Adventures in Uncertainty: An Empirical Investigation of the Use of a Taylor's Series Approximation for the Assessment of Sampling Errors in Educational Research.

ERIC Educational Resources Information Center

Wilson, Mark

This study investigates the accuracy of the Woodruff-Causey technique for estimating sampling errors for complex statistics. The technique may be applied when data are collected by using multistage clustered samples. The technique was chosen for study because of its relevance to the correct use of multivariate analyses in educational survey…

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2006-01-01

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described by rate constants. These problems are isomorphic with chemical kinetics problems. Recently, several efficient techniques for this purpose have been developed based on the approach originally proposed by Gillespie. Although the utility of the techniques mentioned above for Bayesian problems has not been determined, further research along these lines is warranted

Probability sampling in legal cases: Kansas cellphone users

NASA Astrophysics Data System (ADS)

Kadane, Joseph B.

2012-10-01

Probability sampling is a standard statistical technique. This article introduces the basic ideas of probability sampling, and shows in detail how probability sampling was used in a particular legal case.

Statistical evaluation of vibration analysis techniques

NASA Technical Reports Server (NTRS)

Milner, G. Martin; Miller, Patrice S.

1987-01-01

An evaluation methodology is presented for a selection of candidate vibration analysis techniques applicable to machinery representative of the environmental control and life support system of advanced spacecraft; illustrative results are given. Attention is given to the statistical analysis of small sample experiments, the quantification of detection performance for diverse techniques through the computation of probability of detection versus probability of false alarm, and the quantification of diagnostic performance.

Analysis of defect structure in silicon. Characterization of samples from UCP ingot 5848-13C

NASA Technical Reports Server (NTRS)

Natesh, R.; Guyer, T.; Stringfellow, G. B.

1982-01-01

Statistically significant quantitative structural imperfection measurements were made on samples from ubiquitous crystalline process (UCP) Ingot 5848 - 13 C. Important trends were noticed between the measured data, cell efficiency, and diffusion length. Grain boundary substructure appears to have an important effect on the conversion efficiency of solar cells from Semix material. Quantitative microscopy measurements give statistically significant information compared to other microanalytical techniques. A surface preparation technique to obtain proper contrast of structural defects suitable for QTM analysis was perfected.

Statistical Analysis Techniques for Small Sample Sizes

NASA Technical Reports Server (NTRS)

Navard, S. E.

1984-01-01

The small sample sizes problem which is encountered when dealing with analysis of space-flight data is examined. Because of such a amount of data available, careful analyses are essential to extract the maximum amount of information with acceptable accuracy. Statistical analysis of small samples is described. The background material necessary for understanding statistical hypothesis testing is outlined and the various tests which can be done on small samples are explained. Emphasis is on the underlying assumptions of each test and on considerations needed to choose the most appropriate test for a given type of analysis.

The potential of statistical shape modelling for geometric morphometric analysis of human teeth in archaeological research

PubMed Central

Fernee, Christianne; Browne, Martin; Zakrzewski, Sonia

2017-01-01

This paper introduces statistical shape modelling (SSM) for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM) tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA). Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique’s application was demonstrated for inter-sample comparison through analysis of the principal component (PC) weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA) and reconstruction from partial datasets. PMID:29216199

Taking a statistical approach

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

Wild, M.; Rouhani, S.

1995-02-01

A typical site investigation entails extensive sampling and monitoring. In the past, sampling plans have been designed on purely ad hoc bases, leading to significant expenditures and, in some cases, collection of redundant information. In many instances, sampling costs exceed the true worth of the collected data. The US Environmental Protection Agency (EPA) therefore has advocated the use of geostatistics to provide a logical framework for sampling and analysis of environmental data. Geostatistical methodology uses statistical techniques for the spatial analysis of a variety of earth-related data. The use of geostatistics was developed by the mining industry to estimate oremore » concentrations. The same procedure is effective in quantifying environmental contaminants in soils for risk assessments. Unlike classical statistical techniques, geostatistics offers procedures to incorporate the underlying spatial structure of the investigated field. Sample points spaced close together tend to be more similar than samples spaced further apart. This can guide sampling strategies and determine complex contaminant distributions. Geostatistic techniques can be used to evaluate site conditions on the basis of regular, irregular, random and even spatially biased samples. In most environmental investigations, it is desirable to concentrate sampling in areas of known or suspected contamination. The rigorous mathematical procedures of geostatistics allow for accurate estimates at unsampled locations, potentially reducing sampling requirements. The use of geostatistics serves as a decision-aiding and planning tool and can significantly reduce short-term site assessment costs, long-term sampling and monitoring needs, as well as lead to more accurate and realistic remedial design criteria.« less

[Statistical prediction methods in violence risk assessment and its application].

PubMed

Liu, Yuan-Yuan; Hu, Jun-Mei; Yang, Min; Li, Xiao-Song

2013-06-01

It is an urgent global problem how to improve the violence risk assessment. As a necessary part of risk assessment, statistical methods have remarkable impacts and effects. In this study, the predicted methods in violence risk assessment from the point of statistics are reviewed. The application of Logistic regression as the sample of multivariate statistical model, decision tree model as the sample of data mining technique, and neural networks model as the sample of artificial intelligence technology are all reviewed. This study provides data in order to contribute the further research of violence risk assessment.

A technique for evaluating the influence of spatial sampling on the determination of global mean total columnar ozone

NASA Technical Reports Server (NTRS)

Tolson, R. H.

1981-01-01

A technique is described for providing a means of evaluating the influence of spatial sampling on the determination of global mean total columnar ozone. A finite number of coefficients in the expansion are determined, and the truncated part of the expansion is shown to contribute an error to the estimate, which depends strongly on the spatial sampling and is relatively insensitive to data noise. First and second order statistics are derived for each term in a spherical harmonic expansion which represents the ozone field, and the statistics are used to estimate systematic and random errors in the estimates of total ozone.

Effect of different mixing methods on the physical properties of Portland cement.

PubMed

Shahi, Shahriar; Ghasemi, Negin; Rahimi, Saeed; Yavari, Hamidreza; Samiei, Mohammad; Jafari, Farnaz

2016-12-01

The Portland cement is hydrophilic cement; as a result, the powder-to-liquid ratio affects the properties of the final mix. In addition, the mixing technique affects hydration. The aim of this study was to evaluate the effect of different mixing techniques (conventional, amalgamator and ultrasonic) on some selective physical properties of Portland cement. The physical properties to be evaluated were determined using the ISO 6786:2001 specification. One hundred sixty two samples of Portland cement were prepared for three mixing techniques for each physical property (each 6 samples). Data were analyzed using descriptive statistics, one-way ANOVA and post hoc Tukey tests. Statistical significance was set at P <0.05. The mixing technique had no significant effect on the compressive strength, film thickness and flow of Portland cement ( P >0.05). Dimensional changes (shrinkage), solubility and pH increased significantly by amalgamator and ultrasonic mixing techniques ( P <0.05). The ultrasonic technique significantly decreased working time, and the amalgamator and ultrasonic techniques significantly decreased the setting time ( P <0.05). The mixing technique exerted no significant effect on the flow, film thickness and compressive strength of Portland cement samples. Key words: Physical properties, Portland cement, mixing methods.

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

Gilbert, Richard O.

The application of statistics to environmental pollution monitoring studies requires a knowledge of statistical analysis methods particularly well suited to pollution data. This book fills that need by providing sampling plans, statistical tests, parameter estimation procedure techniques, and references to pertinent publications. Most of the statistical techniques are relatively simple, and examples, exercises, and case studies are provided to illustrate procedures. The book is logically divided into three parts. Chapters 1, 2, and 3 are introductory chapters. Chapters 4 through 10 discuss field sampling designs and Chapters 11 through 18 deal with a broad range of statistical analysis procedures. Somemore » statistical techniques given here are not commonly seen in statistics book. For example, see methods for handling correlated data (Sections 4.5 and 11.12), for detecting hot spots (Chapter 10), and for estimating a confidence interval for the mean of a lognormal distribution (Section 13.2). Also, Appendix B lists a computer code that estimates and tests for trends over time at one or more monitoring stations using nonparametric methods (Chapters 16 and 17). Unfortunately, some important topics could not be included because of their complexity and the need to limit the length of the book. For example, only brief mention could be made of time series analysis using Box-Jenkins methods and of kriging techniques for estimating spatial and spatial-time patterns of pollution, although multiple references on these topics are provided. Also, no discussion of methods for assessing risks from environmental pollution could be included.« less

Image correlation and sampling study

NASA Technical Reports Server (NTRS)

Popp, D. J.; Mccormack, D. S.; Sedwick, J. L.

1972-01-01

The development of analytical approaches for solving image correlation and image sampling of multispectral data is discussed. Relevant multispectral image statistics which are applicable to image correlation and sampling are identified. The general image statistics include intensity mean, variance, amplitude histogram, power spectral density function, and autocorrelation function. The translation problem associated with digital image registration and the analytical means for comparing commonly used correlation techniques are considered. General expressions for determining the reconstruction error for specific image sampling strategies are developed.

Evaluation of the color stability of two techniques for reproducing artificial irides after microwave polymerization

PubMed Central

GOIATO, Marcelo Coelho; dos SANTOS, Daniela Micheline; MORENO, Amália; GENNARI-FILHO, Humberto; PELLIZZER, Eduardo Piza

2011-01-01

The use of ocular prostheses for ophthalmic patients aims to rebuild facial aesthetics and provide an artificial substitute to the visual organ. Natural intemperate conditions promote discoloration of artificial irides and many studies have attempted to produce irides with greater chromatic paint durability using different paint materials. Objectives The present study evaluated the color stability of artificial irides obtained with two techniques (oil painting and digital image) and submitted to microwave polymerization. Material and Methods Forty samples were fabricated simulating ocular prostheses. Each sample was constituted by one disc of acrylic resin N1 and one disc of colorless acrylic resin with the iris interposed between the discs. The irides in brown and blue color were obtained by oil painting or digital image. The color stability was determined by a reflection spectrophotometer and measurements were taken before and after microwave polymerization. Statistical analysis of the techniques for reproducing artificial irides was performed by applying the normal data distribution test followed by 2-way ANOVA and Tukey HSD test (α=.05). Results Chromatic alterations occurred in all specimens and statistically significant differences were observed between the oil-painted samples and those obtained by digital imaging. There was no statistical difference between the brown and blue colors. Independently of technique, all samples suffered color alterations after microwave polymerization. Conclusion The digital imaging technique for reproducing irides presented better color stability after microwave polymerization. PMID:21625733

Analytical Applications of Monte Carlo Techniques.

ERIC Educational Resources Information Center

Guell, Oscar A.; Holcombe, James A.

1990-01-01

Described are analytical applications of the theory of random processes, in particular solutions obtained by using statistical procedures known as Monte Carlo techniques. Supercomputer simulations, sampling, integration, ensemble, annealing, and explicit simulation are discussed. (CW)

Evaluation of primary immunization coverage of infants under universal immunization programme in an urban area of bangalore city using cluster sampling and lot quality assurance sampling techniques.

PubMed

K, Punith; K, Lalitha; G, Suman; Bs, Pradeep; Kumar K, Jayanth

2008-07-01

Is LQAS technique better than cluster sampling technique in terms of resources to evaluate the immunization coverage in an urban area? To assess and compare the lot quality assurance sampling against cluster sampling in the evaluation of primary immunization coverage. Population-based cross-sectional study. Areas under Mathikere Urban Health Center. Children aged 12 months to 23 months. 220 in cluster sampling, 76 in lot quality assurance sampling. Percentages and Proportions, Chi square Test. (1) Using cluster sampling, the percentage of completely immunized, partially immunized and unimmunized children were 84.09%, 14.09% and 1.82%, respectively. With lot quality assurance sampling, it was 92.11%, 6.58% and 1.31%, respectively. (2) Immunization coverage levels as evaluated by cluster sampling technique were not statistically different from the coverage value as obtained by lot quality assurance sampling techniques. Considering the time and resources required, it was found that lot quality assurance sampling is a better technique in evaluating the primary immunization coverage in urban area.

Comparative study of nail sampling techniques in onychomycosis.

PubMed

Shemer, Avner; Davidovici, Batya; Grunwald, Marcelo H; Trau, Henri; Amichai, Boaz

2009-07-01

Onychomycosis is a common problem. Obtaining accurate laboratory test results before treatment is important in clinical practice. The purpose of this study was to compare results of curettage and drilling techniques of nail sampling in the diagnosis of onychomycosis, and to establish the best technique and location of sampling. We evaluated 60 patients suffering from distal and lateral subungual onychomycosis and lateral subungual onychomycosis using curettage and vertical and horizontal drilling sampling techniques from three different sites of the infected nail. KOH examination and fungal culture were used for detection and identification of fungal infection. At each sample site, the horizontal drilling technique has a better culture sensitivity than curettage. Trichophyton rubrum was by far the most common pathogen detected by both techniques from all sampling sites. The drilling technique was found to be statistically better than curettage at each site of sampling, furthermore vertical drilling from the proximal part of the affected nail was found to be the best procedure for nail sampling. With each technique we found that the culture sensitivity improved as the location of the sample was more proximal. More types of pathogens were detected in samples taken by both methods from proximal parts of the affected nails.

A comparative analysis of conventional cytopreparatory and liquid based cytological techniques (Sure Path) in evaluation of serous effusion fluids.

PubMed

Dadhich, Hrishikesh; Toi, Pampa Ch; Siddaraju, Neelaiah; Sevvanthi, Kalidas

2016-11-01

Clinically, detection of malignant cells in serous body fluids is critical, as their presence implies the upstaging of the disease. Cytology of body cavity fluids serves as an important tool when other diagnostic tests cannot be performed. In most laboratories, currently, the effusion fluid samples are analysed chiefly by the conventional cytopreparatory (CCP) technique. Although, there are several studies comparing the liquid-based cytology (LBC), with CCP technique in the field of cervicovaginal cytology; the literature on such comparison with respect to serous body fluid examination is sparse. One hundred samples of serous body fluids were processed by both CCP and LBC techniques. Slides prepared by these techniques were studied using six parameters. A comparative analysis of the advantages and disadvantages of the techniques in detection of malignant cells was carried out with appropriate statistical tests. The samples comprised 52 pleural, 44 peritoneal and four pericardial fluids. No statistically significant difference was noted with respect to cellularity (P values = 0.22), cell distribution (P values = 0.39) and diagnosis of malignancy (P values = 0.20). As for the remaining parameters, LBC provided statistically significant clearer smear background (P values < 0.0001) and shorter screening time (P values < 0.0001), while CPP technique provided a significantly better staining quality (P values 0.01) and sharper cytomorphologic features (P values 0.05). Although, a reduced screening time and clearer smear background are the two major advantages of LBC; the CCP technique provides the better staining quality with sharper cytomorphologic features which is more critical from the cytologic interpretation point of view. Diagn. Cytopathol. 2016;44:874-879. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Uncertainty Quantification and Statistical Convergence Guidelines for PIV Data

NASA Astrophysics Data System (ADS)

Stegmeir, Matthew; Kassen, Dan

2016-11-01

As Particle Image Velocimetry has continued to mature, it has developed into a robust and flexible technique for velocimetry used by expert and non-expert users. While historical estimates of PIV accuracy have typically relied heavily on "rules of thumb" and analysis of idealized synthetic images, recently increased emphasis has been placed on better quantifying real-world PIV measurement uncertainty. Multiple techniques have been developed to provide per-vector instantaneous uncertainty estimates for PIV measurements. Often real-world experimental conditions introduce complications in collecting "optimal" data, and the effect of these conditions is important to consider when planning an experimental campaign. The current work utilizes the results of PIV Uncertainty Quantification techniques to develop a framework for PIV users to utilize estimated PIV confidence intervals to compute reliable data convergence criteria for optimal sampling of flow statistics. Results are compared using experimental and synthetic data, and recommended guidelines and procedures leveraging estimated PIV confidence intervals for efficient sampling for converged statistics are provided.

Experimental Investigations of Non-Stationary Properties In Radiometer Receivers Using Measurements of Multiple Calibration References

NASA Technical Reports Server (NTRS)

Racette, Paul; Lang, Roger; Zhang, Zhao-Nan; Zacharias, David; Krebs, Carolyn A. (Technical Monitor)

2002-01-01

Radiometers must be periodically calibrated because the receiver response fluctuates. Many techniques exist to correct for the time varying response of a radiometer receiver. An analytical technique has been developed that uses generalized least squares regression (LSR) to predict the performance of a wide variety of calibration algorithms. The total measurement uncertainty including the uncertainty of the calibration can be computed using LSR. The uncertainties of the calibration samples used in the regression are based upon treating the receiver fluctuations as non-stationary processes. Signals originating from the different sources of emission are treated as simultaneously existing random processes. Thus, the radiometer output is a series of samples obtained from these random processes. The samples are treated as random variables but because the underlying processes are non-stationary the statistics of the samples are treated as non-stationary. The statistics of the calibration samples depend upon the time for which the samples are to be applied. The statistics of the random variables are equated to the mean statistics of the non-stationary processes over the interval defined by the time of calibration sample and when it is applied. This analysis opens the opportunity for experimental investigation into the underlying properties of receiver non stationarity through the use of multiple calibration references. In this presentation we will discuss the application of LSR to the analysis of various calibration algorithms, requirements for experimental verification of the theory, and preliminary results from analyzing experiment measurements.

40 CFR 761.130 - Sampling requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... sampling scheme and the guidance document are available on EPA's PCB Web site at http://www.epa.gov/pcb, or... § 761.125(c) (2) through (4). Using its best engineering judgment, EPA may sample a statistically valid random or grid sampling technique, or both. When using engineering judgment or random “grab” samples, EPA...

40 CFR 761.130 - Sampling requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... sampling scheme and the guidance document are available on EPA's PCB Web site at http://www.epa.gov/pcb, or... § 761.125(c) (2) through (4). Using its best engineering judgment, EPA may sample a statistically valid random or grid sampling technique, or both. When using engineering judgment or random “grab” samples, EPA...

Methods for trend analysis: Examples with problem/failure data

NASA Technical Reports Server (NTRS)

Church, Curtis K.

1989-01-01

Statistics are emphasized as an important role in quality control and reliability. Consequently, Trend Analysis Techniques recommended a variety of statistical methodologies that could be applied to time series data. The major goal of the working handbook, using data from the MSFC Problem Assessment System, is to illustrate some of the techniques in the NASA standard, some different techniques, and to notice patterns of data. Techniques for trend estimation used are: regression (exponential, power, reciprocal, straight line) and Kendall's rank correlation coefficient. The important details of a statistical strategy for estimating a trend component are covered in the examples. However, careful analysis and interpretation is necessary because of small samples and frequent zero problem reports in a given time period. Further investigations to deal with these issues are being conducted.

Promotional methods used by representatives of drug companies: A prospective survey in general practice

PubMed Central

Schramm, Jesper; Andersen, Morten; Vach, Kirstin; Kragstrup, Jakob; Peter Kampmann, Jens; Søndergaard, Jens

2007-01-01

Objective To examine the extent and composition of pharmaceutical industry representatives’ marketing techniques with a particular focus on drug sampling in relation to drug age. Design A group of 47 GPs prospectively collected data on drug promotional activities during a six-month period, and a sub-sample of 10 GPs furthermore recorded the representatives’ marketing techniques in detail. Setting Primary healthcare. Subjects General practitioners in the County of Funen, Denmark. Main outcome measures. Promotional visits and corresponding marketing techniques. Results The 47 GPs recorded 1050 visits corresponding to a median of 19 (range 3 to 63) per GP in the six months. The majority of drugs promoted (52%) were marketed more than five years ago. There was a statistically significant decline in the proportion of visits where drug samples were offered with drug age, but the decline was small OR 0.97 (95% CI 0.95;0.98) per year. Leaflets (68%), suggestions on how to improve therapy for a specific patient registered with the practice (53%), drug samples (48%), and gifts (36%) were the most frequently used marketing techniques. Conclusion Drug-industry representatives use a variety of promotional methods. The tendency to hand out drug samples was statistically significantly associated with drug age, but the decline was small. PMID:17497486

7 CFR 3600.3 - Functions.

Code of Federal Regulations, 2011 CFR

2011-01-01

.... agricultural and rural economy. (2) Administering a methodological research program to improve agricultural... design and data collection methodologies to the agricultural statistics program. Major functions include...) Designing, testing, and establishing survey techniques and standards, including sample design, sample...

7 CFR 3600.3 - Functions.

Code of Federal Regulations, 2010 CFR

2010-01-01

.... agricultural and rural economy. (2) Administering a methodological research program to improve agricultural... design and data collection methodologies to the agricultural statistics program. Major functions include...) Designing, testing, and establishing survey techniques and standards, including sample design, sample...

7 CFR 3600.3 - Functions.

Code of Federal Regulations, 2012 CFR

2012-01-01

.... agricultural and rural economy. (2) Administering a methodological research program to improve agricultural... design and data collection methodologies to the agricultural statistics program. Major functions include...) Designing, testing, and establishing survey techniques and standards, including sample design, sample...

7 CFR 3600.3 - Functions.

Code of Federal Regulations, 2013 CFR

2013-01-01

.... agricultural and rural economy. (2) Administering a methodological research program to improve agricultural... design and data collection methodologies to the agricultural statistics program. Major functions include...) Designing, testing, and establishing survey techniques and standards, including sample design, sample...

7 CFR 3600.3 - Functions.

Code of Federal Regulations, 2014 CFR

2014-01-01

.... agricultural and rural economy. (2) Administering a methodological research program to improve agricultural... design and data collection methodologies to the agricultural statistics program. Major functions include...) Designing, testing, and establishing survey techniques and standards, including sample design, sample...

Sampling methods to the statistical control of the production of blood components.

PubMed

Pereira, Paulo; Seghatchian, Jerard; Caldeira, Beatriz; Santos, Paula; Castro, Rosa; Fernandes, Teresa; Xavier, Sandra; de Sousa, Gracinda; de Almeida E Sousa, João Paulo

2017-12-01

The control of blood components specifications is a requirement generalized in Europe by the European Commission Directives and in the US by the AABB standards. The use of a statistical process control methodology is recommended in the related literature, including the EDQM guideline. The control reliability is dependent of the sampling. However, a correct sampling methodology seems not to be systematically applied. Commonly, the sampling is intended to comply uniquely with the 1% specification to the produced blood components. Nevertheless, on a purely statistical viewpoint, this model could be argued not to be related to a consistent sampling technique. This could be a severe limitation to detect abnormal patterns and to assure that the production has a non-significant probability of producing nonconforming components. This article discusses what is happening in blood establishments. Three statistical methodologies are proposed: simple random sampling, sampling based on the proportion of a finite population, and sampling based on the inspection level. The empirical results demonstrate that these models are practicable in blood establishments contributing to the robustness of sampling and related statistical process control decisions for the purpose they are suggested for. Copyright © 2017 Elsevier Ltd. All rights reserved.

Influence of size-fractioning techniques on concentrations of selected trace metals in bottom materials from two streams in northeastern Ohio

USGS Publications Warehouse

Koltun, G.F.; Helsel, Dennis R.

1986-01-01

Identical stream-bottom material samples, when fractioned to the same size by different techniques, may contain significantly different trace-metal concentrations. Precision of techniques also may differ, which could affect the ability to discriminate between size-fractioned bottom-material samples having different metal concentrations. Bottom-material samples fractioned to less than 0.020 millimeters by means of three common techniques (air elutriation, sieving, and settling) were analyzed for six trace metals to determine whether the technique used to obtain the desired particle-size fraction affects the ability to discriminate between bottom materials having different trace-metal concentrations. In addition, this study attempts to assess whether median trace-metal concentrations in size-fractioned bottom materials of identical origin differ depending on the size-fractioning technique used. Finally, this study evaluates the efficiency of the three size-fractioning techniques in terms of time, expense, and effort involved. Bottom-material samples were collected at two sites in northeastern Ohio: One is located in an undeveloped forested basin, and the other is located in a basin having a mixture of industrial and surface-mining land uses. The sites were selected for their close physical proximity, similar contributing drainage areas, and the likelihood that trace-metal concentrations in the bottom materials would be significantly different. Statistically significant differences in the concentrations of trace metals were detected between bottom-material samples collected at the two sites when the samples had been size-fractioned by means of air elutriation or sieving. Statistical analyses of samples that had been size fractioned by settling in native water were not measurably different in any of the six trace metals analyzed. Results of multiple comparison tests suggest that differences related to size-fractioning technique were evident in median copper, lead, and iron concentrations. Technique-related differences in copper concentrations most likely resulted from contamination of air-elutriated samples by a feed tip on the elutriator apparatus. No technique-related differences were observed in chromium, manganese, or zinc concentrations. Although air elutriation was the most expensive sizefractioning technique investigated, samples fractioned by this technique appeared to provide a superior level of discrimination between metal concentrations present in the bottom materials of the two sites. Sieving was an adequate lower-cost but more laborintensive alternative.

Advanced statistical methods for improved data analysis of NASA astrophysics missions

NASA Technical Reports Server (NTRS)

Feigelson, Eric D.

1992-01-01

The investigators under this grant studied ways to improve the statistical analysis of astronomical data. They looked at existing techniques, the development of new techniques, and the production and distribution of specialized software to the astronomical community. Abstracts of nine papers that were produced are included, as well as brief descriptions of four software packages. The articles that are abstracted discuss analytical and Monte Carlo comparisons of six different linear least squares fits, a (second) paper on linear regression in astronomy, two reviews of public domain software for the astronomer, subsample and half-sample methods for estimating sampling distributions, a nonparametric estimation of survival functions under dependent competing risks, censoring in astronomical data due to nondetections, an astronomy survival analysis computer package called ASURV, and improving the statistical methodology of astronomical data analysis.

Accurate low-cost methods for performance evaluation of cache memory systems

NASA Technical Reports Server (NTRS)

Laha, Subhasis; Patel, Janak H.; Iyer, Ravishankar K.

1988-01-01

Methods of simulation based on statistical techniques are proposed to decrease the need for large trace measurements and for predicting true program behavior. Sampling techniques are applied while the address trace is collected from a workload. This drastically reduces the space and time needed to collect the trace. Simulation techniques are developed to use the sampled data not only to predict the mean miss rate of the cache, but also to provide an empirical estimate of its actual distribution. Finally, a concept of primed cache is introduced to simulate large caches by the sampling-based method.

Evaluating the event-related synchronization and desynchronization by means of a statistical frequency test.

PubMed

Miranda de Sá, Antonio Mauricio F L; Infantosi, Antonio Fernando C; Lazarev, Vladimir V

2007-01-01

In the present work, a commonly used index for evaluating the Event-Related Synchronization and Desynchronization (ERS/ERD) in the EEG was expressed as a function of the Spectral F-Test (SFT), which is a statistical test for assessing if two sample spectra are from populations with identical theoretical spectra. The sampling distribution of SFT has been derived, allowing hence ERS/ERD to be evaluated under a statistical basis. An example of the technique was also provided in the EEG signals from 10 normal subjects during intermittent photic stimulation.

Two sampling techniques for game meat.

PubMed

van der Merwe, Maretha; Jooste, Piet J; Hoffman, Louw C; Calitz, Frikkie J

2013-03-20

A study was conducted to compare the excision sampling technique used by the export market and the sampling technique preferred by European countries, namely the biotrace cattle and swine test. The measuring unit for the excision sampling was grams (g) and square centimetres (cm2) for the swabbing technique. The two techniques were compared after a pilot test was conducted on spiked approved beef carcasses (n = 12) that statistically proved the two measuring units correlated. The two sampling techniques were conducted on the same game carcasses (n = 13) and analyses performed for aerobic plate count (APC), Escherichia coli and Staphylococcus aureus, for both techniques. A more representative result was obtained by swabbing and no damage was caused to the carcass. Conversely, the excision technique yielded fewer organisms and caused minor damage to the carcass. The recovery ratio from the sampling technique improved 5.4 times for APC, 108.0 times for E. coli and 3.4 times for S. aureus over the results obtained from the excision technique. It was concluded that the sampling methods of excision and swabbing can be used to obtain bacterial profiles from both export and local carcasses and could be used to indicate whether game carcasses intended for the local market are possibly on par with game carcasses intended for the export market and therefore safe for human consumption.

Misrepresenting random sampling? A systematic review of research papers in the Journal of Advanced Nursing.

PubMed

Williamson, Graham R

2003-11-01

This paper discusses the theoretical limitations of the use of random sampling and probability theory in the production of a significance level (or P-value) in nursing research. Potential alternatives, in the form of randomization tests, are proposed. Research papers in nursing, medicine and psychology frequently misrepresent their statistical findings, as the P-values reported assume random sampling. In this systematic review of studies published between January 1995 and June 2002 in the Journal of Advanced Nursing, 89 (68%) studies broke this assumption because they used convenience samples or entire populations. As a result, some of the findings may be questionable. The key ideas of random sampling and probability theory for statistical testing (for generating a P-value) are outlined. The result of a systematic review of research papers published in the Journal of Advanced Nursing is then presented, showing how frequently random sampling appears to have been misrepresented. Useful alternative techniques that might overcome these limitations are then discussed. REVIEW LIMITATIONS: This review is limited in scope because it is applied to one journal, and so the findings cannot be generalized to other nursing journals or to nursing research in general. However, it is possible that other nursing journals are also publishing research articles based on the misrepresentation of random sampling. The review is also limited because in several of the articles the sampling method was not completely clearly stated, and in this circumstance a judgment has been made as to the sampling method employed, based on the indications given by author(s). Quantitative researchers in nursing should be very careful that the statistical techniques they use are appropriate for the design and sampling methods of their studies. If the techniques they employ are not appropriate, they run the risk of misinterpreting findings by using inappropriate, unrepresentative and biased samples.

Mixing of thawed coagulation samples prior to testing: Is any technique better than another?

PubMed

Lima-Oliveira, Gabriel; Adcock, Dorothy M; Salvagno, Gian Luca; Favaloro, Emmanuel J; Lippi, Giuseppe

2016-12-01

Thus study was aimed to investigate whether the mixing technique could influence the results of routine and specialized clotting tests on post-thawed specimens. The sample population consisted of 13 healthy volunteers. Venous blood was collected by evacuated system into three 3.5mL tubes containing 0.109mmol/L buffered sodium citrate. The three blood tubes of each subject were pooled immediately after collection inside a Falcon 15mL tube, then mixed by 6 gentle end-over-end inversions, and centrifuged at 1500g for 15min. Plasma-pool of each subject was then divided in 4 identical aliquots. All aliquots were thawed after 2-day freezing -70°C. Immediately afterwards, the plasma of the four paired aliquots were treated using four different techniques: (a) reference procedure, entailing 6 gentle end-over-end inversions; (b) placing the sample on a blood tube rocker (i.e., rotor mixing) for 5min to induce agitation and mixing; (c) use of a vortex mixer for 20s to induce agitation and mixing; and (d) no mixing. The significance of differences against the reference technique for mixing thawed plasma specimens (i.e., 6 gentle end-over-end inversions) were assessed with paired Student's t-test. The statistical significance was set at p<0.05. As compared to the reference 6-time gentle inversion technique, statistically significant differences were only observed for fibrinogen, and factor VIII in plasma mixed on tube rocker. Some trends were observed in the remaining other cases, but the bias did not achieve statistical significance. We hence suggest that each laboratory should standardize the procedures for mixing of thawed plasma according to a single technique. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

A Monte Carlo technique for signal level detection in implanted intracranial pressure monitoring.

PubMed

Avent, R K; Charlton, J D; Nagle, H T; Johnson, R N

1987-01-01

Statistical monitoring techniques like CUSUM, Trigg's tracking signal and EMP filtering have a major advantage over more recent techniques, such as Kalman filtering, because of their inherent simplicity. In many biomedical applications, such as electronic implantable devices, these simpler techniques have greater utility because of the reduced requirements on power, logic complexity and sampling speed. The determination of signal means using some of the earlier techniques are reviewed in this paper, and a new Monte Carlo based method with greater capability to sparsely sample a waveform and obtain an accurate mean value is presented. This technique may find widespread use as a trend detection method when reduced power consumption is a requirement.

Sampling methods for amphibians in streams in the Pacific Northwest.

Treesearch

R. Bruce Bury; Paul Stephen Corn

1991-01-01

Methods describing how to sample aquatic and semiaquatic amphibians in small streams and headwater habitats in the Pacific Northwest are presented. We developed a technique that samples 10-meter stretches of selected streams, which was adequate to detect presence or absence of amphibian species and provided sample sizes statistically sufficient to compare abundance of...

Seasonal rationalization of river water quality sampling locations: a comparative study of the modified Sanders and multivariate statistical approaches.

PubMed

Varekar, Vikas; Karmakar, Subhankar; Jha, Ramakar

2016-02-01

The design of surface water quality sampling location is a crucial decision-making process for rationalization of monitoring network. The quantity, quality, and types of available dataset (watershed characteristics and water quality data) may affect the selection of appropriate design methodology. The modified Sanders approach and multivariate statistical techniques [particularly factor analysis (FA)/principal component analysis (PCA)] are well-accepted and widely used techniques for design of sampling locations. However, their performance may vary significantly with quantity, quality, and types of available dataset. In this paper, an attempt has been made to evaluate performance of these techniques by accounting the effect of seasonal variation, under a situation of limited water quality data but extensive watershed characteristics information, as continuous and consistent river water quality data is usually difficult to obtain, whereas watershed information may be made available through application of geospatial techniques. A case study of Kali River, Western Uttar Pradesh, India, is selected for the analysis. The monitoring was carried out at 16 sampling locations. The discrete and diffuse pollution loads at different sampling sites were estimated and accounted using modified Sanders approach, whereas the monitored physical and chemical water quality parameters were utilized as inputs for FA/PCA. The designed optimum number of sampling locations for monsoon and non-monsoon seasons by modified Sanders approach are eight and seven while that for FA/PCA are eleven and nine, respectively. Less variation in the number and locations of designed sampling sites were obtained by both techniques, which shows stability of results. A geospatial analysis has also been carried out to check the significance of designed sampling location with respect to river basin characteristics and land use of the study area. Both methods are equally efficient; however, modified Sanders approach outperforms FA/PCA when limited water quality and extensive watershed information is available. The available water quality dataset is limited and FA/PCA-based approach fails to identify monitoring locations with higher variation, as these multivariate statistical approaches are data-driven. The priority/hierarchy and number of sampling sites designed by modified Sanders approach are well justified by the land use practices and observed river basin characteristics of the study area.

Detecting subtle hydrochemical anomalies with multivariate statistics: an example from homogeneous groundwaters in the Great Artesian Basin, Australia

NASA Astrophysics Data System (ADS)

O'Shea, Bethany; Jankowski, Jerzy

2006-12-01

The major ion composition of Great Artesian Basin groundwater in the lower Namoi River valley is relatively homogeneous in chemical composition. Traditional graphical techniques have been combined with multivariate statistical methods to determine whether subtle differences in the chemical composition of these waters can be delineated. Hierarchical cluster analysis and principal components analysis were successful in delineating minor variations within the groundwaters of the study area that were not visually identified in the graphical techniques applied. Hydrochemical interpretation allowed geochemical processes to be identified in each statistically defined water type and illustrated how these groundwaters differ from one another. Three main geochemical processes were identified in the groundwaters: ion exchange, precipitation, and mixing between waters from different sources. Both statistical methods delineated an anomalous sample suspected of being influenced by magmatic CO2 input. The use of statistical methods to complement traditional graphical techniques for waters appearing homogeneous is emphasized for all investigations of this type. Copyright

Comparison of destructive and nondestructive sampling techniques of retail chicken carcasses for enumeration of hygiene indicator microorganisms.

PubMed

Cossi, Marcus Vinícius Coutinho; de Almeida, Michelle Vieira; Dias, Mariane Rezende; de Arruda Pinto, Paulo Sérgiode; Nero, Luís Augusto

2012-01-01

The type of sampling technique used to obtain food samples is fundamental to the success of microbiological analysis. Destructive and nondestructive techniques, such as tissue excision and rinsing, respectively, are widely employed in obtaining samples from chicken carcasses. In this study, four sampling techniques used for chicken carcasses were compared to evaluate their performances in the enumeration of hygiene indicator microorganisms. Sixty fresh chicken carcasses were sampled by rinsing, tissue excision, superficial swabbing, and skin excision. All samples were submitted for enumeration of mesophilic aerobes, Enterobacteriaceae, coliforms, and Escherichia coli. The results were compared to determine the statistical significance of differences and correlation (P < 0.05). Tissue excision provided the highest microbial counts compared with the other procedures, with significant differences obtained only for coliforms and E. coli (P < 0.05). Significant correlations (P < 0.05) were observed for all the sampling techniques evaluated for most of the hygiene indicators. Despite presenting a higher recovery ability, tissue excision did not present significant differences for microorganism enumeration compared with other nondestructive techniques, such as rinsing, indicating its adequacy for microbiological analysis of chicken carcasses.

STATISTICAL TECHNIQUES FOR DETERMINATION AND PREDICTION OF FUNDAMENTAL FISH ASSEMBLAGES OF THE MID-ATLANTIC HIGHLANDS

EPA Science Inventory

A statistical software tool, Stream Fish Community Predictor (SFCP), based on EMAP stream sampling in the mid-Atlantic Highlands, was developed to predict stream fish communities using stream and watershed characteristics. Step one in the tool development was a cluster analysis t...

Partial Least Squares Regression Can Aid in Detecting Differential Abundance of Multiple Features in Sets of Metagenomic Samples

PubMed Central

Libiger, Ondrej; Schork, Nicholas J.

2015-01-01

It is now feasible to examine the composition and diversity of microbial communities (i.e., “microbiomes”) that populate different human organs and orifices using DNA sequencing and related technologies. To explore the potential links between changes in microbial communities and various diseases in the human body, it is essential to test associations involving different species within and across microbiomes, environmental settings and disease states. Although a number of statistical techniques exist for carrying out relevant analyses, it is unclear which of these techniques exhibit the greatest statistical power to detect associations given the complexity of most microbiome datasets. We compared the statistical power of principal component regression, partial least squares regression, regularized regression, distance-based regression, Hill's diversity measures, and a modified test implemented in the popular and widely used microbiome analysis methodology “Metastats” across a wide range of simulated scenarios involving changes in feature abundance between two sets of metagenomic samples. For this purpose, simulation studies were used to change the abundance of microbial species in a real dataset from a published study examining human hands. Each technique was applied to the same data, and its ability to detect the simulated change in abundance was assessed. We hypothesized that a small subset of methods would outperform the rest in terms of the statistical power. Indeed, we found that the Metastats technique modified to accommodate multivariate analysis and partial least squares regression yielded high power under the models and data sets we studied. The statistical power of diversity measure-based tests, distance-based regression and regularized regression was significantly lower. Our results provide insight into powerful analysis strategies that utilize information on species counts from large microbiome data sets exhibiting skewed frequency distributions obtained on a small to moderate number of samples. PMID:26734061

Simulating the complex output of rainfall and hydrological processes using the information contained in large data sets: the Direct Sampling approach.

