrations in the positive controls (cycad seeds) showed higher variation (relative standard deviation 21%-32%), implying that D₃BMAA was not a good indicator for the release of BMAA from bound forms. Significant losses occurred during workup for the derivatized method, resulting in low recovery (<10%). Most BMAA was found in a trichloroacetic acid soluble, bound form and we recommend including this fraction during analysis.

Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study.

PubMed

Egbewale, Bolaji E; Lewis, Martyn; Sim, Julius

2014-04-09

Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. 126 hypothetical trial scenarios were evaluated (126,000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power.

The Analysis of Likert Scales Using State Multipoles: An Application of Quantum Methods to Behavioral Sciences Data

ERIC Educational Resources Information Center

Camparo, James; Camparo, Lorinda B.

2013-01-01

Though ubiquitous, Likert scaling's traditional mode of analysis is often unable to uncover all of the valid information in a data set. Here, the authors discuss a solution to this problem based on methodology developed by quantum physicists: the state multipole method. The authors demonstrate the relative ease and value of this method by…

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling

NASA Astrophysics Data System (ADS)

Dai, Heng; Chen, Xingyuan; Ye, Ming; Song, Xuehang; Zachara, John M.

2017-05-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study, we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multilayer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially distributed input variables.

A Geostatistics-Informed Hierarchical Sensitivity Analysis Method for Complex Groundwater Flow and Transport Modeling

NASA Astrophysics Data System (ADS)

Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.

2017-12-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multi-layer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed input variables.

An automated method to analyze language use in patients with schizophrenia and their first-degree relatives

PubMed Central

Elvevåg, Brita; Foltz, Peter W.; Rosenstein, Mark; DeLisi, Lynn E.

2009-01-01

Communication disturbances are prevalent in schizophrenia, and since it is a heritable illness these are likely present - albeit in a muted form - in the relatives of patients. Given the time-consuming, and often subjective nature of discourse analysis, these deviances are frequently not assayed in large scale studies. Recent work in computational linguistics and statistical-based semantic analysis has shown the potential and power of automated analysis of communication. We present an automated and objective approach to modeling discourse that detects very subtle deviations between probands, their first-degree relatives and unrelated healthy controls. Although these findings should be regarded as preliminary due to the limitations of the data at our disposal, we present a brief analysis of the models that best differentiate these groups in order to illustrate the utility of the method for future explorations of how language components are differentially affected by familial and illness related issues. PMID:20383310

Classification of LC columns based on the QSRR method and selectivity toward moclobemide and its metabolites.

PubMed

Plenis, Alina; Olędzka, Ilona; Bączek, Tomasz

2013-05-05

This paper focuses on a comparative study of the column classification system based on the quantitative structure-retention relationships (QSRR method) and column performance in real biomedical analysis. The assay was carried out for the LC separation of moclobemide and its metabolites in human plasma, using a set of 24 stationary phases. The QSRR models established for the studied stationary phases were compared with the column test performance results under two chemometric techniques - the principal component analysis (PCA) and the hierarchical clustering analysis (HCA). The study confirmed that the stationary phase classes found closely related by the QSRR approach yielded comparable separation for moclobemide and its metabolites. Therefore, the QSRR method could be considered supportive in the selection of a suitable column for the biomedical analysis offering the selection of similar or dissimilar columns with a relatively higher certainty. Copyright © 2013 Elsevier B.V. All rights reserved.

Gait Analysis Using Wearable Sensors

PubMed Central

Tao, Weijun; Liu, Tao; Zheng, Rencheng; Feng, Hutian

2012-01-01

Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a clinical tool applied in the rehabilitation and diagnosis of medical conditions and sport activities, gait analysis using wearable sensors shows great prospects. The current paper reviews available wearable sensors and ambulatory gait analysis methods based on the various wearable sensors. After an introduction of the gait phases, the principles and features of wearable sensors used in gait analysis are provided. The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography. Studies on the current methods are reviewed, and applications in sports, rehabilitation, and clinical diagnosis are summarized separately. With the development of sensor technology and the analysis method, gait analysis using wearable sensors is expected to play an increasingly important role in clinical applications. PMID:22438763

Using a voice-centered relational method of data analysis in a feminist study exploring the working world of nursing unit managers.

PubMed

Paliadelis, Penny; Cruickshank, Mary

2008-10-01

In this article, we discuss the application of a data analysis method used in a feminist study that explored the working world of nursing unit managers in Australia. The decision to use a voice-centered relational approach to the data was based on a desire to delve into the working world of nursing unit managers and uncover the layers within the narratives that specifically related to their perceptions of themselves, their world, and the context in which they work. Throughout this article, the focus is on how this method was applied to uncover multiple layers of meaning within the data, rather than on the researchers' and participants' roles in the coconstruction of interview data. An excerpt from an interview transcript is used to illustrate how the stories of the participants were explored using this method.

Fingerprint analysis of Ginkgo biloba leaves and related health foods by high-performance liquid chromatography/electrospray ionization-mass spectrometry.

PubMed

Song, Jiajia; Fang, Guozhen; Zhang, Yan; Deng, Qiliang; Wang, Shuo

2010-01-01

A fingerprint analysis method was developed for Ginkgo biloba leaves and was successfully used for quality evaluation of related health foods by HPLC with electrospray ionization MS. Fifteen samples of G. biloba leaves, which were collected from 15 different locations in China, were analyzed and identified in this study. By both peak analysis and similarity analysis of the fingerprint chromatograms, variation of constituents was easily observed in the leaves from different sources. By comparison with batches of authentic leaves, the authenticity, and quality consistency of related health foods in different matrixes were effectively estimated. It is important to mention that studying a wide range of authentic leaves from various habitats made the quality evaluation of commercial products more convincing and reasonable. The fingerprint-based strategy of the developed method should provide improved QC of G. biloba leaves and products.

An Analysis of Methods Used to Examine Gender Differences in Computer-Related Behavior.

ERIC Educational Resources Information Center

Kay, Robin

1992-01-01

Review of research investigating gender differences in computer-related behavior examines statistical and methodological flaws. Issues addressed include sample selection, sample size, scale development, scale quality, the use of univariate and multivariate analyses, regressional analysis, construct definition, construct testing, and the…

Consumer-led health-related online sources and their impact on consumers: An integrative review of the literature.

PubMed

Laukka, Elina; Rantakokko, Piia; Suhonen, Marjo

2017-04-01

The aim of the review was to describe consumer-led health-related online sources and their impact on consumers. The review was carried out as an integrative literature review. Quantisation and qualitative content analysis were used as the analysis method. The most common method used by the included studies was qualitative content analysis. This review identified the consumer-led health-related online sources used between 2009 and 2016 as health-related online communities, health-related social networking sites and health-related rating websites. These sources had an impact on peer support; empowerment; health literacy; physical, mental and emotional wellbeing; illness management; and relationships between healthcare organisations and consumers. The knowledge of the existence of the health-related online sources provides healthcare organisations with an opportunity to listen to their consumers' 'voice'. The sources make healthcare consumers more competent actors in relation to healthcare, and the knowledge of them is a valuable resource for healthcare organisations. Additionally, these health-related online sources might create an opportunity to reduce the need for drifting among the healthcare services. Healthcare policymakers and organisations could benefit from having a strategy of increasing their health-related online sources.

A comparison of analysis methods to estimate contingency strength.

PubMed

Lloyd, Blair P; Staubitz, Johanna L; Tapp, Jon T

2018-05-09

To date, several data analysis methods have been used to estimate contingency strength, yet few studies have compared these methods directly. To compare the relative precision and sensitivity of four analysis methods (i.e., exhaustive event-based, nonexhaustive event-based, concurrent interval, concurrent+lag interval), we applied all methods to a simulated data set in which several response-dependent and response-independent schedules of reinforcement were programmed. We evaluated the degree to which contingency strength estimates produced from each method (a) corresponded with expected values for response-dependent schedules and (b) showed sensitivity to parametric manipulations of response-independent reinforcement. Results indicated both event-based methods produced contingency strength estimates that aligned with expected values for response-dependent schedules, but differed in sensitivity to response-independent reinforcement. The precision of interval-based methods varied by analysis method (concurrent vs. concurrent+lag) and schedule type (continuous vs. partial), and showed similar sensitivities to response-independent reinforcement. Recommendations and considerations for measuring contingencies are identified. © 2018 Society for the Experimental Analysis of Behavior.

Direct determination of one-dimensional interphase structures using normalized crystal truncation rod analysis

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

Kawaguchi, Tomoya; Liu, Yihua; Reiter, Anthony

Here, a one-dimensional non-iterative direct method was employed for normalized crystal truncation rod analysis. The non-iterative approach, utilizing the Kramers–Kronig relation, avoids the ambiguities due to an improper initial model or incomplete convergence in the conventional iterative methods. The validity and limitations of the present method are demonstrated through both numerical simulations and experiments with Pt(111) in a 0.1 M CsF aqueous solution. The present method is compared with conventional iterative phase-retrieval methods.

Direct determination of one-dimensional interphase structures using normalized crystal truncation rod analysis

DOE PAGES

Kawaguchi, Tomoya; Liu, Yihua; Reiter, Anthony; ...

2018-04-20

Here, a one-dimensional non-iterative direct method was employed for normalized crystal truncation rod analysis. The non-iterative approach, utilizing the Kramers–Kronig relation, avoids the ambiguities due to an improper initial model or incomplete convergence in the conventional iterative methods. The validity and limitations of the present method are demonstrated through both numerical simulations and experiments with Pt(111) in a 0.1 M CsF aqueous solution. The present method is compared with conventional iterative phase-retrieval methods.

Study of flutter related computational procedures for minimum weight structural sizing of advanced aircraft, supplemental data

NASA Technical Reports Server (NTRS)

Oconnell, R. F.; Hassig, H. J.; Radovcich, N. A.

1975-01-01

Computational aspects of (1) flutter optimization (minimization of structural mass subject to specified flutter requirements), (2) methods for solving the flutter equation, and (3) efficient methods for computing generalized aerodynamic force coefficients in the repetitive analysis environment of computer-aided structural design are discussed. Specific areas included: a two-dimensional Regula Falsi approach to solving the generalized flutter equation; method of incremented flutter analysis and its applications; the use of velocity potential influence coefficients in a five-matrix product formulation of the generalized aerodynamic force coefficients; options for computational operations required to generate generalized aerodynamic force coefficients; theoretical considerations related to optimization with one or more flutter constraints; and expressions for derivatives of flutter-related quantities with respect to design variables.

Determine equilibrium dissociation constant of drug-membrane receptor affinity using the cell membrane chromatography relative standard method.

PubMed

Ma, Weina; Yang, Liu; Lv, Yanni; Fu, Jia; Zhang, Yanmin; He, Langchong

2017-06-23

The equilibrium dissociation constant (K D ) of drug-membrane receptor affinity is the basic parameter that reflects the strength of interaction. The cell membrane chromatography (CMC) method is an effective technique to study the characteristics of drug-membrane receptor affinity. In this study, the K D value of CMC relative standard method for the determination of drug-membrane receptor affinity was established to analyze the relative K D values of drugs binding to the membrane receptors (Epidermal growth factor receptor and angiotensin II receptor). The K D values obtained by the CMC relative standard method had a strong correlation with those obtained by the frontal analysis method. Additionally, the K D values obtained by CMC relative standard method correlated with pharmacological activity of the drug being evaluated. The CMC relative standard method is a convenient and effective method to evaluate drug-membrane receptor affinity. Copyright © 2017 Elsevier B.V. All rights reserved.

Domain fusion analysis by applying relational algebra to protein sequence and domain databases.

PubMed

Truong, Kevin; Ikura, Mitsuhiko

2003-05-06

Domain fusion analysis is a useful method to predict functionally linked proteins that may be involved in direct protein-protein interactions or in the same metabolic or signaling pathway. As separate domain databases like BLOCKS, PROSITE, Pfam, SMART, PRINTS-S, ProDom, TIGRFAMs, and amalgamated domain databases like InterPro continue to grow in size and quality, a computational method to perform domain fusion analysis that leverages on these efforts will become increasingly powerful. This paper proposes a computational method employing relational algebra to find domain fusions in protein sequence databases. The feasibility of this method was illustrated on the SWISS-PROT+TrEMBL sequence database using domain predictions from the Pfam HMM (hidden Markov model) database. We identified 235 and 189 putative functionally linked protein partners in H. sapiens and S. cerevisiae, respectively. From scientific literature, we were able to confirm many of these functional linkages, while the remainder offer testable experimental hypothesis. Results can be viewed at http://calcium.uhnres.utoronto.ca/pi. As the analysis can be computed quickly on any relational database that supports standard SQL (structured query language), it can be dynamically updated along with the sequence and domain databases, thereby improving the quality of predictions over time.

A Tutorial in Bayesian Potential Outcomes Mediation Analysis.

PubMed

Miočević, Milica; Gonzalez, Oscar; Valente, Matthew J; MacKinnon, David P

2018-01-01

Statistical mediation analysis is used to investigate intermediate variables in the relation between independent and dependent variables. Causal interpretation of mediation analyses is challenging because randomization of subjects to levels of the independent variable does not rule out the possibility of unmeasured confounders of the mediator to outcome relation. Furthermore, commonly used frequentist methods for mediation analysis compute the probability of the data given the null hypothesis, which is not the probability of a hypothesis given the data as in Bayesian analysis. Under certain assumptions, applying the potential outcomes framework to mediation analysis allows for the computation of causal effects, and statistical mediation in the Bayesian framework gives indirect effects probabilistic interpretations. This tutorial combines causal inference and Bayesian methods for mediation analysis so the indirect and direct effects have both causal and probabilistic interpretations. Steps in Bayesian causal mediation analysis are shown in the application to an empirical example.

The effect of uncertainties in distance-based ranking methods for multi-criteria decision making

NASA Astrophysics Data System (ADS)

Jaini, Nor I.; Utyuzhnikov, Sergei V.

2017-08-01

Data in the multi-criteria decision making are often imprecise and changeable. Therefore, it is important to carry out sensitivity analysis test for the multi-criteria decision making problem. The paper aims to present a sensitivity analysis for some ranking techniques based on the distance measures in multi-criteria decision making. Two types of uncertainties are considered for the sensitivity analysis test. The first uncertainty is related to the input data, while the second uncertainty is towards the Decision Maker preferences (weights). The ranking techniques considered in this study are TOPSIS, the relative distance and trade-off ranking methods. TOPSIS and the relative distance method measure a distance from an alternative to the ideal and antiideal solutions. In turn, the trade-off ranking calculates a distance of an alternative to the extreme solutions and other alternatives. Several test cases are considered to study the performance of each ranking technique in both types of uncertainties.

A century of enzyme kinetic analysis, 1913 to 2013.

PubMed

Johnson, Kenneth A

2013-09-02

This review traces the history and logical progression of methods for quantitative analysis of enzyme kinetics from the 1913 Michaelis and Menten paper to the application of modern computational methods today. Following a brief review of methods for fitting steady state kinetic data, modern methods are highlighted for fitting full progress curve kinetics based upon numerical integration of rate equations, including a re-analysis of the original Michaelis-Menten full time course kinetic data. Finally, several illustrations of modern transient state kinetic methods of analysis are shown which enable the elucidation of reactions occurring at the active sites of enzymes in order to relate structure and function. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

75 FR 16202 - Notice of Issuance of Regulatory Guide

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-31

..., Revision 2, ``An Acceptable Model and Related Statistical Methods for the Analysis of Fuel Densification.... Introduction The U.S. Nuclear Regulatory Commission (NRC) is issuing a revision to an existing guide in the... nuclear power reactors. To meet these objectives, the guide describes statistical methods related to...

Investigation of dispersion-relation-preserving scheme and spectral analysis methods for acoustic waves

NASA Technical Reports Server (NTRS)

Vanel, Florence O.; Baysal, Oktay

1995-01-01

Important characteristics of the aeroacoustic wave propagation are mostly encoded in their dispersion relations. Hence, a computational aeroacoustic (CAA) algorithm, which reasonably preserves these relations, was investigated. It was derived using an optimization procedure to ensure, that the numerical derivatives preserved the wave number and angular frequency of the differential terms in the linearized, 2-D Euler equations. Then, simulations were performed to validate the scheme and a compatible set of discretized boundary conditions. The computational results were found to agree favorably with the exact solutions. The boundary conditions were transparent to the outgoing waves, except when the disturbance source was close to a boundary. The time-domain data generated by such CAA solutions were often intractable until their spectra was analyzed. Therefore, the relative merits of three different methods were included in the study. For simple, periodic waves, the periodogram method produced better estimates of the steep-sloped spectra than the Blackman-Tukey method. Also, for this problem, the Hanning window was more effective when used with the weighted-overlapped-segment-averaging and Blackman-Tukey methods gave better results than the periodogram method. Finally, it was demonstrated that the representation of time domain-data was significantly dependent on the particular spectral analysis method employed.

Identifying reprioritization response shift in a stroke caregiver population: a comparison of missing data methods.

PubMed

Sajobi, Tolulope T; Lix, Lisa M; Singh, Gurbakhshash; Lowerison, Mark; Engbers, Jordan; Mayo, Nancy E

2015-03-01

Response shift (RS) is an important phenomenon that influences the assessment of longitudinal changes in health-related quality of life (HRQOL) studies. Given that RS effects are often small, missing data due to attrition or item non-response can contribute to failure to detect RS effects. Since missing data are often encountered in longitudinal HRQOL data, effective strategies to deal with missing data are important to consider. This study aims to compare different imputation methods on the detection of reprioritization RS in the HRQOL of caregivers of stroke survivors. Data were from a Canadian multi-center longitudinal study of caregivers of stroke survivors over a one-year period. The Stroke Impact Scale physical function score at baseline, with a cutoff of 75, was used to measure patient stroke severity for the reprioritization RS analysis. Mean imputation, likelihood-based expectation-maximization imputation, and multiple imputation methods were compared in test procedures based on changes in relative importance weights to detect RS in SF-36 domains over a 6-month period. Monte Carlo simulation methods were used to compare the statistical powers of relative importance test procedures for detecting RS in incomplete longitudinal data under different missing data mechanisms and imputation methods. Of the 409 caregivers, 15.9 and 31.3 % of them had missing data at baseline and 6 months, respectively. There were no statistically significant changes in relative importance weights on any of the domains when complete-case analysis was adopted. But statistical significant changes were detected on physical functioning and/or vitality domains when mean imputation or EM imputation was adopted. There were also statistically significant changes in relative importance weights for physical functioning, mental health, and vitality domains when multiple imputation method was adopted. Our simulations revealed that relative importance test procedures were least powerful under complete-case analysis method and most powerful when a mean imputation or multiple imputation method was adopted for missing data, regardless of the missing data mechanism and proportion of missing data. Test procedures based on relative importance measures are sensitive to the type and amount of missing data and imputation method. Relative importance test procedures based on mean imputation and multiple imputation are recommended for detecting RS in incomplete data.

Multi-locus variable number tandem repeat analysis for Escherichia coli causing extraintestinal infections.

PubMed

Manges, Amee R; Tellis, Patricia A; Vincent, Caroline; Lifeso, Kimberley; Geneau, Geneviève; Reid-Smith, Richard J; Boerlin, Patrick

2009-11-01

Discriminatory genotyping methods for the analysis of Escherichia coli other than O157:H7 are necessary for public health-related activities. A new multi-locus variable number tandem repeat analysis protocol is presented; this method achieves an index of discrimination of 99.5% and is reproducible and valid when tested on a collection of 836 diverse E. coli.

Method and apparatus for ceramic analysis

DOEpatents

Jankowiak, Ryszard J.; Schilling, Chris; Small, Gerald J.; Tomasik, Piotr

2003-04-01

The present invention relates to a method and apparatus for ceramic analysis, in particular, a method for analyzing density, density gradients and/or microcracks, including an apparatus with optical instrumentation for analysis of density, density gradients and/or microcracks in ceramics. The method provides analyzing density of a ceramic comprising exciting a component on a surface/subsurface of the ceramic by exposing the material to excitation energy. The method may further include the step of obtaining a measurement of an emitted energy from the component. The method may additionally include comparing the measurement of the emitted energy from the component with a predetermined reference measurement so as to obtain a density for said ceramic.

Dangers in Using Analysis of Covariance Procedures.

ERIC Educational Resources Information Center

Campbell, Kathleen T.

Problems associated with the use of analysis of covariance (ANCOVA) as a statistical control technique are explained. Three problems relate to the use of "OVA" methods (analysis of variance, analysis of covariance, multivariate analysis of variance, and multivariate analysis of covariance) in general. These are: (1) the wasting of information when…

Analysis of cancer-related fatigue based on smart bracelet devices.

PubMed

Shen, Hong; Hou, Honglun; Tian, Wei; Wu, MingHui; Chen, Tianzhou; Zhong, Xian

2016-01-01

Fatigue is the most common symptom associated with cancer and its treatment, and profoundly affects all aspects of quality of life for cancer patients. It is very important to measure and manage cancer-related fatigue. Usually, the cancer-related fatigue scores, which estimate the degree of fatigue, are self-reported by cancer patients using standardized assessment tools. But most of the classical methods used for measurement of fatigue are subjective and inconvenient. In this study, we try to establish a new method to assess cancer-related fatigue objectively and accurately by using smart bracelet. All patients with metastatic pancreatic cancer wore smart bracelet for recording the physical activity including step count and sleep time before and after chemotherapy. Meantime, their psychological state was assessed by completing questionnaire tables as cancer-related fatigue scores. Step count record by smart bracelet reflecting the physical performance dramatically decreased in the initial days of chemotherapy and recovered in the next few days. Statistical analysis showed a strong and significant correlation between self-reported cancer-related fatigue and physical performance (P= 0.000, r=-0.929). Sleep time was also significantly correlated with fatigue (P= 0.000, r= 0.723). Multiple regression analysis showed that physical performance and sleep time are significant predictors of fatigue. Measuring activity using smart bracelets may be an appropriate method for quantitative and objective measurement of cancer-related fatigue by using smart bracelet devices.

Establishment of analysis method for methane detection by gas chromatography

NASA Astrophysics Data System (ADS)

Liu, Xinyuan; Yang, Jie; Ye, Tianyi; Han, Zeyu

2018-02-01

The study focused on the establishment of analysis method for methane determination by gas chromatography. Methane was detected by hydrogen flame ionization detector, and the quantitative relationship was determined by working curve of y=2041.2x+2187 with correlation coefficient of 0.9979. The relative standard deviation of 2.60-6.33% and the recovery rate of 96.36%∼105.89% were obtained during the parallel determination of standard gas. This method was not quite suitable for biogas content analysis because methane content in biogas would be over the measurement range in this method.

A Novel Bit-level Image Encryption Method Based on Chaotic Map and Dynamic Grouping

NASA Astrophysics Data System (ADS)

Zhang, Guo-Ji; Shen, Yan

2012-10-01

In this paper, a novel bit-level image encryption method based on dynamic grouping is proposed. In the proposed method, the plain-image is divided into several groups randomly, then permutation-diffusion process on bit level is carried out. The keystream generated by logistic map is related to the plain-image, which confuses the relationship between the plain-image and the cipher-image. The computer simulation results of statistical analysis, information entropy analysis and sensitivity analysis show that the proposed encryption method is secure and reliable enough to be used for communication application.

Uniform Sampling Table Method and its Applications II--Evaluating the Uniform Sampling by Experiment.

PubMed

Chen, Yibin; Chen, Jiaxi; Chen, Xuan; Wang, Min; Wang, Wei

2015-01-01

A new method of uniform sampling is evaluated in this paper. The items and indexes were adopted to evaluate the rationality of the uniform sampling. The evaluation items included convenience of operation, uniformity of sampling site distribution, and accuracy and precision of measured results. The evaluation indexes included operational complexity, occupation rate of sampling site in a row and column, relative accuracy of pill weight, and relative deviation of pill weight. They were obtained from three kinds of drugs with different shape and size by four kinds of sampling methods. Gray correlation analysis was adopted to make the comprehensive evaluation by comparing it with the standard method. The experimental results showed that the convenience of uniform sampling method was 1 (100%), odds ratio of occupation rate in a row and column was infinity, relative accuracy was 99.50-99.89%, reproducibility RSD was 0.45-0.89%, and weighted incidence degree exceeded the standard method. Hence, the uniform sampling method was easy to operate, and the selected samples were distributed uniformly. The experimental results demonstrated that the uniform sampling method has good accuracy and reproducibility, which can be put into use in drugs analysis.

Pulse analysis of acoustic emission signals

NASA Technical Reports Server (NTRS)

Houghton, J. R.; Packman, P. F.

1977-01-01

A method for the signature analysis of pulses in the frequency domain and the time domain is presented. Fourier spectrum, Fourier transfer function, shock spectrum and shock spectrum ratio were examined in the frequency domain analysis and pulse shape deconvolution was developed for use in the time domain analysis. Comparisons of the relative performance of each analysis technique are made for the characterization of acoustic emission pulses recorded by a measuring system. To demonstrate the relative sensitivity of each of the methods to small changes in the pulse shape, signatures of computer modeled systems with analytical pulses are presented. Optimization techniques are developed and used to indicate the best design parameter values for deconvolution of the pulse shape. Several experiments are presented that test the pulse signature analysis methods on different acoustic emission sources. These include acoustic emission associated with (a) crack propagation, (b) ball dropping on a plate, (c) spark discharge, and (d) defective and good ball bearings. Deconvolution of the first few micro-seconds of the pulse train is shown to be the region in which the significant signatures of the acoustic emission event are to be found.

Pulse analysis of acoustic emission signals

NASA Technical Reports Server (NTRS)

Houghton, J. R.; Packman, P. F.

1977-01-01

A method for the signature analysis of pulses in the frequency domain and the time domain is presented. Fourier spectrum, Fourier transfer function, shock spectrum and shock spectrum ratio were examined in the frequency domain analysis, and pulse shape deconvolution was developed for use in the time domain analysis. Comparisons of the relative performance of each analysis technique are made for the characterization of acoustic emission pulses recorded by a measuring system. To demonstrate the relative sensitivity of each of the methods to small changes in the pulse shape, signatures of computer modeled systems with analytical pulses are presented. Optimization techniques are developed and used to indicate the best design parameters values for deconvolution of the pulse shape. Several experiments are presented that test the pulse signature analysis methods on different acoustic emission sources. These include acoustic emissions associated with: (1) crack propagation, (2) ball dropping on a plate, (3) spark discharge and (4) defective and good ball bearings. Deconvolution of the first few micro-seconds of the pulse train are shown to be the region in which the significant signatures of the acoustic emission event are to be found.

Slope stability analysis using limit equilibrium method in nonlinear criterion.

PubMed

Lin, Hang; Zhong, Wenwen; Xiong, Wei; Tang, Wenyu

2014-01-01

In slope stability analysis, the limit equilibrium method is usually used to calculate the safety factor of slope based on Mohr-Coulomb criterion. However, Mohr-Coulomb criterion is restricted to the description of rock mass. To overcome its shortcomings, this paper combined Hoek-Brown criterion and limit equilibrium method and proposed an equation for calculating the safety factor of slope with limit equilibrium method in Hoek-Brown criterion through equivalent cohesive strength and the friction angle. Moreover, this paper investigates the impact of Hoek-Brown parameters on the safety factor of slope, which reveals that there is linear relation between equivalent cohesive strength and weakening factor D. However, there are nonlinear relations between equivalent cohesive strength and Geological Strength Index (GSI), the uniaxial compressive strength of intact rock σ ci , and the parameter of intact rock m i . There is nonlinear relation between the friction angle and all Hoek-Brown parameters. With the increase of D, the safety factor of slope F decreases linearly; with the increase of GSI, F increases nonlinearly; when σ ci is relatively small, the relation between F and σ ci is nonlinear, but when σ ci is relatively large, the relation is linear; with the increase of m i , F decreases first and then increases.

Slope Stability Analysis Using Limit Equilibrium Method in Nonlinear Criterion

PubMed Central

Lin, Hang; Zhong, Wenwen; Xiong, Wei; Tang, Wenyu

2014-01-01

In slope stability analysis, the limit equilibrium method is usually used to calculate the safety factor of slope based on Mohr-Coulomb criterion. However, Mohr-Coulomb criterion is restricted to the description of rock mass. To overcome its shortcomings, this paper combined Hoek-Brown criterion and limit equilibrium method and proposed an equation for calculating the safety factor of slope with limit equilibrium method in Hoek-Brown criterion through equivalent cohesive strength and the friction angle. Moreover, this paper investigates the impact of Hoek-Brown parameters on the safety factor of slope, which reveals that there is linear relation between equivalent cohesive strength and weakening factor D. However, there are nonlinear relations between equivalent cohesive strength and Geological Strength Index (GSI), the uniaxial compressive strength of intact rock σ ci, and the parameter of intact rock m i. There is nonlinear relation between the friction angle and all Hoek-Brown parameters. With the increase of D, the safety factor of slope F decreases linearly; with the increase of GSI, F increases nonlinearly; when σ ci is relatively small, the relation between F and σ ci is nonlinear, but when σ ci is relatively large, the relation is linear; with the increase of m i, F decreases first and then increases. PMID:25147838

A Collaborative Evaluation of LC-MS/MS Based Methods for BMAA Analysis: Soluble Bound BMAA Found to Be an Important Fraction

PubMed Central

Faassen, Elisabeth J.; Antoniou, Maria G.; Beekman-Lukassen, Wendy; Blahova, Lucie; Chernova, Ekaterina; Christophoridis, Christophoros; Combes, Audrey; Edwards, Christine; Fastner, Jutta; Harmsen, Joop; Hiskia, Anastasia; Ilag, Leopold L.; Kaloudis, Triantafyllos; Lopicic, Srdjan; Lürling, Miquel; Mazur-Marzec, Hanna; Meriluoto, Jussi; Porojan, Cristina; Viner-Mozzini, Yehudit; Zguna, Nadezda

2016-01-01

Exposure to β-N-methylamino-l-alanine (BMAA) might be linked to the incidence of amyotrophic lateral sclerosis, Alzheimer’s disease and Parkinson’s disease. Analytical chemistry plays a crucial role in determining human BMAA exposure and the associated health risk, but the performance of various analytical methods currently employed is rarely compared. A CYANOCOST initiated workshop was organized aimed at training scientists in BMAA analysis, creating mutual understanding and paving the way towards interlaboratory comparison exercises. During this workshop, we tested different methods (extraction followed by derivatization and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) analysis, or directly followed by LC-MS/MS analysis) for trueness and intermediate precision. We adapted three workup methods for the underivatized analysis of animal, brain and cyanobacterial samples. Based on recovery of the internal standard D3BMAA, the underivatized methods were accurate (mean recovery 80%) and precise (mean relative standard deviation 10%), except for the cyanobacterium Leptolyngbya. However, total BMAA concentrations in the positive controls (cycad seeds) showed higher variation (relative standard deviation 21%–32%), implying that D3BMAA was not a good indicator for the release of BMAA from bound forms. Significant losses occurred during workup for the derivatized method, resulting in low recovery (<10%). Most BMAA was found in a trichloroacetic acid soluble, bound form and we recommend including this fraction during analysis. PMID:26938542

Data accuracy assessment using enterprise architecture

NASA Astrophysics Data System (ADS)

Närman, Per; Holm, Hannes; Johnson, Pontus; König, Johan; Chenine, Moustafa; Ekstedt, Mathias

2011-02-01

Errors in business processes result in poor data accuracy. This article proposes an architecture analysis method which utilises ArchiMate and the Probabilistic Relational Model formalism to model and analyse data accuracy. Since the resources available for architecture analysis are usually quite scarce, the method advocates interviews as the primary data collection technique. A case study demonstrates that the method yields correct data accuracy estimates and is more resource-efficient than a competing sampling-based data accuracy estimation method.

A Heterogeneous Network Based Method for Identifying GBM-Related Genes by Integrating Multi-Dimensional Data.

PubMed

Chen Peng; Ao Li

2017-01-01

The emergence of multi-dimensional data offers opportunities for more comprehensive analysis of the molecular characteristics of human diseases and therefore improving diagnosis, treatment, and prevention. In this study, we proposed a heterogeneous network based method by integrating multi-dimensional data (HNMD) to identify GBM-related genes. The novelty of the method lies in that the multi-dimensional data of GBM from TCGA dataset that provide comprehensive information of genes, are combined with protein-protein interactions to construct a weighted heterogeneous network, which reflects both the general and disease-specific relationships between genes. In addition, a propagation algorithm with resistance is introduced to precisely score and rank GBM-related genes. The results of comprehensive performance evaluation show that the proposed method significantly outperforms the network based methods with single-dimensional data and other existing approaches. Subsequent analysis of the top ranked genes suggests they may be functionally implicated in GBM, which further corroborates the superiority of the proposed method. The source code and the results of HNMD can be downloaded from the following URL: http://bioinformatics.ustc.edu.cn/hnmd/ .

Analysis of the nature and cause of turbulence upset using airline flight records

NASA Technical Reports Server (NTRS)

Parks, E. K.; Bach, R. E., Jr.; Wingrove, R. C.

1982-01-01

The development and application of methods for determining aircraft motions and related winds, using data normally recorded during airline flight operations, are described. The methods are being developed, in cooperation with the National Transportation Safety Board, to aid in the analysis and understanding of circumstances associated with aircraft accidents or incidents. Data from a recent DC-10 encounter with severe, high-altitude turbulence are used to illustrate the methods. The analysis of this encounter shows the turbulence to be a series of equally spaced horizontal swirls known as 'cat's eyes' vortices. The use of flight-data analysis methods to identify this type of turbulence phenomenon is presented for the first time.

Methods of analyzing crude oil

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

Cooks, Robert Graham; Jjunju, Fred Paul Mark; Li, Anyin

The invention generally relates to methods of analyzing crude oil. In certain embodiments, methods of the invention involve obtaining a crude oil sample, and subjecting the crude oil sample to mass spectrometry analysis. In certain embodiments, the method is performed without any sample pre-purification steps.

A standards-based method for compositional analysis by energy dispersive X-ray spectrometry using multivariate statistical analysis: application to multicomponent alloys.

PubMed

Rathi, Monika; Ahrenkiel, S P; Carapella, J J; Wanlass, M W

2013-02-01

Given an unknown multicomponent alloy, and a set of standard compounds or alloys of known composition, can one improve upon popular standards-based methods for energy dispersive X-ray (EDX) spectrometry to quantify the elemental composition of the unknown specimen? A method is presented here for determining elemental composition of alloys using transmission electron microscopy-based EDX with appropriate standards. The method begins with a discrete set of related reference standards of known composition, applies multivariate statistical analysis to those spectra, and evaluates the compositions with a linear matrix algebra method to relate the spectra to elemental composition. By using associated standards, only limited assumptions about the physical origins of the EDX spectra are needed. Spectral absorption corrections can be performed by providing an estimate of the foil thickness of one or more reference standards. The technique was applied to III-V multicomponent alloy thin films: composition and foil thickness were determined for various III-V alloys. The results were then validated by comparing with X-ray diffraction and photoluminescence analysis, demonstrating accuracy of approximately 1% in atomic fraction.

Regional analysis of annual maximum rainfall using TL-moments method

NASA Astrophysics Data System (ADS)

Shabri, Ani Bin; Daud, Zalina Mohd; Ariff, Noratiqah Mohd

2011-06-01

Information related to distributions of rainfall amounts are of great importance for designs of water-related structures. One of the concerns of hydrologists and engineers is the probability distribution for modeling of regional data. In this study, a novel approach to regional frequency analysis using L-moments is revisited. Subsequently, an alternative regional frequency analysis using the TL-moments method is employed. The results from both methods were then compared. The analysis was based on daily annual maximum rainfall data from 40 stations in Selangor Malaysia. TL-moments for the generalized extreme value (GEV) and generalized logistic (GLO) distributions were derived and used to develop the regional frequency analysis procedure. TL-moment ratio diagram and Z-test were employed in determining the best-fit distribution. Comparison between the two approaches showed that the L-moments and TL-moments produced equivalent results. GLO and GEV distributions were identified as the most suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation was used for performance evaluation, and it showed that the method of TL-moments was more efficient for lower quantile estimation compared with the L-moments.

[A new method of processing quantitative PCR data].

PubMed

Ke, Bing-Shen; Li, Guang-Yun; Chen, Shi-Min; Huang, Xiang-Yan; Chen, Ying-Jian; Xu, Jun

2003-05-01

Today standard PCR can't satisfy the need of biotechnique development and clinical research any more. After numerous dynamic research, PE company found there is a linear relation between initial template number and cycling time when the accumulating fluorescent product is detectable.Therefore,they developed a quantitative PCR technique to be used in PE7700 and PE5700. But the error of this technique is too great to satisfy the need of biotechnique development and clinical research. A better quantitative PCR technique is needed. The mathematical model submitted here is combined with the achievement of relative science,and based on the PCR principle and careful analysis of molecular relationship of main members in PCR reaction system. This model describes the function relation between product quantity or fluorescence intensity and initial template number and other reaction conditions, and can reflect the accumulating rule of PCR product molecule accurately. Accurate quantitative PCR analysis can be made use this function relation. Accumulated PCR product quantity can be obtained from initial template number. Using this model to do quantitative PCR analysis,result error is only related to the accuracy of fluorescence intensity or the instrument used. For an example, when the fluorescence intensity is accurate to 6 digits and the template size is between 100 to 1,000,000, the quantitative result accuracy will be more than 99%. The difference of result error is distinct using same condition,same instrument but different analysis method. Moreover,if the PCR quantitative analysis system is used to process data, it will get result 80 times of accuracy than using CT method.

A Review of Content and Task Analysis Methodology. Technical Report No. 2.

ERIC Educational Resources Information Center

Gibbons, Andrew S.

A review of the literature related to methods for analyzing content or tasks prior to instructional development is presented. The review classifies methods according to a two-dimensional matrix. The first dimension differentiates phases of analysis, each dealing with content and tasks of a particular scope and each generating certain…

A Simple Plasma Retinol Isotope Ratio Method for Estimating β-Carotene Relative Bioefficacy in Humans: Validation with the Use of Model-Based Compartmental Analysis.

PubMed

Ford, Jennifer Lynn; Green, Joanne Balmer; Lietz, Georg; Oxley, Anthony; Green, Michael H

2017-09-01

Background: Provitamin A carotenoids are an important source of dietary vitamin A for many populations. Thus, accurate and simple methods for estimating carotenoid bioefficacy are needed to evaluate the vitamin A value of test solutions and plant sources. β-Carotene bioefficacy is often estimated from the ratio of the areas under plasma isotope response curves after subjects ingest labeled β-carotene and a labeled retinyl acetate reference dose [isotope reference method (IRM)], but to our knowledge, the method has not yet been evaluated for accuracy. Objectives: Our objectives were to develop and test a physiologically based compartmental model that includes both absorptive and postabsorptive β-carotene bioconversion and to use the model to evaluate the accuracy of the IRM and a simple plasma retinol isotope ratio [(RIR), labeled β-carotene-derived retinol/labeled reference-dose-derived retinol in one plasma sample] for estimating relative bioefficacy. Methods: We used model-based compartmental analysis (Simulation, Analysis and Modeling software) to develop and apply a model that provided known values for β-carotene bioefficacy. Theoretical data for 10 subjects were generated by the model and used to determine bioefficacy by RIR and IRM; predictions were compared with known values. We also applied RIR and IRM to previously published data. Results: Plasma RIR accurately predicted β-carotene relative bioefficacy at 14 d or later. IRM also accurately predicted bioefficacy by 14 d, except that, when there was substantial postabsorptive bioconversion, IRM underestimated bioefficacy. Based on our model, 1-d predictions of relative bioefficacy include absorptive plus a portion of early postabsorptive conversion. Conclusion: The plasma RIR is a simple tracer method that accurately predicts β-carotene relative bioefficacy based on analysis of one blood sample obtained at ≥14 d after co-ingestion of labeled β-carotene and retinyl acetate. The method also provides information about the contributions of absorptive and postabsorptive conversion to total bioefficacy if an additional sample is taken at 1 d. © 2017 American Society for Nutrition.

Relative Contributions of Three Descriptive Methods: Implications for Behavioral Assessment

ERIC Educational Resources Information Center

Pence, Sacha T.; Roscoe, Eileen M.; Bourret, Jason C.; Ahearn, William H.

2009-01-01

This study compared the outcomes of three descriptive analysis methods--the ABC method, the conditional probability method, and the conditional and background probability method--to each other and to the results obtained from functional analyses. Six individuals who had been diagnosed with developmental delays and exhibited problem behavior…

Surfing for suicide methods and help: content analysis of websites retrieved with search engines in Austria and the United States.

PubMed

Till, Benedikt; Niederkrotenthaler, Thomas

2014-08-01

The Internet provides a variety of resources for individuals searching for suicide-related information. Structured content-analytic approaches to assess intercultural differences in web contents retrieved with method-related and help-related searches are scarce. We used the 2 most popular search engines (Google and Yahoo/Bing) to retrieve US-American and Austrian search results for the term suicide, method-related search terms (e.g., suicide methods, how to kill yourself, painless suicide, how to hang yourself), and help-related terms (e.g., suicidal thoughts, suicide help) on February 11, 2013. In total, 396 websites retrieved with US search engines and 335 websites from Austrian searches were analyzed with content analysis on the basis of current media guidelines for suicide reporting. We assessed the quality of websites and compared findings across search terms and between the United States and Austria. In both countries, protective outweighed harmful website characteristics by approximately 2:1. Websites retrieved with method-related search terms (e.g., how to hang yourself) contained more harmful (United States: P < .001, Austria: P < .05) and fewer protective characteristics (United States: P < .001, Austria: P < .001) compared to the term suicide. Help-related search terms (e.g., suicidal thoughts) yielded more websites with protective characteristics (United States: P = .07, Austria: P < .01). Websites retrieved with U.S. search engines generally had more protective characteristics (P < .001) than searches with Austrian search engines. Resources with harmful characteristics were better ranked than those with protective characteristics (United States: P < .01, Austria: P < .05). The quality of suicide-related websites obtained depends on the search terms used. Preventive efforts to improve the ranking of preventive web content, particularly regarding method-related search terms, seem necessary. © Copyright 2014 Physicians Postgraduate Press, Inc.

Data mining and computationally intensive methods: summary of Group 7 contributions to Genetic Analysis Workshop 13.

PubMed

Costello, Tracy J; Falk, Catherine T; Ye, Kenny Q

2003-01-01

The Framingham Heart Study data, as well as a related simulated data set, were generously provided to the participants of the Genetic Analysis Workshop 13 in order that newly developed and emerging statistical methodologies could be tested on that well-characterized data set. The impetus driving the development of novel methods is to elucidate the contributions of genes, environment, and interactions between and among them, as well as to allow comparison between and validation of methods. The seven papers that comprise this group used data-mining methodologies (tree-based methods, neural networks, discriminant analysis, and Bayesian variable selection) in an attempt to identify the underlying genetics of cardiovascular disease and related traits in the presence of environmental and genetic covariates. Data-mining strategies are gaining popularity because they are extremely flexible and may have greater efficiency and potential in identifying the factors involved in complex disorders. While the methods grouped together here constitute a diverse collection, some papers asked similar questions with very different methods, while others used the same underlying methodology to ask very different questions. This paper briefly describes the data-mining methodologies applied to the Genetic Analysis Workshop 13 data sets and the results of those investigations. Copyright 2003 Wiley-Liss, Inc.

A method of searching for related literature on protein structure analysis by considering a user's intention

PubMed Central

2015-01-01

Background In recent years, with advances in techniques for protein structure analysis, the knowledge about protein structure and function has been published in a vast number of articles. A method to search for specific publications from such a large pool of articles is needed. In this paper, we propose a method to search for related articles on protein structure analysis by using an article itself as a query. Results Each article is represented as a set of concepts in the proposed method. Then, by using similarities among concepts formulated from databases such as Gene Ontology, similarities between articles are evaluated. In this framework, the desired search results vary depending on the user's search intention because a variety of information is included in a single article. Therefore, the proposed method provides not only one input article (primary article) but also additional articles related to it as an input query to determine the search intention of the user, based on the relationship between two query articles. In other words, based on the concepts contained in the input article and additional articles, we actualize a relevant literature search that considers user intention by varying the degree of attention given to each concept and modifying the concept hierarchy graph. Conclusions We performed an experiment to retrieve relevant papers from articles on protein structure analysis registered in the Protein Data Bank by using three query datasets. The experimental results yielded search results with better accuracy than when user intention was not considered, confirming the effectiveness of the proposed method. PMID:25952498

EHR Improvement Using Incident Reports.

PubMed

Teame, Tesfay; Stålhane, Tor; Nytrø, Øystein

2017-01-01

This paper discusses reactive improvement of clinical software using methods for incident analysis. We used the "Five Whys" method because we had only descriptive data and depended on a domain expert for the analysis. The analysis showed that there are two major root causes for EHR software failure, and that they are related to human and organizational errors. A main identified improvement is allocating more resources to system maintenance and user training.

Experiences in Eliciting Security Requirements

DTIC Science & Technology

2006-12-01

FODA ) FODA is a domain analysis and engineer- ing method that focuses on developing reusable assets [9]. By examining related software systems and...describe a trade-off analysis that we used to select a suitable requirements elici- tation method and present results detailed from a case study of one...disaster planning, and how to improve Medicare. Eventually, technology-oriented problems may emerge from these soft problems, but much more analysis is

Piecewise multivariate modelling of sequential metabolic profiling data.

PubMed

Rantalainen, Mattias; Cloarec, Olivier; Ebbels, Timothy M D; Lundstedt, Torbjörn; Nicholson, Jeremy K; Holmes, Elaine; Trygg, Johan

2008-02-19

Modelling the time-related behaviour of biological systems is essential for understanding their dynamic responses to perturbations. In metabolic profiling studies, the sampling rate and number of sampling points are often restricted due to experimental and biological constraints. A supervised multivariate modelling approach with the objective to model the time-related variation in the data for short and sparsely sampled time-series is described. A set of piecewise Orthogonal Projections to Latent Structures (OPLS) models are estimated, describing changes between successive time points. The individual OPLS models are linear, but the piecewise combination of several models accommodates modelling and prediction of changes which are non-linear with respect to the time course. We demonstrate the method on both simulated and metabolic profiling data, illustrating how time related changes are successfully modelled and predicted. The proposed method is effective for modelling and prediction of short and multivariate time series data. A key advantage of the method is model transparency, allowing easy interpretation of time-related variation in the data. The method provides a competitive complement to commonly applied multivariate methods such as OPLS and Principal Component Analysis (PCA) for modelling and analysis of short time-series data.

Profiling and relative quantification of phosphatidylethanolamine based on acetone stable isotope derivatization.

PubMed

Wang, Xiang; Wei, Fang; Xu, Ji-Qu; Lv, Xin; Dong, Xu-Yan; Han, Xianlin; Quek, Siew-Young; Huang, Feng-Hong; Chen, Hong

2016-01-01

Phosphatidylethanolamine (PE) is considered to be one of the pivotal lipids for normal cellular function as well as disease initiation and progression. In this study, a simple, efficient, reliable, and inexpensive method for the qualitative analysis and relative quantification of PE, based on acetone stable isotope derivatization combined with double neutral loss scan-shotgun electrospray ionization tandem-quadrupole mass spectrometry analysis (ASID-DNLS-Shotgun ESI-MS/MS), was developed. The ASID method led to alkylation of the primary amino groups of PE with an isopropyl moiety. The use of acetone (d0-acetone) and deuterium-labeled acetone (d6-acetone) introduced a 6 Da mass shift that was ideally suited for relative quantitative analysis, and enhanced sensitivity for mass analysis. The DNLS model was introduced to simultaneously analyze the differential derivatized PEs by shotgun ESI-MS/MS with high selectivity and accuracy. The reaction specificity, labeling efficiency, and linearity of the ASID method were thoroughly evaluated in this study. Its excellent applicability was validated by qualitative and relative quantitative analysis of PE species presented in liver samples from rats fed different diets. Using the ASID-DNLS-Shotgun ESI-MS/MS method, 45 PE species from rat livers have been identified and quantified in an efficient manner. The level of total PEs tended to decrease in the livers of rats on high fat diets compared with controls. The levels of PE 32:1, 34:3, 34:2, 36:3, 36:2, 42:10, plasmalogen PE 36:1 and lyso PE 22:6 were significantly reduced, while levels of PE 36:1 and lyso PE 16:0 increased. Copyright © 2015 Elsevier B.V. All rights reserved.

Correlating the EMC analysis and testing methods for space systems in MIL-STD-1541A

NASA Technical Reports Server (NTRS)

Perez, Reinaldo J.

1990-01-01

A study was conducted to improve the correlation between the electromagnetic compatibility (EMC) analysis models stated in MIL-STD-1541A and the suggested testing methods used for space systems. The test and analysis methods outlined in MIL-STD-1541A are described, and a comparative assessment of testing and analysis techniques as they relate to several EMC areas is presented. Suggestions on present analysis and test methods are introduced to harmonize and bring the analysis and testing tools in MIL-STD-1541A into closer agreement. It is suggested that test procedures in MIL-STD-1541A must be improved by providing alternatives to the present use of shielded enclosures as the primary site for such tests. In addition, the alternate use of anechoic chambers and open field test sites must be considered.

Analysis of iodinated haloacetic acids in drinking water by reversed-phase liquid chromatography/electrospray ionization/tandem mass spectrometry with large volume direct aqueous injection.

PubMed

Li, Yongtao; Whitaker, Joshua S; McCarty, Christina L

2012-07-06

A large volume direct aqueous injection method was developed for the analysis of iodinated haloacetic acids in drinking water by using reversed-phase liquid chromatography/electrospray ionization/tandem mass spectrometry in the negative ion mode. Both the external and internal standard calibration methods were studied for the analysis of monoiodoacetic acid, chloroiodoacetic acid, bromoiodoacetic acid, and diiodoacetic acid in drinking water. The use of a divert valve technique for the mobile phase solvent delay, along with isotopically labeled analogs used as internal standards, effectively reduced and compensated for the ionization suppression typically caused by coexisting common inorganic anions. Under the optimized method conditions, the mean absolute and relative recoveries resulting from the replicate fortified deionized water and chlorinated drinking water analyses were 83-107% with a relative standard deviation of 0.7-11.7% and 84-111% with a relative standard deviation of 0.8-12.1%, respectively. The method detection limits resulting from the external and internal standard calibrations, based on seven fortified deionized water replicates, were 0.7-2.3 ng/L and 0.5-1.9 ng/L, respectively. Copyright © 2012 Elsevier B.V. All rights reserved.

Comparison of data analysis strategies for intent-to-treat analysis in pre-test-post-test designs with substantial dropout rates.