NASA Astrophysics Data System (ADS)

Oriani, Fabio

2017-04-01

The unpredictable nature of rainfall makes its estimation as much difficult as it is essential to hydrological applications. Stochastic simulation is often considered a convenient approach to asses the uncertainty of rainfall processes, but preserving their irregular behavior and variability at multiple scales is a challenge even for the most advanced techniques. In this presentation, an overview on the Direct Sampling technique [1] and its recent application to rainfall and hydrological data simulation [2, 3] is given. The algorithm, having its roots in multiple-point statistics, makes use of a training data set to simulate the outcome of a process without inferring any explicit probability measure: the data are simulated in time or space by sampling the training data set where a sufficiently similar group of neighbor data exists. This approach allows preserving complex statistical dependencies at different scales with a good approximation, while reducing the parameterization to the minimum. The straights and weaknesses of the Direct Sampling approach are shown through a series of applications to rainfall and hydrological data: from time-series simulation to spatial rainfall fields conditioned by elevation or a climate scenario. In the era of vast databases, is this data-driven approach a valid alternative to parametric simulation techniques? [1] Mariethoz G., Renard P., and Straubhaar J. (2010), The Direct Sampling method to perform multiple-point geostatistical simulations, Water. Rerous. Res., 46(11), http://dx.doi.org/10.1029/2008WR007621 [2] Oriani F., Straubhaar J., Renard P., and Mariethoz G. (2014), Simulation of rainfall time series from different climatic regions using the direct sampling technique, Hydrol. Earth Syst. Sci., 18, 3015-3031, http://dx.doi.org/10.5194/hess-18-3015-2014 [3] Oriani F., Borghi A., Straubhaar J., Mariethoz G., Renard P. (2016), Missing data simulation inside flow rate time-series using multiple-point statistics, Environ. Model. Softw., vol. 86, pp. 264 - 276, http://dx.doi.org/10.1016/j.envsoft.2016.10.002

Explorations in statistics: the log transformation.

PubMed

Curran-Everett, Douglas

2018-06-01

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This thirteenth installment of Explorations in Statistics explores the log transformation, an established technique that rescales the actual observations from an experiment so that the assumptions of some statistical analysis are better met. A general assumption in statistics is that the variability of some response Y is homogeneous across groups or across some predictor variable X. If the variability-the standard deviation-varies in rough proportion to the mean value of Y, a log transformation can equalize the standard deviations. Moreover, if the actual observations from an experiment conform to a skewed distribution, then a log transformation can make the theoretical distribution of the sample mean more consistent with a normal distribution. This is important: the results of a one-sample t test are meaningful only if the theoretical distribution of the sample mean is roughly normal. If we log-transform our observations, then we want to confirm the transformation was useful. We can do this if we use the Box-Cox method, if we bootstrap the sample mean and the statistic t itself, and if we assess the residual plots from the statistical model of the actual and transformed sample observations.

The Effects of Finite Sampling on State Assessment Sample Requirements. NAEP Validity Studies. Working Paper Series.

ERIC Educational Resources Information Center

Chromy, James R.

This study addressed statistical techniques that might ameliorate some of the sampling problems currently facing states with small populations participating in State National Assessment of Educational Progress (NAEP) assessments. The study explored how the application of finite population correction factors to the between-school component of…

Regression sampling: some results for resource managers and researchers

Treesearch

William G. O' Regan; Robert W. Boyd

1974-01-01

Regression sampling is widely used in natural resources management and research to estimate quantities of resources per unit area. This note brings together results found in the statistical literature in the application of this sampling technique. Conditional and unconditional estimators are listed and for each estimator, exact variances and unbiased estimators for the...

Toward Robust and Efficient Climate Downscaling for Wind Energy

NASA Astrophysics Data System (ADS)

Vanvyve, E.; Rife, D.; Pinto, J. O.; Monaghan, A. J.; Davis, C. A.

2011-12-01

This presentation describes a more accurate and economical (less time, money and effort) wind resource assessment technique for the renewable energy industry, that incorporates innovative statistical techniques and new global mesoscale reanalyzes. The technique judiciously selects a collection of "case days" that accurately represent the full range of wind conditions observed at a given site over a 10-year period, in order to estimate the long-term energy yield. We will demonstrate that this new technique provides a very accurate and statistically reliable estimate of the 10-year record of the wind resource by intelligently choosing a sample of ±120 case days. This means that the expense of downscaling to quantify the wind resource at a prospective wind farm can be cut by two thirds from the current industry practice of downscaling a randomly chosen 365-day sample to represent winds over a "typical" year. This new estimate of the long-term energy yield at a prospective wind farm also has far less statistical uncertainty than the current industry standard approach. This key finding has the potential to reduce significantly market barriers to both onshore and offshore wind farm development, since insurers and financiers charge prohibitive premiums on investments that are deemed to be high risk. Lower uncertainty directly translates to lower perceived risk, and therefore far more attractive financing terms could be offered to wind farm developers who employ this new technique.

The classification of secondary colorectal liver cancer in human biopsy samples using angular dispersive x-ray diffraction and multivariate analysis

NASA Astrophysics Data System (ADS)

Theodorakou, Chrysoula; Farquharson, Michael J.

2009-08-01

The motivation behind this study is to assess whether angular dispersive x-ray diffraction (ADXRD) data, processed using multivariate analysis techniques, can be used for classifying secondary colorectal liver cancer tissue and normal surrounding liver tissue in human liver biopsy samples. The ADXRD profiles from a total of 60 samples of normal liver tissue and colorectal liver metastases were measured using a synchrotron radiation source. The data were analysed for 56 samples using nonlinear peak-fitting software. Four peaks were fitted to all of the ADXRD profiles, and the amplitude, area, amplitude and area ratios for three of the four peaks were calculated and used for the statistical and multivariate analysis. The statistical analysis showed that there are significant differences between all the peak-fitting parameters and ratios between the normal and the diseased tissue groups. The technique of soft independent modelling of class analogy (SIMCA) was used to classify normal liver tissue and colorectal liver metastases resulting in 67% of the normal tissue samples and 60% of the secondary colorectal liver tissue samples being classified correctly. This study has shown that the ADXRD data of normal and secondary colorectal liver cancer are statistically different and x-ray diffraction data analysed using multivariate analysis have the potential to be used as a method of tissue classification.

Comparison of dialysis membrane diffusion samplers and two purging methods in bedrock wells

USGS Publications Warehouse

Imbrigiotta, T.E.; Ehlke, T.A.; Lacombe, P.J.; Dale, J.M.; ,

2002-01-01

Collection of ground-water samples from bedrock wells using low-flow purging techniques is problematic because of the random spacing, variable hydraulic conductivity, and variable contamination of contributing fractures in each well's open interval. To test alternatives to this purging method, a field comparison of three ground-water-sampling techniques was conducted on wells in fractured bedrock at a site contaminated primarily with volatile organic compounds. Constituent concentrations in samples collected with a diffusion sampler constructed from dialysis membrane material were compared to those in samples collected from the same wells with a standard low-flow purging technique and a hybrid (high-flow/low-flow) purging technique. Concentrations of trichloroethene, cis-1,2-dichloroethene, vinyl chloride, calcium, chloride, and alkalinity agreed well among samples collected with all three techniques in 9 of the 10 wells tested. Iron concentrations varied more than those of the other parameters, but their pattern of variation was not consistent. Overall, the results of nonparametric analysis of variance testing on the nine wells sampled twice showed no statistically significant difference at the 95-percent confidence level among the concentrations of volatile organic compounds or inorganic constituents recovered by use of any of the three sampling techniques.

40Ar/39Ar technique of KAr dating: a comparison with the conventional technique

USGS Publications Warehouse

Brent, Dalrymple G.; Lanphere, M.A.

1971-01-01

K-Ar ages have been determined by the 40Ar/39Ar total fusion technique on 19 terrestrial samples whose conventional K-Ar ages range from 3.4 my to nearly 1700 my. Sample materials included biotite, muscovite, sanidine, adularia, plagioclase, hornblende, actinolite, alunite, dacite, and basalt. For 18 samples there are no significant differences at the 95% confidence level between the KAr ages obtained by these two techniques; for one sample the difference is 4.3% and is statistically significant. For the neutron doses used in these experiments (???4 ?? 1018 nvt) it appears that corrections for interfering Ca- and K-derived Ar isotopes can be made without significant loss of precision for samples with K/Ca > 1 as young as about 5 ?? 105 yr, and for samples with K/Ca < 1 as young as about 107 yr. For younger samples the combination of large atmospheric Ar corrections and large corrections for Ca- and K-derived Ar may make the precision of the 40Ar/39Ar technique less than that of the conventional technique unless the irradiation parameters are adjusted to minimize these corrections. ?? 1971.

Comparison of Sample Size by Bootstrap and by Formulas Based on Normal Distribution Assumption.

PubMed

Wang, Zuozhen

2018-01-01

Bootstrapping technique is distribution-independent, which provides an indirect way to estimate the sample size for a clinical trial based on a relatively smaller sample. In this paper, sample size estimation to compare two parallel-design arms for continuous data by bootstrap procedure are presented for various test types (inequality, non-inferiority, superiority, and equivalence), respectively. Meanwhile, sample size calculation by mathematical formulas (normal distribution assumption) for the identical data are also carried out. Consequently, power difference between the two calculation methods is acceptably small for all the test types. It shows that the bootstrap procedure is a credible technique for sample size estimation. After that, we compared the powers determined using the two methods based on data that violate the normal distribution assumption. To accommodate the feature of the data, the nonparametric statistical method of Wilcoxon test was applied to compare the two groups in the data during the process of bootstrap power estimation. As a result, the power estimated by normal distribution-based formula is far larger than that by bootstrap for each specific sample size per group. Hence, for this type of data, it is preferable that the bootstrap method be applied for sample size calculation at the beginning, and that the same statistical method as used in the subsequent statistical analysis is employed for each bootstrap sample during the course of bootstrap sample size estimation, provided there is historical true data available that can be well representative of the population to which the proposed trial is planning to extrapolate.

Use of missing data methods in longitudinal studies: the persistence of bad practices in developmental psychology.

PubMed

Jelicić, Helena; Phelps, Erin; Lerner, Richard M

2009-07-01

Developmental science rests on describing, explaining, and optimizing intraindividual changes and, hence, empirically requires longitudinal research. Problems of missing data arise in most longitudinal studies, thus creating challenges for interpreting the substance and structure of intraindividual change. Using a sample of reports of longitudinal studies obtained from three flagship developmental journals-Child Development, Developmental Psychology, and Journal of Research on Adolescence-we examined the number of longitudinal studies reporting missing data and the missing data techniques used. Of the 100 longitudinal studies sampled, 57 either reported having missing data or had discrepancies in sample sizes reported for different analyses. The majority of these studies (82%) used missing data techniques that are statistically problematic (either listwise deletion or pairwise deletion) and not among the methods recommended by statisticians (i.e., the direct maximum likelihood method and the multiple imputation method). Implications of these results for developmental theory and application, and the need for understanding the consequences of using statistically inappropriate missing data techniques with actual longitudinal data sets, are discussed.

Exploring Tree Age & Diameter to Illustrate Sample Design & Inference in Observational Ecology

ERIC Educational Resources Information Center

Casady, Grant M.

2015-01-01

Undergraduate biology labs often explore the techniques of data collection but neglect the statistical framework necessary to express findings. Students can be confused about how to use their statistical knowledge to address specific biological questions. Growth in the area of observational ecology requires that students gain experience in…

Comparison of two headspace sampling techniques for the analysis of off-flavour volatiles from oat based products.

PubMed

Cognat, Claudine; Shepherd, Tom; Verrall, Susan R; Stewart, Derek

2012-10-01

Two different headspace sampling techniques were compared for analysis of aroma volatiles from freshly produced and aged plain oatcakes. Solid phase microextraction (SPME) using a Carboxen-Polydimethylsiloxane (PDMS) fibre and entrainment on Tenax TA within an adsorbent tube were used for collection of volatiles. The effects of variation in the sampling method were also considered using SPME. The data obtained using both techniques were processed by multivariate statistical analysis (PCA). Both techniques showed similar capacities to discriminate between the samples at different ages. Discrimination between fresh and rancid samples could be made on the basis of changes in the relative abundances of 14-15 of the constituents in the volatile profiles. A significant effect on the detection level of volatile compounds was observed when samples were crushed and analysed by SPME-GC-MS, in comparison to undisturbed product. The applicability and cost effectiveness of both methods were considered. Copyright © 2012 Elsevier Ltd. All rights reserved.

Comparison of laser and power bleaching techniques in tooth color change.

PubMed

Fekrazad, Reza; Alimazandarani, Shervin; Kalhori, Katayoun Am; Assadian, Hadi; Mirmohammadi, Seyed-Mahdi

2017-04-01

Laser-assisted bleaching uses laser beam to accelerate release of free radicals within the bleaching gel to decrease time of whitening procedure. The aim of this study was to compare the efficacy of power bleaching using Opalescence Xtra Boost® and laser bleaching technique using LaserSmile gel and diode laser as an activator in their tooth whitening capacity. Student t test showed that the laser bleaching group significantly outperformed the power bleaching group in changing ∆E ( p =0.977). Similarly, while comparing the groups in changing ∆L, the laser bleaching group indicated significantly superior results ( p =0.953). Statistical data from student t test while comparing the groups in changing the parameter of yellowness indicated that samples in laser bleaching group underwent a more significant reduction than power-bleached samples ( p =0.85). Correspondingly, changes in whiteness were statistically tested through student t test, showing that laser bleaching technique increased whiteness of the samples significantly more than those treated by power bleaching ( p =0.965). The digital color evaluation data was in accordance with spectrophotometry and showed that laser bleaching outperformed power bleaching technique. Both techniques were able to increase whiteness and decrease yellowness ratio of the samples. ΔE decrease for laser bleaching and power bleaching groups were 3.05 and 1.67, respectively. Tooth color change in laser bleaching group was 1.88 times more than that of power bleaching group ( p <0.001). It could be concluded that under the conditions of this study, both laser-assisted and power bleaching techniques were capable of altering tooth color change, but laser bleaching was deemed a more efficient technique in this regard. Key words: Laser, power bleaching, tooth color introduction.

Comparison of Two Surface Contamination Sampling Techniques Conducted for the Characterization of Two Pajarito Site Manhattan Project National Historic Park Properties

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

Lopez, Tammy Ann

Technical Area-18 (TA-18), also known as Pajarito Site, is located on Los Alamos National Laboratory property and has historic buildings that will be included in the Manhattan Project National Historic Park. Characterization studies of metal contamination were needed in two of the four buildings that are on the historic registry in this area, a “battleship” bunker building (TA-18-0002) and the Pond cabin (TA-18-0029). However, these two buildings have been exposed to the elements, are decades old, and have porous and rough surfaces (wood and concrete). Due to these conditions, it was questioned whether standard wipe sampling would be adequate tomore » detect surface dust metal contamination in these buildings. Thus, micro-vacuum and surface wet wipe sampling techniques were performed side-by-side at both buildings and results were compared statistically. A two-tail paired t-test revealed that the micro-vacuum and wet wipe techniques were statistically different for both buildings. Further mathematical analysis revealed that the wet wipe technique picked up more metals from the surface than the microvacuum technique. Wet wipes revealed concentrations of beryllium and lead above internal housekeeping limits; however, using an yttrium normalization method with linear regression analysis between beryllium and yttrium revealed a correlation indicating that the beryllium levels were likely due to background and not operational contamination. PPE and administrative controls were implemented for National Park Service (NPS) and Department of Energy (DOE) tours as a result of this study. Overall, this study indicates that the micro-vacuum technique may not be an efficient technique to sample for metal dust contamination.« less

Does size matter? Statistical limits of paleomagnetic field reconstruction from small rock specimens

NASA Astrophysics Data System (ADS)

Berndt, Thomas; Muxworthy, Adrian R.; Fabian, Karl

2016-01-01

As samples of ever decreasing sizes are being studied paleomagnetically, care has to be taken that the underlying assumptions of statistical thermodynamics (Maxwell-Boltzmann statistics) are being met. Here we determine how many grains and how large a magnetic moment a sample needs to have to be able to accurately record an ambient field. It is found that for samples with a thermoremanent magnetic moment larger than 10-11Am2 the assumption of a sufficiently large number of grains is usually given. Standard 25 mm diameter paleomagnetic samples usually contain enough magnetic grains such that statistical errors are negligible, but "single silicate crystal" works on, for example, zircon, plagioclase, and olivine crystals are approaching the limits of what is physically possible, leading to statistic errors in both the angular deviation and paleointensity that are comparable to other sources of error. The reliability of nanopaleomagnetic imaging techniques capable of resolving individual grains (used, for example, to study the cloudy zone in meteorites), however, is questionable due to the limited area of the material covered.

Inventory and mapping of flood inundation using interactive digital image analysis techniques

USGS Publications Warehouse

Rohde, Wayne G.; Nelson, Charles A.; Taranik, J.V.

1979-01-01

LANDSAT digital data and color infra-red photographs were used in a multiphase sampling scheme to estimate the area of agricultural land affected by a flood. The LANDSAT data were classified with a maximum likelihood algorithm. Stratification of the LANDSAT data, prior to classification, greatly reduced misclassification errors. The classification results were used to prepare a map overlay showing the areal extent of flooding. These data also provided statistics required to estimate sample size in a two phase sampling scheme, and provided quick, accurate estimates of areas flooded for the first phase. The measurements made in the second phase, based on ground data and photo-interpretation, were used with two phase sampling statistics to estimate the area of agricultural land affected by flooding These results show that LANDSAT digital data can be used to prepare map overlays showing the extent of flooding on agricultural land and, with two phase sampling procedures, can provide acreage estimates with sampling errors of about 5 percent. This procedure provides a technique for rapidly assessing the areal extent of flood conditions on agricultural land and would provide a basis for designing a sampling framework to estimate the impact of flooding on crop production.

Evaluation of Three Different Processing Techniques in the Fabrication of Complete Dentures

PubMed Central

Chintalacheruvu, Vamsi Krishna; Balraj, Rajasekaran Uttukuli; Putchala, Lavanya Sireesha; Pachalla, Sreelekha

2017-01-01

Aims and Objectives: The objective of the present study is to compare the effectiveness of three different processing techniques and to find out the accuracy of processing techniques through number of occlusal interferences and increase in vertical dimension after denture processing. Materials and Methods: A cross-sectional study was conducted on a sample of 18 patients indicated for complete denture fabrication was selected for the study and they were divided into three subgroups. Three processing techniques, compression molding and injection molding using prepolymerized resin and unpolymerized resin, were used to fabricate dentures for each of the groups. After processing, laboratory-remounted dentures were evaluated for number of occlusal interferences in centric and eccentric relations and change in vertical dimension through vertical pin rise in articulator. Data were analyzed using statistical test ANOVA and SPSS software version 19.0 by IBM was used. Results: Data obtained from three groups were subjected to one-way ANOVA test. After ANOVA test, results with significant variations were subjected to post hoc test. Number of occlusal interferences with compression molding technique was reported to be more in both centric and eccentric positions as compared to the two injection molding techniques with statistical significance in centric, protrusive, right lateral nonworking, and left lateral working positions (P < 0.05). Mean vertical pin rise (0.52 mm) was reported to more in compression molding technique as compared to injection molding techniques, which is statistically significant (P < 0.001). Conclusions: Within the limitations of this study, injection molding techniques exhibited less processing errors as compared to compression molding technique with statistical significance. There was no statistically significant difference in processing errors reported within two injection molding systems. PMID:28713763

Evaluation of Three Different Processing Techniques in the Fabrication of Complete Dentures.

PubMed

Chintalacheruvu, Vamsi Krishna; Balraj, Rajasekaran Uttukuli; Putchala, Lavanya Sireesha; Pachalla, Sreelekha

2017-06-01

The objective of the present study is to compare the effectiveness of three different processing techniques and to find out the accuracy of processing techniques through number of occlusal interferences and increase in vertical dimension after denture processing. A cross-sectional study was conducted on a sample of 18 patients indicated for complete denture fabrication was selected for the study and they were divided into three subgroups. Three processing techniques, compression molding and injection molding using prepolymerized resin and unpolymerized resin, were used to fabricate dentures for each of the groups. After processing, laboratory-remounted dentures were evaluated for number of occlusal interferences in centric and eccentric relations and change in vertical dimension through vertical pin rise in articulator. Data were analyzed using statistical test ANOVA and SPSS software version 19.0 by IBM was used. Data obtained from three groups were subjected to one-way ANOVA test. After ANOVA test, results with significant variations were subjected to post hoc test. Number of occlusal interferences with compression molding technique was reported to be more in both centric and eccentric positions as compared to the two injection molding techniques with statistical significance in centric, protrusive, right lateral nonworking, and left lateral working positions ( P < 0.05). Mean vertical pin rise (0.52 mm) was reported to more in compression molding technique as compared to injection molding techniques, which is statistically significant ( P < 0.001). Within the limitations of this study, injection molding techniques exhibited less processing errors as compared to compression molding technique with statistical significance. There was no statistically significant difference in processing errors reported within two injection molding systems.

Analyzing thematic maps and mapping for accuracy

USGS Publications Warehouse

Rosenfield, G.H.

1982-01-01

Two problems which exist while attempting to test the accuracy of thematic maps and mapping are: (1) evaluating the accuracy of thematic content, and (2) evaluating the effects of the variables on thematic mapping. Statistical analysis techniques are applicable to both these problems and include techniques for sampling the data and determining their accuracy. In addition, techniques for hypothesis testing, or inferential statistics, are used when comparing the effects of variables. A comprehensive and valid accuracy test of a classification project, such as thematic mapping from remotely sensed data, includes the following components of statistical analysis: (1) sample design, including the sample distribution, sample size, size of the sample unit, and sampling procedure; and (2) accuracy estimation, including estimation of the variance and confidence limits. Careful consideration must be given to the minimum sample size necessary to validate the accuracy of a given. classification category. The results of an accuracy test are presented in a contingency table sometimes called a classification error matrix. Usually the rows represent the interpretation, and the columns represent the verification. The diagonal elements represent the correct classifications. The remaining elements of the rows represent errors by commission, and the remaining elements of the columns represent the errors of omission. For tests of hypothesis that compare variables, the general practice has been to use only the diagonal elements from several related classification error matrices. These data are arranged in the form of another contingency table. The columns of the table represent the different variables being compared, such as different scales of mapping. The rows represent the blocking characteristics, such as the various categories of classification. The values in the cells of the tables might be the counts of correct classification or the binomial proportions of these counts divided by either the row totals or the column totals from the original classification error matrices. In hypothesis testing, when the results of tests of multiple sample cases prove to be significant, some form of statistical test must be used to separate any results that differ significantly from the others. In the past, many analyses of the data in this error matrix were made by comparing the relative magnitudes of the percentage of correct classifications, for either individual categories, the entire map or both. More rigorous analyses have used data transformations and (or) two-way classification analysis of variance. A more sophisticated step of data analysis techniques would be to use the entire classification error matrices using the methods of discrete multivariate analysis or of multiviariate analysis of variance.

MANCOVA for one way classification with homogeneity of regression coefficient vectors

NASA Astrophysics Data System (ADS)

Mokesh Rayalu, G.; Ravisankar, J.; Mythili, G. Y.

2017-11-01

The MANOVA and MANCOVA are the extensions of the univariate ANOVA and ANCOVA techniques to multidimensional or vector valued observations. The assumption of a Gaussian distribution has been replaced with the Multivariate Gaussian distribution for the vectors data and residual term variables in the statistical models of these techniques. The objective of MANCOVA is to determine if there are statistically reliable mean differences that can be demonstrated between groups later modifying the newly created variable. When randomization assignment of samples or subjects to groups is not possible, multivariate analysis of covariance (MANCOVA) provides statistical matching of groups by adjusting dependent variables as if all subjects scored the same on the covariates. In this research article, an extension has been made to the MANCOVA technique with more number of covariates and homogeneity of regression coefficient vectors is also tested.

[Statistical analysis of German radiologic periodicals: developmental trends in the last 10 years].

PubMed

Golder, W

1999-09-01

To identify which statistical tests are applied in German radiological publications, to what extent their use has changed during the last decade, and which factors might be responsible for this development. The major articles published in "ROFO" and "DER RADIOLOGE" during 1988, 1993 and 1998 were reviewed for statistical content. The contributions were classified by principal focus and radiological subspecialty. The methods used were assigned to descriptive, basal and advanced statistics. Sample size, significance level and power were established. The use of experts' assistance was monitored. Finally, we calculated the so-called cumulative accessibility of the publications. 525 contributions were found to be eligible. In 1988, 87% used descriptive statistics only, 12.5% basal, and 0.5% advanced statistics. The corresponding figures in 1993 and 1998 are 62 and 49%, 32 and 41%, and 6 and 10%, respectively. Statistical techniques were most likely to be used in research on musculoskeletal imaging and articles dedicated to MRI. Six basic categories of statistical methods account for the complete statistical analysis appearing in 90% of the articles. ROC analysis is the single most common advanced technique. Authors make increasingly use of statistical experts' opinion and programs. During the last decade, the use of statistical methods in German radiological journals has fundamentally improved, both quantitatively and qualitatively. Presently, advanced techniques account for 20% of the pertinent statistical tests. This development seems to be promoted by the increasing availability of statistical analysis software.

Passive fit and accuracy of three dental implant impression techniques.

PubMed

Al Quran, Firas A; Rashdan, Bashar A; Zomar, AbdelRahman A Abu; Weiner, Saul

2012-02-01

To reassess the accuracy of three impression techniques relative to the passive fit of the prosthesis. An edentulous maxillary cast was fabricated in epoxy resin with four dental implants embedded and secured with heat-cured acrylic resin. Three techniques were tested: closed tray, open tray nonsplinted, and open tray splinted. One light-cured custom acrylic tray was fabricated for each impression technique, and transfer copings were attached to the implants. Fifteen impressions for each technique were prepared with medium-bodied consistency polyether. Subsequently, the impressions were poured in type IV die stone. The distances between the implants were measured using a digital micrometer. The statistical analysis of the data was performed with ANOVA and a one-sample t test at a 95% confidence interval. The lowest mean difference in dimensional accuracy was found within the direct (open tray) splinted technique. Also, the one-sample t test showed that the direct splinted technique has the least statistical significant difference from direct nonsplinted and indirect (closed tray) techniques. All discrepancies were less than 100 Μm. Within the limitations of this study, the best accuracy of the definitive prosthesis was achieved when the impression copings were splinted with autopolymerized acrylic resin, sectioned, and rejoined. However, the errors associated with all of these techniques were less than 100 Μm, and based on the current definitions of passive fit, they all would be clinically acceptable.

Variation of Water Quality Parameters with Siltation Depth for River Ichamati Along International Border with Bangladesh Using Multivariate Statistical Techniques

NASA Astrophysics Data System (ADS)

Roy, P. K.; Pal, S.; Banerjee, G.; Biswas Roy, M.; Ray, D.; Majumder, A.

2014-12-01

River is considered as one of the main sources of freshwater all over the world. Hence analysis and maintenance of this water resource is globally considered a matter of major concern. This paper deals with the assessment of surface water quality of the Ichamati river using multivariate statistical techniques. Eight distinct surface water quality observation stations were located and samples were collected. For the samples collected statistical techniques were applied to the physico-chemical parameters and depth of siltation. In this paper cluster analysis is done to determine the relations between surface water quality and siltation depth of river Ichamati. Multiple regressions and mathematical equation modeling have been done to characterize surface water quality of Ichamati river on the basis of physico-chemical parameters. It was found that surface water quality of the downstream river was different from the water quality of the upstream. The analysis of the water quality parameters of the Ichamati river clearly indicate high pollution load on the river water which can be accounted to agricultural discharge, tidal effect and soil erosion. The results further reveal that with the increase in depth of siltation, water quality degraded.

[Comparison between rapid detection method of enzyme substrate technique and multiple-tube fermentation technique in water coliform bacteria detection].

PubMed

Sun, Zong-ke; Wu, Rong; Ding, Pei; Xue, Jin-Rong

2006-07-01

To compare between rapid detection method of enzyme substrate technique and multiple-tube fermentation technique in water coliform bacteria detection. Using inoculated and real water samples to compare the equivalence and false positive rate between two methods. Results demonstrate that enzyme substrate technique shows equivalence with multiple-tube fermentation technique (P = 0.059), false positive rate between the two methods has no statistical difference. It is suggested that enzyme substrate technique can be used as a standard method for water microbiological safety evaluation.

Frontiers of Two-Dimensional Correlation Spectroscopy. Part 1. New concepts and noteworthy developments

NASA Astrophysics Data System (ADS)

Noda, Isao

2014-07-01

A comprehensive survey review of new and noteworthy developments, which are advancing forward the frontiers in the field of 2D correlation spectroscopy during the last four years, is compiled. This review covers books, proceedings, and review articles published on 2D correlation spectroscopy, a number of significant conceptual developments in the field, data pretreatment methods and other pertinent topics, as well as patent and publication trends and citation activities. Developments discussed include projection 2D correlation analysis, concatenated 2D correlation, and correlation under multiple perturbation effects, as well as orthogonal sample design, predicting 2D correlation spectra, manipulating and comparing 2D spectra, correlation strategy based on segmented data blocks, such as moving-window analysis, features like determination of sequential order and enhanced spectral resolution, statistical 2D spectroscopy using covariance and other statistical metrics, hetero-correlation analysis, and sample-sample correlation technique. Data pretreatment operations prior to 2D correlation analysis are discussed, including the correction for physical effects, background and baseline subtraction, selection of reference spectrum, normalization and scaling of data, derivatives spectra and deconvolution technique, and smoothing and noise reduction. Other pertinent topics include chemometrics and statistical considerations, peak position shift phenomena, variable sampling increments, computation and software, display schemes, such as color coded format, slice and power spectra, tabulation, and other schemes.

Arsenic health risk assessment in drinking water and source apportionment using multivariate statistical techniques in Kohistan region, northern Pakistan.

PubMed

Muhammad, Said; Tahir Shah, M; Khan, Sardar

2010-10-01

The present study was conducted in Kohistan region, where mafic and ultramafic rocks (Kohistan island arc and Indus suture zone) and metasedimentary rocks (Indian plate) are exposed. Water samples were collected from the springs, streams and Indus river and analyzed for physical parameters, anions, cations and arsenic (As(3+), As(5+) and arsenic total). The water quality in Kohistan region was evaluated by comparing the physio-chemical parameters with permissible limits set by Pakistan environmental protection agency and world health organization. Most of the studied parameters were found within their respective permissible limits. However in some samples, the iron and arsenic concentrations exceeded their permissible limits. For health risk assessment of arsenic, the average daily dose, hazards quotient (HQ) and cancer risk were calculated by using statistical formulas. The values of HQ were found >1 in the samples collected from Jabba, Dubair, while HQ values were <1 in rest of the samples. This level of contamination should have low chronic risk and medium cancer risk when compared with US EPA guidelines. Furthermore, the inter-dependence of physio-chemical parameters and pollution load was also calculated by using multivariate statistical techniques like one-way ANOVA, correlation analysis, regression analysis, cluster analysis and principle component analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

Neutron/Gamma-ray discrimination through measures of fit

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

Amiri, Moslem; Prenosil, Vaclav; Cvachovec, Frantisek

2015-07-01

Statistical tests and their underlying measures of fit can be utilized to separate neutron/gamma-ray pulses in a mixed radiation field. In this article, first the application of a sample statistical test is explained. Fit measurement-based methods require true pulse shapes to be used as reference for discrimination. This requirement makes practical implementation of these methods difficult; typically another discrimination approach should be employed to capture samples of neutrons and gamma-rays before running the fit-based technique. In this article, we also propose a technique to eliminate this requirement. These approaches are applied to several sets of mixed neutron and gamma-ray pulsesmore » obtained through different digitizers using stilbene scintillator in order to analyze them and measure their discrimination quality. (authors)« less

Statistical differences between relative quantitative molecular fingerprints from microbial communities.

PubMed

Portillo, M C; Gonzalez, J M

2008-08-01

Molecular fingerprints of microbial communities are a common method for the analysis and comparison of environmental samples. The significance of differences between microbial community fingerprints was analyzed considering the presence of different phylotypes and their relative abundance. A method is proposed by simulating coverage of the analyzed communities as a function of sampling size applying a Cramér-von Mises statistic. Comparisons were performed by a Monte Carlo testing procedure. As an example, this procedure was used to compare several sediment samples from freshwater ponds using a relative quantitative PCR-DGGE profiling technique. The method was able to discriminate among different samples based on their molecular fingerprints, and confirmed the lack of differences between aliquots from a single sample.

Fragment size distribution statistics in dynamic fragmentation of laser shock-loaded tin

NASA Astrophysics Data System (ADS)

He, Weihua; Xin, Jianting; Zhao, Yongqiang; Chu, Genbai; Xi, Tao; Shui, Min; Lu, Feng; Gu, Yuqiu

2017-06-01

This work investigates the geometric statistics method to characterize the size distribution of tin fragments produced in the laser shock-loaded dynamic fragmentation process. In the shock experiments, the ejection of the tin sample with etched V-shape groove in the free surface are collected by the soft recovery technique. Subsequently, the produced fragments are automatically detected with the fine post-shot analysis techniques including the X-ray micro-tomography and the improved watershed method. To characterize the size distributions of the fragments, a theoretical random geometric statistics model based on Poisson mixtures is derived for dynamic heterogeneous fragmentation problem, which reveals linear combinational exponential distribution. The experimental data related to fragment size distributions of the laser shock-loaded tin sample are examined with the proposed theoretical model, and its fitting performance is compared with that of other state-of-the-art fragment size distribution models. The comparison results prove that our proposed model can provide far more reasonable fitting result for the laser shock-loaded tin.

Statistics of Crack Growth in Engine Materials. Volume 2. Spectrum Loading and advanced Techniques

DTIC Science & Technology

1984-02-01

Histories of Some WPB Fastener H oles ..................................................................................... 66 51 Typical Sample Function of...Computed Directly from Some Actual Time- Histories of W PB Fastener Holes ................................................................ 77 56 Simulated...Sample Functions of Crack Propagation Time- Histories for W PB Fastener Holes ................................................................ 78 57

Hydrogeology and water quality of glacial-drift aquifers in the Bemidji-Bagley area, Beltrami, Clearwater, Cass, and Hubbard counties, Minnesota

USGS Publications Warehouse

Stark, J.R.; Busch, J.P.; Deters, M.H.

1991-01-01

The Kruskil-Wallis test, a nonparametric that for 12 of the 21 constituents sampled in groups in the unconfined-drift aquifer, a of these constituents and land use was found statistical technique, indicated common in all land-use type relation between the concentration to be statistically significant.

Statistical techniques for sampling and monitoring natural resources

Treesearch

Hans T. Schreuder; Richard Ernst; Hugo Ramirez-Maldonado

2004-01-01

We present the statistical theory of inventory and monitoring from a probabilistic point of view. We start with the basics and show the interrelationships between designs and estimators illustrating the methods with a small artificial population as well as with a mapped realistic population. For such applications, useful open source software is given in Appendix 4....

Simulation and statistics: Like rhythm and song

NASA Astrophysics Data System (ADS)

Othman, Abdul Rahman

2013-04-01

Simulation has been introduced to solve problems in the form of systems. By using this technique the following two problems can be overcome. First, a problem that has an analytical solution but the cost of running an experiment to solve is high in terms of money and lives. Second, a problem exists but has no analytical solution. In the field of statistical inference the second problem is often encountered. With the advent of high-speed computing devices, a statistician can now use resampling techniques such as the bootstrap and permutations to form pseudo sampling distribution that will lead to the solution of the problem that cannot be solved analytically. This paper discusses how a Monte Carlo simulation was and still being used to verify the analytical solution in inference. This paper also discusses the resampling techniques as simulation techniques. The misunderstandings about these two techniques are examined. The successful usages of both techniques are also explained.

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

PubMed

Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

2011-06-01

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

Preliminary statistical studies concerning the Campos RJ sugar cane area, using LANDSAT imagery and aerial photographs

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Costa, S. R. X.; Paiao, L. B. F.; Mendonca, F. J.; Shimabukuro, Y. E.; Duarte, V.

1983-01-01

The two phase sampling technique was applied to estimate the area cultivated with sugar cane in an approximately 984 sq km pilot region of Campos. Correlation between existing aerial photography and LANDSAT data was used. The two phase sampling technique corresponded to 99.6% of the results obtained by aerial photography, taken as ground truth. This estimate has a standard deviation of 225 ha, which constitutes a coefficient of variation of 0.6%.

Sampling western spruce budworm by counting larvae on lower crown branches.

Treesearch

R.R. Mason; B.E. Wickman; H.G. Paul

1989-01-01

A technique is described for sampling spruce budworm larvae after bud flush by nondestructively beating branches in the lower crown. Sample data were collected from 32 plots representing a wide range of budworm densities. Statistical analyses indicated that larvae were less aggregated in the lower crown than at the same density in the middle crown. In an independent...

Water quality analysis of the Rapur area, Andhra Pradesh, South India using multivariate techniques

NASA Astrophysics Data System (ADS)

Nagaraju, A.; Sreedhar, Y.; Thejaswi, A.; Sayadi, Mohammad Hossein

2017-10-01

The groundwater samples from Rapur area were collected from different sites to evaluate the major ion chemistry. The large number of data can lead to difficulties in the integration, interpretation, and representation of the results. Two multivariate statistical methods, hierarchical cluster analysis (HCA) and factor analysis (FA), were applied to evaluate their usefulness to classify and identify geochemical processes controlling groundwater geochemistry. Four statistically significant clusters were obtained from 30 sampling stations. This has resulted two important clusters viz., cluster 1 (pH, Si, CO3, Mg, SO4, Ca, K, HCO3, alkalinity, Na, Na + K, Cl, and hardness) and cluster 2 (EC and TDS) which are released to the study area from different sources. The application of different multivariate statistical techniques, such as principal component analysis (PCA), assists in the interpretation of complex data matrices for a better understanding of water quality of a study area. From PCA, it is clear that the first factor (factor 1), accounted for 36.2% of the total variance, was high positive loading in EC, Mg, Cl, TDS, and hardness. Based on the PCA scores, four significant cluster groups of sampling locations were detected on the basis of similarity of their water quality.

Statistical classification techniques for engineering and climatic data samples

NASA Technical Reports Server (NTRS)

Temple, E. C.; Shipman, J. R.

1981-01-01

Fisher's sample linear discriminant function is modified through an appropriate alteration of the common sample variance-covariance matrix. The alteration consists of adding nonnegative values to the eigenvalues of the sample variance covariance matrix. The desired results of this modification is to increase the number of correct classifications by the new linear discriminant function over Fisher's function. This study is limited to the two-group discriminant problem.

Imaging Extended Emission-Line Regions of Obscured AGN with the Subaru Hyper Suprime-Cam Survey

NASA Astrophysics Data System (ADS)

Sun, Ai-Lei; Greene, Jenny E.; Zakamska, Nadia L.; Goulding, Andy; Strauss, Michael A.; Huang, Song; Johnson, Sean; Kawaguchi, Toshihiro; Matsuoka, Yoshiki; Marsteller, Alisabeth A.; Nagao, Tohru; Toba, Yoshiki

2018-05-01

Narrow-line regions excited by active galactic nuclei (AGN) are important for studying AGN photoionization and feedback. Their strong [O III] lines can be detected with broadband images, allowing morphological studies of these systems with large-area imaging surveys. We develop a new broad-band imaging technique to reconstruct the images of the [O III] line using the Subaru Hyper Suprime-Cam (HSC) Survey aided with spectra from the Sloan Digital Sky Survey (SDSS). The technique involves a careful subtraction of the galactic continuum to isolate emission from the [O III]λ5007 and [O III]λ4959 lines. Compared to traditional targeted observations, this technique is more efficient at covering larger samples without dedicated observational resources. We apply this technique to an SDSS spectroscopically selected sample of 300 obscured AGN at redshifts 0.1 - 0.7, uncovering extended emission-line region candidates with sizes up to tens of kpc. With the largest sample of uniformly derived narrow-line region sizes, we revisit the narrow-line region size - luminosity relation. The area and radii of the [O III] emission-line regions are strongly correlated with the AGN luminosity inferred from the mid-infrared (15 μm rest-frame) with a power-law slope of 0.62^{+0.05}_{-0.06}± 0.10 (statistical and systematic errors), consistent with previous spectroscopic findings. We discuss the implications for the physics of AGN emission-line regions and future applications of this technique, which should be useful for current and next-generation imaging surveys to study AGN photoionization and feedback with large statistical samples.

Smart Sampling and HPC-based Probabilistic Look-ahead Contingency Analysis Implementation and its Evaluation with Real-world Data

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

Chen, Yousu; Etingov, Pavel V.; Ren, Huiying

This paper describes a probabilistic look-ahead contingency analysis application that incorporates smart sampling and high-performance computing (HPC) techniques. Smart sampling techniques are implemented to effectively represent the structure and statistical characteristics of uncertainty introduced by different sources in the power system. They can significantly reduce the data set size required for multiple look-ahead contingency analyses, and therefore reduce the time required to compute them. High-performance-computing (HPC) techniques are used to further reduce computational time. These two techniques enable a predictive capability that forecasts the impact of various uncertainties on potential transmission limit violations. The developed package has been tested withmore » real world data from the Bonneville Power Administration. Case study results are presented to demonstrate the performance of the applications developed.« less

Influence of manufacturing parameters on the strength of PLA parts using Layered Manufacturing technique: A statistical approach

NASA Astrophysics Data System (ADS)

Jaya Christiyan, K. G.; Chandrasekhar, U.; Mathivanan, N. Rajesh; Venkateswarlu, K.

2018-02-01

A 3D printing was successfully used to fabricate samples of Polylactic Acid (PLA). Processing parameters such as Lay-up speed, Lay-up thickness, and printing nozzle were varied. All samples were tested for flexural strength using three point load test. A statistical mathematical model was developed to correlate the processing parameters with flexural strength. The result clearly demonstrated that the lay-up thickness and nozzle diameter influenced flexural strength significantly, whereas lay-up speed hardly influenced the flexural strength.

The intercrater plains of Mercury and the Moon: Their nature, origin and role in terrestrial planet evolution. Measurement and errors of crater statistics. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Leake, M. A.

1982-01-01

Planetary imagery techniques, errors in measurement or degradation assignment, and statistical formulas are presented with respect to cratering data. Base map photograph preparation, measurement of crater diameters and sampled area, and instruments used are discussed. Possible uncertainties, such as Sun angle, scale factors, degradation classification, and biases in crater recognition are discussed. The mathematical formulas used in crater statistics are presented.

Experimental toxicology: Issues of statistics, experimental design, and replication.

PubMed

Briner, Wayne; Kirwan, Jeral

2017-01-01

The difficulty of replicating experiments has drawn considerable attention. Issues with replication occur for a variety of reasons ranging from experimental design to laboratory errors to inappropriate statistical analysis. Here we review a variety of guidelines for statistical analysis, design, and execution of experiments in toxicology. In general, replication can be improved by using hypothesis driven experiments with adequate sample sizes, randomization, and blind data collection techniques. Copyright © 2016 Elsevier B.V. All rights reserved.

Statistical Techniques For Real-time Anomaly Detection Using Spark Over Multi-source VMware Performance Data

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

Solaimani, Mohiuddin; Iftekhar, Mohammed; Khan, Latifur

Anomaly detection refers to the identi cation of an irregular or unusual pat- tern which deviates from what is standard, normal, or expected. Such deviated patterns typically correspond to samples of interest and are assigned different labels in different domains, such as outliers, anomalies, exceptions, or malware. Detecting anomalies in fast, voluminous streams of data is a formidable chal- lenge. This paper presents a novel, generic, real-time distributed anomaly detection framework for heterogeneous streaming data where anomalies appear as a group. We have developed a distributed statistical approach to build a model and later use it to detect anomaly. Asmore » a case study, we investigate group anomaly de- tection for a VMware-based cloud data center, which maintains a large number of virtual machines (VMs). We have built our framework using Apache Spark to get higher throughput and lower data processing time on streaming data. We have developed a window-based statistical anomaly detection technique to detect anomalies that appear sporadically. We then relaxed this constraint with higher accuracy by implementing a cluster-based technique to detect sporadic and continuous anomalies. We conclude that our cluster-based technique out- performs other statistical techniques with higher accuracy and lower processing time.« less

An Analysis of Variance Framework for Matrix Sampling.

ERIC Educational Resources Information Center

Sirotnik, Kenneth

Significant cost savings can be achieved with the use of matrix sampling in estimating population parameters from psychometric data. The statistical design is intuitively simple, using the framework of the two-way classification analysis of variance technique. For example, the mean and variance are derived from the performance of a certain grade…

Unbiased, scalable sampling of protein loop conformations from probabilistic priors.

PubMed

Zhang, Yajia; Hauser, Kris

2013-01-01

Protein loops are flexible structures that are intimately tied to function, but understanding loop motion and generating loop conformation ensembles remain significant computational challenges. Discrete search techniques scale poorly to large loops, optimization and molecular dynamics techniques are prone to local minima, and inverse kinematics techniques can only incorporate structural preferences in adhoc fashion. This paper presents Sub-Loop Inverse Kinematics Monte Carlo (SLIKMC), a new Markov chain Monte Carlo algorithm for generating conformations of closed loops according to experimentally available, heterogeneous structural preferences. Our simulation experiments demonstrate that the method computes high-scoring conformations of large loops (>10 residues) orders of magnitude faster than standard Monte Carlo and discrete search techniques. Two new developments contribute to the scalability of the new method. First, structural preferences are specified via a probabilistic graphical model (PGM) that links conformation variables, spatial variables (e.g., atom positions), constraints and prior information in a unified framework. The method uses a sparse PGM that exploits locality of interactions between atoms and residues. Second, a novel method for sampling sub-loops is developed to generate statistically unbiased samples of probability densities restricted by loop-closure constraints. Numerical experiments confirm that SLIKMC generates conformation ensembles that are statistically consistent with specified structural preferences. Protein conformations with 100+ residues are sampled on standard PC hardware in seconds. Application to proteins involved in ion-binding demonstrate its potential as a tool for loop ensemble generation and missing structure completion.

Unbiased, scalable sampling of protein loop conformations from probabilistic priors

PubMed Central

2013-01-01

Background Protein loops are flexible structures that are intimately tied to function, but understanding loop motion and generating loop conformation ensembles remain significant computational challenges. Discrete search techniques scale poorly to large loops, optimization and molecular dynamics techniques are prone to local minima, and inverse kinematics techniques can only incorporate structural preferences in adhoc fashion. This paper presents Sub-Loop Inverse Kinematics Monte Carlo (SLIKMC), a new Markov chain Monte Carlo algorithm for generating conformations of closed loops according to experimentally available, heterogeneous structural preferences. Results Our simulation experiments demonstrate that the method computes high-scoring conformations of large loops (>10 residues) orders of magnitude faster than standard Monte Carlo and discrete search techniques. Two new developments contribute to the scalability of the new method. First, structural preferences are specified via a probabilistic graphical model (PGM) that links conformation variables, spatial variables (e.g., atom positions), constraints and prior information in a unified framework. The method uses a sparse PGM that exploits locality of interactions between atoms and residues. Second, a novel method for sampling sub-loops is developed to generate statistically unbiased samples of probability densities restricted by loop-closure constraints. Conclusion Numerical experiments confirm that SLIKMC generates conformation ensembles that are statistically consistent with specified structural preferences. Protein conformations with 100+ residues are sampled on standard PC hardware in seconds. Application to proteins involved in ion-binding demonstrate its potential as a tool for loop ensemble generation and missing structure completion. PMID:24565175

Field Penetration in a Rectangular Box Using Numerical Techniques: An Effort to Obtain Statistical Shielding Effectiveness

NASA Technical Reports Server (NTRS)

Bunting, Charles F.; Yu, Shih-Pin

2006-01-01

This paper emphasizes the application of numerical methods to explore the ideas related to shielding effectiveness from a statistical view. An empty rectangular box is examined using a hybrid modal/moment method. The basic computational method is presented followed by the results for single- and multiple observation points within the over-moded empty structure. The statistics of the field are obtained by using frequency stirring, borrowed from the ideas connected with reverberation chamber techniques, and extends the ideas of shielding effectiveness well into the multiple resonance regions. The study presented in this paper will address the average shielding effectiveness over a broad spatial sample within the enclosure as the frequency is varied.

Evaluating JTPA Programs for Economically Disadvantaged Adults: A Case Study of Utah and General Findings. Research Report No. 92-02.

ERIC Educational Resources Information Center

Bowman, William R.

A study examined the feasibility of using a "nonexperimental" technique to evaluate Job Training Partnership Act (JTPA) programs for economically disadvantaged adults. New statistical techniques were applied to data about a sample of Utah JTPA participants and data about Employment Security registrants linked with their individual…

Classification of bladder cancer cell lines using Raman spectroscopy: a comparison of excitation wavelength, sample substrate and statistical algorithms

NASA Astrophysics Data System (ADS)

Kerr, Laura T.; Adams, Aine; O'Dea, Shirley; Domijan, Katarina; Cullen, Ivor; Hennelly, Bryan M.

2014-05-01

Raman microspectroscopy can be applied to the urinary bladder for highly accurate classification and diagnosis of bladder cancer. This technique can be applied in vitro to bladder epithelial cells obtained from urine cytology or in vivo as an optical biopsy" to provide results in real-time with higher sensitivity and specificity than current clinical methods. However, there exists a high degree of variability across experimental parameters which need to be standardised before this technique can be utilized in an everyday clinical environment. In this study, we investigate different laser wavelengths (473 nm and 532 nm), sample substrates (glass, fused silica and calcium fluoride) and multivariate statistical methods in order to gain insight into how these various experimental parameters impact on the sensitivity and specificity of Raman cytology.

Chemometric and multivariate statistical analysis of time-of-flight secondary ion mass spectrometry spectra from complex Cu-Fe sulfides.

PubMed

Kalegowda, Yogesh; Harmer, Sarah L

2012-03-20

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) spectra of mineral samples are complex, comprised of large mass ranges and many peaks. Consequently, characterization and classification analysis of these systems is challenging. In this study, different chemometric and statistical data evaluation methods, based on monolayer sensitive TOF-SIMS data, have been tested for the characterization and classification of copper-iron sulfide minerals (chalcopyrite, chalcocite, bornite, and pyrite) at different flotation pulp conditions (feed, conditioned feed, and Eh modified). The complex mass spectral data sets were analyzed using the following chemometric and statistical techniques: principal component analysis (PCA); principal component-discriminant functional analysis (PC-DFA); soft independent modeling of class analogy (SIMCA); and k-Nearest Neighbor (k-NN) classification. PCA was found to be an important first step in multivariate analysis, providing insight into both the relative grouping of samples and the elemental/molecular basis for those groupings. For samples exposed to oxidative conditions (at Eh ~430 mV), each technique (PCA, PC-DFA, SIMCA, and k-NN) was found to produce excellent classification. For samples at reductive conditions (at Eh ~ -200 mV SHE), k-NN and SIMCA produced the most accurate classification. Phase identification of particles that contain the same elements but a different crystal structure in a mixed multimetal mineral system has been achieved.

Quantification and Statistical Analysis Methods for Vessel Wall Components from Stained Images with Masson's Trichrome

PubMed Central

Hernández-Morera, Pablo; Castaño-González, Irene; Travieso-González, Carlos M.; Mompeó-Corredera, Blanca; Ortega-Santana, Francisco

2016-01-01

Purpose To develop a digital image processing method to quantify structural components (smooth muscle fibers and extracellular matrix) in the vessel wall stained with Masson’s trichrome, and a statistical method suitable for small sample sizes to analyze the results previously obtained. Methods The quantification method comprises two stages. The pre-processing stage improves tissue image appearance and the vessel wall area is delimited. In the feature extraction stage, the vessel wall components are segmented by grouping pixels with a similar color. The area of each component is calculated by normalizing the number of pixels of each group by the vessel wall area. Statistical analyses are implemented by permutation tests, based on resampling without replacement from the set of the observed data to obtain a sampling distribution of an estimator. The implementation can be parallelized on a multicore machine to reduce execution time. Results The methods have been tested on 48 vessel wall samples of the internal saphenous vein stained with Masson’s trichrome. The results show that the segmented areas are consistent with the perception of a team of doctors and demonstrate good correlation between the expert judgments and the measured parameters for evaluating vessel wall changes. Conclusion The proposed methodology offers a powerful tool to quantify some components of the vessel wall. It is more objective, sensitive and accurate than the biochemical and qualitative methods traditionally used. The permutation tests are suitable statistical techniques to analyze the numerical measurements obtained when the underlying assumptions of the other statistical techniques are not met. PMID:26761643

Improved Reference Sampling and Subtraction: A Technique for Reducing the Read Noise of Near-infrared Detector Systems

NASA Astrophysics Data System (ADS)

Rauscher, Bernard J.; Arendt, Richard G.; Fixsen, D. J.; Greenhouse, Matthew A.; Lander, Matthew; Lindler, Don; Loose, Markus; Moseley, S. H.; Mott, D. Brent; Wen, Yiting; Wilson, Donna V.; Xenophontos, Christos

2017-10-01

Near-infrared array detectors, like the James Webb Space Telescope (JWST) NIRSpec’s Teledyne’s H2RGs, often provide reference pixels and a reference output. These are used to remove correlated noise. Improved reference sampling and subtraction (IRS2) is a statistical technique for using this reference information optimally in a least-squares sense. Compared with the traditional H2RG readout, IRS2 uses a different clocking pattern to interleave many more reference pixels into the data than is otherwise possible. Compared with standard reference correction techniques, IRS2 subtracts the reference pixels and reference output using a statistically optimized set of frequency-dependent weights. The benefits include somewhat lower noise variance and much less obvious correlated noise. NIRSpec’s IRS2 images are cosmetically clean, with less 1/f banding than in traditional data from the same system. This article describes the IRS2 clocking pattern and presents the equations needed to use IRS2 in systems other than NIRSpec. For NIRSpec, applying these equations is already an option in the calibration pipeline. As an aid to instrument builders, we provide our prototype IRS2 calibration software and sample JWST NIRSpec data. The same techniques are applicable to other detector systems, including those based on Teledyne’s H4RG arrays. The H4RG’s interleaved reference pixel readout mode is effectively one IRS2 pattern.

Comparison of two non-invasive methods of microbial analysis in surgery practice: incision swabbing and the indirect imprint technique.

PubMed

Chovanec, Zdenek; Veverkova, Lenka; Votava, Miroslav; Svoboda, Jiri; Jedlicka, Vaclav; Capov, Ivan

2014-12-01

A variety of methods exist to take samples from surgical site infections for cultivation; however, an unambiguous and suitable method has not yet been defined. The aim of our retrospective non-randomized study was to compare two non-invasive techniques of sampling material for microbiologic analysis in surgical practice. We compared bacteria cultured from samples obtained with the use of the swab technique, defined in our study as the gold standard, with the indirect imprint technique. A cotton-tipped swab (Copan, Brescia, Italy) was used; the imprints were taken using Whatman no. 4 filter paper (Macherey-Nagal, Duren, Germany) cut into 5×5 cm pieces placed on blood agar in a Petri dish. To culture the microorganisms in the microbiology laboratory, we used blood agar, UriSelect 4 medium (Bio-Rad, Marnes-la-Coquette, France), and a medium with sodium chloride (blood agar with salt). After careful debridement, a sample was taken from the incision surface by swab and subsequently the same area of the surface was imprinted onto filter paper. The samples were analyzed in the microbiology laboratory under standard safety precautions. The cultivation results of the two techniques were processed statistically using contingency tables and the McNemar test. Those samples that were simultaneously cultivation-positive by imprint and -negative by swabbing were processed in greater detail. Over the period between October 2008 and March 2013, 177 samples from 70 patients were analyzed. Sampling was carried out from 42 males and 28 females. One hundred forty-six samples were from incisions after operations (21 samples from six patients after operation on the thoracic cavity, 73 samples from 35 patients after operation on the abdominal cavity combined with the gastrointestinal tract, 52 samples from 19 patients with other surgical site infections not included above) and 31 samples from 11 patients with no post-operative infection. One patient had a sample taken both from a post-operative and a non-post-operative site. Coincidently, the most frequent cultivation finding with both techniques was a sterile one (imprint, 62; swab, 50). The microorganism cultivated most frequently after swabbing was Pseudomonas aeruginosa (22 cases), compared with Escherichia coli when the filter paper (imprint) was used (31 cases). The imprint technique was evaluated as more sensitive compared with swabbing (p=0.0001). The κ statistic used to evaluate the concordance between the two techniques was 0.302. Of the 177 samples there were 53 samples simultaneously sterile using the swab and positive in the imprint. In three samples colony- forming units (CFU) were not counted; 22 samples were within the limit of 0-25×10(1) CFU/cm(2), 20 samples within the limit of 25×10(1)-25×10(2) CFU/cm(2), five within the limit of 25×10(2)-25×10(3) CFU/cm(2), and three of more than 25×10(4) CFU/cm(2). The hypothesis of swabbing as a more precise technique was not confirmed. In our study the imprint technique was more sensitive than swabbing; the strength of agreement was fair. We obtained information not only on the type of the microorganism cultured, but also on the number of viable colonies, expressed in CFU/cm(2).

Steganalysis of recorded speech

NASA Astrophysics Data System (ADS)

Johnson, Micah K.; Lyu, Siwei; Farid, Hany

2005-03-01

Digital audio provides a suitable cover for high-throughput steganography. At 16 bits per sample and sampled at a rate of 44,100 Hz, digital audio has the bit-rate to support large messages. In addition, audio is often transient and unpredictable, facilitating the hiding of messages. Using an approach similar to our universal image steganalysis, we show that hidden messages alter the underlying statistics of audio signals. Our statistical model begins by building a linear basis that captures certain statistical properties of audio signals. A low-dimensional statistical feature vector is extracted from this basis representation and used by a non-linear support vector machine for classification. We show the efficacy of this approach on LSB embedding and Hide4PGP. While no explicit assumptions about the content of the audio are made, our technique has been developed and tested on high-quality recorded speech.

The Importance of Practice in the Development of Statistics.

DTIC Science & Technology

1983-01-01

RESOLUTION TEST CHART NATIONAL BUREAU OIF STANDARDS 1963 -A NRC Technical Summary Report #2471 C THE IMORTANCE OF PRACTICE IN to THE DEVELOPMENT OF STATISTICS...component analysis, bioassay, limits for a ratio, quality control, sampling inspection, non-parametric tests , transformation theory, ARIMA time series...models, sequential tests , cumulative sum charts, data analysis plotting techniques, and a resolution of the Bayes - frequentist controversy. It appears

Changes in sample collection and analytical techniques and effects on retrospective comparability of low-level concentrations of trace elements in ground water

USGS Publications Warehouse

Ivahnenko, T.; Szabo, Z.; Gibs, J.

2001-01-01

Ground-water sampling techniques were modified to reduce random low-level contamination during collection of filtered water samples for determination of trace-element concentrations. The modified sampling techniques were first used in New Jersey by the US Geological Survey in 1994 along with inductively coupled plasma-mass spectrometry (ICP-MS) analysis to determine the concentrations of 18 trace elements at the one microgram-per-liter (μg/L) level in the oxic water of the unconfined sand and gravel Kirkwood-Cohansey aquifer system. The revised technique tested included a combination of the following: collection of samples (1) with flow rates of about 2L per minute, (2) through acid-washed single-use disposable tubing and (3) a single-use disposable 0.45-μm pore size capsule filter, (4) contained within portable glove boxes, (5) in a dedicated clean sampling van, (6) only after turbidity stabilized at values less than 2 nephelometric turbidity units (NTU), when possible. Quality-assurance data, obtained from equipment blanks and split samples, indicated that trace element concentrations, with the exception of iron, chromium, aluminum, and zinc, measured in the samples collected in 1994 were not subject to random contamination at 1μg/L.Results from samples collected in 1994 were compared to those from samples collected in 1991 from the same 12 PVC-cased observation wells using the available sampling and analytical techniques at that time. Concentrations of copper, lead, manganese and zinc were statistically significantly lower in samples collected in 1994 than in 1991. Sampling techniques used in 1994 likely provided trace-element data that represented concentrations in the aquifer with less bias than data from 1991 when samples were collected without the same degree of attention to sample handling.

Using Sieving and Unknown Sand Samples for a Sedimentation-Stratigraphy Class Project with Linkage to Introductory Courses

ERIC Educational Resources Information Center

Videtich, Patricia E.; Neal, William J.

2012-01-01

Using sieving and sample "unknowns" for instructional grain-size analysis and interpretation of sands in undergraduate sedimentology courses has advantages over other techniques. Students (1) learn to calculate and use statistics; (2) visually observe differences in the grain-size fractions, thereby developing a sense of specific size…

A Monte Carlo study of Weibull reliability analysis for space shuttle main engine components

NASA Technical Reports Server (NTRS)

Abernethy, K.

1986-01-01

The incorporation of a number of additional capabilities into an existing Weibull analysis computer program and the results of Monte Carlo computer simulation study to evaluate the usefulness of the Weibull methods using samples with a very small number of failures and extensive censoring are discussed. Since the censoring mechanism inherent in the Space Shuttle Main Engine (SSME) data is hard to analyze, it was decided to use a random censoring model, generating censoring times from a uniform probability distribution. Some of the statistical techniques and computer programs that are used in the SSME Weibull analysis are described. The methods documented in were supplemented by adding computer calculations of approximate (using iteractive methods) confidence intervals for several parameters of interest. These calculations are based on a likelihood ratio statistic which is asymptotically a chisquared statistic with one degree of freedom. The assumptions built into the computer simulations are described. The simulation program and the techniques used in it are described there also. Simulation results are tabulated for various combinations of Weibull shape parameters and the numbers of failures in the samples.

Ensembles of radial basis function networks for spectroscopic detection of cervical precancer

NASA Technical Reports Server (NTRS)

Tumer, K.; Ramanujam, N.; Ghosh, J.; Richards-Kortum, R.

1998-01-01

The mortality related to cervical cancer can be substantially reduced through early detection and treatment. However, current detection techniques, such as Pap smear and colposcopy, fail to achieve a concurrently high sensitivity and specificity. In vivo fluorescence spectroscopy is a technique which quickly, noninvasively and quantitatively probes the biochemical and morphological changes that occur in precancerous tissue. A multivariate statistical algorithm was used to extract clinically useful information from tissue spectra acquired from 361 cervical sites from 95 patients at 337-, 380-, and 460-nm excitation wavelengths. The multivariate statistical analysis was also employed to reduce the number of fluorescence excitation-emission wavelength pairs required to discriminate healthy tissue samples from precancerous tissue samples. The use of connectionist methods such as multilayered perceptrons, radial basis function (RBF) networks, and ensembles of such networks was investigated. RBF ensemble algorithms based on fluorescence spectra potentially provide automated and near real-time implementation of precancer detection in the hands of nonexperts. The results are more reliable, direct, and accurate than those achieved by either human experts or multivariate statistical algorithms.

Logistic regression applied to natural hazards: rare event logistic regression with replications

NASA Astrophysics Data System (ADS)

Guns, M.; Vanacker, V.

2012-06-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

A statistical comparison of two carbon fiber/epoxy fabrication techniques

NASA Technical Reports Server (NTRS)

Hodge, A. J.

1991-01-01

A statistical comparison of the compression strengths of specimens that were fabricated by either a platen press or an autoclave were performed on IM6/3501-6 carbon/epoxy composites of 16-ply (0,+45,90,-45)(sub S2) lay-up configuration. The samples were cured with the same parameters and processing materials. It was found that the autoclaved panels were thicker than the platen press cured samples. Two hundred samples of each type of cure process were compression tested. The autoclaved samples had an average strength of 450 MPa (65.5 ksi), while the press cured samples had an average strength of 370 MPa (54.0 ksi). A Weibull analysis of the data showed that there is only a 30 pct. probability that the two types of cure systems yield specimens that can be considered from the same family.

Spectral analysis of groove spacing on Ganymede

NASA Technical Reports Server (NTRS)

Grimm, R. E.

1984-01-01

The technique used to analyze groove spacing on Ganymede is presented. Data from Voyager images are used determine the surface topography and position of the grooves. Power spectal estimates are statistically analyzed and sample data is included.

Combination of complementary data mining methods for geographical characterization of extra virgin olive oils based on mineral composition.

PubMed

Sayago, Ana; González-Domínguez, Raúl; Beltrán, Rafael; Fernández-Recamales, Ángeles

2018-09-30

This work explores the potential of multi-element fingerprinting in combination with advanced data mining strategies to assess the geographical origin of extra virgin olive oil samples. For this purpose, the concentrations of 55 elements were determined in 125 oil samples from multiple Spanish geographic areas. Several unsupervised and supervised multivariate statistical techniques were used to build classification models and investigate the relationship between mineral composition of olive oils and their provenance. Results showed that Spanish extra virgin olive oils exhibit characteristic element profiles, which can be differentiated on the basis of their origin in accordance with three geographical areas: Atlantic coast (Huelva province), Mediterranean coast and inland regions. Furthermore, statistical modelling yielded high sensitivity and specificity, principally when random forest and support vector machines were employed, thus demonstrating the utility of these techniques in food traceability and authenticity research. Copyright © 2018 Elsevier Ltd. All rights reserved.

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review.

PubMed

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-12-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0-0.10 m, or 0-0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis (PCA) and cluster analysis (CA). Copyright © 2017 Elsevier Ltd. All rights reserved.

Statistical and sampling issues when using multiple particle tracking

NASA Astrophysics Data System (ADS)

Savin, Thierry; Doyle, Patrick S.

2007-08-01

Video microscopy can be used to simultaneously track several microparticles embedded in a complex material. The trajectories are used to extract a sample of displacements at random locations in the material. From this sample, averaged quantities characterizing the dynamics of the probes are calculated to evaluate structural and/or mechanical properties of the assessed material. However, the sampling of measured displacements in heterogeneous systems is singular because the volume of observation with video microscopy is finite. By carefully characterizing the sampling design in the experimental output of the multiple particle tracking technique, we derive estimators for the mean and variance of the probes’ dynamics that are independent of the peculiar statistical characteristics. We expose stringent tests of these estimators using simulated and experimental complex systems with a known heterogeneous structure. Up to a certain fundamental limitation, which we characterize through a material degree of sampling by the embedded probe tracking, these estimators can be applied to quantify the heterogeneity of a material, providing an original and intelligible kind of information on complex fluid properties. More generally, we show that the precise assessment of the statistics in the multiple particle tracking output sample of observations is essential in order to provide accurate unbiased measurements.

Data mining and statistical inference in selective laser melting

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

Kamath, Chandrika

Selective laser melting (SLM) is an additive manufacturing process that builds a complex three-dimensional part, layer-by-layer, using a laser beam to fuse fine metal powder together. The design freedom afforded by SLM comes associated with complexity. As the physical phenomena occur over a broad range of length and time scales, the computational cost of modeling the process is high. At the same time, the large number of parameters that control the quality of a part make experiments expensive. In this paper, we describe ways in which we can use data mining and statistical inference techniques to intelligently combine simulations andmore » experiments to build parts with desired properties. We start with a brief summary of prior work in finding process parameters for high-density parts. We then expand on this work to show how we can improve the approach by using feature selection techniques to identify important variables, data-driven surrogate models to reduce computational costs, improved sampling techniques to cover the design space adequately, and uncertainty analysis for statistical inference. Here, our results indicate that techniques from data mining and statistics can complement those from physical modeling to provide greater insight into complex processes such as selective laser melting.« less

Data mining and statistical inference in selective laser melting

DOE PAGES

Kamath, Chandrika

2016-01-11

Selective laser melting (SLM) is an additive manufacturing process that builds a complex three-dimensional part, layer-by-layer, using a laser beam to fuse fine metal powder together. The design freedom afforded by SLM comes associated with complexity. As the physical phenomena occur over a broad range of length and time scales, the computational cost of modeling the process is high. At the same time, the large number of parameters that control the quality of a part make experiments expensive. In this paper, we describe ways in which we can use data mining and statistical inference techniques to intelligently combine simulations andmore » experiments to build parts with desired properties. We start with a brief summary of prior work in finding process parameters for high-density parts. We then expand on this work to show how we can improve the approach by using feature selection techniques to identify important variables, data-driven surrogate models to reduce computational costs, improved sampling techniques to cover the design space adequately, and uncertainty analysis for statistical inference. Here, our results indicate that techniques from data mining and statistics can complement those from physical modeling to provide greater insight into complex processes such as selective laser melting.« less

Statistical summaries of fatigue data for design purposes

NASA Technical Reports Server (NTRS)

Wirsching, P. H.

1983-01-01

Two methods are discussed for constructing a design curve on the safe side of fatigue data. Both the tolerance interval and equivalent prediction interval (EPI) concepts provide such a curve while accounting for both the distribution of the estimators in small samples and the data scatter. The EPI is also useful as a mechanism for providing necessary statistics on S-N data for a full reliability analysis which includes uncertainty in all fatigue design factors. Examples of statistical analyses of the general strain life relationship are presented. The tolerance limit and EPI techniques for defining a design curve are demonstrated. Examples usng WASPALOY B and RQC-100 data demonstrate that a reliability model could be constructed by considering the fatigue strength and fatigue ductility coefficients as two independent random variables. A technique given for establishing the fatigue strength for high cycle lives relies on an extrapolation technique and also accounts for "runners." A reliability model or design value can be specified.

Analysis of defect structure in silicon. Characterization of SEMIX material. Silicon sheet growth development for the large area silicon sheet task of the low-cost solar array project

NASA Technical Reports Server (NTRS)

Natesh, R.; Stringfellow, G. B.; Virkar, A. V.; Dunn, J.; Guyer, T.

1983-01-01

Statistically significant quantitative structural imperfection measurements were made on samples from ubiquitous crystalline process (UCP) Ingot 5848 - 13C. Important correlation was obtained between defect densities, cell efficiency, and diffusion length. Grain boundary substructure displayed a strong influence on the conversion efficiency of solar cells from Semix material. Quantitative microscopy measurements gave statistically significant information compared to other microanalytical techniques. A surface preparation technique to obtain proper contrast of structural defects suitable for quantimet quantitative image analyzer (QTM) analysis was perfected and is used routinely. The relationships between hole mobility and grain boundary density was determined. Mobility was measured using the van der Pauw technique, and grain boundary density was measured using quantitative microscopy technique. Mobility was found to decrease with increasing grain boundary density.

Reducing statistical uncertainties in simulated organ doses of phantoms immersed in water

DOE PAGES

Hiller, Mauritius M.; Veinot, Kenneth G.; Easterly, Clay E.; ...

2016-08-13

In this study, methods are addressed to reduce the computational time to compute organ-dose rate coefficients using Monte Carlo techniques. Several variance reduction techniques are compared including the reciprocity method, importance sampling, weight windows and the use of the ADVANTG software package. For low-energy photons, the runtime was reduced by a factor of 10 5 when using the reciprocity method for kerma computation for immersion of a phantom in contaminated water. This is particularly significant since impractically long simulation times are required to achieve reasonable statistical uncertainties in organ dose for low-energy photons in this source medium and geometry. Althoughmore » the MCNP Monte Carlo code is used in this paper, the reciprocity technique can be used equally well with other Monte Carlo codes.« less

Annealing of Co-Cr dental alloy: effects on nanostructure and Rockwell hardness.

PubMed

Ayyıldız, Simel; Soylu, Elif Hilal; Ide, Semra; Kılıç, Selim; Sipahi, Cumhur; Pişkin, Bulent; Gökçe, Hasan Suat

2013-11-01

The aim of the study was to evaluate the effect of annealing on the nanostructure and hardness of Co-Cr metal ceramic samples that were fabricated with a direct metal laser sintering (DMLS) technique. Five groups of Co-Cr dental alloy samples were manufactured in a rectangular form measuring 4 × 2 × 2 mm. Samples fabricated by a conventional casting technique (Group I) and prefabricated milling blanks (Group II) were examined as conventional technique groups. The DMLS samples were randomly divided into three groups as not annealed (Group III), annealed in argon atmosphere (Group IV), or annealed in oxygen atmosphere (Group V). The nanostructure was examined with the small-angle X-ray scattering method. The Rockwell hardness test was used to measure the hardness changes in each group, and the means and standard deviations were statistically analyzed by one-way ANOVA for comparison of continuous variables and Tukey's HSD test was used for post hoc analysis. P values of <.05 were accepted as statistically significant. The general nanostructures of the samples were composed of small spherical entities stacked atop one another in dendritic form. All groups also displayed different hardness values depending on the manufacturing technique. The annealing procedure and environment directly affected both the nanostructure and hardness of the Co-Cr alloy. Group III exhibited a non-homogeneous structure and increased hardness (48.16 ± 3.02 HRC) because the annealing process was incomplete and the inner stress was not relieved. Annealing in argon atmosphere of Group IV not only relieved the inner stresses but also decreased the hardness (27.40 ± 3.98 HRC). The results of fitting function presented that Group IV was the most homogeneous product as the minimum bilayer thickness was measured (7.11 Å). After the manufacturing with DMLS technique, annealing in argon atmosphere is an essential process for Co-Cr metal ceramic substructures. The dentists should be familiar with the materials that are used in clinic for prosthodontics treatments.

Solving large-scale PDE-constrained Bayesian inverse problems with Riemann manifold Hamiltonian Monte Carlo

NASA Astrophysics Data System (ADS)

Bui-Thanh, T.; Girolami, M.

2014-11-01

We consider the Riemann manifold Hamiltonian Monte Carlo (RMHMC) method for solving statistical inverse problems governed by partial differential equations (PDEs). The Bayesian framework is employed to cast the inverse problem into the task of statistical inference whose solution is the posterior distribution in infinite dimensional parameter space conditional upon observation data and Gaussian prior measure. We discretize both the likelihood and the prior using the H1-conforming finite element method together with a matrix transfer technique. The power of the RMHMC method is that it exploits the geometric structure induced by the PDE constraints of the underlying inverse problem. Consequently, each RMHMC posterior sample is almost uncorrelated/independent from the others providing statistically efficient Markov chain simulation. However this statistical efficiency comes at a computational cost. This motivates us to consider computationally more efficient strategies for RMHMC. At the heart of our construction is the fact that for Gaussian error structures the Fisher information matrix coincides with the Gauss-Newton Hessian. We exploit this fact in considering a computationally simplified RMHMC method combining state-of-the-art adjoint techniques and the superiority of the RMHMC method. Specifically, we first form the Gauss-Newton Hessian at the maximum a posteriori point and then use it as a fixed constant metric tensor throughout RMHMC simulation. This eliminates the need for the computationally costly differential geometric Christoffel symbols, which in turn greatly reduces computational effort at a corresponding loss of sampling efficiency. We further reduce the cost of forming the Fisher information matrix by using a low rank approximation via a randomized singular value decomposition technique. This is efficient since a small number of Hessian-vector products are required. The Hessian-vector product in turn requires only two extra PDE solves using the adjoint technique. Various numerical results up to 1025 parameters are presented to demonstrate the ability of the RMHMC method in exploring the geometric structure of the problem to propose (almost) uncorrelated/independent samples that are far away from each other, and yet the acceptance rate is almost unity. The results also suggest that for the PDE models considered the proposed fixed metric RMHMC can attain almost as high a quality performance as the original RMHMC, i.e. generating (almost) uncorrelated/independent samples, while being two orders of magnitude less computationally expensive.

The Effect of Unequal Samples, Heterogeneity of Covariance Matrices, and Number of Variables on Discriminant Analysis Classification Tables and Related Statistics.

ERIC Educational Resources Information Center

Spearing, Debra; Woehlke, Paula

To assess the effect on discriminant analysis in terms of correct classification into two groups, the following parameters were systematically altered using Monte Carlo techniques: sample sizes; proportions of one group to the other; number of independent variables; and covariance matrices. The pairing of the off diagonals (or covariances) with…

Information Entropy Production of Maximum Entropy Markov Chains from Spike Trains

NASA Astrophysics Data System (ADS)

Cofré, Rodrigo; Maldonado, Cesar

2018-01-01

We consider the maximum entropy Markov chain inference approach to characterize the collective statistics of neuronal spike trains, focusing on the statistical properties of the inferred model. We review large deviations techniques useful in this context to describe properties of accuracy and convergence in terms of sampling size. We use these results to study the statistical fluctuation of correlations, distinguishability and irreversibility of maximum entropy Markov chains. We illustrate these applications using simple examples where the large deviation rate function is explicitly obtained for maximum entropy models of relevance in this field.