PubMed

Salim, Agus; Mackinnon, Andrew; Christensen, Helen; Griffiths, Kathleen

2008-09-30

The pre-test-post-test design (PPD) is predominant in trials of psychotherapeutic treatments. Missing data due to withdrawals present an even bigger challenge in assessing treatment effectiveness under the PPD than under designs with more observations since dropout implies an absence of information about response to treatment. When confronted with missing data, often it is reasonable to assume that the mechanism underlying missingness is related to observed but not to unobserved outcomes (missing at random, MAR). Previous simulation and theoretical studies have shown that, under MAR, modern techniques such as maximum-likelihood (ML) based methods and multiple imputation (MI) can be used to produce unbiased estimates of treatment effects. In practice, however, ad hoc methods such as last observation carried forward (LOCF) imputation and complete-case (CC) analysis continue to be used. In order to better understand the behaviour of these methods in the PPD, we compare the performance of traditional approaches (LOCF, CC) and theoretically sound techniques (MI, ML), under various MAR mechanisms. We show that the LOCF method is seriously biased and conclude that its use should be abandoned. Complete-case analysis produces unbiased estimates only when the dropout mechanism does not depend on pre-test values even when dropout is related to fixed covariates including treatment group (covariate-dependent: CD). However, CC analysis is generally biased under MAR. The magnitude of the bias is largest when the correlation of post- and pre-test is relatively low.

Contingency Space Analysis: An Alternative Method for Identifying Contingent Relations from Observational Data

PubMed Central

Martens, Brian K; DiGennaro, Florence D; Reed, Derek D; Szczech, Frances M; Rosenthal, Blair D

2008-01-01

Descriptive assessment methods have been used in applied settings to identify consequences for problem behavior, thereby aiding in the design of effective treatment programs. Consensus has not been reached, however, regarding the types of data or analytic strategies that are most useful for describing behavior–consequence relations. One promising approach involves the analysis of conditional probabilities from sequential recordings of behavior and events that follow its occurrence. In this paper we review several strategies for identifying contingent relations from conditional probabilities, and propose an alternative strategy known as a contingency space analysis (CSA). Step-by-step procedures for conducting and interpreting a CSA using sample data are presented, followed by discussion of the potential use of a CSA for conducting descriptive assessments, informing intervention design, and evaluating changes in reinforcement contingencies following treatment. PMID:18468280

Development of an SPE/CE method for analyzing HAAs

USGS Publications Warehouse

Zhang, L.; Capel, P.D.; Hozalski, R.M.

2007-01-01

The haloacetic acid (HAA) analysis methods approved by the US Environmental Protection Agency involve extraction and derivatization of HAAs (typically to their methyl ester form) and analysis by gas chromatography (GC) with electron capture detection (ECD). Concerns associated with these methods include the time and effort of the derivatization process, use of potentially hazardous chemicals or conditions during methylation, poor recoveries because of low extraction efficiencies for some HAAs or matrix effects from sulfate, and loss of tribromoacetic acid because of decarboxylation. The HAA analysis method introduced here uses solid-phase extraction (SPE) followed by capillary electrophoresis (CE) analysis. The method is accurate, reproducible, sensitive, relatively safe, and easy to perform, and avoids the use of large amounts of solvent for liquid-liquid extraction and the potential hazards and hassles of derivatization. The cost of analyzing HAAs using this method should be lower than the currently approved methods, and utilities with a GC/ECD can perform the analysis in-house.

Analysis of the discriminative methods for diagnosis of benign and malignant solitary pulmonary nodules based on serum markers.

PubMed

Wang, Wanping; Liu, Mingyue; Wang, Jing; Tian, Rui; Dong, Junqiang; Liu, Qi; Zhao, Xianping; Wang, Yuanfang

2014-01-01

Screening indexes of tumor serum markers for benign and malignant solitary pulmonary nodules (SPNs) were analyzed to find the optimum method for diagnosis. Enzyme-linked immunosorbent assays, an automatic immune analyzer and radioimmunoassay methods were used to examine the levels of 8 serum markers in 164 SPN patients, and the sensitivity for differential diagnosis of malignant or benign SPN was compared for detection using a single plasma marker or a combination of markers. The results for serological indicators that closely relate to benign and malignant SPNs were screened using the Fisher discriminant analysis and a non-conditional logistic regression analysis method, respectively. The results were then verified by the k-means clustering analysis method. The sensitivity when using a combination of serum markers to detect SPN was higher than that using a single marker. By Fisher discriminant analysis, cytokeratin 19 fragments (CYFRA21-1), carbohydrate antigen 125 (CA125), squamous cell carcinoma antigen (SCC) and breast cancer antigen (CA153), which relate to the benign and malignant SPNs, were screened. Through non-conditional logistic regression analysis, CYFRA21-1, SCC and CA153 were obtained. Using the k-means clustering analysis, the cophenetic correlation coefficient (0.940) obtained by the Fisher discriminant analysis was higher than that obtained with logistic regression analysis (0.875). This study indicated that the Fisher discriminant analysis functioned better in screening out serum markers to recognize the benign and malignant SPN. The combined detection of CYFRA21-1, CA125, SCC and CA153 is an effective way to distinguish benign and malignant SPN, and will find an important clinical application in the early diagnosis of SPN. © 2014 S. Karger GmbH, Freiburg.

A Descriptive Analysis of Health-Related Infomercials: Implications for Health Education and Media Literacy

ERIC Educational Resources Information Center

Hill, Susan C.; Lindsay, Gordon B.; Thomsen, Steve R.; Olsen, Astrid M.

2003-01-01

Media literacy education helps individuals become discriminating consumers of health information. Informed consumers are less likely to purchase useless health products if informed of misleading and deceptive advertising methods. The purpose of this study was to conduct a content analysis of health-related TV infomercials. An instrument…

Relations among Children's Use of Dialect and Literacy Skills: A Meta-Analysis

ERIC Educational Resources Information Center

Gatlin, Brandy; Wanzek, Jeanne

2015-01-01

Purpose: The current meta-analysis examines recent empirical research studies that have investigated relations among dialect use and the development and achievement of reading, spelling, and writing skills. Method: Studies published between 1998 and 2014 were selected if they: (a) included participants who were in Grades K-6 and were typically…

Determining Predictor Importance in Hierarchical Linear Models Using Dominance Analysis

ERIC Educational Resources Information Center

Luo, Wen; Azen, Razia

2013-01-01

Dominance analysis (DA) is a method used to evaluate the relative importance of predictors that was originally proposed for linear regression models. This article proposes an extension of DA that allows researchers to determine the relative importance of predictors in hierarchical linear models (HLM). Commonly used measures of model adequacy in…

Methods, apparatuses, and computer-readable media for projectional morphological analysis of N-dimensional signals

DOEpatents

Glazoff, Michael V.; Gering, Kevin L.; Garnier, John E.; Rashkeev, Sergey N.; Pyt'ev, Yuri Petrovich

2016-05-17

Embodiments discussed herein in the form of methods, systems, and computer-readable media deal with the application of advanced "projectional" morphological algorithms for solving a broad range of problems. In a method of performing projectional morphological analysis, an N-dimensional input signal is supplied. At least one N-dimensional form indicative of at least one feature in the N-dimensional input signal is identified. The N-dimensional input signal is filtered relative to the at least one N-dimensional form and an N-dimensional output signal is generated indicating results of the filtering at least as differences in the N-dimensional input signal relative to the at least one N-dimensional form.

Comparison of Chemical Constituents in Scrophulariae Radix Processed by Different Methods based on UFLC-MS Combined with Multivariate Statistical Analysis.

PubMed

Wang, Shengnan; Hua, Yujiao; Zou, Lisi; Liu, Xunhong; Yan, Ying; Zhao, Hui; Luo, Yiyuan; Liu, Juanxiu

2018-02-01

Scrophulariae Radix is one of the most popular traditional Chinese medicines (TCMs). Primary processing of Scrophulariae Radix is an important link which closely related to the quality of products in this TCM. The aim of this study is to explore the influence of different processing methods on chemical constituents in Scrophulariae Radix. The difference of chemical constituents in Scrophulariae Radix processed by different methods was analyzed by using ultra fast liquid chromatography-triple quadrupole-time of flight mass spectrometry coupled with principal component analysis and orthogonal partial least squares discriminant analysis. Furthermore, the contents of 12 index differential constituents in Scrophulariae Radix processed by different methods were simultaneously determined by using ultra fast liquid chromatography coupled with triple quadrupole-linear ion trap mass spectrometry. Gray relational analysis was performed to evaluate the different processed samples according to the contents of 12 constituents. All of the results demonstrated that the quality of Scrophulariae Radix processed by "sweating" method was better. This study will provide the basic information for revealing the change law of chemical constituents in Scrophulariae Radix processed by different methods and facilitating selection of the suitable processing method of this TCM. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Expert system for web based collaborative CAE

NASA Astrophysics Data System (ADS)

Hou, Liang; Lin, Zusheng

2006-11-01

An expert system for web based collaborative CAE was developed based on knowledge engineering, relational database and commercial FEA (Finite element analysis) software. The architecture of the system was illustrated. In this system, the experts' experiences, theories and typical examples and other related knowledge, which will be used in the stage of pre-process in FEA, were categorized into analysis process and object knowledge. Then, the integrated knowledge model based on object-oriented method and rule based method was described. The integrated reasoning process based on CBR (case based reasoning) and rule based reasoning was presented. Finally, the analysis process of this expert system in web based CAE application was illustrated, and an analysis example of a machine tool's column was illustrated to prove the validity of the system.

Methods for extracting social network data from chatroom logs

NASA Astrophysics Data System (ADS)

Osesina, O. Isaac; McIntire, John P.; Havig, Paul R.; Geiselman, Eric E.; Bartley, Cecilia; Tudoreanu, M. Eduard

2012-06-01

Identifying social network (SN) links within computer-mediated communication platforms without explicit relations among users poses challenges to researchers. Our research aims to extract SN links in internet chat with multiple users engaging in synchronous overlapping conversations all displayed in a single stream. We approached this problem using three methods which build on previous research. Response-time analysis builds on temporal proximity of chat messages; word context usage builds on keywords analysis and direct addressing which infers links by identifying the intended message recipient from the screen name (nickname) referenced in the message [1]. Our analysis of word usage within the chat stream also provides contexts for the extracted SN links. To test the capability of our methods, we used publicly available data from Internet Relay Chat (IRC), a real-time computer-mediated communication (CMC) tool used by millions of people around the world. The extraction performances of individual methods and their hybrids were assessed relative to a ground truth (determined a priori via manual scoring).

Prediction of sweetness and amino acid content in soybean crops from hyperspectral imagery

NASA Astrophysics Data System (ADS)

Monteiro, Sildomar Takahashi; Minekawa, Yohei; Kosugi, Yukio; Akazawa, Tsuneya; Oda, Kunio

Hyperspectral image data provides a powerful tool for non-destructive crop analysis. This paper investigates a hyperspectral image data-processing method to predict the sweetness and amino acid content of soybean crops. Regression models based on artificial neural networks were developed in order to calculate the level of sucrose, glucose, fructose, and nitrogen concentrations, which can be related to the sweetness and amino acid content of vegetables. A performance analysis was conducted comparing regression models obtained using different preprocessing methods, namely, raw reflectance, second derivative, and principal components analysis. This method is demonstrated using high-resolution hyperspectral data of wavelengths ranging from the visible to the near infrared acquired from an experimental field of green vegetable soybeans. The best predictions were achieved using a nonlinear regression model of the second derivative transformed dataset. Glucose could be predicted with greater accuracy, followed by sucrose, fructose and nitrogen. The proposed method provides the possibility to provide relatively accurate maps predicting the chemical content of soybean crop fields.

Regression Analysis and Calibration Recommendations for the Characterization of Balance Temperature Effects

NASA Technical Reports Server (NTRS)

Ulbrich, N.; Volden, T.

2018-01-01

Analysis and use of temperature-dependent wind tunnel strain-gage balance calibration data are discussed in the paper. First, three different methods are presented and compared that may be used to process temperature-dependent strain-gage balance data. The first method uses an extended set of independent variables in order to process the data and predict balance loads. The second method applies an extended load iteration equation during the analysis of balance calibration data. The third method uses temperature-dependent sensitivities for the data analysis. Physical interpretations of the most important temperature-dependent regression model terms are provided that relate temperature compensation imperfections and the temperature-dependent nature of the gage factor to sets of regression model terms. Finally, balance calibration recommendations are listed so that temperature-dependent calibration data can be obtained and successfully processed using the reviewed analysis methods.

Risk-Stratified Imputation in Survival Analysis

PubMed Central

Kennedy, Richard E.; Adragni, Kofi P.; Tiwari, Hemant K.; Voeks, Jenifer H.; Brott, Thomas G.; Howard, George

2013-01-01

Background Censoring that is dependent on covariates associated with survival can arise in randomized trials due to changes in recruitment and eligibility criteria to minimize withdrawals, potentially leading to biased treatment effect estimates. Imputation approaches have been proposed to address censoring in survival analysis; and while these approaches may provide unbiased estimates of treatment effects, imputation of a large number of outcomes may over- or underestimate the associated variance based on the imputation pool selected. Purpose We propose an improved method, risk-stratified imputation, as an alternative to address withdrawal related to the risk of events in the context of time-to-event analyses. Methods Our algorithm performs imputation from a pool of replacement subjects with similar values of both treatment and covariate(s) of interest, that is, from a risk-stratified sample. This stratification prior to imputation addresses the requirement of time-to-event analysis that censored observations are representative of all other observations in the risk group with similar exposure variables. We compared our risk-stratified imputation to case deletion and bootstrap imputation in a simulated dataset in which the covariate of interest (study withdrawal) was related to treatment. A motivating example from a recent clinical trial is also presented to demonstrate the utility of our method. Results In our simulations, risk-stratified imputation gives estimates of treatment effect comparable to bootstrap and auxiliary variable imputation while avoiding inaccuracies of the latter two in estimating the associated variance. Similar results were obtained in analysis of clinical trial data. Limitations Risk-stratified imputation has little advantage over other imputation methods when covariates of interest are not related to treatment, although its performance is superior when covariates are related to treatment. Risk-stratified imputation is intended for categorical covariates, and may be sensitive to the width of the matching window if continuous covariates are used. Conclusions The use of the risk-stratified imputation should facilitate the analysis of many clinical trials, in which one group has a higher withdrawal rate that is related to treatment. PMID:23818434

Application of multi response optimization with grey relational analysis and fuzzy logic method

NASA Astrophysics Data System (ADS)

Winarni, Sri; Wahyu Indratno, Sapto

2018-01-01

Multi-response optimization is an optimization process by considering multiple responses simultaneously. The purpose of this research is to get the optimum point on multi-response optimization process using grey relational analysis and fuzzy logic method. The optimum point is determined from the Fuzzy-GRG (Grey Relational Grade) variable which is the conversion of the Signal to Noise Ratio of the responses involved. The case study used in this research are case optimization of electrical process parameters in electrical disharge machining. It was found that the combination of treatments resulting to optimum MRR and SR was a 70 V gap voltage factor, peak current 9 A and duty factor 0.8.

Estimation of environment-related properties of chemicals for design of sustainable processes: development of group-contribution+ (GC+) property models and uncertainty analysis.

PubMed

Hukkerikar, Amol Shivajirao; Kalakul, Sawitree; Sarup, Bent; Young, Douglas M; Sin, Gürkan; Gani, Rafiqul

2012-11-26

The aim of this work is to develop group-contribution(+) (GC(+)) method (combined group-contribution (GC) method and atom connectivity index (CI) method) based property models to provide reliable estimations of environment-related properties of organic chemicals together with uncertainties of estimated property values. For this purpose, a systematic methodology for property modeling and uncertainty analysis is used. The methodology includes a parameter estimation step to determine parameters of property models and an uncertainty analysis step to establish statistical information about the quality of parameter estimation, such as the parameter covariance, the standard errors in predicted properties, and the confidence intervals. For parameter estimation, large data sets of experimentally measured property values of a wide range of chemicals (hydrocarbons, oxygenated chemicals, nitrogenated chemicals, poly functional chemicals, etc.) taken from the database of the US Environmental Protection Agency (EPA) and from the database of USEtox is used. For property modeling and uncertainty analysis, the Marrero and Gani GC method and atom connectivity index method have been considered. In total, 22 environment-related properties, which include the fathead minnow 96-h LC(50), Daphnia magna 48-h LC(50), oral rat LD(50), aqueous solubility, bioconcentration factor, permissible exposure limit (OSHA-TWA), photochemical oxidation potential, global warming potential, ozone depletion potential, acidification potential, emission to urban air (carcinogenic and noncarcinogenic), emission to continental rural air (carcinogenic and noncarcinogenic), emission to continental fresh water (carcinogenic and noncarcinogenic), emission to continental seawater (carcinogenic and noncarcinogenic), emission to continental natural soil (carcinogenic and noncarcinogenic), and emission to continental agricultural soil (carcinogenic and noncarcinogenic) have been modeled and analyzed. The application of the developed property models for the estimation of environment-related properties and uncertainties of the estimated property values is highlighted through an illustrative example. The developed property models provide reliable estimates of environment-related properties needed to perform process synthesis, design, and analysis of sustainable chemical processes and allow one to evaluate the effect of uncertainties of estimated property values on the calculated performance of processes giving useful insights into quality and reliability of the design of sustainable processes.

Comparison of histomorphometrical data obtained with two different image analysis methods.

PubMed

Ballerini, Lucia; Franke-Stenport, Victoria; Borgefors, Gunilla; Johansson, Carina B

2007-08-01

A common way to determine tissue acceptance of biomaterials is to perform histomorphometrical analysis on histologically stained sections from retrieved samples with surrounding tissue, using various methods. The "time and money consuming" methods and techniques used are often "in house standards". We address light microscopic investigations of bone tissue reactions on un-decalcified cut and ground sections of threaded implants. In order to screen sections and generate results faster, the aim of this pilot project was to compare results generated with the in-house standard visual image analysis tool (i.e., quantifications and judgements done by the naked eye) with a custom made automatic image analysis program. The histomorphometrical bone area measurements revealed no significant differences between the methods but the results of the bony contacts varied significantly. The raw results were in relative agreement, i.e., the values from the two methods were proportional to each other: low bony contact values in the visual method corresponded to low values with the automatic method. With similar resolution images and further improvements of the automatic method this difference should become insignificant. A great advantage using the new automatic image analysis method is that it is time saving--analysis time can be significantly reduced.

An Quantitative Analysis Method Of Trabecular Pattern In A Bone

NASA Astrophysics Data System (ADS)

Idesawa, Masanor; Yatagai, Toyohiko

1982-11-01

Orientation and density of trabecular pattern observed in a bone is closely related to its mechanical properties and deseases of a bone are appeared as changes of orientation and/or density distrbution of its trabecular patterns. They have been treated from a qualitative point of view so far because quantitative analysis method has not be established. In this paper, the authors proposed and investigated some quantitative analysis methods of density and orientation of trabecular patterns observed in a bone. These methods can give an index for evaluating orientation of trabecular pattern quantitatively and have been applied to analyze trabecular pattern observed in a head of femur and their availabilities are confirmed. Key Words: Index of pattern orientation, Trabecular pattern, Pattern density, Quantitative analysis

Perturbation Selection and Local Influence Analysis for Nonlinear Structural Equation Model

ERIC Educational Resources Information Center

Chen, Fei; Zhu, Hong-Tu; Lee, Sik-Yum

2009-01-01

Local influence analysis is an important statistical method for studying the sensitivity of a proposed model to model inputs. One of its important issues is related to the appropriate choice of a perturbation vector. In this paper, we develop a general method to select an appropriate perturbation vector and a second-order local influence measure…

Qualitative Research in Career Development: Content Analysis from 1990 to 2009

ERIC Educational Resources Information Center

Stead, Graham B.; Perry, Justin C.; Munka, Linda M.; Bonnett, Heather R.; Shiban, Abbey P.; Care, Esther

2012-01-01

A content analysis of 11 journals that published career, vocational, and work-related articles from 1990 to 2009 was conducted. Of 3,279 articles analyzed, 55.9% used quantitative methods and 35.5% were theoretical/conceptual articles. Only 6.3% used qualitative research methods. Among the qualitative empirical studies, standards of academic rigor…

Method and apparatus for enhanced sequencing of complex molecules using surface-induced dissociation in conjunction with mass spectrometric analysis

DOEpatents

Laskin, Julia [Richland, WA; Futrell, Jean H [Richland, WA

2008-04-29

The invention relates to a method and apparatus for enhanced sequencing of complex molecules using surface-induced dissociation (SID) in conjunction with mass spectrometric analysis. Results demonstrate formation of a wide distribution of structure-specific fragments having wide sequence coverage useful for sequencing and identifying the complex molecules.

Sight-Singing Pedagogy: A Content Analysis of Choral Methods Textbooks

ERIC Educational Resources Information Center

Floyd, Eva G.; Haning, Marshall A.

2015-01-01

The purpose of this study was to examine the sight-singing pedagogy content of choral methods textbooks, with the intent of determining what elements of sight-singing pedagogy are most commonly included in these resources. A content analysis was conducted to analyze information related to sight-singing pedagogy in 10 textbooks that are commonly…

Functional connectivity analysis of the neural bases of emotion regulation: A comparison of independent component method with density-based k-means clustering method.

PubMed

Zou, Ling; Guo, Qian; Xu, Yi; Yang, Biao; Jiao, Zhuqing; Xiang, Jianbo

2016-04-29

Functional magnetic resonance imaging (fMRI) is an important tool in neuroscience for assessing connectivity and interactions between distant areas of the brain. To find and characterize the coherent patterns of brain activity as a means of identifying brain systems for the cognitive reappraisal of the emotion task, both density-based k-means clustering and independent component analysis (ICA) methods can be applied to characterize the interactions between brain regions involved in cognitive reappraisal of emotion. Our results reveal that compared with the ICA method, the density-based k-means clustering method provides a higher sensitivity of polymerization. In addition, it is more sensitive to those relatively weak functional connection regions. Thus, the study concludes that in the process of receiving emotional stimuli, the relatively obvious activation areas are mainly distributed in the frontal lobe, cingulum and near the hypothalamus. Furthermore, density-based k-means clustering method creates a more reliable method for follow-up studies of brain functional connectivity.

Analysis of a turbulent boundary layer over a moving ground plane

NASA Technical Reports Server (NTRS)

Roper, A. T.; Gentry, G. L., Jr.

1972-01-01

Four methods of predicting the integral and friction parameters for a turbulent boundary layer over a moving ground plane were evaluated by using test information obtained in 76.2- by 50.8-centimeter tunnel. The tunnel was operated in the open sidewall configuration. These methods are (1) relative integral parameter method, (2) modified power law method, (3) relative power law method, and (4) modified law of the wall method. The modified law of the wall method predicts a more rapid decrease in skin friction with an increase in the ratio of belt velocity to free steam velocity than do methods (1) and (3).

PSEA: Kinase-specific prediction and analysis of human phosphorylation substrates

NASA Astrophysics Data System (ADS)

Suo, Sheng-Bao; Qiu, Jian-Ding; Shi, Shao-Ping; Chen, Xiang; Liang, Ru-Ping

2014-03-01

Protein phosphorylation catalysed by kinases plays crucial regulatory roles in intracellular signal transduction. With the increasing number of kinase-specific phosphorylation sites and disease-related phosphorylation substrates that have been identified, the desire to explore the regulatory relationship between protein kinases and disease-related phosphorylation substrates is motivated. In this work, we analysed the kinases' characteristic of all disease-related phosphorylation substrates by using our developed Phosphorylation Set Enrichment Analysis (PSEA) method. We evaluated the efficiency of our method with independent test and concluded that our approach is reliable for identifying kinases responsible for phosphorylated substrates. In addition, we found that Mitogen-activated protein kinase (MAPK) and Glycogen synthase kinase (GSK) families are more associated with abnormal phosphorylation. It can be anticipated that our method might be helpful to identify the mechanism of phosphorylation and the relationship between kinase and phosphorylation related diseases. A user-friendly web interface is now freely available at http://bioinfo.ncu.edu.cn/PKPred_Home.aspx.

Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks

PubMed Central

2018-01-01

Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181

Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies.

PubMed

Thorsen, Jonathan; Brejnrod, Asker; Mortensen, Martin; Rasmussen, Morten A; Stokholm, Jakob; Al-Soud, Waleed Abu; Sørensen, Søren; Bisgaard, Hans; Waage, Johannes

2016-11-25

There is an immense scientific interest in the human microbiome and its effects on human physiology, health, and disease. A common approach for examining bacterial communities is high-throughput sequencing of 16S rRNA gene hypervariable regions, aggregating sequence-similar amplicons into operational taxonomic units (OTUs). Strategies for detecting differential relative abundance of OTUs between sample conditions include classical statistical approaches as well as a plethora of newer methods, many borrowing from the related field of RNA-seq analysis. This effort is complicated by unique data characteristics, including sparsity, sequencing depth variation, and nonconformity of read counts to theoretical distributions, which is often exacerbated by exploratory and/or unbalanced study designs. Here, we assess the robustness of available methods for (1) inference in differential relative abundance analysis and (2) beta-diversity-based sample separation, using a rigorous benchmarking framework based on large clinical 16S microbiome datasets from different sources. Running more than 380,000 full differential relative abundance tests on real datasets with permuted case/control assignments and in silico-spiked OTUs, we identify large differences in method performance on a range of parameters, including false positive rates, sensitivity to sparsity and case/control balances, and spike-in retrieval rate. In large datasets, methods with the highest false positive rates also tend to have the best detection power. For beta-diversity-based sample separation, we show that library size normalization has very little effect and that the distance metric is the most important factor in terms of separation power. Our results, generalizable to datasets from different sequencing platforms, demonstrate how the choice of method considerably affects analysis outcome. Here, we give recommendations for tools that exhibit low false positive rates, have good retrieval power across effect sizes and case/control proportions, and have low sparsity bias. Result output from some commonly used methods should be interpreted with caution. We provide an easily extensible framework for benchmarking of new methods and future microbiome datasets.

A needs analysis method for land-use planning of illegal dumping sites: a case study in Aomori-Iwate, Japan.

PubMed

Ishii, Kazuei; Furuichi, Toru; Nagao, Yukari

2013-02-01

Land use at contaminated sites, following remediation, is often needed for regional redevelopment. However, there exist few methods of developing economically and socially feasible land-use plans based on regional needs because of the wide variety of land-use requirements. This study proposes a new needs analysis method for the conceptual land-use planning of contaminated sites and illustrates this method with a case study of an illegal dumping site for hazardous waste. In this method, planning factors consisting of the land-use attributes and related facilities are extracted from the potential needs of the residents through a preliminary questionnaire. Using the extracted attributes of land use and the related facilities, land-use cases are designed for selection-based conjoint analysis. A second questionnaire for respondents to the first one who indicated an interest in participating in the second questionnaire is conducted for the conjoint analysis to determine the utility function and marginal cost of each attribute in order to prioritize the planning factors to develop a quantitative and economically and socially feasible land-use plan. Based on the results, site-specific land-use alternatives are developed and evaluated by the utility function obtained from the conjoint analysis. In this case study of an illegal dumping site for hazardous waste, the uses preferred as part of a conceptual land-use plan following remediation of the site were (1) agricultural land and a biogas plant designed to recover energy from biomass or (2) a park with a welfare facility and an athletic field. Our needs analysis method with conjoint analysis is applicable to the development of conceptual land-use planning for similar sites following remediation, particularly when added value is considered. Copyright © 2012 Elsevier Ltd. All rights reserved.

Uncertainty of quantitative microbiological methods of pharmaceutical analysis.

PubMed

Gunar, O V; Sakhno, N G

2015-12-30

The total uncertainty of quantitative microbiological methods, used in pharmaceutical analysis, consists of several components. The analysis of the most important sources of the quantitative microbiological methods variability demonstrated no effect of culture media and plate-count techniques in the estimation of microbial count while the highly significant effect of other factors (type of microorganism, pharmaceutical product and individual reading and interpreting errors) was established. The most appropriate method of statistical analysis of such data was ANOVA which enabled not only the effect of individual factors to be estimated but also their interactions. Considering all the elements of uncertainty and combining them mathematically the combined relative uncertainty of the test results was estimated both for method of quantitative examination of non-sterile pharmaceuticals and microbial count technique without any product. These data did not exceed 35%, appropriated for a traditional plate count methods. Copyright © 2015 Elsevier B.V. All rights reserved.

Grid related issues for static and dynamic geometry problems using systems of overset structured grids

NASA Technical Reports Server (NTRS)

Meakin, Robert L.

1995-01-01

Grid related issues of the Chimera overset grid method are discussed in the context of a method of solution and analysis of unsteady three-dimensional viscous flows. The state of maturity of the various pieces of support software required to use the approach is considered. Current limitations of the approach are identified.

Views of School Administrators Related to In-Service Training Activities

ERIC Educational Resources Information Center

Güngör, Semra Kiranli; Yildirim, Yusuf

2016-01-01

The aim of this research is to specify the views of school administrators related to in-service training activities. In this research, semi-structured interview method, one of the qualitative research methods, has been used. Content analysis has been used in order to analyze the interview data and themes and sub-themes have been constituted. The…

Estimation of low back moments from video analysis: a validation study.

PubMed

Coenen, Pieter; Kingma, Idsart; Boot, Cécile R L; Faber, Gert S; Xu, Xu; Bongers, Paulien M; van Dieën, Jaap H

2011-09-02

This study aimed to develop, compare and validate two versions of a video analysis method for assessment of low back moments during occupational lifting tasks since for epidemiological studies and ergonomic practice relatively cheap and easily applicable methods to assess low back loads are needed. Ten healthy subjects participated in a protocol comprising 12 lifting conditions. Low back moments were assessed using two variants of a video analysis method and a lab-based reference method. Repeated measures ANOVAs showed no overall differences in peak moments between the two versions of the video analysis method and the reference method. However, two conditions showed a minor overestimation of one of the video analysis method moments. Standard deviations were considerable suggesting that errors in the video analysis were random. Furthermore, there was a small underestimation of dynamic components and overestimation of the static components of the moments. Intraclass correlations coefficients for peak moments showed high correspondence (>0.85) of the video analyses with the reference method. It is concluded that, when a sufficient number of measurements can be taken, the video analysis method for assessment of low back loads during lifting tasks provides valid estimates of low back moments in ergonomic practice and epidemiological studies for lifts up to a moderate level of asymmetry. Copyright © 2011 Elsevier Ltd. All rights reserved.

Applications of Response Surface-Based Methods to Noise Analysis in the Conceptual Design of Revolutionary Aircraft

NASA Technical Reports Server (NTRS)

Hill, Geoffrey A.; Olson, Erik D.

2004-01-01

Due to the growing problem of noise in today's air transportation system, there have arisen needs to incorporate noise considerations in the conceptual design of revolutionary aircraft. Through the use of response surfaces, complex noise models may be converted into polynomial equations for rapid and simplified evaluation. This conversion allows many of the commonly used response surface-based trade space exploration methods to be applied to noise analysis. This methodology is demonstrated using a noise model of a notional 300 passenger Blended-Wing-Body (BWB) transport. Response surfaces are created relating source noise levels of the BWB vehicle to its corresponding FAR-36 certification noise levels and the resulting trade space is explored. Methods demonstrated include: single point analysis, parametric study, an optimization technique for inverse analysis, sensitivity studies, and probabilistic analysis. Extended applications of response surface-based methods in noise analysis are also discussed.

Rapid analysis of pharmaceutical drugs using LIBS coupled with multivariate analysis.

PubMed

Tiwari, P K; Awasthi, S; Kumar, R; Anand, R K; Rai, P K; Rai, A K

2018-02-01

Type 2 diabetes drug tablets containing voglibose having dose strengths of 0.2 and 0.3 mg of various brands have been examined, using laser-induced breakdown spectroscopy (LIBS) technique. The statistical methods such as the principal component analysis (PCA) and the partial least square regression analysis (PLSR) have been employed on LIBS spectral data for classifying and developing the calibration models of drug samples. We have developed the ratio-based calibration model applying PLSR in which relative spectral intensity ratios H/C, H/N and O/N are used. Further, the developed model has been employed to predict the relative concentration of element in unknown drug samples. The experiment has been performed in air and argon atmosphere, respectively, and the obtained results have been compared. The present model provides rapid spectroscopic method for drug analysis with high statistical significance for online control and measurement process in a wide variety of pharmaceutical industrial applications.

Methods for Force Analysis of Overconstrained Parallel Mechanisms: A Review

NASA Astrophysics Data System (ADS)

Liu, Wen-Lan; Xu, Yun-Dou; Yao, Jian-Tao; Zhao, Yong-Sheng

2017-11-01

The force analysis of overconstrained PMs is relatively complex and difficult, for which the methods have always been a research hotspot. However, few literatures analyze the characteristics and application scopes of the various methods, which is not convenient for researchers and engineers to master and adopt them properly. A review of the methods for force analysis of both passive and active overconstrained PMs is presented. The existing force analysis methods for these two kinds of overconstrained PMs are classified according to their main ideas. Each category is briefly demonstrated and evaluated from such aspects as the calculation amount, the comprehensiveness of considering limbs' deformation, and the existence of explicit expressions of the solutions, which provides an important reference for researchers and engineers to quickly find a suitable method. The similarities and differences between the statically indeterminate problem of passive overconstrained PMs and that of active overconstrained PMs are discussed, and a universal method for these two kinds of overconstrained PMs is pointed out. The existing deficiencies and development directions of the force analysis methods for overconstrained systems are indicated based on the overview.

Performance Evaluation of Technical Institutions: An Application of Data Envelopment Analysis

ERIC Educational Resources Information Center

Debnath, Roma Mitra; Shankar, Ravi; Kumar, Surender

2008-01-01

Technical institutions (TIs) are playing an important role in making India a knowledge hub of this century. There is still great diversity in their relative performance, which is a matter of concern to the education planner. This article employs the method of data envelopment analysis (DEA) to compare the relative efficiency of TIs in India. The…

Aiming to Complete the Matrix: Eye-Movement Analysis of Processing Strategies in Children's Relational Thinking

ERIC Educational Resources Information Center

Chen, Zhe; Honomichl, Ryan; Kennedy, Diane; Tan, Enda

2016-01-01

The present study examines 5- to 8-year-old children's relation reasoning in solving matrix completion tasks. This study incorporates a componential analysis, an eye-tracking method, and a microgenetic approach, which together allow an investigation of the cognitive processing strategies involved in the development and learning of children's…

Exploring the relationship between the engineering and physical sciences and the health and life sciences by advanced bibliometric methods.

PubMed

Waltman, Ludo; van Raan, Anthony F J; Smart, Sue

2014-01-01

We investigate the extent to which advances in the health and life sciences (HLS) are dependent on research in the engineering and physical sciences (EPS), particularly physics, chemistry, mathematics, and engineering. The analysis combines two different bibliometric approaches. The first approach to analyze the 'EPS-HLS interface' is based on term map visualizations of HLS research fields. We consider 16 clinical fields and five life science fields. On the basis of expert judgment, EPS research in these fields is studied by identifying EPS-related terms in the term maps. In the second approach, a large-scale citation-based network analysis is applied to publications from all fields of science. We work with about 22,000 clusters of publications, each representing a topic in the scientific literature. Citation relations are used to identify topics at the EPS-HLS interface. The two approaches complement each other. The advantages of working with textual data compensate for the limitations of working with citation relations and the other way around. An important advantage of working with textual data is in the in-depth qualitative insights it provides. Working with citation relations, on the other hand, yields many relevant quantitative statistics. We find that EPS research contributes to HLS developments mainly in the following five ways: new materials and their properties; chemical methods for analysis and molecular synthesis; imaging of parts of the body as well as of biomaterial surfaces; medical engineering mainly related to imaging, radiation therapy, signal processing technology, and other medical instrumentation; mathematical and statistical methods for data analysis. In our analysis, about 10% of all EPS and HLS publications are classified as being at the EPS-HLS interface. This percentage has remained more or less constant during the past decade.

Exploring the Relationship between the Engineering and Physical Sciences and the Health and Life Sciences by Advanced Bibliometric Methods

PubMed Central

Waltman, Ludo; van Raan, Anthony F. J.; Smart, Sue

2014-01-01

We investigate the extent to which advances in the health and life sciences (HLS) are dependent on research in the engineering and physical sciences (EPS), particularly physics, chemistry, mathematics, and engineering. The analysis combines two different bibliometric approaches. The first approach to analyze the ‘EPS-HLS interface’ is based on term map visualizations of HLS research fields. We consider 16 clinical fields and five life science fields. On the basis of expert judgment, EPS research in these fields is studied by identifying EPS-related terms in the term maps. In the second approach, a large-scale citation-based network analysis is applied to publications from all fields of science. We work with about 22,000 clusters of publications, each representing a topic in the scientific literature. Citation relations are used to identify topics at the EPS-HLS interface. The two approaches complement each other. The advantages of working with textual data compensate for the limitations of working with citation relations and the other way around. An important advantage of working with textual data is in the in-depth qualitative insights it provides. Working with citation relations, on the other hand, yields many relevant quantitative statistics. We find that EPS research contributes to HLS developments mainly in the following five ways: new materials and their properties; chemical methods for analysis and molecular synthesis; imaging of parts of the body as well as of biomaterial surfaces; medical engineering mainly related to imaging, radiation therapy, signal processing technology, and other medical instrumentation; mathematical and statistical methods for data analysis. In our analysis, about 10% of all EPS and HLS publications are classified as being at the EPS-HLS interface. This percentage has remained more or less constant during the past decade. PMID:25360616

Comparison of two occurrence risk assessment methods for collapse gully erosion ——A case study in Guangdong province

NASA Astrophysics Data System (ADS)

Sun, K.; Cheng, D. B.; He, J. J.; Zhao, Y. L.

2018-02-01

Collapse gully erosion is a specific type of soil erosion in the red soil region of southern China, and early warning and prevention of the occurrence of collapse gully erosion is very important. Based on the idea of risk assessment, this research, taking Guangdong province as an example, adopt the information acquisition analysis and the logistic regression analysis, to discuss the feasibility for collapse gully erosion risk assessment in regional scale, and compare the applicability of the different risk assessment methods. The results show that in the Guangdong province, the risk degree of collapse gully erosion occurrence is high in northeastern and western area, and relatively low in southwestern and central part. The comparing analysis of the different risk assessment methods on collapse gully also indicated that the risk distribution patterns from the different methods were basically consistent. However, the accuracy of risk map from the information acquisition analysis method was slightly better than that from the logistic regression analysis method.

The Application of Social Network Analysis to Team Sports

ERIC Educational Resources Information Center

Lusher, Dean; Robins, Garry; Kremer, Peter

2010-01-01

This article reviews how current social network analysis might be used to investigate individual and group behavior in sporting teams. Social network analysis methods permit researchers to explore social relations between team members and their individual-level qualities simultaneously. As such, social network analysis can be seen as augmenting…

Do Our Means of Inquiry Match our Intentions?

PubMed Central

Petscher, Yaacov

2016-01-01

A key stage of the scientific method is the analysis of data, yet despite the variety of methods that are available to researchers they are most frequently distilled to a model that focuses on the average relation between variables. Although research questions are frequently conceived with broad inquiry in mind, most regression methods are limited in comprehensively evaluating how observed behaviors are related to each other. Quantile regression is a largely unknown yet well-suited analytic technique similar to traditional regression analysis, but allows for a more systematic approach to understanding complex associations among observed phenomena in the psychological sciences. Data from the National Education Longitudinal Study of 1988/2000 are used to illustrate how quantile regression overcomes the limitations of average associations in linear regression by showing that psychological well-being and sex each differentially relate to reading achievement depending on one’s level of reading achievement. PMID:27486410

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling: GEOSTATISTICAL SENSITIVITY ANALYSIS

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

Dai, Heng; Chen, Xingyuan; Ye, Ming

Sensitivity analysis is an important tool for quantifying uncertainty in the outputs of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a hierarchical sensitivity analysis method that (1) constructs an uncertainty hierarchy by analyzing the input uncertainty sources, and (2) accounts for the spatial correlation among parameters at each level ofmore » the hierarchy using geostatistical tools. The contribution of uncertainty source at each hierarchy level is measured by sensitivity indices calculated using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport in model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally as driven by the dynamic interaction between groundwater and river water at the site. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed parameters.« less

Effectiveness evaluation of objective and subjective weighting methods for aquifer vulnerability assessment in urban context

NASA Astrophysics Data System (ADS)

Sahoo, Madhumita; Sahoo, Satiprasad; Dhar, Anirban; Pradhan, Biswajeet

2016-10-01

Groundwater vulnerability assessment has been an accepted practice to identify the zones with relatively increased potential for groundwater contamination. DRASTIC is the most popular secondary information-based vulnerability assessment approach. Original DRASTIC approach considers relative importance of features/sub-features based on subjective weighting/rating values. However variability of features at a smaller scale is not reflected in this subjective vulnerability assessment process. In contrast to the subjective approach, the objective weighting-based methods provide flexibility in weight assignment depending on the variation of the local system. However experts' opinion is not directly considered in the objective weighting-based methods. Thus effectiveness of both subjective and objective weighting-based approaches needs to be evaluated. In the present study, three methods - Entropy information method (E-DRASTIC), Fuzzy pattern recognition method (F-DRASTIC) and Single parameter sensitivity analysis (SA-DRASTIC), were used to modify the weights of the original DRASTIC features to include local variability. Moreover, a grey incidence analysis was used to evaluate the relative performance of subjective (DRASTIC and SA-DRASTIC) and objective (E-DRASTIC and F-DRASTIC) weighting-based methods. The performance of the developed methodology was tested in an urban area of Kanpur City, India. Relative performance of the subjective and objective methods varies with the choice of water quality parameters. This methodology can be applied without/with suitable modification. These evaluations establish the potential applicability of the methodology for general vulnerability assessment in urban context.

Rubber.

ERIC Educational Resources Information Center

Krishen, Anoop

1989-01-01

This review covers methods for identification, characterization, and determination of rubber and materials in rubber. Topics include: general information, nuclear magnetic resonance spectroscopy, infrared spectroscopy, thermal methods, gel permeation chromatography, size exclusion chromatography, analysis related to safety and health, and…

Novel strategies to mine alcoholism-related haplotypes and genes by combining existing knowledge framework.

PubMed

Zhang, RuiJie; Li, Xia; Jiang, YongShuai; Liu, GuiYou; Li, ChuanXing; Zhang, Fan; Xiao, Yun; Gong, BinSheng

2009-02-01

High-throughout single nucleotide polymorphism detection technology and the existing knowledge provide strong support for mining the disease-related haplotypes and genes. In this study, first, we apply four kinds of haplotype identification methods (Confidence Intervals, Four Gamete Tests, Solid Spine of LD and fusing method of haplotype block) into high-throughout SNP genotype data to identify blocks, then use cluster analysis to verify the effectiveness of the four methods, and select the alcoholism-related SNP haplotypes through risk analysis. Second, we establish a mapping from haplotypes to alcoholism-related genes. Third, we inquire NCBI SNP and gene databases to locate the blocks and identify the candidate genes. In the end, we make gene function annotation by KEGG, Biocarta, and GO database. We find 159 haplotype blocks, which relate to the alcoholism most possibly on chromosome 1 approximately 22, including 227 haplotypes, of which 102 SNP haplotypes may increase the risk of alcoholism. We get 121 alcoholism-related genes and verify their reliability by the functional annotation of biology. In a word, we not only can handle the SNP data easily, but also can locate the disease-related genes precisely by combining our novel strategies of mining alcoholism-related haplotypes and genes with existing knowledge framework.

Comparing direct and iterative equation solvers in a large structural analysis software system

NASA Technical Reports Server (NTRS)

Poole, E. L.

1991-01-01

Two direct Choleski equation solvers and two iterative preconditioned conjugate gradient (PCG) equation solvers used in a large structural analysis software system are described. The two direct solvers are implementations of the Choleski method for variable-band matrix storage and sparse matrix storage. The two iterative PCG solvers include the Jacobi conjugate gradient method and an incomplete Choleski conjugate gradient method. The performance of the direct and iterative solvers is compared by solving several representative structural analysis problems. Some key factors affecting the performance of the iterative solvers relative to the direct solvers are identified.

Multiscale Characterization of PM2.5 in Southern Taiwan based on Noise-assisted Multivariate Empirical Mode Decomposition and Time-dependent Intrinsic Correlation

NASA Astrophysics Data System (ADS)

Hsiao, Y. R.; Tsai, C.

2017-12-01

As the WHO Air Quality Guideline indicates, ambient air pollution exposes world populations under threat of fatal symptoms (e.g. heart disease, lung cancer, asthma etc.), raising concerns of air pollution sources and relative factors. This study presents a novel approach to investigating the multiscale variations of PM2.5 in southern Taiwan over the past decade, with four meteorological influencing factors (Temperature, relative humidity, precipitation and wind speed),based on Noise-assisted Multivariate Empirical Mode Decomposition(NAMEMD) algorithm, Hilbert Spectral Analysis(HSA) and Time-dependent Intrinsic Correlation(TDIC) method. NAMEMD algorithm is a fully data-driven approach designed for nonlinear and nonstationary multivariate signals, and is performed to decompose multivariate signals into a collection of channels of Intrinsic Mode Functions (IMFs). TDIC method is an EMD-based method using a set of sliding window sizes to quantify localized correlation coefficients for multiscale signals. With the alignment property and quasi-dyadic filter bank of NAMEMD algorithm, one is able to produce same number of IMFs for all variables and estimates the cross correlation in a more accurate way. The performance of spectral representation of NAMEMD-HSA method is compared with Complementary Empirical Mode Decomposition/ Hilbert Spectral Analysis (CEEMD-HSA) and Wavelet Analysis. The nature of NAMAMD-based TDICC analysis is then compared with CEEMD-based TDIC analysis and the traditional correlation analysis.

Analysis of swainsonine and swainsonine N-oxide as trimethylsilyl derivatives by Liquid Chromatography-Mass Spectrometry and their relative occurrence in plants toxic to livestock

USDA-ARS?s Scientific Manuscript database

A liquid chromatography-mass spectrometry method was developed for the analysis of the indolizidine alkaloid swainsonine and its N-oxide. The method is based on a one step solvent partitioning extraction procedure followed by trimethylsilylation of the dried extract and subsequent detection and qua...

Automotive Exterior Noise Optimization Using Grey Relational Analysis Coupled with Principal Component Analysis

NASA Astrophysics Data System (ADS)

Chen, Shuming; Wang, Dengfeng; Liu, Bo

This paper investigates optimization design of the thickness of the sound package performed on a passenger automobile. The major characteristics indexes for performance selected to evaluate the processes are the SPL of the exterior noise and the weight of the sound package, and the corresponding parameters of the sound package are the thickness of the glass wool with aluminum foil for the first layer, the thickness of the glass fiber for the second layer, and the thickness of the PE foam for the third layer. In this paper, the process is fundamentally with multiple performances, thus, the grey relational analysis that utilizes grey relational grade as performance index is especially employed to determine the optimal combination of the thickness of the different layers for the designed sound package. Additionally, in order to evaluate the weighting values corresponding to various performance characteristics, the principal component analysis is used to show their relative importance properly and objectively. The results of the confirmation experiments uncover that grey relational analysis coupled with principal analysis methods can successfully be applied to find the optimal combination of the thickness for each layer of the sound package material. Therefore, the presented method can be an effective tool to improve the vehicle exterior noise and lower the weight of the sound package. In addition, it will also be helpful for other applications in the automotive industry, such as the First Automobile Works in China, Changan Automobile in China, etc.

Valsartan.

PubMed

Ardiana, Febry; Suciati; Indrayanto, Gunawan

2015-01-01

Valsartan is an antihypertensive drug which selectively inhibits angiotensin receptor type II. Generally, valsartan is available as film-coated tablets. This review summarizes thermal analysis, spectroscopy characteristics (UV, IR, MS, and NMR), polymorphism forms, impurities, and related compounds of valsartan. The methods of analysis of valsartan in pharmaceutical dosage forms and in biological fluids using spectrophotometer, CE, TLC, and HPLC methods are discussed in details. Both official and nonofficial methods are described. It is recommended to use LC-MS method for analyzing valsartan in complex matrices such as biological fluids and herbal preparations; in this case, MRM is preferred than SIM method. © 2015 Elsevier Inc. All rights reserved.

Diverse expected gradient active learning for relative attributes.

PubMed

You, Xinge; Wang, Ruxin; Tao, Dacheng

2014-07-01

The use of relative attributes for semantic understanding of images and videos is a promising way to improve communication between humans and machines. However, it is extremely labor- and time-consuming to define multiple attributes for each instance in large amount of data. One option is to incorporate active learning, so that the informative samples can be actively discovered and then labeled. However, most existing active-learning methods select samples one at a time (serial mode), and may therefore lose efficiency when learning multiple attributes. In this paper, we propose a batch-mode active-learning method, called diverse expected gradient active learning. This method integrates an informativeness analysis and a diversity analysis to form a diverse batch of queries. Specifically, the informativeness analysis employs the expected pairwise gradient length as a measure of informativeness, while the diversity analysis forces a constraint on the proposed diverse gradient angle. Since simultaneous optimization of these two parts is intractable, we utilize a two-step procedure to obtain the diverse batch of queries. A heuristic method is also introduced to suppress imbalanced multiclass distributions. Empirical evaluations of three different databases demonstrate the effectiveness and efficiency of the proposed approach.

Diverse Expected Gradient Active Learning for Relative Attributes.

PubMed

You, Xinge; Wang, Ruxin; Tao, Dacheng

2014-06-02

The use of relative attributes for semantic understanding of images and videos is a promising way to improve communication between humans and machines. However, it is extremely labor- and time-consuming to define multiple attributes for each instance in large amount of data. One option is to incorporate active learning, so that the informative samples can be actively discovered and then labeled. However, most existing active-learning methods select samples one at a time (serial mode), and may therefore lose efficiency when learning multiple attributes. In this paper, we propose a batch-mode active-learning method, called Diverse Expected Gradient Active Learning (DEGAL). This method integrates an informativeness analysis and a diversity analysis to form a diverse batch of queries. Specifically, the informativeness analysis employs the expected pairwise gradient length as a measure of informativeness, while the diversity analysis forces a constraint on the proposed diverse gradient angle. Since simultaneous optimization of these two parts is intractable, we utilize a two-step procedure to obtain the diverse batch of queries. A heuristic method is also introduced to suppress imbalanced multi-class distributions. Empirical evaluations of three different databases demonstrate the effectiveness and efficiency of the proposed approach.

Selecting supplier combination based on fuzzy multicriteria analysis

NASA Astrophysics Data System (ADS)

Han, Zhi-Qiu; Luo, Xin-Xing; Chen, Xiao-Hong; Yang, Wu-E.

2015-07-01

Existing multicriteria analysis (MCA) methods are probably ineffective in selecting a supplier combination. Thus, an MCA-based fuzzy 0-1 programming method is introduced. The programming relates to a simple MCA matrix that is used to select a single supplier. By solving the programming, the most feasible combination of suppliers is selected. Importantly, this result differs from selecting suppliers one by one according to a single-selection order, which is used to rank sole suppliers in existing MCA methods. An example highlights such difference and illustrates the proposed method.