Planetary mass function and planetary systems

NASA Astrophysics Data System (ADS)

Dominik, M.

2011-02-01

With planets orbiting stars, a planetary mass function should not be seen as a low-mass extension of the stellar mass function, but a proper formalism needs to take care of the fact that the statistical properties of planet populations are linked to the properties of their respective host stars. This can be accounted for by describing planet populations by means of a differential planetary mass-radius-orbit function, which together with the fraction of stars with given properties that are orbited by planets and the stellar mass function allows the derivation of all statistics for any considered sample. These fundamental functions provide a framework for comparing statistics that result from different observing techniques and campaigns which all have their very specific selection procedures and detection efficiencies. Moreover, recent results both from gravitational microlensing campaigns and radial-velocity surveys of stars indicate that planets tend to cluster in systems rather than being the lonely child of their respective parent star. While planetary multiplicity in an observed system becomes obvious with the detection of several planets, its quantitative assessment however comes with the challenge to exclude the presence of further planets. Current exoplanet samples begin to give us first hints at the population statistics, whereas pictures of planet parameter space in its full complexity call for samples that are 2-4 orders of magnitude larger. In order to derive meaningful statistics, however, planet detection campaigns need to be designed in such a way that well-defined fully deterministic target selection, monitoring and detection criteria are applied. The probabilistic nature of gravitational microlensing makes this technique an illustrative example of all the encountered challenges and uncertainties.

Determining the lifetime of detectable amounts of gunshot residue on the hands of a shooter using laser-induced breakdown spectroscopy.

PubMed

Rosenberg, Matthew B; Dockery, Christopher R

2008-11-01

Laser-induced breakdown spectroscopy (LIBS) has been used to determine the period of time that a shooter will test positive for gunshot residue (GSR) after firing a revolver. Multiple rounds of primer were fired and samples collected at multiple hour intervals using an adhesive tape pressed against the skin. Samples were analyzed directly using a commercially available laser-induced breakdown spectrometer where barium emission (originating from barium nitrate in the primer) was observed. Population statistics were used to compare suspected GSR to a library of blank samples from which a threshold value was established. Statistically significant results, positive for GSR, are obtained 5.27 days after a firearm discharge using these techniques.

Spectroscopic and statistical approach of archaeological artifacts recently excavated from Tamilnadu, South India

NASA Astrophysics Data System (ADS)

Seetha, D.; Velraj, G.

2015-10-01

The ancient materials characterization will bring back the more evidence of the ancient people life styles. In this study, the archaeological pottery shards recently excavated from Kodumanal, Erode District in Tamilnadu, South India were investigated. The experimental results enlighten us to the elemental and the mineral composition of the pottery shards. The FT-IR technique tells that the mineralogy and the firing temperature of the samples are less than 800 °C, in the oxidizing/reducing atmosphere and the XRD was used as a complementary technique for the mineralogy. A thorough scientific study of SEM-EDS with the help of statistical approach done to find the provenance of the selected pot shards has not yet been performed. EDS and XRF results revealed that the investigated samples have the elements O, Si, Al, Fe, Mn, Mg, Ca, Ti, K and Na are in different compositions. For establishing the provenance (same or different origin) of pottery samples, Al and Si concentration ratio as well as hierarchical cluster analysis (HCA) was used and the results are correlated.

Endodontic filling removal procedure: an ex vivo comparative study between two rotary techniques.

PubMed

Vale, Mônica Sampaio do; Moreno, Melinna dos Santos; Silva, Priscila Macêdo França da; Botelho, Thereza Cristina Farias

2013-01-01

In this study, we compared the ex vivo removal capacity of two endodontic rotary techniques and determined whether there was a significant quantitative difference in residual material when comparing root thirds. Forty extracted molars were used. The palatal roots were selected, and the canals were prepared using a step-back technique and filled using a lateral condensation technique with gutta-percha points and Endofill sealer. After two weeks of storage in a 0.9% saline solution at 37 ºC in an oven, the specimens were divided into 2 groups of 20, with group 1 samples subjected to Gates-Glidden drills and group 2 samples subjected to the ProTaper retreatment System. Hedstroem files and eucalyptol solvent were used in both groups to complete the removal procedure. Then, the roots thirds were radiographed and the images were submitted to the NIH ImageJ program to measure the residual filling material in mm. Each root third was related to the total area of the root canals. The data were analyzed using Student's t test. There was a statistically significant difference between the two techniques as more filling material was removed by technique 2 (ProTaper) than technique 1 (Gates-Glidden drills, p < 0.05). The apical third had a greater amount of residual filling material than the cervical and middle thirds, and the difference was statistically significant (p < 0.05). None of the selected techniques removed all filling material, and the material was most difficult to remove from the apical third. The ProTaper files removed more material than the Gates-Glidden drills.

Proficiency Testing for Determination of Water Content in Toluene of Chemical Reagents by iteration robust statistic technique

NASA Astrophysics Data System (ADS)

Wang, Hao; Wang, Qunwei; He, Ming

2018-05-01

In order to investigate and improve the level of detection technology of water content in liquid chemical reagents of domestic laboratories, proficiency testing provider PT0031 (CNAS) has organized proficiency testing program of water content in toluene, 48 laboratories from 18 provinces/cities/municipals took part in the PT. This paper introduces the implementation process of proficiency testing for determination of water content in toluene, including sample preparation, homogeneity and stability test, the results of statistics of iteration robust statistic technique and analysis, summarized and analyzed those of the different test standards which are widely used in the laboratories, put forward the technological suggestions for the improvement of the test quality of water content. Satisfactory results were obtained by 43 laboratories, amounting to 89.6% of the total participating laboratories.

Statistical Analysis of Large Scale Structure by the Discrete Wavelet Transform

NASA Astrophysics Data System (ADS)

Pando, Jesus

1997-10-01

The discrete wavelet transform (DWT) is developed as a general statistical tool for the study of large scale structures (LSS) in astrophysics. The DWT is used in all aspects of structure identification including cluster analysis, spectrum and two-point correlation studies, scale-scale correlation analysis and to measure deviations from Gaussian behavior. The techniques developed are demonstrated on 'academic' signals, on simulated models of the Lymanα (Lyα) forests, and on observational data of the Lyα forests. This technique can detect clustering in the Ly-α clouds where traditional techniques such as the two-point correlation function have failed. The position and strength of these clusters in both real and simulated data is determined and it is shown that clusters exist on scales as large as at least 20 h-1 Mpc at significance levels of 2-4 σ. Furthermore, it is found that the strength distribution of the clusters can be used to distinguish between real data and simulated samples even where other traditional methods have failed to detect differences. Second, a method for measuring the power spectrum of a density field using the DWT is developed. All common features determined by the usual Fourier power spectrum can be calculated by the DWT. These features, such as the index of a power law or typical scales, can be detected even when the samples are geometrically complex, the samples are incomplete, or the mean density on larger scales is not known (the infrared uncertainty). Using this method the spectra of Ly-α forests in both simulated and real samples is calculated. Third, a method for measuring hierarchical clustering is introduced. Because hierarchical evolution is characterized by a set of rules of how larger dark matter halos are formed by the merging of smaller halos, scale-scale correlations of the density field should be one of the most sensitive quantities in determining the merging history. We show that these correlations can be completely determined by the correlations between discrete wavelet coefficients on adjacent scales and at nearly the same spatial position, Cj,j+12/cdot2. Scale-scale correlations on two samples of the QSO Ly-α forests absorption spectra are computed. Lastly, higher order statistics are developed to detect deviations from Gaussian behavior. These higher order statistics are necessary to fully characterize the Ly-α forests because the usual 2nd order statistics, such as the two-point correlation function or power spectrum, give inconclusive results. It is shown how this technique takes advantage of the locality of the DWT to circumvent the central limit theorem. A non-Gaussian spectrum is defined and this spectrum reveals not only the magnitude, but the scales of non-Gaussianity. When applied to simulated and observational samples of the Ly-α clouds, it is found that different popular models of structure formation have different spectra while two, independent observational data sets, have the same spectra. Moreover, the non-Gaussian spectra of real data sets are significantly different from the spectra of various possible random samples. (Abstract shortened by UMI.)

Statistical auditing of toxicology reports.

PubMed

Deaton, R R; Obenchain, R L

1994-06-01

Statistical auditing is a new report review process used by the quality assurance unit at Eli Lilly and Co. Statistical auditing allows the auditor to review the process by which the report was generated, as opposed to the process by which the data was generated. We have the flexibility to use different sampling techniques and still obtain thorough coverage of the report data. By properly implementing our auditing process, we can work smarter rather than harder and continue to help our customers increase the quality of their products (reports). Statistical auditing is helping our quality assurance unit meet our customers' need, while maintaining or increasing the quality of our regulatory obligations.

When continuous observations just won't do: developing accurate and efficient sampling strategies for the laying hen.

PubMed

Daigle, Courtney L; Siegford, Janice M

2014-03-01

Continuous observation is the most accurate way to determine animals' actual time budget and can provide a 'gold standard' representation of resource use, behavior frequency, and duration. Continuous observation is useful for capturing behaviors that are of short duration or occur infrequently. However, collecting continuous data is labor intensive and time consuming, making multiple individual or long-term data collection difficult. Six non-cage laying hens were video recorded for 15 h and behavioral data collected every 2 s were compared with data collected using scan sampling intervals of 5, 10, 15, 30, and 60 min and subsamples of 2 second observations performed for 10 min every 30 min, 15 min every 1 h, 30 min every 1.5 h, and 15 min every 2 h. Three statistical approaches were used to provide a comprehensive analysis to examine the quality of the data obtained via different sampling methods. General linear mixed models identified how the time budget from the sampling techniques differed from continuous observation. Correlation analysis identified how strongly results from the sampling techniques were associated with those from continuous observation. Regression analysis identified how well the results from the sampling techniques were associated with those from continuous observation, changes in magnitude, and whether a sampling technique had bias. Static behaviors were well represented with scan and time sampling techniques, while dynamic behaviors were best represented with time sampling techniques. Methods for identifying an appropriate sampling strategy based upon the type of behavior of interest are outlined and results for non-caged laying hens are presented. Copyright © 2013 Elsevier B.V. All rights reserved.

[Effect of techniques of composite resin insertion and polymerization on microleakage and microhardness].

PubMed

Amaral, Cristiane Mariote; Castro, Ana Karina Barbieri Bedran de; Pimenta, Luiz André Freire; Ambrosano, Glaucia Maria Boni

2002-01-01

The aim of this study was to evaluate the influence of techniques of composite resin polymerization and insertion on microleakage and microhardness. One hundred and eighty class II cavities were prepared in bovine teeth and assigned to six groups: G1 - bulk filling + conventional polymerization; G2 - bucco-lingual increments + conventional polymerization; G3 - bulk filling + soft-start polymerization; G4 - bucco-lingual increments + soft-start polymerization; G5 - bulk filling + progressive polymerization; G6 - bucco-lingual increments + progressive polymerization. All cavities were restored with the Z100/Single Bond system (3M). After thermocycling, the samples were immersed in 2% methylene blue dye solution for 4 hours. Half of the samples were embedded in polystyrene resin, and Knoop microhardness was measured. The Kruskal-Wallis test did not reveal statistical differences (p > 0.05) between the polymerization and insertion techniques as to microleakage. Regarding microhardness, the two-way ANOVA and the Tukey test did not reveal statistical differences between the restorative techniques (p > 0.05), but progressive polymerization (G5 and G6) was associated with smaller Knoop microhardness values (p < 0.05): G = 144.11; G2 = 143.89; G3 = 141.14; G4 = 142.79; G5 = 132.15; G6 = 131.67. It was concluded that the evaluated polymerization and insertion techniques did not affect marginal microleakage, but a decrease in microhardness occurred when progressive polymerization was carried out.

A Comparative Evaluation of the Efficacy of Different Caries Excavation Techniques in reducing the Cariogenic Flora: An in vivo Study.

PubMed

Hassan, Afrah Fatima; Yadav, Gunjan; Tripathi, Abhay Mani; Mehrotra, Mridul; Saha, Sonali; Garg, Nishita

2016-01-01

Caries excavation is a noninvasive technique of caries removal with maximum preservation of healthy tooth structure. To compare the efficacy of three different caries excavation techniques in reducing the count of cariogenic flora. Sixty healthy primary molars were selected from 26 healthy children with occlusal carious lesions without pulpal involvement and divided into three groups in which caries excavation was done with the help of (1) carbide bur; (2) polymer bur using slow-speed handpiece; and (3) ultrasonic tip with ultrasonic machine. Samples were collected before and after caries excavation for microbiological analysis with the help of sterile sharp spoon excavator. Samples were inoculated on blood agar plate and incubated at 37°C for 48 hours. After bacterial cultivation, the bacterial count of Streptococcus mutans was obtained. All statistical analysis was performed using SPSS 13 statistical software version. Kruskal-Wallis analysis of variance, Wilcoxon matched pairs test, and Z test were performed to reveal the statistical significance. The decrease in bacterial count of S. mutans before and after caries excavation was significant (p < 0.001) in all the three groups. Carbide bur showed most efficient reduction in cariogenic flora, while ultrasonic tip showed almost comparable results, while polymer bur showed least reduction in cariogenic flora after caries excavation. Hassan AF, Yadav G, Tripathi AM, Mehrotra M, Saha S, Garg N. A Comparative Evaluation of the Efficacy of Different Caries Excavation Techniques in reducing the Cariogenic Flora: An in vivo Study. Int J Clin Pediatr Dent 2016;9(3):214-217.

Evaluation of the marginal fit of metal copings fabricated on three different marginal designs using conventional and accelerated casting techniques: an in vitro study.

PubMed

Vaidya, Sharad; Parkash, Hari; Bhargava, Akshay; Gupta, Sharad

2014-01-01

Abundant resources and techniques have been used for complete coverage crown fabrication. Conventional investing and casting procedures for phosphate-bonded investments require a 2- to 4-h procedure before completion. Accelerated casting techniques have been used, but may not result in castings with matching marginal accuracy. The study measured the marginal gap and determined the clinical acceptability of single cast copings invested in a phosphate-bonded investment with the use of conventional and accelerated methods. One hundred and twenty cast coping samples were fabricated using conventional and accelerated methods, with three finish lines: Chamfer, shoulder and shoulder with bevel. Sixty copings were prepared with each technique. Each coping was examined with a stereomicroscope at four predetermined sites and measurements of marginal gaps were documented for each. A master chart was prepared for all the data and was analyzed using Statistical Package for the Social Sciences version. Evidence of marginal gap was then evaluated by t-test. Analysis of variance and Post-hoc analysis were used to compare two groups as well as to make comparisons between three subgroups . Measurements recorded showed no statistically significant difference between conventional and accelerated groups. Among the three marginal designs studied, shoulder with bevel showed the best marginal fit with conventional as well as accelerated casting techniques. Accelerated casting technique could be a vital alternative to the time-consuming conventional casting technique. The marginal fit between the two casting techniques showed no statistical difference.

Ozone data and mission sampling analysis

NASA Technical Reports Server (NTRS)

Robbins, J. L.

1980-01-01

A methodology was developed to analyze discrete data obtained from the global distribution of ozone. Statistical analysis techniques were applied to describe the distribution of data variance in terms of empirical orthogonal functions and components of spherical harmonic models. The effects of uneven data distribution and missing data were considered. Data fill based on the autocorrelation structure of the data is described. Computer coding of the analysis techniques is included.

The multiple imputation method: a case study involving secondary data analysis.

PubMed

Walani, Salimah R; Cleland, Charles M

2015-05-01

To illustrate with the example of a secondary data analysis study the use of the multiple imputation method to replace missing data. Most large public datasets have missing data, which need to be handled by researchers conducting secondary data analysis studies. Multiple imputation is a technique widely used to replace missing values while preserving the sample size and sampling variability of the data. The 2004 National Sample Survey of Registered Nurses. The authors created a model to impute missing values using the chained equation method. They used imputation diagnostics procedures and conducted regression analysis of imputed data to determine the differences between the log hourly wages of internationally educated and US-educated registered nurses. The authors used multiple imputation procedures to replace missing values in a large dataset with 29,059 observations. Five multiple imputed datasets were created. Imputation diagnostics using time series and density plots showed that imputation was successful. The authors also present an example of the use of multiple imputed datasets to conduct regression analysis to answer a substantive research question. Multiple imputation is a powerful technique for imputing missing values in large datasets while preserving the sample size and variance of the data. Even though the chained equation method involves complex statistical computations, recent innovations in software and computation have made it possible for researchers to conduct this technique on large datasets. The authors recommend nurse researchers use multiple imputation methods for handling missing data to improve the statistical power and external validity of their studies.

Moisture Damage Modeling in Lime and Chemically Modified Asphalt at Nanolevel Using Ensemble Computational Intelligence

PubMed Central

2018-01-01

This paper measures the adhesion/cohesion force among asphalt molecules at nanoscale level using an Atomic Force Microscopy (AFM) and models the moisture damage by applying state-of-the-art Computational Intelligence (CI) techniques (e.g., artificial neural network (ANN), support vector regression (SVR), and an Adaptive Neuro Fuzzy Inference System (ANFIS)). Various combinations of lime and chemicals as well as dry and wet environments are used to produce different asphalt samples. The parameters that were varied to generate different asphalt samples and measure the corresponding adhesion/cohesion forces are percentage of antistripping agents (e.g., Lime and Unichem), AFM tips K values, and AFM tip types. The CI methods are trained to model the adhesion/cohesion forces given the variation in values of the above parameters. To achieve enhanced performance, the statistical methods such as average, weighted average, and regression of the outputs generated by the CI techniques are used. The experimental results show that, of the three individual CI methods, ANN can model moisture damage to lime- and chemically modified asphalt better than the other two CI techniques for both wet and dry conditions. Moreover, the ensemble of CI along with statistical measurement provides better accuracy than any of the individual CI techniques. PMID:29849551

Assessing statistical differences between parameters estimates in Partial Least Squares path modeling.

PubMed

Rodríguez-Entrena, Macario; Schuberth, Florian; Gelhard, Carsten

2018-01-01

Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess differences between parameters that are estimated for different subpopulations, the study at hand introduces a technique that allows to also assess whether two parameter estimates that are derived from the same sample are statistically different. To illustrate this advancement to PLS-SEM, we particularly refer to a reduced version of the well-established technology acceptance model.

A Monte Carlo investigation of thrust imbalance of solid rocket motor pairs

NASA Technical Reports Server (NTRS)

Sforzini, R. H.; Foster, W. A., Jr.; Johnson, J. S., Jr.

1974-01-01

A technique is described for theoretical, statistical evaluation of the thrust imbalance of pairs of solid-propellant rocket motors (SRMs) firing in parallel. Sets of the significant variables, determined as a part of the research, are selected using a random sampling technique and the imbalance calculated for a large number of motor pairs. The performance model is upgraded to include the effects of statistical variations in the ovality and alignment of the motor case and mandrel. Effects of cross-correlations of variables are minimized by selecting for the most part completely independent input variables, over forty in number. The imbalance is evaluated in terms of six time - varying parameters as well as eleven single valued ones which themselves are subject to statistical analysis. A sample study of the thrust imbalance of 50 pairs of 146 in. dia. SRMs of the type to be used on the space shuttle is presented. The FORTRAN IV computer program of the analysis and complete instructions for its use are included. Performance computation time for one pair of SRMs is approximately 35 seconds on the IBM 370/155 using the FORTRAN H compiler.

Reliability of horizontal and vertical tube shift techniques in the localisation of supernumerary teeth.

PubMed

Mallineni, S K; Anthonappa, R P; King, N M

2016-12-01

To assess the reliability of the vertical tube shift technique (VTST) and horizontal tube shift technique (HTST) for the localisation of unerupted supernumerary teeth (ST) in the anterior region of the maxilla. A convenience sample of 83 patients who attended a major teaching hospital because of unerupted ST was selected. Only non-syndromic patients with ST and who had complete clinical and radiographic and surgical records were included in the study. Ten examiners independently rated the paired set of radiographs for each technique. Chi-square test, paired t test and kappa statistics were employed to assess the intra- and inter-examiner reliability. Paired sets of 1660 radiographs (830 pairs for each technique) were available for the analysis. The overall sensitivity for VTST and HTST was 80.6 and 72.1% respectively, with slight inter-examiner and good intra-examiner reliability. Statistically significant differences were evident between the two localisation techniques (p < 0.05). Localisation of unerupted ST using VTST was more successful than HTST in the anterior region of the maxilla.

Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep

2015-05-01

The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.

Estimation of within-stratum variance for sample allocation: Foreign commodity production forecasting

NASA Technical Reports Server (NTRS)

Chhikara, R. S.; Perry, C. R., Jr. (Principal Investigator)

1980-01-01

The problem of determining the stratum variances required for an optimum sample allocation for remotely sensed crop surveys is investigated with emphasis on an approach based on the concept of stratum variance as a function of the sampling unit size. A methodology using the existing and easily available information of historical statistics is developed for obtaining initial estimates of stratum variances. The procedure is applied to variance for wheat in the U.S. Great Plains and is evaluated based on the numerical results obtained. It is shown that the proposed technique is viable and performs satisfactorily with the use of a conservative value (smaller than the expected value) for the field size and with the use of crop statistics from the small political division level.

Statistics 101 for Radiologists.

PubMed

Anvari, Arash; Halpern, Elkan F; Samir, Anthony E

2015-10-01

Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced. © RSNA, 2015.

Classical Statistics and Statistical Learning in Imaging Neuroscience

PubMed Central

Bzdok, Danilo

2017-01-01

Brain-imaging research has predominantly generated insight by means of classical statistics, including regression-type analyses and null-hypothesis testing using t-test and ANOVA. Throughout recent years, statistical learning methods enjoy increasing popularity especially for applications in rich and complex data, including cross-validated out-of-sample prediction using pattern classification and sparsity-inducing regression. This concept paper discusses the implications of inferential justifications and algorithmic methodologies in common data analysis scenarios in neuroimaging. It is retraced how classical statistics and statistical learning originated from different historical contexts, build on different theoretical foundations, make different assumptions, and evaluate different outcome metrics to permit differently nuanced conclusions. The present considerations should help reduce current confusion between model-driven classical hypothesis testing and data-driven learning algorithms for investigating the brain with imaging techniques. PMID:29056896

Analysis of the Einstein sample of early-type galaxies

NASA Technical Reports Server (NTRS)

Eskridge, Paul B.; Fabbiano, Giuseppina

1993-01-01

The EINSTEIN galaxy catalog contains x-ray data for 148 early-type (E and SO) galaxies. A detailed analysis of the global properties of this sample are studied. By comparing the x-ray properties with other tracers of the ISM, as well as with observables related to the stellar dynamics and populations of the sample, we expect to determine more clearly the physical relationships that determine the evolution of early-type galaxies. Previous studies with smaller samples have explored the relationships between x-ray luminosity (L(sub x)) and luminosities in other bands. Using our larger sample and the statistical techniques of survival analysis, a number of these earlier analyses were repeated. For our full sample, a strong statistical correlation is found between L(sub X) and L(sub B) (the probability that the null hypothesis is upheld is P less than 10(exp -4) from a variety of rank correlation tests. Regressions with several algorithms yield consistent results.

Applying neutron transmission physics and 3D statistical full-field model to understand 2D Bragg-edge imaging

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

Xie, Qingge; Song, Gian; Gorti, Sarma B.

Bragg-edge imaging, which is also known as neutron radiography, has recently emerged as a novel crystalline characterization technique. Modelling of this novel technique by incorporating various features of the underlying microstructure (including the crystallographic texture, the morphological texture, and the grain size) of the material remains a subject of considerable research and development. In this paper, Inconel 718 samples made by additive manufacturing were investigated by neutron diffraction and neutron radiography techniques. The specimen features strong morphological and crystallographic textures and a highly heterogeneous microstructure. A 3D statistical full-field model is introduced by taking details of the microstructure into accountmore » to understand the experimental neutron radiography results. The Bragg-edge imaging and the total cross section were calculated based on the neutron transmission physics. A good match was obtained between the model predictions and experimental results at different incident beam angles with respect to the sample build direction. The current theoretical approach has the ability to incorporate 3D spatially resolved microstructural heterogeneity information and shows promise in understanding the 2D neutron radiography of bulk samples. With further development to incorporate the heterogeneity in lattice strain in the model, it can be used as a powerful tool in the future to better understand the neutron radiography data.« less

Applying neutron transmission physics and 3D statistical full-field model to understand 2D Bragg-edge imaging

DOE PAGES

Xie, Qingge; Song, Gian; Gorti, Sarma B.; ...

2018-02-21

Bragg-edge imaging, which is also known as neutron radiography, has recently emerged as a novel crystalline characterization technique. Modelling of this novel technique by incorporating various features of the underlying microstructure (including the crystallographic texture, the morphological texture, and the grain size) of the material remains a subject of considerable research and development. In this paper, Inconel 718 samples made by additive manufacturing were investigated by neutron diffraction and neutron radiography techniques. The specimen features strong morphological and crystallographic textures and a highly heterogeneous microstructure. A 3D statistical full-field model is introduced by taking details of the microstructure into accountmore » to understand the experimental neutron radiography results. The Bragg-edge imaging and the total cross section were calculated based on the neutron transmission physics. A good match was obtained between the model predictions and experimental results at different incident beam angles with respect to the sample build direction. The current theoretical approach has the ability to incorporate 3D spatially resolved microstructural heterogeneity information and shows promise in understanding the 2D neutron radiography of bulk samples. With further development to incorporate the heterogeneity in lattice strain in the model, it can be used as a powerful tool in the future to better understand the neutron radiography data.« less

Determination of Acidity in Donor Milk.

PubMed

Escuder-Vieco, Diana; Vázquez-Román, Sara; Sánchez-Pallás, Juan; Ureta-Velasco, Noelia; Mosqueda-Peña, Rocío; Pallás-Alonso, Carmen Rosa

2016-11-01

There is no uniformity among milk banks on milk acceptance criteria. The acidity obtained by the Dornic titration technique is a widely used quality control in donor milk. However, there are no comparative data with other acidity-measuring techniques, such as the pH meter. The objective of this study was to assess the correlation between the Dornic technique and the pH measure to determine the pH cutoff corresponding to the Dornic degree limit value used as a reference for donor milk quality control. Fifty-two human milk samples were obtained from 48 donors. Acidity was measured using the Dornic method and pH meter in triplicate. Statistical data analysis to estimate significant correlations between variables was carried out. The Dornic acidity value that led to rejecting donor milk was ≥ 8 Dornic degrees (°D). In the evaluated sample size, Dornic acidity measure and pH values showed a statistically significant negative correlation (τ = -0.780; P = .000). A pH value of 6.57 corresponds to 8°D and of 7.12 to 4°D. Donor milk with a pH over 6.57 may be accepted for subsequent processing in the milk bank. Moreover, the pH measurement seems to be more useful due to certain advantages over the Dornic method, such as objectivity, accuracy, standardization, the lack of chemical reagents required, and the fact that it does not destroy the milk sample.

Performance of Statistical Temporal Downscaling Techniques of Wind Speed Data Over Aegean Sea

NASA Astrophysics Data System (ADS)

Gokhan Guler, Hasan; Baykal, Cuneyt; Ozyurt, Gulizar; Kisacik, Dogan

2016-04-01

Wind speed data is a key input for many meteorological and engineering applications. Many institutions provide wind speed data with temporal resolutions ranging from one hour to twenty four hours. Higher temporal resolution is generally required for some applications such as reliable wave hindcasting studies. One solution to generate wind data at high sampling frequencies is to use statistical downscaling techniques to interpolate values of the finer sampling intervals from the available data. In this study, the major aim is to assess temporal downscaling performance of nine statistical interpolation techniques by quantifying the inherent uncertainty due to selection of different techniques. For this purpose, hourly 10-m wind speed data taken from 227 data points over Aegean Sea between 1979 and 2010 having a spatial resolution of approximately 0.3 degrees are analyzed from the National Centers for Environmental Prediction (NCEP) The Climate Forecast System Reanalysis database. Additionally, hourly 10-m wind speed data of two in-situ measurement stations between June, 2014 and June, 2015 are considered to understand effect of dataset properties on the uncertainty generated by interpolation technique. In this study, nine statistical interpolation techniques are selected as w0 (left constant) interpolation, w6 (right constant) interpolation, averaging step function interpolation, linear interpolation, 1D Fast Fourier Transform interpolation, 2nd and 3rd degree Lagrange polynomial interpolation, cubic spline interpolation, piecewise cubic Hermite interpolating polynomials. Original data is down sampled to 6 hours (i.e. wind speeds at 0th, 6th, 12th and 18th hours of each day are selected), then 6 hourly data is temporally downscaled to hourly data (i.e. the wind speeds at each hour between the intervals are computed) using nine interpolation technique, and finally original data is compared with the temporally downscaled data. A penalty point system based on coefficient of variation root mean square error, normalized mean absolute error, and prediction skill is selected to rank nine interpolation techniques according to their performance. Thus, error originated from the temporal downscaling technique is quantified which is an important output to determine wind and wave modelling uncertainties, and the performance of these techniques are demonstrated over Aegean Sea indicating spatial trends and discussing relevance to data type (i.e. reanalysis data or in-situ measurements). Furthermore, bias introduced by the best temporal downscaling technique is discussed. Preliminary results show that overall piecewise cubic Hermite interpolating polynomials have the highest performance to temporally downscale wind speed data for both reanalysis data and in-situ measurements over Aegean Sea. However, it is observed that cubic spline interpolation performs much better along Aegean coastline where the data points are close to the land. Acknowledgement: This research was partly supported by TUBITAK Grant number 213M534 according to Turkish Russian Joint research grant with RFBR and the CoCoNET (Towards Coast to Coast Network of Marine Protected Areas Coupled by Wİnd Energy Potential) project funded by European Union FP7/2007-2013 program.

A computational visual saliency model based on statistics and machine learning.

PubMed

Lin, Ru-Je; Lin, Wei-Song

2014-08-01

Identifying the type of stimuli that attracts human visual attention has been an appealing topic for scientists for many years. In particular, marking the salient regions in images is useful for both psychologists and many computer vision applications. In this paper, we propose a computational approach for producing saliency maps using statistics and machine learning methods. Based on four assumptions, three properties (Feature-Prior, Position-Prior, and Feature-Distribution) can be derived and combined by a simple intersection operation to obtain a saliency map. These properties are implemented by a similarity computation, support vector regression (SVR) technique, statistical analysis of training samples, and information theory using low-level features. This technique is able to learn the preferences of human visual behavior while simultaneously considering feature uniqueness. Experimental results show that our approach performs better in predicting human visual attention regions than 12 other models in two test databases. © 2014 ARVO.

Effect of background correction on peak detection and quantification in online comprehensive two-dimensional liquid chromatography using diode array detection.

PubMed

Allen, Robert C; John, Mallory G; Rutan, Sarah C; Filgueira, Marcelo R; Carr, Peter W

2012-09-07

A singular value decomposition-based background correction (SVD-BC) technique is proposed for the reduction of background contributions in online comprehensive two-dimensional liquid chromatography (LC×LC) data. The SVD-BC technique was compared to simply subtracting a blank chromatogram from a sample chromatogram and to a previously reported background correction technique for one dimensional chromatography, which uses an asymmetric weighted least squares (AWLS) approach. AWLS was the only background correction technique to completely remove the background artifacts from the samples as evaluated by visual inspection. However, the SVD-BC technique greatly reduced or eliminated the background artifacts as well and preserved the peak intensity better than AWLS. The loss in peak intensity by AWLS resulted in lower peak counts at the detection thresholds established using standards samples. However, the SVD-BC technique was found to introduce noise which led to detection of false peaks at the lower detection thresholds. As a result, the AWLS technique gave more precise peak counts than the SVD-BC technique, particularly at the lower detection thresholds. While the AWLS technique resulted in more consistent percent residual standard deviation values, a statistical improvement in peak quantification after background correction was not found regardless of the background correction technique used. Copyright © 2012 Elsevier B.V. All rights reserved.

Application of scanning acoustic microscopy to advanced structural ceramics

NASA Technical Reports Server (NTRS)

Vary, Alex; Klima, Stanley J.

1987-01-01

A review is presentod of research investigations of several acoustic microscopy techniques for application to structural ceramics for advanced heat engines. Results obtained with scanning acoustic microscopy (SAM), scanning laser acoustic microscopy (SLAM), scanning electron acoustic microscopy (SEAM), and photoacoustic microscopy (PAM) are compared. The techniques were evaluated on research samples of green and sintered monolithic silicon nitrides and silicon carbides in the form of modulus-of-rupture bars containing deliberately introduced flaws. Strengths and limitations of the techniques are described with emphasis on statistics of detectability of flaws that constitute potential fracture origins.

General statistical considerations

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

Eberhardt, L L; Gilbert, R O

From NAEG plutonium environmental studies program meeting; Las Vegas, Nevada, USA (2 Oct 1973). The high sampling variability encountered in environmental plutonium studies along with high analytical costs makes it very important that efficient soil sampling plans be used. However, efficient sampling depends on explicit and simple statements of the objectives of the study. When there are multiple objectives it may be difficult to devise a wholly suitable sampling scheme. Sampling for long-term changes in plutonium concentration in soils may also be complex and expensive. Further attention to problems associated with compositing samples is recommended, as is the consistent usemore » of random sampling as a basic technique. (auth)« less

Arsenic distribution and valence state variation studied by fast hierarchical length-scale morphological, compositional, and speciation imaging at the Nanoscopium, Synchrotron Soleil

NASA Astrophysics Data System (ADS)

Somogyi, Andrea; Medjoubi, Kadda; Sancho-Tomas, Maria; Visscher, P. T.; Baranton, Gil; Philippot, Pascal

2017-09-01

The understanding of real complex geological, environmental and geo-biological processes depends increasingly on in-depth non-invasive study of chemical composition and morphology. In this paper we used scanning hard X-ray nanoprobe techniques in order to study the elemental composition, morphology and As speciation in complex highly heterogeneous geological samples. Multivariate statistical analytical techniques, such as principal component analysis and clustering were used for data interpretation. These measurements revealed the quantitative and valance state inhomogeneity of As and its relation to the total compositional and morphological variation of the sample at sub-μm scales.

Regression modeling of particle size distributions in urban storm water: advancements through improved sample collection methods

USGS Publications Warehouse

Fienen, Michael N.; Selbig, William R.

2012-01-01

A new sample collection system was developed to improve the representation of sediment entrained in urban storm water by integrating water quality samples from the entire water column. The depth-integrated sampler arm (DISA) was able to mitigate sediment stratification bias in storm water, thereby improving the characterization of suspended-sediment concentration and particle size distribution at three independent study locations. Use of the DISA decreased variability, which improved statistical regression to predict particle size distribution using surrogate environmental parameters, such as precipitation depth and intensity. The performance of this statistical modeling technique was compared to results using traditional fixed-point sampling methods and was found to perform better. When environmental parameters can be used to predict particle size distributions, environmental managers have more options when characterizing concentrations, loads, and particle size distributions in urban runoff.

Optimizing Integrated Terminal Airspace Operations Under Uncertainty

NASA Technical Reports Server (NTRS)

Bosson, Christabelle; Xue, Min; Zelinski, Shannon

2014-01-01

In the terminal airspace, integrated departures and arrivals have the potential to increase operations efficiency. Recent research has developed geneticalgorithm- based schedulers for integrated arrival and departure operations under uncertainty. This paper presents an alternate method using a machine jobshop scheduling formulation to model the integrated airspace operations. A multistage stochastic programming approach is chosen to formulate the problem and candidate solutions are obtained by solving sample average approximation problems with finite sample size. Because approximate solutions are computed, the proposed algorithm incorporates the computation of statistical bounds to estimate the optimality of the candidate solutions. A proof-ofconcept study is conducted on a baseline implementation of a simple problem considering a fleet mix of 14 aircraft evolving in a model of the Los Angeles terminal airspace. A more thorough statistical analysis is also performed to evaluate the impact of the number of scenarios considered in the sampled problem. To handle extensive sampling computations, a multithreading technique is introduced.

Area estimation using multiyear designs and partial crop identification

NASA Technical Reports Server (NTRS)

Sielken, R. L., Jr.

1984-01-01

Statistical procedures were developed for large area assessments using both satellite and conventional data. Crop acreages, other ground cover indices, and measures of change were the principal characteristics of interest. These characteristics are capable of being estimated from samples collected possibly from several sources at varying times, with different levels of identification. Multiyear analysis techniques were extended to include partially identified samples; the best current year sampling design corresponding to a given sampling history was determined; weights reflecting the precision or confidence in each observation were identified and utilized, and the variation in estimates incorporating partially identified samples were quantified.

Assessment of Hygiene Habits in Acrylic Denture Wearers: a Cross-sectional Study

PubMed Central

Aoun, Georges; Gerges, Elie

2017-01-01

Objectives: To assess the denture hygiene habits in a population of Lebanese denture wearers. Materials and Methods: One hundred and thirty-two (132) patients [71 women (53.8%) and 61 men (46.2%)] wearing their acrylic dentures for more than two years were included in this study. The hygiene methods related to their dentures were evaluated and the data obtained were analyzed statistically using the IBM® SPSS® statistics 20.0 (USA) statistical package. Results: Regardless of the cleaning technique, the big majority of our participants [123 out of 132 (93.1%)] cleaned their dentures daily. The two mostly used denture cleaning techniques were rinsing with tap water (34.1%) and brushing with toothpaste (31.8%). Nearly half of our patients (45.5%) soaked their dentures during the night; most of them with cleansing tablets dissolved in water (28.8%). Conclusions: Within the limitations of our study, it was concluded that in a sample of Lebanese population surveyed about denture hygiene habits, the daily frequency of denture cleaning is satisfactory, but the techniques and products used were self-estimated and, consequently, not sufficient. PMID:29109670

Utilizing the Zero-One Linear Programming Constraints to Draw Multiple Sets of Matched Samples from a Non-Treatment Population as Control Groups for the Quasi-Experimental Design

ERIC Educational Resources Information Center

Li, Yuan H.; Yang, Yu N.; Tompkins, Leroy J.; Modarresi, Shahpar

2005-01-01

The statistical technique, "Zero-One Linear Programming," that has successfully been used to create multiple tests with similar characteristics (e.g., item difficulties, test information and test specifications) in the area of educational measurement, was deemed to be a suitable method for creating multiple sets of matched samples to be…

Comparative Evaluation of Marginal Accuracy of a Cast Fixed Partial Denture Compared to Soldered Fixed Partial Denture Made of Two Different Base Metal Alloys and Casting Techniques: An In vitro Study.