Determination of Yohimbine in Yohimbe Bark and Related Dietary Supplements Using UHPLC-UV/MS: Single-Laboratory Validation.

PubMed

Chen, Pei; Bryden, Noella

2015-01-01

A single-laboratory validation was performed on a practical ultra-HPLC (UHPLC)-diode array detector (DAD)/tandem MS method for determination of yohimbine in yohimbe barks and related dietary supplements. Good separation was achieved using a Waters Acquity ethylene bridged hybrid C18 column with gradient elution using 0.1% (v/v) aqueous ammonium hydroxide and 0.1% ammonium hydroxide in methanol as the mobile phases. The method can separate corynanthine from yohimbine in yohimbe bark extract, which is critical for accurate quantitation of yohimbine in yohimbe bark and related dietary supplements. Accuracy of the method was demonstrated using standard addition methods. Both intraday and interday precisions of the method were good. The method can be used without MS since yohimbine concentration in yohimbe barks and related dietary supplements are usually high enough for DAD detection, which can make it an easy and economical method for routine analysis of yohimbe barks and related dietary supplements. On the other hand, the method can be used with MS if desired for more challenging work such as biological and/or clinical studies.

Emergy analysis of an industrial park: the case of Dalian, China.

PubMed

Geng, Yong; Zhang, Pan; Ulgiati, Sergio; Sarkis, Joseph

2010-10-15

With the rapid development of eco-industrial park projects in China, evaluating their overall eco-efficiency is becoming an important need and a big challenge academically. Developing ecologically conscious industrial park management requires analysis of both industrial and ecological systems. Traditional evaluation methods based on neoclassical economics and embodied energy and exergy analyses have certain limitations due to their focus with environmental issues considered secondary to the maximization of economic and technical objectives. Such methods focus primarily on the environmental impact of emissions and their economic consequences. These approaches ignore the contribution of ecological products and services as well as the load placed on environmental systems and related problems of carrying capacity of economic and industrial development. This paper presents a new method, based upon emergy analysis and synthesis. Such a method links economic and ecological systems together, highlighting the internal relations among the different subsystems and components. The emergy-based method provides insight into the environmental performance and sustainability of an industrial park. This paper depicts the methodology of emergy analysis at the industrial park level and provides a series of emergy-based indices. A case study is investigated and discussed in order to show the emergy method's practical potential. Results from DEDZ (Dalian Economic Development Zone) case show us the potential of emergy synthesis method at the industrial park level for environmental policy making. Its advantages and limitations are also discussed with avenues for future research identified. Copyright © 2010 Elsevier B.V. All rights reserved.

Methods for the visualization and analysis of extracellular matrix protein structure and degradation.

PubMed

Leonard, Annemarie K; Loughran, Elizabeth A; Klymenko, Yuliya; Liu, Yueying; Kim, Oleg; Asem, Marwa; McAbee, Kevin; Ravosa, Matthew J; Stack, M Sharon

2018-01-01

This chapter highlights methods for visualization and analysis of extracellular matrix (ECM) proteins, with particular emphasis on collagen type I, the most abundant protein in mammals. Protocols described range from advanced imaging of complex in vivo matrices to simple biochemical analysis of individual ECM proteins. The first section of this chapter describes common methods to image ECM components and includes protocols for second harmonic generation, scanning electron microscopy, and several histological methods of ECM localization and degradation analysis, including immunohistochemistry, Trichrome staining, and in situ zymography. The second section of this chapter details both a common transwell invasion assay and a novel live imaging method to investigate cellular behavior with respect to collagen and other ECM proteins of interest. The final section consists of common electrophoresis-based biochemical methods that are used in analysis of ECM proteins. Use of the methods described herein will enable researchers to gain a greater understanding of the role of ECM structure and degradation in development and matrix-related diseases such as cancer and connective tissue disorders. © 2018 Elsevier Inc. All rights reserved.

Improved omit set displacement recoveries in dynamic analysis

NASA Technical Reports Server (NTRS)

Allen, Tom; Cook, Greg; Walls, Bill

1993-01-01

Two related methods for improving the dependent (OMIT set) displacements after performing a Guyan reduction are presented. The theoretical bases for the methods are derived. The NASTRAN DMAP ALTERs used to implement the methods in a NASTRAN execution are described. Data are presented that verify the methods and the NASTRAN DMAP ALTERs.

Using Case-Mix Adjustment Methods To Measure the Effectiveness of Substance Abuse Treatment: Three Examples Using Client Employment Outcomes.

ERIC Educational Resources Information Center

Koenig, Lane; Fields, Errol L.; Dall, Timothy M.; Ameen, Ansari Z.; Harwood, Henrick J.

This report demonstrates three applications of case-mix methods using regression analysis. The results are used to assess the relative effectiveness of substance abuse treatment providers. The report also examines the ability of providers to improve client employment outcomes, an outcome domain relatively unexamined in the assessment of provider…

A simple method for estimating potential relative radiation (PRR) for landscape-vegetation analysis.

Treesearch

Kenneth B. Jr. Pierce; Todd Lookingbill; Dean Urban

2005-01-01

Radiation is one of the primary influences on vegetation composition and spatial pattern. Topographic orientation is often used as a proxy for relative radiation load due to its effects on evaporative demand and local temperature. Common methods for incorporating this information (i.e., site measures of slope and aspect) fail to include daily or annual changes in solar...

Comparability of river suspended-sediment sampling and laboratory analysis methods

USGS Publications Warehouse

Groten, Joel T.; Johnson, Gregory D.

2018-03-06

Accurate measurements of suspended sediment, a leading water-quality impairment in many Minnesota rivers, are important for managing and protecting water resources; however, water-quality standards for suspended sediment in Minnesota are based on grab field sampling and total suspended solids (TSS) laboratory analysis methods that have underrepresented concentrations of suspended sediment in rivers compared to U.S. Geological Survey equal-width-increment or equal-discharge-increment (EWDI) field sampling and suspended sediment concentration (SSC) laboratory analysis methods. Because of this underrepresentation, the U.S. Geological Survey, in collaboration with the Minnesota Pollution Control Agency, collected concurrent grab and EWDI samples at eight sites to compare results obtained using different combinations of field sampling and laboratory analysis methods.Study results determined that grab field sampling and TSS laboratory analysis results were biased substantially low compared to EWDI sampling and SSC laboratory analysis results, respectively. Differences in both field sampling and laboratory analysis methods caused grab and TSS methods to be biased substantially low. The difference in laboratory analysis methods was slightly greater than field sampling methods.Sand-sized particles had a strong effect on the comparability of the field sampling and laboratory analysis methods. These results indicated that grab field sampling and TSS laboratory analysis methods fail to capture most of the sand being transported by the stream. The results indicate there is less of a difference among samples collected with grab field sampling and analyzed for TSS and concentration of fines in SSC. Even though differences are present, the presence of strong correlations between SSC and TSS concentrations provides the opportunity to develop site specific relations to address transport processes not captured by grab field sampling and TSS laboratory analysis methods.

Specialty Selections of Jefferson Medical College Students: A Conjoint Analysis.

ERIC Educational Resources Information Center

Diamond, James J.; And Others

1994-01-01

A consumer research technique, conjoint analysis, was used to assess the relative importance of several factors in 104 fourth-year medical students' selection of specialty. Conjoint analysis appears to be a useful method for investigating the complex process of specialty selection. (SLD)

Contrast Analysis: A Tutorial

ERIC Educational Resources Information Center

Haans, Antal

2018-01-01

Contrast analysis is a relatively simple but effective statistical method for testing theoretical predictions about differences between group means against the empirical data. Despite its advantages, contrast analysis is hardly used to date, perhaps because it is not implemented in a convenient manner in many statistical software packages. This…

Psychophysiological whole-brain network clustering based on connectivity dynamics analysis in naturalistic conditions.

PubMed

Raz, Gal; Shpigelman, Lavi; Jacob, Yael; Gonen, Tal; Benjamini, Yoav; Hendler, Talma

2016-12-01

We introduce a novel method for delineating context-dependent functional brain networks whose connectivity dynamics are synchronized with the occurrence of a specific psychophysiological process of interest. In this method of context-related network dynamics analysis (CRNDA), a continuous psychophysiological index serves as a reference for clustering the whole-brain into functional networks. We applied CRNDA to fMRI data recorded during the viewing of a sadness-inducing film clip. The method reliably demarcated networks in which temporal patterns of connectivity related to the time series of reported emotional intensity. Our work successfully replicated the link between network connectivity and emotion rating in an independent sample group for seven of the networks. The demarcated networks have clear common functional denominators. Three of these networks overlap with distinct empathy-related networks, previously identified in distinct sets of studies. The other networks are related to sensorimotor processing, language, attention, and working memory. The results indicate that CRNDA, a data-driven method for network clustering that is sensitive to transient connectivity patterns, can productively and reliably demarcate networks that follow psychologically meaningful processes. Hum Brain Mapp 37:4654-4672, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

An Online Forum As a Qualitative Research Method: Practical Issues

PubMed Central

Im, Eun-Ok; Chee, Wonshik

2008-01-01

Background Despite positive aspects of online forums as a qualitative research method, very little is known about practical issues involved in using online forums for data collection, especially for a qualitative research project. Objectives The purpose of this paper is to describe the practical issues that the researchers encountered in implementing an online forum as a qualitative component of a larger study on cancer pain experience. Method Throughout the study process, the research staff recorded issues ranged from minor technical problems to serious ethical dilemmas as they arose and wrote memos about them. The memos and written records of discussions were reviewed and analyzed using the content analysis suggested by Weber. Results Two practical issues related to credibility were identified: a high response and retention rate and automatic transcripts. An issue related to dependability was the participants’ easy forgetfulness. The issues related to confirmability were difficulties in theoretical saturation and unstandardized computer and Internet jargon. A security issue related to hacking attempts was noted as well. Discussion The analysis of these issues suggests several implications for future researchers who want to use online forums as a qualitative data collection method. PMID:16849979

[Quantitative Analysis of Heavy Metals in Water with LIBS Based on Signal-to-Background Ratio].

PubMed

Hu, Li; Zhao, Nan-jing; Liu, Wen-qing; Fang, Li; Zhang, Da-hai; Wang, Yin; Meng, De Shuo; Yu, Yang; Ma, Ming-jun

2015-07-01

There are many influence factors in the precision and accuracy of the quantitative analysis with LIBS technology. According to approximately the same characteristics trend of background spectrum and characteristic spectrum along with the change of temperature through in-depth analysis, signal-to-background ratio (S/B) measurement and regression analysis could compensate the spectral line intensity changes caused by system parameters such as laser power, spectral efficiency of receiving. Because the measurement dates were limited and nonlinear, we used support vector machine (SVM) for regression algorithm. The experimental results showed that the method could improve the stability and the accuracy of quantitative analysis of LIBS, and the relative standard deviation and average relative error of test set respectively were 4.7% and 9.5%. Data fitting method based on signal-to-background ratio(S/B) is Less susceptible to matrix elements and background spectrum etc, and provides data processing reference for real-time online LIBS quantitative analysis technology.

Microfluidic direct injection method for analysis of urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) using molecularly imprinted polymers coupled on-line with LC-MS/MS.

PubMed

Shah, Kumar A; Peoples, Michael C; Halquist, Matthew S; Rutan, Sarah C; Karnes, H Thomas

2011-01-25

The work described in this paper involves development of a high-throughput on-line microfluidic sample extraction method using capillary micro-columns packed with MIP beads coupled with tandem mass spectrometry for the analysis of urinary NNAL. The method was optimized and matrix effects were evaluated and resolved. The method enabled low sample volume (200 μL) and rapid analysis of urinary NNAL by direct injection onto the microfluidic column packed with molecularly imprinted beads engineered to NNAL. The method was validated according to the FDA bioanalytical method validation guidance. The dynamic range extended from 20.0 to 2500.0 pg/mL with a percent relative error of ±5.9% and a run time of 7.00 min. The lower limit of quantitation was 20.0 pg/mL. The method was used for the analysis of NNAL and NNAL-Gluc concentrations in smokers' urine. Copyright © 2010 Elsevier B.V. All rights reserved.

Global Qualitative Flow-Path Modeling for Local State Determination in Simulation and Analysis

NASA Technical Reports Server (NTRS)

Malin, Jane T. (Inventor); Fleming, Land D. (Inventor)

1998-01-01

For qualitative modeling and analysis, a general qualitative abstraction of power transmission variables (flow and effort) for elements of flow paths includes information on resistance, net flow, permissible directions of flow, and qualitative potential is discussed. Each type of component model has flow-related variables and an associated internal flow map, connected into an overall flow network of the system. For storage devices, the implicit power transfer to the environment is represented by "virtual" circuits that include an environmental junction. A heterogeneous aggregation method simplifies the path structure. A method determines global flow-path changes during dynamic simulation and analysis, and identifies corresponding local flow state changes that are effects of global configuration changes. Flow-path determination is triggered by any change in a flow-related device variable in a simulation or analysis. Components (path elements) that may be affected are identified, and flow-related attributes favoring flow in the two possible directions are collected for each of them. Next, flow-related attributes are determined for each affected path element, based on possibly conflicting indications of flow direction. Spurious qualitative ambiguities are minimized by using relative magnitudes and permissible directions of flow, and by favoring flow sources over effort sources when comparing flow tendencies. The results are output to local flow states of affected components.

Multiway analysis methods applied to the fluorescence excitation-emission dataset for the simultaneous quantification of valsartan and amlodipine in tablets

NASA Astrophysics Data System (ADS)

Dinç, Erdal; Ertekin, Zehra Ceren; Büker, Eda

2017-09-01

In this study, excitation-emission matrix datasets, which have strong overlapping bands, were processed by using four different chemometric calibration algorithms consisting of parallel factor analysis, Tucker3, three-way partial least squares and unfolded partial least squares for the simultaneous quantitative estimation of valsartan and amlodipine besylate in tablets. In analyses, preliminary separation step was not used before the application of parallel factor analysis Tucker3, three-way partial least squares and unfolded partial least squares approaches for the analysis of the related drug substances in samples. Three-way excitation-emission matrix data array was obtained by concatenating excitation-emission matrices of the calibration set, validation set, and commercial tablet samples. The excitation-emission matrix data array was used to get parallel factor analysis, Tucker3, three-way partial least squares and unfolded partial least squares calibrations and to predict the amounts of valsartan and amlodipine besylate in samples. For all the methods, calibration and prediction of valsartan and amlodipine besylate were performed in the working concentration ranges of 0.25-4.50 μg/mL. The validity and the performance of all the proposed methods were checked by using the validation parameters. From the analysis results, it was concluded that the described two-way and three-way algorithmic methods were very useful for the simultaneous quantitative resolution and routine analysis of the related drug substances in marketed samples.

An Evaluation of Practical Applicability of Multi-Assortment Production Break-Even Analysis based on Mining Companies

NASA Astrophysics Data System (ADS)

Fuksa, Dariusz; Trzaskuś-Żak, Beata; Gałaś, Zdzisław; Utrata, Arkadiusz

2017-03-01

In the practice of mining companies, the vast majority of them produce more than one product. The analysis of the break-even, which is referred to as CVP (Cost-Volume-Profit) analysis (Wilkinson, 2005; Czopek, 2003) in their case is significantly constricted, given the necessity to include multi-assortment structure in the analysis, which may have more than 20 types of assortments (depending on the grain size) in their offer, as in the case of open-pit mines. The article presents methods of evaluation of break-even (volume and value) for both a single-assortment production and a multi-assortment production. The complexity of problem of break-even evaluation for multi-assortment production has resulted in formation of many methods, and, simultaneously, various approaches to its analysis, especially differences in accounting fixed costs, which may be either totally accounted for among particular assortments, relating to the whole company or partially accounted for among particular assortments and partially relating to the company, as a whole. The evaluation of the chosen methods of break-even analysis, given the availability of data, was based on two examples of mining companies: an open-pit mine of rock materials and an underground hard coal mine. The selection of methods was set by the available data provided by the companies. The data for the analysis comes from internal documentation of the mines - financial statements, breakdowns and cost calculations.

Relative entropy and optimization-driven coarse-graining methods in VOTCA

DOE PAGES

Mashayak, S. Y.; Jochum, Mara N.; Koschke, Konstantin; ...

2015-07-20

We discuss recent advances of the VOTCA package for systematic coarse-graining. Two methods have been implemented, namely the downhill simplex optimization and the relative entropy minimization. We illustrate the new methods by coarse-graining SPC/E bulk water and more complex water-methanol mixture systems. The CG potentials obtained from both methods are then evaluated by comparing the pair distributions from the coarse-grained to the reference atomistic simulations.We have also added a parallel analysis framework to improve the computational efficiency of the coarse-graining process.

Mach Reflection, Mach Disc, and the Associated Nozzle Free Jet Flows. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chang, I.

1973-01-01

The numerical method involving both the method of integral relations and the method of characteristics have been applied to investigate the steady flow phenomena associated with the accurrence of Mach reflection and Mach disc from nozzle flows. The solutions of triple-shock intersection are presented. The regime where Mach configuration appears is defines for the inviscid analysis. The method of integral relations developed for the blunt body problem is modified and extended to the attached shock wave and to internal nozzle flow problems.

[Evaluation of the risk related to repetitive work activities: testing of several methods proposed in the literature].

PubMed

Capodaglio, E M; Facioli, M; Bazzini, G

2001-01-01

Pathologies due to the repetitive activity of the upper limbs constitutes a growing part of the work-related musculo-skeletal disorders. At the moment, there are no universally accepted and validated methods for the description and assessment of the work-related risks. Yet, the criteria fundamentally characterizing the exposure are rather clear and even. This study reports a practical example of the application of some recent risk assessment methods proposed in the literature, combining objective and subjective measures obtained on the field, with the traditional activity analysis.

Discrete choice experiments of pharmacy services: a systematic review.

PubMed

Vass, Caroline; Gray, Ewan; Payne, Katherine

2016-06-01

Background Two previous systematic reviews have summarised the application of discrete choice experiments to value preferences for pharmacy services. These reviews identified a total of twelve studies and described how discrete choice experiments have been used to value pharmacy services but did not describe or discuss the application of methods used in the design or analysis. Aims (1) To update the most recent systematic review and critically appraise current discrete choice experiments of pharmacy services in line with published reporting criteria and; (2) To provide an overview of key methodological developments in the design and analysis of discrete choice experiments. Methods The review used a comprehensive strategy to identify eligible studies (published between 1990 and 2015) by searching electronic databases for key terms related to discrete choice and best-worst scaling (BWS) experiments. All healthcare choice experiments were then hand-searched for key terms relating to pharmacy. Data were extracted using a published checklist. Results A total of 17 discrete choice experiments eliciting preferences for pharmacy services were identified for inclusion in the review. No BWS studies were identified. The studies elicited preferences from a variety of populations (pharmacists, patients, students) for a range of pharmacy services. Most studies were from a United Kingdom setting, although examples from Europe, Australia and North America were also identified. Discrete choice experiments for pharmacy services tended to include more attributes than non-pharmacy choice experiments. Few studies reported the use of qualitative research methods in the design and interpretation of the experiments (n = 9) or use of new methods of analysis to identify and quantify preference and scale heterogeneity (n = 4). No studies reported the use of Bayesian methods in their experimental design. Conclusion Incorporating more sophisticated methods in the design of pharmacy-related discrete choice experiments could help researchers produce more efficient experiments which are better suited to valuing complex pharmacy services. Pharmacy-related discrete choice experiments could also benefit from more sophisticated analytical techniques such as investigations into scale and preference heterogeneity. Employing these sophisticated methods for both design and analysis could extend the usefulness of discrete choice experiments to inform health and pharmacy policy.

How Social Network Position Relates to Knowledge Building in Online Learning Communities

ERIC Educational Resources Information Center

Wang, Lu

2010-01-01

Social Network Analysis, Statistical Analysis, Content Analysis and other research methods were used to research online learning communities at Capital Normal University, Beijing. Analysis of the two online courses resulted in the following conclusions: (1) Social networks of the two online courses form typical core-periphery structures; (2)…

Evaluation of methods for measuring relative permeability of anhydride from the Salado Formation: Sensitivity analysis and data reduction

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

Christiansen, R.L.; Kalbus, J.S.; Howarth, S.M.

This report documents, demonstrates, evaluates, and provides theoretical justification for methods used to convert experimental data into relative permeability relationships. The report facilities accurate determination of relative permeabilities of anhydride rock samples from the Salado Formation at the Waste Isolation Pilot Plant (WIPP). Relative permeability characteristic curves are necessary for WIPP Performance Assessment (PA) predictions of the potential for flow of waste-generated gas from the repository and brine flow into repository. This report follows Christiansen and Howarth (1995), a comprehensive literature review of methods for measuring relative permeability. It focuses on unsteady-state experiments and describes five methods for obtaining relativemore » permeability relationships from unsteady-state experiments. Unsteady-state experimental methods were recommended for relative permeability measurements of low-permeability anhydrite rock samples form the Salado Formation because these tests produce accurate relative permeability information and take significantly less time to complete than steady-state tests. Five methods for obtaining relative permeability relationships from unsteady-state experiments are described: the Welge method, the Johnson-Bossler-Naumann method, the Jones-Roszelle method, the Ramakrishnan-Cappiello method, and the Hagoort method. A summary, an example of the calculations, and a theoretical justification are provided for each of the five methods. Displacements in porous media are numerically simulated for the calculation examples. The simulated product data were processed using the methods, and the relative permeabilities obtained were compared with those input to the numerical model. A variety of operating conditions were simulated to show sensitivity of production behavior to rock-fluid properties.« less

Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2014-01-01

Gene set enrichment analysis (GSEA) is an important approach to the analysis of coordinate expression changes at a pathway level. Although many statistical and computational methods have been proposed for GSEA, the issue of a concordant integrative GSEA of multiple expression data sets has not been well addressed. Among different related data sets collected for the same or similar study purposes, it is important to identify pathways or gene sets with concordant enrichment. We categorize the underlying true states of differential expression into three representative categories: no change, positive change and negative change. Due to data noise, what we observe from experiments may not indicate the underlying truth. Although these categories are not observed in practice, they can be considered in a mixture model framework. Then, we define the mathematical concept of concordant gene set enrichment and calculate its related probability based on a three-component multivariate normal mixture model. The related false discovery rate can be calculated and used to rank different gene sets. We used three published lung cancer microarray gene expression data sets to illustrate our proposed method. One analysis based on the first two data sets was conducted to compare our result with a previous published result based on a GSEA conducted separately for each individual data set. This comparison illustrates the advantage of our proposed concordant integrative gene set enrichment analysis. Then, with a relatively new and larger pathway collection, we used our method to conduct an integrative analysis of the first two data sets and also all three data sets. Both results showed that many gene sets could be identified with low false discovery rates. A consistency between both results was also observed. A further exploration based on the KEGG cancer pathway collection showed that a majority of these pathways could be identified by our proposed method. This study illustrates that we can improve detection power and discovery consistency through a concordant integrative analysis of multiple large-scale two-sample gene expression data sets.

Model-free fMRI group analysis using FENICA.

PubMed

Schöpf, V; Windischberger, C; Robinson, S; Kasess, C H; Fischmeister, F PhS; Lanzenberger, R; Albrecht, J; Kleemann, A M; Kopietz, R; Wiesmann, M; Moser, E

2011-03-01

Exploratory analysis of functional MRI data allows activation to be detected even if the time course differs from that which is expected. Independent Component Analysis (ICA) has emerged as a powerful approach, but current extensions to the analysis of group studies suffer from a number of drawbacks: they can be computationally demanding, results are dominated by technical and motion artefacts, and some methods require that time courses be the same for all subjects or that templates be defined to identify common components. We have developed a group ICA (gICA) method which is based on single-subject ICA decompositions and the assumption that the spatial distribution of signal changes in components which reflect activation is similar between subjects. This approach, which we have called Fully Exploratory Network Independent Component Analysis (FENICA), identifies group activation in two stages. ICA is performed on the single-subject level, then consistent components are identified via spatial correlation. Group activation maps are generated in a second-level GLM analysis. FENICA is applied to data from three studies employing a wide range of stimulus and presentation designs. These are an event-related motor task, a block-design cognition task and an event-related chemosensory experiment. In all cases, the group maps identified by FENICA as being the most consistent over subjects correspond to task activation. There is good agreement between FENICA results and regions identified in prior GLM-based studies. In the chemosensory task, additional regions are identified by FENICA and temporal concatenation ICA that we show is related to the stimulus, but exhibit a delayed response. FENICA is a fully exploratory method that allows activation to be identified without assumptions about temporal evolution, and isolates activation from other sources of signal fluctuation in fMRI. It has the advantage over other gICA methods that it is computationally undemanding, spotlights components relating to activation rather than artefacts, allows the use of familiar statistical thresholding through deployment of a higher level GLM analysis and can be applied to studies where the paradigm is different for all subjects. Copyright © 2010 Elsevier Inc. All rights reserved.

Task-Related Edge Density (TED)—A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain

PubMed Central

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach “Task-related Edge Density” (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function. PMID:27341204

Task-Related Edge Density (TED)-A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain.

PubMed

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.

New method for designing serial resonant power converters

NASA Astrophysics Data System (ADS)

Hinov, Nikolay

2017-12-01

In current work is presented one comprehensive method for design of serial resonant energy converters. The method is based on new simplified approach in analysis of such kind power electronic devices. It is grounded on supposing resonant mode of operation when finding relation between input and output voltage regardless of other operational modes (when controlling frequency is below or above resonant frequency). This approach is named `quasiresonant method of analysis', because it is based on assuming that all operational modes are `sort of' resonant modes. An estimation of error was made because of the a.m. hypothesis and is compared to the classic analysis. The `quasiresonant method' of analysis gains two main advantages: speed and easiness in designing of presented power circuits. Hence it is very useful in practice and in teaching Power Electronics. Its applicability is proven with mathematic modelling and computer simulation.

Performance Improvement of Power Analysis Attacks on AES with Encryption-Related Signals

NASA Astrophysics Data System (ADS)

Lee, You-Seok; Lee, Young-Jun; Han, Dong-Guk; Kim, Ho-Won; Kim, Hyoung-Nam

A power analysis attack is a well-known side-channel attack but the efficiency of the attack is frequently degraded by the existence of power components, irrelative to the encryption included in signals used for the attack. To enhance the performance of the power analysis attack, we propose a preprocessing method based on extracting encryption-related parts from the measured power signals. Experimental results show that the attacks with the preprocessed signals detect correct keys with much fewer signals, compared to the conventional power analysis attacks.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

Aeroelastic Stability and Response of Rotating Structures

NASA Technical Reports Server (NTRS)

Keith, Theo G., Jr.; Reddy, Tondapu

2004-01-01

A summary of the work performed under NASA grant is presented. More details can be found in the cited references. This grant led to the development of relatively faster aeroelastic analysis methods for predicting flutter and forced response in fans, compressors, and turbines using computational fluid dynamic (CFD) methods. These methods are based on linearized two- and three-dimensional, unsteady, nonlinear aerodynamic equations. During the period of the grant, aeroelastic analysis that includes the effects of uncertainties in the design variables has also been developed.

A simple method for processing data with least square method

NASA Astrophysics Data System (ADS)

Wang, Chunyan; Qi, Liqun; Chen, Yongxiang; Pang, Guangning

2017-08-01

The least square method is widely used in data processing and error estimation. The mathematical method has become an essential technique for parameter estimation, data processing, regression analysis and experimental data fitting, and has become a criterion tool for statistical inference. In measurement data analysis, the distribution of complex rules is usually based on the least square principle, i.e., the use of matrix to solve the final estimate and to improve its accuracy. In this paper, a new method is presented for the solution of the method which is based on algebraic computation and is relatively straightforward and easy to understand. The practicability of this method is described by a concrete example.

Advancing the application of systems thinking in health: provider payment and service supply behaviour and incentives in the Ghana National Health Insurance Scheme--a systems approach.

PubMed

Agyepong, Irene A; Aryeetey, Geneieve C; Nonvignon, Justice; Asenso-Boadi, Francis; Dzikunu, Helen; Antwi, Edward; Ankrah, Daniel; Adjei-Acquah, Charles; Esena, Reuben; Aikins, Moses; Arhinful, Daniel K

2014-08-05

Assuring equitable universal access to essential health services without exposure to undue financial hardship requires adequate resource mobilization, efficient use of resources, and attention to quality and responsiveness of services. The way providers are paid is a critical part of this process because it can create incentives and patterns of behaviour related to supply. The objective of this work was to describe provider behaviour related to supply of health services to insured clients in Ghana and the influence of provider payment methods on incentives and behaviour. A mixed methods study involving grey and published literature reviews, as well as health management information system and primary data collection and analysis was used. Primary data collection involved in-depth interviews, observations of time spent obtaining service, prescription analysis, and exit interviews with clients. Qualitative data was analysed manually to draw out themes, commonalities, and contrasts. Quantitative data was analysed in Excel and Stata. Causal loop and cause tree diagrams were used to develop a qualitative explanatory model of provider supply incentives and behaviour related to payment method in context. There are multiple provider payment methods in the Ghanaian health system. National Health Insurance provider payment methods are the most recent additions. At the time of the study, the methods used nationwide were the Ghana Diagnostic Related Groupings payment for services and an itemized and standardized fee schedule for medicines. The influence of provider payment method on supply behaviour was sometimes intuitive and sometimes counter intuitive. It appeared to be related to context and the interaction of the methods with context and each other rather than linearly to any given method. As countries work towards Universal Health Coverage, there is a need to holistically design, implement, and manage provider payment methods reforms from systems rather than linear perspectives, since the latter fail to recognize the effects of context and the between-methods and context interactions in producing net effects.

Modeling and Analysis of Wrinkled Membranes: An Overview

NASA Technical Reports Server (NTRS)

Yang, B.; Ding, H.; Lou, M.; Fang, H.; Broduer, Steve (Technical Monitor)

2001-01-01

Thin-film membranes are basic elements of a variety of space inflatable/deployable structures. Wrinkling degrades the performance and reliability of these membrane structures, and hence has been a topic of continued interest. Wrinkling analysis of membranes for general geometry and arbitrary boundary conditions is quite challenging. The objective of this presentation is two-fold. Firstly, the existing models of wrinkled membranes and related numerical solution methods are reviewed. The important issues to be discussed are the capability of a membrane model to characterize taut, wrinkled and slack states of membranes in a consistent and physically reasonable manner; the ability of a wrinkling analysis method to predict the formation and growth of wrinkled regions, and to determine out-of-plane deformation and wrinkled waves; the convergence of a numerical solution method for wrinkling analysis; and the compatibility of a wrinkling analysis with general-purpose finite element codes. According to this review, several opening issues in modeling and analysis of wrinkled membranes that are to be addressed in future research are summarized, The second objective of this presentation is to discuss a newly developed membrane model of two viable parameters (2-VP model) and associated parametric finite element method (PFEM) for wrinkling analysis are introduced. The innovations and advantages of the proposed membrane model and PFEM-based wrinkling analysis are: (1) Via a unified stress-strain relation; the 2-VP model treat the taut, wrinkled, and slack states of membranes consistently; (2) The PFEM-based wrinkling analysis has guaranteed convergence; (3) The 2-VP model along with PFEM is capable of predicting membrane out-of-plane deformations; and (4) The PFEM can be integrated into any existing finite element code. Preliminary numerical examples are also included in this presentation to demonstrate the 2-VP model and PFEM-based wrinkling analysis approach.

Introduction to Psychology and Leadership. Typological Analysis of Student Characteristics: Preliminary Report.

ERIC Educational Resources Information Center

Bessemer, David W.; Shrage, Jules H.

Recommendations for an alternative plan, based on typological analysis techniques, for the evaluation of student characteristics related to media, presentation design, and academic performance are presented. Difficulties with present evaluation plans are discussed, and different methods of typological analysis are described. Included are…

A functional U-statistic method for association analysis of sequencing data.

PubMed

Jadhav, Sneha; Tong, Xiaoran; Lu, Qing

2017-11-01

Although sequencing studies hold great promise for uncovering novel variants predisposing to human diseases, the high dimensionality of the sequencing data brings tremendous challenges to data analysis. Moreover, for many complex diseases (e.g., psychiatric disorders) multiple related phenotypes are collected. These phenotypes can be different measurements of an underlying disease, or measurements characterizing multiple related diseases for studying common genetic mechanism. Although jointly analyzing these phenotypes could potentially increase the power of identifying disease-associated genes, the different types of phenotypes pose challenges for association analysis. To address these challenges, we propose a nonparametric method, functional U-statistic method (FU), for multivariate analysis of sequencing data. It first constructs smooth functions from individuals' sequencing data, and then tests the association of these functions with multiple phenotypes by using a U-statistic. The method provides a general framework for analyzing various types of phenotypes (e.g., binary and continuous phenotypes) with unknown distributions. Fitting the genetic variants within a gene using a smoothing function also allows us to capture complexities of gene structure (e.g., linkage disequilibrium, LD), which could potentially increase the power of association analysis. Through simulations, we compared our method to the multivariate outcome score test (MOST), and found that our test attained better performance than MOST. In a real data application, we apply our method to the sequencing data from Minnesota Twin Study (MTS) and found potential associations of several nicotine receptor subunit (CHRN) genes, including CHRNB3, associated with nicotine dependence and/or alcohol dependence. © 2017 WILEY PERIODICALS, INC.

Alcohol-related hot-spot analysis and prediction : final report.

DOT National Transportation Integrated Search

2017-05-01

This project developed methods to more accurately identify alcohol-related crash hot spots, ultimately allowing for more effective and efficient enforcement and safety campaigns. Advancements in accuracy came from improving the calculation of spatial...

A Statistical Method for Synthesizing Mediation Analyses Using the Product of Coefficient Approach Across Multiple Trials

PubMed Central

Huang, Shi; MacKinnon, David P.; Perrino, Tatiana; Gallo, Carlos; Cruden, Gracelyn; Brown, C Hendricks

2016-01-01

Mediation analysis often requires larger sample sizes than main effect analysis to achieve the same statistical power. Combining results across similar trials may be the only practical option for increasing statistical power for mediation analysis in some situations. In this paper, we propose a method to estimate: 1) marginal means for mediation path a, the relation of the independent variable to the mediator; 2) marginal means for path b, the relation of the mediator to the outcome, across multiple trials; and 3) the between-trial level variance-covariance matrix based on a bivariate normal distribution. We present the statistical theory and an R computer program to combine regression coefficients from multiple trials to estimate a combined mediated effect and confidence interval under a random effects model. Values of coefficients a and b, along with their standard errors from each trial are the input for the method. This marginal likelihood based approach with Monte Carlo confidence intervals provides more accurate inference than the standard meta-analytic approach. We discuss computational issues, apply the method to two real-data examples and make recommendations for the use of the method in different settings. PMID:28239330

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis

PubMed Central

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization. PMID:29377956

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis.

PubMed

Zu, Xianghuan; Yang, Chuanlei; Wang, Hechun; Wang, Yinyan

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.

[Proposal of a method for collective analysis of work-related accidents in the hospital setting].

PubMed

Osório, Claudia; Machado, Jorge Mesquita Huet; Minayo-Gomez, Carlos

2005-01-01

The article presents a method for the analysis of work-related accidents in hospitals, with the double aim of analyzing accidents in light of actual work activity and enhancing the vitality of the various professions that comprise hospital work. This process involves both research and intervention, combining knowledge output with training of health professionals, fostering expanded participation by workers in managing their daily work. The method consists of stimulating workers to recreate the situation in which a given accident occurred, shifting themselves to the position of observers of their own work. In the first stage of analysis, workers are asked to show the work analyst how the accident occurred; in the second stage, the work accident victim and analyst jointly record the described series of events in a diagram; in the third, the resulting record is re-discussed and further elaborated; in the fourth, the work accident victim and analyst evaluate and implement measures aimed to prevent the accident from recurring. The article concludes by discussing the method's possibilities and limitations in the hospital setting.

Reevaluation of analytical methods for photogenerated singlet oxygen

PubMed Central

Nakamura, Keisuke; Ishiyama, Kirika; Ikai, Hiroyo; Kanno, Taro; Sasaki, Keiichi; Niwano, Yoshimi; Kohno, Masahiro

2011-01-01

The aim of the present study is to compare different analytical methods for singlet oxygen and to discuss an appropriate way to evaluate the yield of singlet oxygen photogenerated from photosensitizers. Singlet oxygen photogenerated from rose bengal was evaluated by electron spin resonance analysis using sterically hindered amines, spectrophotometric analysis of 1,3-diphenylisobenzofuran oxidation, and analysis of fluorescent probe (Singlet Oxygen Sensor Green®). All of the analytical methods could evaluate the relative yield of singlet oxygen. The sensitivity of the analytical methods was 1,3-diphenylisobenzofuran < electron spin resonance < Singlet Oxygen Sensor Green®. However, Singlet Oxygen Sensor Green® could be used only when the concentration of rose bengal was very low (<1 µM). In addition, since the absorption spectra of 1,3-diphenylisobenzofuran is considerably changed by irradiation of 405 nm laser, photosensitizers which are excited by light with a wavelength of around 400 nm such as hematoporphyrin cannot be used in the 1,3-diphenylisobenzofuran oxidation method. On the other hand, electron spin resonance analysis using a sterically hindered amine, especially 2,2,6,6-tetramethyl-4-piperidinol and 2,2,5,5-tetramethyl-3-pyrroline-3-carboxamide, had proper sensitivity and wide detectable range for the yield of photogenerated singlet oxygen. Therefore, in photodynamic therapy, it is suggested that the relative yield of singlet oxygen generated by various photosensitizers can be evaluated properly by electron spin resonance analysis. PMID:21980223

Systematic text condensation: a strategy for qualitative analysis.

PubMed

Malterud, Kirsti

2012-12-01

To present background, principles, and procedures for a strategy for qualitative analysis called systematic text condensation and discuss this approach compared with related strategies. Giorgi's psychological phenomenological analysis is the point of departure and inspiration for systematic text condensation. The basic elements of Giorgi's method and the elaboration of these in systematic text condensation are presented, followed by a detailed description of procedures for analysis according to systematic text condensation. Finally, similarities and differences compared with other frequently applied methods for qualitative analysis are identified, as the foundation of a discussion of strengths and limitations of systematic text condensation. Systematic text condensation is a descriptive and explorative method for thematic cross-case analysis of different types of qualitative data, such as interview studies, observational studies, and analysis of written texts. The method represents a pragmatic approach, although inspired by phenomenological ideas, and various theoretical frameworks can be applied. The procedure consists of the following steps: 1) total impression - from chaos to themes; 2) identifying and sorting meaning units - from themes to codes; 3) condensation - from code to meaning; 4) synthesizing - from condensation to descriptions and concepts. Similarities and differences comparing systematic text condensation with other frequently applied qualitative methods regarding thematic analysis, theoretical methodological framework, analysis procedures, and taxonomy are discussed. Systematic text condensation is a strategy for analysis developed from traditions shared by most of the methods for analysis of qualitative data. The method offers the novice researcher a process of intersubjectivity, reflexivity, and feasibility, while maintaining a responsible level of methodological rigour.

Scaling of mode shapes from operational modal analysis using harmonic forces

NASA Astrophysics Data System (ADS)

Brandt, A.; Berardengo, M.; Manzoni, S.; Cigada, A.

2017-10-01

This paper presents a new method for scaling mode shapes obtained by means of operational modal analysis. The method is capable of scaling mode shapes on any structure, also structures with closely coupled modes, and the method can be used in the presence of ambient vibration from traffic or wind loads, etc. Harmonic excitation can be relatively easily accomplished by using general-purpose actuators, also for force levels necessary for driving large structures such as bridges and highrise buildings. The signal processing necessary for mode shape scaling by the proposed method is simple and the method can easily be implemented in most measurement systems capable of generating a sine wave output. The tests necessary to scale the modes are short compared to typical operational modal analysis test time. The proposed method is thus easy to apply and inexpensive relative to some other methods for scaling mode shapes that are available in literature. Although it is not necessary per se, we propose to excite the structure at, or close to, the eigenfrequencies of the modes to be scaled, since this provides better signal-to-noise ratio in the response sensors, thus permitting the use of smaller actuators. An extensive experimental activity on a real structure was carried out and the results reported demonstrate the feasibility and accuracy of the proposed method. Since the method utilizes harmonic excitation for the mode shape scaling, we propose to call the method OMAH.

Estimation of railroad capacity using parametric methods.

DOT National Transportation Integrated Search

2013-12-01

This paper reviews different methodologies used for railroad capacity estimation and presents a user-friendly method to measure capacity. The objective of this paper is to use multivariate regression analysis to develop a continuous relation of the d...

Comprehensive Deployment Method for Technical Characteristics Base on Multi-failure Modes Correlation Analysis

NASA Astrophysics Data System (ADS)

Zheng, W.; Gao, J. M.; Wang, R. X.; Chen, K.; Jiang, Y.

2017-12-01

This paper put forward a new method of technical characteristics deployment based on Reliability Function Deployment (RFD) by analysing the advantages and shortages of related research works on mechanical reliability design. The matrix decomposition structure of RFD was used to describe the correlative relation between failure mechanisms, soft failures and hard failures. By considering the correlation of multiple failure modes, the reliability loss of one failure mode to the whole part was defined, and a calculation and analysis model for reliability loss was presented. According to the reliability loss, the reliability index value of the whole part was allocated to each failure mode. On the basis of the deployment of reliability index value, the inverse reliability method was employed to acquire the values of technology characteristics. The feasibility and validity of proposed method were illustrated by a development case of machining centre’s transmission system.

Frequency Domain Analysis of Sensor Data for Event Classification in Real-Time Robot Assisted Deburring

PubMed Central

Pappachan, Bobby K; Caesarendra, Wahyu; Tjahjowidodo, Tegoeh; Wijaya, Tomi

2017-01-01

Process monitoring using indirect methods relies on the usage of sensors. Using sensors to acquire vital process related information also presents itself with the problem of big data management and analysis. Due to uncertainty in the frequency of events occurring, a higher sampling rate is often used in real-time monitoring applications to increase the chances of capturing and understanding all possible events related to the process. Advanced signal processing methods are used to further decipher meaningful information from the acquired data. In this research work, power spectrum density (PSD) of sensor data acquired at sampling rates between 40–51.2 kHz was calculated and the corelation between PSD and completed number of cycles/passes is presented. Here, the progress in number of cycles/passes is the event this research work intends to classify and the algorithm used to compute PSD is Welch’s estimate method. A comparison between Welch’s estimate method and statistical methods is also discussed. A clear co-relation was observed using Welch’s estimate to classify the number of cycles/passes. The paper also succeeds in classifying vibration signal generated by the spindle from the vibration signal acquired during finishing process. PMID:28556809

Reliable differentiation of Meyerozyma guilliermondii from Meyerozyma caribbica by internal transcribed spacer restriction fingerprinting.

PubMed

Romi, Wahengbam; Keisam, Santosh; Ahmed, Giasuddin; Jeyaram, Kumaraswamy

2014-02-28

Meyerozyma guilliermondii (anamorph Candida guilliermondii) and Meyerozyma caribbica (anamorph Candida fermentati) are closely related species of the genetically heterogenous M. guilliermondii complex. Conventional phenotypic methods frequently misidentify the species within this complex and also with other species of the Saccharomycotina CTG clade. Even the long-established sequencing of large subunit (LSU) rRNA gene remains ambiguous. We also faced similar problem during identification of yeast isolates of M. guilliermondii complex from indigenous bamboo shoot fermentation in North East India. There is a need for development of reliable and accurate identification methods for these closely related species because of their increasing importance as emerging infectious yeasts and associated biotechnological attributes. We targeted the highly variable internal transcribed spacer (ITS) region (ITS1-5.8S-ITS2) and identified seven restriction enzymes through in silico analysis for differentiating M. guilliermondii from M. caribbica. Fifty five isolates of M. guilliermondii complex which could not be delineated into species-specific taxonomic ranks by API 20 C AUX and LSU rRNA gene D1/D2 sequencing were subjected to ITS-restriction fragment length polymorphism (ITS-RFLP) analysis. TaqI ITS-RFLP distinctly differentiated the isolates into M. guilliermondii (47 isolates) and M. caribbica (08 isolates) with reproducible species-specific patterns similar to the in silico prediction. The reliability of this method was validated by ITS1-5.8S-ITS2 sequencing, mitochondrial DNA RFLP and electrophoretic karyotyping. We herein described a reliable ITS-RFLP method for distinct differentiation of frequently misidentified M. guilliermondii from M. caribbica. Even though in silico analysis differentiated other closely related species of M. guilliermondii complex from the above two species, it is yet to be confirmed by in vitro analysis using reference strains. This method can be used as a reliable tool for rapid and accurate identification of closely related species of M. guilliermondii complex and for differentiating emerging infectious yeasts of the Saccharomycotina CTG clade.

Precise determination of N-acetylcysteine in pharmaceuticals by microchip electrophoresis.

PubMed

Rudašová, Marína; Masár, Marián

2016-01-01

A novel microchip electrophoresis method for the rapid and high-precision determination of N-acetylcysteine, a pharmaceutically active ingredient, in mucolytics has been developed. Isotachophoresis separations were carried out at pH 6.0 on a microchip with conductivity detection. The methods of external calibration and internal standard were used to evaluate the results. The internal standard method effectively eliminated variations in various working parameters, mainly run-to-run fluctuations of an injected volume. The repeatability and accuracy of N-acetylcysteine determination in all mucolytic preparations tested (Solmucol 90 and 200, and ACC Long 600) were more than satisfactory with the relative standard deviation and relative error values <0.7 and <1.9%, respectively. A recovery range of 99-101% of N-acetylcysteine in the analyzed pharmaceuticals predetermines the proposed method for accurate analysis as well. This work, in general, indicates analytical possibilities of microchip isotachophoresis for the quantitative analysis of simplified samples such as pharmaceuticals that contain the analyte(s) at relatively high concentrations. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spectroscopic Chemical Analysis Methods and Apparatus

NASA Technical Reports Server (NTRS)

Hug, William F.; Reid, Ray D.

2012-01-01

This invention relates to non-contact spectroscopic methods and apparatus for performing chemical analysis and the ideal wavelengths and sources needed for this analysis. It employs deep ultraviolet (200- to 300-nm spectral range) electron-beam-pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor lightemitting devices, and hollow cathode metal ion lasers. Three achieved goals for this innovation are to reduce the size (under 20 L), reduce the weight [under 100 lb (.45 kg)], and reduce the power consumption (under 100 W). This method can be used in microscope or macroscope to provide measurement of Raman and/or native fluorescence emission spectra either by point-by-point measurement, or by global imaging of emissions within specific ultraviolet spectral bands. In other embodiments, the method can be used in analytical instruments such as capillary electrophoresis, capillary electro-chromatography, high-performance liquid chromatography, flow cytometry, and related instruments for detection and identification of unknown analytes using a combination of native fluorescence and/or Raman spectroscopic methods. This design provides an electron-beampumped semiconductor radiation-producing method, or source, that can emit at a wavelength (or wavelengths) below 300 nm, e.g. in the deep ultraviolet between about 200 and 300 nm, and more preferably less than 260 nm. In some variations, the method is to produce incoherent radiation, while in other implementations it produces laser radiation. In some variations, this object is achieved by using an AlGaN emission medium, while in other implementations a diamond emission medium may be used. This instrument irradiates a sample with deep UV radiation, and then uses an improved filter for separating wavelengths to be detected. This provides a multi-stage analysis of the sample. To avoid the difficulties related to producing deep UV semiconductor sources, a pumping approach has been developed that uses ballistic electron beam injection directly into the active region of a wide bandgap semiconductor material.

An Excel‐based implementation of the spectral method of action potential alternans analysis

PubMed Central

Pearman, Charles M.

2014-01-01

Abstract Action potential (AP) alternans has been well established as a mechanism of arrhythmogenesis and sudden cardiac death. Proper interpretation of AP alternans requires a robust method of alternans quantification. Traditional methods of alternans analysis neglect higher order periodicities that may have greater pro‐arrhythmic potential than classical 2:1 alternans. The spectral method of alternans analysis, already widely used in the related study of microvolt T‐wave alternans, has also been used to study AP alternans. Software to meet the specific needs of AP alternans analysis is not currently available in the public domain. An AP analysis tool is implemented here, written in Visual Basic for Applications and using Microsoft Excel as a shell. This performs a sophisticated analysis of alternans behavior allowing reliable distinction of alternans from random fluctuations, quantification of alternans magnitude, and identification of which phases of the AP are most affected. In addition, the spectral method has been adapted to allow detection and quantification of higher order regular oscillations. Analysis of action potential morphology is also performed. A simple user interface enables easy import, analysis, and export of collated results. PMID:25501439

A POSTERIORI ERROR ANALYSIS OF TWO STAGE COMPUTATION METHODS WITH APPLICATION TO EFFICIENT DISCRETIZATION AND THE PARAREAL ALGORITHM.

PubMed

Chaudhry, Jehanzeb Hameed; Estep, Don; Tavener, Simon; Carey, Varis; Sandelin, Jeff

2016-01-01

We consider numerical methods for initial value problems that employ a two stage approach consisting of solution on a relatively coarse discretization followed by solution on a relatively fine discretization. Examples include adaptive error control, parallel-in-time solution schemes, and efficient solution of adjoint problems for computing a posteriori error estimates. We describe a general formulation of two stage computations then perform a general a posteriori error analysis based on computable residuals and solution of an adjoint problem. The analysis accommodates various variations in the two stage computation and in formulation of the adjoint problems. We apply the analysis to compute "dual-weighted" a posteriori error estimates, to develop novel algorithms for efficient solution that take into account cancellation of error, and to the Parareal Algorithm. We test the various results using several numerical examples.

Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening

PubMed Central

Pan, Rui; Wang, Hansheng; Li, Runze

2016-01-01

This paper is concerned with the problem of feature screening for multi-class linear discriminant analysis under ultrahigh dimensional setting. We allow the number of classes to be relatively large. As a result, the total number of relevant features is larger than usual. This makes the related classification problem much more challenging than the conventional one, where the number of classes is small (very often two). To solve the problem, we propose a novel pairwise sure independence screening method for linear discriminant analysis with an ultrahigh dimensional predictor. The proposed procedure is directly applicable to the situation with many classes. We further prove that the proposed method is screening consistent. Simulation studies are conducted to assess the finite sample performance of the new procedure. We also demonstrate the proposed methodology via an empirical analysis of a real life example on handwritten Chinese character recognition. PMID:28127109

A comparison of three methods of assessing differential item functioning (DIF) in the Hospital Anxiety Depression Scale: ordinal logistic regression, Rasch analysis and the Mantel chi-square procedure.

PubMed

Cameron, Isobel M; Scott, Neil W; Adler, Mats; Reid, Ian C

2014-12-01

It is important for clinical practice and research that measurement scales of well-being and quality of life exhibit only minimal differential item functioning (DIF). DIF occurs where different groups of people endorse items in a scale to different extents after being matched by the intended scale attribute. We investigate the equivalence or otherwise of common methods of assessing DIF. Three methods of measuring age- and sex-related DIF (ordinal logistic regression, Rasch analysis and Mantel χ(2) procedure) were applied to Hospital Anxiety Depression Scale (HADS) data pertaining to a sample of 1,068 patients consulting primary care practitioners. Three items were flagged by all three approaches as having either age- or sex-related DIF with a consistent direction of effect; a further three items identified did not meet stricter criteria for important DIF using at least one method. When applying strict criteria for significant DIF, ordinal logistic regression was slightly less sensitive. Ordinal logistic regression, Rasch analysis and contingency table methods yielded consistent results when identifying DIF in the HADS depression and HADS anxiety scales. Regardless of methods applied, investigators should use a combination of statistical significance, magnitude of the DIF effect and investigator judgement when interpreting the results.

Further Insight and Additional Inference Methods for Polynomial Regression Applied to the Analysis of Congruence

ERIC Educational Resources Information Center

Cohen, Ayala; Nahum-Shani, Inbal; Doveh, Etti

2010-01-01

In their seminal paper, Edwards and Parry (1993) presented the polynomial regression as a better alternative to applying difference score in the study of congruence. Although this method is increasingly applied in congruence research, its complexity relative to other methods for assessing congruence (e.g., difference score methods) was one of the…

Chromatographic immunoassays: strategies and recent developments in the analysis of drugs and biological agents

PubMed Central

Matsuda, Ryan; Rodriguez, Elliott; Suresh, Doddavenkatanna; Hage, David S

2015-01-01

A chromatographic immunoassay is a technique in which an antibody or antibody-related agent is used as part of a chromatographic system for the isolation or measurement of a specific target. Various binding agents, detection methods, supports and assay formats have been developed for this group of methods, and applications have been reported that range from drugs, hormones and herbicides to peptides, proteins and bacteria. This review discusses the general principles and applications of chromatographic immunoassays, with an emphasis being given to methods and formats that have been developed for the analysis of drugs and biological agents. The relative advantages or limitations of each format are discussed. Recent developments and research in this field, as well as possible future directions, are also considered. PMID:26571109

A study of the application of power-spectral methods of generalized harmonic analysis to gust loads on airplanes

NASA Technical Reports Server (NTRS)

Press, Harry; Mazelsky, Bernard

1954-01-01

The applicability of some results from the theory of generalized harmonic analysis (or power-spectral analysis) to the analysis of gust loads on airplanes in continuous rough air is examined. The general relations for linear systems between power spectrums of a random input disturbance and an output response are used to relate the spectrum of airplane load in rough air to the spectrum of atmospheric gust velocity. The power spectrum of loads is shown to provide a measure of the load intensity in terms of the standard deviation (root mean square) of the load distribution for an airplane in flight through continuous rough air. For the case of a load output having a normal distribution, which appears from experimental evidence to apply to homogeneous rough air, the standard deviation is shown to describe the probability distribution of loads or the proportion of total time that the load has given values. Thus, for airplane in flight through homogeneous rough air, the probability distribution of loads may be determined from a power-spectral analysis. In order to illustrate the application of power-spectral analysis to gust-load analysis and to obtain an insight into the relations between loads and airplane gust-response characteristics, two selected series of calculations are presented. The results indicate that both methods of analysis yield results that are consistent to a first approximation.

An online forum as a qualitative research method: practical issues.

PubMed

Im, Eun-Ok; Chee, Wonshik

2006-01-01

Despite the positive aspects of online forums as a qualitative research method, very little is known on the practical issues involved in using online forums for data collection, especially for a qualitative research project. The aim of this study was to describe the practical issues encountered in implementing an online forum as a qualitative component of a larger study on cancer pain experience. Throughout the study process, the research staff recorded issues ranging from minor technical problems to serious ethical dilemmas as they arose and wrote memos about them. The memos and written records of the discussions were reviewed and analyzed using content analysis. Two practical issues related to credibility were identified: (a) a high response and retention rate and (b) automatic transcripts. An issue related to dependability was the participants' forgetfulness. The issues related to confirmability were difficulties in theoretical saturation and unstandardized computer and Internet jargon. A security issue related to hacking attempts was noted as well. The analysis of these issues suggests several implications for future researchers who want to use online forums as a qualitative data collection method.

Raman structural study of melt-mixed blends of isotactic polypropylene with polyethylene of various densities

NASA Astrophysics Data System (ADS)

Prokhorov, K. A.; Nikolaeva, G. Yu; Sagitova, E. A.; Pashinin, P. P.; Guseva, M. A.; Shklyaruk, B. F.; Gerasin, V. A.

2018-04-01

We report a Raman structural study of melt-mixed blends of isotactic polypropylene with two grades of polyethylene: linear high-density and branched low-density polyethylenes. Raman methods, which had been suggested for the analysis of neat polyethylene and isotactic polypropylene, were modified in this study for quantitative analysis of polyethylene/polypropylene blends. We revealed the dependence of the degree of crystallinity and conformational composition of macromolecules in the blends on relative content of the blend components and preparation conditions (quenching or annealing). We suggested a simple Raman method for evaluation of the relative content of the components in polyethylene/polypropylene blends. The degree of crystallinity of our samples, evaluated by Raman spectroscopy, is in good agreement with the results of analysis by differential scanning calorimetry.

Quantitative analysis of Si1-xGex alloy films by SIMS and XPS depth profiling using a reference material

NASA Astrophysics Data System (ADS)

Oh, Won Jin; Jang, Jong Shik; Lee, Youn Seoung; Kim, Ansoon; Kim, Kyung Joong

2018-02-01

Quantitative analysis methods of multi-element alloy films were compared. The atomic fractions of Si1-xGex alloy films were measured by depth profiling analysis with secondary ion mass spectrometry (SIMS) and X-ray Photoelectron Spectroscopy (XPS). Intensity-to-composition conversion factor (ICF) was used as a mean to convert the intensities to compositions instead of the relative sensitivity factors. The ICFs were determined from a reference Si1-xGex alloy film by the conventional method, average intensity (AI) method and total number counting (TNC) method. In the case of SIMS, although the atomic fractions measured by oxygen ion beams were not quantitative due to severe matrix effect, the results by cesium ion beam were very quantitative. The quantitative analysis results by SIMS using MCs2+ ions are comparable to the results by XPS. In the case of XPS, the measurement uncertainty was highly improved by the AI method and TNC method.

Cluster Analysis of Minnesota School Districts. A Research Report.

ERIC Educational Resources Information Center

Cleary, James

The term "cluster analysis" refers to a set of statistical methods that classify entities with similar profiles of scores on a number of measured dimensions, in order to create empirically based typologies. A 1980 Minnesota House Research Report employed cluster analysis to categorize school districts according to their relative mixtures…

Lunar carbon chemistry - Relations to and implications for terrestrial organic geochemistry.

NASA Technical Reports Server (NTRS)

Eglinton, G.; Maxwell, J. R.; Pillinger, C. T.

1972-01-01

Survey of the various ways in which studies of lunar carbon chemistry have beneficially affected terrestrial organic geochemistry. A lunar organic gas-analysis operating system is cited as the most important instrumental development in relation to terrestrial organic geochemistry. Improved methods of analysis and handling of organic samples are cited as another benefit derived from studies of lunar carbon chemistry. The problem of controlling contamination and minimizing organic vapors is considered, as well as the possibility of analyzing terrestrial samples by the techniques developed for lunar samples. A need for new methods of analyzing carbonaceous material which is insoluble in organic solvents is indicated.

Using Public Libraries To Provide Technology Access for Individuals in Poverty: A Nationwide Analysis of Library Market Areas Using a Geographic Information System.

ERIC Educational Resources Information Center

Jue, Dean K.; Koontz, Christie M.; Magpantay, J. Andrew; Lance, Keith Curry; Seidl, Ann M.

1999-01-01

Assesses the distribution of poverty areas in the United States relative to public library outlet locations to begin discussion on the best possible public library funding and development policies that would serve individuals in poverty areas. Provides a comparative analysis of poverty relative to public library outlets using two common methods of…

Vector form Intrinsic Finite Element Method for the Two-Dimensional Analysis of Marine Risers with Large Deformations

NASA Astrophysics Data System (ADS)

Li, Xiaomin; Guo, Xueli; Guo, Haiyan

2018-06-01

Robust numerical models that describe the complex behaviors of risers are needed because these constitute dynamically sensitive systems. This paper presents a simple and efficient algorithm for the nonlinear static and dynamic analyses of marine risers. The proposed approach uses the vector form intrinsic finite element (VFIFE) method, which is based on vector mechanics theory and numerical calculation. In this method, the risers are described by a set of particles directly governed by Newton's second law and are connected by weightless elements that can only resist internal forces. The method does not require the integration of the stiffness matrix, nor does it need iterations to solve the governing equations. Due to these advantages, the method can easily increase or decrease the element and change the boundary conditions, thus representing an innovative concept of solving nonlinear behaviors, such as large deformation and large displacement. To prove the feasibility of the VFIFE method in the analysis of the risers, rigid and flexible risers belonging to two different categories of marine risers, which usually have differences in modeling and solving methods, are employed in the present study. In the analysis, the plane beam element is adopted in the simulation of interaction forces between the particles and the axial force, shear force, and bending moment are also considered. The results are compared with the conventional finite element method (FEM) and those reported in the related literature. The findings revealed that both the rigid and flexible risers could be modeled in a similar unified analysis model and that the VFIFE method is feasible for solving problems related to the complex behaviors of marine risers.

Detection and categorization of bacteria habitats using shallow linguistic analysis

PubMed Central

2015-01-01

Background Information regarding bacteria biotopes is important for several research areas including health sciences, microbiology, and food processing and preservation. One of the challenges for scientists in these domains is the huge amount of information buried in the text of electronic resources. Developing methods to automatically extract bacteria habitat relations from the text of these electronic resources is crucial for facilitating research in these areas. Methods We introduce a linguistically motivated rule-based approach for recognizing and normalizing names of bacteria habitats in biomedical text by using an ontology. Our approach is based on the shallow syntactic analysis of the text that include sentence segmentation, part-of-speech (POS) tagging, partial parsing, and lemmatization. In addition, we propose two methods for identifying bacteria habitat localization relations. The underlying assumption for the first method is that discourse changes with a new paragraph. Therefore, it operates on a paragraph-basis. The second method performs a more fine-grained analysis of the text and operates on a sentence-basis. We also develop a novel anaphora resolution method for bacteria coreferences and incorporate it with the sentence-based relation extraction approach. Results We participated in the Bacteria Biotope (BB) Task of the BioNLP Shared Task 2013. Our system (Boun) achieved the second best performance with 68% Slot Error Rate (SER) in Sub-task 1 (Entity Detection and Categorization), and ranked third with an F-score of 27% in Sub-task 2 (Localization Event Extraction). This paper reports the system that is implemented for the shared task, including the novel methods developed and the improvements obtained after the official evaluation. The extensions include the expansion of the OntoBiotope ontology using the training set for Sub-task 1, and the novel sentence-based relation extraction method incorporated with anaphora resolution for Sub-task 2. These extensions resulted in promising results for Sub-task 1 with a SER of 68%, and state-of-the-art performance for Sub-task 2 with an F-score of 53%. Conclusions Our results show that a linguistically-oriented approach based on the shallow syntactic analysis of the text is as effective as machine learning approaches for the detection and ontology-based normalization of habitat entities. Furthermore, the newly developed sentence-based relation extraction system with the anaphora resolution module significantly outperforms the paragraph-based one, as well as the other systems that participated in the BB Shared Task 2013. PMID:26201262

Cost-Effectiveness and Cost-Benefit Analysis: Confronting the Problem of Choice.

ERIC Educational Resources Information Center

Clardy, Alan

Cost-effectiveness analysis and cost-benefit analysis are two related yet distinct methods to help decision makers choose the best course of action from among competing alternatives. For both types of analysis, costs are computed similarly. Costs may be reduced to present value amounts for multi-year programs, and parameters may be altered to show…

Polypyrrole nanowire as an excellent solid phase microextraction fiber for bisphenol A analysis in food samples followed by ion mobility spectrometry.

PubMed

Kamalabadi, Mahdie; Mohammadi, Abdorreza; Alizadeh, Naader

2016-08-15

A polypyrrole nanowire coated fiber was prepared and used in head-space solid phase microextraction coupled with ion mobility spectrometry (HS-SPME-IMS) to the analysis of bisphenol A (BPA) in canned food samples, for the first time. This fiber was synthesized by electrochemical oxidation of the monomer in aqueous solution. The fiber characterization by scanning electron microscopy (SEM) revealed that the new fiber exhibited two-dimensional structures with a nanowire morphology. The effects of important extraction parameters on the efficiency of HS-SPME were investigated and optimized. Under the optimum conditions, the linearity of 10-150ngg(-1) and limit of detection (based on S/N=3) of 1ngg(-1) were obtained in BPA analysis. The repeatability (n=5) expressed as the relative standard deviation (RSD%) was 5.8%. At the end, the proposed method was successfully applied to determine BPA in various canned food samples (peas, corns, beans). Relative recoveries were obtained 93-96%. Method validation was conducted by comparing our results with those obtained through HPLC with fluorescence detection (FLD). Compatible results indicate that the proposed method can be successfully used in BPA analysis. This method is simple and cheaper than chromatographic methods, with no need of extra organic solvent consumption and derivatization prior to sample introduction. Copyright © 2016 Elsevier B.V. All rights reserved.

A hybrid wavelet analysis-cloud model data-extending approach for meteorologic and hydrologic time series

NASA Astrophysics Data System (ADS)

Wang, Dong; Ding, Hao; Singh, Vijay P.; Shang, Xiaosan; Liu, Dengfeng; Wang, Yuankun; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing

2015-05-01

For scientific and sustainable management of water resources, hydrologic and meteorologic data series need to be often extended. This paper proposes a hybrid approach, named WA-CM (wavelet analysis-cloud model), for data series extension. Wavelet analysis has time-frequency localization features, known as "mathematics microscope," that can decompose and reconstruct hydrologic and meteorologic series by wavelet transform. The cloud model is a mathematical representation of fuzziness and randomness and has strong robustness for uncertain data. The WA-CM approach first employs the wavelet transform to decompose the measured nonstationary series and then uses the cloud model to develop an extension model for each decomposition layer series. The final extension is obtained by summing the results of extension of each layer. Two kinds of meteorologic and hydrologic data sets with different characteristics and different influence of human activity from six (three pairs) representative stations are used to illustrate the WA-CM approach. The approach is also compared with four other methods, which are conventional correlation extension method, Kendall-Theil robust line method, artificial neural network method (back propagation, multilayer perceptron, and radial basis function), and single cloud model method. To evaluate the model performance completely and thoroughly, five measures are used, which are relative error, mean relative error, standard deviation of relative error, root mean square error, and Thiel inequality coefficient. Results show that the WA-CM approach is effective, feasible, and accurate and is found to be better than other four methods compared. The theory employed and the approach developed here can be applied to extension of data in other areas as well.

Parametric study on single shot peening by dimensional analysis method incorporated with finite element method

NASA Astrophysics Data System (ADS)

Wu, Xian-Qian; Wang, Xi; Wei, Yan-Peng; Song, Hong-Wei; Huang, Chen-Guang

2012-06-01

Shot peening is a widely used surface treatment method by generating compressive residual stress near the surface of metallic materials to increase fatigue life and resistance to corrosion fatigue, cracking, etc. Compressive residual stress and dent profile are important factors to evaluate the effectiveness of shot peening process. In this paper, the influence of dimensionless parameters on maximum compressive residual stress and maximum depth of the dent were investigated. Firstly, dimensionless relations of processing parameters that affect the maximum compressive residual stress and the maximum depth of the dent were deduced by dimensional analysis method. Secondly, the influence of each dimensionless parameter on dimensionless variables was investigated by the finite element method. Furthermore, related empirical formulas were given for each dimensionless parameter based on the simulation results. Finally, comparison was made and good agreement was found between the simulation results and the empirical formula, which shows that a useful approach is provided in this paper for analyzing the influence of each individual parameter.

A comparison of the usefulness of canonical analysis, principal components analysis, and band selection for extraction of features from TMS data for landcover analysis

NASA Technical Reports Server (NTRS)

Boyd, R. K.; Brumfield, J. O.; Campbell, W. J.

1984-01-01

Three feature extraction methods, canonical analysis (CA), principal component analysis (PCA), and band selection, have been applied to Thematic Mapper Simulator (TMS) data in order to evaluate the relative performance of the methods. The results obtained show that CA is capable of providing a transformation of TMS data which leads to better classification results than provided by all seven bands, by PCA, or by band selection. A second conclusion drawn from the study is that TMS bands 2, 3, 4, and 7 (thermal) are most important for landcover classification.

Proteomics analysis of "Rovabiot Excel", a secreted protein cocktail from the filamentous fungus Penicillium funiculosum grown under industrial process fermentation.

PubMed

Guais, Olivier; Borderies, Gisèle; Pichereaux, Carole; Maestracci, Marc; Neugnot, Virginie; Rossignol, Michel; François, Jean Marie

2008-12-01

MS/MS techniques are well customized now for proteomic analysis, even for non-sequenced organisms, since peptide sequences obtained by these methods can be matched with those found in databases from closely related sequenced organisms. We used this approach to characterize the protein content of the "Rovabio Excel", an enzymatic cocktail produced by Penicillium funiculosum that is used as feed additive in animal nutrition. Protein separation by bi-dimensional electrophoresis yielded more than 100 spots, from which 37 proteins were unambiguously assigned from peptide sequences. By one-dimensional SDS-gel electrophoresis, 34 proteins were identified among which 8 were not found in the 2-DE analysis. A third method, termed 'peptidic shotgun', which consists in a direct treatment of the cocktail by trypsin followed by separation of the peptides on two-dimensional liquid chromatography, resulted in the identification of two additional proteins not found by the two other methods. Altogether, more than 50 proteins, among which several glycosylhydrolytic, hemicellulolytic and proteolytic enzymes, were identified by combining three separation methods in this enzymatic cocktail. This work confirmed the power of proteome analysis to explore the genome expression of a non-sequenced fungus by taking advantage of sequences from phylogenetically related filamentous fungi and pave the way for further functional analysis of P. funiculosum.

Kaplan-Meier survival analysis overestimates cumulative incidence of health-related events in competing risk settings: a meta-analysis.

PubMed

Lacny, Sarah; Wilson, Todd; Clement, Fiona; Roberts, Derek J; Faris, Peter; Ghali, William A; Marshall, Deborah A

2018-01-01

Kaplan-Meier survival analysis overestimates cumulative incidence in competing risks (CRs) settings. The extent of overestimation (or its clinical significance) has been questioned, and CRs methods are infrequently used. This meta-analysis compares the Kaplan-Meier method to the cumulative incidence function (CIF), a CRs method. We searched MEDLINE, EMBASE, BIOSIS Previews, Web of Science (1992-2016), and article bibliographies for studies estimating cumulative incidence using the Kaplan-Meier method and CIF. For studies with sufficient data, we calculated pooled risk ratios (RRs) comparing Kaplan-Meier and CIF estimates using DerSimonian and Laird random effects models. We performed stratified meta-analyses by clinical area, rate of CRs (CRs/events of interest), and follow-up time. Of 2,192 identified abstracts, we included 77 studies in the systematic review and meta-analyzed 55. The pooled RR demonstrated the Kaplan-Meier estimate was 1.41 [95% confidence interval (CI): 1.36, 1.47] times higher than the CIF. Overestimation was highest among studies with high rates of CRs [RR = 2.36 (95% CI: 1.79, 3.12)], studies related to hepatology [RR = 2.60 (95% CI: 2.12, 3.19)], and obstetrics and gynecology [RR = 1.84 (95% CI: 1.52, 2.23)]. The Kaplan-Meier method overestimated the cumulative incidence across 10 clinical areas. Using CRs methods will ensure accurate results inform clinical and policy decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of atmospheric organic sources using the carbon hollow tube-gas chromatography method and factor analysis

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

Cobb, G.P.; Braman, R.S.; Gilbert, R.A.

Atmospheric organics were sampled and analyzed by using the carbon hollow tube-gas chromatography method. Chromatograms from spice mixtures, cigarettes, and ambient air were analyzed. Principal factor analysis of row order chromatographic data produces factors which are eigenchromatograms of the components in the samples. Component sources are identified from the eigenchromatograms in all experiments and the individual eigenchromatogram corresponding to a particular source is determined in most cases. Organic sources in ambient air and in cigaretts are identified with 87% certainty. Analysis of clove cigarettes allows the determination of the relative amount of clove in different cigarettes. A new nondestructive qualitymore » control method using the hollow tube-gas chromatography analysis is discussed.« less

A scoping review of spatial cluster analysis techniques for point-event data.

PubMed

Fritz, Charles E; Schuurman, Nadine; Robertson, Colin; Lear, Scott

2013-05-01

Spatial cluster analysis is a uniquely interdisciplinary endeavour, and so it is important to communicate and disseminate ideas, innovations, best practices and challenges across practitioners, applied epidemiology researchers and spatial statisticians. In this research we conducted a scoping review to systematically search peer-reviewed journal databases for research that has employed spatial cluster analysis methods on individual-level, address location, or x and y coordinate derived data. To illustrate the thematic issues raised by our results, methods were tested using a dataset where known clusters existed. Point pattern methods, spatial clustering and cluster detection tests, and a locally weighted spatial regression model were most commonly used for individual-level, address location data (n = 29). The spatial scan statistic was the most popular method for address location data (n = 19). Six themes were identified relating to the application of spatial cluster analysis methods and subsequent analyses, which we recommend researchers to consider; exploratory analysis, visualization, spatial resolution, aetiology, scale and spatial weights. It is our intention that researchers seeking direction for using spatial cluster analysis methods, consider the caveats and strengths of each approach, but also explore the numerous other methods available for this type of analysis. Applied spatial epidemiology researchers and practitioners should give special consideration to applying multiple tests to a dataset. Future research should focus on developing frameworks for selecting appropriate methods and the corresponding spatial weighting schemes.

Method variation in the impact of missing data on response shift detection.

PubMed

Schwartz, Carolyn E; Sajobi, Tolulope T; Verdam, Mathilde G E; Sebille, Veronique; Lix, Lisa M; Guilleux, Alice; Sprangers, Mirjam A G

2015-03-01

Missing data due to attrition or item non-response can result in biased estimates and loss of power in longitudinal quality-of-life (QOL) research. The impact of missing data on response shift (RS) detection is relatively unknown. This overview article synthesizes the findings of three methods tested in this special section regarding the impact of missing data patterns on RS detection in incomplete longitudinal data. The RS detection methods investigated include: (1) Relative importance analysis to detect reprioritization RS in stroke caregivers; (2) Oort's structural equation modeling (SEM) to detect recalibration, reprioritization, and reconceptualization RS in cancer patients; and (3) Rasch-based item-response theory-based (IRT) models as compared to SEM models to detect recalibration and reprioritization RS in hospitalized chronic disease patients. Each method dealt with missing data differently, either with imputation (1), attrition-based multi-group analysis (2), or probabilistic analysis that is robust to missingness due to the specific objectivity property (3). Relative importance analyses were sensitive to the type and amount of missing data and imputation method, with multiple imputation showing the largest RS effects. The attrition-based multi-group SEM revealed differential effects of both the changes in health-related QOL and the occurrence of response shift by attrition stratum, and enabled a more complete interpretation of findings. The IRT RS algorithm found evidence of small recalibration and reprioritization effects in General Health, whereas SEM mostly evidenced small recalibration effects. These differences may be due to differences between the two methods in handling of missing data. Missing data imputation techniques result in different conclusions about the presence of reprioritization RS using the relative importance method, while the attrition-based SEM approach highlighted different recalibration and reprioritization RS effects by attrition group. The IRT analyses detected more recalibration and reprioritization RS effects than SEM, presumably due to IRT's robustness to missing data. Future research should apply simulation techniques in order to make conclusive statements about the impacts of missing data according to the type and amount of RS.

GAMA/H-ATLAS: a meta-analysis of SFR indicators - comprehensive measures of the SFR-M* relation and cosmic star formation history at z < 0.4

NASA Astrophysics Data System (ADS)

Davies, L. J. M.; Driver, S. P.; Robotham, A. S. G.; Grootes, M. W.; Popescu, C. C.; Tuffs, R. J.; Hopkins, A.; Alpaslan, M.; Andrews, S. K.; Bland-Hawthorn, J.; Bremer, M. N.; Brough, S.; Brown, M. J. I.; Cluver, M. E.; Croom, S.; da Cunha, E.; Dunne, L.; Lara-López, M. A.; Liske, J.; Loveday, J.; Moffett, A. J.; Owers, M.; Phillipps, S.; Sansom, A. E.; Taylor, E. N.; Michalowski, M. J.; Ibar, E.; Smith, M.; Bourne, N.

2016-09-01

We present a meta-analysis of star formation rate (SFR) indicators in the Galaxy And Mass Assembly (GAMA) survey, producing 12 different SFR metrics and determining the SFR-M* relation for each. We compare and contrast published methods to extract the SFR from each indicator, using a well-defined local sample of morphologically selected spiral galaxies, which excludes sources which potentially have large recent changes to their SFR. The different methods are found to yield SFR-M* relations with inconsistent slopes and normalizations, suggesting differences between calibration methods. The recovered SFR-M* relations also have a large range in scatter which, as SFRs of the targets may be considered constant over the different time-scales, suggests differences in the accuracy by which methods correct for attenuation in individual targets. We then recalibrate all SFR indicators to provide new, robust and consistent luminosity-to-SFR calibrations, finding that the most consistent slopes and normalizations of the SFR-M* relations are obtained when recalibrated using the radiation transfer method of Popescu et al. These new calibrations can be used to directly compare SFRs across different observations, epochs and galaxy populations. We then apply our calibrations to the GAMA II equatorial data set and explore the evolution of star formation in the local Universe. We determine the evolution of the normalization to the SFR-M* relation from 0 < z < 0.35 - finding consistent trends with previous estimates at 0.3 < z < 1.2. We then provide the definitive z < 0.35 cosmic star formation history, SFR-M* relation and its evolution over the last 3 billion years.

Text grouping in patent analysis using adaptive K-means clustering algorithm

NASA Astrophysics Data System (ADS)

Shanie, Tiara; Suprijadi, Jadi; Zulhanif

2017-03-01

Patents are one of the Intellectual Property. Analyzing patent is one requirement in knowing well the development of technology in each country and in the world now. This study uses the patent document coming from the Espacenet server about Green Tea. Patent documents related to the technology in the field of tea is still widespread, so it will be difficult for users to information retrieval (IR). Therefore, it is necessary efforts to categorize documents in a specific group of related terms contained therein. This study uses titles patent text data with the proposed Green Tea in Statistical Text Mining methods consists of two phases: data preparation and data analysis stage. The data preparation phase uses Text Mining methods and data analysis stage is done by statistics. Statistical analysis in this study using a cluster analysis algorithm, the Adaptive K-Means Clustering Algorithm. Results from this study showed that based on the maximum value Silhouette, generate 87 clusters associated fifteen terms therein that can be utilized in the process of information retrieval needs.

The Effects of Diagnostic Definitions in Claims Data on Healthcare Cost Estimates: Evidence from a Large-Scale Panel Data Analysis of Diabetes Care in Japan.

PubMed

Fukuda, Haruhisa; Ikeda, Shunya; Shiroiwa, Takeru; Fukuda, Takashi

2016-10-01

Inaccurate estimates of diabetes-related healthcare costs can undermine the efficiency of resource allocation for diabetes care. The quantification of these costs using claims data may be affected by the method for defining diagnoses. The aims were to use panel data analysis to estimate diabetes-related healthcare costs and to comparatively evaluate the effects of diagnostic definitions on cost estimates. Monthly panel data analysis of Japanese claims data. The study included a maximum of 141,673 patients with type 2 diabetes who received treatment between 2005 and 2013. Additional healthcare costs associated with diabetes and diabetes-related complications were estimated for various diagnostic definition methods using fixed-effects panel data regression models. The average follow-up period per patient ranged from 49.4 to 52.3 months. The number of patients identified as having type 2 diabetes varied widely among the diagnostic definition methods, ranging from 14,743 patients to 141,673 patients. The fixed-effects models showed that the additional costs per patient per month associated with diabetes ranged from US$180 [95 % confidence interval (CI) 178-181] to US$223 (95 % CI 221-224). When the diagnostic definition excluded rule-out diagnoses, the diabetes-related complications associated with higher additional healthcare costs were ischemic heart disease with surgery (US$13,595; 95 % CI 13,568-13,622), neuropathy/extremity disease with surgery (US$4594; 95 % CI 3979-5208), and diabetic nephropathy with dialysis (US$3689; 95 % CI 3667-3711). Diabetes-related healthcare costs are sensitive to diagnostic definition methods. Determining appropriate diagnostic definitions can further advance healthcare cost research for diabetes and its applications in healthcare policies.

Underlying risk factors for prescribing errors in long-term aged care: a qualitative study.

PubMed

Tariq, Amina; Georgiou, Andrew; Raban, Magdalena; Baysari, Melissa Therese; Westbrook, Johanna

2016-09-01

To identify system-related risk factors perceived to contribute to prescribing errors in Australian long-term care settings, that is, residential aged care facilities (RACFs). The study used qualitative methods to explore factors that contribute to unsafe prescribing in RACFs. Data were collected at three RACFs in metropolitan Sydney, Australia between May and November 2011. Participants included RACF managers, doctors, pharmacists and RACF staff actively involved in prescribing-related processes. Methods included non-participant observations (74 h), in-depth semistructured interviews (n=25) and artefact analysis. Detailed process activity models were developed for observed prescribing episodes supplemented by triangulated analysis using content analysis methods. System-related factors perceived to increase the risk of prescribing errors in RACFs were classified into three overarching themes: communication systems, team coordination and staff management. Factors associated with communication systems included limited point-of-care access to information, inadequate handovers, information storage across different media (paper, electronic and memory), poor legibility of charts, information double handling, multiple faxing of medication charts and reliance on manual chart reviews. Team factors included lack of established lines of responsibility, inadequate team communication and limited participation of doctors in multidisciplinary initiatives like medication advisory committee meetings. Factors related to staff management and workload included doctors' time constraints and their accessibility, lack of trained RACF staff and high RACF staff turnover. The study highlights several system-related factors including laborious methods for exchanging medication information, which often act together to contribute to prescribing errors. Multiple interventions (eg, technology systems, team communication protocols) are required to support the collaborative nature of RACF prescribing. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Genetic Comparison of B. Anthracis and its Close Relatives Using AFLP and PCR Analysis

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

Jackson, P.J.; Hill, K.K.; Laker, M.T.

1999-02-01

Amplified Fragment length Polymorphism (AFLP) analysis allows a rapid, relatively simple analysis of a large portion of a microbial genome, providing information about the species and its phylogenetic relationship to other microbes (Vos, et al., 1995). The method simply surveys the genome for length and sequence polymorphisms. The pattern identified can be used for comparison to the genomes of other species. Unlike other methods, it does not rely on analysis of a single genetic locus that may bias the interpretation of results and it does not require any prior knowledge of the targeted organism. Moreover, a standard set of reagentsmore » can be applied to any species without using species-specific information or molecular probes. The authors are using AFLP's to rapidly identify different bacterial species. A comparison of AFLP profiles generated from a large battery of B. anthracis strains shows very little variability among different isolates (Keim, et al., 1997). By contrast, there is a significant difference between AFLP profiles generated for any B. anthracis strain and even the most closely related Bacillus species. Sufficient variability is apparent among all known microbial species to allow phylogenetic analysis based on large numbers of genetically unlinked loci. These striking differences among AFLP profiles allow unambiguous identification of previously identified species and phylogenetic placement of newly characterized isolates relative to known species based on a large number of independent genetic loci. Data generated thus far show that the method provides phylogenetic analyses that are consistent with other widely accepted phylogenetic methods. However, AFLP analysis provides a more detailed analysis of the targets and samples a much larger portion of the genome. Consequently, it provides an inexpensive, rapid means of characterizing microbial isolates to further differentiate among strains and closely related microbial species. Such information cannot be rapidly generated by other means. AFLP sample analysis quickly generates a very large amount of molecular information about microbial genomes. However, this information cannot be analyzed rapidly using manual methods. The authors are developing a large archive of electronic AFLP signatures that is being used to identify isolates collected from medical, veterinary, forensic and environmental samples. They are also developing the computational packages necessary to rapidly and unambiguously analyze the AFLP profiles and conduct a phylogenetic comparison of these data relative to information already in the database. They will use this archive and the associated algorithms to determine the species identity of previously uncharacterized isolates and place them phylogenetically relative to other microbes based on their AFLP signatures. This study provides significant new information about microbes with environmental, veterinary and medical significance. This information can be used in further studies to understand the relationships among these species and the factors that distinguish them from one another. It should also allow identification of unique factors that contribute to important microbial traits including pathogenicity and virulence. They are also using AFLP data to identify, isolate and sequence DNA fragments that are unique to particular microbial species and strains. The fragment patterns and sequence information provide insights into the complexity and organization of bacterial genomes relative to one another. They also provide the information necessary for development of species-specific PCR primers that can be used to interrogate complex samples for the presence of B. anthracis, other microbial pathogens or their remnants.« less

An Emerging New Risk Analysis Science: Foundations and Implications.

PubMed

Aven, Terje

2018-05-01

To solve real-life problems-such as those related to technology, health, security, or climate change-and make suitable decisions, risk is nearly always a main issue. Different types of sciences are often supporting the work, for example, statistics, natural sciences, and social sciences. Risk analysis approaches and methods are also commonly used, but risk analysis is not broadly accepted as a science in itself. A key problem is the lack of explanatory power and large uncertainties when assessing risk. This article presents an emerging new risk analysis science based on novel ideas and theories on risk analysis developed in recent years by the risk analysis community. It builds on a fundamental change in thinking, from the search for accurate predictions and risk estimates, to knowledge generation related to concepts, theories, frameworks, approaches, principles, methods, and models to understand, assess, characterize, communicate, and (in a broad sense) manage risk. Examples are used to illustrate the importance of this distinct/separate risk analysis science for solving risk problems, supporting science in general and other disciplines in particular. © 2017 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Estimating Sobol Sensitivity Indices Using Correlations

EPA Science Inventory

Sensitivity analysis is a crucial tool in the development and evaluation of complex mathematical models. Sobol's method is a variance-based global sensitivity analysis technique that has been applied to computational models to assess the relative importance of input parameters on...

CERAMIC: Case-Control Association Testing in Samples with Related Individuals, Based on Retrospective Mixed Model Analysis with Adjustment for Covariates

PubMed Central

Zhong, Sheng; McPeek, Mary Sara

2016-01-01

We consider the problem of genetic association testing of a binary trait in a sample that contains related individuals, where we adjust for relevant covariates and allow for missing data. We propose CERAMIC, an estimating equation approach that can be viewed as a hybrid of logistic regression and linear mixed-effects model (LMM) approaches. CERAMIC extends the recently proposed CARAT method to allow samples with related individuals and to incorporate partially missing data. In simulations, we show that CERAMIC outperforms existing LMM and generalized LMM approaches, maintaining high power and correct type 1 error across a wider range of scenarios. CERAMIC results in a particularly large power increase over existing methods when the sample includes related individuals with some missing data (e.g., when some individuals with phenotype and covariate information have missing genotype), because CERAMIC is able to make use of the relationship information to incorporate partially missing data in the analysis while correcting for dependence. Because CERAMIC is based on a retrospective analysis, it is robust to misspecification of the phenotype model, resulting in better control of type 1 error and higher power than that of prospective methods, such as GMMAT, when the phenotype model is misspecified. CERAMIC is computationally efficient for genomewide analysis in samples of related individuals of almost any configuration, including small families, unrelated individuals and even large, complex pedigrees. We apply CERAMIC to data on type 2 diabetes (T2D) from the Framingham Heart Study. In a genome scan, 9 of the 10 smallest CERAMIC p-values occur in or near either known T2D susceptibility loci or plausible candidates, verifying that CERAMIC is able to home in on the important loci in a genome scan. PMID:27695091

Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women

PubMed Central

Ashman, Amy M.; Collins, Clare E.; Brown, Leanne J.; Rae, Kym M.; Rollo, Megan E.

2017-01-01

Image-based dietary records could lower participant burden associated with traditional prospective methods of dietary assessment. They have been used in children, adolescents and adults, but have not been evaluated in pregnant women. The current study evaluated relative validity of the DietBytes image-based dietary assessment method for assessing energy and nutrient intakes. Pregnant women collected image-based dietary records (via a smartphone application) of all food, drinks and supplements consumed over three non-consecutive days. Intakes from the image-based method were compared to intakes collected from three 24-h recalls, taken on random days; once per week, in the weeks following the image-based record. Data were analyzed using nutrient analysis software. Agreement between methods was ascertained using Pearson correlations and Bland-Altman plots. Twenty-five women (27 recruited, one withdrew, one incomplete), median age 29 years, 15 primiparas, eight Aboriginal Australians, completed image-based records for analysis. Significant correlations between the two methods were observed for energy, macronutrients and fiber (r = 0.58–0.84, all p < 0.05), and for micronutrients both including (r = 0.47–0.94, all p < 0.05) and excluding (r = 0.40–0.85, all p < 0.05) supplements in the analysis. Bland-Altman plots confirmed acceptable agreement with no systematic bias. The DietBytes method demonstrated acceptable relative validity for assessment of nutrient intakes of pregnant women. PMID:28106758

Analysis options for estimating status and trends in long-term monitoring

USGS Publications Warehouse

Bart, Jonathan; Beyer, Hawthorne L.

2012-01-01

This chapter describes methods for estimating long-term trends in ecological parameters. Other chapters in this volume discuss more advanced methods for analyzing monitoring data, but these methods may be relatively inaccessible to some readers. Therefore, this chapter provides an introduction to trend analysis for managers and biologists while also discussing general issues relevant to trend assessment in any long-term monitoring program. For simplicity, we focus on temporal trends in population size across years. We refer to the survey results for each year as the “annual means” (e.g. mean per transect, per plot, per time period). The methods apply with little or no modification, however, to formal estimates of population size, other temporal units (e.g. a month), to spatial or other dimensions such as elevation or a north–south gradient, and to other quantities such as chemical or geological parameters. The chapter primarily discusses methods for estimating population-wide parameters rather than studying variation in trend within the population, which can be examined using methods presented in other chapters (e.g. Chapters 7, 12, 20). We begin by reviewing key concepts related to trend analysis. We then describe how to evaluate potential bias in trend estimates. An overview of the statistical models used to quantify trends is then presented. We conclude by showing ways to estimate trends using simple methods that can be implemented with spreadsheets.

A feasibility study on age-related factors of wrist pulse using principal component analysis.

PubMed

Jang-Han Bae; Young Ju Jeon; Sanghun Lee; Jaeuk U Kim

2016-08-01

Various analysis methods for examining wrist pulse characteristics are needed for accurate pulse diagnosis. In this feasibility study, principal component analysis (PCA) was performed to observe age-related factors of wrist pulse from various analysis parameters. Forty subjects in the age group of 20s and 40s were participated, and their wrist pulse signal and respiration signal were acquired with the pulse tonometric device. After pre-processing of the signals, twenty analysis parameters which have been regarded as values reflecting pulse characteristics were calculated and PCA was performed. As a results, we could reduce complex parameters to lower dimension and age-related factors of wrist pulse were observed by combining-new analysis parameter derived from PCA. These results demonstrate that PCA can be useful tool for analyzing wrist pulse signal.

Development of Novel Noninvasive Methods of Stress Assessment in Baleen Whales

DTIC Science & Technology

2014-09-30

large whales. Few methods exist for assessment of physiological stress levels of free-swimming cetaceans (Amaral 2010, ONR 2010, Hunt et al. 2013...hormone aldosterone . Our aim in this project is to further develop both techniques - respiratory hormone analysis and fecal hormone analysis - for use...noninvasive aldosterone assay (for both feces and blow) that can be used as an alternative measure of adrenal gland activation relative to stress

Price Analysis on Commercial Item Purchases Within the Department of the Navy

DTIC Science & Technology

2015-04-30

has advised 20 students , seven of whom worked on acquisition and contracting-related projects. Dr. Gera’s research is in networks, publishing 32...commercial item procurements. The importance of market research and price analysis methods has increased because of this change (Gera & Maddox, 2013...require that pricing be discussed in the market research reports (p. 54). The FAR identifies market research as a method for determining price

Gender differences and age-related changes in body fat mass in Tibetan children and teenagers: an analysis by the bioelectrical impedance method.

PubMed

Zhang, Hai-Long; Fu, Qiang; Li, Wen-Hui; Liu, Su-Wei; Zhong, Hua; Duoji, Bai-Ma; Zhang, Mei-Zhi; Lv, Po; Xi, Huan-Jiu

2015-01-01

We aimed to obtain the fat base value and the fat distribution characteristics of Tibetan children and teenagers by estimating their body fat content with the bioelectrical impedance method. We recruited 1427 healthy children and teenagers by a stratified cluster sampling method. By using bioelectrical impedance analysis, we obtained various values relevant to fat. We found that total body fat mass and the fat mass of various body parts increased with age in boys and girls. Yet there were no differences between age groups until 11 years. However, fat mass increased quickly between 11 and 18 years, and significant differences were seen between adolescent boys and girls; all fat indices were higher in girls than in boys (p<0.05). The characteristics of fat in Tibetan children and teenagers in Tibet is related to age and gender related hormone secretion, which reflects the physiological characteristics in different developmental stages.

Changes in monosaccharides, organic acids and amino acids during Cabernet Sauvignon wine ageing based on a simultaneous analysis using gas chromatography-mass spectrometry.

PubMed

Zhang, Xin-Ke; Lan, Yi-Bin; Zhu, Bao-Qing; Xiang, Xiao-Feng; Duan, Chang-Qing; Shi, Ying

2018-01-01

Monosaccharides, organic acids and amino acids are the important flavour-related components in wines. The aim of this article is to develop and validate a method that could simultaneously analyse these compounds in wine based on silylation derivatisation and gas chromatography-mass spectrometry (GC-MS), and apply this method to the investigation of the changes of these compounds and speculate upon their related influences on Cabernet Sauvignon wine flavour during wine ageing. This work presented a new approach for wine analysis and provided more information concerning red wine ageing. This method could simultaneously quantitatively analyse 2 monosaccharides, 8 organic acids and 13 amino acids in wine. A validation experiment showed good linearity, sensitivity, reproducibility and recovery. Multiple derivatives of five amino acids have been found but their effects on quantitative analysis were negligible, except for methionine. The evolution pattern of each category was different, and we speculated that the corresponding mechanisms involving microorganism activities, physical interactions and chemical reactions had a great correlation with red wine flavours during ageing. Simultaneously quantitative analysis of monosaccharides, organic acids and amino acids in wine was feasible and reliable and this method has extensive application prospects. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

MALDI MS-based Composition Analysis of the Polymerization Reaction of Toluene Diisocyanate (TDI) and Ethylene Glycol (EG).

PubMed

Ahn, Yeong Hee; Lee, Yeon Jung; Kim, Sung Ho

2015-01-01

This study describes an MS-based analysis method for monitoring changes in polymer composition during the polyaddition polymerization reaction of toluene diisocyanate (TDI) and ethylene glycol (EG). The polymerization was monitored as a function of reaction time using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF MS). The resulting series of polymer adducts terminated with various end-functional groups were precisely identified and the relative compositions of those series were estimated. A new MALDI MS data interpretation method was developed, consisting of a peak-resolving algorithm for overlapping peaks in MALDI MS spectra, a retrosynthetic analysis for the generation of reduced unit mass peaks, and a Gaussian fit-based selection of the most prominent polymer series among the reconstructed unit mass peaks. This method of data interpretation avoids errors originating from side reactions due to the presence of trace water in the reaction mixture or MALDI analysis. Quantitative changes in the relative compositions of the resulting polymer products were monitored as a function of reaction time. These results demonstrate that the mass data interpretation method described herein can be a powerful tool for estimating quantitative changes in the compositions of polymer products arising during a polymerization reaction.

On the analysis of very small samples of Gaussian repeated measurements: an alternative approach.

PubMed

Westgate, Philip M; Burchett, Woodrow W

2017-03-15

The analysis of very small samples of Gaussian repeated measurements can be challenging. First, due to a very small number of independent subjects contributing outcomes over time, statistical power can be quite small. Second, nuisance covariance parameters must be appropriately accounted for in the analysis in order to maintain the nominal test size. However, available statistical strategies that ensure valid statistical inference may lack power, whereas more powerful methods may have the potential for inflated test sizes. Therefore, we explore an alternative approach to the analysis of very small samples of Gaussian repeated measurements, with the goal of maintaining valid inference while also improving statistical power relative to other valid methods. This approach uses generalized estimating equations with a bias-corrected empirical covariance matrix that accounts for all small-sample aspects of nuisance correlation parameter estimation in order to maintain valid inference. Furthermore, the approach utilizes correlation selection strategies with the goal of choosing the working structure that will result in the greatest power. In our study, we show that when accurate modeling of the nuisance correlation structure impacts the efficiency of regression parameter estimation, this method can improve power relative to existing methods that yield valid inference. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Microrheology with optical tweezers: measuring the relative viscosity of solutions 'at a glance'.

PubMed

Tassieri, Manlio; Del Giudice, Francesco; Robertson, Emma J; Jain, Neena; Fries, Bettina; Wilson, Rab; Glidle, Andrew; Greco, Francesco; Netti, Paolo Antonio; Maffettone, Pier Luca; Bicanic, Tihana; Cooper, Jonathan M

2015-03-06

We present a straightforward method for measuring the relative viscosity of fluids via a simple graphical analysis of the normalised position autocorrelation function of an optically trapped bead, without the need of embarking on laborious calculations. The advantages of the proposed microrheology method are evident when it is adopted for measurements of materials whose availability is limited, such as those involved in biological studies. The method has been validated by direct comparison with conventional bulk rheology methods, and has been applied both to characterise synthetic linear polyelectrolytes solutions and to study biomedical samples.

Microrheology with Optical Tweezers: Measuring the relative viscosity of solutions ‘at a glance'

PubMed Central

Tassieri, Manlio; Giudice, Francesco Del; Robertson, Emma J.; Jain, Neena; Fries, Bettina; Wilson, Rab; Glidle, Andrew; Greco, Francesco; Netti, Paolo Antonio; Maffettone, Pier Luca; Bicanic, Tihana; Cooper, Jonathan M.

2015-01-01

We present a straightforward method for measuring the relative viscosity of fluids via a simple graphical analysis of the normalised position autocorrelation function of an optically trapped bead, without the need of embarking on laborious calculations. The advantages of the proposed microrheology method are evident when it is adopted for measurements of materials whose availability is limited, such as those involved in biological studies. The method has been validated by direct comparison with conventional bulk rheology methods, and has been applied both to characterise synthetic linear polyelectrolytes solutions and to study biomedical samples. PMID:25743468

Sensitivity of GC-EI/MS, GC-EI/MS/MS, LC-ESI/MS/MS, LC-Ag(+) CIS/MS/MS, and GC-ESI/MS/MS for analysis of anabolic steroids in doping control.

PubMed

Cha, Eunju; Kim, Sohee; Kim, Ho Jun; Lee, Kang Mi; Kim, Ki Hun; Kwon, Oh-Seung; Lee, Jaeick

2015-01-01

This study compared the sensitivity of various separation and ionization methods, including gas chromatography with an electron ionization source (GC-EI), liquid chromatography with an electrospray ionization source (LC-ESI), and liquid chromatography with a silver ion coordination ion spray source (LC-Ag(+) CIS), coupled to a mass spectrometer (MS) for steroid analysis. Chromatographic conditions, mass spectrometric transitions, and ion source parameters were optimized. The majority of steroids in GC-EI/MS/MS and LC-Ag(+) CIS/MS/MS analysis showed higher sensitivities than those obtained with other analytical methods. The limits of detection (LODs) of 65 steroids by GC-EI/MS/MS, 68 steroids by LC-Ag(+) CIS/MS/MS, 56 steroids by GC-EI/MS, 54 steroids by LC-ESI/MS/MS, and 27 steroids by GC-ESI/MS/MS were below cut-off value of 2.0 ng/mL. LODs of steroids that formed protonated ions in LC-ESI/MS/MS analysis were all lower than the cut-off value. Several steroids such as unconjugated C3-hydroxyl with C17-hydroxyl structure showed higher sensitivities in GC-EI/MS/MS analysis relative to those obtained using the LC-based methods. The steroids containing 4, 9, 11-triene structures showed relatively poor sensitivities in GC-EI/MS and GC-ESI/MS/MS analysis. The results of this study provide information that may be useful for selecting suitable analytical methods for confirmatory analysis of steroids. Copyright © 2015 John Wiley & Sons, Ltd.

Prediction of line failure fault based on weighted fuzzy dynamic clustering and improved relational analysis

NASA Astrophysics Data System (ADS)

Meng, Xiaocheng; Che, Renfei; Gao, Shi; He, Juntao

2018-04-01

With the advent of large data age, power system research has entered a new stage. At present, the main application of large data in the power system is the early warning analysis of the power equipment, that is, by collecting the relevant historical fault data information, the system security is improved by predicting the early warning and failure rate of different kinds of equipment under certain relational factors. In this paper, a method of line failure rate warning is proposed. Firstly, fuzzy dynamic clustering is carried out based on the collected historical information. Considering the imbalance between the attributes, the coefficient of variation is given to the corresponding weights. And then use the weighted fuzzy clustering to deal with the data more effectively. Then, by analyzing the basic idea and basic properties of the relational analysis model theory, the gray relational model is improved by combining the slope and the Deng model. And the incremental composition and composition of the two sequences are also considered to the gray relational model to obtain the gray relational degree between the various samples. The failure rate is predicted according to the principle of weighting. Finally, the concrete process is expounded by an example, and the validity and superiority of the proposed method are verified.