PubMed

Jei, J Brintha; Mohan, Jayashree

2014-03-01

The periodontal health of abutment teeth and the durability of fixed partial denture depends on the marginal adaptation of the prosthesis. Any discrepancy in the marginal area leads to dissolution of luting agent and plaque accumulation. This study was done with the aim of evaluating the accuracy of marginal fit of four unit crown and bridge made up of Ni-Cr and Cr-Co alloys under induction and centrifugal casting. They were compared to cast fixed partial denture (FPD) and soldered FPD. For the purpose of this study a metal model was fabricated. A total of 40 samples (4-unit crown and bridge) were prepared in which 20 Cr-Co samples and 20 Ni-Cr samples were fabricated. Within these 20 samples of each group 10 samples were prepared by induction casting technique and other 10 samples with centrifugal casting technique. The cast FPD samples obtained were seated on the model and the samples were then measured with travelling microscope having precision of 0.001 cm. Sectioning of samples was done between the two pontics and measurements were made, then the soldering was made with torch soldering unit. The marginal discrepancy of soldered samples was measured and all findings were statistically analysed. The results revealed minimal marginal discrepancy with Cr-Co samples when compared to Ni-Cr samples done under induction casting technique. When compared to cast FPD samples, the soldered group showed reduced marginal discrepancy.

Differences in sampling techniques on total post-mortem tryptase.

PubMed

Tse, R; Garland, J; Kesha, K; Elstub, H; Cala, A D; Ahn, Y; Stables, S; Palmiere, C

2018-05-01

The measurement of mast cell tryptase is commonly used to support the diagnosis of anaphylaxis. In the post-mortem setting, the literature recommends sampling from peripheral blood sources (femoral blood) but does not specify the exact sampling technique. Sampling techniques vary between pathologists, and it is unclear whether different sampling techniques have any impact on post-mortem tryptase levels. The aim of this study is to compare the difference in femoral total post-mortem tryptase levels between two sampling techniques. A 6-month retrospective study comparing femoral total post-mortem tryptase levels between (1) aspirating femoral vessels with a needle and syringe prior to evisceration and (2) femoral vein cut down during evisceration. Twenty cases were identified, with three cases excluded from analysis. There was a statistically significant difference (paired t test, p < 0.05) between mean post-mortem tryptase by aspiration (10.87 ug/L) and by cut down (14.15 ug/L). The mean difference between the two methods was 3.28 ug/L (median, 1.4 ug/L; min, - 6.1 ug/L; max, 16.5 ug/L; 95% CI, 0.001-6.564 ug/L). Femoral total post-mortem tryptase is significantly different, albeit by a small amount, between the two sampling methods. The clinical significance of this finding and what factors may contribute to it are unclear. When requesting post-mortem tryptase, the pathologist should consider documenting the exact blood collection site and method used for collection. In addition, blood samples acquired by different techniques should not be mixed together and should be analyzed separately if possible.

Estimating TCP Packet Loss Ratio from Sampled ACK Packets

NASA Astrophysics Data System (ADS)

Yamasaki, Yasuhiro; Shimonishi, Hideyuki; Murase, Tutomu

The advent of various quality-sensitive applications has greatly changed the requirements for IP network management and made the monitoring of individual traffic flows more important. Since the processing costs of per-flow quality monitoring are high, especially in high-speed backbone links, packet sampling techniques have been attracting considerable attention. Existing sampling techniques, such as those used in Sampled NetFlow and sFlow, however, focus on the monitoring of traffic volume, and there has been little discussion of the monitoring of such quality indexes as packet loss ratio. In this paper we propose a method for estimating, from sampled packets, packet loss ratios in individual TCP sessions. It detects packet loss events by monitoring duplicate ACK events raised by each TCP receiver. Because sampling reveals only a portion of the actual packet loss, the actual packet loss ratio is estimated statistically. Simulation results show that the proposed method can estimate the TCP packet loss ratio accurately from a 10% sampling of packets.

A proposed method to minimize waste from institutional radiation safety surveillance programs through the application of expected value statistics.

PubMed

Emery, R J

1997-03-01

Institutional radiation safety programs routinely use wipe test sampling and liquid scintillation counting analysis to indicate the presence of removable radioactive contamination. Significant volumes of liquid waste can be generated by such surveillance activities, and the subsequent disposal of these materials can sometimes be difficult and costly. In settings where large numbers of negative results are regularly obtained, the limited grouping of samples for analysis based on expected value statistical techniques is possible. To demonstrate the plausibility of the approach, single wipe samples exposed to varying amounts of contamination were analyzed concurrently with nine non-contaminated samples. Although the sample grouping inevitably leads to increased quenching with liquid scintillation counting systems, the effect did not impact the ability to detect removable contamination in amounts well below recommended action levels. Opportunities to further improve this cost effective semi-quantitative screening procedure are described, including improvements in sample collection procedures, enhancing sample-counting media contact through mixing and extending elution periods, increasing sample counting times, and adjusting institutional action levels.

21 CFR 820.250 - Statistical techniques.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Statistical techniques. 820.250 Section 820.250...) MEDICAL DEVICES QUALITY SYSTEM REGULATION Statistical Techniques § 820.250 Statistical techniques. (a... statistical techniques required for establishing, controlling, and verifying the acceptability of process...

21 CFR 820.250 - Statistical techniques.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Statistical techniques. 820.250 Section 820.250...) MEDICAL DEVICES QUALITY SYSTEM REGULATION Statistical Techniques § 820.250 Statistical techniques. (a... statistical techniques required for establishing, controlling, and verifying the acceptability of process...

Pick a Sample.

ERIC Educational Resources Information Center

Peterson, Ivars

1991-01-01

A method that enables people to obtain the benefits of statistics and probability theory without the shortcomings of conventional methods because it is free of mathematical formulas and is easy to understand and use is described. A resampling technique called the "bootstrap" is discussed in terms of application and development. (KR)

Comparative Evaluation of Two Venous Sampling Techniques for the Assessment of Pancreatic Insulin and Zinc Release upon Glucose Challenge.

PubMed

Pillai, Anil Kumar; Silvers, William; Christensen, Preston; Riegel, Matthew; Adams-Huet, Beverley; Lingvay, Ildiko; Sun, Xiankai; Öz, Orhan K

2015-01-01

Advances in noninvasive imaging modalities have provided opportunities to study β cell function through imaging zinc release from insulin secreting β cells. Understanding the temporal secretory pattern of insulin and zinc corelease after a glucose challenge is essential for proper timing of administration of zinc sensing probes. Portal venous sampling is an essential part of pharmacological and nutritional studies in animal models. The purpose of this study was to compare two different percutaneous image-guided techniques: transhepatic ultrasound guided portal vein access and transsplenic fluoroscopy guided splenic vein access for ease of access, safety, and evaluation of temporal kinetics of insulin and zinc release into the venous effluent from the pancreas. Both techniques were safe, reproducible, and easy to perform. The mean time required to obtain desired catheter position for venous sampling was 15 minutes shorter using the transsplenic technique. A clear biphasic insulin release profile was observed in both techniques. Statistically higher insulin concentration but similar zinc release after a glucose challenge was observed from splenic vein samples, as compared to the ones from the portal vein. To our knowledge, this is the first report of percutaneous methods to assess zinc release kinetics from the porcine pancreas.

Comparative Evaluation of Two Venous Sampling Techniques for the Assessment of Pancreatic Insulin and Zinc Release upon Glucose Challenge

PubMed Central

Pillai, Anil Kumar; Silvers, William; Christensen, Preston; Riegel, Matthew; Adams-Huet, Beverley; Lingvay, Ildiko; Sun, Xiankai; Öz, Orhan K.

2015-01-01

Advances in noninvasive imaging modalities have provided opportunities to study β cell function through imaging zinc release from insulin secreting β cells. Understanding the temporal secretory pattern of insulin and zinc corelease after a glucose challenge is essential for proper timing of administration of zinc sensing probes. Portal venous sampling is an essential part of pharmacological and nutritional studies in animal models. The purpose of this study was to compare two different percutaneous image-guided techniques: transhepatic ultrasound guided portal vein access and transsplenic fluoroscopy guided splenic vein access for ease of access, safety, and evaluation of temporal kinetics of insulin and zinc release into the venous effluent from the pancreas. Both techniques were safe, reproducible, and easy to perform. The mean time required to obtain desired catheter position for venous sampling was 15 minutes shorter using the transsplenic technique. A clear biphasic insulin release profile was observed in both techniques. Statistically higher insulin concentration but similar zinc release after a glucose challenge was observed from splenic vein samples, as compared to the ones from the portal vein. To our knowledge, this is the first report of percutaneous methods to assess zinc release kinetics from the porcine pancreas. PMID:26273676

A comparison of sequential and spiral scanning techniques in brain CT.

PubMed

Pace, Ivana; Zarb, Francis

2015-01-01

To evaluate and compare image quality and radiation dose of sequential computed tomography (CT) examinations of the brain and spiral CT examinations of the brain imaged on a GE HiSpeed NX/I Dual Slice 2CT scanner. A random sample of 40 patients referred for CT examination of the brain was selected and divided into 2 groups. Half of the patients were scanned using the sequential technique; the other half were scanned using the spiral technique. Radiation dose data—both the computed tomography dose index (CTDI) and the dose length product (DLP)—were recorded on a checklist at the end of each examination. Using the European Guidelines on Quality Criteria for Computed Tomography, 4 radiologists conducted a visual grading analysis and rated the level of visibility of 6 anatomical structures considered necessary to produce images of high quality. The mean CTDI(vol) and DLP values were statistically significantly higher (P <.05) with the sequential scans (CTDI(vol): 22.06 mGy; DLP: 304.60 mGy • cm) than with the spiral scans (CTDI(vol): 14.94 mGy; DLP: 229.10 mGy • cm). The mean image quality rating scores for all criteria of the sequential scanning technique were statistically significantly higher (P <.05) in the visual grading analysis than those of the spiral scanning technique. In this local study, the sequential technique was preferred over the spiral technique for both overall image quality and differentiation between gray and white matter in brain CT scans. Other similar studies counter this finding. The radiation dose seen with the sequential CT scanning technique was significantly higher than that seen with the spiral CT scanning technique. However, image quality with the sequential technique was statistically significantly superior (P <.05).

Statistical iterative reconstruction to improve image quality for digital breast tomosynthesis

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

Xu, Shiyu, E-mail: shiyu.xu@gmail.com; Chen, Ying, E-mail: adachen@siu.edu; Lu, Jianping

2015-09-15

Purpose: Digital breast tomosynthesis (DBT) is a novel modality with the potential to improve early detection of breast cancer by providing three-dimensional (3D) imaging with a low radiation dose. 3D image reconstruction presents some challenges: cone-beam and flat-panel geometry, and highly incomplete sampling. A promising means to overcome these challenges is statistical iterative reconstruction (IR), since it provides the flexibility of accurate physics modeling and a general description of system geometry. The authors’ goal was to develop techniques for applying statistical IR to tomosynthesis imaging data. Methods: These techniques include the following: a physics model with a local voxel-pair basedmore » prior with flexible parameters to fine-tune image quality; a precomputed parameter λ in the prior, to remove data dependence and to achieve a uniform resolution property; an effective ray-driven technique to compute the forward and backprojection; and an oversampled, ray-driven method to perform high resolution reconstruction with a practical region-of-interest technique. To assess the performance of these techniques, the authors acquired phantom data on the stationary DBT prototype system. To solve the estimation problem, the authors proposed an optimization-transfer based algorithm framework that potentially allows fewer iterations to achieve an acceptably converged reconstruction. Results: IR improved the detectability of low-contrast and small microcalcifications, reduced cross-plane artifacts, improved spatial resolution, and lowered noise in reconstructed images. Conclusions: Although the computational load remains a significant challenge for practical development, the superior image quality provided by statistical IR, combined with advancing computational techniques, may bring benefits to screening, diagnostics, and intraoperative imaging in clinical applications.« less

Characterization of Surface Water and Groundwater Quality in the Lower Tano River Basin Using Statistical and Isotopic Approach.

NASA Astrophysics Data System (ADS)

Edjah, Adwoba; Stenni, Barbara; Cozzi, Giulio; Turetta, Clara; Dreossi, Giuliano; Tetteh Akiti, Thomas; Yidana, Sandow

2017-04-01

Adwoba Kua- Manza Edjaha, Barbara Stennib,c,Giuliano Dreossib, Giulio Cozzic, Clara Turetta c,T.T Akitid ,Sandow Yidanae a,eDepartment of Earth Science, University of Ghana Legon, Ghana West Africa bDepartment of Enviromental Sciences, Informatics and Statistics, Ca Foscari University of Venice, Italy cInstitute for the Dynamics of Environmental Processes, CNR, Venice, Italy dDepartment of Nuclear Application and Techniques, Graduate School of Nuclear and Allied Sciences University of Ghana Legon This research is part of a PhD research work "Hydrogeological Assessment of the Lower Tano river basin for sustainable economic usage, Ghana, West - Africa". In this study, the researcher investigated surface water and groundwater quality in the Lower Tano river basin. This assessment was based on some selected sampling sites associated with mining activities, and the development of oil and gas. Statistical approach was applied to characterize the quality of surface water and groundwater. Also, water stable isotopes, which is a natural tracer of the hydrological cycle was used to investigate the origin of groundwater recharge in the basin. The study revealed that Pb and Ni values of the surface water and groundwater samples exceeded the WHO standards for drinking water. In addition, water quality index (WQI), based on physicochemical parameters(EC, TDS, pH) and major ions(Ca2+, Na+, Mg2+, HCO3-,NO3-, CL-, SO42-, K+) exhibited good quality water for 60% of the sampled surface water and groundwater. Other statistical techniques, such as Heavy metal pollution index (HPI), degree of contamination (Cd), and heavy metal evaluation index (HEI), based on trace element parameters in the water samples, reveal that 90% of the surface water and groundwater samples belong to high level of pollution. Principal component analysis (PCA) also suggests that the water quality in the basin is likely affected by rock - water interaction and anthropogenic activities (sea water intrusion). This was confirm by further statistical analysis (cluster analysis and correlation matrix) of the water quality parameters. Spatial distribution of water quality parameters, trace elements and the results obtained from the statistical analysis was determined by geographical information system (GIS). In addition, the isotopic analysis of the sampled surface water and groundwater revealed that most of the surface water and groundwater were of meteoric origin with little or no isotopic variations. It is expected that outcomes of this research will form a baseline for making appropriate decision on water quality management by decision makers in the Lower Tano river Basin. Keywords: Water stable isotopes, Trace elements, Multivariate statistics, Evaluation indices, Lower Tano river basin.

Using entropy to cut complex time series

NASA Astrophysics Data System (ADS)

Mertens, David; Poncela Casasnovas, Julia; Spring, Bonnie; Amaral, L. A. N.

2013-03-01

Using techniques from statistical physics, physicists have modeled and analyzed human phenomena varying from academic citation rates to disease spreading to vehicular traffic jams. The last decade's explosion of digital information and the growing ubiquity of smartphones has led to a wealth of human self-reported data. This wealth of data comes at a cost, including non-uniform sampling and statistically significant but physically insignificant correlations. In this talk I present our work using entropy to identify stationary sub-sequences of self-reported human weight from a weight management web site. Our entropic approach-inspired by the infomap network community detection algorithm-is far less biased by rare fluctuations than more traditional time series segmentation techniques. Supported by the Howard Hughes Medical Institute

Annealing of Co-Cr dental alloy: effects on nanostructure and Rockwell hardness

PubMed Central

Soylu, Elif Hilal; İde, Semra; Kılıç, Selim; Sipahi, Cumhur; Pişkin, Bulent; Gökçe, Hasan Suat

2013-01-01

PURPOSE The aim of the study was to evaluate the effect of annealing on the nanostructure and hardness of Co-Cr metal ceramic samples that were fabricated with a direct metal laser sintering (DMLS) technique. MATERIALS AND METHODS Five groups of Co-Cr dental alloy samples were manufactured in a rectangular form measuring 4 × 2 × 2 mm. Samples fabricated by a conventional casting technique (Group I) and prefabricated milling blanks (Group II) were examined as conventional technique groups. The DMLS samples were randomly divided into three groups as not annealed (Group III), annealed in argon atmosphere (Group IV), or annealed in oxygen atmosphere (Group V). The nanostructure was examined with the small-angle X-ray scattering method. The Rockwell hardness test was used to measure the hardness changes in each group, and the means and standard deviations were statistically analyzed by one-way ANOVA for comparison of continuous variables and Tukey's HSD test was used for post hoc analysis. P values of <.05 were accepted as statistically significant. RESULTS The general nanostructures of the samples were composed of small spherical entities stacked atop one another in dendritic form. All groups also displayed different hardness values depending on the manufacturing technique. The annealing procedure and environment directly affected both the nanostructure and hardness of the Co-Cr alloy. Group III exhibited a non-homogeneous structure and increased hardness (48.16 ± 3.02 HRC) because the annealing process was incomplete and the inner stress was not relieved. Annealing in argon atmosphere of Group IV not only relieved the inner stresses but also decreased the hardness (27.40 ± 3.98 HRC). The results of fitting function presented that Group IV was the most homogeneous product as the minimum bilayer thickness was measured (7.11 Å). CONCLUSION After the manufacturing with DMLS technique, annealing in argon atmosphere is an essential process for Co-Cr metal ceramic substructures. The dentists should be familiar with the materials that are used in clinic for prosthodontics treatments. PMID:24353888

From inverse problems to learning: a Statistical Mechanics approach

NASA Astrophysics Data System (ADS)

Baldassi, Carlo; Gerace, Federica; Saglietti, Luca; Zecchina, Riccardo

2018-01-01

We present a brief introduction to the statistical mechanics approaches for the study of inverse problems in data science. We then provide concrete new results on inferring couplings from sampled configurations in systems characterized by an extensive number of stable attractors in the low temperature regime. We also show how these result are connected to the problem of learning with realistic weak signals in computational neuroscience. Our techniques and algorithms rely on advanced mean-field methods developed in the context of disordered systems.

A hybrid LIBS-Raman system combined with chemometrics: an efficient tool for plastic identification and sorting.

PubMed

Shameem, K M Muhammed; Choudhari, Khoobaram S; Bankapur, Aseefhali; Kulkarni, Suresh D; Unnikrishnan, V K; George, Sajan D; Kartha, V B; Santhosh, C

2017-05-01

Classification of plastics is of great importance in the recycling industry as the littering of plastic wastes increases day by day as a result of its extensive use. In this paper, we demonstrate the efficacy of a combined laser-induced breakdown spectroscopy (LIBS)-Raman system for the rapid identification and classification of post-consumer plastics. The atomic information and molecular information of polyethylene terephthalate, polyethylene, polypropylene, and polystyrene were studied using plasma emission spectra and scattered signal obtained in the LIBS and Raman technique, respectively. The collected spectral features of the samples were analyzed using statistical tools (principal component analysis, Mahalanobis distance) to categorize the plastics. The analyses of the data clearly show that elemental information and molecular information obtained from these techniques are efficient for classification of plastics. In addition, the molecular information collected via Raman spectroscopy exhibits clearly distinct features for the transparent plastics (100% discrimination), whereas the LIBS technique shows better spectral feature differences for the colored samples. The study shows that the information obtained from these complementary techniques allows the complete classification of the plastic samples, irrespective of the color or additives. This work further throws some light on the fact that the potential limitations of any of these techniques for sample identification can be overcome by the complementarity of these two techniques. Graphical Abstract ᅟ.

A Generalized Approach to the Two Sample Problem: The Quantile Approach.

DTIC Science & Technology

1981-04-01

advantages in this regard as remarked in Parzen (1979) and Wilk and Gnanadesikan (1968). One explanation of its statistical virtues is the fact that Q...differences between male and female right congruence kneecap angles. Wilkand Gnanadesikan (1968)have named a plot of q versus G- [F(q)] a Q-Q plot and...function techniques. 5.3.5 Comparison Function Techniques Wilk and Gnanadesikan (1968) stimulated research in the area of probability plotting where they

Maximizing Macromolecule Crystal Size for Neutron Diffraction Experiments

NASA Technical Reports Server (NTRS)

Judge, R. A.; Kephart, R.; Leardi, R.; Myles, D. A.; Snell, E. H.; vanderWoerd, M.; Curreri, Peter A. (Technical Monitor)

2002-01-01

A challenge in neutron diffraction experiments is growing large (greater than 1 cu mm) macromolecule crystals. In taking up this challenge we have used statistical experiment design techniques to quickly identify crystallization conditions under which the largest crystals grow. These techniques provide the maximum information for minimal experimental effort, allowing optimal screening of crystallization variables in a simple experimental matrix, using the minimum amount of sample. Analysis of the results quickly tells the investigator what conditions are the most important for the crystallization. These can then be used to maximize the crystallization results in terms of reducing crystal numbers and providing large crystals of suitable habit. We have used these techniques to grow large crystals of Glucose isomerase. Glucose isomerase is an industrial enzyme used extensively in the food industry for the conversion of glucose to fructose. The aim of this study is the elucidation of the enzymatic mechanism at the molecular level. The accurate determination of hydrogen positions, which is critical for this, is a requirement that neutron diffraction is uniquely suited for. Preliminary neutron diffraction experiments with these crystals conducted at the Institute Laue-Langevin (Grenoble, France) reveal diffraction to beyond 2.5 angstrom. Macromolecular crystal growth is a process involving many parameters, and statistical experimental design is naturally suited to this field. These techniques are sample independent and provide an experimental strategy to maximize crystal volume and habit for neutron diffraction studies.

Stratum variance estimation for sample allocation in crop surveys. [Great Plains Corridor

NASA Technical Reports Server (NTRS)

Perry, C. R., Jr.; Chhikara, R. S. (Principal Investigator)

1980-01-01

The problem of determining stratum variances needed in achieving an optimum sample allocation for crop surveys by remote sensing is investigated by considering an approach based on the concept of stratum variance as a function of the sampling unit size. A methodology using the existing and easily available information of historical crop statistics is developed for obtaining initial estimates of tratum variances. The procedure is applied to estimate stratum variances for wheat in the U.S. Great Plains and is evaluated based on the numerical results thus obtained. It is shown that the proposed technique is viable and performs satisfactorily, with the use of a conservative value for the field size and the crop statistics from the small political subdivision level, when the estimated stratum variances were compared to those obtained using the LANDSAT data.

Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

PubMed

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

Anomaly detection for machine learning redshifts applied to SDSS galaxies

NASA Astrophysics Data System (ADS)

Hoyle, Ben; Rau, Markus Michael; Paech, Kerstin; Bonnett, Christopher; Seitz, Stella; Weller, Jochen

2015-10-01

We present an analysis of anomaly detection for machine learning redshift estimation. Anomaly detection allows the removal of poor training examples, which can adversely influence redshift estimates. Anomalous training examples may be photometric galaxies with incorrect spectroscopic redshifts, or galaxies with one or more poorly measured photometric quantity. We select 2.5 million `clean' SDSS DR12 galaxies with reliable spectroscopic redshifts, and 6730 `anomalous' galaxies with spectroscopic redshift measurements which are flagged as unreliable. We contaminate the clean base galaxy sample with galaxies with unreliable redshifts and attempt to recover the contaminating galaxies using the Elliptical Envelope technique. We then train four machine learning architectures for redshift analysis on both the contaminated sample and on the preprocessed `anomaly-removed' sample and measure redshift statistics on a clean validation sample generated without any preprocessing. We find an improvement on all measured statistics of up to 80 per cent when training on the anomaly removed sample as compared with training on the contaminated sample for each of the machine learning routines explored. We further describe a method to estimate the contamination fraction of a base data sample.

Forensic Comparison of Soil Samples Using Nondestructive Elemental Analysis.

PubMed

Uitdehaag, Stefan; Wiarda, Wim; Donders, Timme; Kuiper, Irene

2017-07-01

Soil can play an important role in forensic cases in linking suspects or objects to a crime scene by comparing samples from the crime scene with samples derived from items. This study uses an adapted ED-XRF analysis (sieving instead of grinding to prevent destruction of microfossils) to produce elemental composition data of 20 elements. Different data processing techniques and statistical distances were evaluated using data from 50 samples and the log-LR cost (C llr ). The best performing combination, Canberra distance, relative data, and square root values, is used to construct a discriminative model. Examples of the spatial resolution of the method in crime scenes are shown for three locations, and sampling strategy is discussed. Twelve test cases were analyzed, and results showed that the method is applicable. The study shows how the combination of an analysis technique, a database, and a discriminative model can be used to compare multiple soil samples quickly. © 2016 American Academy of Forensic Sciences.

Optimal spatial sampling techniques for ground truth data in microwave remote sensing of soil moisture

NASA Technical Reports Server (NTRS)

Rao, R. G. S.; Ulaby, F. T.

1977-01-01

The paper examines optimal sampling techniques for obtaining accurate spatial averages of soil moisture, at various depths and for cell sizes in the range 2.5-40 acres, with a minimum number of samples. Both simple random sampling and stratified sampling procedures are used to reach a set of recommended sample sizes for each depth and for each cell size. Major conclusions from statistical sampling test results are that (1) the number of samples required decreases with increasing depth; (2) when the total number of samples cannot be prespecified or the moisture in only one single layer is of interest, then a simple random sample procedure should be used which is based on the observed mean and SD for data from a single field; (3) when the total number of samples can be prespecified and the objective is to measure the soil moisture profile with depth, then stratified random sampling based on optimal allocation should be used; and (4) decreasing the sensor resolution cell size leads to fairly large decreases in samples sizes with stratified sampling procedures, whereas only a moderate decrease is obtained in simple random sampling procedures.

Automated grain mapping using wide angle convergent beam electron diffraction in transmission electron microscope for nanomaterials.

PubMed

Kumar, Vineet

2011-12-01

The grain size statistics, commonly derived from the grain map of a material sample, are important microstructure characteristics that greatly influence its properties. The grain map for nanomaterials is usually obtained manually by visual inspection of the transmission electron microscope (TEM) micrographs because automated methods do not perform satisfactorily. While the visual inspection method provides reliable results, it is a labor intensive process and is often prone to human errors. In this article, an automated grain mapping method is developed using TEM diffraction patterns. The presented method uses wide angle convergent beam diffraction in the TEM. The automated technique was applied on a platinum thin film sample to obtain the grain map and subsequently derive grain size statistics from it. The grain size statistics obtained with the automated method were found in good agreement with the visual inspection method.

Environmental assessment of Al-Hammar Marsh, Southern Iraq.

PubMed

Al-Gburi, Hind Fadhil Abdullah; Al-Tawash, Balsam Salim; Al-Lafta, Hadi Salim

2017-02-01

(a) To determine the spatial distributions and levels of major and minor elements, as well as heavy metals, in water, sediment, and biota (plant and fish) in Al-Hammar Marsh, southern Iraq, and ultimately to supply more comprehensive information for policy-makers to manage the contaminants input into the marsh so that their concentrations do not reach toxic levels. (b) to characterize the seasonal changes in the marsh surface water quality. (c) to address the potential environmental risk of these elements by comparison with the historical levels and global quality guidelines (i.e., World Health Organization (WHO) standard limits). (d) to define the sources of these elements (i.e., natural and/or anthropogenic) using combined multivariate statistical techniques such as Principal Component Analysis (PCA) and Agglomerative Hierarchical Cluster Analysis (AHCA) along with pollution analysis (i.e., enrichment factor analysis). Water, sediment, plant, and fish samples were collected from the marsh, and analyzed for major and minor ions, as well as heavy metals, and then compared to historical levels and global quality guidelines (WHO guidelines). Then, multivariate statistical techniques, such as PCA and AHCA, were used to determine the element sourcing. Water analyses revealed unacceptable values for almost all physio-chemical and biological properties, according to WHO standard limits for drinking water. Almost all major ions and heavy metal concentrations in water showed a distinct decreasing trend at the marsh outlet station compared to other stations. In general, major and minor ions, as well as heavy metals exhibit higher concentrations in winter than in summer. Sediment analyses using multivariate statistical techniques revealed that Mg, Fe, S, P, V, Zn, As, Se, Mo, Co, Ni, Cu, Sr, Br, Cd, Ca, N, Mn, Cr, and Pb were derived from anthropogenic sources, while Al, Si, Ti, K, and Zr were primarily derived from natural sources. Enrichment factor analysis gave results compatible with multivariate statistical techniques findings. Analysis of heavy metals in plant samples revealed that there is no pollution in plants in Al-Hammar Marsh. However, the concentrations of heavy metals in fish samples showed that all samples were contaminated by Pb, Mn, and Ni, while some samples were contaminated by Pb, Mn, and Ni. Decreasing of Tigris and Euphrates discharges during the past decades due to drought conditions and upstream damming, as well as the increasing stress of wastewater effluents from anthropogenic activities, led to degradation of the downstream Al-Hammar Marsh water quality in terms of physical, chemical, and biological properties. As such properties were found to consistently exceed the historical and global quality objectives. However, element concentration decreasing trend at the marsh outlet station compared to other stations indicate that the marsh plays an important role as a natural filtration and bioremediation system. Higher element concentrations in winter were due to runoff from the washing of the surrounding Sabkha during flooding by winter rainstorms. Finally, the high concentrations of heavy metals in fish samples can be attributed to bioaccumulation and biomagnification processes.

Effective Analysis of Reaction Time Data

ERIC Educational Resources Information Center

Whelan, Robert

2008-01-01

Most analyses of reaction time (RT) data are conducted by using the statistical techniques with which psychologists are most familiar, such as analysis of variance on the sample mean. Unfortunately, these methods are usually inappropriate for RT data, because they have little power to detect genuine differences in RT between conditions. In…

Mathematical and statistical approaches for interpreting biomarker compounds in exhaled human breath

EPA Science Inventory

The various instrumental techniques, human studies, and diagnostic tests that produce data from samples of exhaled breath have one thing in common: they all need to be put into a context wherein a posed question can actually be answered. Exhaled breath contains numerous compoun...

Evaluation of dynamically dimensioned search algorithm for optimizing SWAT by altering sampling distributions and searching range

USDA-ARS?s Scientific Manuscript database

The primary advantage of Dynamically Dimensioned Search algorithm (DDS) is that it outperforms many other optimization techniques in both convergence speed and the ability in searching for parameter sets that satisfy statistical guidelines while requiring only one algorithm parameter (perturbation f...

On the Use of Biomineral Oxygen Isotope Data to Identify Human Migrants in the Archaeological Record: Intra-Sample Variation, Statistical Methods and Geographical Considerations

PubMed Central

Lightfoot, Emma; O’Connell, Tamsin C.

2016-01-01

Oxygen isotope analysis of archaeological skeletal remains is an increasingly popular tool to study past human migrations. It is based on the assumption that human body chemistry preserves the δ18O of precipitation in such a way as to be a useful technique for identifying migrants and, potentially, their homelands. In this study, the first such global survey, we draw on published human tooth enamel and bone bioapatite data to explore the validity of using oxygen isotope analyses to identify migrants in the archaeological record. We use human δ18O results to show that there are large variations in human oxygen isotope values within a population sample. This may relate to physiological factors influencing the preservation of the primary isotope signal, or due to human activities (such as brewing, boiling, stewing, differential access to water sources and so on) causing variation in ingested water and food isotope values. We compare the number of outliers identified using various statistical methods. We determine that the most appropriate method for identifying migrants is dependent on the data but is likely to be the IQR or median absolute deviation from the median under most archaeological circumstances. Finally, through a spatial assessment of the dataset, we show that the degree of overlap in human isotope values from different locations across Europe is such that identifying individuals’ homelands on the basis of oxygen isotope analysis alone is not possible for the regions analysed to date. Oxygen isotope analysis is a valid method for identifying first-generation migrants from an archaeological site when used appropriately, however it is difficult to identify migrants using statistical methods for a sample size of less than c. 25 individuals. In the absence of local previous analyses, each sample should be treated as an individual dataset and statistical techniques can be used to identify migrants, but in most cases pinpointing a specific homeland should not be attempted. PMID:27124001

Kinematic and kinetic analysis of overhand, sidearm and underhand lacrosse shot techniques.

PubMed

Macaulay, Charles A J; Katz, Larry; Stergiou, Pro; Stefanyshyn, Darren; Tomaghelli, Luciano

2017-12-01

Lacrosse requires the coordinated performance of many complex skills. One of these skills is shooting on the opponents' net using one of three techniques: overhand, sidearm or underhand. The purpose of this study was to (i) determine which technique generated the highest ball velocity and greatest shot accuracy and (ii) identify kinematic and kinetic variables that contribute to a high velocity and high accuracy shot. Twelve elite male lacrosse players participated in this study. Kinematic data were sampled at 250 Hz, while two-dimensional force plates collected ground reaction force data (1000 Hz). Statistical analysis showed significantly greater ball velocity for the sidearm technique than overhand (P < 0.001) and underhand (P < 0.001) techniques. No statistical difference was found for shot accuracy (P > 0.05). Kinematic and kinetic variables were not significantly correlated to shot accuracy or velocity across all shot types; however, when analysed independently, the lead foot horizontal impulse showed a negative correlation with underhand ball velocity (P = 0.042). This study identifies the technique with the highest ball velocity, defines kinematic and kinetic predictors related to ball velocity and provides information to coaches and athletes concerned with improving lacrosse shot performance.

Computer-aided boundary delineation of agricultural lands

NASA Technical Reports Server (NTRS)

Cheng, Thomas D.; Angelici, Gary L.; Slye, Robert E.; Ma, Matt

1989-01-01

The National Agricultural Statistics Service of the United States Department of Agriculture (USDA) presently uses labor-intensive aerial photographic interpretation techniques to divide large geographical areas into manageable-sized units for estimating domestic crop and livestock production. Prototype software, the computer-aided stratification (CAS) system, was developed to automate the procedure, and currently runs on a Sun-based image processing system. With a background display of LANDSAT Thematic Mapper and United States Geological Survey Digital Line Graph data, the operator uses a cursor to delineate agricultural areas, called sampling units, which are assigned to strata of land-use and land-cover types. The resultant stratified sampling units are used as input into subsequent USDA sampling procedures. As a test, three counties in Missouri were chosen for application of the CAS procedures. Subsequent analysis indicates that CAS was five times faster in creating sampling units than the manual techniques were.

Bayesian Orbit Computation Tools for Objects on Geocentric Orbits

NASA Astrophysics Data System (ADS)

Virtanen, J.; Granvik, M.; Muinonen, K.; Oszkiewicz, D.

2013-08-01

We consider the space-debris orbital inversion problem via the concept of Bayesian inference. The methodology has been put forward for the orbital analysis of solar system small bodies in early 1990's [7] and results in a full solution of the statistical inverse problem given in terms of a posteriori probability density function (PDF) for the orbital parameters. We demonstrate the applicability of our statistical orbital analysis software to Earth orbiting objects, both using well-established Monte Carlo (MC) techniques (for a review, see e.g. [13] as well as recently developed Markov-chain MC (MCMC) techniques (e.g., [9]). In particular, we exploit the novel virtual observation MCMC method [8], which is based on the characterization of the phase-space volume of orbital solutions before the actual MCMC sampling. Our statistical methods and the resulting PDFs immediately enable probabilistic impact predictions to be carried out. Furthermore, this can be readily done also for very sparse data sets and data sets of poor quality - providing that some a priori information on the observational uncertainty is available. For asteroids, impact probabilities with the Earth from the discovery night onwards have been provided, e.g., by [11] and [10], the latter study includes the sampling of the observational-error standard deviation as a random variable.

Creating ensembles of decision trees through sampling

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick

2005-08-30

A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

Adaptive Conditioning of Multiple-Point Geostatistical Facies Simulation to Flow Data with Facies Probability Maps

NASA Astrophysics Data System (ADS)

Khodabakhshi, M.; Jafarpour, B.

2013-12-01

Characterization of complex geologic patterns that create preferential flow paths in certain reservoir systems requires higher-order geostatistical modeling techniques. Multipoint statistics (MPS) provides a flexible grid-based approach for simulating such complex geologic patterns from a conceptual prior model known as a training image (TI). In this approach, a stationary TI that encodes the higher-order spatial statistics of the expected geologic patterns is used to represent the shape and connectivity of the underlying lithofacies. While MPS is quite powerful for describing complex geologic facies connectivity, the nonlinear and complex relation between the flow data and facies distribution makes flow data conditioning quite challenging. We propose an adaptive technique for conditioning facies simulation from a prior TI to nonlinear flow data. Non-adaptive strategies for conditioning facies simulation to flow data can involves many forward flow model solutions that can be computationally very demanding. To improve the conditioning efficiency, we develop an adaptive sampling approach through a data feedback mechanism based on the sampling history. In this approach, after a short period of sampling burn-in time where unconditional samples are generated and passed through an acceptance/rejection test, an ensemble of accepted samples is identified and used to generate a facies probability map. This facies probability map contains the common features of the accepted samples and provides conditioning information about facies occurrence in each grid block, which is used to guide the conditional facies simulation process. As the sampling progresses, the initial probability map is updated according to the collective information about the facies distribution in the chain of accepted samples to increase the acceptance rate and efficiency of the conditioning. This conditioning process can be viewed as an optimization approach where each new sample is proposed based on the sampling history to improve the data mismatch objective function. We extend the application of this adaptive conditioning approach to the case where multiple training images are proposed to describe the geologic scenario in a given formation. We discuss the advantages and limitations of the proposed adaptive conditioning scheme and use numerical experiments from fluvial channel formations to demonstrate its applicability and performance compared to non-adaptive conditioning techniques.

Improving the sampling strategy of the Joint Danube Survey 3 (2013) by means of multivariate statistical techniques applied on selected physico-chemical and biological data.

PubMed

Hamchevici, Carmen; Udrea, Ion

2013-11-01

The concept of basin-wide Joint Danube Survey (JDS) was launched by the International Commission for the Protection of the Danube River (ICPDR) as a tool for investigative monitoring under the Water Framework Directive (WFD), with a frequency of 6 years. The first JDS was carried out in 2001 and its success in providing key information for characterisation of the Danube River Basin District as required by WFD lead to the organisation of the second JDS in 2007, which was the world's biggest river research expedition in that year. The present paper presents an approach for improving the survey strategy for the next planned survey JDS3 (2013) by means of several multivariate statistical techniques. In order to design the optimum structure in terms of parameters and sampling sites, principal component analysis (PCA), factor analysis (FA) and cluster analysis were applied on JDS2 data for 13 selected physico-chemical and one biological element measured in 78 sampling sites located on the main course of the Danube. Results from PCA/FA showed that most of the dataset variance (above 75%) was explained by five varifactors loaded with 8 out of 14 variables: physical (transparency and total suspended solids), relevant nutrients (N-nitrates and P-orthophosphates), feedback effects of primary production (pH, alkalinity and dissolved oxygen) and algal biomass. Taking into account the representation of the factor scores given by FA versus sampling sites and the major groups generated by the clustering procedure, the spatial network of the next survey could be carefully tailored, leading to a decreasing of sampling sites by more than 30%. The approach of target oriented sampling strategy based on the selected multivariate statistics can provide a strong reduction in dimensionality of the original data and corresponding costs as well, without any loss of information.

The exact probability distribution of the rank product statistics for replicated experiments.

PubMed

Eisinga, Rob; Breitling, Rainer; Heskes, Tom

2013-03-18

The rank product method is a widely accepted technique for detecting differentially regulated genes in replicated microarray experiments. To approximate the sampling distribution of the rank product statistic, the original publication proposed a permutation approach, whereas recently an alternative approximation based on the continuous gamma distribution was suggested. However, both approximations are imperfect for estimating small tail probabilities. In this paper we relate the rank product statistic to number theory and provide a derivation of its exact probability distribution and the true tail probabilities. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Scaling up to address data science challenges

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

Wendelberger, Joanne R.

Statistics and Data Science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields such as statistics, machine learning, computer science, and applied mathematics can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing. Here, this article will explore various challenges in Data Science and will highlight statistical approaches that can facilitate analysis of large-scale data including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithmsmore » and procedures for efficient processing.« less

Scaling up to address data science challenges

DOE PAGES

Wendelberger, Joanne R.

2017-04-27

Statistics and Data Science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields such as statistics, machine learning, computer science, and applied mathematics can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing. Here, this article will explore various challenges in Data Science and will highlight statistical approaches that can facilitate analysis of large-scale data including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithmsmore » and procedures for efficient processing.« less

Adventures in Parallel Processing: Entry, Descent and Landing Simulation for the Genesis and Stardust Missions

NASA Technical Reports Server (NTRS)

Lyons, Daniel T.; Desai, Prasun N.

2005-01-01

This paper will describe the Entry, Descent and Landing simulation tradeoffs and techniques that were used to provide the Monte Carlo data required to approve entry during a critical period just before entry of the Genesis Sample Return Capsule. The same techniques will be used again when Stardust returns on January 15, 2006. Only one hour was available for the simulation which propagated 2000 dispersed entry states to the ground. Creative simulation tradeoffs combined with parallel processing were needed to provide the landing footprint statistics that were an essential part of the Go/NoGo decision that authorized release of the Sample Return Capsule a few hours before entry.

Supervised target detection in hyperspectral images using one-class Fukunaga-Koontz Transform

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Bal, Abdullah

2016-05-01

A novel hyperspectral target detection technique based on Fukunaga-Koontz transform (FKT) is presented. FKT offers significant properties for feature selection and ordering. However, it can only be used to solve multi-pattern classification problems. Target detection may be considered as a two-class classification problem, i.e., target versus background clutter. Nevertheless, background clutter typically contains different types of materials. That's why; target detection techniques are different than classification methods by way of modeling clutter. To avoid the modeling of the background clutter, we have improved one-class FKT (OC-FKT) for target detection. The statistical properties of target training samples are used to define tunnel-like boundary of the target class. Non-target samples are then created synthetically as to be outside of the boundary. Thus, only limited target samples become adequate for training of FKT. The hyperspectral image experiments confirm that the proposed OC-FKT technique provides an effective means for target detection.

Innovative acoustic techniques for studying new materials and new developments in solid state physics

NASA Astrophysics Data System (ADS)

Maynard, Julian D.

1994-06-01

The goals of this project involve the use of innovative acoustic techniques to study new materials and new developments in solid state physics. Major accomplishments include (a) the preparation and publication of a number of papers and book chapters, (b) the measurement and new analysis of more samples of aluminum quasicrystal and its cubic approximant to eliminate the possibility of sample artifacts, (c) the use of resonant ultrasound to measure acoustic attenuation and determine the effects of heat treatment on ceramics, (d) the extension of our technique for measuring even lower (possibly the lowest) infrared optical absorption coefficient, and (e) the measurement of the effects of disorder on the propagation of a nonlinear pulse, and (f) the observation of statistical effects in measurements of individual bond breaking events in fracture.

Comparative Evaluation of Conventional and Accelerated Castings on Marginal Fit and Surface Roughness

PubMed Central

Jadhav, Vivek Dattatray; Motwani, Bhagwan K.; Shinde, Jitendra; Adhapure, Prasad

2017-01-01

Aims: The aim of this study was to evaluate the marginal fit and surface roughness of complete cast crowns made by a conventional and an accelerated casting technique. Settings and Design: This study was divided into three parts. In Part I, the marginal fit of full metal crowns made by both casting techniques in the vertical direction was checked, in Part II, the fit of sectional metal crowns in the horizontal direction made by both casting techniques was checked, and in Part III, the surface roughness of disc-shaped metal plate specimens made by both casting techniques was checked. Materials and Methods: A conventional technique was compared with an accelerated technique. In Part I of the study, the marginal fit of the full metal crowns as well as in Part II, the horizontal fit of sectional metal crowns made by both casting techniques was determined, and in Part III, the surface roughness of castings made with the same techniques was compared. Statistical Analysis Used: The results of the t-test and independent sample test do not indicate statistically significant differences in the marginal discrepancy detected between the two casting techniques. Results: For the marginal discrepancy and surface roughness, crowns fabricated with the accelerated technique were significantly different from those fabricated with the conventional technique. Conclusions: Accelerated casting technique showed quite satisfactory results, but the conventional technique was superior in terms of marginal fit and surface roughness. PMID:29042726

A rational approach to legacy data validation when transitioning between electronic health record systems.

PubMed

Pageler, Natalie M; Grazier G'Sell, Max Jacob; Chandler, Warren; Mailes, Emily; Yang, Christine; Longhurst, Christopher A

2016-09-01

The objective of this project was to use statistical techniques to determine the completeness and accuracy of data migrated during electronic health record conversion. Data validation during migration consists of mapped record testing and validation of a sample of the data for completeness and accuracy. We statistically determined a randomized sample size for each data type based on the desired confidence level and error limits. The only error identified in the post go-live period was a failure to migrate some clinical notes, which was unrelated to the validation process. No errors in the migrated data were found during the 12- month post-implementation period. Compared to the typical industry approach, we have demonstrated that a statistical approach to sampling size for data validation can ensure consistent confidence levels while maximizing efficiency of the validation process during a major electronic health record conversion. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The issue of multiple univariate comparisons in the context of neuroelectric brain mapping: an application in a neuromarketing experiment.

PubMed

Vecchiato, G; De Vico Fallani, F; Astolfi, L; Toppi, J; Cincotti, F; Mattia, D; Salinari, S; Babiloni, F

2010-08-30

This paper presents some considerations about the use of adequate statistical techniques in the framework of the neuroelectromagnetic brain mapping. With the use of advanced EEG/MEG recording setup involving hundred of sensors, the issue of the protection against the type I errors that could occur during the execution of hundred of univariate statistical tests, has gained interest. In the present experiment, we investigated the EEG signals from a mannequin acting as an experimental subject. Data have been collected while performing a neuromarketing experiment and analyzed with state of the art computational tools adopted in specialized literature. Results showed that electric data from the mannequin's head presents statistical significant differences in power spectra during the visualization of a commercial advertising when compared to the power spectra gathered during a documentary, when no adjustments were made on the alpha level of the multiple univariate tests performed. The use of the Bonferroni or Bonferroni-Holm adjustments returned correctly no differences between the signals gathered from the mannequin in the two experimental conditions. An partial sample of recently published literature on different neuroscience journals suggested that at least the 30% of the papers do not use statistical protection for the type I errors. While the occurrence of type I errors could be easily managed with appropriate statistical techniques, the use of such techniques is still not so largely adopted in the literature. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Limitations to mapping habitat-use areas in changing landscapes using the Mahalanobis distance statistic

USGS Publications Warehouse

Knick, Steven T.; Rotenberry, J.T.

1998-01-01

We tested the potential of a GIS mapping technique, using a resource selection model developed for black-tailed jackrabbits (Lepus californicus) and based on the Mahalanobis distance statistic, to track changes in shrubsteppe habitats in southwestern Idaho. If successful, the technique could be used to predict animal use areas, or those undergoing change, in different regions from the same selection function and variables without additional sampling. We determined the multivariate mean vector of 7 GIS variables that described habitats used by jackrabbits. We then ranked the similarity of all cells in the GIS coverage from their Mahalanobis distance to the mean habitat vector. The resulting map accurately depicted areas where we sighted jackrabbits on verification surveys. We then simulated an increase in shrublands (which are important habitats). Contrary to expectation, the new configurations were classified as lower similarity relative to the original mean habitat vector. Because the selection function is based on a unimodal mean, any deviation, even if biologically positive, creates larger Malanobis distances and lower similarity values. We recommend the Mahalanobis distance technique for mapping animal use areas when animals are distributed optimally, the landscape is well-sampled to determine the mean habitat vector, and distributions of the habitat variables does not change.

Cancer diagnosis by infrared spectroscopy: methodological aspects

NASA Astrophysics Data System (ADS)

Jackson, Michael; Kim, Keith; Tetteh, John; Mansfield, James R.; Dolenko, Brion; Somorjai, Raymond L.; Orr, F. W.; Watson, Peter H.; Mantsch, Henry H.

1998-04-01

IR spectroscopy is proving to be a powerful tool for the study and diagnosis of cancer. The application of IR spectroscopy to the analysis of cultured tumor cells and grading of breast cancer sections is outlined. Potential sources of error in spectral interpretation due to variations in sample histology and artifacts associated with sample storage and preparation are discussed. The application of statistical techniques to assess differences between spectra and to non-subjectively classify spectra is demonstrated.

Investigation of Error Patterns in Geographical Databases

NASA Technical Reports Server (NTRS)

Dryer, David; Jacobs, Derya A.; Karayaz, Gamze; Gronbech, Chris; Jones, Denise R. (Technical Monitor)

2002-01-01

The objective of the research conducted in this project is to develop a methodology to investigate the accuracy of Airport Safety Modeling Data (ASMD) using statistical, visualization, and Artificial Neural Network (ANN) techniques. Such a methodology can contribute to answering the following research questions: Over a representative sampling of ASMD databases, can statistical error analysis techniques be accurately learned and replicated by ANN modeling techniques? This representative ASMD sample should include numerous airports and a variety of terrain characterizations. Is it possible to identify and automate the recognition of patterns of error related to geographical features? Do such patterns of error relate to specific geographical features, such as elevation or terrain slope? Is it possible to combine the errors in small regions into an error prediction for a larger region? What are the data density reduction implications of this work? ASMD may be used as the source of terrain data for a synthetic visual system to be used in the cockpit of aircraft when visual reference to ground features is not possible during conditions of marginal weather or reduced visibility. In this research, United States Geologic Survey (USGS) digital elevation model (DEM) data has been selected as the benchmark. Artificial Neural Networks (ANNS) have been used and tested as alternate methods in place of the statistical methods in similar problems. They often perform better in pattern recognition, prediction and classification and categorization problems. Many studies show that when the data is complex and noisy, the accuracy of ANN models is generally higher than those of comparable traditional methods.

Curve fitting air sample filter decay curves to estimate transuranic content.

PubMed

Hayes, Robert B; Chiou, Hung Cheng

2004-01-01

By testing industry standard techniques for radon progeny evaluation on air sample filters, a new technique is developed to evaluate transuranic activity on air filters by curve fitting the decay curves. The industry method modified here is simply the use of filter activity measurements at different times to estimate the air concentrations of radon progeny. The primary modification was to not look for specific radon progeny values but rather transuranic activity. By using a method that will provide reasonably conservative estimates of the transuranic activity present on a filter, some credit for the decay curve shape can then be taken. By carrying out rigorous statistical analysis of the curve fits to over 65 samples having no transuranic activity taken over a 10-mo period, an optimization of the fitting function and quality tests for this purpose was attained.

Analyzing the Origins of Childhood Externalizing Behavioral Problems

ERIC Educational Resources Information Center

Barnes, J. C.; Boutwell, Brian B.; Beaver, Kevin M.; Gibson, Chris L.

2013-01-01

Drawing on a sample of twin children from the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B; Snow et al., 2009), the current study analyzed 2 of the most prominent predictors of externalizing behavioral problems (EBP) in children: (a) parental use of spankings and (b) childhood self-regulation. A variety of statistical techniques were…

The Acquisition of Gender Labels in Infancy: Implications for Gender-Typed Play

ERIC Educational Resources Information Center

Zosuls, Kristina M.; Ruble, Diane N.; Tamis-LeMonda, Catherine S.; Shrout, Patrick E.; Bornstein, Marc H.; Greulich, Faith K.

2009-01-01

Two aspects of children's early gender development--the spontaneous production of gender labels and gender-typed play--were examined longitudinally in a sample of 82 children. Survival analysis, a statistical technique well suited to questions involving developmental transitions, was used to investigate the timing of the onset of children's gender…

The Effect of the Multivariate Box-Cox Transformation on the Power of MANOVA.

ERIC Educational Resources Information Center

Kirisci, Levent; Hsu, Tse-Chi

Most of the multivariate statistical techniques rely on the assumption of multivariate normality. The effects of non-normality on multivariate tests are assumed to be negligible when variance-covariance matrices and sample sizes are equal. Therefore, in practice, investigators do not usually attempt to remove non-normality. In this simulation…

Statistical Modeling of the Individual: Rationale and Application of Multivariate Stationary Time Series Analysis

ERIC Educational Resources Information Center

Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter C. M.

2005-01-01

Results obtained with interindividual techniques in a representative sample of a population are not necessarily generalizable to the individual members of this population. In this article the specific condition is presented that must be satisfied to generalize from the interindividual level to the intraindividual level. A way to investigate…

Assessing Students' Metacognitive Awareness of Learning Strategies among Secondary School Students in Edo State, Nigeria

ERIC Educational Resources Information Center

Okoza, Jolly; Aluede, Oyaziwo; Owens-Sogolo, Osasere

2013-01-01

This study examined metacognitive awareness of learning strategies among Secondary School Students in Edo State, Nigeria. The study was an exploratory one, which utilized descriptive statistics. A total number of 1200 students drawn through multistage proportionate random sampling technique participated in the study. The study found that secondary…

Investigation of Particle Sampling Bias in the Shear Flow Field Downstream of a Backward Facing Step

NASA Technical Reports Server (NTRS)

Meyers, James F.; Kjelgaard, Scott O.; Hepner, Timothy E.

1990-01-01

The flow field about a backward facing step was investigated to determine the characteristics of particle sampling bias in the various flow phenomena. The investigation used the calculation of the velocity:data rate correlation coefficient as a measure of statistical dependence and thus the degree of velocity bias. While the investigation found negligible dependence within the free stream region, increased dependence was found within the boundary and shear layers. Full classic correction techniques over-compensated the data since the dependence was weak, even in the boundary layer and shear regions. The paper emphasizes the necessity to determine the degree of particle sampling bias for each measurement ensemble and not use generalized assumptions to correct the data. Further, it recommends the calculation of the velocity:data rate correlation coefficient become a standard statistical calculation in the analysis of all laser velocimeter data.

Destructive testings: dry drilling operations with TruPro system to collect samples in a powder form, from two hulls containing immobilized wastes in a hydraulic binder

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

Pombet, Denis; Desnoyers, Yvon; Charters, Grant

2013-07-01

The TruPro{sup R} process enables to collect a significant number of samples to characterize radiological materials. This innovative and alternative technique is experimented for the ANDRA quality-control inspection of cemented packages. It proves to be quicker and more prolific than the current methodology. Using classical statistics and geo-statistics approaches, the physical and radiological characteristics of two hulls containing immobilized wastes (sludges or concentrates) in a hydraulic binder are assessed in this paper. The waste homogeneity is also evaluated in comparison to ANDRA criterion. Sensibility to sample size (support effect), presence of extreme values, acceptable deviation rate and minimum number ofmore » data are discussed. The final objectives are to check the homogeneity of the two characterized radwaste packages and also to validate and reinforce this alternative characterization methodology. (authors)« less

Analyzing Immunoglobulin Repertoires

PubMed Central

Chaudhary, Neha; Wesemann, Duane R.

2018-01-01

Somatic assembly of T cell receptor and B cell receptor (BCR) genes produces a vast diversity of lymphocyte antigen recognition capacity. The advent of efficient high-throughput sequencing of lymphocyte antigen receptor genes has recently generated unprecedented opportunities for exploration of adaptive immune responses. With these opportunities have come significant challenges in understanding the analysis techniques that most accurately reflect underlying biological phenomena. In this regard, sample preparation and sequence analysis techniques, which have largely been borrowed and adapted from other fields, continue to evolve. Here, we review current methods and challenges of library preparation, sequencing and statistical analysis of lymphocyte receptor repertoire studies. We discuss the general steps in the process of immune repertoire generation including sample preparation, platforms available for sequencing, processing of sequencing data, measurable features of the immune repertoire, and the statistical tools that can be used for analysis and interpretation of the data. Because BCR analysis harbors additional complexities, such as immunoglobulin (Ig) (i.e., antibody) gene somatic hypermutation and class switch recombination, the emphasis of this review is on Ig/BCR sequence analysis. PMID:29593723

The impact of extended voice use on the acoustic characteristics of phonation after training and performance of actors from the La MaMa Experimental Theater club.

PubMed

Ferrone, Carol; Galgano, Jessica; Ramig, Lorraine Olson

2011-05-01

To test the hypothesis that extensive use of La MaMa vocal technique may result in symptoms of vocal abuse, an evaluation of the acoustic and perceptual characteristics of voice for eight performers from the Great Jones Repertory Company of the La MaMa Experimental Theater was conducted. This vocal technique includes wide ranges of frequency from 46 to 2003 Hz and vocal intensity that is sustained at 90-108 dB sound pressure level with a mouth-to-microphone distance of 30 cm for 3-4 hours per performance. The actors rehearsed for 4 hours per day, 5 days per week for 14 weeks before the series of performances. Thirty-nine performances were presented in 6 weeks. Three pretraining, three posttraining, and two postperformance series data collection sessions were carried out for each performer. Speech samples were gathered using the CSL 4500 and analyzed using Real-Time Pitch program and Multidimensional Voice Program. Acoustic analysis was performed on 48 tokens of sustained vowel phonation for each subject. Statistical analysis was performed using the Friedman test of related samples. Perceptual analysis included professional listeners rating voice quality in pretraining, posttraining, and postperformance samples of the Rainbow Passage and sample lines from the plays. The majority of professional listeners (11/12) judged that this technique would result in symptoms of vocal abuse; however, acoustic data revealed statistically stable or improved measurements for all subjects in most dependent acoustic variables when compared with both posttraining and postperformance trials. These findings add support to the notion that a technique that may be perceived as vocally abusive, generating 90-100 dB sound pressure level and sustained over 6 weeks of performances, actually resulted in improved vocal strength and flexibility. Copyright © 2011 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Confocal Imaging of porous media

NASA Astrophysics Data System (ADS)

Shah, S.; Crawshaw, D.; Boek, D.

2012-12-01

Carbonate rocks, which hold approximately 50% of the world's oil and gas reserves, have a very complicated and heterogeneous structure in comparison with sandstone reservoir rock. We present advances with different techniques to image, reconstruct, and characterize statistically the micro-geometry of carbonate pores. The main goal here is to develop a technique to obtain two dimensional and three dimensional images using Confocal Laser Scanning Microscopy. CLSM is used in epi-fluorescent imaging mode, allowing for the very high optical resolution of features well below 1μm size. Images of pore structures were captured using CLSM imaging where spaces in the carbonate samples were impregnated with a fluorescent, dyed epoxy-resin, and scanned in the x-y plane by a laser probe. We discuss the sample preparation in detail for Confocal Imaging to obtain sub-micron resolution images of heterogeneous carbonate rocks. We also discuss the technical and practical aspects of this imaging technique, including its advantages and limitation. We present several examples of this application, including studying pore geometry in carbonates, characterizing sub-resolution porosity in two dimensional images. We then describe approaches to extract statistical information about porosity using image processing and spatial correlation function. We have managed to obtain very low depth information in z -axis (~ 50μm) to develop three dimensional images of carbonate rocks with the current capabilities and limitation of CLSM technique. Hence, we have planned a novel technique to obtain higher depth information to obtain high three dimensional images with sub-micron resolution possible in the lateral and axial planes.

Statistical sex determination from craniometrics: Comparison of linear discriminant analysis, logistic regression, and support vector machines.

PubMed

Santos, Frédéric; Guyomarc'h, Pierre; Bruzek, Jaroslav

2014-12-01

Accuracy of identification tools in forensic anthropology primarily rely upon the variations inherent in the data upon which they are built. Sex determination methods based on craniometrics are widely used and known to be specific to several factors (e.g. sample distribution, population, age, secular trends, measurement technique, etc.). The goal of this study is to discuss the potential variations linked to the statistical treatment of the data. Traditional craniometrics of four samples extracted from documented osteological collections (from Portugal, France, the U.S.A., and Thailand) were used to test three different classification methods: linear discriminant analysis (LDA), logistic regression (LR), and support vector machines (SVM). The Portuguese sample was set as a training model on which the other samples were applied in order to assess the validity and reliability of the different models. The tests were performed using different parameters: some included the selection of the best predictors; some included a strict decision threshold (sex assessed only if the related posterior probability was high, including the notion of indeterminate result); and some used an unbalanced sex-ratio. Results indicated that LR tends to perform slightly better than the other techniques and offers a better selection of predictors. Also, the use of a decision threshold (i.e. p>0.95) is essential to ensure an acceptable reliability of sex determination methods based on craniometrics. Although the Portuguese, French, and American samples share a similar sexual dimorphism, application of Western models on the Thai sample (that displayed a lower degree of dimorphism) was unsuccessful. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Improvements in sub-grid, microphysics averages using quadrature based approaches

NASA Astrophysics Data System (ADS)

Chowdhary, K.; Debusschere, B.; Larson, V. E.

2013-12-01

Sub-grid variability in microphysical processes plays a critical role in atmospheric climate models. In order to account for this sub-grid variability, Larson and Schanen (2013) propose placing a probability density function on the sub-grid cloud microphysics quantities, e.g. autoconversion rate, essentially interpreting the cloud microphysics quantities as a random variable in each grid box. Random sampling techniques, e.g. Monte Carlo and Latin Hypercube, can be used to calculate statistics, e.g. averages, on the microphysics quantities, which then feed back into the model dynamics on the coarse scale. We propose an alternate approach using numerical quadrature methods based on deterministic sampling points to compute the statistical moments of microphysics quantities in each grid box. We have performed a preliminary test on the Kessler autoconversion formula, and, upon comparison with Latin Hypercube sampling, our approach shows an increased level of accuracy with a reduction in sample size by almost two orders of magnitude. Application to other microphysics processes is the subject of ongoing research.

Analysis of chemical warfare agents. II. Use of thiols and statistical experimental design for the trace level determination of vesicant compounds in air samples.

PubMed

Muir, Bob; Quick, Suzanne; Slater, Ben J; Cooper, David B; Moran, Mary C; Timperley, Christopher M; Carrick, Wendy A; Burnell, Christopher K

2005-03-18

Thermal desorption with gas chromatography-mass spectrometry (TD-GC-MS) remains the technique of choice for analysis of trace concentrations of analytes in air samples. This paper describes the development and application of a method for analysing the vesicant compounds sulfur mustard and Lewisites I-III. 3,4-Dimercaptotoluene and butanethiol were used to spike sorbent tubes and vesicant vapours sampled; Lewisite I and II reacted with the thiols while sulfur mustard and Lewisite III did not. Statistical experimental design was used to optimise thermal desorption parameters and the optimum method used to determine vesicant compounds in headspace samples taken from a decontamination trial. 3,4-Dimercaptotoluene reacted with Lewisites I and II to give a common derivative with a limit of detection (LOD) of 260 microg m(-3), while the butanethiol gave distinct derivatives with limits of detection around 30 microg m(-3).

Efficient bootstrap estimates for tail statistics

NASA Astrophysics Data System (ADS)

Breivik, Øyvind; Aarnes, Ole Johan

2017-03-01

Bootstrap resamples can be used to investigate the tail of empirical distributions as well as return value estimates from the extremal behaviour of the sample. Specifically, the confidence intervals on return value estimates or bounds on in-sample tail statistics can be obtained using bootstrap techniques. However, non-parametric bootstrapping from the entire sample is expensive. It is shown here that it suffices to bootstrap from a small subset consisting of the highest entries in the sequence to make estimates that are essentially identical to bootstraps from the entire sample. Similarly, bootstrap estimates of confidence intervals of threshold return estimates are found to be well approximated by using a subset consisting of the highest entries. This has practical consequences in fields such as meteorology, oceanography and hydrology where return values are calculated from very large gridded model integrations spanning decades at high temporal resolution or from large ensembles of independent and identically distributed model fields. In such cases the computational savings are substantial.

Field Validity and Feasibility of Four Techniques for the Detection of Trichuris in Simians: A Model for Monitoring Drug Efficacy in Public Health?

PubMed Central

Levecke, Bruno; De Wilde, Nathalie; Vandenhoute, Els; Vercruysse, Jozef

2009-01-01

Background Soil-transmitted helminths, such as Trichuris trichiura, are of major concern in public health. Current efforts to control these helminth infections involve periodic mass treatment in endemic areas. Since these large-scale interventions are likely to intensify, monitoring the drug efficacy will become indispensible. However, studies comparing detection techniques based on sensitivity, fecal egg counts (FEC), feasibility for mass diagnosis and drug efficacy estimates are scarce. Methodology/Principal Findings In the present study, the ether-based concentration, the Parasep Solvent Free (SF), the McMaster and the FLOTAC techniques were compared based on both validity and feasibility for the detection of Trichuris eggs in 100 fecal samples of nonhuman primates. In addition, the drug efficacy estimates of quantitative techniques was examined using a statistical simulation. Trichuris eggs were found in 47% of the samples. FLOTAC was the most sensitive technique (100%), followed by the Parasep SF (83.0% [95% confidence interval (CI): 82.4–83.6%]) and the ether-based concentration technique (76.6% [95% CI: 75.8–77.3%]). McMaster was the least sensitive (61.7% [95% CI: 60.7–62.6%]) and failed to detect low FEC. The quantitative comparison revealed a positive correlation between the four techniques (Rs = 0.85–0.93; p<0.0001). However, the ether-based concentration technique and the Parasep SF detected significantly fewer eggs than both the McMaster and the FLOTAC (p<0.0083). Overall, the McMaster was the most feasible technique (3.9 min/sample for preparing, reading and cleaning of the apparatus), followed by the ether-based concentration technique (7.7 min/sample) and the FLOTAC (9.8 min/sample). Parasep SF was the least feasible (17.7 min/sample). The simulation revealed that the sensitivity is less important for monitoring drug efficacy and that both FLOTAC and McMaster were reliable estimators. Conclusions/Significance The results of this study demonstrated that McMaster is a promising technique when making use of FEC to monitor drug efficacy in Trichuris. PMID:19172171

Gene coexpression measures in large heterogeneous samples using count statistics.

PubMed

Wang, Y X Rachel; Waterman, Michael S; Huang, Haiyan

2014-11-18

With the advent of high-throughput technologies making large-scale gene expression data readily available, developing appropriate computational tools to process these data and distill insights into systems biology has been an important part of the "big data" challenge. Gene coexpression is one of the earliest techniques developed that is still widely in use for functional annotation, pathway analysis, and, most importantly, the reconstruction of gene regulatory networks, based on gene expression data. However, most coexpression measures do not specifically account for local features in expression profiles. For example, it is very likely that the patterns of gene association may change or only exist in a subset of the samples, especially when the samples are pooled from a range of experiments. We propose two new gene coexpression statistics based on counting local patterns of gene expression ranks to take into account the potentially diverse nature of gene interactions. In particular, one of our statistics is designed for time-course data with local dependence structures, such as time series coupled over a subregion of the time domain. We provide asymptotic analysis of their distributions and power, and evaluate their performance against a wide range of existing coexpression measures on simulated and real data. Our new statistics are fast to compute, robust against outliers, and show comparable and often better general performance.

Comparison of five parasitological techniques for laboratory diagnosis of Balantidium coli cysts.

PubMed

Barbosa, Alynne da Silva; Bastos, Otilio Machado Pereira; Uchôa, Claudia Maria Antunes; Pissinatti, Alcides; Bastos, Augusto César Machado Pereira; Souza, Igo Vieira de; Dib, Laís Verdan; Azevedo, Eduarda Peixoto; Siqueira, Mayara Perlingeiro de; Cardozo, Matheus Lessa; Amendoeira, Maria Regina Reis

2016-01-01

Balantidium coli is a protozoon that can cause dysentery in humans, pigs and nonhuman primates, with zoonotic potential. In the literature, there is still little information on the effectiveness of different laboratory techniques for diagnosing this disease. This study compared and evaluated the performance of the Lutz, modified Ritchie, Faust, modified Sheather and direct examination techniques for detecting cysts of this protozoon. Between 2012 and 2014, 1905 fecal samples were collected from captive animals in the state of Rio de Janeiro. Of these, 790 were obtained from the rectum of pigs and 1115 from enclosures occupied by nonhuman primates. B. coli cysts were most evident through direct examination (22.4% of the samples) and the Lutz technique (21%). Fair agreement (Kappa = 0.41; p < 0.05) was observed only between direct examination and Lutz. The flotation techniques (Faust and modified Sheather) did not show good recovery of cysts. A statistically significant difference (p < 0.05) in the frequency of cysts between pigs and nonhuman primates could only be observed through direct examination and the Lutz technique. The most efficient method for diagnosing this parasitosis was seen to an association between direct examination and the spontaneous sedimentation technique.

Experimental analysis of computer system dependability

NASA Technical Reports Server (NTRS)

Iyer, Ravishankar, K.; Tang, Dong

1993-01-01

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance.

Powerful Statistical Inference for Nested Data Using Sufficient Summary Statistics

PubMed Central

Dowding, Irene; Haufe, Stefan

2018-01-01

Hierarchically-organized data arise naturally in many psychology and neuroscience studies. As the standard assumption of independent and identically distributed samples does not hold for such data, two important problems are to accurately estimate group-level effect sizes, and to obtain powerful statistical tests against group-level null hypotheses. A common approach is to summarize subject-level data by a single quantity per subject, which is often the mean or the difference between class means, and treat these as samples in a group-level t-test. This “naive” approach is, however, suboptimal in terms of statistical power, as it ignores information about the intra-subject variance. To address this issue, we review several approaches to deal with nested data, with a focus on methods that are easy to implement. With what we call the sufficient-summary-statistic approach, we highlight a computationally efficient technique that can improve statistical power by taking into account within-subject variances, and we provide step-by-step instructions on how to apply this approach to a number of frequently-used measures of effect size. The properties of the reviewed approaches and the potential benefits over a group-level t-test are quantitatively assessed on simulated data and demonstrated on EEG data from a simulated-driving experiment. PMID:29615885

Statistics based sampling for controller and estimator design

NASA Astrophysics Data System (ADS)

Tenne, Dirk

The purpose of this research is the development of statistical design tools for robust feed-forward/feedback controllers and nonlinear estimators. This dissertation is threefold and addresses the aforementioned topics nonlinear estimation, target tracking and robust control. To develop statistically robust controllers and nonlinear estimation algorithms, research has been performed to extend existing techniques, which propagate the statistics of the state, to achieve higher order accuracy. The so-called unscented transformation has been extended to capture higher order moments. Furthermore, higher order moment update algorithms based on a truncated power series have been developed. The proposed techniques are tested on various benchmark examples. Furthermore, the unscented transformation has been utilized to develop a three dimensional geometrically constrained target tracker. The proposed planar circular prediction algorithm has been developed in a local coordinate framework, which is amenable to extension of the tracking algorithm to three dimensional space. This tracker combines the predictions of a circular prediction algorithm and a constant velocity filter by utilizing the Covariance Intersection. This combined prediction can be updated with the subsequent measurement using a linear estimator. The proposed technique is illustrated on a 3D benchmark trajectory, which includes coordinated turns and straight line maneuvers. The third part of this dissertation addresses the design of controller which include knowledge of parametric uncertainties and their distributions. The parameter distributions are approximated by a finite set of points which are calculated by the unscented transformation. This set of points is used to design robust controllers which minimize a statistical performance of the plant over the domain of uncertainty consisting of a combination of the mean and variance. The proposed technique is illustrated on three benchmark problems. The first relates to the design of prefilters for a linear and nonlinear spring-mass-dashpot system and the second applies a feedback controller to a hovering helicopter. Lastly, the statistical robust controller design is devoted to a concurrent feed-forward/feedback controller structure for a high-speed low tension tape drive.

Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge.

PubMed

Cash, David M; Frost, Chris; Iheme, Leonardo O; Ünay, Devrim; Kandemir, Melek; Fripp, Jurgen; Salvado, Olivier; Bourgeat, Pierrick; Reuter, Martin; Fischl, Bruce; Lorenzi, Marco; Frisoni, Giovanni B; Pennec, Xavier; Pierson, Ronald K; Gunter, Jeffrey L; Senjem, Matthew L; Jack, Clifford R; Guizard, Nicolas; Fonov, Vladimir S; Collins, D Louis; Modat, Marc; Cardoso, M Jorge; Leung, Kelvin K; Wang, Hongzhi; Das, Sandhitsu R; Yushkevich, Paul A; Malone, Ian B; Fox, Nick C; Schott, Jonathan M; Ourselin, Sebastien

2015-12-01

Structural MRI is widely used for investigating brain atrophy in many neurodegenerative disorders, with several research groups developing and publishing techniques to provide quantitative assessments of this longitudinal change. Often techniques are compared through computation of required sample size estimates for future clinical trials. However interpretation of such comparisons is rendered complex because, despite using the same publicly available cohorts, the various techniques have been assessed with different data exclusions and different statistical analysis models. We created the MIRIAD atrophy challenge in order to test various capabilities of atrophy measurement techniques. The data consisted of 69 subjects (46 Alzheimer's disease, 23 control) who were scanned multiple (up to twelve) times at nine visits over a follow-up period of one to two years, resulting in 708 total image sets. Nine participating groups from 6 countries completed the challenge by providing volumetric measurements of key structures (whole brain, lateral ventricle, left and right hippocampi) for each dataset and atrophy measurements of these structures for each time point pair (both forward and backward) of a given subject. From these results, we formally compared techniques using exactly the same dataset. First, we assessed the repeatability of each technique using rates obtained from short intervals where no measurable atrophy is expected. For those measures that provided direct measures of atrophy between pairs of images, we also assessed symmetry and transitivity. Then, we performed a statistical analysis in a consistent manner using linear mixed effect models. The models, one for repeated measures of volume made at multiple time-points and a second for repeated "direct" measures of change in brain volume, appropriately allowed for the correlation between measures made on the same subject and were shown to fit the data well. From these models, we obtained estimates of the distribution of atrophy rates in the Alzheimer's disease (AD) and control groups and of required sample sizes to detect a 25% treatment effect, in relation to healthy ageing, with 95% significance and 80% power over follow-up periods of 6, 12, and 24months. Uncertainty in these estimates, and head-to-head comparisons between techniques, were carried out using the bootstrap. The lateral ventricles provided the most stable measurements, followed by the brain. The hippocampi had much more variability across participants, likely because of differences in segmentation protocol and less distinct boundaries. Most methods showed no indication of bias based on the short-term interval results, and direct measures provided good consistency in terms of symmetry and transitivity. The resulting annualized rates of change derived from the model ranged from, for whole brain: -1.4% to -2.2% (AD) and -0.35% to -0.67% (control), for ventricles: 4.6% to 10.2% (AD) and 1.2% to 3.4% (control), and for hippocampi: -1.5% to -7.0% (AD) and -0.4% to -1.4% (control). There were large and statistically significant differences in the sample size requirements between many of the techniques. The lowest sample sizes for each of these structures, for a trial with a 12month follow-up period, were 242 (95% CI: 154 to 422) for whole brain, 168 (95% CI: 112 to 282) for ventricles, 190 (95% CI: 146 to 268) for left hippocampi, and 158 (95% CI: 116 to 228) for right hippocampi. This analysis represents one of the most extensive statistical comparisons of a large number of different atrophy measurement techniques from around the globe. The challenge data will remain online and publicly available so that other groups can assess their methods. Copyright © 2015. Published by Elsevier Inc.

Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge

PubMed Central

Cash, David M.; Frost, Chris; Iheme, Leonardo O.; Ünay, Devrim; Kandemir, Melek; Fripp, Jurgen; Salvado, Olivier; Bourgeat, Pierrick; Reuter, Martin; Fischl, Bruce; Lorenzi, Marco; Frisoni, Giovanni B.; Pennec, Xavier; Pierson, Ronald K.; Gunter, Jeffrey L.; Senjem, Matthew L.; Jack, Clifford R.; Guizard, Nicolas; Fonov, Vladimir S.; Collins, D. Louis; Modat, Marc; Cardoso, M. Jorge; Leung, Kelvin K.; Wang, Hongzhi; Das, Sandhitsu R.; Yushkevich, Paul A.; Malone, Ian B.; Fox, Nick C.; Schott, Jonathan M.; Ourselin, Sebastien

2015-01-01

Structural MRI is widely used for investigating brain atrophy in many neurodegenerative disorders, with several research groups developing and publishing techniques to provide quantitative assessments of this longitudinal change. Often techniques are compared through computation of required sample size estimates for future clinical trials. However interpretation of such comparisons is rendered complex because, despite using the same publicly available cohorts, the various techniques have been assessed with different data exclusions and different statistical analysis models. We created the MIRIAD atrophy challenge in order to test various capabilities of atrophy measurement techniques. The data consisted of 69 subjects (46 Alzheimer's disease, 23 control) who were scanned multiple (up to twelve) times at nine visits over a follow-up period of one to two years, resulting in 708 total image sets. Nine participating groups from 6 countries completed the challenge by providing volumetric measurements of key structures (whole brain, lateral ventricle, left and right hippocampi) for each dataset and atrophy measurements of these structures for each time point pair (both forward and backward) of a given subject. From these results, we formally compared techniques using exactly the same dataset. First, we assessed the repeatability of each technique using rates obtained from short intervals where no measurable atrophy is expected. For those measures that provided direct measures of atrophy between pairs of images, we also assessed symmetry and transitivity. Then, we performed a statistical analysis in a consistent manner using linear mixed effect models. The models, one for repeated measures of volume made at multiple time-points and a second for repeated “direct” measures of change in brain volume, appropriately allowed for the correlation between measures made on the same subject and were shown to fit the data well. From these models, we obtained estimates of the distribution of atrophy rates in the Alzheimer's disease (AD) and control groups and of required sample sizes to detect a 25% treatment effect, in relation to healthy ageing, with 95% significance and 80% power over follow-up periods of 6, 12, and 24 months. Uncertainty in these estimates, and head-to-head comparisons between techniques, were carried out using the bootstrap. The lateral ventricles provided the most stable measurements, followed by the brain. The hippocampi had much more variability across participants, likely because of differences in segmentation protocol and less distinct boundaries. Most methods showed no indication of bias based on the short-term interval results, and direct measures provided good consistency in terms of symmetry and transitivity. The resulting annualized rates of change derived from the model ranged from, for whole brain: − 1.4% to − 2.2% (AD) and − 0.35% to − 0.67% (control), for ventricles: 4.6% to 10.2% (AD) and 1.2% to 3.4% (control), and for hippocampi: − 1.5% to − 7.0% (AD) and − 0.4% to − 1.4% (control). There were large and statistically significant differences in the sample size requirements between many of the techniques. The lowest sample sizes for each of these structures, for a trial with a 12 month follow-up period, were 242 (95% CI: 154 to 422) for whole brain, 168 (95% CI: 112 to 282) for ventricles, 190 (95% CI: 146 to 268) for left hippocampi, and 158 (95% CI: 116 to 228) for right hippocampi. This analysis represents one of the most extensive statistical comparisons of a large number of different atrophy measurement techniques from around the globe. The challenge data will remain online and publicly available so that other groups can assess their methods. PMID:26275383

Modeling and Simulation of Upset-Inducing Disturbances for Digital Systems in an Electromagnetic Reverberation Chamber

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2014-01-01

This report describes a modeling and simulation approach for disturbance patterns representative of the environment experienced by a digital system in an electromagnetic reverberation chamber. The disturbance is modeled by a multi-variate statistical distribution based on empirical observations. Extended versions of the Rejection Samping and Inverse Transform Sampling techniques are developed to generate multi-variate random samples of the disturbance. The results show that Inverse Transform Sampling returns samples with higher fidelity relative to the empirical distribution. This work is part of an ongoing effort to develop a resilience assessment methodology for complex safety-critical distributed systems.

Random sampling technique for ultra-fast computations of molecular opacities for exoplanet atmospheres

NASA Astrophysics Data System (ADS)

Min, M.

2017-10-01

Context. Opacities of molecules in exoplanet atmospheres rely on increasingly detailed line-lists for these molecules. The line lists available today contain for many species up to several billions of lines. Computation of the spectral line profile created by pressure and temperature broadening, the Voigt profile, of all of these lines is becoming a computational challenge. Aims: We aim to create a method to compute the Voigt profile in a way that automatically focusses the computation time into the strongest lines, while still maintaining the continuum contribution of the high number of weaker lines. Methods: Here, we outline a statistical line sampling technique that samples the Voigt profile quickly and with high accuracy. The number of samples is adjusted to the strength of the line and the local spectral line density. This automatically provides high accuracy line shapes for strong lines or lines that are spectrally isolated. The line sampling technique automatically preserves the integrated line opacity for all lines, thereby also providing the continuum opacity created by the large number of weak lines at very low computational cost. Results: The line sampling technique is tested for accuracy when computing line spectra and correlated-k tables. Extremely fast computations ( 3.5 × 105 lines per second per core on a standard current day desktop computer) with high accuracy (≤1% almost everywhere) are obtained. A detailed recipe on how to perform the computations is given.

Statistical detection of patterns in unidimensional distributions by continuous wavelet transforms

NASA Astrophysics Data System (ADS)

Baluev, R. V.

2018-04-01

Objective detection of specific patterns in statistical distributions, like groupings or gaps or abrupt transitions between different subsets, is a task with a rich range of applications in astronomy: Milky Way stellar population analysis, investigations of the exoplanets diversity, Solar System minor bodies statistics, extragalactic studies, etc. We adapt the powerful technique of the wavelet transforms to this generalized task, making a strong emphasis on the assessment of the patterns detection significance. Among other things, our method also involves optimal minimum-noise wavelets and minimum-noise reconstruction of the distribution density function. Based on this development, we construct a self-closed algorithmic pipeline aimed to process statistical samples. It is currently applicable to single-dimensional distributions only, but it is flexible enough to undergo further generalizations and development.

Supervised classification in the presence of misclassified training data: a Monte Carlo simulation study in the three group case.

PubMed

Bolin, Jocelyn Holden; Finch, W Holmes

2014-01-01

Statistical classification of phenomena into observed groups is very common in the social and behavioral sciences. Statistical classification methods, however, are affected by the characteristics of the data under study. Statistical classification can be further complicated by initial misclassification of the observed groups. The purpose of this study is to investigate the impact of initial training data misclassification on several statistical classification and data mining techniques. Misclassification conditions in the three group case will be simulated and results will be presented in terms of overall as well as subgroup classification accuracy. Results show decreased classification accuracy as sample size, group separation and group size ratio decrease and as misclassification percentage increases with random forests demonstrating the highest accuracy across conditions.

A comparison of three rotary systems and hand instrumentation technique for the elimination of Enterococcus faecalis from the root canal.

PubMed

Gorduysus, Melahat; Nagas, Emre; Torun, Ozgur Yildirim; Gorduysus, Omer

2011-12-01

The aim of this study was to compare the in vitro reduction of a bacterial population in a root canal by mechanical instrumentation using three rotary systems and hand instrumentation technique. The root canals contaminated with a suspension of Enterococcus faecalis were instrumented using ProTaper, K3, HeroShaper and K-file hand instrumentation technique. Later the root canals were sampled. After serial dilutions, samples were incubated in culture media for 24 h. Bacterial colonies were counted and the results were given as number of colony-forming units per millilitre. The results showed that all the canal instrumentation systems reduced the number of bacterial cells in the root canals. Statistically, ProTaper instruments were more effective in reducing the number of bacteria than the other rotary files or hand instruments. © 2010 The Authors. Australian Endodontic Journal © 2010 Australian Society of Endodontology.

The evaluation of alternate methodologies for land cover classification in an urbanizing area

NASA Technical Reports Server (NTRS)

Smekofski, R. M.

1981-01-01

The usefulness of LANDSAT in classifying land cover and in identifying and classifying land use change was investigated using an urbanizing area as the study area. The question of what was the best technique for classification was the primary focus of the study. The many computer-assisted techniques available to analyze LANDSAT data were evaluated. Techniques of statistical training (polygons from CRT, unsupervised clustering, polygons from digitizer and binary masks) were tested with minimum distance to the mean, maximum likelihood and canonical analysis with minimum distance to the mean classifiers. The twelve output images were compared to photointerpreted samples, ground verified samples and a current land use data base. Results indicate that for a reconnaissance inventory, the unsupervised training with canonical analysis-minimum distance classifier is the most efficient. If more detailed ground truth and ground verification is available, the polygons from the digitizer training with the canonical analysis minimum distance is more accurate.

Multiple signal classification algorithm for super-resolution fluorescence microscopy

PubMed Central

Agarwal, Krishna; Macháň, Radek

2016-01-01

Single-molecule localization techniques are restricted by long acquisition and computational times, or the need of special fluorophores or biologically toxic photochemical environments. Here we propose a statistical super-resolution technique of wide-field fluorescence microscopy we call the multiple signal classification algorithm which has several advantages. It provides resolution down to at least 50 nm, requires fewer frames and lower excitation power and works even at high fluorophore concentrations. Further, it works with any fluorophore that exhibits blinking on the timescale of the recording. The multiple signal classification algorithm shows comparable or better performance in comparison with single-molecule localization techniques and four contemporary statistical super-resolution methods for experiments of in vitro actin filaments and other independently acquired experimental data sets. We also demonstrate super-resolution at timescales of 245 ms (using 49 frames acquired at 200 frames per second) in samples of live-cell microtubules and live-cell actin filaments imaged without imaging buffers. PMID:27934858

Stellar populations in local star-forming galaxies

NASA Astrophysics Data System (ADS)

Perez-Gonzalez, P. G.

2003-11-01

The main goal of this thesis work is studying the main properties of the stellar populations embedded in a statistically complete sample of local active star-forming galaxies: the Universidad Complutense de Madrid (UCM) Survey of emission-line galaxies. This sample contains 191 local star-forming galaxies at an average redshift of 0.026. The survey was carried out using an objective-prism technique centered at the wavelength of the Halpha nebular emission-line (a common tracer of recent star formation). (continues)

Atmospheric turbulence power spectral measurements to long wavelengths for several meteorological conditions

NASA Technical Reports Server (NTRS)

Rhyne, R. H.; Murrow, H. N.; Sidwell, K.

1976-01-01

Use of power spectral design techniques for supersonic transports requires accurate definition of atmospheric turbulence in the long wavelength region below the knee of the power spectral density function curve. Examples are given of data obtained from a current turbulence flight sampling program. These samples are categorized as (1) convective, (2) wind shear, (3) rotor, and (4) mountain-wave turbulence. Time histories, altitudes, root-mean-square values, statistical degrees of freedom, power spectra, and integral scale values are shown and discussed.

Statistical issues in reporting quality data: small samples and casemix variation.

PubMed

Zaslavsky, A M

2001-12-01

To present two key statistical issues that arise in analysis and reporting of quality data. Casemix variation is relevant to quality reporting when the units being measured have differing distributions of patient characteristics that also affect the quality outcome. When this is the case, adjustment using stratification or regression may be appropriate. Such adjustments may be controversial when the patient characteristic does not have an obvious relationship to the outcome. Stratified reporting poses problems for sample size and reporting format, but may be useful when casemix effects vary across units. Although there are no absolute standards of reliability, high reliabilities (interunit F > or = 10 or reliability > or = 0.9) are desirable for distinguishing above- and below-average units. When small or unequal sample sizes complicate reporting, precision may be improved using indirect estimation techniques that incorporate auxiliary information, and 'shrinkage' estimation can help to summarize the strength of evidence about units with small samples. With broader understanding of casemix adjustment and methods for analyzing small samples, quality data can be analysed and reported more accurately.

Non-destructive scanning for applied stress by the continuous magnetic Barkhausen noise method

NASA Astrophysics Data System (ADS)

Franco Grijalba, Freddy A.; Padovese, L. R.

2018-01-01

This paper reports the use of a non-destructive continuous magnetic Barkhausen noise technique to detect applied stress on steel surfaces. The stress profile generated in a sample of 1070 steel subjected to a three-point bending test is analyzed. The influence of different parameters such as pickup coil type, scanner speed, applied magnetic field and frequency band analyzed on the effectiveness of the technique is investigated. A moving smoothing window based on a second-order statistical moment is used to analyze the time signal. The findings show that the technique can be used to detect applied stress profiles.

Comparison between McMaster and Mini-FLOTAC methods for the enumeration of Eimeria maxima oocysts in poultry excreta.

PubMed

Bortoluzzi, C; Paras, K L; Applegate, T J; Verocai, G G

2018-04-30

Monitoring Eimeria shedding has become more important due to the recent restrictions to the use of antibiotics within the poultry industry. Therefore, there is a need for the implementation of more precise and accurate quantitative diagnostic techniques. The objective of this study was to compare the precision and accuracy between the Mini-FLOTAC and the McMaster techniques for quantitative diagnosis of Eimeria maxima oocyst in poultry. Twelve pools of excreta samples of broiler chickens experimentally infected with E. maxima were analyzed for the comparison between Mini-FLOTAC and McMaster technique using, the detection limits (dl) of 23 and 25, respectively. Additionally, six excreta samples were used to compare the precision of different dl (5, 10, 23, and 46) using the Mini-FLOTAC technique. For precision comparisons, five technical replicates of each sample (five replicate slides on one excreta slurry) were read for calculating the mean oocyst per gram of excreta (OPG) count, standard deviation (SD), coefficient of variation (CV), and precision of both aforementioned comparisons. To compare accuracy between the methods (McMaster, and Mini-FLOTAC dl 5 and 23), excreta from uninfected chickens was spiked with 100, 500, 1,000, 5,000, or 10,000 OPG; additional samples remained unspiked (negative control). For each spiking level, three samples were read in triplicate, totaling nine reads per spiking level per technique. Data were transformed using log10 to obtain normality and homogeneity of variances. A significant correlation (R = 0.74; p = 0.006) was observed between the mean OPG of the McMaster dl 25 and the Mini-FLOTAC dl 23. Mean OPG, CV, SD, and precision were not statistically different between the McMaster dl 25 and Mini-FLOTAC dl 23. Despite the absence of statistical difference (p > 0.05), Mini-FLOTAC dl 5 showed a numerically lower SD and CV than Mini-FLOTAC dl 23. The Pearson correlation coefficient revealed significant and positive correlation among the four dl (p ≤ 0.05). In the accuracy study, it was observed that the Mini-FLOTAC dl 5 and 23 were more accurate than the McMaster for 100 OPG, and the Mini-FLOTAC dl 23 had the highest accuracy for 500 OPG. The McMaster and Mini-FLOTAC dl 23 techniques were more accurate than the Mini-FLOTAC dl 5 for 5,000 OPG, and both dl of the Mini-FLOTAC were less accurate for 10,000 OPG counts than the McMaster technique. However, the overall accuracy of the Mini-FLOTAC dl 23 was higher than the McMaster and Mini-FLOTAC dl 5 techniques. Copyright © 2018 Elsevier B.V. All rights reserved.

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

PubMed

Dazard, Jean-Eudes; Rao, J Sunil

2012-07-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

Reexamining Sample Size Requirements for Multivariate, Abundance-Based Community Research: When Resources are Limited, the Research Does Not Have to Be.

PubMed

Forcino, Frank L; Leighton, Lindsey R; Twerdy, Pamela; Cahill, James F

2015-01-01

Community ecologists commonly perform multivariate techniques (e.g., ordination, cluster analysis) to assess patterns and gradients of taxonomic variation. A critical requirement for a meaningful statistical analysis is accurate information on the taxa found within an ecological sample. However, oversampling (too many individuals counted per sample) also comes at a cost, particularly for ecological systems in which identification and quantification is substantially more resource consuming than the field expedition itself. In such systems, an increasingly larger sample size will eventually result in diminishing returns in improving any pattern or gradient revealed by the data, but will also lead to continually increasing costs. Here, we examine 396 datasets: 44 previously published and 352 created datasets. Using meta-analytic and simulation-based approaches, the research within the present paper seeks (1) to determine minimal sample sizes required to produce robust multivariate statistical results when conducting abundance-based, community ecology research. Furthermore, we seek (2) to determine the dataset parameters (i.e., evenness, number of taxa, number of samples) that require larger sample sizes, regardless of resource availability. We found that in the 44 previously published and the 220 created datasets with randomly chosen abundances, a conservative estimate of a sample size of 58 produced the same multivariate results as all larger sample sizes. However, this minimal number varies as a function of evenness, where increased evenness resulted in increased minimal sample sizes. Sample sizes as small as 58 individuals are sufficient for a broad range of multivariate abundance-based research. In cases when resource availability is the limiting factor for conducting a project (e.g., small university, time to conduct the research project), statistically viable results can still be obtained with less of an investment.

Proceedings of the workshop on research methodologies and applications for Pacific Island agroforestry; July 16-20, 1990; Kolonia, Pohnpei, Federated States of Micronesia

Treesearch

Bill Raynor; Roger R. Bay

1993-01-01

Includes 19 papers presented at the workshop, covering such topics as sampling techniques and statistical considerations, indigenous agricultural and agroforestry systems, crop testing and evaluation, and agroforestry practices in the Pacific Islands, including Micronesia, Northern Marianas Islands, Palau, and American Samoa.

INVESTIGATION OF THE USE OF STATISTICS IN COUNSELING STUDENTS.

ERIC Educational Resources Information Center

HEWES, ROBERT F.

THE OBJECTIVE WAS TO EMPLOY TECHNIQUES OF PROFILE ANALYSIS TO DEVELOP THE JOINT PROBABILITY OF SELECTING A SUITABLE SUBJECT MAJOR AND OF ASSURING TO A HIGH DEGREE GRADUATION FROM COLLEGE WITH THAT MAJOR. THE SAMPLE INCLUDED 1,197 MIT FRESHMEN STUDENTS IN 1952-53, AND THE VALIDATION GROUP INCLUDED 699 ENTRANTS IN 1954. DATA INCLUDED SECONDARY…

Understanding Loan Use and Debt Burden among Low-Income and Minority Students at a Large Urban Community College

ERIC Educational Resources Information Center

Luna-Torres, Maria; McKinney, Lyle; Horn, Catherine; Jones, Sara

2018-01-01

This study examined a sample of community college students from a diverse, large urban community college system in Texas. To gain a deeper understanding about the effects of background characteristics on student borrowing behaviors and enrollment outcomes, the study employed descriptive statistics and regression techniques to examine two separate…

[Health-related behavior in a sample of Brazilian college students: gender differences].

PubMed

Colares, Viviane; Franca, Carolina da; Gonzalez, Emília

2009-03-01

This study investigated whether undergraduate students' health-risk behaviors differed according to gender. The sample consisted of 382 subjects, aged 20-29 years, from public universities in Pernambuco State, Brazil. Data were collected using the National College Health Risk Behavior Survey, previously validated in Portuguese. Descriptive and inferential statistical techniques were used. Associations were analyzed with the chi-square test or Fisher's exact test. Statistical significance was set at p < or = 0.05. In general, females engaged in the following risk behaviors less frequently than males: alcohol consumption (p = 0.005), smoking (p = 0.002), experimenting with marijuana (p = 0.002), consumption of inhalants (p < or = 0.001), steroid use (p = 0.003), carrying weapons (p = 0.001), and involvement in physical fights (p = 0.014). Meanwhile, female students displayed more concern about losing or maintaining weight, although they exercised less frequently than males. The findings thus showed statistically different health behaviors between genders. In conclusion, different approaches need to be used for the two genders.

Mercury Speciation by X-ray Absorption Fine Structure Spectroscopy and Sequential Chemical Extractions: A Comparison of Speciation Methods

USGS Publications Warehouse

Kim, C.S.; Bloom, N.S.; Rytuba, J.J.; Brown, Gordon E.

2003-01-01

Determining the chemical speciation of mercury in contaminated mining and industrial environments is essential for predicting its solubility, transport behavior, and potential bioavailability as well as for designing effective remediation strategies. In this study, two techniques for determining Hg speciation-X-ray absorption fine structure (XAFS) spectroscopy and sequential chemical extractions (SCE)-are independently applied to a set of samples with Hg concentrations ranging from 132 to 7539 mg/kg to determine if the two techniques provide comparable Hg speciation results. Generally, the proportions of insoluble HgS (cinnabar, metacinnabar) and HgSe identified by XAFS correlate well with the proportion of Hg removed in the aqua regia extraction demonstrated to remove HgS and HgSe. Statistically significant (> 10%) differences are observed however in samples containing more soluble Hg-containing phases (HgCl2, HgO, Hg3S2O 4). Such differences may be related to matrix, particle size, or crystallinity effects, which could affect the apparent solubility of Hg phases present. In more highly concentrated samples, microscopy techniques can help characterize the Hg-bearing species in complex multiphase natural samples.

Evaluating sufficient similarity for drinking-water disinfection by-product (DBP) mixtures with bootstrap hypothesis test procedures.

PubMed

Feder, Paul I; Ma, Zhenxu J; Bull, Richard J; Teuschler, Linda K; Rice, Glenn

2009-01-01

In chemical mixtures risk assessment, the use of dose-response data developed for one mixture to estimate risk posed by a second mixture depends on whether the two mixtures are sufficiently similar. While evaluations of similarity may be made using qualitative judgments, this article uses nonparametric statistical methods based on the "bootstrap" resampling technique to address the question of similarity among mixtures of chemical disinfectant by-products (DBP) in drinking water. The bootstrap resampling technique is a general-purpose, computer-intensive approach to statistical inference that substitutes empirical sampling for theoretically based parametric mathematical modeling. Nonparametric, bootstrap-based inference involves fewer assumptions than parametric normal theory based inference. The bootstrap procedure is appropriate, at least in an asymptotic sense, whether or not the parametric, distributional assumptions hold, even approximately. The statistical analysis procedures in this article are initially illustrated with data from 5 water treatment plants (Schenck et al., 2009), and then extended using data developed from a study of 35 drinking-water utilities (U.S. EPA/AMWA, 1989), which permits inclusion of a greater number of water constituents and increased structure in the statistical models.

BATSE analysis techniques for probing the GRB spatial and luminosity distributions

NASA Technical Reports Server (NTRS)

Hakkila, Jon; Meegan, Charles A.

1992-01-01

The Burst And Transient Source Experiment (BATSE) has measured homogeneity and isotropy parameters from an increasingly large sample of observed gamma-ray bursts (GRBs), while also maintaining a summary of the way in which the sky has been sampled. Measurement of both of these are necessary for any study of the BATSE data statistically, as they take into account the most serious observational selection effects known in the study of GRBs: beam-smearing and inhomogeneous, anisotropic sky sampling. Knowledge of these effects is important to analysis of GRB angular and intensity distributions. In addition to determining that the bursts are local, it is hoped that analysis of such distributions will allow boundaries to be placed on the true GRB spatial distribution and luminosity function. The technique for studying GRB spatial and luminosity distributions is direct. Results of BATSE analyses are compared to Monte Carlo models parameterized by a variety of spatial and luminosity characteristics.

Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set

NASA Technical Reports Server (NTRS)

Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.

2002-01-01

The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.

Estimation of Global Network Statistics from Incomplete Data

PubMed Central

Bliss, Catherine A.; Danforth, Christopher M.; Dodds, Peter Sheridan

2014-01-01

Complex networks underlie an enormous variety of social, biological, physical, and virtual systems. A profound complication for the science of complex networks is that in most cases, observing all nodes and all network interactions is impossible. Previous work addressing the impacts of partial network data is surprisingly limited, focuses primarily on missing nodes, and suggests that network statistics derived from subsampled data are not suitable estimators for the same network statistics describing the overall network topology. We generate scaling methods to predict true network statistics, including the degree distribution, from only partial knowledge of nodes, links, or weights. Our methods are transparent and do not assume a known generating process for the network, thus enabling prediction of network statistics for a wide variety of applications. We validate analytical results on four simulated network classes and empirical data sets of various sizes. We perform subsampling experiments by varying proportions of sampled data and demonstrate that our scaling methods can provide very good estimates of true network statistics while acknowledging limits. Lastly, we apply our techniques to a set of rich and evolving large-scale social networks, Twitter reply networks. Based on 100 million tweets, we use our scaling techniques to propose a statistical characterization of the Twitter Interactome from September 2008 to November 2008. Our treatment allows us to find support for Dunbar's hypothesis in detecting an upper threshold for the number of active social contacts that individuals maintain over the course of one week. PMID:25338183

mapDIA: Preprocessing and statistical analysis of quantitative proteomics data from data independent acquisition mass spectrometry.

PubMed

Teo, Guoshou; Kim, Sinae; Tsou, Chih-Chiang; Collins, Ben; Gingras, Anne-Claude; Nesvizhskii, Alexey I; Choi, Hyungwon

2015-11-03

Data independent acquisition (DIA) mass spectrometry is an emerging technique that offers more complete detection and quantification of peptides and proteins across multiple samples. DIA allows fragment-level quantification, which can be considered as repeated measurements of the abundance of the corresponding peptides and proteins in the downstream statistical analysis. However, few statistical approaches are available for aggregating these complex fragment-level data into peptide- or protein-level statistical summaries. In this work, we describe a software package, mapDIA, for statistical analysis of differential protein expression using DIA fragment-level intensities. The workflow consists of three major steps: intensity normalization, peptide/fragment selection, and statistical analysis. First, mapDIA offers normalization of fragment-level intensities by total intensity sums as well as a novel alternative normalization by local intensity sums in retention time space. Second, mapDIA removes outlier observations and selects peptides/fragments that preserve the major quantitative patterns across all samples for each protein. Last, using the selected fragments and peptides, mapDIA performs model-based statistical significance analysis of protein-level differential expression between specified groups of samples. Using a comprehensive set of simulation datasets, we show that mapDIA detects differentially expressed proteins with accurate control of the false discovery rates. We also describe the analysis procedure in detail using two recently published DIA datasets generated for 14-3-3β dynamic interaction network and prostate cancer glycoproteome. The software was written in C++ language and the source code is available for free through SourceForge website http://sourceforge.net/projects/mapdia/.This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

Multiclass Bayes error estimation by a feature space sampling technique

NASA Technical Reports Server (NTRS)

Mobasseri, B. G.; Mcgillem, C. D.

1979-01-01

A general Gaussian M-class N-feature classification problem is defined. An algorithm is developed that requires the class statistics as its only input and computes the minimum probability of error through use of a combined analytical and numerical integration over a sequence simplifying transformations of the feature space. The results are compared with those obtained by conventional techniques applied to a 2-class 4-feature discrimination problem with results previously reported and 4-class 4-feature multispectral scanner Landsat data classified by training and testing of the available data.

Basic forest cover mapping using digitized remote sensor data and automated data processing techniques

NASA Technical Reports Server (NTRS)

Coggeshall, M. E.; Hoffer, R. M.

1973-01-01

Remote sensing equipment and automatic data processing techniques were employed as aids in the institution of improved forest resource management methods. On the basis of automatically calculated statistics derived from manually selected training samples, the feature selection processor of LARSYS selected, upon consideration of various groups of the four available spectral regions, a series of channel combinations whose automatic classification performances (for six cover types, including both deciduous and coniferous forest) were tested, analyzed, and further compared with automatic classification results obtained from digitized color infrared photography.

The Effect of Different Mixing Methods on Working Time, Setting Time, Dimensional Changes and Film Thickness of Mineral Trioxide Aggregate and Calcium-Enriched Mixture.

PubMed

Shahi, Shahriar; Ghasemi, Negin; Rahimi, Saeed; Yavari, Hamidreza; Janani, Maryam; Mokhtari, Hadi; Bahari, Mahmood; Rabbani, Parastu

2015-01-01

The aim of the present study was to evaluate the effect of different mixing techniques (conventional, amalgamator and ultrasonic mixing) on the physical properties the working time (WT), setting time (ST), dimensional changes (DC) and film thickness (FT)] of calcium-enriched mixture (CEM) cement and mineral trioxide aggregate (MTA). The mentioned physical properties were determined using the ISO 6786:2001 specification. Six samples of each material were prepared for three mixing techniques (totally 36 samples). Data were analyzed using descriptive statistics, two-way ANOVA and Post Hoc Tukey's tests. The level of significance was defined at 0.05. Irrespective of mixing technique, there was no significant difference between the WT and FT of the tested materials. Except for the DC of MTA and the FT of the all materials, other properties were significantly affected with mixing techniques (P<0.05). The ultrasonic technique decreased the ST of MTA and CEM cement and increased the WT of CEM cement (P<0.05). The mixing technique of the materials had no significant effect on the dimensional changes of MTA and the film thickness of both materials.

Characterization of controlled bone defects using 2D and 3D ultrasound imaging techniques.

PubMed

Parmar, Biren J; Longsine, Whitney; Sabonghy, Eric P; Han, Arum; Tasciotti, Ennio; Weiner, Bradley K; Ferrari, Mauro; Righetti, Raffaella

2010-08-21

Ultrasound is emerging as an attractive alternative modality to standard x-ray and CT methods for bone assessment applications. As of today, however, there is a lack of systematic studies that investigate the performance of diagnostic ultrasound techniques in bone imaging applications. This study aims at understanding the performance limitations of new ultrasound techniques for imaging bones in controlled experiments in vitro. Experiments are performed on samples of mammalian and non-mammalian bones with controlled defects with size ranging from 400 microm to 5 mm. Ultrasound findings are statistically compared with those obtained from the same samples using standard x-ray imaging modalities and optical microscopy. The results of this study demonstrate that it is feasible to use diagnostic ultrasound imaging techniques to assess sub-millimeter bone defects in real time and with high accuracy and precision. These results also demonstrate that ultrasound imaging techniques perform comparably better than x-ray imaging and optical imaging methods, in the assessment of a wide range of controlled defects both in mammalian and non-mammalian bones. In the future, ultrasound imaging techniques might provide a cost-effective, real-time, safe and portable diagnostic tool for bone imaging applications.

Identification of biogeochemical hot spots using time-lapse hydrogeophysics

NASA Astrophysics Data System (ADS)

Franz, T. E.; Loecke, T.; Burgin, A.

2016-12-01

The identification and monitoring of biogeochemical hot spots and hot moments is difficult using point based sampling techniques and sensors. Without proper monitoring and accounting of water, energy, and trace gas fluxes it is difficult to assess the environmental footprint of land management practices. One key limitation is optimal placement of sensors/chambers that adequately capture the point scale fluxes and thus a reasonable integration to landscape scale flux. In this work we present time-lapse hydrogeophysical imaging at an old agricultural field converted into a wetland mitigation bank near Dayton, Ohio. While the wetland was previously instrumented with a network of soil sensors and surface chambers to capture a suite of state variables and fluxes, we hypothesize that time-lapse hydrogeophysical imaging is an underutilized and critical reconnaissance tool for effective network design and landscape scaling. Here we combine the time-lapse hydrogeophysical imagery with the multivariate statistical technique of Empirical Orthogonal Functions (EOF) in order to isolate the spatial and temporal components of the imagery. Comparisons of soil core information (e.g. soil texture, soil carbon) from around the study site and organized within like spatial zones reveal statistically different mean values of soil properties. Moreover, the like spatial zones can be used to identify a finite number of future sampling locations, evaluation of the placement of existing sensors/chambers, upscale/downscale observations, all of which are desirable techniques for commercial use in precision agriculture. Finally, we note that combining the EOF analysis with continuous monitoring from point sensors or remote sensing products may provide a robust statistical framework for scaling observations through time as well as provide appropriate datasets for use in landscape biogeochemical models.

Coarse kMC-based replica exchange algorithms for the accelerated simulation of protein folding in explicit solvent.

PubMed

Peter, Emanuel K; Shea, Joan-Emma; Pivkin, Igor V

2016-05-14

In this paper, we present a coarse replica exchange molecular dynamics (REMD) approach, based on kinetic Monte Carlo (kMC). The new development significantly can reduce the amount of replicas and the computational cost needed to enhance sampling in protein simulations. We introduce 2 different methods which primarily differ in the exchange scheme between the parallel ensembles. We apply this approach on folding of 2 different β-stranded peptides: the C-terminal β-hairpin fragment of GB1 and TrpZip4. Additionally, we use the new simulation technique to study the folding of TrpCage, a small fast folding α-helical peptide. Subsequently, we apply the new methodology on conformation changes in signaling of the light-oxygen voltage (LOV) sensitive domain from Avena sativa (AsLOV2). Our results agree well with data reported in the literature. In simulations of dialanine, we compare the statistical sampling of the 2 techniques with conventional REMD and analyze their performance. The new techniques can reduce the computational cost of REMD significantly and can be used in enhanced sampling simulations of biomolecules.

Statistical methods used in the public health literature and implications for training of public health professionals

PubMed Central

Hayat, Matthew J.; Powell, Amanda; Johnson, Tessa; Cadwell, Betsy L.

2017-01-01

Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals. PMID:28591190

Statistical methods used in the public health literature and implications for training of public health professionals.

PubMed

Hayat, Matthew J; Powell, Amanda; Johnson, Tessa; Cadwell, Betsy L

2017-01-01

Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals.

Geospatial techniques for developing a sampling frame of watersheds across a region

USGS Publications Warehouse

Gresswell, Robert E.; Bateman, Douglas S.; Lienkaemper, George; Guy, T.J.

2004-01-01

Current land-management decisions that affect the persistence of native salmonids are often influenced by studies of individual sites that are selected based on judgment and convenience. Although this approach is useful for some purposes, extrapolating results to areas that were not sampled is statistically inappropriate because the sampling design is usually biased. Therefore, in recent investigations of coastal cutthroat trout (Oncorhynchus clarki clarki) located above natural barriers to anadromous salmonids, we used a methodology for extending the statistical scope of inference. The purpose of this paper is to apply geospatial tools to identify a population of watersheds and develop a probability-based sampling design for coastal cutthroat trout in western Oregon, USA. The population of mid-size watersheds (500-5800 ha) west of the Cascade Range divide was derived from watershed delineations based on digital elevation models. Because a database with locations of isolated populations of coastal cutthroat trout did not exist, a sampling frame of isolated watersheds containing cutthroat trout had to be developed. After the sampling frame of watersheds was established, isolated watersheds with coastal cutthroat trout were stratified by ecoregion and erosion potential based on dominant bedrock lithology (i.e., sedimentary and igneous). A stratified random sample of 60 watersheds was selected with proportional allocation in each stratum. By comparing watershed drainage areas of streams in the general population to those in the sampling frame and the resulting sample (n = 60), we were able to evaluate the how representative the subset of watersheds was in relation to the population of watersheds. Geospatial tools provided a relatively inexpensive means to generate the information necessary to develop a statistically robust, probability-based sampling design.

Phospholipid Fatty Acid Analysis: Past, Present and Future

NASA Astrophysics Data System (ADS)

Findlay, R. H.

2008-12-01

With their 1980 publication, Bobbie and White initiated the use of phospholipid fatty acids for the study of microbial communities. This method, integrated with a previously published biomass assay based on the colorimetric detection of orthophosphate liberated from phospholipids, provided the first quantitative method for determining microbial community structure. The method is based on a quantitative extraction of lipids from the sample matrix, isolation of the phospholipids, conversion of the phospholipid fatty acids to their corresponding fatty acid methyl esters (known by the acronym FAME) and the separation, identification and quantification of the FAME by gas chromatography. Early laboratory and field samples focused on correlating individual fatty acids to particular groups of microorganisms. Subsequent improvements to the methodology include reduced solvent volumes for extractions, improved sensitivity in the detection of orthophosphate and the use of solid phase extraction technology. Improvements in the field of gas chromatography also increased accessibility of the technique and it has been widely applied to water, sediment, soil and aerosol samples. Whole cell fatty acid analysis, a related but not equal technique, is currently used for phenotypic characterization in bacterial species descriptions and is the basis for a commercial, rapid bacterial identification system. In the early 1990ês application of multivariate statistical analysis, first cluster analysis and then principal component analysis, further improved the usefulness of the technique and allowed the development of a functional group approach to interpretation of phospholipid fatty acid profiles. Statistical techniques currently applied to the analysis of phospholipid fatty acid profiles include constrained ordinations and neutral networks. Using redundancy analysis, a form of constrained ordination, we have recently shown that both cation concentration and dissolved organic matter (DOM) quality are determinates of microbial community structure in forested headwater streams. One of the most exciting recent developments in phospholipid fatty acid analysis is the application of compound specific stable isotope analysis. We are currently applying this technique to stream sediments to help determine which microorganisms are involved in the initial processing of DOM and the technique promises to be a useful tool for assigning ecological function to microbial populations.

Relationship between uterine biopsy score, endometrial infection and inflammation in the mare.

PubMed

Buczkowska, Justyna; Kozdrowski, Roland; Nowak, Marcin; Sikora, Monika

2016-06-16

Endometrial biopsy score is an accepted marker of uterine health and predicted fertility, and it has been suggested that endometrial alternations are correlated with susceptibility to persistent infectious endometritis. The objective of this study was to investigate associations of endometrial biopsy score with: 1) presence of polymorphonuclear cells (PMNs) in the epithelium and stratum compactum in histopathology; 2) presence of PMNs in cytology and 3) presence of infection in microbiology. The material for examination was collected from 69 mares suspected for subclinical endometritis (bred three or more times unsuccessfully in the same breeding season) and from 15 maiden mares. Samples were collected by endometrial biopsy and cytobrush technique. Endometrial alterations (biopsy score IIA, IIB, III) were found in 64 of 82 mares (78%). There was an increase in PMN occurrence for grades IIA, IIB and III. When comparing grades and PMNs infiltration, we observed statistically significant differences between grades I and IIA (p  = 0.222) and grades I and IIB (p = 0.042) in samples collected by endometrial biopsy. Statistically significant differences were found in microbiological examination (biopsy p = 0.036; cytobrush p = 0.189), cytological examination (biopsy p = 0.040; cytobrush p = 0.079) and PMN infiltration (p    =    0.042) between mares with biopsy scores I and IIB. Furthermore, the highest percentage of infected mares was in grade IIA and IIB, and we found statistically significant differences between grades I and IIA (p = 0.043), and grades I and IIB (p = 0.036) in biopsy samples. We observed a tendency to higher prevalence of endometrial infection in mares with biopsy score IIA, IIB and III than with biopsy score I in samples collected using cytobrush technique. However, there were no statistical significant differences. Degenerative endometrial changes can predispose to uterine infection and inflammation. Our study shows that mares with endometrial score I are less predisposed to infection than mares with category IIA, IIB and III. Endometrial biopsy is a reliable diagnostic tool.

Identifying biologically relevant differences between metagenomic communities.

PubMed

Parks, Donovan H; Beiko, Robert G

2010-03-15

Metagenomics is the study of genetic material recovered directly from environmental samples. Taxonomic and functional differences between metagenomic samples can highlight the influence of ecological factors on patterns of microbial life in a wide range of habitats. Statistical hypothesis tests can help us distinguish ecological influences from sampling artifacts, but knowledge of only the P-value from a statistical hypothesis test is insufficient to make inferences about biological relevance. Current reporting practices for pairwise comparative metagenomics are inadequate, and better tools are needed for comparative metagenomic analysis. We have developed a new software package, STAMP, for comparative metagenomics that supports best practices in analysis and reporting. Examination of a pair of iron mine metagenomes demonstrates that deeper biological insights can be gained using statistical techniques available in our software. An analysis of the functional potential of 'Candidatus Accumulibacter phosphatis' in two enhanced biological phosphorus removal metagenomes identified several subsystems that differ between the A.phosphatis stains in these related communities, including phosphate metabolism, secretion and metal transport. Python source code and binaries are freely available from our website at http://kiwi.cs.dal.ca/Software/STAMP CONTACT: beiko@cs.dal.ca Supplementary data are available at Bioinformatics online.