Clustering-Constrained ICA for Ballistocardiogram Artifacts Removal in Simultaneous EEG-fMRI

PubMed Central

Wang, Kai; Li, Wenjie; Dong, Li; Zou, Ling; Wang, Changming

2018-01-01

Combination of electroencephalogram (EEG) recording and functional magnetic resonance imaging (fMRI) plays a potential role in neuroimaging due to its high spatial and temporal resolution. However, EEG is easily influenced by ballistocardiogram (BCG) artifacts and may cause false identification of the related EEG features, such as epileptic spikes. There are many related methods to remove them, however, they do not consider the time-varying features of BCG artifacts. In this paper, a novel method using clustering algorithm to catch the BCG artifacts' features and together with the constrained ICA (ccICA) is proposed to remove the BCG artifacts. We first applied this method to the simulated data, which was constructed by adding the BCG artifacts to the EEG signal obtained from the conventional environment. Then, our method was tested to demonstrate the effectiveness during EEG and fMRI experiments on 10 healthy subjects. In simulated data analysis, the value of error in signal amplitude (Er) computed by ccICA method was lower than those from other methods including AAS, OBS, and cICA (p < 0.005). In vivo data analysis, the Improvement of Normalized Power Spectrum (INPS) calculated by ccICA method in all electrodes was much higher than AAS, OBS, and cICA methods (p < 0.005). We also used other evaluation index (e.g., power analysis) to compare our method with other traditional methods. In conclusion, our novel method successfully and effectively removed BCG artifacts in both simulated and vivo EEG data tests, showing the potentials of removing artifacts in EEG-fMRI applications. PMID:29487499

Advanced quantitative magnetic nondestructive evaluation methods - Theory and experiment

NASA Technical Reports Server (NTRS)

Barton, J. R.; Kusenberger, F. N.; Beissner, R. E.; Matzkanin, G. A.

1979-01-01

The paper reviews the scale of fatigue crack phenomena in relation to the size detection capabilities of nondestructive evaluation methods. An assessment of several features of fatigue in relation to the inspection of ball and roller bearings suggested the use of magnetic methods; magnetic domain phenomena including the interaction of domains and inclusions, and the influence of stress and magnetic field on domains are discussed. Experimental results indicate that simplified calculations can be used to predict many features of these results; the data predicted by analytic models which use finite element computer analysis predictions do not agree with respect to certain features. Experimental analyses obtained on rod-type fatigue specimens which show experimental magnetic measurements in relation to the crack opening displacement and volume and crack depth should provide methods for improved crack characterization in relation to fracture mechanics and life prediction.

Risk-Based Prioritization Method for the Classification of Groundwater Pollution from Hazardous Waste Landfills.

PubMed

Yang, Yu; Jiang, Yong-Hai; Lian, Xin-Ying; Xi, Bei-Dou; Ma, Zhi-Fei; Xu, Xiang-Jian; An, Da

2016-12-01

Hazardous waste landfill sites are a significant source of groundwater pollution. To ensure that these landfills with a significantly high risk of groundwater contamination are properly managed, a risk-based ranking method related to groundwater contamination is needed. In this research, a risk-based prioritization method for the classification of groundwater pollution from hazardous waste landfills was established. The method encompasses five phases, including risk pre-screening, indicator selection, characterization, classification and, lastly, validation. In the risk ranking index system employed here, 14 indicators involving hazardous waste landfills and migration in the vadose zone as well as aquifer were selected. The boundary of each indicator was determined by K-means cluster analysis and the weight of each indicator was calculated by principal component analysis. These methods were applied to 37 hazardous waste landfills in China. The result showed that the risk for groundwater contamination from hazardous waste landfills could be ranked into three classes from low to high risk. In all, 62.2 % of the hazardous waste landfill sites were classified in the low and medium risk classes. The process simulation method and standardized anomalies were used to validate the result of risk ranking; the results were consistent with the simulated results related to the characteristics of contamination. The risk ranking method was feasible, valid and can provide reference data related to risk management for groundwater contamination at hazardous waste landfill sites.

[Recent advances in sample preparation methods of plant hormones].

PubMed

Wu, Qian; Wang, Lus; Wu, Dapeng; Duan, Chunfeng; Guan, Yafeng

2014-04-01

Plant hormones are a group of naturally occurring trace substances which play a crucial role in controlling the plant development, growth and environment response. With the development of the chromatography and mass spectroscopy technique, chromatographic analytical method has become a widely used way for plant hormone analysis. Among the steps of chromatographic analysis, sample preparation is undoubtedly the most vital one. Thus, a highly selective and efficient sample preparation method is critical for accurate identification and quantification of phytohormones. For the three major kinds of plant hormones including acidic plant hormones & basic plant hormones, brassinosteroids and plant polypeptides, the sample preparation methods are reviewed in sequence especially the recently developed methods. The review includes novel methods, devices, extractive materials and derivative reagents for sample preparation of phytohormones analysis. Especially, some related works of our group are included. At last, the future developments in this field are also prospected.

Uncertainty Analysis in Humidity Measurements by the Psychrometer Method

PubMed Central

Chen, Jiunyuan; Chen, Chiachung

2017-01-01

The most common and cheap indirect technique to measure relative humidity is by using psychrometer based on a dry and a wet temperature sensor. In this study, the measurement uncertainty of relative humidity was evaluated by this indirect method with some empirical equations for calculating relative humidity. Among the six equations tested, the Penman equation had the best predictive ability for the dry bulb temperature range of 15–50 °C. At a fixed dry bulb temperature, an increase in the wet bulb depression increased the error. A new equation for the psychrometer constant was established by regression analysis. This equation can be computed by using a calculator. The average predictive error of relative humidity was <0.1% by this new equation. The measurement uncertainty of the relative humidity affected by the accuracy of dry and wet bulb temperature and the numeric values of measurement uncertainty were evaluated for various conditions. The uncertainty of wet bulb temperature was the main factor on the RH measurement uncertainty. PMID:28216599

Uncertainty Analysis in Humidity Measurements by the Psychrometer Method.

PubMed

Chen, Jiunyuan; Chen, Chiachung

2017-02-14

The most common and cheap indirect technique to measure relative humidity is by using psychrometer based on a dry and a wet temperature sensor. In this study, the measurement uncertainty of relative humidity was evaluated by this indirect method with some empirical equations for calculating relative humidity. Among the six equations tested, the Penman equation had the best predictive ability for the dry bulb temperature range of 15-50 °C. At a fixed dry bulb temperature, an increase in the wet bulb depression increased the error. A new equation for the psychrometer constant was established by regression analysis. This equation can be computed by using a calculator. The average predictive error of relative humidity was <0.1% by this new equation. The measurement uncertainty of the relative humidity affected by the accuracy of dry and wet bulb temperature and the numeric values of measurement uncertainty were evaluated for various conditions. The uncertainty of wet bulb temperature was the main factor on the RH measurement uncertainty.

New insight in quantitative analysis of vascular permeability during immune reaction (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kalchenko, Vyacheslav; Molodij, Guillaume; Kuznetsov, Yuri; Smolyakov, Yuri; Israeli, David; Meglinski, Igor; Harmelin, Alon

2016-03-01

The use of fluorescence imaging of vascular permeability becomes a golden standard for assessing the inflammation process during experimental immune response in vivo. The use of the optical fluorescence imaging provides a very useful and simple tool to reach this purpose. The motivation comes from the necessity of a robust and simple quantification and data presentation of inflammation based on a vascular permeability. Changes of the fluorescent intensity, as a function of time is a widely accepted method to assess the vascular permeability during inflammation related to the immune response. In the present study we propose to bring a new dimension by applying a more sophisticated approach to the analysis of vascular reaction by using a quantitative analysis based on methods derived from astronomical observations, in particular by using a space-time Fourier filtering analysis followed by a polynomial orthogonal modes decomposition. We demonstrate that temporal evolution of the fluorescent intensity observed at certain pixels correlates quantitatively to the blood flow circulation at normal conditions. The approach allows to determine the regions of permeability and monitor both the fast kinetics related to the contrast material distribution in the circulatory system and slow kinetics associated with extravasation of the contrast material. Thus, we introduce a simple and convenient method for fast quantitative visualization of the leakage related to the inflammatory (immune) reaction in vivo.

Finite element analysis (FEA) analysis of the preflex beam

NASA Astrophysics Data System (ADS)

Wan, Lijuan; Gao, Qilang

2017-10-01

The development of finite element analysis (FEA) has been relatively mature, and is one of the important means of structural analysis. This method changes the problem that the research of complex structure in the past needs to be done by a large number of experiments. Through the finite element method, the numerical simulation of the structure can be used to achieve a variety of static and dynamic simulation analysis of the mechanical problems, it is also convenient to study the parameters of the structural parameters. Combined with a certain number of experiments to verify the simulation model can be completed in the past all the needs of experimental research. The nonlinear finite element method is used to simulate the flexural behavior of the prestressed composite beams with corrugated steel webs. The finite element analysis is used to understand the mechanical properties of the structure under the action of bending load.

Traceable Coulomb blockade thermometry

NASA Astrophysics Data System (ADS)

Hahtela, O.; Mykkänen, E.; Kemppinen, A.; Meschke, M.; Prunnila, M.; Gunnarsson, D.; Roschier, L.; Penttilä, J.; Pekola, J.

2017-02-01

We present a measurement and analysis scheme for determining traceable thermodynamic temperature at cryogenic temperatures using Coulomb blockade thermometry. The uncertainty of the electrical measurement is improved by utilizing two sampling digital voltmeters instead of the traditional lock-in technique. The remaining uncertainty is dominated by that of the numerical analysis of the measurement data. Two analysis methods are demonstrated: numerical fitting of the full conductance curve and measuring the height of the conductance dip. The complete uncertainty analysis shows that using either analysis method the relative combined standard uncertainty (k  =  1) in determining the thermodynamic temperature in the temperature range from 20 mK to 200 mK is below 0.5%. In this temperature range, both analysis methods produced temperature estimates that deviated from 0.39% to 0.67% from the reference temperatures provided by a superconducting reference point device calibrated against the Provisional Low Temperature Scale of 2000.

An analysis of life expectancy of airplane wings in normal cruising flight

NASA Technical Reports Server (NTRS)

Putnam, Abbott A

1945-01-01

In order to provide a basis for judging the relative importance of wing failure by fatigue and by single intense gusts, an analysis of wing life for normal cruising flight was made based on data on the frequency of atmospheric gusts. The independent variables considered in the analysis included stress-concentration factor, stress-load relation, wing loading, design and cruising speeds, design gust velocity, and airplane size. Several methods for estimating fatigue life from gust frequencies are discussed. The procedure selected for the analysis is believed to be simple and reasonably accurate, though slightly conservative.

An Analysis of Transmission and Storage Gains from Sliding Checksum Methods

DTIC Science & Technology

1998-11-01

analysed a protocol "rsync" for synchronising related files at different ends of a communications channel with a minimum of transmitted data. This report...Sliding Checksum Methods Executive Summary In a previous report we described, modelled and analysed a protocol "rsync" for synchronising related...collaborative writing of documentation and synchronisation of distributed databases in the situation where no one location is aware of the differences

Statistical Analysis of a Class: Monte Carlo and Multiple Imputation Spreadsheet Methods for Estimation and Extrapolation

ERIC Educational Resources Information Center

Fish, Laurel J.; Halcoussis, Dennis; Phillips, G. Michael

2017-01-01

The Monte Carlo method and related multiple imputation methods are traditionally used in math, physics and science to estimate and analyze data and are now becoming standard tools in analyzing business and financial problems. However, few sources explain the application of the Monte Carlo method for individuals and business professionals who are…

Soil structure characterized using computed tomographic images

Treesearch

Zhanqi Cheng; Stephen H. Anderson; Clark J. Gantzer; J. W. Van Sambeek

2003-01-01

Fractal analysis of soil structure is a relatively new method for quantifying the effects of management systems on soil properties and quality. The objective of this work was to explore several methods of studying images to describe and quantify structure of soils under forest management. This research uses computed tomography and a topological method called Multiple...

Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

PubMed Central

2010-01-01

Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is preferable, in particular if the gene selection is successful. However, this is an area that needs to be studied further in order to draw any general conclusions. Conclusions The choice of cluster analysis, and in particular gene selection, has a large impact on the ability to cluster individuals correctly based on expression profiles. Normalization has a positive effect, but the relative performance of different normalizations is an area that needs more research. In summary, although clustering, gene selection and normalization are considered standard methods in bioinformatics, our comprehensive analysis shows that selecting the right methods, and the right combinations of methods, is far from trivial and that much is still unexplored in what is considered to be the most basic analysis of genomic data. PMID:20937082

Monitoring Method of Cow Anthrax Based on Gis and Spatial Statistical Analysis

NASA Astrophysics Data System (ADS)

Li, Lin; Yang, Yong; Wang, Hongbin; Dong, Jing; Zhao, Yujun; He, Jianbin; Fan, Honggang

Geographic information system (GIS) is a computer application system, which possesses the ability of manipulating spatial information and has been used in many fields related with the spatial information management. Many methods and models have been established for analyzing animal diseases distribution models and temporal-spatial transmission models. Great benefits have been gained from the application of GIS in animal disease epidemiology. GIS is now a very important tool in animal disease epidemiological research. Spatial analysis function of GIS can be widened and strengthened by using spatial statistical analysis, allowing for the deeper exploration, analysis, manipulation and interpretation of spatial pattern and spatial correlation of the animal disease. In this paper, we analyzed the cow anthrax spatial distribution characteristics in the target district A (due to the secret of epidemic data we call it district A) based on the established GIS of the cow anthrax in this district in combination of spatial statistical analysis and GIS. The Cow anthrax is biogeochemical disease, and its geographical distribution is related closely to the environmental factors of habitats and has some spatial characteristics, and therefore the correct analysis of the spatial distribution of anthrax cow for monitoring and the prevention and control of anthrax has a very important role. However, the application of classic statistical methods in some areas is very difficult because of the pastoral nomadic context. The high mobility of livestock and the lack of enough suitable sampling for the some of the difficulties in monitoring currently make it nearly impossible to apply rigorous random sampling methods. It is thus necessary to develop an alternative sampling method, which could overcome the lack of sampling and meet the requirements for randomness. The GIS computer application software ArcGIS9.1 was used to overcome the lack of data of sampling sites.Using ArcGIS 9.1 and GEODA to analyze the cow anthrax spatial distribution of district A. we gained some conclusions about cow anthrax' density: (1) there is a spatial clustering model. (2) there is an intensely spatial autocorrelation. We established a prediction model to estimate the anthrax distribution based on the spatial characteristic of the density of cow anthrax. Comparing with the true distribution, the prediction model has a well coincidence and is feasible to the application. The method using a GIS tool facilitates can be implemented significantly in the cow anthrax monitoring and investigation, and the space statistics - related prediction model provides a fundamental use for other study on space-related animal diseases.

Patient Involvement in Safe Delivery: A Qualitative Study.

PubMed

Olfati, Forozun; Asefzadeh, Saeid; Changizi, Nasrin; Keramat, Afsaneh; Yunesian, Masud

2015-09-28

Patient involvement in safe delivery planning is considered important yet not widely practiced. The present study aimed at identifythe factors that affect patient involvementin safe delivery, as recommended by parturient women. This study was part of a qualitative research conducted by content analysis method and purposive sampling in 2013.The data were collected through 63 semi-structured interviews in4 hospitalsand analyzed using thematic content analysis. The participants in this research were women before discharge and after delivery. Findings were analyzed using Colaizzi's method. Four categories of factors that could affect patient involvement in safe delivery emerged from our analysis: patient-related (true and false beliefs, literacy, privacy, respect for patient), illness-related (pain, type of delivery, patient safety incidents), health care professional-relatedand task-related factors (behavior, monitoring &training), health care setting-related (financial aspects, facilities). More research is needed to explore the factors affecting the participation of mothers. It is therefore, recommended to: 1) take notice of mother education, their husbands, midwives and specialists; 2) provide pregnant women with insurance coverage from the outset of pregnancy, especially during prenatal period; 3) form a labor pain committee consisting of midwives, obstetricians, and anesthesiologists in order to identify the preferred painless labor methods based on the existing facilities and conditions, 4) carry out research on observing patients' privacy and dignity; 5) pay more attention on the factors affecting cesarean.

A graphic method for identification of novel glioma related genes.

PubMed

Gao, Yu-Fei; Shu, Yang; Yang, Lei; He, Yi-Chun; Li, Li-Peng; Huang, GuaHua; Li, Hai-Peng; Jiang, Yang

2014-01-01

Glioma, as the most common and lethal intracranial tumor, is a serious disease that causes many deaths every year. Good comprehension of the mechanism underlying this disease is very helpful to design effective treatments. However, up to now, the knowledge of this disease is still limited. It is an important step to understand the mechanism underlying this disease by uncovering its related genes. In this study, a graphic method was proposed to identify novel glioma related genes based on known glioma related genes. A weighted graph was constructed according to the protein-protein interaction information retrieved from STRING and the well-known shortest path algorithm was employed to discover novel genes. The following analysis suggests that some of them are related to the biological process of glioma, proving that our method was effective in identifying novel glioma related genes. We hope that the proposed method would be applied to study other diseases and provide useful information to medical workers, thereby designing effective treatments of different diseases.

Pulse analysis of acoustic emission signals. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Houghton, J. R.

1976-01-01

A method for the signature analysis of pulses in the frequency domain and the time domain is presented. Fourier spectrum, Fourier transfer function, shock spectrum and shock spectrum ratio are examined in the frequency domain analysis, and pulse shape deconvolution is developed for use in the time domain analysis. To demonstrate the relative sensitivity of each of the methods to small changes in the pulse shape, signatures of computer modeled systems with analytical pulses are presented. Optimization techniques are developed and used to indicate the best design parameters values for deconvolution of the pulse shape. Several experiments are presented that test the pulse signature analysis methods on different acoustic emission sources. These include acoustic emissions associated with: (1) crack propagation, (2) ball dropping on a plate, (3) spark discharge and (4) defective and good ball bearings.

Analysis of backward error recovery for concurrent processes with recovery blocks

NASA Technical Reports Server (NTRS)

Shin, K. G.; Lee, Y. H.

1982-01-01

Three different methods of implementing recovery blocks (RB's). These are the asynchronous, synchronous, and the pseudo recovery point implementations. Pseudo recovery points so that unbounded rollback may be avoided while maintaining process autonomy are proposed. Probabilistic models for analyzing these three methods under standard assumptions in computer performance analysis, i.e., exponential distributions for related random variables were developed. The interval between two successive recovery lines for asynchronous RB's mean loss in computation power for the synchronized method, and additional overhead and rollback distance in case PRP's are used were estimated.

Determination of Nutrient Intakes by a Modified Visual Estimation Method and Computerized Nutritional Analysis for Dietary Assessments

DTIC Science & Technology

1987-09-01

a useful average for population studies, do not delay data processing , and is relatively Inexpensive. Using MVEN and observing recipe preparation...for population studies, do not delay data processing , and is relatively inexpensive. Using HVEM and observing recipe preparation procedures improve the...extensive review of the procedures and problems in design, collection, analysis, processing and interpretation of dietary survey data for individuals

Deriving pathway maps from automated text analysis using a grammar-based approach.

PubMed

Olsson, Björn; Gawronska, Barbara; Erlendsson, Björn

2006-04-01

We demonstrate how automated text analysis can be used to support the large-scale analysis of metabolic and regulatory pathways by deriving pathway maps from textual descriptions found in the scientific literature. The main assumption is that correct syntactic analysis combined with domain-specific heuristics provides a good basis for relation extraction. Our method uses an algorithm that searches through the syntactic trees produced by a parser based on a Referent Grammar formalism, identifies relations mentioned in the sentence, and classifies them with respect to their semantic class and epistemic status (facts, counterfactuals, hypotheses). The semantic categories used in the classification are based on the relation set used in KEGG (Kyoto Encyclopedia of Genes and Genomes), so that pathway maps using KEGG notation can be automatically generated. We present the current version of the relation extraction algorithm and an evaluation based on a corpus of abstracts obtained from PubMed. The results indicate that the method is able to combine a reasonable coverage with high accuracy. We found that 61% of all sentences were parsed, and 97% of the parse trees were judged to be correct. The extraction algorithm was tested on a sample of 300 parse trees and was found to produce correct extractions in 90.5% of the cases.

Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks

PubMed Central

Zhang, Yihua; Li, Wan; Feng, Yuyan; Guo, Shanshan; Zhao, Xilei; Wang, Yahui; He, Yuehan; He, Weiming; Chen, Lina

2017-01-01

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD. PMID:29262568

Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks.

PubMed

Zhang, Yihua; Li, Wan; Feng, Yuyan; Guo, Shanshan; Zhao, Xilei; Wang, Yahui; He, Yuehan; He, Weiming; Chen, Lina

2017-11-28

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD.

Stability-Indicating Related Substances HPLC Method for Droxidopa and Characterization of Related Substances Using LC-MS and NMR.

PubMed

Kumar, Thangarathinam; Ramya, Mohandass; Arockiasamy Xavier, S J

2016-11-01

Stress degradation studies using high-performance liquid chromatography (HPLC) was performed and validated for Droxidopa (L-DOPS). Droxidopa was susceptible to acid hydrolysis (0.1 N HCl), alkaline hydrolysis (0.15 N NaOH) and thermal degradation (105°C). It was found to be resistant to white light, oxidation and UV light exposure (72 h). The thermal, acid and alkali degradation impurities were detected with the retention time (RT) of 12.7, 19.25 and 22.95 min. Our HPLC method detected process impurities (2R,3R)-2-amino-3-(3,4-dihydroxyphenyl)-3-hydroxypropionic acid (Impurity H), N-Hydroxypthalimide (Impurity N), (2R,3S)-2-amino-3-(benzo[d][1,3]dioxol-5-yl)-3-hydroxypropionic acid (Impurity L) and L-threo n-phthaloyl-3-(3, 4-dihydroxyphenyl)-serine (Intermediate) with RTs of 3.48, 15.5, 25.76 and 28.0 min. The related substances were further characterized and confirmed by liquid chromatography-mass spectroscopy (LC-MS), and nuclear magnetic resonance spectroscopy analysis. Our HPLC method detected up to 0.05 µg/mL of Droxidopa with S/N > 3.0 and quantified up to 0.10 µg /mL of Droxidopa with S/N ratio > 10.0. Droxidopa was highly stable for 12 h after its preparation for HPLC analysis. Our newly developed HPLC method was highly precise, specific, reliable and accurate for the analysis of Droxidopa and its related substances. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Survey of Legionella spp. in Mud Spring Recreation Area

NASA Astrophysics Data System (ADS)

Hsu, B.-M.; Ma, P.-H.; Su, I.-Z.; Chen, N.-S.

2009-04-01

Legionella genera are parasites of FLA, and intracellular bacterial replication within the FLA plays a major role in the transmission of disease. At least 13 FLA species—including Acanthamoeba spp., Naegleria spp., and Hartmannella spp.—support intracellular bacterial replication. In the study, Legionellae were detected with microbial culture or by direct DNA extraction and analysis from concentrated water samples or cultured free-living amoebae, combined with molecular methods that allow the taxonomic identification of these pathogens. The water samples were taken from a mud spring recreation area located in a mud-rock-formation area in southern Taiwan. Legionella were detected in 15 of the 34 samples (44.1%). Four of the 34 samples analyzed by Legionella culture were positive for Legionella, five of 34 were positive for Legionella when analyzed by direct DNA extraction and analysis, and 11 of 34 were positive for amoebae-resistant Legionella when analyzed by FLA culture. Ten samples were shown to be positive for Legionella by one analysis method and five samples were shown to be positive by two analysis methods. However, Legionella was detected in no sample by all three analysis methods. This suggests that the three analysis methods should be used together to detect Legionella in aquatic environments. In this study, L. pneumophila serotype 6 coexisted with A. polyphaga, and two uncultured Legionella spp. coexisted with either H. vermiformis or N. australiensis. Of the unnamed Legionella genotypes detected in six FLA culture samples, three were closely related to L. waltersii and the other three were closely related to L. pneumophila serotype 6. Legionella pneumophila serotype 6, L. drancourtii, and L. waltersii are noted endosymbionts of FLA and are categorized as pathogenic bacteria. This is significant for human health because these Legionella exist within FLA and thus come into contact with typically immunocompromised people.

Using Trial-Based Functional Analysis to Design Effective Interventions for Students Diagnosed with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Larkin, Wallace; Hawkins, Renee O.; Collins, Tai

2016-01-01

Functional behavior assessments and function-based interventions are effective methods for addressing the challenging behaviors of children; however, traditional functional analysis has limitations that impact usability in applied settings. Trial-based functional analysis addresses concerns relating to the length of time, level of expertise…

Pathway analysis of high-throughput biological data within a Bayesian network framework.

PubMed

Isci, Senol; Ozturk, Cengizhan; Jones, Jon; Otu, Hasan H

2011-06-15

Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Proposed method takes into account the connectivity and relatedness between nodes of the pathway through factoring pathway topology in its model. Our simulations using synthetic data demonstrated robustness of our approach. We tested proposed method, Bayesian Pathway Analysis (BPA), on human microarray data regarding renal cell carcinoma (RCC) and compared our results with gene set enrichment analysis. BPA was able to find broader and more specific pathways related to RCC. Accompanying BPA software (BPAS) package is freely available for academic use at http://bumil.boun.edu.tr/bpa.

High resolution melting (HRM) analysis of DNA--its role and potential in food analysis.

PubMed

Druml, Barbara; Cichna-Markl, Margit

2014-09-01

DNA based methods play an increasing role in food safety control and food adulteration detection. Recent papers show that high resolution melting (HRM) analysis is an interesting approach. It involves amplification of the target of interest in the presence of a saturation dye by the polymerase chain reaction (PCR) and subsequent melting of the amplicons by gradually increasing the temperature. Since the melting profile depends on the GC content, length, sequence and strand complementarity of the product, HRM analysis is highly suitable for the detection of single-base variants and small insertions or deletions. The review gives an introduction into HRM analysis, covers important aspects in the development of an HRM analysis method and describes how HRM data are analysed and interpreted. Then we discuss the potential of HRM analysis based methods in food analysis, i.e. for the identification of closely related species and cultivars and the identification of pathogenic microorganisms. Copyright © 2014 Elsevier Ltd. All rights reserved.

An exploration of function analysis and function allocation in the commercial flight domain

NASA Technical Reports Server (NTRS)

Mcguire, James C.; Zich, John A.; Goins, Richard T.; Erickson, Jeffery B.; Dwyer, John P.; Cody, William J.; Rouse, William B.

1991-01-01

The applicability is explored of functional analysis methods to support cockpit design. Specifically, alternative techniques are studied for ensuring an effective division of responsibility between the flight crew and automation. A functional decomposition is performed of the commercial flight domain to provide the information necessary to support allocation decisions and demonstrate methodology for allocating functions to flight crew or to automation. The function analysis employed 'bottom up' and 'top down' analyses and demonstrated the comparability of identified functions, using the 'lift off' segment of the 'take off' phase as a test case. The normal flight mission and selected contingencies were addressed. Two alternative methods for using the functional description in the allocation of functions between man and machine were investigated. The two methods were compared in order to ascertain their relative strengths and weaknesses. Finally, conclusions were drawn regarding the practical utility of function analysis methods.

A simple analytical procedure to replace HPLC for monitoring treatment concentrations of chloramine-T on fish culture facilities

USGS Publications Warehouse

Dawson, Verdel K.; Meinertz, Jeffery R.; Schmidt, Larry J.; Gingerich, William H.

2003-01-01

Concentrations of chloramine-T must be monitored during experimental treatments of fish when studying the effectiveness of the drug for controlling bacterial gill disease. A surrogate analytical method for analysis of chloramine-T to replace the existing high-performance liquid chromatography (HPLC) method is described. A surrogate method was needed because the existing HPLC method is expensive, requires a specialist to use, and is not generally available at fish hatcheries. Criteria for selection of a replacement method included ease of use, analysis time, cost, safety, sensitivity, accuracy, and precision. The most promising approach was to use the determination of chlorine concentrations as an indicator of chloramine-T. Of the currently available methods for analysis of chlorine, the DPD (N,N-diethyl-p-phenylenediamine) colorimetric method best fit the established criteria. The surrogate method was evaluated under a variety of water quality conditions. Regression analysis of all DPD colorimetric analyses with the HPLC values produced a linear model (Y=0.9602 X+0.1259) with an r2 value of 0.9960. The average accuracy (percent recovery) of the DPD method relative to the HPLC method for the combined set of water quality data was 101.5%. The surrogate method was also evaluated with chloramine-T solutions that contained various concentrations of fish feed or selected densities of rainbow trout. When samples were analyzed within 2 h, the results of the surrogate method were consistent with those of the HPLC method. When samples with high concentrations of organic material were allowed to age more than 2 h before being analyzed, the DPD method seemed to be susceptible to interference, possibly from the development of other chloramine compounds. However, even after aging samples 6 h, the accuracy of the surrogate DPD method relative to the HPLC method was within the range of 80–120%. Based on the data comparing the two methods, the U.S. Food and Drug Administration has concluded that the DPD colorimetric method is appropriate to use to measure chloramine-T in water during pivotal efficacy trials designed to support the approval of chloramine-T for use in fish culture.

Identification of Poly-N-Acetyllactosamine-Carrying Glycoproteins from HL-60 Human Promyelocytic Leukemia Cells Using a Site-Specific Glycome Analysis Method, Glyco-RIDGE

NASA Astrophysics Data System (ADS)

Togayachi, Akira; Tomioka, Azusa; Fujita, Mika; Sukegawa, Masako; Noro, Erika; Takakura, Daisuke; Miyazaki, Michiyo; Shikanai, Toshihide; Narimatsu, Hisashi; Kaji, Hiroyuki

2018-04-01

To elucidate the relationship between the protein function and the diversity and heterogeneity of glycans conjugated to the protein, glycosylation sites, glycan variation, and glycan proportions at each site of the glycoprotein must be analyzed. Glycopeptide-based structural analysis technology using mass spectrometry has been developed; however, complicated analyses of complex spectra obtained by multistage fragmentation are necessary, and sensitivity and throughput of the analyses are low. Therefore, we developed a liquid chromatography/mass spectrometry (MS)-based glycopeptide analysis method to reveal the site-specific glycome (Glycan heterogeneity-based Relational IDentification of Glycopeptide signals on Elution profile, Glyco-RIDGE). This method used accurate masses and retention times of glycopeptides, without requiring MS2, and could be applied to complex mixtures. To increase the number of identified peptide, fractionation of sample glycopeptides for reduction of sample complexity is required. Therefore, in this study, glycopeptides were fractionated into four fractions by hydrophilic interaction chromatography, and each fraction was analyzed using the Glyco-RIDGE method. As a result, many glycopeptides having long glycans were enriched in the highest hydrophilic fraction. Based on the monosaccharide composition, these glycans were thought to be poly-N-acetyllactosamine (polylactosamine [pLN]), and 31 pLN-carrier proteins were identified in HL-60 cells. Gene ontology enrichment analysis revealed that pLN carriers included many molecules related to signal transduction, receptors, and cell adhesion. Thus, these findings provided important insights into the analysis of the glycoproteome using our novel Glyco-RIDGE method. [Figure not available: see fulltext.

Method for high resolution magnetic resonance analysis using magic angle technique

DOEpatents

Wind, Robert A.; Hu, Jian Zhi

2003-12-30

A method of performing a magnetic resonance analysis of a biological object that includes placing the object in a main magnetic field (that has a static field direction) and in a radio frequency field; rotating the object at a frequency of less than about 100 Hz around an axis positioned at an angle of about 54.degree.44' relative to the main magnetic static field direction; pulsing the radio frequency to provide a sequence that includes a phase-corrected magic angle turning pulse segment; and collecting data generated by the pulsed radio frequency. The object may be reoriented about the magic angle axis between three predetermined positions that are related to each other by 120.degree.. The main magnetic field may be rotated mechanically or electronically. Methods for magnetic resonance imaging of the object are also described.

Method for high resolution magnetic resonance analysis using magic angle technique

DOEpatents

Wind, Robert A.; Hu, Jian Zhi

2004-12-28

A method of performing a magnetic resonance analysis of a biological object that includes placing the object in a main magnetic field (that has a static field direction) and in a radio frequency field; rotating the object at a frequency of less than about 100 Hz around an axis positioned at an angle of about 54.degree.44' relative to the main magnetic static field direction; pulsing the radio frequency to provide a sequence that includes a phase-corrected magic angle turning pulse segment; and collecting data generated by the pulsed radio frequency. The object may be reoriented about the magic angle axis between three predetermined positions that are related to each other by 120.degree.. The main magnetic field may be rotated mechanically or electronically. Methods for magnetic resonance imaging of the object are also described.

Determination of isocyanate groups in the organic intermediates by reaction-based headspace gas chromatography.

PubMed

Xie, Wei-Qi; Chai, Xin-Sheng

2016-10-14

This work reports on a novel method for the determination of isocyanate groups in the related organic intermediates by a reaction-based headspace gas chromatography. The method is based on measuring the CO 2 formed from the reaction between the isocyanate groups in the organic intermediates and water in a closed headspace sample vial at 45°C for 20min. The results showed that the method has a good precision and accuracy, in which the relative standard deviation in the repeatability measurement was 5.26%, and the relative differences between the data obtained by the HS-GC method and the reference back-titration method were within 9.42%. The present method is simple and efficient and is particularly suitable to be used for determining the isocyanate groups in the batch sample analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Algorithms for sum-of-squares-based stability analysis and control design of uncertain nonlinear systems

NASA Astrophysics Data System (ADS)

Ataei-Esfahani, Armin

In this dissertation, we present algorithmic procedures for sum-of-squares based stability analysis and control design for uncertain nonlinear systems. In particular, we consider the case of robust aircraft control design for a hypersonic aircraft model subject to parametric uncertainties in its aerodynamic coefficients. In recent years, Sum-of-Squares (SOS) method has attracted increasing interest as a new approach for stability analysis and controller design of nonlinear dynamic systems. Through the application of SOS method, one can describe a stability analysis or control design problem as a convex optimization problem, which can efficiently be solved using Semidefinite Programming (SDP) solvers. For nominal systems, the SOS method can provide a reliable and fast approach for stability analysis and control design for low-order systems defined over the space of relatively low-degree polynomials. However, The SOS method is not well-suited for control problems relating to uncertain systems, specially those with relatively high number of uncertainties or those with non-affine uncertainty structure. In order to avoid issues relating to the increased complexity of the SOS problems for uncertain system, we present an algorithm that can be used to transform an SOS problem with uncertainties into a LMI problem with uncertainties. A new Probabilistic Ellipsoid Algorithm (PEA) is given to solve the robust LMI problem, which can guarantee the feasibility of a given solution candidate with an a-priori fixed probability of violation and with a fixed confidence level. We also introduce two approaches to approximate the robust region of attraction (RROA) for uncertain nonlinear systems with non-affine dependence on uncertainties. The first approach is based on a combination of PEA and SOS method and searches for a common Lyapunov function, while the second approach is based on the generalized Polynomial Chaos (gPC) expansion theorem combined with the SOS method and searches for parameter-dependent Lyapunov functions. The control design problem is investigated through a case study of a hypersonic aircraft model with parametric uncertainties. Through time-scale decomposition and a series of function approximations, the complexity of the aircraft model is reduced to fall within the capability of SDP solvers. The control design problem is then formulated as a convex problem using the dual of the Lyapunov theorem. A nonlinear robust controller is searched using the combined PEA/SOS method. The response of the uncertain aircraft model is evaluated for two sets of pilot commands. As the simulation results show, the aircraft remains stable under up to 50% uncertainty in aerodynamic coefficients and can follow the pilot commands.

Identification of faulty sensor using relative partial decomposition via independent component analysis

NASA Astrophysics Data System (ADS)

Wang, Z.; Quek, S. T.

2015-07-01

Performance of any structural health monitoring algorithm relies heavily on good measurement data. Hence, it is necessary to employ robust faulty sensor detection approaches to isolate sensors with abnormal behaviour and exclude the highly inaccurate data in the subsequent analysis. The independent component analysis (ICA) is implemented to detect the presence of sensors showing abnormal behaviour. A normalized form of the relative partial decomposition contribution (rPDC) is proposed to identify the faulty sensor. Both additive and multiplicative types of faults are addressed and the detectability illustrated using a numerical and an experimental example. An empirical method to establish control limits for detecting and identifying the type of fault is also proposed. The results show the effectiveness of the ICA and rPDC method in identifying faulty sensor assuming that baseline cases are available.

Advancing the application of systems thinking in health: provider payment and service supply behaviour and incentives in the Ghana National Health Insurance Scheme – a systems approach

PubMed Central

2014-01-01

Background Assuring equitable universal access to essential health services without exposure to undue financial hardship requires adequate resource mobilization, efficient use of resources, and attention to quality and responsiveness of services. The way providers are paid is a critical part of this process because it can create incentives and patterns of behaviour related to supply. The objective of this work was to describe provider behaviour related to supply of health services to insured clients in Ghana and the influence of provider payment methods on incentives and behaviour. Methods A mixed methods study involving grey and published literature reviews, as well as health management information system and primary data collection and analysis was used. Primary data collection involved in-depth interviews, observations of time spent obtaining service, prescription analysis, and exit interviews with clients. Qualitative data was analysed manually to draw out themes, commonalities, and contrasts. Quantitative data was analysed in Excel and Stata. Causal loop and cause tree diagrams were used to develop a qualitative explanatory model of provider supply incentives and behaviour related to payment method in context. Results There are multiple provider payment methods in the Ghanaian health system. National Health Insurance provider payment methods are the most recent additions. At the time of the study, the methods used nationwide were the Ghana Diagnostic Related Groupings payment for services and an itemized and standardized fee schedule for medicines. The influence of provider payment method on supply behaviour was sometimes intuitive and sometimes counter intuitive. It appeared to be related to context and the interaction of the methods with context and each other rather than linearly to any given method. Conclusions As countries work towards Universal Health Coverage, there is a need to holistically design, implement, and manage provider payment methods reforms from systems rather than linear perspectives, since the latter fail to recognize the effects of context and the between-methods and context interactions in producing net effects. PMID:25096303

Biomechanical evaluation of three different fixation methods of the Chevron osteotomy of the olecranon: an analysis with Roentgen Stereophotogrammatic Analysis.

PubMed

Wagener, Marc L; Driesprong, Marco; Heesterbeek, Petra J C; Verdonschot, Nico; Eygendaal, Denise

2013-08-01

In this study three different methods for fixating the Chevron osteotomy of the olecranon are evaluated. Transcortical fixed Kirschner wires with a tension band, a large cancellous screw with a tension band, and a large cancellous screw alone are compared using Roentgen Stereophotogrammatic Analysis (RSA). The different fixation methods were tested in 17 cadaver specimens by applying increasing repetitive force to the triceps tendon. Forces applied were 200N, 350N, and 500N. Translation and rotation of the osteotomy were recorded using Roentgen Stereophotogrammatic Analysis. Both the fixations with a cancellous screw with tension band and with bi-cortical placed Kirschner wires with a tension band provide enough stability to withstand the forces of normal daily use. Since fixation with a cancellous screw with tension band is a fast and easy method and is related to minimal soft tissue damage this method can preferably be used for fixation of a Chevron osteotomy of the olecranon. © 2013.

Weighted analysis of paired microarray experiments.

PubMed

Kristiansson, Erik; Sjögren, Anders; Rudemo, Mats; Nerman, Olle

2005-01-01

In microarray experiments quality often varies, for example between samples and between arrays. The need for quality control is therefore strong. A statistical model and a corresponding analysis method is suggested for experiments with pairing, including designs with individuals observed before and after treatment and many experiments with two-colour spotted arrays. The model is of mixed type with some parameters estimated by an empirical Bayes method. Differences in quality are modelled by individual variances and correlations between repetitions. The method is applied to three real and several simulated datasets. Two of the real datasets are of Affymetrix type with patients profiled before and after treatment, and the third dataset is of two-colour spotted cDNA type. In all cases, the patients or arrays had different estimated variances, leading to distinctly unequal weights in the analysis. We suggest also plots which illustrate the variances and correlations that affect the weights computed by our analysis method. For simulated data the improvement relative to previously published methods without weighting is shown to be substantial.

Resilience Metrics for the Electric Power System: A Performance-Based Approach.

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

Vugrin, Eric D.; Castillo, Andrea R; Silva-Monroy, Cesar Augusto

Grid resilience is a concept related to a power system's ability to continue operating and delivering power even in the event that low probability, high-consequence disruptions such as hurricanes, earthquakes, and cyber-attacks occur. Grid resilience objectives focus on managing and, ideally, minimizing potential consequences that occur as a result of these disruptions. Currently, no formal grid resilience definitions, metrics, or analysis methods have been universally accepted. This document describes an effort to develop and describe grid resilience metrics and analysis methods. The metrics and methods described herein extend upon the Resilience Analysis Process (RAP) developed by Watson et al. formore » the 2015 Quadrennial Energy Review. The extension allows for both outputs from system models and for historical data to serve as the basis for creating grid resilience metrics and informing grid resilience planning and response decision-making. This document describes the grid resilience metrics and analysis methods. Demonstration of the metrics and methods is shown through a set of illustrative use cases.« less

Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods

NASA Astrophysics Data System (ADS)

Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.

2011-12-01

Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion of random effects. However, in the biased case, only Method 3 correctly estimates all the unknown parameters, and both Methods 1 and 2 provide wrong values for the biased parameters. The synthetic case study demonstrates that if the covariance matrix for PCA analysis is inconsistent with true models, the PCA methods with geometric or MCMC sampling will provide incorrect estimates.

Simultaneous determination of flubendiamide its metabolite desiodo flubendiamide residues in cabbage, tomato and pigeon pea by HPLC.

PubMed

Paramasivam, M; Banerjee, Hemanta

2011-10-01

A sensitive and simple method for simultaneous analysis of flubendiamide and its metabolite desiodo flubendiamide in cabbage, tomato and pigeon pea has been developed. The residues were extracted with QuEChERS method followed by dispersive solid-phase extraction with primary secondary amine sorbent to remove co extractives, prior to analysis by HPLC coupled with UV-Vis detector. The recoveries of flubendiamide and desiodo flubendiamide were ranged from 85.1 to 98.5% and 85.9 to 97.1% respectively with relative standard deviations (RSD) less than 5% and sensitivity of 0.01 μg g(-1). The method offers a less expensive and safer alternative to the existing residue analysis methods for vegetables. © Springer Science+Business Media, LLC 2011

Ice Growth Measurements from Image Data to Support Ice Crystal and Mixed-Phase Accretion Testing

NASA Technical Reports Server (NTRS)

Struk, Peter M.; Lynch, Christopher J.

2012-01-01

This paper describes the imaging techniques as well as the analysis methods used to measure the ice thickness and growth rate in support of ice-crystal icing tests performed at the National Research Council of Canada (NRC) Research Altitude Test Facility (RATFac). A detailed description of the camera setup, which involves both still and video cameras, as well as the analysis methods using the NASA Spotlight software, are presented. Two cases, one from two different test entries, showing significant ice growth are analyzed in detail describing the ice thickness and growth rate which is generally linear. Estimates of the bias uncertainty are presented for all measurements. Finally some of the challenges related to the imaging and analysis methods are discussed as well as methods used to overcome them.

Ice Growth Measurements from Image Data to Support Ice-Crystal and Mixed-Phase Accretion Testing

NASA Technical Reports Server (NTRS)

Struk, Peter, M; Lynch, Christopher, J.

2012-01-01

This paper describes the imaging techniques as well as the analysis methods used to measure the ice thickness and growth rate in support of ice-crystal icing tests performed at the National Research Council of Canada (NRC) Research Altitude Test Facility (RATFac). A detailed description of the camera setup, which involves both still and video cameras, as well as the analysis methods using the NASA Spotlight software, are presented. Two cases, one from two different test entries, showing significant ice growth are analyzed in detail describing the ice thickness and growth rate which is generally linear. Estimates of the bias uncertainty are presented for all measurements. Finally some of the challenges related to the imaging and analysis methods are discussed as well as methods used to overcome them.

Development of Novel Noninvasive Methods of Stress Assessment in Baleen Whales

DTIC Science & Technology

2015-09-30

large whales. Few methods exist for assessment of physiological stress levels of free-swimming cetaceans (Amaral 2010, ONR 2010, Hunt et al. 2013...adrenal hormone aldosterone . Our aim in this project is to further develop both techniques - respiratory hormone analysis and fecal hormone analysis...development of a noninvasive aldosterone assay (for both feces and blow) that can be used as an alternative measure of adrenal gland activation relative to

Meta-analysis in clinical trials revisited.

PubMed

DerSimonian, Rebecca; Laird, Nan

2015-11-01

In this paper, we revisit a 1986 article we published in this Journal, Meta-Analysis in Clinical Trials, where we introduced a random-effects model to summarize the evidence about treatment efficacy from a number of related clinical trials. Because of its simplicity and ease of implementation, our approach has been widely used (with more than 12,000 citations to date) and the "DerSimonian and Laird method" is now often referred to as the 'standard approach' or a 'popular' method for meta-analysis in medical and clinical research. The method is especially useful for providing an overall effect estimate and for characterizing the heterogeneity of effects across a series of studies. Here, we review the background that led to the original 1986 article, briefly describe the random-effects approach for meta-analysis, explore its use in various settings and trends over time and recommend a refinement to the method using a robust variance estimator for testing overall effect. We conclude with a discussion of repurposing the method for Big Data meta-analysis and Genome Wide Association Studies for studying the importance of genetic variants in complex diseases. Published by Elsevier Inc.

Detrended Partial-Cross-Correlation Analysis: A New Method for Analyzing Correlations in Complex System

PubMed Central

Yuan, Naiming; Fu, Zuntao; Zhang, Huan; Piao, Lin; Xoplaki, Elena; Luterbacher, Juerg

2015-01-01

In this paper, a new method, detrended partial-cross-correlation analysis (DPCCA), is proposed. Based on detrended cross-correlation analysis (DCCA), this method is improved by including partial-correlation technique, which can be applied to quantify the relations of two non-stationary signals (with influences of other signals removed) on different time scales. We illustrate the advantages of this method by performing two numerical tests. Test I shows the advantages of DPCCA in handling non-stationary signals, while Test II reveals the “intrinsic” relations between two considered time series with potential influences of other unconsidered signals removed. To further show the utility of DPCCA in natural complex systems, we provide new evidence on the winter-time Pacific Decadal Oscillation (PDO) and the winter-time Nino3 Sea Surface Temperature Anomaly (Nino3-SSTA) affecting the Summer Rainfall over the middle-lower reaches of the Yangtze River (SRYR). By applying DPCCA, better significant correlations between SRYR and Nino3-SSTA on time scales of 6 ~ 8 years are found over the period 1951 ~ 2012, while significant correlations between SRYR and PDO on time scales of 35 years arise. With these physically explainable results, we have confidence that DPCCA is an useful method in addressing complex systems. PMID:25634341

Improved modeling of in vivo confocal Raman data using multivariate curve resolution (MCR) augmentation of ordinary least squares models.

PubMed

Hancewicz, Thomas M; Xiao, Chunhong; Zhang, Shuliang; Misra, Manoj

2013-12-01

In vivo confocal Raman spectroscopy has become the measurement technique of choice for skin health and skin care related communities as a way of measuring functional chemistry aspects of skin that are key indicators for care and treatment of various skin conditions. Chief among these techniques are stratum corneum water content, a critical health indicator for severe skin condition related to dryness, and natural moisturizing factor components that are associated with skin protection and barrier health. In addition, in vivo Raman spectroscopy has proven to be a rapid and effective method for quantifying component penetration in skin for topically applied skin care formulations. The benefit of such a capability is that noninvasive analytical chemistry can be performed in vivo in a clinical setting, significantly simplifying studies aimed at evaluating product performance. This presumes, however, that the data and analysis methods used are compatible and appropriate for the intended purpose. The standard analysis method used by most researchers for in vivo Raman data is ordinary least squares (OLS) regression. The focus of work described in this paper is the applicability of OLS for in vivo Raman analysis with particular attention given to use for non-ideal data that often violate the inherent limitations and deficiencies associated with proper application of OLS. We then describe a newly developed in vivo Raman spectroscopic analysis methodology called multivariate curve resolution-augmented ordinary least squares (MCR-OLS), a relatively simple route to addressing many of the issues with OLS. The method is compared with the standard OLS method using the same in vivo Raman data set and using both qualitative and quantitative comparisons based on model fit error, adherence to known data constraints, and performance against calibration samples. A clear improvement is shown in each comparison for MCR-OLS over standard OLS, thus supporting the premise that the MCR-OLS method is better suited for general-purpose multicomponent analysis of in vivo Raman spectral data. This suggests that the methodology is more readily adaptable to a wide range of component systems and is thus more generally applicable than standard OLS.

An Excel-based implementation of the spectral method of action potential alternans analysis.

PubMed

Pearman, Charles M

2014-12-01

Action potential (AP) alternans has been well established as a mechanism of arrhythmogenesis and sudden cardiac death. Proper interpretation of AP alternans requires a robust method of alternans quantification. Traditional methods of alternans analysis neglect higher order periodicities that may have greater pro-arrhythmic potential than classical 2:1 alternans. The spectral method of alternans analysis, already widely used in the related study of microvolt T-wave alternans, has also been used to study AP alternans. Software to meet the specific needs of AP alternans analysis is not currently available in the public domain. An AP analysis tool is implemented here, written in Visual Basic for Applications and using Microsoft Excel as a shell. This performs a sophisticated analysis of alternans behavior allowing reliable distinction of alternans from random fluctuations, quantification of alternans magnitude, and identification of which phases of the AP are most affected. In addition, the spectral method has been adapted to allow detection and quantification of higher order regular oscillations. Analysis of action potential morphology is also performed. A simple user interface enables easy import, analysis, and export of collated results. © 2014 The Author. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

The Fourier Transform in Chemistry. Part 1. Nuclear Magnetic Resonance: Introduction.

ERIC Educational Resources Information Center

King, Roy W.; Williams, Kathryn R.

1989-01-01

Using fourier transformation methods in nuclear magnetic resonance has made possible increased sensitivity in chemical analysis. This article describes these methods as they relate to magnetization, the RF magnetic field, nuclear relaxation, the RF pulse, and free induction decay. (CW)

Finite element analysis of elasto-plastic soils. Report no. 4: Finite element analysis of elasto-plastic frictional materials for application to lunar earth sciences

NASA Technical Reports Server (NTRS)

Marr, W. A., Jr.

1972-01-01

The behavior of finite element models employing different constitutive relations to describe the stress-strain behavior of soils is investigated. Three models, which assume small strain theory is applicable, include a nondilatant, a dilatant and a strain hardening constitutive relation. Two models are formulated using large strain theory and include a hyperbolic and a Tresca elastic perfectly plastic constitutive relation. These finite element models are used to analyze retaining walls and footings. Methods of improving the finite element solutions are investigated. For nonlinear problems better solutions can be obtained by using smaller load increment sizes and more iterations per load increment than by increasing the number of elements. Suitable methods of treating tension stresses and stresses which exceed the yield criteria are discussed.

[Determination of five naphthaquinones in Arnebia euchroma by quantitative analysis multi-components with single-marker].

PubMed

Zhao, Wen-Wen; Wu, Zhi-Min; Wu, Xia; Zhao, Hai-Yu; Chen, Xiao-Qing

2016-10-01

This study is to determine five naphthaquinones (acetylshikonin, β-acetoxyisovalerylalkannin, isobutylshikonin, β,β'-dimethylacrylalkannin,α-methyl-n-butylshikonin） by quantitative analysis of multi-components with a single marker (QAMS). β,β'-Dimethylacrylalkannin was selected as the internal reference substance, and the relative correlation factors (RCFs) of acetylshikonin, β-acetoxyisovalerylalkannin, isobutylshikonin and α-methyl-n-butylshikonin were calculated. Then the ruggedness of relative correction factors was tested on different instruments and columns. Meanwhile, 16 batches of Arnebia euchroma were analyzed by external standard method (ESM) and QAMS, respectively. The peaks were identifited by LC-MS. The ruggedness of relative correction factors was good. And the analytical results calculated by ESM and QAMS showed no difference. The quantitative method established was feasible and suitable for the quality evaluation of A. euchroma. Copyright© by the Chinese Pharmaceutical Association.

Quantifying distinct associations on different temporal scales: comparison of DCCA and Pearson methods

NASA Astrophysics Data System (ADS)

Piao, Lin; Fu, Zuntao

2016-11-01

Cross-correlation between pairs of variables takes multi-time scale characteristic, and it can be totally different on different time scales (changing from positive correlation to negative one), e.g., the associations between mean air temperature and relative humidity over regions to the east of Taihang mountain in China. Therefore, how to correctly unveil these correlations on different time scales is really of great importance since we actually do not know if the correlation varies with scales in advance. Here, we compare two methods, i.e. Detrended Cross-Correlation Analysis (DCCA for short) and Pearson correlation, in quantifying scale-dependent correlations directly to raw observed records and artificially generated sequences with known cross-correlation features. Studies show that 1) DCCA related methods can indeed quantify scale-dependent correlations, but not Pearson method; 2) the correlation features from DCCA related methods are robust to contaminated noises, however, the results from Pearson method are sensitive to noise; 3) the scale-dependent correlation results from DCCA related methods are robust to the amplitude ratio between slow and fast components, while Pearson method may be sensitive to the amplitude ratio. All these features indicate that DCCA related methods take some advantages in correctly quantifying scale-dependent correlations, which results from different physical processes.

Quantifying distinct associations on different temporal scales: comparison of DCCA and Pearson methods.

PubMed

Piao, Lin; Fu, Zuntao

2016-11-09

Cross-correlation between pairs of variables takes multi-time scale characteristic, and it can be totally different on different time scales (changing from positive correlation to negative one), e.g., the associations between mean air temperature and relative humidity over regions to the east of Taihang mountain in China. Therefore, how to correctly unveil these correlations on different time scales is really of great importance since we actually do not know if the correlation varies with scales in advance. Here, we compare two methods, i.e. Detrended Cross-Correlation Analysis (DCCA for short) and Pearson correlation, in quantifying scale-dependent correlations directly to raw observed records and artificially generated sequences with known cross-correlation features. Studies show that 1) DCCA related methods can indeed quantify scale-dependent correlations, but not Pearson method; 2) the correlation features from DCCA related methods are robust to contaminated noises, however, the results from Pearson method are sensitive to noise; 3) the scale-dependent correlation results from DCCA related methods are robust to the amplitude ratio between slow and fast components, while Pearson method may be sensitive to the amplitude ratio. All these features indicate that DCCA related methods take some advantages in correctly quantifying scale-dependent correlations, which results from different physical processes.

Toward a Mixed-Methods Research Approach to Content Analysis in The Digital Age: The Combined Content-Analysis Model and its Applications to Health Care Twitter Feeds

PubMed Central

Hamad, Eradah O; Savundranayagam, Marie Y; Holmes, Jeffrey D; Kinsella, Elizabeth Anne

2016-01-01

Background Twitter’s 140-character microblog posts are increasingly used to access information and facilitate discussions among health care professionals and between patients with chronic conditions and their caregivers. Recently, efforts have emerged to investigate the content of health care-related posts on Twitter. This marks a new area for researchers to investigate and apply content analysis (CA). In current infodemiology, infoveillance and digital disease detection research initiatives, quantitative and qualitative Twitter data are often combined, and there are no clear guidelines for researchers to follow when collecting and evaluating Twitter-driven content. Objective The aim of this study was to identify studies on health care and social media that used Twitter feeds as a primary data source and CA as an analysis technique. We evaluated the resulting 18 studies based on a narrative review of previous methodological studies and textbooks to determine the criteria and main features of quantitative and qualitative CA. We then used the key features of CA and mixed-methods research designs to propose the combined content-analysis (CCA) model as a solid research framework for designing, conducting, and evaluating investigations of Twitter-driven content. Methods We conducted a PubMed search to collect studies published between 2010 and 2014 that used CA to analyze health care-related tweets. The PubMed search and reference list checks of selected papers identified 21 papers. We excluded 3 papers and further analyzed 18. Results Results suggest that the methods used in these studies were not purely quantitative or qualitative, and the mixed-methods design was not explicitly chosen for data collection and analysis. A solid research framework is needed for researchers who intend to analyze Twitter data through the use of CA. Conclusions We propose the CCA model as a useful framework that provides a straightforward approach to guide Twitter-driven studies and that adds rigor to health care social media investigations. We provide suggestions for the use of the CCA model in elder care-related contexts. PMID:26957477

ANALYSIS OF RICIN TOXIN PREPARATIONS FOR CARBOHYDRATE AND FATTY ACID ABUNDANCE AND ISOTOPE RATIO INFORMATION

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

Wunschel, David S.; Kreuzer-Martin, Helen W.; Antolick, Kathryn C.

2009-12-01

This report describes method development and preliminary evaluation for analyzing castor samples for signatures of purifying ricin. Ricin purification from the source castor seeds is essentially a problem of protein purification using common biochemical methods. Indications of protein purification will likely manifest themselves as removal of the non-protein fractions of the seed. Two major, non-protein, types of biochemical constituents in the seed are the castor oil and various carbohydrates. The oil comprises roughly half the seed weight while the carbohydrate component comprises roughly half of the remaining “mash” left after oil and hull removal. Different castor oil and carbohydrate componentsmore » can serve as indicators of specific toxin processing steps. Ricinoleic acid is a relatively unique fatty acid in nature and is the most abundant component of castor oil. The loss of ricinoleic acid indicates a step to remove oil from the seeds. The relative amounts of carbohydrates and carbohydrate-like compounds, including arabinose, xylose, myo-inositol fucose, rhamnose, glucosamine and mannose detected in the sample can also indicate specific processing steps. For instance, the differential loss of arabinose relative to mannose and N-acetyl glucosamine indicates enrichment for the protein fraction of the seed using protein precipitation. The methods developed in this project center on fatty acid and carbohydrate extraction from castor samples followed by derivatization to permit analysis by gas chromatography-mass spectrometry (GC-MS). Method descriptions herein include: the source and preparation of castor materials used for method evaluation, the equipment and description of procedure required for chemical derivatization, and the instrument parameters used in the analysis. Two types of derivatization methods describe analysis of carbohydrates and one procedure for analysis of fatty acids. Two types of GC-MS analysis is included in the method development, one employing a quadrupole MS system for compound identification and an isotope ratio MS for measuring the stable isotope ratios of deuterium and hydrogen (D/H) in fatty acids. Finally, the method for analyzing the compound abundance data is included. This study indicates that removal of ricinoleic acid is a conserved consequence of each processing step we tested. Furthermore, the stable isotope D/H ratio of ricinoleic acid distinguished between two of the three castor seed sources. Concentrations of arabinose, xylose, mannose, glucosamine and myo-inositol differentiated between crude or acetone extracted samples and samples produced by protein precipitation. Taken together these data illustrate the ability to distinguish between processes used to purify a ricin sample as well as potentially the source seeds.« less

Quantitation of flavonoid constituents in citrus fruits.

PubMed

Kawaii, S; Tomono, Y; Katase, E; Ogawa, K; Yano, M

1999-09-01

Twenty-four flavonoids have been determined in 66 Citrus species and near-citrus relatives, grown in the same field and year, by means of reversed phase high-performance liquid chromatography analysis. Statistical methods have been applied to find relations among the species. The F ratios of 21 flavonoids obtained by applying ANOVA analysis are significant, indicating that a classification of the species using these variables is reasonable to pursue. Principal component analysis revealed that the distributions of Citrus species belonging to different classes were largely in accordance with Tanaka's classification system.

Compendium of methods for applying measured data to vibration and acoustic problems

NASA Astrophysics Data System (ADS)

Dejong, R. G.

1985-10-01

The scope of this report includes the measurement, analysis and use of vibration and acoustic data. The purpose of this report is then two-fold. First, it provides introductory material in an easily understood manner to engineers, technicians, and their managers in areas other than their specialties relating to the measurement, analysis and use of vibration and acoustic data. Second, it provides a quick reference source for engineers, technicians and their managers in the areas of their specialties relating to the measurement, analysis and use of vibration and acoustic data.

Using multipliers analysis in order to get another perspective related to the role of ICT sectors in national economy of Indonesia: 1990-2005

NASA Astrophysics Data System (ADS)

Zuhdi, Ubaidillah

2014-04-01

The purpose of this study is to get another perspective related to the role of Information and Communication Technology (ICT) sectors in national economy of Indonesia. The period of analysis of this study is 1990-2005. This study employs Input-Output (IO) analysis as a tool of analysis. More specifically, this study uses simple output multipliers method in order to achieve the purpose. Comparison with previous study is conducted in order to get the objective of this study. Previous study, using Structural Decomposition Analysis (SDA), showed that ICT sectors did not have an important role in Indonesian national economy in above period. The similar results also appear in this study. In other words, from this study, another perspective related to the role of these sectors in Indonesian national economy in analysis period is not found.

Formal Language Design in the Context of Domain Engineering

DTIC Science & Technology

2000-03-28

73 Related Work 75 5.1 Feature oriented domain analysis ( FODA ) 75 5.2 Organizational domain modeling (ODM) 76 5.3 Domain-Specific Software...However there are only a few that are well defined and used repeatedly in practice. These include: Feature oriented domain analysis ( FODA ), Organizational...Feature oriented domain analysis ( FODA ) Feature oriented domain analysis ( FODA ) is a domain analysis method being researched and applied by the SEI

Safety and business benefit analysis of NASA's aviation safety program

DOT National Transportation Integrated Search

2004-09-20

NASA Aviation Safety Program elements encompass a wide range of products that require both public and private investment. Therefore, two methods of analysis, one relating to the public and the other to the private industry, must be combined to unders...

RECENT APPLICATIONS OF SOURCE APPORTIONMENT METHODS AND RELATED NEEDS

EPA Science Inventory

Traditional receptor modeling studies have utilized factor analysis (like principal component analysis, PCA) and/or Chemical Mass Balance (CMB) to assess source influences. The limitations with these approaches is that PCA is qualitative and CMB requires the input of source pr...

Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

NASA Astrophysics Data System (ADS)

Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

Prescription-drug-related risk in driving: comparing conventional and lasso shrinkage logistic regressions.

PubMed

Avalos, Marta; Adroher, Nuria Duran; Lagarde, Emmanuel; Thiessard, Frantz; Grandvalet, Yves; Contrand, Benjamin; Orriols, Ludivine

2012-09-01

Large data sets with many variables provide particular challenges when constructing analytic models. Lasso-related methods provide a useful tool, although one that remains unfamiliar to most epidemiologists. We illustrate the application of lasso methods in an analysis of the impact of prescribed drugs on the risk of a road traffic crash, using a large French nationwide database (PLoS Med 2010;7:e1000366). In the original case-control study, the authors analyzed each exposure separately. We use the lasso method, which can simultaneously perform estimation and variable selection in a single model. We compare point estimates and confidence intervals using (1) a separate logistic regression model for each drug with a Bonferroni correction and (2) lasso shrinkage logistic regression analysis. Shrinkage regression had little effect on (bias corrected) point estimates, but led to less conservative results, noticeably for drugs with moderate levels of exposure. Carbamates, carboxamide derivative and fatty acid derivative antiepileptics, drugs used in opioid dependence, and mineral supplements of potassium showed stronger associations. Lasso is a relevant method in the analysis of databases with large number of exposures and can be recommended as an alternative to conventional strategies.

Document co-citation analysis to enhance transdisciplinary research

PubMed Central

Trujillo, Caleb M.; Long, Tammy M.

2018-01-01

Specialized and emerging fields of research infrequently cross disciplinary boundaries and would benefit from frameworks, methods, and materials informed by other fields. Document co-citation analysis, a method developed by bibliometric research, is demonstrated as a way to help identify key literature for cross-disciplinary ideas. To illustrate the method in a useful context, we mapped peer-recognized scholarship related to systems thinking. In addition, three procedures for validation of co-citation networks are proposed and implemented. This method may be useful for strategically selecting information that can build consilience about ideas and constructs that are relevant across a range of disciplines. PMID:29308433

Alternative statistical methods for interpreting airborne Alder (Alnus glutimosa (L.) Gaertner) pollen concentrations.

PubMed

González Parrado, Zulima; Valencia Barrera, Rosa M; Fuertes Rodríguez, Carmen R; Vega Maray, Ana M; Pérez Romero, Rafael; Fraile, Roberto; Fernández González, Delia

2009-01-01

This paper reports on the behaviour of Alnus glutinosa (alder) pollen grains in the atmosphere of Ponferrada (León, NW Spain) from 1995 to 2006. The study, which sought to determine the effects of various weather-related parameters on Alnus pollen counts, was performed using a volumetric method. The main pollination period for this taxon is January-February. Alder pollen is one of the eight major airborne pollen allergens found in the study area. An analysis was made of the correlation between pollen counts and major weather-related parameters over each period. In general, the strongest positive correlation was with temperature, particularly maximum temperature. During each period, peak pollen counts occurred when the maximum temperature fell within the range 9 degrees C-14 degrees C. Finally, multivariate analysis showed that the parameter exerting the greatest influence was temperature, a finding confirmed by Spearman correlation tests. Principal components analysis suggested that periods with high pollen counts were characterised by high maximum temperature, low rainfall and an absolute humidity of around 6 g m(-3). Use of this type of analysis in conjunction with other methods is essential for obtaining an accurate record of pollen-count variations over a given period.

Unplanned pregnancy: does past experience influence the use of a contraceptive method?

PubMed

Matteson, Kristen A; Peipert, Jeffrey F; Allsworth, Jenifer; Phipps, Maureen G; Redding, Colleen A

2006-01-01

To investigate whether women between the ages of 14 and 25 years with a past unplanned pregnancy were more likely to use a contraceptive method compared with women without a history of unplanned pregnancy. We analyzed baseline data of 424 nonpregnant women between the ages of 14 and 25 years enrolled in a randomized trial to prevent sexually transmitted diseases and unplanned pregnancy (Project PROTECT). Women at high risk for sexually transmitted diseases or unplanned pregnancy were included. Participants completed a demographic, substance use, and reproductive health questionnaire. We compared women with and without a history of unplanned pregnancy using bivariate analysis and log binomial regression. The prevalence of past unplanned pregnancy in this sample was 43%. Women reporting an unplanned pregnancy were older, and had less education, and were more likely to be nonwhite race or ethnicity. History of an unplanned pregnancy was not associated with usage of a contraceptive method (relative risk 1.01, 95% confidence interval 0.87-1.16) in bivariate analysis or when potential confounders were accounted for in the analysis (adjusted relative risk 1.10, 95% confidence interval 0.95-1.28). Several factors were associated with both unplanned pregnancy and overall contraceptive method use in this population. However, a past unplanned pregnancy was not associated with overall contraceptive method usage. Future studies are necessary to investigate the complex relationship between unplanned pregnancy and contraceptive method use. II-2.

Patterns of presentation for attempted suicide: analysis of a cohort of individuals who subsequently died by suicide.

PubMed

Mallon, Sharon; Rosato, Michael; Galway, Karen; Hughes, Lynette; Rondon-Sulbaran, Janeet; McConkey, Sam; Leavey, Gerard

2015-06-01

All suicides and related prior attempts occurring in Northern Ireland over two years were analyzed, focusing on number and timing of attempts, method, and mental health diagnoses. Cases were derived from coroner's records, with 90% subsequently linked to associated general practice records. Of those included, 45% recorded at least one prior attempt (with 59% switching from less to more lethal methods between attempt and suicide). Compared with those recording one attempt, those with 2+ attempts were more likely to have used less lethal methods at the suicide (OR = 2.77: 95% CI = 1.06, 7.23); and those using less lethal methods at the attempts were more likely to persist with these into the suicide (OR = 3.21: 0.79, 13.07). Finally, those with preexisting mental problems were more likely to use less lethal methods in the suicide: severe mental illness (OR = 7.88: 1.58, 39.43); common mental problems (OR = 3.68: 0.83, 16.30); and alcohol/drugs related (OR = 2.02: 0.41, 9.95). This analysis uses readily available data to highlight the persisting use of less lethal methods by visible and vulnerable attempters who eventually complete their suicide. Further analysis of such conditions could allow more effective prevention strategies to be developed. © 2014 The American Association of Suicidology.

The cosmological analysis of X-ray cluster surveys - I. A new method for interpreting number counts

NASA Astrophysics Data System (ADS)

Clerc, N.; Pierre, M.; Pacaud, F.; Sadibekova, T.

2012-07-01

We present a new method aimed at simplifying the cosmological analysis of X-ray cluster surveys. It is based on purely instrumental observable quantities considered in a two-dimensional X-ray colour-magnitude diagram (hardness ratio versus count rate). The basic principle is that even in rather shallow surveys, substantial information on cluster redshift and temperature is present in the raw X-ray data and can be statistically extracted; in parallel, such diagrams can be readily predicted from an ab initio cosmological modelling. We illustrate the methodology for the case of a 100-deg2XMM survey having a sensitivity of ˜10-14 erg s-1 cm-2 and fit at the same time, the survey selection function, the cluster evolutionary scaling relations and the cosmology; our sole assumption - driven by the limited size of the sample considered in the case study - is that the local cluster scaling relations are known. We devote special attention to the realistic modelling of the count-rate measurement uncertainties and evaluate the potential of the method via a Fisher analysis. In the absence of individual cluster redshifts, the count rate and hardness ratio (CR-HR) method appears to be much more efficient than the traditional approach based on cluster counts (i.e. dn/dz, requiring redshifts). In the case where redshifts are available, our method performs similar to the traditional mass function (dn/dM/dz) for the purely cosmological parameters, but constrains better parameters defining the cluster scaling relations and their evolution. A further practical advantage of the CR-HR method is its simplicity: this fully top-down approach totally bypasses the tedious steps consisting in deriving cluster masses from X-ray temperature measurements.

Homeless youth: a concept analysis.

PubMed

Washington, Philisie Starling

2011-07-01

INTRODUCTION. A variety of terms have been used to describe the homeless youth population. PURPOSE. The purpose of this article is to analyze the conceptual meanings of the term homeless youths by examining the evolution of the concept and its related terms in the current literature. Method. Online databases from 1990-2010 were analyzed using the Rodgers evolutionary approach. RESULTS. The 6 attributes relating to homeless youth were physical location, age, health, behavior, choice, and survival. CONCLUSION. The analysis provided insight and clarification of homeless youth from a variety of related terms in the literature.

Statistical significance of task related deep brain EEG dynamic changes in the time-frequency domain.

PubMed

Chládek, J; Brázdil, M; Halámek, J; Plešinger, F; Jurák, P

2013-01-01

We present an off-line analysis procedure for exploring brain activity recorded from intra-cerebral electroencephalographic data (SEEG). The objective is to determine the statistical differences between different types of stimulations in the time-frequency domain. The procedure is based on computing relative signal power change and subsequent statistical analysis. An example of characteristic statistically significant event-related de/synchronization (ERD/ERS) detected across different frequency bands following different oddball stimuli is presented. The method is used for off-line functional classification of different brain areas.

Beauty and the beast: Some perspectives on efficient model analysis, surrogate models, and the future of modeling

NASA Astrophysics Data System (ADS)

Hill, M. C.; Jakeman, J.; Razavi, S.; Tolson, B.

2015-12-01

For many environmental systems model runtimes have remained very long as more capable computers have been used to add more processes and more time and space discretization. Scientists have also added more parameters and kinds of observations, and many model runs are needed to explore the models. Computational demand equals run time multiplied by number of model runs divided by parallelization opportunities. Model exploration is conducted using sensitivity analysis, optimization, and uncertainty quantification. Sensitivity analysis is used to reveal consequences of what may be very complex simulated relations, optimization is used to identify parameter values that fit the data best, or at least better, and uncertainty quantification is used to evaluate the precision of simulated results. The long execution times make such analyses a challenge. Methods for addressing this challenges include computationally frugal analysis of the demanding original model and a number of ingenious surrogate modeling methods. Both commonly use about 50-100 runs of the demanding original model. In this talk we consider the tradeoffs between (1) original model development decisions, (2) computationally frugal analysis of the original model, and (3) using many model runs of the fast surrogate model. Some questions of interest are as follows. If the added processes and discretization invested in (1) are compared with the restrictions and approximations in model analysis produced by long model execution times, is there a net benefit related of the goals of the model? Are there changes to the numerical methods that could reduce the computational demands while giving up less fidelity than is compromised by using computationally frugal methods or surrogate models for model analysis? Both the computationally frugal methods and surrogate models require that the solution of interest be a smooth function of the parameters or interest. How does the information obtained from the local methods typical of (2) and the global averaged methods typical of (3) compare for typical systems? The discussion will use examples of response of the Greenland glacier to global warming and surface and groundwater modeling.

Qualitative and quantitative analysis of an alkaloid fraction from Piper longum L. using ultra-high performance liquid chromatography-diode array detector-electrospray ionization mass spectrometry.

PubMed

Li, Kuiyong; Fan, Yunpeng; Wang, Hui; Fu, Qing; Jin, Yu; Liang, Xinmiao

2015-05-10

In a previous research, an alkaloid fraction and 18 alkaloid compounds were prepared from Piper longum L. by series of purification process. In this paper, a qualitative and quantitative analysis method using ultra-high performance liquid chromatography-diode array detector-mass spectrometry (UHPLC-DAD-MS) was developed to evaluate the alkaloid fraction. Qualitative analysis of the alkaloid fraction was firstly completed by UHPLC-DAD method and 18 amide alkaloid compounds were identified. A further qualitative analysis of the alkaloid fraction was accomplished by UHPLC-MS/MS method. Another 25 amide alkaloids were identified according to their characteristic ions and neutral losses. At last, a quantitative method for the alkaloid fraction was established using four marker compounds including piperine, pipernonatine, guineensine and N-isobutyl-2E,4E-octadecadienamide. After the validation of this method, the contents of above four marker compounds in the alkaloid fraction were 57.5mg/g, 65.6mg/g, 17.7mg/g and 23.9mg/g, respectively. Moreover, the relative response factors of other three compounds to piperine were calculated. A comparative study between external standard quantification and relative response factor quantification proved no remarkable difference. UHPLC-DAD-MS method was demonstrated to be a powerful tool for the characterization of the alkaloid fraction from P. longum L. and the result proved that the quality of alkaloid fraction was efficiently improved after appropriate purification. Copyright © 2015. Published by Elsevier B.V.

A Hybrid Computational Method for the Discovery of Novel Reproduction-Related Genes

PubMed Central

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

2015-01-01

Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations. PMID:25768094

A hybrid computational method for the discovery of novel reproduction-related genes.

PubMed

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

2015-01-01

Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

Incorporating interaction networks into the determination of functionally related hit genes in genomic experiments with Markov random fields

PubMed Central

Robinson, Sean; Nevalainen, Jaakko; Pinna, Guillaume; Campalans, Anna; Radicella, J. Pablo; Guyon, Laurent

2017-01-01

Abstract Motivation: Incorporating gene interaction data into the identification of ‘hit’ genes in genomic experiments is a well-established approach leveraging the ‘guilt by association’ assumption to obtain a network based hit list of functionally related genes. We aim to develop a method to allow for multivariate gene scores and multiple hit labels in order to extend the analysis of genomic screening data within such an approach. Results: We propose a Markov random field-based method to achieve our aim and show that the particular advantages of our method compared with those currently used lead to new insights in previously analysed data as well as for our own motivating data. Our method additionally achieves the best performance in an independent simulation experiment. The real data applications we consider comprise of a survival analysis and differential expression experiment and a cell-based RNA interference functional screen. Availability and implementation: We provide all of the data and code related to the results in the paper. Contact: sean.j.robinson@utu.fi or laurent.guyon@cea.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28881978

Proposal of Constraints Analysis Method Based on Network Model for Task Planning

NASA Astrophysics Data System (ADS)

Tomiyama, Tomoe; Sato, Tatsuhiro; Morita, Toyohisa; Sasaki, Toshiro

Deregulation has been accelerating several activities toward reengineering business processes, such as railway through service and modal shift in logistics. Making those activities successful, business entities have to regulate new business rules or know-how (we call them ‘constraints’). According to the new constraints, they need to manage business resources such as instruments, materials, workers and so on. In this paper, we propose a constraint analysis method to define constraints for task planning of the new business processes. To visualize each constraint's influence on planning, we propose a network model which represents allocation relations between tasks and resources. The network can also represent task ordering relations and resource grouping relations. The proposed method formalizes the way of defining constraints manually as repeatedly checking the network structure and finding conflicts between constraints. Being applied to crew scheduling problems shows that the method can adequately represent and define constraints of some task planning problems with the following fundamental features, (1) specifying work pattern to some resources, (2) restricting the number of resources for some works, (3) requiring multiple resources for some works, (4) prior allocation of some resources to some works and (5) considering the workload balance between resources.

Comprehensive comparative analysis of 5'-end RNA-sequencing methods.

PubMed

Adiconis, Xian; Haber, Adam L; Simmons, Sean K; Levy Moonshine, Ami; Ji, Zhe; Busby, Michele A; Shi, Xi; Jacques, Justin; Lancaster, Madeline A; Pan, Jen Q; Regev, Aviv; Levin, Joshua Z

2018-06-04

Specialized RNA-seq methods are required to identify the 5' ends of transcripts, which are critical for studies of gene regulation, but these methods have not been systematically benchmarked. We directly compared six such methods, including the performance of five methods on a single human cellular RNA sample and a new spike-in RNA assay that helps circumvent challenges resulting from uncertainties in annotation and RNA processing. We found that the 'cap analysis of gene expression' (CAGE) method performed best for mRNA and that most of its unannotated peaks were supported by evidence from other genomic methods. We applied CAGE to eight brain-related samples and determined sample-specific transcription start site (TSS) usage, as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.

Guidelines for Design and Analysis of Large, Brittle Spacecraft Components

NASA Technical Reports Server (NTRS)

Robinson, E. Y.

1993-01-01

There were two related parts to this work. The first, conducted at The Aerospace Corporation was to develop and define methods for integrating the statistical theory of brittle strength with conventional finite element stress analysis, and to carry out a limited laboratory test program to illustrate the methods. The second part, separately funded at Aerojet Electronic Systems Division, was to create the finite element postprocessing program for integrating the statistical strength analysis with the structural analysis. The second part was monitored by Capt. Jeff McCann of USAF/SMC, as Special Study No.11, which authorized Aerojet to support Aerospace on this work requested by NASA. This second part is documented in Appendix A. The activity at Aerojet was guided by the Aerospace methods developed in the first part of this work. This joint work of Aerospace and Aerojet stemmed from prior related work for the Defense Support Program (DSP) Program Office, to qualify the DSP sensor main mirror and corrector lens for flight as part of a shuttle payload. These large brittle components of the DSP sensor are provided by Aerojet. This document defines rational methods for addressing the structural integrity and safety of large, brittle, payload components, which have low and variable tensile strength and can suddenly break or shatter. The methods are applicable to the evaluation and validation of such components, which, because of size and configuration restrictions, cannot be validated by direct proof test.

Field evaluation of personal sampling methods for multiple bioaerosols.

PubMed

Wang, Chi-Hsun; Chen, Bean T; Han, Bor-Cheng; Liu, Andrew Chi-Yeu; Hung, Po-Chen; Chen, Chih-Yong; Chao, Hsing Jasmine

2015-01-01

Ambient bioaerosols are ubiquitous in the daily environment and can affect health in various ways. However, few studies have been conducted to comprehensively evaluate personal bioaerosol exposure in occupational and indoor environments because of the complex composition of bioaerosols and the lack of standardized sampling/analysis methods. We conducted a study to determine the most efficient collection/analysis method for the personal exposure assessment of multiple bioaerosols. The sampling efficiencies of three filters and four samplers were compared. According to our results, polycarbonate (PC) filters had the highest relative efficiency, particularly for bacteria. Side-by-side sampling was conducted to evaluate the three filter samplers (with PC filters) and the NIOSH Personal Bioaerosol Cyclone Sampler. According to the results, the Button Aerosol Sampler and the IOM Inhalable Dust Sampler had the highest relative efficiencies for fungi and bacteria, followed by the NIOSH sampler. Personal sampling was performed in a pig farm to assess occupational bioaerosol exposure and to evaluate the sampling/analysis methods. The Button and IOM samplers yielded a similar performance for personal bioaerosol sampling at the pig farm. However, the Button sampler is more likely to be clogged at high airborne dust concentrations because of its higher flow rate (4 L/min). Therefore, the IOM sampler is a more appropriate choice for performing personal sampling in environments with high dust levels. In summary, the Button and IOM samplers with PC filters are efficient sampling/analysis methods for the personal exposure assessment of multiple bioaerosols.

Exploratory analysis of textual data from the Mother and Child Handbook using the text-mining method: Relationships with maternal traits and post-partum depression.

PubMed

Matsuda, Yoshio; Manaka, Tomoko; Kobayashi, Makiko; Sato, Shuhei; Ohwada, Michitaka

2016-06-01

The aim of the present study was to examine the possibility of screening apprehensive pregnant women and mothers at risk for post-partum depression from an analysis of the textual data in the Mother and Child Handbook by using the text-mining method. Uncomplicated pregnant women (n = 58) were divided into two groups according to State-Trait Anxiety Inventory grade (high trait [group I, n = 21] and low trait [group II, n = 37]) or Edinburgh Postnatal Depression Scale score (high score [group III, n = 15] and low score [group IV, n = 43]). An exploratory analysis of the textual data from the Maternal and Child Handbook was conducted using the text-mining method with the Word Miner software program. A comparison of the 'structure elements' was made between the two groups. The number of structure elements extracted by separated words from text data was 20 004 and the number of structure elements with a threshold of 2 or more as an initial value was 1168. Fifteen key words related to maternal anxiety, and six key words related to post-partum depression were extracted. The text-mining method is useful for the exploratory analysis of textual data obtained from pregnant woman, and this screening method has been suggested to be useful for apprehensive pregnant women and mothers at risk for post-partum depression. © 2016 Japan Society of Obstetrics and Gynecology.

Self-care Concept Analysis in Cancer Patients: An Evolutionary Concept Analysis

PubMed Central

Hasanpour-Dehkordi, Ali

2016-01-01

Background: Self-care is a frequently used concept in both the theory and the clinical practice of nursing and is considered an element of nursing theory by Orem. The aim of this paper is to identify the core attributes of the self-care concept in cancer patients. Materials and Methods: We used Rodgers’ evolutionary method of concept analysis. The articles published in English language from 1980 to 2015 on nursing and non-nursing disciplines were analyzed. Finally, 85 articles, an MSc thesis, and a PhD thesis were selected, examined, and analyzed in-depth. Two experts checked the process of analysis and monitored and reviewed the articles. Results: The analysis showed that self-care concept is determined by four attributes of education, interaction, self-control, and self-reliance. Three types of antecedents in the present study were client-related (self-efficacy, self-esteem), system-related (adequate sources, social networks, and cultural factors), and healthcare professionals-related (participation). Conclusion: The self-care concept has considerably evolved among patients with chronic diseases, particularly cancer, over the past 35 years, and nurses have managed to enhance their knowledge about self-care remarkably for the clients so that the nurses in healthcare teams have become highly efficient and able to assume the responsibility for self-care teams. PMID:27803559

Determination of valproic acid in human plasma using dispersive liquid-liquid microextraction followed by gas chromatography-flame ionization detection

PubMed Central

Fazeli-Bakhtiyari, Rana; Panahi-Azar, Vahid; Sorouraddin, Mohammad Hossein; Jouyban, Abolghasem

2015-01-01

Objective(s): Dispersive liquid-liquid microextraction coupled with gas chromatography (GC)-flame ionization detector was developed for the determination of valproic acid (VPA) in human plasma. Materials and Methods: Using a syringe, a mixture of suitable extraction solvent (40 µl chloroform) and disperser (1 ml acetone) was quickly added to 10 ml of diluted plasma sample containing VPA (pH, 1.0; concentration of NaCl, 4% (w/v)), resulting in a cloudy solution. After centrifugation (6000 rpm for 6 min), an aliquot (1 µl) of the sedimented organic phase was removed using a 1-µl GC microsyringe and injected into the GC system for analysis. One variable at a time optimization method was used to study various parameters affecting the extraction efficiency of target analyte. Then, the developed method was fully validated for its accuracy, precision, recovery, stability, and robustness. Results: Under the optimum extraction conditions, good linearity range was obtained for the calibration graph, with correlation coefficient higher than 0.998. Limit of detection and lower limit of quantitation were 3.2 and 6 μg/ml, respectively. The relative standard deviations of intra and inter-day analysis of examined compound were less than 11.5%. The relative recoveries were found in the range of 97 to 107.5%. Finally, the validated method was successfully applied to the analysis of VPA in patient sample. Conclusion: The presented method has acceptable levels of precision, accuracy and relative recovery and could be used for therapeutic drug monitoring of VPA in human plasma. PMID:26730332

Transmutation approximations for the application of hybrid Monte Carlo/deterministic neutron transport to shutdown dose rate analysis

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

Biondo, Elliott D.; Wilson, Paul P. H.

In fusion energy systems (FES) neutrons born from burning plasma activate system components. The photon dose rate after shutdown from resulting radionuclides must be quantified. This shutdown dose rate (SDR) is calculated by coupling neutron transport, activation analysis, and photon transport. The size, complexity, and attenuating configuration of FES motivate the use of hybrid Monte Carlo (MC)/deterministic neutron transport. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) method can be used to optimize MC neutron transport for coupled multiphysics problems, including SDR analysis, using deterministic estimates of adjoint flux distributions. When used for SDR analysis, MS-CADIS requires the formulation ofmore » an adjoint neutron source that approximates the transmutation process. In this work, transmutation approximations are used to derive a solution for this adjoint neutron source. It is shown that these approximations are reasonably met for typical FES neutron spectra and materials over a range of irradiation scenarios. When these approximations are met, the Groupwise Transmutation (GT)-CADIS method, proposed here, can be used effectively. GT-CADIS is an implementation of the MS-CADIS method for SDR analysis that uses a series of single-energy-group irradiations to calculate the adjoint neutron source. For a simple SDR problem, GT-CADIS provides speedups of 200 100 relative to global variance reduction with the Forward-Weighted (FW)-CADIS method and 9 ± 5 • 104 relative to analog. As a result, this work shows that GT-CADIS is broadly applicable to FES problems and will significantly reduce the computational resources necessary for SDR analysis.« less

Transmutation approximations for the application of hybrid Monte Carlo/deterministic neutron transport to shutdown dose rate analysis

DOE PAGES

Biondo, Elliott D.; Wilson, Paul P. H.

2017-05-08

In fusion energy systems (FES) neutrons born from burning plasma activate system components. The photon dose rate after shutdown from resulting radionuclides must be quantified. This shutdown dose rate (SDR) is calculated by coupling neutron transport, activation analysis, and photon transport. The size, complexity, and attenuating configuration of FES motivate the use of hybrid Monte Carlo (MC)/deterministic neutron transport. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) method can be used to optimize MC neutron transport for coupled multiphysics problems, including SDR analysis, using deterministic estimates of adjoint flux distributions. When used for SDR analysis, MS-CADIS requires the formulation ofmore » an adjoint neutron source that approximates the transmutation process. In this work, transmutation approximations are used to derive a solution for this adjoint neutron source. It is shown that these approximations are reasonably met for typical FES neutron spectra and materials over a range of irradiation scenarios. When these approximations are met, the Groupwise Transmutation (GT)-CADIS method, proposed here, can be used effectively. GT-CADIS is an implementation of the MS-CADIS method for SDR analysis that uses a series of single-energy-group irradiations to calculate the adjoint neutron source. For a simple SDR problem, GT-CADIS provides speedups of 200 100 relative to global variance reduction with the Forward-Weighted (FW)-CADIS method and 9 ± 5 • 104 relative to analog. As a result, this work shows that GT-CADIS is broadly applicable to FES problems and will significantly reduce the computational resources necessary for SDR analysis.« less

Franck-Condon Factors for Diatomics: Insights and Analysis Using the Fourier Grid Hamiltonian Method

ERIC Educational Resources Information Center

Ghosh, Supriya; Dixit, Mayank Kumar; Bhattacharyya, S. P.; Tembe, B. L.

2013-01-01

Franck-Condon factors (FCFs) play a crucial role in determining the intensities of the vibrational bands in electronic transitions. In this article, a relatively simple method to calculate the FCFs is illustrated. An algorithm for the Fourier Grid Hamiltonian (FGH) method for computing the vibrational wave functions and the corresponding energy…

Research Methods

DTIC Science & Technology

1992-01-01

cognitive function. For example. physiological methods allow for visual sensitivity measurements in infants and children with about the same level of...potential (ERP), the event-related magnetic field (ERF), and pupillometry . Where possible, we cite specific experiments that deal with display or stimulus...technical barrier preventing the application of these methods to the analysis of human performance with color displays. Pupillometry . The pupillary

Efficacy of the Cooperative Learning Method on Mathematics Achievement and Attitude: A Meta-Analysis Research

ERIC Educational Resources Information Center

Capar, Gulfer; Tarim, Kamuran

2015-01-01

This research compiles experimental studies from 1988 to 2010 that examined the influence of the cooperative learning method, as compared with that of traditional methods, on mathematics achievement and on attitudes towards mathematics. The related field was searched using the following key words in Turkish "matematik ve isbirlikli ögrenme,…

Measurement of relative density of tissue using wavelet analysis and neural nets

NASA Astrophysics Data System (ADS)

Suyatinov, Sergey I.; Kolentev, Sergey V.; Buldakova, Tatyana I.

2001-01-01

Development of methods for indirect measurement of substance's consistence and characteristics is highly actual problem of medical diagnostics. Many diseases bring about changes of tissue density or appearances of alien bodies (e.g. stones in kidneys or gallbladders). Propose to use wavelet-analysis and neural nets for indirect measurement of relative density of tissue by images of internal organs. It shall allow to reveal a disease on early stage.

Retinal imaging and image analysis.

PubMed

Abràmoff, Michael D; Garvin, Mona K; Sonka, Milan

2010-01-01

Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships.

Retinal Imaging and Image Analysis

PubMed Central

Abràmoff, Michael D.; Garvin, Mona K.; Sonka, Milan

2011-01-01

Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships. PMID:22275207

Characterizing the marker-dye correction for Gafchromic(®) EBT2 film: a comparison of three analysis methods.

PubMed

McCaw, Travis J; Micka, John A; Dewerd, Larry A

2011-10-01

Gafchromic(®) EBT2 film has a yellow marker dye incorporated into the active layer of the film that can be used to correct the film response for small variations in thickness. This work characterizes the effect of the marker-dye correction on the uniformity and uncertainty of dose measurements with EBT2 film. The effect of variations in time postexposure on the uniformity of EBT2 is also investigated. EBT2 films were used to measure the flatness of a (60)Co field to provide a high-spatial resolution evaluation of the film uniformity. As a reference, the flatness of the (60)Co field was also measured with Kodak EDR2 films. The EBT2 films were digitized with a flatbed document scanner 24, 48, and 72 h postexposure, and the images were analyzed using three methods: (1) the manufacturer-recommended marker-dye correction, (2) an in-house marker-dye correction, and (3) a net optical density (OD) measurement in the red color channel. The field flatness was calculated from orthogonal profiles through the center of the field using each analysis method, and the results were compared with the EDR2 measurements. Uncertainty was propagated through a dose calculation for each analysis method. The change in the measured field flatness for increasing times postexposure was also determined. Both marker-dye correction methods improved the field flatness measured with EBT2 film relative to the net OD method, with a maximum improvement of 1% using the manufacturer-recommended correction. However, the manufacturer-recommended correction also resulted in a dose uncertainty an order of magnitude greater than the other two methods. The in-house marker-dye correction lowered the dose uncertainty relative to the net OD method. The measured field flatness did not exhibit any unidirectional change with increasing time postexposure and showed a maximum change of 0.3%. The marker dye in EBT2 can be used to improve the response uniformity of the film. Depending on the film analysis method used, however, application of a marker-dye correction can improve or degrade the dose uncertainty relative to the net OD method. The uniformity of EBT2 was found to be independent of the time postexposure.

Plane elasto-plastic analysis of v-notched plate under bending by boundary integral equation method. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Rzasnicki, W.

1973-01-01

A method of solution is presented, which, when applied to the elasto-plastic analysis of plates having a v-notch on one edge and subjected to pure bending, will produce stress and strain fields in much greater detail than presently available. Application of the boundary integral equation method results in two coupled Fredholm-type integral equations, subject to prescribed boundary conditions. These equations are replaced by a system of simultaneous algebraic equations and solved by a successive approximation method employing Prandtl-Reuss incremental plasticity relations. The method is first applied to number of elasto-static problems and the results compared with available solutions. Good agreement is obtained in all cases. The elasto-plastic analysis provides detailed stress and strain distributions for several cases of plates with various notch angles and notch depths. A strain hardening material is assumed and both plane strain and plane stress conditions are considered.

Tactical missile aerodynamics

NASA Technical Reports Server (NTRS)

Hemsch, Michael J. (Editor); Nielsen, Jack N. (Editor)

1986-01-01

The present conference on tactical missile aerodynamics discusses autopilot-related aerodynamic design considerations, flow visualization methods' role in the study of high angle-of-attack aerodynamics, low aspect ratio wing behavior at high angle-of-attack, supersonic airbreathing propulsion system inlet design, missile bodies with noncircular cross section and bank-to-turn maneuvering capabilities, 'waverider' supersonic cruise missile concepts and design methods, asymmetric vortex sheding phenomena from bodies-of-revolution, and swept shock wave/boundary layer interaction phenomena. Also discussed are the assessment of aerodynamic drag in tactical missiles, the analysis of supersonic missile aerodynamic heating, the 'equivalent angle-of-attack' concept for engineering analysis, the vortex cloud model for body vortex shedding and tracking, paneling methods with vorticity effects and corrections for nonlinear compressibility, the application of supersonic full potential method to missile bodies, Euler space marching methods for missiles, three-dimensional missile boundary layers, and an analysis of exhaust plumes and their interaction with missile airframes.

[Quantitative analysis of nucleotide mixtures with terahertz time domain spectroscopy].

PubMed

Zhang, Zeng-yan; Xiao, Ti-qiao; Zhao, Hong-wei; Yu, Xiao-han; Xi, Zai-jun; Xu, Hong-jie

2008-09-01

Adenosine, thymidine, guanosine, cytidine and uridine form the building blocks of ribose nucleic acid (RNA) and deoxyribose nucleic acid (DNA). Nucleosides and their derivants are all have biological activities. Some of them can be used as medicine directly or as materials to synthesize other medicines. It is meaningful to detect the component and content in nucleosides mixtures. In the present paper, components and contents of the mixtures of adenosine, thymidine, guanosine, cytidine and uridine were analyzed. THz absorption spectra of pure nucleosides were set as standard spectra. The mixture's absorption spectra were analyzed by linear regression with non-negative constraint to identify the components and their relative content in the mixtures. The experimental and analyzing results show that it is simple and effective to get the components and their relative percentage in the mixtures by terahertz time domain spectroscopy with a relative error less than 10%. Component which is absent could be excluded exactly by this method, and the error sources were also analyzed. All the experiments and analysis confirms that this method is of no damage or contamination to the sample. This means that it will be a simple, effective and new method in biochemical materials analysis, which extends the application field of THz-TDS.

Testing for genetic association taking into account phenotypic information of relatives.

PubMed

Uh, Hae-Won; Wijk, Henk Jan van der; Houwing-Duistermaat, Jeanine J

2009-12-15

We investigated efficient case-control association analysis using family data. The outcome of interest was coronary heart disease. We employed existing and new methods that take into account the correlations among related individuals to obtain the proper type I error rates. The methods considered for autosomal single-nucleotide polymorphisms were: 1) generalized estimating equations-based methods, 2) variance-modified Cochran-Armitage (MCA) trend test incorporating kinship coefficients, and 3) genotypic modified quasi-likelihood score test. Additionally, for X-linked single-nucleotide polymorphisms we proposed a two-degrees-of-freedom test. Performance of these methods was tested using Framingham Heart Study 500 k array data.

STANDARD OPERATING PROCEDURE FOR QUALITY ASSURANCE IN ANALYTICAL CHEMISTRY METHODS DEVELOPMENT

EPA Science Inventory

The Environmental Protection Agency's (EPA) Office of Research and Development (ORD) is engaged in the development, demonstration, and validation of new or newly adapted methods of analysis for environmentally related samples. Recognizing that a "one size fits all" approach to qu...

Machine Learning, Sentiment Analysis, and Tweets: An Examination of Alzheimer's Disease Stigma on Twitter.

PubMed

Oscar, Nels; Fox, Pamela A; Croucher, Racheal; Wernick, Riana; Keune, Jessica; Hooker, Karen

2017-09-01

Social scientists need practical methods for harnessing large, publicly available datasets that inform the social context of aging. We describe our development of a semi-automated text coding method and use a content analysis of Alzheimer's disease (AD) and dementia portrayal on Twitter to demonstrate its use. The approach improves feasibility of examining large publicly available datasets. Machine learning techniques modeled stigmatization expressed in 31,150 AD-related tweets collected via Twitter's search API based on 9 AD-related keywords. Two researchers manually coded 311 random tweets on 6 dimensions. This input from 1% of the dataset was used to train a classifier against the tweet text and code the remaining 99% of the dataset. Our automated process identified that 21.13% of the AD-related tweets used AD-related keywords to perpetuate public stigma, which could impact stereotypes and negative expectations for individuals with the disease and increase "excess disability". This technique could be applied to questions in social gerontology related to how social media outlets reflect and shape attitudes bearing on other developmental outcomes. Recommendations for the collection and analysis of large Twitter datasets are discussed. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Stability-Derivative Determination from Flight Data

NASA Technical Reports Server (NTRS)

Holowicz, Chester H.; Holleman, Euclid C.

1958-01-01

A comprehensive discussion of the various factors affecting the determination of stability and control derivatives from flight data is presented based on the experience of the NASA High-Speed Flight Station. Factors relating to test techniques, determination of mass characteristics, instrumentation, and methods of analysis are discussed. For most longitudinal-stability-derivative analyses simple equations utilizing period and damping have been found to be as satisfactory as more comprehensive methods. The graphical time-vector method has been the basis of lateral-derivative analysis, although simple approximate methods can be useful If applied with caution. Control effectiveness has been generally obtained by relating the peak acceleration to the rapid control input, and consideration must be given to aerodynamic contributions if reasonable accuracy is to be realized.. Because of the many factors involved In the determination of stability derivatives, It is believed that the primary stability and control derivatives are probably accurate to within 10 to 25 percent, depending upon the specific derivative. Static-stability derivatives at low angle of attack show the greatest accuracy.

Field Demonstration Report Applied Innovative Technologies for Characterization of Nitrocellulose- and Nitroglycerine Contaminated Buildings and Soils, Rev 1

DTIC Science & Technology

2007-01-05

positive / false negatives. The quantitative on-site methods were evaluated using linear regression analysis and relative percent difference (RPD) comparison...Conclusion ...............................................................................................3-9 3.2 Quantitative Analysis Using CRREL...3-37 3.3 Quantitative Analysis for NG by GC/TID.........................................................3-38 3.3.1 Introduction

The Effects of Health Education on Patients with Hypertension in China: A Meta-Analysis

ERIC Educational Resources Information Center

Xu, L. J.; Meng, Q.; He, S. W.; Yin, X. L.; Tang, Z. L.; Bo, H. Y.; Lan, X. Y.

2014-01-01

Objective: This study collected on from all research relating to health education and hypertension in China and, with the aid of meta-analysis tools, assessed the outcomes of such health education. The analysis provides a basis for the further development of health-education programmes for patients with hypertension. Methods: Literature searches…

A Novel Quantitative Approach to Concept Analysis: The Internomological Network

PubMed Central

Cook, Paul F.; Larsen, Kai R.; Sakraida, Teresa J.; Pedro, Leli

2012-01-01

Background When a construct such as patients’ transition to self-management of chronic illness is studied by researchers across multiple disciplines, the meaning of key terms can become confused. This results from inherent problems in language where a term can have multiple meanings (polysemy) and different words can mean the same thing (synonymy). Objectives To test a novel quantitative method for clarifying the meaning of constructs by examining the similarity of published contexts in which they are used. Method Published terms related to the concept transition to self-management of chronic illness were analyzed using the internomological network (INN), a type of latent semantic analysis to calculate the mathematical relationships between constructs based on the contexts in which researchers use each term. This novel approach was tested by comparing results to those from concept analysis, a best-practice qualitative approach to clarifying meanings of terms. By comparing results of the two methods, the best synonyms of transition to self-management, as well as key antecedent, attribute, and consequence terms, were identified. Results Results from INN analysis were consistent with those from concept analysis. The potential synonyms self-management, transition, and adaptation had the greatest utility. Adaptation was the clearest overall synonym, but had lower cross-disciplinary use. The terms coping and readiness had more circumscribed meanings. The INN analysis confirmed key features of transition to self-management, and suggested related concepts not found by the previous review. Discussion The INN analysis is a promising novel methodology that allows researchers to quantify the semantic relationships between constructs. The method works across disciplinary boundaries, and may help to integrate the diverse literature on self-management of chronic illness. PMID:22592387

Sampling and pyrosequencing methods for characterizing bacterial communities in the human gut using 16S sequence tags.

PubMed

Wu, Gary D; Lewis, James D; Hoffmann, Christian; Chen, Ying-Yu; Knight, Rob; Bittinger, Kyle; Hwang, Jennifer; Chen, Jun; Berkowsky, Ronald; Nessel, Lisa; Li, Hongzhe; Bushman, Frederic D

2010-07-30

Intense interest centers on the role of the human gut microbiome in health and disease, but optimal methods for analysis are still under development. Here we present a study of methods for surveying bacterial communities in human feces using 454/Roche pyrosequencing of 16S rRNA gene tags. We analyzed fecal samples from 10 individuals and compared methods for storage, DNA purification and sequence acquisition. To assess reproducibility, we compared samples one cm apart on a single stool specimen for each individual. To analyze storage methods, we compared 1) immediate freezing at -80 degrees C, 2) storage on ice for 24 or 3) 48 hours. For DNA purification methods, we tested three commercial kits and bead beating in hot phenol. Variations due to the different methodologies were compared to variation among individuals using two approaches--one based on presence-absence information for bacterial taxa (unweighted UniFrac) and the other taking into account their relative abundance (weighted UniFrac). In the unweighted analysis relatively little variation was associated with the different analytical procedures, and variation between individuals predominated. In the weighted analysis considerable variation was associated with the purification methods. Particularly notable was improved recovery of Firmicutes sequences using the hot phenol method. We also carried out surveys of the effects of different 454 sequencing methods (FLX versus Titanium) and amplification of different 16S rRNA variable gene segments. Based on our findings we present recommendations for protocols to collect, process and sequence bacterial 16S rDNA from fecal samples--some major points are 1) if feasible, bead-beating in hot phenol or use of the PSP kit improves recovery; 2) storage methods can be adjusted based on experimental convenience; 3) unweighted (presence-absence) comparisons are less affected by lysis method.

Technical note: validation of a motion analysis system for measuring the relative motion of the intermediate component of a tripolar total hip arthroplasty prosthesis.

PubMed

Chen, Qingshan; Lazennec, Jean Yves; Guyen, Olivier; Kinbrum, Amy; Berry, Daniel J; An, Kai-Nan

2005-07-01

Tripolar total hip arthroplasty (THA) prosthesis had been suggested as a method to reduce the occurrence of hip dislocation and microseparation. Precisely measuring the motion of the intermediate component in vitro would provide fundamental knowledge for understanding its mechanism. The present study validates the accuracy and repeatability of a three-dimensional motion analysis system to quantitatively measure the relative motion of the intermediate component of tripolar total hip arthroplasty prostheses. Static and dynamic validations of the system were made by comparing the measurement to that of a potentiometer. Differences between the mean system-calculated angle and the angle measured by the potentiometer were within +/-1 degrees . The mean within-trial variability was less than 1 degrees . The mean slope was 0.9-1.02 for different angular velocities. The dynamic noise was within 1 degrees . The system was then applied to measure the relative motion of an eccentric THA prosthesis. The study shows that this motion analysis system provides an accurate and practical method for measuring the relative motion of the tripolar THA prosthesis in vitro, a necessary first step towards the understanding of its in vivo kinematics.

Optimization of Injection Molding Parameters for HDPE/TiO₂ Nanocomposites Fabrication with Multiple Performance Characteristics Using the Taguchi Method and Grey Relational Analysis.

PubMed

Pervez, Hifsa; Mozumder, Mohammad S; Mourad, Abdel-Hamid I

2016-08-22

The current study presents an investigation on the optimization of injection molding parameters of HDPE/TiO₂ nanocomposites using grey relational analysis with the Taguchi method. Four control factors, including filler concentration (i.e., TiO₂), barrel temperature, residence time and holding time, were chosen at three different levels of each. Mechanical properties, such as yield strength, Young's modulus and elongation, were selected as the performance targets. Nine experimental runs were carried out based on the Taguchi L₉ orthogonal array, and the data were processed according to the grey relational steps. The optimal process parameters were found based on the average responses of the grey relational grades, and the ideal operating conditions were found to be a filler concentration of 5 wt % TiO₂, a barrel temperature of 225 °C, a residence time of 30 min and a holding time of 20 s. Moreover, analysis of variance (ANOVA) has also been applied to identify the most significant factor, and the percentage of TiO₂ nanoparticles was found to have the most significant effect on the properties of the HDPE/TiO₂ nanocomposites fabricated through the injection molding process.

Gravity Tides Extracted from Relative Gravimeter Data by Combining Empirical Mode Decomposition and Independent Component Analysis

NASA Astrophysics Data System (ADS)

Yu, Hongjuan; Guo, Jinyun; Kong, Qiaoli; Chen, Xiaodong

2018-04-01

The static observation data from a relative gravimeter contain noise and signals such as gravity tides. This paper focuses on the extraction of the gravity tides from the static relative gravimeter data for the first time applying the combined method of empirical mode decomposition (EMD) and independent component analysis (ICA), called the EMD-ICA method. The experimental results from the CG-5 gravimeter (SCINTREX Limited Ontario Canada) data show that the gravity tides time series derived by EMD-ICA are consistent with the theoretical reference (Longman formula) and the RMS of their differences only reaches 4.4 μGal. The time series of the gravity tides derived by EMD-ICA have a strong correlation with the theoretical time series and the correlation coefficient is greater than 0.997. The accuracy of the gravity tides estimated by EMD-ICA is comparable to the theoretical model and is slightly higher than that of independent component analysis (ICA). EMD-ICA could overcome the limitation of ICA having to process multiple observations and slightly improve the extraction accuracy and reliability of gravity tides from relative gravimeter data compared to that estimated with ICA.

Variance analysis of forecasted streamflow maxima in a wet temperate climate

NASA Astrophysics Data System (ADS)

Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

2018-05-01

Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

Review of the Air-Coupled Impact-Echo Method for Non-Destructive Testing

NASA Astrophysics Data System (ADS)

Nowotarski, Piotr; Dubas, Sebastian; Milwicz, Roman

2017-10-01

The article presents the general idea of Air-Coupled Impact-Echo (ACIE) method which is one of the non-destructive testing (NDT) techniques used in the construction industry. One of the main advantages of the general Impact Echo (IE) method is that it is sufficient to access from one side to that of the structure which greatly facilitate research in the road facilities or places which are difficult to access and diagnose. The main purpose of the article is to present state-of-the-art related to ACIE method based on the publications available at Thomson Reuters Web of Science Core Collection database (WOS) with the further analysis of the mentioned methods. Deeper analysis was also performed for the newest publications published within last 3 years related to ACIE for investigation on the subject of main focus of the researchers and scientists to try to define possible regions where additional examination and work is necessary. One of the main conclusions that comes from the performed analysis is that ACIE methods can be widely used for performing NDT of concrete structures and can be performed faster than standard IE method thanks to the Air-coupled sensors. What is more, 92.3% of the analysed recent research described in publications connected with ACIE was performed in laboratories, and only 23.1% in-situ on real structures. This indicates that method requires further research to prepare test stand ready to perform analysis on real objects outside laboratory conditions. Moreover, algorithms that are used for data processing and later presentation in ACIE method are still being developed and there is no universal solution available for all kinds of the existing and possible to find defects, which indicates possible research area for further works. Authors are of the opinion that emerging ACIE method could be good opportunity for ND testing especially for concrete structures. Development and refinement of test stands that will allow to perform in-situ tests could shorten the overall time of the research and with the connection of implementation of higher accuracy algorithms for data analysis better precision of defects localization can be achieved.

Classification of the European Union member states according to the relative level of sustainable development.

PubMed

Anna, Bluszcz

Nowadays methods of measurement and assessment of the level of sustained development at the international, national and regional level are a current research problem, which requires multi-dimensional analysis. The relative assessment of the sustainability level of the European Union member states and the comparative analysis of the position of Poland relative to other countries was the aim of the conducted studies in the article. EU member states were treated as objects in the multi-dimensional space. Dimensions of space were specified by ten diagnostic variables describing the sustainability level of UE countries in three dimensions, i.e., social, economic and environmental. Because the compiled statistical data were expressed in different units of measure, taxonomic methods were used for building an aggregated measure to assess the level of sustainable development of EU member states, which through normalisation of variables enabled the comparative analysis between countries. Methodology of studies consisted of eight stages, which included, among others: defining data matrices, calculating the variability coefficient for all variables, which variability coefficient was under 10 %, division of variables into stimulants and destimulants, selection of the method of variable normalisation, developing matrices of normalised data, selection of the formula and calculating the aggregated indicator of the relative level of sustainable development of the EU countries, calculating partial development indicators for three studies dimensions: social, economic and environmental and the classification of the EU countries according to the relative level of sustainable development. Statistical date were collected based on the Polish Central Statistical Office publication.

Spatial analysis of volatile organic compounds in South Philadelphia using passive samplers

EPA Science Inventory

Select volatile organic compounds (VOCs) were measured in the vicinity of a petroleum refinery and related operations in South Philadelphia, Pennsylvania, USA, using passive air sampling and laboratory analysis methods. Two-week, time-integrated samplers were deployed at 17 sites...

A comparative analysis of spectral exponent estimation techniques for 1/fβ processes with applications to the analysis of stride interval time series

PubMed Central

Schaefer, Alexander; Brach, Jennifer S.; Perera, Subashan; Sejdić, Ervin

2013-01-01

Background The time evolution and complex interactions of many nonlinear systems, such as in the human body, result in fractal types of parameter outcomes that exhibit self similarity over long time scales by a power law in the frequency spectrum S(f) = 1/fβ. The scaling exponent β is thus often interpreted as a “biomarker” of relative health and decline. New Method This paper presents a thorough comparative numerical analysis of fractal characterization techniques with specific consideration given to experimentally measured gait stride interval time series. The ideal fractal signals generated in the numerical analysis are constrained under varying lengths and biases indicative of a range of physiologically conceivable fractal signals. This analysis is to complement previous investigations of fractal characteristics in healthy and pathological gait stride interval time series, with which this study is compared. Results The results of our analysis showed that the averaged wavelet coefficient method consistently yielded the most accurate results. Comparison with Existing Methods: Class dependent methods proved to be unsuitable for physiological time series. Detrended fluctuation analysis as most prevailing method in the literature exhibited large estimation variances. Conclusions The comparative numerical analysis and experimental applications provide a thorough basis for determining an appropriate and robust method for measuring and comparing a physiologically meaningful biomarker, the spectral index β. In consideration of the constraints of application, we note the significant drawbacks of detrended fluctuation analysis and conclude that the averaged wavelet coefficient method can provide reasonable consistency and accuracy for characterizing these fractal time series. PMID:24200509

Systematic analysis of molecular mechanisms for HCC metastasis via text mining approach.

PubMed

Zhen, Cheng; Zhu, Caizhong; Chen, Haoyang; Xiong, Yiru; Tan, Junyuan; Chen, Dong; Li, Jin

2017-02-21

To systematically explore the molecular mechanism for hepatocellular carcinoma (HCC) metastasis and identify regulatory genes with text mining methods. Genes with highest frequencies and significant pathways related to HCC metastasis were listed. A handful of proteins such as EGFR, MDM2, TP53 and APP, were identified as hub nodes in PPI (protein-protein interaction) network. Compared with unique genes for HBV-HCCs, genes particular to HCV-HCCs were less, but may participate in more extensive signaling processes. VEGFA, PI3KCA, MAPK1, MMP9 and other genes may play important roles in multiple phenotypes of metastasis. Genes in abstracts of HCC-metastasis literatures were identified. Word frequency analysis, KEGG pathway and PPI network analysis were performed. Then co-occurrence analysis between genes and metastasis-related phenotypes were carried out. Text mining is effective for revealing potential regulators or pathways, but the purpose of it should be specific, and the combination of various methods will be more useful.

Biotoxicity of commonly used root canal sealers: A meta-analysis

PubMed Central

Kaur, Amandeep; Shah, Naseem; Logani, Ajay; Mishra, Navin

2015-01-01

Introduction: The main objective of a root canal sealer is to provide a fluid tight seal. The purpose of this systematic meta-analysis was to determine the relative toxicity of commonly used root canal sealers like zinc oxide eugenol, calcium hydroxide, and resin-based sealers. Materials and Methods: An online search was conducted in peer-reviewed journals listed in PubMed, Cochrane, EBSCO, and IndMed databases between 2000 and 2012). Statistical analysis was carried out by using analysis of variance (ANOVA) followed by post-hoc comparison by Bonferroni method. The comparison between toxicity at 24 h and between 3 and 7 days was done by using paired t-test for each sealer. Results: At 24 h, the relative biotoxicity of the three sealers reported was insignificant (P- value 0.29), but the difference in toxicity was found significant (P < 0.001) after 3 days. Conclusion: Calcium hydroxide sealer and zinc oxide eugenol were found to be significantly biotoxic as compared to resin-based sealers after 3 days. PMID:25829682

Methods for geochemical analysis

USGS Publications Warehouse

Baedecker, Philip A.

1987-01-01

The laboratories for analytical chemistry within the Geologic Division of the U.S. Geological Survey are administered by the Office of Mineral Resources. The laboratory analysts provide analytical support to those programs of the Geologic Division that require chemical information and conduct basic research in analytical and geochemical areas vital to the furtherance of Division program goals. Laboratories for research and geochemical analysis are maintained at the three major centers in Reston, Virginia, Denver, Colorado, and Menlo Park, California. The Division has an expertise in a broad spectrum of analytical techniques, and the analytical research is designed to advance the state of the art of existing techniques and to develop new methods of analysis in response to special problems in geochemical analysis. The geochemical research and analytical results are applied to the solution of fundamental geochemical problems relating to the origin of mineral deposits and fossil fuels, as well as to studies relating to the distribution of elements in varied geologic systems, the mechanisms by which they are transported, and their impact on the environment.

A comparative study of biomass integrated gasification combined cycle power systems: Performance analysis.

PubMed

Zang, Guiyan; Tejasvi, Sharma; Ratner, Albert; Lora, Electo Silva

2018-05-01

The Biomass Integrated Gasification Combined Cycle (BIGCC) power system is believed to potentially be a highly efficient way to utilize biomass to generate power. However, there is no comparative study of BIGCC systems that examines all the latest improvements for gasification agents, gas turbine combustion methods, and CO 2 Capture and Storage options. This study examines the impact of recent advancements on BIGCC performance through exergy analysis using Aspen Plus. Results show that the exergy efficiency of these systems is ranged from 22.3% to 37.1%. Furthermore, exergy analysis indicates that the gas turbine with external combustion has relatively high exergy efficiency, and Selexol CO 2 removal method has low exergy destruction. Moreover, the sensitivity analysis shows that the system exergy efficiency is more sensitive to the initial temperature and pressure ratio of the gas turbine, whereas has a relatively weak dependence on the initial temperature and initial pressure of the steam turbine. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evaluation of DNA extraction methods for the analysis of microbial community in biological activated carbon.

PubMed

Zheng, Lu; Gao, Naiyun; Deng, Yang

2012-01-01

It is difficult to isolate DNA from biological activated carbon (BAC) samples used in water treatment plants, owing to the scarcity of microorganisms in BAC samples. The aim of this study was to identify DNA extraction methods suitable for a long-term, comprehensive ecological analysis of BAC microbial communities. To identify a procedure that can produce high molecular weight DNA, maximizes detectable diversity and is relatively free from contaminants, the microwave extraction method, the cetyltrimethylammonium bromide (CTAB) extraction method, a commercial DNA extraction kit, and the ultrasonic extraction method were used for the extraction of DNA from BAC samples. Spectrophotometry, agarose gel electrophoresis and polymerase chain reaction (PCR)-restriction fragment length polymorphisms (RFLP) analysis were conducted to compare the yield and quality of DNA obtained using these methods. The results showed that the CTAB method produce the highest yield and genetic diversity of DNA from BAC samples, but DNA purity was slightly less than that obtained with the DNA extraction-kit method. This study provides a theoretical basis for establishing and selecting DNA extraction methods for BAC samples.

Mathematical modeling of vibration processes in reinforced concrete structures for setting up crack initiation monitoring

NASA Astrophysics Data System (ADS)

Bykov, A. A.; Matveenko, B. P.; Serovaev, G. S.; Shardakov, I. N.; Shestakov, A. P.

2015-03-01

The contemporary construction industry is based on the use of reinforced concrete structures, but emergency situations resulting in fracture can arise in their exploitation. In a majority of cases, reinforced concrete fracture is realized as the process of crack formation and development. As a rule, the appearance of the first cracks does not lead to the complete loss of the carrying capacity but is a fracture precursor. One method for ensuring the safe operation of building structures is based on crack initiation monitoring. A vibration method for the monitoring of reinforced concrete structures is justified in this paper. An example of a reinforced concrete beam is used to consider all stages related to the analysis of the behavior of natural frequencies in the development of a crack-shaped defect and the use of the obtained numerical results for the vibration test method. The efficiency of the method is illustrated by the results of modeling of the physical part of the method related to the analysis of the natural frequency evolution as a response to the impact action in the crack development process.

Extraction and Determination of Cyproheptadine in Human Urine by DLLME-HPLC Method.

PubMed

Maham, Mehdi; Kiarostami, Vahid; Waqif-Husain, Syed; Abroomand-Azar, Parviz; Tehrani, Mohammad Saber; Khoeini Sharifabadi, Malihe; Afrouzi, Hossein; Shapouri, Mahmoudreza; Karami-Osboo, Rouhollah

2013-01-01

Novel dispersive liquid-liquid microextraction (DLLME), coupled with high performance liquid chromatography with photodiode array detection (HPLC-DAD) has been applied for the extraction and determination of cyproheptadine (CPH), an antihistamine, in human urine samples. In this method, 0.6 mL of acetonitrile (disperser solvent) containing 30 μL of carbon tetrachloride (extraction solvent) was rapidly injected by a syringe into 5 mL urine sample. After centrifugation, the sedimented phase containing enriched analyte was dissolved in acetonitrile and an aliquot of this solution injected into the HPLC system for analysis. Development of DLLME procedure includes optimization of some important parameters such as kind and volume of extraction and disperser solvent, pH and salt addition. The proposed method has good linearity in the range of 0.02-4.5 μg mL(-1) and low detection limit (13.1 ng mL(-1)). The repeatability of the method, expressed as relative standard deviation was 4.9% (n = 3). This method has also been applied to the analysis of real urine samples with satisfactory relative recoveries in the range of 91.6-101.0%.

Efficient genotype compression and analysis of large genetic variation datasets

PubMed Central

Layer, Ryan M.; Kindlon, Neil; Karczewski, Konrad J.; Quinlan, Aaron R.

2015-01-01

Genotype Query Tools (GQT) is a new indexing strategy that expedites analyses of genome variation datasets in VCF format based on sample genotypes, phenotypes and relationships. GQT’s compressed genotype index minimizes decompression for analysis, and performance relative to existing methods improves with cohort size. We show substantial (up to 443 fold) performance gains over existing methods and demonstrate GQT’s utility for exploring massive datasets involving thousands to millions of genomes. PMID:26550772

Residents' experiences of relationships with nurses in community-based supported housing - a qualitative study based on Giorgi's method of analysis and self psychology.

PubMed

Rønning, Solrun Brenk; Bjørkly, Stål

2017-01-01

One of the prioritizations in the World Health Organization's (WHO) Mental Health Action Plan 2013-2020 is the provision of community mental health and social care services, such as supported housing. The ongoing process of such deinstitutionalization has raised issues concerning the impact on users' quality of life. The purpose of this study was to explore how residents in supported housing experience receiving professional help and how they perceived their relationships with nurses. The second aim was to investigate the relevance of Giorgi's method of analysis and self psychology in analyzing these experiences. Four residents were interviewed individually. The interviews were based on a semi-structured interview guide and analyzed by Giorgi's method of analysis. Relations were interpreted within self psychology. The residents reported that they not only felt safe in the community but also felt a greater awareness of wanting to appear normal. They seemed to have an easier daily life and felt that the personnel met their selfobject needs when routines allowed for it. Professional awareness of empathic attunement and selfobject roles might enhance residents' self-cohesiveness. The interviews were analyzed by Giorgi's method of analysis, and the use of clinical concepts from self psychology was chosen to achieve a more dynamic understanding of the participants' relational experiences and needs in supported housing.

The efficiency of parameter estimation of latent path analysis using summated rating scale (SRS) and method of successive interval (MSI) for transformation of score to scale

NASA Astrophysics Data System (ADS)

Solimun, Fernandes, Adji Achmad Rinaldo; Arisoesilaningsih, Endang

2017-12-01

Research in various fields generally investigates systems and involves latent variables. One method to analyze the model representing the system is path analysis. The data of latent variables measured using questionnaires by applying attitude scale model yields data in the form of score, before analyzed should be transformation so that it becomes data of scale. Path coefficient, is parameter estimator, calculated from scale data using method of successive interval (MSI) and summated rating scale (SRS). In this research will be identifying which data transformation method is better. Path coefficients have smaller varieties are said to be more efficient. The transformation method that produces scaled data and used in path analysis capable of producing path coefficients (parameter estimators) with smaller varieties is said to be better. The result of analysis using real data shows that on the influence of Attitude variable to Intention Entrepreneurship, has relative efficiency (ER) = 1, where it shows that the result of analysis using data transformation of MSI and SRS as efficient. On the other hand, for simulation data, at high correlation between items (0.7-0.9), MSI method is more efficient 1.3 times better than SRS method.

Determination of low molecular weight alcohols including fusel oil in various samples by diethyl ether extraction and capillary gas chromatography.

PubMed

Woo, Kang-Lyung

2005-01-01

Low molecular weight alcohols including fusel oil were determined using diethyl ether extraction and capillary gas chromatography. Twelve kinds of alcohols were successfully resolved on the HP-FFAP (polyethylene glycol) capillary column. The diethyl ether extraction method was very useful for the analysis of alcohols in alcoholic beverages and biological samples with excellent cleanliness of the resulting chromatograms and high sensitivity compared to the direct injection method. Calibration graphs for all standard alcohols showed good linearity in the concentration range used, 0.001-2% (w/v) for all alcohols. Salting out effects were significant (p < 0.01) for the low molecular weight alcohols methanol, isopropanol, propanol, 2-butanol, n-butanol and ethanol, but not for the relatively high molecular weight alcohols amyl alcohol, isoamyl alcohol, and heptanol. The coefficients of variation of the relative molar responses were less than 5% for all of the alcohols. The limits of detection and quantitation were 1-5 and 10-60 microg/L for the diethyl ether extraction method, and 10-50 and 100-350 microg/L for the direct injection method, respectively. The retention times and relative retention times of standard alcohols were significantly shifted in the direct injection method when the injection volumes were changed, even with the same analysis conditions, but they were not influenced in the diethyl ether extraction method. The recoveries by the diethyl ether extraction method were greater than 95% for all samples and greater than 97% for biological samples.

Development and validation of a reversed phase liquid chromatographic method for analysis of oxytetracycline and related impurities.

PubMed

Kahsay, Getu; Shraim, Fairouz; Villatte, Philippe; Rotger, Jacques; Cassus-Coussère, Céline; Van Schepdael, Ann; Hoogmartens, Jos; Adams, Erwin

2013-03-05

A simple, robust and fast high-performance liquid chromatographic method is described for the analysis of oxytetracycline and its related impurities. The principal peak and impurities are all baseline separated in 20 min using an Inertsil C₈ (150 mm × 4.6 mm, 5 μm) column kept at 50 °C. The mobile phase consists of a gradient mixture of mobile phases A (0.05% trifluoroacetic acid in water) and B (acetonitrile-methanol-tetrahydrofuran, 80:15:5, v/v/v) pumped at a flow rate of 1.3 ml/min. UV detection was performed at 254 nm. The developed method was validated for its robustness, sensitivity, precision and linearity in the range from limit of quantification (LOQ) to 120%. The limits of detection (LOD) and LOQ were found to be 0.08 μg/ml and 0.32 μg/ml, respectively. This method allows the separation of oxytetracycline from all known and 5 unknown impurities, which is better than previously reported in the literature. Moreover, the simple mobile phase composition devoid of non-volatile buffers made the method suitable to interface with mass spectrometry for further characterization of unknown impurities. The developed method has been applied for determination of related substances in oxytetracycline bulk samples available from four manufacturers. The validation results demonstrate that the method is reliable for quantification of oxytetracycline and its impurities. Copyright © 2012 Elsevier B.V. All rights reserved.

Online Social Networking for HIV Education and Prevention: A Mixed Methods Analysis

PubMed Central

Young, Sean D.; Jaganath, Devan

2013-01-01

Background The purpose of this study is to use mixed (qualitative/quantitative) methods to determine 1) the feasibility and acceptability of using online social networking to facilitate HIV-related discussions, and 2) the relationship between HIV-related online discussions and requests for a home-based HIV testing kit, among men who have sex with men (MSM). Methods Participants, primarily African American and Latino, were invited to join a “secret” group on the social networking website, Facebook. Peer leaders, trained in HIV prevention, posted HIV-related content. Participants were not obligated to respond to discussions or remain within the group. Participant public group conversations were qualitatively and thematically analyzed. Quantitative methods tested associations between qualitative data, participants’ demographic information, and likelihood of requesting a home-based HIV testing kit. Results Latino and African-American participants (N=57) voluntarily used Facebook to discuss the following HIV-related topics (N=485 conversations): Prevention and Testing; Knowledge; Stigma; and Advocacy. Older participants more frequently discussed Prevention and Testing, Stigma, and Advocacy, though younger participants more frequently discussed HIV Knowledge-related conversations. As the study progressed, the proportion of messages related to Prevention and Testing and HIV Stigma increased. Multivariate analysis showed that participants posting about HIV Prevention and Testing (compared to those who did not) were significantly more likely to request an HIV testing kit (OR 11.14, p = 0.001). Conclusions Facebook can serve as an innovative forum to increase both HIV prevention discussions and HIV testing requests among at-risk groups. PMID:23324979

Nonclinical dose formulation analysis method validation and sample analysis.

PubMed

Whitmire, Monica Lee; Bryan, Peter; Henry, Teresa R; Holbrook, John; Lehmann, Paul; Mollitor, Thomas; Ohorodnik, Susan; Reed, David; Wietgrefe, Holly D

2010-12-01

Nonclinical dose formulation analysis methods are used to confirm test article concentration and homogeneity in formulations and determine formulation stability in support of regulated nonclinical studies. There is currently no regulatory guidance for nonclinical dose formulation analysis method validation or sample analysis. Regulatory guidance for the validation of analytical procedures has been developed for drug product/formulation testing; however, verification of the formulation concentrations falls under the framework of GLP regulations (not GMP). The only current related regulatory guidance is the bioanalytical guidance for method validation. The fundamental parameters for bioanalysis and formulation analysis validations that overlap include: recovery, accuracy, precision, specificity, selectivity, carryover, sensitivity, and stability. Divergence in bioanalytical and drug product validations typically center around the acceptance criteria used. As the dose formulation samples are not true "unknowns", the concept of quality control samples that cover the entire range of the standard curve serving as the indication for the confidence in the data generated from the "unknown" study samples may not always be necessary. Also, the standard bioanalytical acceptance criteria may not be directly applicable, especially when the determined concentration does not match the target concentration. This paper attempts to reconcile the different practices being performed in the community and to provide recommendations of best practices and proposed acceptance criteria for nonclinical dose formulation method validation and sample analysis.

Associations between heavy-vehicle driver compensation methods, fatigue-related driving behavior, and sleepiness.

PubMed

Thompson, Jason; Stevenson, Mark

2014-01-01

There has been growing recognition that broader economic and organizational factors play a role in creating work environments that facilitate high-risk driving behavior. This study investigates the association between compensation methods for drivers, fatigue-related driving behavior, and sleepiness among Australian heavy-vehicle drivers. Specifically, we hypothesized that piece-rate compensation methods linked to performance outcomes would be associated with greater levels of fatigue-related driving behaviors and sleepiness. We examined data from a random sample of 346 long-haul heavy-vehicle drivers who had not been involved in a crash. A 40-min interview was conducted that elicited information regarding driver demographics, truck characteristics, and compensation arrangements. Specific details about drivers' behavior on their most recent trip including load(s) carried, distances driven, hours driven, rest breaks, and hours of sleep on the previous night were taken. The interview also included a standardized assessment of sleepiness using the Epworth Sleepiness Scale (ESS). A multivariate analysis of covariance demonstrated a significant multivariate effect for compensation methods across the combined, fatigue-related driving behavior dependent variables, F (10, 676)=2.80, p<.01. Between-subject effects demonstrated significant association between compensation methods and 4 of 5 fatigue-related variables under study, including kilometers driven per day, F (2, 340)=7.75, p<.001, hours driven per day, F (2, 341)=2.64, p<.05, total hours worked per week, F (2, 340)=5.27, p<.01, and mean driving time between breaks, F (2, 341)=4.45, p<.05. Post hoc tests revealed that piece-rate compensation methods were associated with higher levels of fatigue-related driving than non-piece-rate methods. Follow-up analysis also revealed higher caffeine and amphetamines use among piece-rate drivers for the purpose of staying awake while driving. Despite this, no association between compensation methods and sleepiness were revealed. RESULTS confirmed that performance-based compensation methods are associated with work practices that may exacerbate driving behaviors associated with fatigue. Despite this finding, however, performance-based compensation methods were not associated with higher levels of sleepiness. This highlights the presence of potential differences in self-selection, operational, or fatigue management practices that may be common to drivers paid under various methods. Implications of these results for safety policy and future safety research within the heavy-vehicle industry are discussed.

Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force.

PubMed

Hauber, A Brett; González, Juan Marcos; Groothuis-Oudshoorn, Catharina G M; Prior, Thomas; Marshall, Deborah A; Cunningham, Charles; IJzerman, Maarten J; Bridges, John F P

2016-06-01

Conjoint analysis is a stated-preference survey method that can be used to elicit responses that reveal preferences, priorities, and the relative importance of individual features associated with health care interventions or services. Conjoint analysis methods, particularly discrete choice experiments (DCEs), have been increasingly used to quantify preferences of patients, caregivers, physicians, and other stakeholders. Recent consensus-based guidance on good research practices, including two recent task force reports from the International Society for Pharmacoeconomics and Outcomes Research, has aided in improving the quality of conjoint analyses and DCEs in outcomes research. Nevertheless, uncertainty regarding good research practices for the statistical analysis of data from DCEs persists. There are multiple methods for analyzing DCE data. Understanding the characteristics and appropriate use of different analysis methods is critical to conducting a well-designed DCE study. This report will assist researchers in evaluating and selecting among alternative approaches to conducting statistical analysis of DCE data. We first present a simplistic DCE example and a simple method for using the resulting data. We then present a pedagogical example of a DCE and one of the most common approaches to analyzing data from such a question format-conditional logit. We then describe some common alternative methods for analyzing these data and the strengths and weaknesses of each alternative. We present the ESTIMATE checklist, which includes a list of questions to consider when justifying the choice of analysis method, describing the analysis, and interpreting the results. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Relevant Feature Set Estimation with a Knock-out Strategy and Random Forests

PubMed Central

Ganz, Melanie; Greve, Douglas N.; Fischl, Bruce; Konukoglu, Ender

2015-01-01

Group analysis of neuroimaging data is a vital tool for identifying anatomical and functional variations related to diseases as well as normal biological processes. The analyses are often performed on a large number of highly correlated measurements using a relatively smaller number of samples. Despite the correlation structure, the most widely used approach is to analyze the data using univariate methods followed by post-hoc corrections that try to account for the data’s multivariate nature. Although widely used, this approach may fail to recover from the adverse effects of the initial analysis when local effects are not strong. Multivariate pattern analysis (MVPA) is a powerful alternative to the univariate approach for identifying relevant variations. Jointly analyzing all the measures, MVPA techniques can detect global effects even when individual local effects are too weak to detect with univariate analysis. Current approaches are successful in identifying variations that yield highly predictive and compact models. However, they suffer from lessened sensitivity and instabilities in identification of relevant variations. Furthermore, current methods’ user-defined parameters are often unintuitive and difficult to determine. In this article, we propose a novel MVPA method for group analysis of high-dimensional data that overcomes the drawbacks of the current techniques. Our approach explicitly aims to identify all relevant variations using a “knock-out” strategy and the Random Forest algorithm. In evaluations with synthetic datasets the proposed method achieved substantially higher sensitivity and accuracy than the state-of-the-art MVPA methods, and outperformed the univariate approach when the effect size is low. In experiments with real datasets the proposed method identified regions beyond the univariate approach, while other MVPA methods failed to replicate the univariate results. More importantly, in a reproducibility study with the well-known ADNI dataset the proposed method yielded higher stability and power than the univariate approach. PMID:26272728

Evaluation of microarray data normalization procedures using spike-in experiments

PubMed Central

Rydén, Patrik; Andersson, Henrik; Landfors, Mattias; Näslund, Linda; Hartmanová, Blanka; Noppa, Laila; Sjöstedt, Anders

2006-01-01

Background Recently, a large number of methods for the analysis of microarray data have been proposed but there are few comparisons of their relative performances. By using so-called spike-in experiments, it is possible to characterize the analyzed data and thereby enable comparisons of different analysis methods. Results A spike-in experiment using eight in-house produced arrays was used to evaluate established and novel methods for filtration, background adjustment, scanning, channel adjustment, and censoring. The S-plus package EDMA, a stand-alone tool providing characterization of analyzed cDNA-microarray data obtained from spike-in experiments, was developed and used to evaluate 252 normalization methods. For all analyses, the sensitivities at low false positive rates were observed together with estimates of the overall bias and the standard deviation. In general, there was a trade-off between the ability of the analyses to identify differentially expressed genes (i.e. the analyses' sensitivities) and their ability to provide unbiased estimators of the desired ratios. Virtually all analysis underestimated the magnitude of the regulations; often less than 50% of the true regulations were observed. Moreover, the bias depended on the underlying mRNA-concentration; low concentration resulted in high bias. Many of the analyses had relatively low sensitivities, but analyses that used either the constrained model (i.e. a procedure that combines data from several scans) or partial filtration (a novel method for treating data from so-called not-found spots) had with few exceptions high sensitivities. These methods gave considerable higher sensitivities than some commonly used analysis methods. Conclusion The use of spike-in experiments is a powerful approach for evaluating microarray preprocessing procedures. Analyzed data are characterized by properties of the observed log-ratios and the analysis' ability to detect differentially expressed genes. If bias is not a major problem; we recommend the use of either the CM-procedure or partial filtration. PMID:16774679

A Comparison of Different Methods for Evaluating Diet, Physical Activity, and Long-Term Weight Gain in 3 Prospective Cohort Studies123

PubMed Central

Smith, Jessica D; Hou, Tao; Hu, Frank B; Rimm, Eric B; Spiegelman, Donna; Willett, Walter C; Mozaffarian, Dariush

2015-01-01

Background: The insidious pace of long-term weight gain (∼1 lb/y or 0.45 kg/y) makes it difficult to study in trials; long-term prospective cohorts provide crucial evidence on its key contributors. Most previous studies have evaluated how prevalent lifestyle habits relate to future weight gain rather than to lifestyle changes, which may be more temporally and physiologically relevant. Objective: Our objective was to evaluate and compare different methodological approaches for investigating diet, physical activity (PA), and long-term weight gain. Methods: In 3 prospective cohorts (total n = 117,992), we assessed how lifestyle relates to long-term weight change (up to 24 y of follow-up) in 4-y periods by comparing 3 analytic approaches: 1) prevalent diet and PA and 4-y weight change (prevalent analysis); 2) 4-y changes in diet and PA with a 4-y weight change (change analysis); and 3) 4-y change in diet and PA with weight change in the subsequent 4 y (lagged-change analysis). We compared these approaches and evaluated the consistency across cohorts, magnitudes of associations, and biological plausibility of findings. Results: Across the 3 methods, consistent, robust, and biologically plausible associations were seen only for the change analysis. Results for prevalent or lagged-change analyses were less consistent across cohorts, smaller in magnitude, and biologically implausible. For example, for each serving of a sugar-sweetened beverage, the observed weight gain was 0.01 lb (95% CI: −0.08, 0.10) [0.005 kg (95% CI: −0.04, 0.05)] based on prevalent analysis; 0.99 lb (95% CI: 0.83, 1.16) [0.45 kg (95% CI: 0.38, 0.53)] based on change analysis; and 0.05 lb (95% CI: −0.10, 0.21) [0.02 kg (95% CI: −0.05, 0.10)] based on lagged-change analysis. Findings were similar for other foods and PA. Conclusions: Robust, consistent, and biologically plausible relations between lifestyle and long-term weight gain are seen when evaluating lifestyle changes and weight changes in discrete periods rather than in prevalent lifestyle or lagged changes. These findings inform the optimal methods for evaluating lifestyle and long-term weight gain and the potential for bias when other methods are used. PMID:26377763

In Response to Lindsay and Emerson

ERIC Educational Resources Information Center

Sturmey, Peter

2006-01-01

Background: Lindsay's comments related mostly behaviour, analytic conceptions of human behaviour and therapy. Materials and Method: I argue that radical behaviourism addresses many of his concerns relating to private behaviour and his cognitive analysis of the private behaviour of offenders with intellectual disabilities. Cognitive explanations of…

A method for the inclusion of physical activity-related health benefits in cost-benefit analysis of built environment initiatives.

PubMed

Zapata-Diomedi, Belen; Gunn, Lucy; Giles-Corti, Billie; Shiell, Alan; Lennert Veerman, J

2018-01-01

The built environment has a significant influence on population levels of physical activity (PA) and therefore health. However, PA-related health benefits are seldom considered in transport and urban planning (i.e. built environment interventions) cost-benefit analysis. Cost-benefit analysis implies that the benefits of any initiative are valued in monetary terms to make them commensurable with costs. This leads to the need for monetised values of the health benefits of PA. The aim of this study was to explore a method for the incorporation of monetised PA-related health benefits in cost-benefit analysis of built environment interventions. Firstly, we estimated the change in population level of PA attributable to a change in the built environment due to the intervention. Then, changes in population levels of PA were translated into monetary values. For the first step we used estimates from the literature for the association of built environment features with physical activity outcomes. For the second step we used the multi-cohort proportional multi-state life table model to predict changes in health-adjusted life years and health care costs as a function of changes in PA. Finally, we monetised health-adjusted life years using the value of a statistical life year. Future research could adapt these methods to assess the health and economic impacts of specific urban development scenarios by working in collaboration with urban planners. Copyright © 2017 Elsevier Inc. All rights reserved.

Rapid iterative reanalysis for automated design

NASA Technical Reports Server (NTRS)

Bhatia, K. G.

1973-01-01

A method for iterative reanalysis in automated structural design is presented for a finite-element analysis using the direct stiffness approach. A basic feature of the method is that the generalized stiffness and inertia matrices are expressed as functions of structural design parameters, and these generalized matrices are expanded in Taylor series about the initial design. Only the linear terms are retained in the expansions. The method is approximate because it uses static condensation, modal reduction, and the linear Taylor series expansions. The exact linear representation of the expansions of the generalized matrices is also described and a basis for the present method is established. Results of applications of the present method to the recalculation of the natural frequencies of two simple platelike structural models are presented and compared with results obtained by using a commonly applied analysis procedure used as a reference. In general, the results are in good agreement. A comparison of the computer times required for the use of the present method and the reference method indicated that the present method required substantially less time for reanalysis. Although the results presented are for relatively small-order problems, the present method will become more efficient relative to the reference method as the problem size increases. An extension of the present method to static reanalysis is described, ana a basis for unifying the static and dynamic reanalysis procedures is presented.

Genetic analysis of 430 Chinese Cynodon dactylon accessions using sequence-related amplified polymorphism markers.

PubMed

Huang, Chunqiong; Liu, Guodao; Bai, Changjun; Wang, Wenqiang

2014-10-21

Although Cynodon dactylon (C. dactylon) is widely distributed in China, information on its genetic diversity within the germplasm pool is limited. The objective of this study was to reveal the genetic variation and relationships of 430 C. dactylon accessions collected from 22 Chinese provinces using sequence-related amplified polymorphism (SRAP) markers. Fifteen primer pairs were used to amplify specific C. dactylon genomic sequences. A total of 481 SRAP fragments were generated, with fragment sizes ranging from 260-1800 base pairs (bp). Genetic similarity coefficients (GSC) among the 430 accessions averaged 0.72 and ranged from 0.53-0.96. Cluster analysis conducted by two methods, namely the unweighted pair-group method with arithmetic averages (UPGMA) and principle coordinate analysis (PCoA), separated the accessions into eight distinct groups. Our findings verify that Chinese C. dactylon germplasms have rich genetic diversity, which is an excellent basis for C. dactylon breeding for new cultivars.

Challenges for Better thesis supervision

PubMed Central

Ghadirian, Laleh; Sayarifard, Azadeh; Majdzadeh, Reza; Rajabi, Fatemeh; Yunesian, Masoud

2014-01-01

Background: Conduction of thesis by the students is one of their major academic activities. Thesis quality and acquired experiences are highly dependent on the supervision. Our study is aimed at identifing the challenges in thesis supervision from both students and faculty members point of view. Methods: This study was conducted using individual in-depth interviews and Focus Group Discussions (FGD). The participants were 43 students and faculty members selected by purposive sampling. It was carried out in Tehran University of Medical Sciences in 2012. Data analysis was done concurrently with data gathering using content analysis method. Results: Our data analysis resulted in 162 codes, 17 subcategories and 4 major categories, "supervisory knowledge and skills", "atmosphere", "bylaws and regulations relating to supervision" and "monitoring and evaluation". Conclusion: This study showed that more attention and planning in needed for modifying related rules and regulations, qualitative and quantitative improvement in mentorship training, research atmosphere improvement and effective monitoring and evaluation in supervisory area. PMID:25250273

The death of the Job plot, transparency, open science and online tools, uncertainty estimation methods and other developments in supramolecular chemistry data analysis.

PubMed

Brynn Hibbert, D; Thordarson, Pall

2016-10-25

Data analysis is central to understanding phenomena in host-guest chemistry. We describe here recent developments in this field starting with the revelation that the popular Job plot method is inappropriate for most problems in host-guest chemistry and that the focus should instead be on systematically fitting data and testing all reasonable binding models. We then discuss approaches for estimating uncertainties in binding studies using case studies and simulations to highlight key issues. Related to this is the need for ready access to data and transparency in the methodology or software used, and we demonstrate an example a webportal () that aims to address this issue. We conclude with a list of best-practice protocols for data analysis in supramolecular chemistry that could easily be translated to other related problems in chemistry including measuring rate constants or drug IC 50 values.

Stress analysis of ribbon parachutes

NASA Technical Reports Server (NTRS)

Reynolds, D. T.; Mullins, W. M.

1975-01-01

An analytical method has been developed for determining the internal load distribution for ribbon parachutes subjected to known riser and aerodynamic forces. Finite elements with non-linear elastic properties represent the parachute structure. This method is an extension of the analysis previously developed by the authors and implemented in the digital computer program CANO. The present analysis accounts for the effect of vertical ribbons in the solution for canopy shape and stress distribution. Parametric results are presented which relate the canopy stress distribution to such factors as vertical ribbon strength, number of gores, and gore shape in a ribbon parachute.

Analysis of radiometric signal in sedimentating suspension flow in open channel

NASA Astrophysics Data System (ADS)

Zych, Marcin; Hanus, Robert; Petryka, Leszek; Świsulski, Dariusz; Doktor, Marek; Mastej, Wojciech

2015-05-01

The article discusses issues related to the estimation of the sedimentating solid particles average flow velocity in an open channel using radiometric methods. Due to the composition of the compound, which formed water and diatomite, received data have a very weak signal to noise ratio. In the process analysis the known determining of the solid phase transportation time delay the classical cross-correlation function is the most reliable method. The use of advanced frequency analysis based on mutual spectral density function and wavelet transform of recorded signals allows a reduction of the noise contribution.

Exploring the Concept of HIV-Related Stigma

PubMed Central

Florom-Smith, Aubrey L.; De Santis, Joseph P.

2013-01-01

BACKGROUND HIV infection is a chronic, manageable illness. Despite advances in the care and treatment of people living with HIV infection, HIV-related stigma remains a challenge to HIV testing, care, and prevention. Numerous studies have documented the impact of HIV-related stigma among various groups of people living with HIV infection, but the concept of HIV-related stigma remains unclear. PURPOSE Concept exploration of HIV-related stigma via an integrative literature review was conducted in order to examine the existing knowledge base of this concept. METHODS Search engines were employed to review the existing knowledge base of this concept. CONCLUSION After the integrative literature review, an analysis of HIV-related stigma emerged. Implications for future concept analysis, research, and practice are included. PMID:22861652

The behavioral economics of drug self-administration: A review and new analytical approach for within-session procedures

PubMed Central

Bentzley, Brandon S.; Fender, Kimberly M.; Aston-Jones, Gary

2012-01-01

Rationale Behavioral-economic demand curve analysis offers several useful measures of drug self-administration. Although generation of demand curves previously required multiple days, recent within-session procedures allow curve construction from a single 110-min cocaine self-administration session, making behavioral-economic analyses available to a broad range of self-administration experiments. However, a mathematical approach of curve fitting has not been reported for the within-session threshold procedure. Objectives We review demand curve analysis in drug self-administration experiments and provide a quantitative method for fitting curves to single-session data that incorporates relative stability of brain drug concentration. Methods Sprague-Dawley rats were trained to self-administer cocaine, and then tested with the threshold procedure in which the cocaine dose was sequentially decreased on a fixed ratio-1 schedule. Price points (responses/mg cocaine) outside of relatively stable brain cocaine concentrations were removed before curves were fit. Curve-fit accuracy was determined by the degree of correlation between graphical and calculated parameters for cocaine consumption at low price (Q0) and the price at which maximal responding occurred (Pmax). Results Removing price points that occurred at relatively unstable brain cocaine concentrations generated precise estimates of Q0 and resulted in Pmax values with significantly closer agreement with graphical Pmax than conventional methods. Conclusion The exponential demand equation can be fit to single-session data using the threshold procedure for cocaine self-administration. Removing data points that occur during relatively unstable brain cocaine concentrations resulted in more accurate estimates of demand curve slope than graphical methods, permitting a more comprehensive analysis of drug self-administration via a behavioral-economic framework. PMID:23086021

Liquid chromatography/electrospray ionization/isotopic dilution mass spectrometry analysis of n-(phosphonomethyl) glycine and mass spectrometry analysis of aminomethyl phosphonic acid in environmental water and vegetation matrixes.

PubMed

Grey, L; Nguyen, B; Yang, P

2001-01-01

A liquid chromatography/electrospray/mass spectrometry (LC/ES/MS) method was developed for the analysis of glyphosate (n-phosphonomethyl glycine) and its metabolite, aminomethyl phosphonic acid (AMPA) using isotope-labelled glyphosate as a method surrogate. Optimized parameters were achieved to derivatize glyphosate and AMPA using 9-fluorenylmethyl chloroformate (FMOC-Cl) in borate buffer prior to a reversed-phase LC analysis. Method spike recovery data obtained using laboratory and real world sample matrixes indicated an excellent correlation between the recovery of the native and isotope-labelled glyphosate. Hence, the first performance-based, isotope dilution MS method with superior precision, accuracy, and data quality was developed for the analysis of glyphosate. There was, however, no observable correlation between the isotope-labelled glyphosate and AMPA. Thus, the use of this procedure for the accurate analysis of AMPA was not supported. Method detection limits established using standard U.S. Environmental Protection Agency protocol were 0.06 and 0.30 microg/L, respectively, for glyphosate and AMPA in water matrixes and 0.11 and 0.53 microg/g, respectively, in vegetation matrixes. Problems, solutions, and the method performance data related to the analysis of chlorine-treated drinking water samples are discussed. Applying this method to other environmental matrixes, e.g., soil, with minimum modifications is possible, assuring accurate, multimedia studies of glyphosate concentration in the environment and the delivery of useful multimedia information for regulatory applications.

40 CFR 60.435 - Test methods and procedures.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Section 60.435 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS... of any affected facility using solvent-borne ink systems shall determine the VOC content of the raw inks and related coatings used at the affected facility by: (1) Analysis using Method 24A of routine...

40 CFR 60.435 - Test methods and procedures.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Section 60.435 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS... of any affected facility using solvent-borne ink systems shall determine the VOC content of the raw inks and related coatings used at the affected facility by: (1) Analysis using Method 24A of routine...

Vectorized Monte Carlo methods for reactor lattice analysis

NASA Technical Reports Server (NTRS)

Brown, F. B.

1984-01-01

Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.

Analysis of X-Ray Line Spectra from a Transient Plasma Under Solar Flare Conditions - Part Three - Diagnostics for Measuring Electron Temperature and Density

NASA Astrophysics Data System (ADS)

Sylwester, J.; Mewe, R.; Schrijver, J.

1980-06-01

In this paper, the third in a series dealing with plasmas out of equilibrium we present quantitative methods of analysis of non-stationary flare plasma parameters. The method is designed to be used for the interpretation of the SMM XRP Bent Crystal Spectrometer spectra. Our analysis is based on measurements of 11 specific lines in the 1.77-3.3 Å range. Using the proposed method we are able to derive information about temperature, density, emission measure, and other related parameters of the flare plasma. It is shown that the measurements, to be made by XRP can give detailed information on these parameters and their time evolution. The method is then tested on some artificial flares, and proves to be useful and accurate.

A novel Markov Blanket-based repeated-fishing strategy for capturing phenotype-related biomarkers in big omics data.

PubMed

Li, Hongkai; Yuan, Zhongshang; Ji, Jiadong; Xu, Jing; Zhang, Tao; Zhang, Xiaoshuai; Xue, Fuzhong

2016-03-09

We propose a novel Markov Blanket-based repeated-fishing strategy (MBRFS) in attempt to increase the power of existing Markov Blanket method (DASSO-MB) and maintain its advantages in omic data analysis. Both simulation and real data analysis were conducted to assess its performances by comparing with other methods including χ(2) test with Bonferroni and B-H adjustment, least absolute shrinkage and selection operator (LASSO) and DASSO-MB. A serious of simulation studies showed that the true discovery rate (TDR) of proposed MBRFS was always close to zero under null hypothesis (odds ratio = 1 for each SNPs) with excellent stability in all three scenarios of independent phenotype-related SNPs without linkage disequilibrium (LD) around them, correlated phenotype-related SNPs without LD around them, and phenotype-related SNPs with strong LD around them. As expected, under different odds ratio and minor allel frequency (MAFs), MBRFS always had the best performances in capturing the true phenotype-related biomarkers with higher matthews correlation coefficience (MCC) for all three scenarios above. More importantly, since proposed MBRFS using the repeated fishing strategy, it still captures more phenotype-related SNPs with minor effects when non-significant phenotype-related SNPs emerged under χ(2) test after Bonferroni multiple correction. The various real omics data analysis, including GWAS data, DNA methylation data, gene expression data and metabolites data, indicated that the proposed MBRFS always detected relatively reasonable biomarkers. Our proposed MBRFS can exactly capture the true phenotype-related biomarkers with the reduction of false negative rate when the phenotype-related biomarkers are independent or correlated, as well as the circumstance that phenotype-related biomarkers are associated with non-phenotype-related ones.

The Technologist Function in Fields Related to Radiology: Tasks in Radiation Therapy and Diagnostic Ultrasound. Research Report No. 9; Relating Technologist Tasks in Diagnostic Radiology, Ultrasound and Radiation Therapy. Research Report No. 10.

ERIC Educational Resources Information Center

Gilpatrick, Eleanor

The two research reports included in this document describe the application of the Health Services Mobility Study (HSMS) task analysis method to two technologist functions and examine the interrelationships of these tasks with those in diagnostic radiology. (The HSMS method includes processes for using the data for designing job ladders, for…

Skeletal mechanism generation for surrogate fuels using directed relation graph with error propagation and sensitivity analysis

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

Niemeyer, Kyle E.; Sung, Chih-Jen; Raju, Mandhapati P.

2010-09-15

A novel implementation for the skeletal reduction of large detailed reaction mechanisms using the directed relation graph with error propagation and sensitivity analysis (DRGEPSA) is developed and presented with examples for three hydrocarbon components, n-heptane, iso-octane, and n-decane, relevant to surrogate fuel development. DRGEPSA integrates two previously developed methods, directed relation graph-aided sensitivity analysis (DRGASA) and directed relation graph with error propagation (DRGEP), by first applying DRGEP to efficiently remove many unimportant species prior to sensitivity analysis to further remove unimportant species, producing an optimally small skeletal mechanism for a given error limit. It is illustrated that the combination ofmore » the DRGEP and DRGASA methods allows the DRGEPSA approach to overcome the weaknesses of each, specifically that DRGEP cannot identify all unimportant species and that DRGASA shields unimportant species from removal. Skeletal mechanisms for n-heptane and iso-octane generated using the DRGEP, DRGASA, and DRGEPSA methods are presented and compared to illustrate the improvement of DRGEPSA. From a detailed reaction mechanism for n-alkanes covering n-octane to n-hexadecane with 2115 species and 8157 reactions, two skeletal mechanisms for n-decane generated using DRGEPSA, one covering a comprehensive range of temperature, pressure, and equivalence ratio conditions for autoignition and the other limited to high temperatures, are presented and validated. The comprehensive skeletal mechanism consists of 202 species and 846 reactions and the high-temperature skeletal mechanism consists of 51 species and 256 reactions. Both mechanisms are further demonstrated to well reproduce the results of the detailed mechanism in perfectly-stirred reactor and laminar flame simulations over a wide range of conditions. The comprehensive and high-temperature n-decane skeletal mechanisms are included as supplementary material with this article. (author)« less

Analysis of Parasite and Other Skewed Counts

PubMed Central

Alexander, Neal

2012-01-01

Objective To review methods for the statistical analysis of parasite and other skewed count data. Methods Statistical methods for skewed count data are described and compared, with reference to those used over a ten year period of Tropical Medicine and International Health. Two parasitological datasets are used for illustration. Results Ninety papers were identified, 89 with descriptive and 60 with inferential analysis. A lack of clarity is noted in identifying measures of location, in particular the Williams and geometric mean. The different measures are compared, emphasizing the legitimacy of the arithmetic mean for skewed data. In the published papers, the t test and related methods were often used on untransformed data, which is likely to be invalid. Several approaches to inferential analysis are described, emphasizing 1) non-parametric methods, while noting that they are not simply comparisons of medians, and 2) generalized linear modelling, in particular with the negative binomial distribution. Additional methods, such as the bootstrap, with potential for greater use are described. Conclusions Clarity is recommended when describing transformations and measures of location. It is suggested that non-parametric methods and generalized linear models are likely to be sufficient for most analyses. PMID:22943299

Diagnostic performance of swab PCR as an alternative to tissue culture methods for diagnosing infections associated with fracture fixation devices.

PubMed

Omar, Mohamed; Suero, Eduardo M; Liodakis, Emmanouil; Reichling, Moritz; Guenther, Daniel; Decker, Sebastian; Stiesch, Meike; Krettek, Christian; Eberhard, Jörg

2016-07-01

Molecular procedures could potentially improve diagnoses of orthopaedic implant-related infections, but are not yet clinically implemented. Analysis of sonication fluid shows the highest sensitivity for diagnosing implant infections in cases of revision surgery with implant removal. However, there remains controversy regarding the best method for obtaining specimens in cases of revision surgery with implant retention. Tissue culture is the most common diagnostic method for pathogen identification in such cases. Here we aimed to assess the diagnostic performance of swab PCR analysis compared to tissue culture from patients undergoing revision surgery of fracture fixation devices. We prospectively investigated 62 consecutive subjects who underwent revision surgery of fracture fixation devices during a two-year period. Tissue samples were collected for cultures, and swabs from the implant surface were obtained for 16S rRNA PCR analysis. Subjects were classified as having an implant-related infection if (1) they presented with a sinus tract or open wound in communication with the implant; or (2) purulence was encountered intraoperatively; or (3) two out of three tissue cultures tested positive for the presence of the same pathogen. Tissue culture and swab PCR results from the subjects were used to calculate the sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and area under the ROC curve (AUC) for identifying an orthopaedic implant-related infection. Orthopaedic implant-related infections were detected in 51 subjects. Tissue culture identified infections in 47 cases, and swab PCR in 35 cases. Among the 11 aseptic cases, tissue culture was positive in 2 cases and swab PCR in 4 cases. Tissue culture showed a significantly higher area under the ROC curve for diagnosing infection (AUC=0.89; 95% CI, 0.67-0.96) compared to swab PCR (AUC=0.66; 95% CI, 0.46-0.80) (p=0.033). Compared to swab PCR, tissue culture showed better performance for diagnosing orthopaedic implant-related infection. Although molecular methods are expected to yield higher diagnostic accuracy than cultures, it appears that the method of obtaining specimens plays an important role. Improved methods of specimen collection are required before swab PCR can become a reliable alternative to tissue-consumptive methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fuzzy decision analysis for integrated environmental vulnerability assessment of the mid-Atlantic Region.

PubMed

Tran, Liem T; Knight, C Gregory; O'Neill, Robert V; Smith, Elizabeth R; Riitters, Kurt H; Wickham, James

2002-06-01

A fuzzy decision analysis method for integrating ecological indicators was developed. This was a combination of a fuzzy ranking method and the analytic hierarchy process (AHP). The method was capable of ranking ecosystems in terms of environmental conditions and suggesting cumulative impacts across a large region. Using data on land cover, population, roads, streams, air pollution, and topography of the Mid-Atlantic region, we were able to point out areas that were in relatively poor condition and/or vulnerable to future deterioration. The method offered an easy and comprehensive way to combine the strengths of fuzzy set theory and the AHP for ecological assessment. Furthermore, the suggested method can serve as a building block for the evaluation of environmental policies.

Ion mobility analysis of lipoproteins

DOEpatents

Benner, W Henry [Danville, CA; Krauss, Ronald M [Berkeley, CA; Blanche, Patricia J [Berkeley, CA

2007-08-21

A medical diagnostic method and instrumentation system for analyzing noncovalently bonded agglomerated biological particles is described. The method and system comprises: a method of preparation for the biological particles; an electrospray generator; an alpha particle radiation source; a differential mobility analyzer; a particle counter; and data acquisition and analysis means. The medical device is useful for the assessment of human diseases, such as cardiac disease risk and hyperlipidemia, by rapid quantitative analysis of lipoprotein fraction densities. Initially, purification procedures are described to reduce an initial blood sample to an analytical input to the instrument. The measured sizes from the analytical sample are correlated with densities, resulting in a spectrum of lipoprotein densities. The lipoprotein density distribution can then be used to characterize cardiac and other lipid-related health risks.

Acoustics based assessment of respiratory diseases using GMM classification.

PubMed

Mayorga, P; Druzgalski, C; Morelos, R L; Gonzalez, O H; Vidales, J

2010-01-01

The focus of this paper is to present a method utilizing lung sounds for a quantitative assessment of patient health as it relates to respiratory disorders. In order to accomplish this, applicable traditional techniques within the speech processing domain were utilized to evaluate lung sounds obtained with a digital stethoscope. Traditional methods utilized in the evaluation of asthma involve auscultation and spirometry, but utilization of more sensitive electronic stethoscopes, which are currently available, and application of quantitative signal analysis methods offer opportunities of improved diagnosis. In particular we propose an acoustic evaluation methodology based on the Gaussian Mixed Models (GMM) which should assist in broader analysis, identification, and diagnosis of asthma based on the frequency domain analysis of wheezing and crackles.

EnvironmentalWaveletTool: Continuous and discrete wavelet analysis and filtering for environmental time series

NASA Astrophysics Data System (ADS)

Galiana-Merino, J. J.; Pla, C.; Fernandez-Cortes, A.; Cuezva, S.; Ortiz, J.; Benavente, D.

2014-10-01

A MATLAB-based computer code has been developed for the simultaneous wavelet analysis and filtering of several environmental time series, particularly focused on the analyses of cave monitoring data. The continuous wavelet transform, the discrete wavelet transform and the discrete wavelet packet transform have been implemented to provide a fast and precise time-period examination of the time series at different period bands. Moreover, statistic methods to examine the relation between two signals have been included. Finally, the entropy of curves and splines based methods have also been developed for segmenting and modeling the analyzed time series. All these methods together provide a user-friendly and fast program for the environmental signal analysis, with useful, practical and understandable results.

Cluster analysis of European Y-chromosomal STR haplotypes using the discrete Laplace method.

PubMed

Andersen, Mikkel Meyer; Eriksen, Poul Svante; Morling, Niels

2014-07-01

The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models the probability distribution of the Y-STR haplotypes. Creating a consistent statistical model of the haplotypes enables us to perform a wide range of analyses. Previously, haplotype frequency estimation using the discrete Laplace method has been validated. In this paper we investigate how the discrete Laplace method can be used for cluster analysis to further validate the discrete Laplace method. A very important practical fact is that the calculations can be performed on a normal computer. We identified two sub-clusters of the Eastern and Western European Y-STR haplotypes similar to results of previous studies. We also compared pairwise distances (between geographically separated samples) with those obtained using the AMOVA method and found good agreement. Further analyses that are impossible with AMOVA were made using the discrete Laplace method: analysis of the homogeneity in two different ways and calculating marginal STR distributions. We found that the Y-STR haplotypes from e.g. Finland were relatively homogeneous as opposed to the relatively heterogeneous Y-STR haplotypes from e.g. Lublin, Eastern Poland and Berlin, Germany. We demonstrated that the observed distributions of alleles at each locus were similar to the expected ones. We also compared pairwise distances between geographically separated samples from Africa with those obtained using the AMOVA method and found good agreement. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Identification, characterization, synthesis and HPLC quantification of new process-related impurities and degradation products in retigabine.

PubMed

Douša, Michal; Srbek, Jan; Rádl, Stanislav; Cerný, Josef; Klecán, Ondřej; Havlíček, Jaroslav; Tkadlecová, Marcela; Pekárek, Tomáš; Gibala, Petr; Nováková, Lucie

2014-06-01

Two new impurities were described and determined using gradient HPLC method with UV detection in retigabine (RET). Using LC-HRMS, NMR and IR analysis the impurities were identified as RET-dimer I: diethyl {4,4'-diamino-6,6'-bis[(4-fluorobenzyl)amino]biphenyl-3,3'-diyl}biscarbamate and RET-dimer II: ethyl {2-amino-5-[{2-amino-4-[(4-fluorobenzyl) amino] phenyl} (ethoxycarbonyl) amino]-4-[(4-fluorobenzyl)amino] phenyl}carbamate. Reference standards of these impurities were synthesized followed by semipreparative HPLC purification. The mechanism of the formation of these impurities is also discussed. An HPLC method was optimized in order to separate, selectively detect and quantify all process-related impurities and degradation products of RET. The presented method, which was validated in terms of linearity, limit of detection (LOD), limit of quantification (LOQ) and selectivity is very quick (less than 11min including re-equilibration time) and therefore highly suitable for routine analysis of RET related substances as well as stability studies. Copyright © 2014 Elsevier B.V. All rights reserved.

Characterization of the Mechanical Stress-Strain Performance of Aerospace Alloy Materials Using Frequency-Domain Photoacoustic Ultrasound and Photothermal Methods: An FEM Approach

NASA Astrophysics Data System (ADS)

Huan, Huiting; Mandelis, Andreas; Liu, Lixian

2018-04-01

Determining and keeping track of a material's mechanical performance is very important for safety in the aerospace industry. The mechanical strength of alloy materials is precisely quantified in terms of its stress-strain relation. It has been proven that frequency-domain photothermoacoustic (FD-PTA) techniques are effective methods for characterizing the stress-strain relation of metallic alloys. PTA methodologies include photothermal (PT) diffusion and laser thermoelastic photoacoustic ultrasound (PAUS) generation which must be separately discussed because the relevant frequency ranges and signal detection principles are widely different. In this paper, a detailed theoretical analysis of the connection between thermoelastic parameters and stress/strain tensor is presented with respect to FD-PTA nondestructive testing. Based on the theoretical model, a finite element method (FEM) was further implemented to simulate the PT and PAUS signals at very different frequency ranges as an important analysis tool of experimental data. The change in the stress-strain relation has an impact on both thermal and elastic properties, verified by FEM and results/signals from both PT and PAUS experiments.

Evaluation of quantification methods for real-time PCR minor groove binding hybridization probe assays.

PubMed

Durtschi, Jacob D; Stevenson, Jeffery; Hymas, Weston; Voelkerding, Karl V

2007-02-01

Real-time PCR data analysis for quantification has been the subject of many studies aimed at the identification of new and improved quantification methods. Several analysis methods have been proposed as superior alternatives to the common variations of the threshold crossing method. Notably, sigmoidal and exponential curve fit methods have been proposed. However, these studies have primarily analyzed real-time PCR with intercalating dyes such as SYBR Green. Clinical real-time PCR assays, in contrast, often employ fluorescent probes whose real-time amplification fluorescence curves differ from those of intercalating dyes. In the current study, we compared four analysis methods related to recent literature: two versions of the threshold crossing method, a second derivative maximum method, and a sigmoidal curve fit method. These methods were applied to a clinically relevant real-time human herpes virus type 6 (HHV6) PCR assay that used a minor groove binding (MGB) Eclipse hybridization probe as well as an Epstein-Barr virus (EBV) PCR assay that used an MGB Pleiades hybridization probe. We found that the crossing threshold method yielded more precise results when analyzing the HHV6 assay, which was characterized by lower signal/noise and less developed amplification curve plateaus. In contrast, the EBV assay, characterized by greater signal/noise and amplification curves with plateau regions similar to those observed with intercalating dyes, gave results with statistically similar precision by all four analysis methods.

Chosen aspects of multi-criteria analysis applied to support the choice of materials for building structures

NASA Astrophysics Data System (ADS)

Szafranko, E.

2017-08-01

When planning a building structure, dilemmas arise as to what construction and material solutions are feasible. The decisions are not always obvious. A procedure for selecting the variant that will best satisfy the expectations of the investor and future users of a structure must be founded on mathematical methods. The following deserve special attention: the MCE methods, Hierarchical Analysis Methods and Weighting Methods. Another interesting solution, particularly useful when dealing with evaluations which take into account negative values, is the Indicator Method. MCE methods are relatively popular owing to the simplicity of the calculations and ease of the interpretation of the results. Having prepared the input data properly, they enable the user to compare them on the same level. In a situation where an analysis involves a large number of data, it is more convenient to divide them into groups according to main criteria and subcriteria. This option is provided by hierarchical analysis methods. They are based on ordered sets of criteria, which are evaluated in groups. In some cases, this approach yields the results that are superior and easier to read. If an analysis encompasses direct and indirect effects, an Indicator Method seems to be a justified choice for selecting the right solution. The Indicator Method is different in character and relies on weights and assessments of effects. It allows the user to evaluate effectively the analyzed variants. This article explains the methodology of conducting a multi-criteria analysis, showing its advantages and disadvantages. An example of calculations contained in the article shows what problems can be encountered when making an assessment of various solutions regarding building materials and structures. For comparison, an analysis based on graphical methods developed by the author was presented.

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

Valuing vaccines using value of statistical life measures.

PubMed

Laxminarayan, Ramanan; Jamison, Dean T; Krupnick, Alan J; Norheim, Ole F

2014-09-03

Vaccines are effective tools to improve human health, but resources to pursue all vaccine-related investments are lacking. Benefit-cost and cost-effectiveness analysis are the two major methodological approaches used to assess the impact, efficiency, and distributional consequences of disease interventions, including those related to vaccinations. Childhood vaccinations can have important non-health consequences for productivity and economic well-being through multiple channels, including school attendance, physical growth, and cognitive ability. Benefit-cost analysis would capture such non-health benefits; cost-effectiveness analysis does not. Standard cost-effectiveness analysis may grossly underestimate the benefits of vaccines. A specific willingness-to-pay measure is based on the notion of the value of a statistical life (VSL), derived from trade-offs people are willing to make between fatality risk and wealth. Such methods have been used widely in the environmental and health literature to capture the broader economic benefits of improving health, but reservations remain about their acceptability. These reservations remain mainly because the methods may reflect ability to pay, and hence be discriminatory against the poor. However, willingness-to-pay methods can be made sensitive to income distribution by using appropriate income-sensitive distributional weights. Here, we describe the pros and cons of these methods and how they compare against standard cost-effectiveness analysis using pure health metrics, such as quality-adjusted life years (QALYs) and disability-adjusted life years (DALYs), in the context of vaccine priorities. We conclude that if appropriately used, willingness-to-pay methods will not discriminate against the poor, and they can capture important non-health benefits such as financial risk protection, productivity gains, and economic wellbeing. Copyright © 2014 Elsevier Ltd. All rights reserved.

Molecular analysis of microflora associated with dentoalveolar abscesses.

PubMed Central

Dymock, D; Weightman, A J; Scully, C; Wade, W G

1996-01-01

The microflora associated with three dentoalveolar abscesses was determined by cultural and molecular methods. 16S rRNA genes were randomly amplified by means of conserved eubacterial primers and cloned. Restriction fragment length polymorphism analysis of the clones and amplified genes encoding 16S rRNA from the cultured bacteria was used to detect putative unculturable bacteria. Clones representative of five predominant groups of uncultured organisms were sequenced. Two were identified as Porphyromonas gingivalis and Prevotella oris, and one was found to be closely related to Peptostreptococcus micros. The remaining two clones did not correspond to known, previously sequenced organisms. One was related to Zoogloea ramigera, a species of aerobic waterborne organisms, while the other was distantly related to the genus Prevotella. This study has demonstrated the possibility of the characterization of microflora associated with human infection by molecular methods without the inherent biases of culture. PMID:8904410

Narrative review: Diabetic foot and infrared thermography

NASA Astrophysics Data System (ADS)

Hernandez-Contreras, D.; Peregrina-Barreto, H.; Rangel-Magdaleno, J.; Gonzalez-Bernal, J.

2016-09-01

Diabetic foot is one of the major complications experienced by diabetic patients. An early identification and appropriate treatment of diabetic foot problems can prevent devastating consequences such as limb amputation. Several studies have demonstrated that temperature variations in the plantar region can be related to diabetic foot problems. Infrared thermography has been successfully used to detect complication related to diabetic foot, mainly because it is presented as a rapid, non-contact and non-invasive technique to visualize the temperature distribution of the feet. In this review, an overview of studies that relate foot temperature with diabetic foot problems through infrared thermography is presented. Through this research, it can be appreciated the potential of infrared thermography and the benefits that this technique present in this application. This paper also presents the different methods for thermogram analysis and the advantages and disadvantages of each one, being the asymmetric analysis the method most used so far.

Trophic hierarchies revealed via amino acid isotopic analysis

USDA-ARS?s Scientific Manuscript database

Despite the potential of isotopic methods to illuminate trophic function, accurate estimates of lifetime feeding tendencies have remained elusive. A relatively new approach—referred to as compound-specific isotopic analysis (CSIA)—has emerged, centering on the measurement of 15N:14N ratios in amino ...

AVOIDING HYDROLYSIS OF FUEL ETHER OXYGENATES DURING STATIC HEADSPACE ANALYSIS

EPA Science Inventory

A headspace autosampler, gas chromatograph and ion trap mass spectrometer (headspace GC/MS) were used for trace analysis of fuel oxygenates and related compounds and aromatics in water. A method has been developed for determination of methyl tert-butyl ether (MTBE), ethyl tert-b...

Detecting evidence of luteal activity by least-squares quantitative basal temperature analysis against urinary progesterone metabolites and the effect of wake-time variability.

PubMed

Bedford, Jennifer L; Prior, Jerilynn C; Hitchcock, Christine L; Barr, Susan I

2009-09-01

To assess computerised least-squares analysis of quantitative basal temperature (LS-BT) against urinary pregnanediol glucuronide (PdG) as an indirect measure of ovulation, and to evaluate the stability of LS-QBT to wake-time variation. Cross-sectional study of 40 healthy, normal-weight, regularly menstruating women aged 19-34. Participants recorded basal temperature and collected first void urine daily for one complete menstrual cycle. Evidence of luteal activity (ELA), an indirect ovulation indicator, was assessed using Kassam's PdG algorithm, which identifies a sustained 3-day PdG rise, and the LS-QBT algorithm, by determining whether the temperature curve is significantly biphasic. Cycles were classified as ELA(+) or ELA(-). We explored the need to pre-screen for wake-time variations by repeating the analysis using: (A) all recorded temperatures, (B) wake-time adjusted temperatures, (C) temperatures within 2h of average wake-time, and (D) expert reviewed temperatures. Relative to PdG, classification of cycles as ELA(+) was 35 of 36 for LS-QBT methods A and B, 33 of 34 (method C) and 30 of 31 (method D). Classification of cycles as ELA(-) was 1 of 4 (methods A and B) and 0 of 3 (methods C and D). Positive predictive value was 92% for methods A-C and 91% for method D. Negative predictive value was 50% for methods A and B and 0% for methods C and D. Overall accuracy was 90% for methods A and B, 89% for method C and 88% for method D. The day of a significant temperature increase by LS-QBT and the first day of a sustained PdG rise were correlated (r=0.803, 0.741, 0.651, 0.747 for methods A-D, respectively, all p<0.001). LS-QBT showed excellent detection of ELA(+) cycles (sensitivity, positive predictive value) but poor detection of ELA(-) cycles (specificity, negative predictive value) relative to urinary PdG. Correlations between the methods and overall accuracy were good and similar for all analyses. Findings suggest that LS-QBT is robust to wake-time variability and that expert interpretation is unnecessary. This method shows promise for use as an epidemiological tool to document cyclic progesterone increase. Further validation relative to daily transvaginal ultrasound is required.

System and method for high precision isotope ratio destructive analysis

DOEpatents

Bushaw, Bruce A; Anheier, Norman C; Phillips, Jon R

2013-07-02

A system and process are disclosed that provide high accuracy and high precision destructive analysis measurements for isotope ratio determination of relative isotope abundance distributions in liquids, solids, and particulate samples. The invention utilizes a collinear probe beam to interrogate a laser ablated plume. This invention provides enhanced single-shot detection sensitivity approaching the femtogram range, and isotope ratios that can be determined at approximately 1% or better precision and accuracy (relative standard deviation).

Concept Analysis: Alzheimer’s Caregiver Stress

PubMed Central

Llanque, Sarah; Savage, Lynette; Rosenburg, Neal; Honor’s, BA; Caserta, Michael

2015-01-01

AIM The aim of this article was to analyze the concept of caregiver stress in the context of caring for a person with Alzheimer’s disease and related dementias. BACKGROUND Currently, there are more than 15 million unpaid care-givers for persons suffering from Alzheimer’s disease and related dementias. This unpaid care can be stressful for caregivers due to the chronic nature of the disease process, as well as other factors. METHOD The paper incorporates the modified method of Wilson’s concept analysis procedure to analyze the concept of caregiver stress. DATA SOURCES A review of the literature was undertaken using the Cumulative Index to Nursing and Allied Health Literature, Google Scholar, and PubMed. RESULTS A theoretical definition of caregiver stress is provided, and the defining attributes, related concepts, antecedents, and consequences of caregiver stress are proposed, and case studies are presented. CONCLUSIONS The analysis demonstrates that caregiver stress is the unequal exchange of assistance among people who stand in close relationship to one another, which results in emotional and physical stress on the caregiver. Implications for future nursing research and practice conclude the paper. PMID:24787468

Sleep Duration and Waist Circumference in Adults: A Meta-Analysis

PubMed Central

Sperry, Susan D.; Scully, Iiona D.; Gramzow, Richard H.; Jorgensen, Randall S.

2015-01-01

Background: Previous research has demonstrated a relation between insufficient sleep and overall obesity. Waist circumference (WC), a measure of central adiposity, has been demonstrated to improve prediction of health risk. However, recent research on the relation of insufficient sleep duration to WC in adults has yielded inconsistent findings. Objectives: To assess the magnitude and the consistency of the relation of insufficient sleep and WC Methods: A systematic search of Internet and research databases using Google Scholar, Medline, PubMed, and PsycINFO through July 2013 was conducted. All articles in English with adult human subjects that included measurements of WC and sleep duration were reviewed. A random effects meta-analysis and regression analyses were performed. Heterogeneity and publication bias were checked. Results are expressed as Pearson correlations (r; 95% confidence interval). Results: Of 1,376 articles, 30 met inclusion criteria and 21 studies (22 samples for a total of 56,259 participants) provided sufficient data for meta-analysis. Results showed a significant negative relation between sleep duration and WC (r = −0.10, P < 0.0001) with significant heterogeneity related to sleep comparison method. Potential moderators of the relation between sleep duration and WC were not significant. Funnel plots showed no indication of publication bias. In addition, a fail-safe N calculation indicated that 418 studies with null effects would be necessary to bring the overall mean effect size to a trivial value of r = −0.005. Conclusions: Internationally, cross-sectional studies demonstrate a significant negative relation between sleep duration and waist circumference, indicating shorter sleep durations covary with central adiposity. Future research should include prospective studies. Citation: Sperry SD, Scully ID, Gramzow RH, Jorgensen RS. Sleep duration and waist circumference in adults: a meta-analysis. SLEEP 2015;38(8):1269–1276. PMID:25581918

Machine Learning–Based Differential Network Analysis: A Study of Stress-Responsive Transcriptomes in Arabidopsis[W

PubMed Central

Ma, Chuang; Xin, Mingming; Feldmann, Kenneth A.; Wang, Xiangfeng

2014-01-01

Machine learning (ML) is an intelligent data mining technique that builds a prediction model based on the learning of prior knowledge to recognize patterns in large-scale data sets. We present an ML-based methodology for transcriptome analysis via comparison of gene coexpression networks, implemented as an R package called machine learning–based differential network analysis (mlDNA) and apply this method to reanalyze a set of abiotic stress expression data in Arabidopsis thaliana. The mlDNA first used a ML-based filtering process to remove nonexpressed, constitutively expressed, or non-stress-responsive “noninformative” genes prior to network construction, through learning the patterns of 32 expression characteristics of known stress-related genes. The retained “informative” genes were subsequently analyzed by ML-based network comparison to predict candidate stress-related genes showing expression and network differences between control and stress networks, based on 33 network topological characteristics. Comparative evaluation of the network-centric and gene-centric analytic methods showed that mlDNA substantially outperformed traditional statistical testing–based differential expression analysis at identifying stress-related genes, with markedly improved prediction accuracy. To experimentally validate the mlDNA predictions, we selected 89 candidates out of the 1784 predicted salt stress–related genes with available SALK T-DNA mutagenesis lines for phenotypic screening and identified two previously unreported genes, mutants of which showed salt-sensitive phenotypes. PMID:24520154

Scenario-Based Case Study Method and the Functionality of the Section Called "From Production to Consumption" from the Perspective of Primary School Students

ERIC Educational Resources Information Center

Taneri, Ahu

2018-01-01

In this research, the aim was showing the evaluation of students on scenario-based case study method and showing the functionality of the studied section called "from production to consumption". Qualitative research method and content analysis were used to reveal participants' experiences and reveal meaningful relations regarding…

An Analysis of Prospective Chemistry Teachers' Cognitive Structures through Flow Map Method: The Subject of Oxidation and Reduction

ERIC Educational Resources Information Center

Temel, Senar

2016-01-01

This study aims to analyse prospective chemistry teachers' cognitive structures related to the subject of oxidation and reduction through a flow map method. Purposeful sampling method was employed in this study, and 8 prospective chemistry teachers from a group of students who had taken general chemistry and analytical chemistry courses were…

Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways

PubMed Central

2013-01-01

Background Analysis of global gene expression by DNA microarrays is widely used in experimental molecular biology. However, the complexity of such high-dimensional data sets makes it difficult to fully understand the underlying biological features present in the data. The aim of this study is to introduce a method for DNA microarray analysis that provides an intuitive interpretation of data through dimension reduction and pattern recognition. We present the first “Archetypal Analysis” of global gene expression. The analysis is based on microarray data from five integrated studies of Pseudomonas aeruginosa isolated from the airways of cystic fibrosis patients. Results Our analysis clustered samples into distinct groups with comprehensible characteristics since the archetypes representing the individual groups are closely related to samples present in the data set. Significant changes in gene expression between different groups identified adaptive changes of the bacteria residing in the cystic fibrosis lung. The analysis suggests a similar gene expression pattern between isolates with a high mutation rate (hypermutators) despite accumulation of different mutations for these isolates. This suggests positive selection in the cystic fibrosis lung environment, and changes in gene expression for these isolates are therefore most likely related to adaptation of the bacteria. Conclusions Archetypal analysis succeeded in identifying adaptive changes of P. aeruginosa. The combination of clustering and matrix factorization made it possible to reveal minor similarities among different groups of data, which other analytical methods failed to identify. We suggest that this analysis could be used to supplement current methods used to analyze DNA microarray data. PMID:24059747

Generalized fourier analyses of the advection-diffusion equation - Part II: two-dimensional domains

NASA Astrophysics Data System (ADS)

Voth, Thomas E.; Martinez, Mario J.; Christon, Mark A.

2004-07-01

Part I of this work presents a detailed multi-methods comparison of the spatial errors associated with the one-dimensional finite difference, finite element and finite volume semi-discretizations of the scalar advection-diffusion equation. In Part II we extend the analysis to two-dimensional domains and also consider the effects of wave propagation direction and grid aspect ratio on the phase speed, and the discrete and artificial diffusivities. The observed dependence of dispersive and diffusive behaviour on propagation direction makes comparison of methods more difficult relative to the one-dimensional results. For this reason, integrated (over propagation direction and wave number) error and anisotropy metrics are introduced to facilitate comparison among the various methods. With respect to these metrics, the consistent mass Galerkin and consistent mass control-volume finite element methods, and their streamline upwind derivatives, exhibit comparable accuracy, and generally out-perform their lumped mass counterparts and finite-difference based schemes. While this work can only be considered a first step in a comprehensive multi-methods analysis and comparison, it serves to identify some of the relative strengths and weaknesses of multiple numerical methods in a common mathematical framework. Published in 2004 by John Wiley & Sons, Ltd.

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory

PubMed Central

Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM. PMID:29391864

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.

PubMed

Yang, Haimin; Pan, Zhisong; Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

Laboratory theory and methods for sediment analysis

USGS Publications Warehouse

Guy, Harold P.

1969-01-01

The diverse character of fluvial sediments makes the choice of laboratory analysis somewhat arbitrary and the pressing of sediment samples difficult. This report presents some theories and methods used by the Water Resources Division for analysis of fluvial sediments to determine the concentration of suspended-sediment samples and the particle-size distribution of both suspended-sediment and bed-material samples. Other analyses related to these determinations may include particle shape, mineral content, and specific gravity, the organic matter and dissolved solids of samples, and the specific weight of soils. The merits and techniques of both the evaporation and filtration methods for concentration analysis are discussed. Methods used for particle-size analysis of suspended-sediment samples may include the sieve pipet, the VA tube-pipet, or the BW tube-VA tube depending on the equipment available, the concentration and approximate size of sediment in the sample, and the settling medium used. The choice of method for most bed-material samples is usually limited to procedures suitable for sand or to some type of visual analysis for large sizes. Several tested forms are presented to help insure a well-ordered system in the laboratory to handle the samples, to help determine the kind of analysis required for each, to conduct the required processes, and to assist in the required computations. Use of the manual should further 'standardize' methods of fluvial sediment analysis among the many laboratories and thereby help to achieve uniformity and precision of the data.

Understanding the context of healthcare utilization: assessing environmental and provider-related variables in the behavioral model of utilization.

PubMed Central

Phillips, K A; Morrison, K R; Andersen, R; Aday, L A

1998-01-01

OBJECTIVE: The behavioral model of utilization, developed by Andersen, Aday, and others, is one of the most frequently used frameworks for analyzing the factors that are associated with patient utilization of healthcare services. However, the use of the model for examining the context within which utilization occurs-the role of the environment and provider-related factors-has been largely neglected. OBJECTIVE: To conduct a systematic review and analysis to determine if studies of medical care utilization that have used the behavioral model during the last 20 years have included environmental and provider-related variables and the methods used to analyze these variables. We discuss barriers to the use of these contextual variables and potential solutions. DATA SOURCES: The Social Science Citation Index and Science Citation Index. We included all articles from 1975-1995 that cited any of three key articles on the behavioral model, that included all articles that were empirical analyses and studies of formal medical care utilization, and articles that specifically stated their use of the behavioral model (n = 139). STUDY DESIGN: Design was a systematic literature review. DATA ANALYSIS: We used a structured review process to code articles on whether they included contextual variables: (1) environmental variables (characteristics of the healthcare delivery system, external environment, and community-level enabling factors); and (2) provider-related variables (patient factors that may be influenced by providers and provider characteristics that interact with patient characteristics to influence utilization). We also examined the methods used in studies that included contextual variables. PRINCIPAL FINDINGS: Forty-five percent of the studies included environmental variables and 51 percent included provider-related variables. Few studies examined specific measures of the healthcare system or provider characteristics or used methods other than simple regression analysis with hierarchical entry of variables. Only 14 percent of studies analyzed the context of healthcare by including both environmental and provider-related variables as well as using relevant methods. CONCLUSIONS: By assessing whether and how contextual variables are used, we are able to highlight the contributions made by studies using these approaches, to identify variables and methods that have been relatively underused, and to suggest solutions to barriers in using contextual variables. PMID:9685123

Research on the spatial analysis method of seismic hazard for island

NASA Astrophysics Data System (ADS)

Jia, Jing; Jiang, Jitong; Zheng, Qiuhong; Gao, Huiying

2017-05-01

Seismic hazard analysis(SHA) is a key component of earthquake disaster prevention field for island engineering, whose result could provide parameters for seismic design microscopically and also is the requisite work for the island conservation planning’s earthquake and comprehensive disaster prevention planning macroscopically, in the exploitation and construction process of both inhabited and uninhabited islands. The existing seismic hazard analysis methods are compared in their application, and their application and limitation for island is analysed. Then a specialized spatial analysis method of seismic hazard for island (SAMSHI) is given to support the further related work of earthquake disaster prevention planning, based on spatial analysis tools in GIS and fuzzy comprehensive evaluation model. The basic spatial database of SAMSHI includes faults data, historical earthquake record data, geological data and Bouguer gravity anomalies data, which are the data sources for the 11 indices of the fuzzy comprehensive evaluation model, and these indices are calculated by the spatial analysis model constructed in ArcGIS’s Model Builder platform.

Fingerprint analysis of polysaccharides from different Ganoderma by HPLC combined with chemometrics methods.

PubMed

Sun, Xiaomei; Wang, Haohao; Han, Xiaofeng; Chen, Shangwei; Zhu, Song; Dai, Jun

2014-12-19

A fingerprint analysis method has been developed for characterization and discrimination of polysaccharides from different Ganoderma by high performance liquid chromatography (HPLC) coupled with chemometrics means. The polysaccharides were extracted under ultrasonic-assisted condition, and then partly hydrolyzed with trifluoroacetic acid. Monosaccharides and oligosaccharides in the hydrolyzates were subjected to pre-column derivatization with 1-phenyl-3-methyl-5-pyrazolone and HPLC analysis, which will generate unique fingerprint information related to chemical composition and structure of polysaccharides. The peak data were imported to professional software in order to obtain standard fingerprint profiles and evaluate similarity of different samples. Meanwhile, the data were further processed by hierarchical cluster analysis and principal component analysis. Polysaccharides from different parts or species of Ganoderma or polysaccharides from the same parts of Ganoderma but from different geographical regions or different strains could be differentiated clearly. This fingerprint analysis method can be applied to identification and quality control of different Ganoderma and their products. Copyright © 2014 Elsevier Ltd. All rights reserved.

A symmetrical method to obtain shear moduli from microrheology.

PubMed

Nishi, Kengo; Kilfoil, Maria L; Schmidt, Christoph F; MacKintosh, F C

2018-05-16

Passive microrheology typically deduces shear elastic loss and storage moduli from displacement time series or mean-squared displacements (MSD) of thermally fluctuating probe particles in equilibrium materials. Common data analysis methods use either Kramers-Kronig (KK) transformation or functional fitting to calculate frequency-dependent loss and storage moduli. We propose a new analysis method for passive microrheology that avoids the limitations of both of these approaches. In this method, we determine both real and imaginary components of the complex, frequency-dependent response function χ(ω) = χ'(ω) + iχ''(ω) as direct integral transforms of the MSD of thermal particle motion. This procedure significantly improves the high-frequency fidelity of χ(ω) relative to the use of KK transformation, which has been shown to lead to artifacts in χ'(ω). We test our method on both model and experimental data. Experiments were performed on solutions of worm-like micelles and dilute collagen solutions. While the present method agrees well with established KK-based methods at low frequencies, we demonstrate significant improvement at high frequencies using our symmetric analysis method, up to almost the fundamental Nyquist limit.

A thioacidolysis method tailored for higher‐throughput quantitative analysis of lignin monomers

PubMed Central

Foster, Cliff; Happs, Renee M.; Doeppke, Crissa; Meunier, Kristoffer; Gehan, Jackson; Yue, Fengxia; Lu, Fachuang; Davis, Mark F.

2016-01-01

Abstract Thioacidolysis is a method used to measure the relative content of lignin monomers bound by β‐O‐4 linkages. Current thioacidolysis methods are low‐throughput as they require tedious steps for reaction product concentration prior to analysis using standard GC methods. A quantitative thioacidolysis method that is accessible with general laboratory equipment and uses a non‐chlorinated organic solvent and is tailored for higher‐throughput analysis is reported. The method utilizes lignin arylglycerol monomer standards for calibration, requires 1–2 mg of biomass per assay and has been quantified using fast‐GC techniques including a Low Thermal Mass Modular Accelerated Column Heater (LTM MACH). Cumbersome steps, including standard purification, sample concentrating and drying have been eliminated to help aid in consecutive day‐to‐day analyses needed to sustain a high sample throughput for large screening experiments without the loss of quantitation accuracy. The method reported in this manuscript has been quantitatively validated against a commonly used thioacidolysis method and across two different research sites with three common biomass varieties to represent hardwoods, softwoods, and grasses. PMID:27534715

A thioacidolysis method tailored for higher-throughput quantitative analysis of lignin monomers

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

Harman-Ware, Anne E.; Foster, Cliff; Happs, Renee M.

Thioacidolysis is a method used to measure the relative content of lignin monomers bound by β-O-4 linkages. Current thioacidolysis methods are low-throughput as they require tedious steps for reaction product concentration prior to analysis using standard GC methods. A quantitative thioacidolysis method that is accessible with general laboratory equipment and uses a non-chlorinated organic solvent and is tailored for higher-throughput analysis is reported. The method utilizes lignin arylglycerol monomer standards for calibration, requires 1-2 mg of biomass per assay and has been quantified using fast-GC techniques including a Low Thermal Mass Modular Accelerated Column Heater (LTM MACH). Cumbersome steps, includingmore » standard purification, sample concentrating and drying have been eliminated to help aid in consecutive day-to-day analyses needed to sustain a high sample throughput for large screening experiments without the loss of quantitation accuracy. As a result, the method reported in this manuscript has been quantitatively validated against a commonly used thioacidolysis method and across two different research sites with three common biomass varieties to represent hardwoods, softwoods, and grasses.« less

A thioacidolysis method tailored for higher-throughput quantitative analysis of lignin monomers

DOE PAGES

Harman-Ware, Anne E.; Foster, Cliff; Happs, Renee M.; ...

2016-09-14

Thioacidolysis is a method used to measure the relative content of lignin monomers bound by β-O-4 linkages. Current thioacidolysis methods are low-throughput as they require tedious steps for reaction product concentration prior to analysis using standard GC methods. A quantitative thioacidolysis method that is accessible with general laboratory equipment and uses a non-chlorinated organic solvent and is tailored for higher-throughput analysis is reported. The method utilizes lignin arylglycerol monomer standards for calibration, requires 1-2 mg of biomass per assay and has been quantified using fast-GC techniques including a Low Thermal Mass Modular Accelerated Column Heater (LTM MACH). Cumbersome steps, includingmore » standard purification, sample concentrating and drying have been eliminated to help aid in consecutive day-to-day analyses needed to sustain a high sample throughput for large screening experiments without the loss of quantitation accuracy. As a result, the method reported in this manuscript has been quantitatively validated against a commonly used thioacidolysis method and across two different research sites with three common biomass varieties to represent hardwoods, softwoods, and grasses.« less

Analysis of heparin oligosaccharides by capillary electrophoresis-negative-ion electrospray ionization mass spectrometry.

PubMed

Lin, Lei; Liu, Xinyue; Zhang, Fuming; Chi, Lianli; Amster, I Jonathan; Leach, Franklyn E; Xia, Qiangwei; Linhardt, Robert J

2017-01-01

Most hyphenated analytical approaches that rely on liquid chromatography-MS require relatively long separation times, produce incomplete resolution of oligosaccharide mixtures, use eluents that are incompatible with electrospray ionization, or require oligosaccharide derivatization. Here we demonstrate the analysis of heparin oligosaccharides, including disaccharides, ultralow molecular weight heparin, and a low molecular weight heparin, using a novel electrokinetic pump-based CE-MS coupling eletrospray ion source. Reverse polarity CE separation and negative-mode electrospray ionization were optimized using a volatile methanolic ammonium acetate electrolyte and sheath fluid. The online CE hyphenated negative-ion electrospray ionization MS on an LTQ Orbitrap mass spectrometer was useful in disaccharide compositional analysis and bottom-up and top-down analysis of low molecular weight heparin. The application of this CE-MS method to ultralow molecular heparin suggests that a charge state distribution and the low level of sulfate group loss that is achieved make this method useful for online tandem MS analysis of heparins. Graphical abstract Most hyphenated analytical approaches that rely on liquid chromatography-MS require relatively long separation times, produce incomplete resolution of oligosaccharide mixtures, use eluents that are incompatible with electrospray ionization, or require oligosaccharide derivatization. Here we demonstrate the analysis of heparin oligosaccharides, including disaccharides, ultralow molecular weight heparin, and a low molecular weight heparin, using a novel electrokinetic pump-based CE-MS coupling eletrospray ion source. Reverse polarity CE separation and negative-mode electrospray ionization were optimized using a volatile methanolic ammonium acetate electrolyte and sheath fluid. The online CE hyphenated negative-ion electrospray ionization MS on an LTQ Orbitrap mass spectrometer was useful in disaccharide compositional analysis and bottom-up and top-down analysis of low molecular weight heparin. The application of this CE-MS method to ultralow molecular heparin suggests that a charge state distribution and the low level of sulfate group loss that is achieved make this method useful for online tandem MS analysis of heparins.

Developing techniques for cause-responsibility analysis of occupational accidents.

PubMed

Jabbari, Mousa; Ghorbani, Roghayeh

2016-11-01

The aim of this study was to specify the causes of occupational accidents, determine social responsibility and the role of groups involved in work-related accidents. This study develops occupational accidents causes tree, occupational accidents responsibility tree, and occupational accidents component-responsibility analysis worksheet; based on these methods, it develops cause-responsibility analysis (CRA) techniques, and for testing them, analyzes 100 fatal/disabling occupational accidents in the construction setting that were randomly selected from all the work-related accidents in Tehran, Iran, over a 5-year period (2010-2014). The main result of this study involves two techniques for CRA: occupational accidents tree analysis (OATA) and occupational accidents components analysis (OACA), used in parallel for determination of responsible groups and responsibilities rate. From the results, we find that the management group of construction projects has 74.65% responsibility of work-related accidents. The developed techniques are purposeful for occupational accidents investigation/analysis, especially for the determination of detailed list of tasks, responsibilities, and their rates. Therefore, it is useful for preventing work-related accidents by focusing on the responsible group's duties. Copyright © 2016 Elsevier Ltd. All rights reserved.

Method for the Simultaneous Quantitation of Apolipoprotein E Isoforms using Tandem Mass Spectrometry

PubMed Central

Wildsmith, Kristin R.; Han, Bomie; Bateman, Randall J.

2009-01-01

Using Apolipoprotein E (ApoE) as a model protein, we developed a protein isoform analysis method utilizing Stable Isotope Labeling Tandem Mass Spectrometry (SILT MS). ApoE isoforms are quantitated using the intensities of the b and y ions of the 13C-labeled tryptic isoform-specific peptides versus unlabeled tryptic isoform-specific peptides. The ApoE protein isoform analysis using SILT allows for the simultaneous detection and relative quantitation of different ApoE isoforms from the same sample. This method provides a less biased assessment of ApoE isoforms compared to antibody-dependent methods, and may lead to a better understanding of the biological differences between isoforms. PMID:19653990

Policy Analysis: A Tool for Setting District Computer Use Policy. Paper and Report Series No. 97.

ERIC Educational Resources Information Center

Gray, Peter J.

This report explores the use of policy analysis as a tool for setting computer use policy in a school district by discussing the steps in the policy formation and implementation processes and outlining how policy analysis methods can contribute to the creation of effective policy. Factors related to the adoption and implementation of innovations…

DNA BASED METHOD OF MOLD AND APPLYING THE ENVIRONMENTAL RELATIVE MOLDINESS INDEX (ERMI)

EPA Science Inventory

NASA facilities can potentially have mold contamination problems. The EPA has created an Environmental Relative Moldiness Index based on the analysis of dust by Mold Specific Quantitative PCR (MSQPCR). In this presentation, the scientific background for the ERMI will be present...

Phylogenetic rooting using minimal ancestor deviation.

PubMed

Tria, Fernando Domingues Kümmel; Landan, Giddy; Dagan, Tal

2017-06-19

Ancestor-descendent relations play a cardinal role in evolutionary theory. Those relations are determined by rooting phylogenetic trees. Existing rooting methods are hampered by evolutionary rate heterogeneity or the unavailability of auxiliary phylogenetic information. Here we present a rooting approach, the minimal ancestor deviation (MAD) method, which accommodates heterotachy by using all pairwise topological and metric information in unrooted trees. We demonstrate the performance of the method, in comparison to existing rooting methods, by the analysis of phylogenies from eukaryotes and prokaryotes. MAD correctly recovers the known root of eukaryotes and uncovers evidence for the origin of cyanobacteria in the ocean. MAD is more robust and consistent than existing methods, provides measures of the root inference quality and is applicable to any tree with branch lengths.

Analysis of Observational Studies in the Presence of Treatment Selection Bias: Effects of Invasive Cardiac Management on AMI Survival Using Propensity Score and Instrumental Variable Methods

PubMed Central

Stukel, Thérèse A.; Fisher, Elliott S; Wennberg, David E.; Alter, David A.; Gottlieb, Daniel J.; Vermeulen, Marian J.

2007-01-01

Context Comparisons of outcomes between patients treated and untreated in observational studies may be biased due to differences in patient prognosis between groups, often because of unobserved treatment selection biases. Objective To compare 4 analytic methods for removing the effects of selection bias in observational studies: multivariable model risk adjustment, propensity score risk adjustment, propensity-based matching, and instrumental variable analysis. Design, Setting, and Patients A national cohort of 122 124 patients who were elderly (aged 65–84 years), receiving Medicare, and hospitalized with acute myocardial infarction (AMI) in 1994–1995, and who were eligible for cardiac catheterization. Baseline chart reviews were taken from the Cooperative Cardiovascular Project and linked to Medicare health administrative data to provide a rich set of prognostic variables. Patients were followed up for 7 years through December 31, 2001, to assess the association between long-term survival and cardiac catheterization within 30 days of hospital admission. Main Outcome Measure Risk-adjusted relative mortality rate using each of the analytic methods. Results Patients who received cardiac catheterization (n=73 238) were younger and had lower AMI severity than those who did not. After adjustment for prognostic factors by using standard statistical risk-adjustment methods, cardiac catheterization was associated with a 50% relative decrease in mortality (for multivariable model risk adjustment: adjusted relative risk [RR], 0.51; 95% confidence interval [CI], 0.50–0.52; for propensity score risk adjustment: adjusted RR, 0.54; 95% CI, 0.53–0.55; and for propensity-based matching: adjusted RR, 0.54; 95% CI, 0.52–0.56). Using regional catheterization rate as an instrument, instrumental variable analysis showed a 16% relative decrease in mortality (adjusted RR, 0.84; 95% CI, 0.79–0.90). The survival benefits of routine invasive care from randomized clinical trials are between 8% and 21 %. Conclusions Estimates of the observational association of cardiac catheterization with long-term AMI mortality are highly sensitive to analytic method. All standard risk-adjustment methods have the same limitations regarding removal of unmeasured treatment selection biases. Compared with standard modeling, instrumental variable analysis may produce less biased estimates of treatment effects, but is more suited to answering policy questions than specific clinical questions. PMID:17227979

High throughput reconfigurable data analysis system

NASA Technical Reports Server (NTRS)

Bearman, Greg (Inventor); Pelletier, Michael J. (Inventor); Seshadri, Suresh (Inventor); Pain, Bedabrata (Inventor)

2008-01-01

The present invention relates to a system and method for performing rapid and programmable analysis of data. The present invention relates to a reconfigurable detector comprising at least one array of a plurality of pixels, where each of the plurality of pixels can be selected to receive and read-out an input. The pixel array is divided into at least one pixel group for conducting a common predefined analysis. Each of the pixels has a programmable circuitry programmed with a dynamically configurable user-defined function to modify the input. The present detector also comprises a summing circuit designed to sum the modified input.

The Tracer Method of Curriculum Analysis in Cancer Education

ERIC Educational Resources Information Center

Mahan, J. Maurice; And Others

1976-01-01

To assist faculty involved in cancer education in various courses in the curriculum, rather than instituting a new course in oncology, a method was developed for identifying and assessing cancer-related content (a clinical clerk attended lectures, interviewed instructors, reviewed syllibi etc.) and a comprehensive description was produced and…

Assessing economic tradeoffs in forest management.

Treesearch

Ernie Niemi; Ed. Whitelaw

1999-01-01

Method is described for assessing the competing demands for forest resources in a forest management plan by addressing economics values, economic impacts, and perceptions of fairness around each demand. Economics trends and forces that shape the dynamic ecosystem-economy relation are developed. The method is demonstrated through an illustrative analysis of a forest-...

77 FR 14814 - Tobacco Product Analysis; Scientific Workshop; Request for Comments

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-13

... work to develop tobacco reference products that are not currently available for laboratory use. Discuss... methods used to analyze tobacco products. FDA will invite speakers to address scientific and technical matters relating to the testing of tobacco reference products and the analytical methods used to measure...

NMR analysis of biodiesel

USDA-ARS?s Scientific Manuscript database

Biodiesel is usually analyzed by the various methods called for in standards such as ASTM D6751 and EN 14214. Nuclear magnetic resonance (NMR) is not one of these methods. However, NMR, with 1H-NMR commonly applied, can be useful in a variety of applications related to biodiesel. These include monit...