Atherosclerosis imaging using 3D black blood TSE SPACE vs 2D TSE

PubMed Central

Wong, Stephanie K; Mobolaji-Iawal, Motunrayo; Arama, Leron; Cambe, Joy; Biso, Sylvia; Alie, Nadia; Fayad, Zahi A; Mani, Venkatesh

2014-01-01

AIM: To compare 3D Black Blood turbo spin echo (TSE) sampling perfection with application-optimized contrast using different flip angle evolution (SPACE) vs 2D TSE in evaluating atherosclerotic plaques in multiple vascular territories. METHODS: The carotid, aortic, and femoral arterial walls of 16 patients at risk for cardiovascular or atherosclerotic disease were studied using both 3D black blood magnetic resonance imaging SPACE and conventional 2D multi-contrast TSE sequences using a consolidated imaging approach in the same imaging session. Qualitative and quantitative analyses were performed on the images. Agreement of morphometric measurements between the two imaging sequences was assessed using a two-sample t-test, calculation of the intra-class correlation coefficient and by the method of linear regression and Bland-Altman analyses. RESULTS: No statistically significant qualitative differences were found between the 3D SPACE and 2D TSE techniques for images of the carotids and aorta. For images of the femoral arteries, however, there were statistically significant differences in all four qualitative scores between the two techniques. Using the current approach, 3D SPACE is suboptimal for femoral imaging. However, this may be due to coils not being optimized for femoral imaging. Quantitatively, in our study, higher mean total vessel area measurements for the 3D SPACE technique across all three vascular beds were observed. No significant differences in lumen area for both the right and left carotids were observed between the two techniques. Overall, a significant-correlation existed between measures obtained between the two approaches. CONCLUSION: Qualitative and quantitative measurements between 3D SPACE and 2D TSE techniques are comparable. 3D-SPACE may be a feasible approach in the evaluation of cardiovascular patients. PMID:24876923

Spherical disharmonics in the Earth sciences and the spatial solution: Ridges, hotspots, slabs, geochemistry and tomography correlations

NASA Technical Reports Server (NTRS)

Ray, Terrill W.; Anderson, Don L.

1994-01-01

There is increasing use of statistical correlations between geophysical fields and between geochemical and geophysical fields in attempts to understand how the Earth works. Typically, such correlations have been based on spherical harmonic expansions. The expression of functions on the sphere as spherical harmonic series has many pitfalls, especially if the data are nonuniformly and/or sparsely sampled. Many of the difficulties involved in the use of spherical harmonic expansion techniques can be avoided through the use of spatial domain correlations, but this introduces other complications, such as the choice of a sampling lattice. Additionally, many geophysical and geochemical fields fail to satisfy the assumptions of standard statistical significance tests. This is especially problematic when the data values to be correlated with a geophysical field were collected at sample locations which themselves correlate with that field. This paper examines many correlations which have been claimed in the past between geochemistry and mantle tomography and between hotspot, ridge, and slab locations and tomography using both spherical harmonic coefficient correlations and spatial domain correlations. No conclusively significant correlations are found between isotopic geochemistry and mantle tomography. The Crough and Jurdy (short) hotspot location list shows statistically significant correlation with lowermost mantle tomography for degree 2 of the spherical harmonic expansion, but there are no statistically significant correlations in the spatial case. The Vogt (long) hotspot location list does not correlate with tomography anywhere in the mantle using either technique. Both hotspot lists show a strong correlation between hotspot locations and geoid highs when spatially correlated, but no correlations are revealed by spherical harmonic techniques. Ridge locations do not show any statistically significant correlations with tomography, slab locations, or the geoid; the strongest correlation is with lowermost mantle tomography, which is probably spurious. The most striking correlations are between mantle tomography and post-Pangean subducted slabs. The integrated locations of slabs correlate strongly with fast areas near the transition zone and the core-mantle boundary and with slow regions from 1022-1248 km depth. This seems to be consistent with the 'avalanching' downwellings which have been indicated by models of the mantle which include an endothermic phase transition at the 670-km discontinuity, although this is not a unique interpretation. Taken as a whole, these results suggest that slabs and associated cold downwellings are the dominant feature of mantle convection. Hotspot locations are no better correlated with lower mantle tomography than are ridge locations.

Evaluation of Root Canal Preparation Using Rotary System and Hand Instruments Assessed by Micro-Computed Tomography

PubMed Central

Stavileci, Miranda; Hoxha, Veton; Görduysus, Ömer; Tatar, Ilkan; Laperre, Kjell; Hostens, Jeroen; Küçükkaya, Selen; Muhaxheri, Edmond

2015-01-01

Background Complete mechanical preparation of the root canal system is rarely achieved. Therefore, the purpose of this study was to evaluate and compare the root canal shaping efficacy of ProTaper rotary files and standard stainless steel K-files using micro-computed tomography. Material/Methods Sixty extracted upper second premolars were selected and divided into 2 groups of 30 teeth each. Before preparation, all samples were scanned by micro-computed tomography. Thirty teeth were prepared with the ProTaper system and the other 30 with stainless steel files. After preparation, the untouched surface and root canal straightening were evaluated with micro-computed tomography. The percentage of untouched root canal surface was calculated in the coronal, middle, and apical parts of the canal. We also calculated straightening of the canal after root canal preparation. Results from the 2 groups were statistically compared using the Minitab statistical package. Results ProTaper rotary files left less untouched root canal surface compared with manual preparation in coronal, middle, and apical sector (p<0.001). Similarly, there was a statistically significant difference in root canal straightening after preparation between the techniques (p<0.001). Conclusions Neither manual nor rotary techniques completely prepared the root canal, and both techniques caused slight straightening of the root canal. PMID:26092929

Evaluation of Root Canal Preparation Using Rotary System and Hand Instruments Assessed by Micro-Computed Tomography.

PubMed

Stavileci, Miranda; Hoxha, Veton; Görduysus, Ömer; Tatar, Ilkan; Laperre, Kjell; Hostens, Jeroen; Küçükkaya, Selen; Muhaxheri, Edmond

2015-06-20

Complete mechanical preparation of the root canal system is rarely achieved. Therefore, the purpose of this study was to evaluate and compare the root canal shaping efficacy of ProTaper rotary files and standard stainless steel K-files using micro-computed tomography. Sixty extracted upper second premolars were selected and divided into 2 groups of 30 teeth each. Before preparation, all samples were scanned by micro-computed tomography. Thirty teeth were prepared with the ProTaper system and the other 30 with stainless steel files. After preparation, the untouched surface and root canal straightening were evaluated with micro-computed tomography. The percentage of untouched root canal surface was calculated in the coronal, middle, and apical parts of the canal. We also calculated straightening of the canal after root canal preparation. Results from the 2 groups were statistically compared using the Minitab statistical package. ProTaper rotary files left less untouched root canal surface compared with manual preparation in coronal, middle, and apical sector (p<0.001). Similarly, there was a statistically significant difference in root canal straightening after preparation between the techniques (p<0.001). Neither manual nor rotary techniques completely prepared the root canal, and both techniques caused slight straightening of the root canal.

Difficulties in learning and teaching statistics: teacher views

NASA Astrophysics Data System (ADS)

Koparan, Timur

2015-01-01

The purpose of this study is to define teacher views about the difficulties in learning and teaching middle school statistics subjects. To serve this aim, a number of interviews were conducted with 10 middle school maths teachers in 2011-2012 school year in the province of Trabzon. Of the qualitative descriptive research methods, the semi-structured interview technique was applied in the research. In accordance with the aim, teacher opinions about the statistics subjects were examined and analysed. Similar responses from the teachers were grouped and evaluated. The teachers stated that it was positive that middle school statistics subjects were taught gradually in every grade but some difficulties were experienced in the teaching of this subject. The findings are presented in eight themes which are context, sample, data representation, central tendency and dispersion measure, probability, variance, and other difficulties.

Statistical characterization of short wind waves from stereo images of the sea surface

NASA Astrophysics Data System (ADS)

Mironov, Alexey; Yurovskaya, Maria; Dulov, Vladimir; Hauser, Danièle; Guérin, Charles-Antoine

2013-04-01

We propose a methodology to extract short-scale statistical characteristics of the sea surface topography by means of stereo image reconstruction. The possibilities and limitations of the technique are discussed and tested on a data set acquired from an oceanographic platform at the Black Sea. The analysis shows that reconstruction of the topography based on stereo method is an efficient way to derive non-trivial statistical properties of surface short- and intermediate-waves (say from 1 centimer to 1 meter). Most technical issues pertaining to this type of datasets (limited range of scales, lacunarity of data or irregular sampling) can be partially overcome by appropriate processing of the available points. The proposed technique also allows one to avoid linear interpolation which dramatically corrupts properties of retrieved surfaces. The processing technique imposes that the field of elevation be polynomially detrended, which has the effect of filtering out the large scales. Hence the statistical analysis can only address the small-scale components of the sea surface. The precise cut-off wavelength, which is approximatively half the patch size, can be obtained by applying a high-pass frequency filter on the reference gauge time records. The results obtained for the one- and two-points statistics of small-scale elevations are shown consistent, at least in order of magnitude, with the corresponding gauge measurements as well as other experimental measurements available in the literature. The calculation of the structure functions provides a powerful tool to investigate spectral and statistical properties of the field of elevations. Experimental parametrization of the third-order structure function, the so-called skewness function, is one of the most important and original outcomes of this study. This function is of primary importance in analytical scattering models from the sea surface and was up to now unavailable in field conditions. Due to the lack of precise reference measurements for the small-scale wave field, we could not quantify exactly the accuracy of the retrieval technique. However, it appeared clearly that the obtained accuracy is good enough for the estimation of second-order statistical quantities (such as the correlation function), acceptable for third-order quantities (such as the skwewness function) and insufficient for fourth-order quantities (such as kurtosis). Therefore, the stereo technique in the present stage should not be thought as a self-contained universal tool to characterize the surface statistics. Instead, it should be used in conjunction with other well calibrated but sparse reference measurement (such as wave gauges) for cross-validation and calibration. It then completes the statistical analysis in as much as it provides a snapshot of the three-dimensional field and allows for the evaluation of higher-order spatial statistics.

Data precision of X-ray fluorescence (XRF) scanning of discrete samples with the ITRAX XRF core-scanner exemplified on loess-paleosol samples

NASA Astrophysics Data System (ADS)

Profe, Jörn; Ohlendorf, Christian

2017-04-01

XRF-scanning is the state-of-the-art technique for geochemical analyses in marine and lacustrine sedimentology for more than a decade. However, little attention has been paid to data precision and technical limitations so far. Using homogenized, dried and powdered samples (certified geochemical reference standards and samples from a lithologically-contrasting loess-paleosol sequence) minimizes many adverse effects that influence the XRF-signal when analyzing wet sediment cores. This allows the investigation of data precision under ideal conditions and documents a new application of the XRF core-scanner technology at the same time. Reliable interpretations of XRF results require data precision evaluation of single elements as a function of X-ray tube, measurement time, sample compaction and quality of peak fitting. Ten-fold measurement of each sample constitutes data precision. Data precision of XRF measurements theoretically obeys Poisson statistics. Fe and Ca exhibit largest deviations from Poisson statistics. The same elements show the least mean relative standard deviations in the range from 0.5% to 1%. This represents the technical limit of data precision achievable by the installed detector. Measurement times ≥ 30 s reveal mean relative standard deviations below 4% for most elements. The quality of peak fitting is only relevant for elements with overlapping fluorescence lines such as Ba, Ti and Mn or for elements with low concentrations such as Y, for example. Differences in sample compaction are marginal and do not change mean relative standard deviation considerably. Data precision is in the range reported for geochemical reference standards measured by conventional techniques. Therefore, XRF scanning of discrete samples provide a cost- and time-efficient alternative to conventional multi-element analyses. As best trade-off between economical operation and data quality, we recommend a measurement time of 30 s resulting in a total scan time of 30 minutes for 30 samples.

Errors in radial velocity variance from Doppler wind lidar

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

Wang, H.; Barthelmie, R. J.; Doubrawa, P.

A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, themore » systematic error is negligible but the random error exceeds about 10%.« less

Errors in radial velocity variance from Doppler wind lidar

DOE PAGES

Wang, H.; Barthelmie, R. J.; Doubrawa, P.; ...

2016-08-29

A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, themore » systematic error is negligible but the random error exceeds about 10%.« less

Multi-level methods and approximating distribution functions

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

Wilson, D., E-mail: daniel.wilson@dtc.ox.ac.uk; Baker, R. E.

2016-07-15

Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie’s direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparablemore » to Gillespie’s direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146–179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.« less

Lightweight and Statistical Techniques for Petascale PetaScale Debugging

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

Miller, Barton

2014-06-30

This project investigated novel techniques for debugging scientific applications on petascale architectures. In particular, we developed lightweight tools that narrow the problem space when bugs are encountered. We also developed techniques that either limit the number of tasks and the code regions to which a developer must apply a traditional debugger or that apply statistical techniques to provide direct suggestions of the location and type of error. We extend previous work on the Stack Trace Analysis Tool (STAT), that has already demonstrated scalability to over one hundred thousand MPI tasks. We also extended statistical techniques developed to isolate programming errorsmore » in widely used sequential or threaded applications in the Cooperative Bug Isolation (CBI) project to large scale parallel applications. Overall, our research substantially improved productivity on petascale platforms through a tool set for debugging that complements existing commercial tools. Previously, Office Of Science application developers relied either on primitive manual debugging techniques based on printf or they use tools, such as TotalView, that do not scale beyond a few thousand processors. However, bugs often arise at scale and substantial effort and computation cycles are wasted in either reproducing the problem in a smaller run that can be analyzed with the traditional tools or in repeated runs at scale that use the primitive techniques. New techniques that work at scale and automate the process of identifying the root cause of errors were needed. These techniques significantly reduced the time spent debugging petascale applications, thus leading to a greater overall amount of time for application scientists to pursue the scientific objectives for which the systems are purchased. We developed a new paradigm for debugging at scale: techniques that reduced the debugging scenario to a scale suitable for traditional debuggers, e.g., by narrowing the search for the root-cause analysis to a small set of nodes or by identifying equivalence classes of nodes and sampling our debug targets from them. We implemented these techniques as lightweight tools that efficiently work on the full scale of the target machine. We explored four lightweight debugging refinements: generic classification parameters, such as stack traces, application-specific classification parameters, such as global variables, statistical data acquisition techniques and machine learning based approaches to perform root cause analysis. Work done under this project can be divided into two categories, new algorithms and techniques for scalable debugging, and foundation infrastructure work on our MRNet multicast-reduction framework for scalability, and Dyninst binary analysis and instrumentation toolkits.« less

Determination of ABO blood grouping and Rhesus factor from tooth material

PubMed Central

Kumar, Pooja Vijay; Vanishree, M; Anila, K; Hunasgi, Santosh; Suryadevra, Sri Sujan; Kardalkar, Swetha

2016-01-01

Objective: The aim of the study was to determine blood groups and Rhesus factor from dentin and pulp using absorption-elution (AE) technique in different time periods at 0, 3, 6, 9 and 12 months, respectively. Materials and Methods: A total of 150 cases, 30 patients each at 0, 3, 6, 9 and 12 months were included in the study. The samples consisted of males and females with age ranging 13–60 years. Patient's blood group was checked and was considered as “control.” The dentin and pulp of extracted teeth were tested for the presence of ABO/Rh antigen, at respective time periods by AE technique. Statistical Analysis: Data were analyzed in proportion. For comparison, Chi-square test or Fisher's exact test was used for the small sample. Results: Blood group antigens of ABO and Rh factor were detected in dentin and pulp up to 12 months. For both ABO and Rh factor, dentin and pulp showed 100% sensitivity for the samples tested at 0 month and showed a gradual decrease in the sensitivity as time period increased. The sensitivity of pulp was better than dentin for both the blood grouping systems and ABO blood group antigens were better detected than Rh antigens. Conclusion: In dentin and pulp, the antigens of ABO and Rh factor were detected up to 12 months but showed a progressive decrease in the antigenicity as the time period increased. When compared the results obtained of dentin and pulp in ABO and Rh factor grouping showed similar results with no statistical significance. The sensitivity of ABO blood grouping was better than Rh factor blood grouping and showed a statistically significant result. PMID:27721625

A Hybrid Semi-supervised Classification Scheme for Mining Multisource Geospatial Data

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

Vatsavai, Raju; Bhaduri, Budhendra L

2011-01-01

Supervised learning methods such as Maximum Likelihood (ML) are often used in land cover (thematic) classification of remote sensing imagery. ML classifier relies exclusively on spectral characteristics of thematic classes whose statistical distributions (class conditional probability densities) are often overlapping. The spectral response distributions of thematic classes are dependent on many factors including elevation, soil types, and ecological zones. A second problem with statistical classifiers is the requirement of large number of accurate training samples (10 to 30 |dimensions|), which are often costly and time consuming to acquire over large geographic regions. With the increasing availability of geospatial databases, itmore » is possible to exploit the knowledge derived from these ancillary datasets to improve classification accuracies even when the class distributions are highly overlapping. Likewise newer semi-supervised techniques can be adopted to improve the parameter estimates of statistical model by utilizing a large number of easily available unlabeled training samples. Unfortunately there is no convenient multivariate statistical model that can be employed for mulitsource geospatial databases. In this paper we present a hybrid semi-supervised learning algorithm that effectively exploits freely available unlabeled training samples from multispectral remote sensing images and also incorporates ancillary geospatial databases. We have conducted several experiments on real datasets, and our new hybrid approach shows over 25 to 35% improvement in overall classification accuracy over conventional classification schemes.« less

A statistical assessment of pesticide pollution in surface waters using environmental monitoring data: Chlorpyrifos in Central Valley, California.

PubMed

Wang, Dan; Singhasemanon, Nan; Goh, Kean S

2016-11-15

Pesticides are routinely monitored in surface waters and resultant data are analyzed to assess whether their uses will damage aquatic eco-systems. However, the utility of the monitoring data is limited because of the insufficiency in the temporal and spatial sampling coverage and the inability to detect and quantify trace concentrations. This study developed a novel assessment procedure that addresses those limitations by combining 1) statistical methods capable of extracting information from concentrations below changing detection limits, 2) statistical resampling techniques that account for uncertainties rooted in the non-detects and insufficient/irregular sampling coverage, and 3) multiple lines of evidence that improve confidence in the final conclusion. This procedure was demonstrated by an assessment on chlorpyrifos monitoring data in surface waters of California's Central Valley (2005-2013). We detected a significant downward trend in the concentrations, which cannot be observed by commonly-used statistical approaches. We assessed that the aquatic risk was low using a probabilistic method that works with non-detects and has the ability to differentiate indicator groups with varying sensitivity. In addition, we showed that the frequency of exceedance over ambient aquatic life water quality criteria was affected by pesticide use, precipitation and irrigation demand in certain periods anteceding the water sampling events. Copyright © 2016 Elsevier B.V. All rights reserved.

Use of near infared spectroscopy to measure the chemical and mechanical properties of solid wood

Treesearch

Stephen S. Kelley; Timothy G. Rials; Rebecca Snell; Leslie H. Groom; Amie Sluiter

2004-01-01

Near infrared (NIR) spectroscopy (500 nm-2400 nm), coupled with multivariate analytic (MVA) statistical techniques, have been used to predict the chemical and mechanical properties of solid loblolly pine wood. The samples were selected from different radial locations and heights of three loblolly pine trees grown in Arkansas. The chemical composition and mechanical...

Use of near infrared spectroscopy to measure the chemical and mechanical properties of solid wood

Treesearch

Stephen S. Kelley; Timothy G. Rials; Rebecca Snell; Leslie H. Groom; Amie Sluiter

2004-01-01

Near infrared (NIR) spectroscopy (500 nm-2400 nm), coupled with multivariate analytic (MVA) statistical techniques, have been used to predict the chemical and mechanical properties of solid loblolly pine wood. The samples were selected from different radial locations and heights of three loblolly pine trees grown in Arkansas. The chemical composition and mechanical...

Estimating the Latent Number of Types in Growing Corpora with Reduced Cost-Accuracy Trade-Off

ERIC Educational Resources Information Center

Hidaka, Shohei

2016-01-01

The number of unique words in children's speech is one of most basic statistics indicating their language development. We may, however, face difficulties when trying to accurately evaluate the number of unique words in a child's growing corpus over time with a limited sample size. This study proposes a novel technique to estimate the latent number…

A statistically valid method for using FIA plots to guide spectral class rejection in producing stratification maps

Treesearch

Michael L. Hoppus; Andrew J. Lister

2002-01-01

A Landsat TM classification method (iterative guided spectral class rejection) produced a forest cover map of southern West Virginia that provided the stratification layer for producing estimates of timberland area from Forest Service FIA ground plots using a stratified sampling technique. These same high quality and expensive FIA ground plots provided ground reference...

Forest Fire History... A Computer Method of Data Analysis

Treesearch

Romain M. Meese

1973-01-01

A series of computer programs is available to extract information from the individual Fire Reports (U.S. Forest Service Form 5100-29). The programs use a statistical technique to fit a continuous distribution to a set of sampled data. The goodness-of-fit program is applicable to data other than the fire history. Data summaries illustrate analysis of fire occurrence,...

Renormalization group theory outperforms other approaches in statistical comparison between upscaling techniques for porous media

NASA Astrophysics Data System (ADS)

Hanasoge, Shravan; Agarwal, Umang; Tandon, Kunj; Koelman, J. M. Vianney A.

2017-09-01

Determining the pressure differential required to achieve a desired flow rate in a porous medium requires solving Darcy's law, a Laplace-like equation, with a spatially varying tensor permeability. In various scenarios, the permeability coefficient is sampled at high spatial resolution, which makes solving Darcy's equation numerically prohibitively expensive. As a consequence, much effort has gone into creating upscaled or low-resolution effective models of the coefficient while ensuring that the estimated flow rate is well reproduced, bringing to the fore the classic tradeoff between computational cost and numerical accuracy. Here we perform a statistical study to characterize the relative success of upscaling methods on a large sample of permeability coefficients that are above the percolation threshold. We introduce a technique based on mode-elimination renormalization group theory (MG) to build coarse-scale permeability coefficients. Comparing the results with coefficients upscaled using other methods, we find that MG is consistently more accurate, particularly due to its ability to address the tensorial nature of the coefficients. MG places a low computational demand, in the manner in which we have implemented it, and accurate flow-rate estimates are obtained when using MG-upscaled permeabilities that approach or are beyond the percolation threshold.

Defining window-boundaries for genomic analyses using smoothing spline techniques

DOE PAGES

Beissinger, Timothy M.; Rosa, Guilherme J.M.; Kaeppler, Shawn M.; ...

2015-04-17

High-density genomic data is often analyzed by combining information over windows of adjacent markers. Interpretation of data grouped in windows versus at individual locations may increase statistical power, simplify computation, reduce sampling noise, and reduce the total number of tests performed. However, use of adjacent marker information can result in over- or under-smoothing, undesirable window boundary specifications, or highly correlated test statistics. We introduce a method for defining windows based on statistically guided breakpoints in the data, as a foundation for the analysis of multiple adjacent data points. This method involves first fitting a cubic smoothing spline to the datamore » and then identifying the inflection points of the fitted spline, which serve as the boundaries of adjacent windows. This technique does not require prior knowledge of linkage disequilibrium, and therefore can be applied to data collected from individual or pooled sequencing experiments. Moreover, in contrast to existing methods, an arbitrary choice of window size is not necessary, since these are determined empirically and allowed to vary along the genome.« less

CRN5EXP: Expert system for statistical quality control

NASA Technical Reports Server (NTRS)

Hentea, Mariana

1991-01-01

The purpose of the Expert System CRN5EXP is to assist in checking the quality of the coils at two very important mills: Hot Rolling and Cold Rolling in a steel plant. The system interprets the statistical quality control charts, diagnoses and predicts the quality of the steel. Measurements of process control variables are recorded in a database and sample statistics such as the mean and the range are computed and plotted on a control chart. The chart is analyzed through patterns using the C Language Integrated Production System (CLIPS) and a forward chaining technique to reach a conclusion about the causes of defects and to take management measures for the improvement of the quality control techniques. The Expert System combines the certainty factors associated with the process control variables to predict the quality of the steel. The paper presents the approach to extract data from the database, the reason to combine certainty factors, the architecture and the use of the Expert System. However, the interpretation of control charts patterns requires the human expert's knowledge and lends to Expert Systems rules.

Statistical robustness of machine-learning estimates for characterizing a groundwater-surface water system, Southland, New Zealand

NASA Astrophysics Data System (ADS)

Friedel, M. J.; Daughney, C.

2016-12-01

The development of a successful surface-groundwater management strategy depends on the quality of data provided for analysis. This study evaluates the statistical robustness when using a modified self-organizing map (MSOM) technique to estimate missing values for three hypersurface models: synoptic groundwater-surface water hydrochemistry, time-series of groundwater-surface water hydrochemistry, and mixed-survey (combination of groundwater-surface water hydrochemistry and lithologies) hydrostratigraphic unit data. These models of increasing complexity are developed and validated based on observations from the Southland region of New Zealand. In each case, the estimation method is sufficiently robust to cope with groundwater-surface water hydrochemistry vagaries due to sample size and extreme data insufficiency, even when >80% of the data are missing. The estimation of surface water hydrochemistry time series values enabled the evaluation of seasonal variation, and the imputation of lithologies facilitated the evaluation of hydrostratigraphic controls on groundwater-surface water interaction. The robust statistical results for groundwater-surface water models of increasing data complexity provide justification to apply the MSOM technique in other regions of New Zealand and abroad.

Load research manual. Volume 1. Load research procedures

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

Brandenburg, L.; Clarkson, G.; Grund, Jr., C.

1980-11-01

This three-volume manual presents technical guidelines for electric utility load research. Special attention is given to issues raised by the load data reporting requirements of the Public Utility Regulatory Policies Act of 1978 and to problems faced by smaller utilities that are initiating load research programs. In Volumes 1 and 2, procedures are suggested for determining data requirements for load research, establishing the size and customer composition of a load survey sample, selecting and using equipment to record customer electricity usage, processing data tapes from the recording equipment, and analyzing the data. Statistical techniques used in customer sampling are discussedmore » in detail. The costs of load research also are estimated, and ongoing load research programs at three utilities are described. The manual includes guides to load research literature and glossaries of load research and statistical terms.« less

Physical and dynamical studies of meteors. Meteor-fragmentation and stream-distribution studies

NASA Technical Reports Server (NTRS)

Sekanina, Z.; Southworth, R. B.

1975-01-01

Population parameters of 275 streams including 20 additional streams in the synoptic-year sample were found by a computer technique. Some 16 percent of the sample is in these streams. Four meteor streams that have close orbital resemblance to Adonis cannot be positively identified as meteors ejected by Adonis within the last 12000 years. Ceplecha's discrete levels of meteor height are not evident in radar meteors. The spread of meteoroid fragments along their common trajectory was computed for most of the observed radar meteors. There is an unexpected relationship between spread and velocity that perhaps conceals relationships between fragmentation and orbits; a theoretical treatment will be necessary to resolve these relationships. Revised unbiased statistics of synoptic-year orbits are presented, together with parallel statistics for the 1961 to 1965 radar meteor orbits.

Evaluation of C-reactive protein and interleukin-6 in the peripheral blood of patients with chronic periodontitis.

PubMed

Gani, Dhruva Kumar; Lakshmi, Deepa; Krishnan, Rama; Emmadi, Pamela

2009-05-01

The aim of the present study was to investigate systemic levels of inflammatory markers of cardiovascular diseases like C-reactive protein and interleukin-6 in patients with chronic periodontitis, in comparison to periodontally healthy individuals. A total of 42 individuals, both males and females above the age of 30 years, were included in the study. Healthy controls (Group I, n = 14), chronic localized periodontitis (Group II, n = 14), and chronic generalized periodontitis (Group III, n = 14), all without any medical disorder, were recruited. Peripheral blood samples were taken and C-reactive protein (CRP) levels were estimated in the serum samples by using the Particle-Enhanced Turbidimetric Immunoassay (PETIA) technique. Serum samples of Interleukin-6 (IL-6) were assayed by using the Chemiluminescent Immunoassay (IMMULITE) technique. When mean CRP levels were compared between the groups, group III showed statistical significance when compared to group I (P = 0.04). Group III had a higher median IL-6 level (6.35 pg/mL) than Group II (< 5.0 pg/mL) and group I (< 5.0 pg/mL). Differences in median values of IL-6 were not statistically significant in any group (P = 0.29). Periodontitis results in higher systemic levels of CRP and IL-6. These elevated inflammatory factors may increase inflammatory activity in atherosclerotic lesions and potentially increasing the risk for cardiovascular events.

Application of Multivariate Statistical Analysis to Biomarkers in Se-Turkey Crude Oils

NASA Astrophysics Data System (ADS)

Gürgey, K.; Canbolat, S.

2017-11-01

Twenty-four crude oil samples were collected from the 24 oil fields distributed in different districts of SE-Turkey. API and Sulphur content (%), Stable Carbon Isotope, Gas Chromatography (GC), and Gas Chromatography-Mass Spectrometry (GC-MS) data were used to construct a geochemical data matrix. The aim of this study is to examine the genetic grouping or correlations in the crude oil samples, hence the number of source rocks present in the SE-Turkey. To achieve these aims, two of the multivariate statistical analysis techniques (Principle Component Analysis [PCA] and Cluster Analysis were applied to data matrix of 24 samples and 8 source specific biomarker variables/parameters. The results showed that there are 3 genetically different oil groups: Batman-Nusaybin Oils, Adıyaman-Kozluk Oils and Diyarbakir Oils, in addition to a one mixed group. These groupings imply that at least, three different source rocks are present in South-Eastern (SE) Turkey. Grouping of the crude oil samples appears to be consistent with the geographic locations of the oils fields, subsurface stratigraphy as well as geology of the area.

Surveying Europe's Only Cave-Dwelling Chordate Species (Proteus anguinus) Using Environmental DNA.

PubMed

Vörös, Judit; Márton, Orsolya; Schmidt, Benedikt R; Gál, Júlia Tünde; Jelić, Dušan

2017-01-01

In surveillance of subterranean fauna, especially in the case of rare or elusive aquatic species, traditional techniques used for epigean species are often not feasible. We developed a non-invasive survey method based on environmental DNA (eDNA) to detect the presence of the red-listed cave-dwelling amphibian, Proteus anguinus, in the caves of the Dinaric Karst. We tested the method in fifteen caves in Croatia, from which the species was previously recorded or expected to occur. We successfully confirmed the presence of P. anguinus from ten caves and detected the species for the first time in five others. Using a hierarchical occupancy model we compared the availability and detection probability of eDNA of two water sampling methods, filtration and precipitation. The statistical analysis showed that both availability and detection probability depended on the method and estimates for both probabilities were higher using filter samples than for precipitation samples. Combining reliable field and laboratory methods with robust statistical modeling will give the best estimates of species occurrence.

Pearson's chi-square test and rank correlation inferences for clustered data.

PubMed

Shih, Joanna H; Fay, Michael P

2017-09-01

Pearson's chi-square test has been widely used in testing for association between two categorical responses. Spearman rank correlation and Kendall's tau are often used for measuring and testing association between two continuous or ordered categorical responses. However, the established statistical properties of these tests are only valid when each pair of responses are independent, where each sampling unit has only one pair of responses. When each sampling unit consists of a cluster of paired responses, the assumption of independent pairs is violated. In this article, we apply the within-cluster resampling technique to U-statistics to form new tests and rank-based correlation estimators for possibly tied clustered data. We develop large sample properties of the new proposed tests and estimators and evaluate their performance by simulations. The proposed methods are applied to a data set collected from a PET/CT imaging study for illustration. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Creating ensembles of oblique decision trees with evolutionary algorithms and sampling

DOEpatents

Cantu-Paz, Erick [Oakland, CA; Kamath, Chandrika [Tracy, CA

2006-06-13

A decision tree system that is part of a parallel object-oriented pattern recognition system, which in turn is part of an object oriented data mining system. A decision tree process includes the step of reading the data. If necessary, the data is sorted. A potential split of the data is evaluated according to some criterion. An initial split of the data is determined. The final split of the data is determined using evolutionary algorithms and statistical sampling techniques. The data is split. Multiple decision trees are combined in ensembles.

Techniques for recognizing identity of several response functions from the data of visual inspection

NASA Astrophysics Data System (ADS)

Nechval, Nicholas A.

1996-08-01

The purpose of this paper is to present some efficient techniques for recognizing from the observed data whether several response functions are identical to each other. For example, in an industrial setting the problem may be to determine whether the production coefficients established in a small-scale pilot study apply to each of several large- scale production facilities. The techniques proposed here combine sensor information from automated visual inspection of manufactured products which is carried out by means of pixel-by-pixel comparison of the sensed image of the product to be inspected with some reference pattern (or image). Let (a1, . . . , am) be p-dimensional parameters associated with m response models of the same type. This study is concerned with the simultaneous comparison of a1, . . . , am. A generalized maximum likelihood ratio (GMLR) test is derived for testing equality of these parameters, where each of the parameters represents a corresponding vector of regression coefficients. The GMLR test reduces to an equivalent test based on a statistic that has an F distribution. The main advantage of the test lies in its relative simplicity and the ease with which it can be applied. Another interesting test for the same problem is an application of Fisher's method of combining independent test statistics which can be considered as a parallel procedure to the GMLR test. The combination of independent test statistics does not appear to have been used very much in applied statistics. There does, however, seem to be potential data analytic value in techniques for combining distributional assessments in relation to statistically independent samples which are of joint experimental relevance. In addition, a new iterated test for the problem defined above is presented. A rejection of the null hypothesis by this test provides some reason why all the parameters are not equal. A numerical example is discussed in the context of the proposed procedures for hypothesis testing.

Analytic score distributions for a spatially continuous tridirectional Monte Carol transport problem

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

Booth, T.E.

1996-01-01

The interpretation of the statistical error estimates produced by Monte Carlo transport codes is still somewhat of an art. Empirically, there are variance reduction techniques whose error estimates are almost always reliable, and there are variance reduction techniques whose error estimates are often unreliable. Unreliable error estimates usually result from inadequate large-score sampling from the score distribution`s tail. Statisticians believe that more accurate confidence interval statements are possible if the general nature of the score distribution can be characterized. Here, the analytic score distribution for the exponential transform applied to a simple, spatially continuous Monte Carlo transport problem is provided.more » Anisotropic scattering and implicit capture are included in the theory. In large part, the analytic score distributions that are derived provide the basis for the ten new statistical quality checks in MCNP.« less

Experimental statistical signature of many-body quantum interference

NASA Astrophysics Data System (ADS)

Giordani, Taira; Flamini, Fulvio; Pompili, Matteo; Viggianiello, Niko; Spagnolo, Nicolò; Crespi, Andrea; Osellame, Roberto; Wiebe, Nathan; Walschaers, Mattia; Buchleitner, Andreas; Sciarrino, Fabio

2018-03-01

Multi-particle interference is an essential ingredient for fundamental quantum mechanics phenomena and for quantum information processing to provide a computational advantage, as recently emphasized by boson sampling experiments. Hence, developing a reliable and efficient technique to witness its presence is pivotal in achieving the practical implementation of quantum technologies. Here, we experimentally identify genuine many-body quantum interference via a recent efficient protocol, which exploits statistical signatures at the output of a multimode quantum device. We successfully apply the test to validate three-photon experiments in an integrated photonic circuit, providing an extensive analysis on the resources required to perform it. Moreover, drawing upon established techniques of machine learning, we show how such tools help to identify the—a priori unknown—optimal features to witness these signatures. Our results provide evidence on the efficacy and feasibility of the method, paving the way for its adoption in large-scale implementations.

Comparison of two modalities: a novel technique, 'chromohysteroscopy', and blind endometrial sampling for the evaluation of abnormal uterine bleeding.

PubMed

Alay, Asli; Usta, Taner A; Ozay, Pinar; Karadugan, Ozgur; Ates, Ugur

2014-05-01

The objective of this study was to compare classical blind endometrial tissue sampling with hysteroscopic biopsy sampling following methylene blue dyeing in premenopausal and postmenopausal patients with abnormal uterine bleeding. A prospective case-control study was carried out in the Office Hysteroscopy Unit. Fifty-four patients with complaints of abnormal uterine bleeding were evaluated. Data of 38 patients were included in the statistical analysis. Three groups were compared by examining samples obtained through hysteroscopic biopsy before and after methylene blue dyeing, and classical blind endometrial tissue sampling. First, uterine cavity was evaluated with office hysteroscopy. Methylene blue dye was administered through the hysteroscopic inlet. Tissue samples were obtained from stained and non-stained areas. Blind endometrial sampling was performed in the same patients immediately after the hysteroscopy procedure. The results of hysteroscopic biopsy from methylene blue stained and non-stained areas and blind biopsy were compared. No statistically significant differences were determined in the comparison of biopsy samples obtained from methylene-blue stained, non-stained areas and blind biopsy (P > 0.05). We suggest that chromohysteroscopy is not superior to endometrial sampling in cases of abnormal uterine bleeding. Further studies with greater sample sizes should be performed to assess the validity of routine use of endometrial dyeing. © 2014 The Authors. Journal of Obstetrics and Gynaecology Research © 2014 Japan Society of Obstetrics and Gynecology.

A measure of the signal-to-noise ratio of microarray samples and studies using gene correlations.

PubMed

Venet, David; Detours, Vincent; Bersini, Hugues

2012-01-01

The quality of gene expression data can vary dramatically from platform to platform, study to study, and sample to sample. As reliable statistical analysis rests on reliable data, determining such quality is of the utmost importance. Quality measures to spot problematic samples exist, but they are platform-specific, and cannot be used to compare studies. As a proxy for quality, we propose a signal-to-noise ratio for microarray data, the "Signal-to-Noise Applied to Gene Expression Experiments", or SNAGEE. SNAGEE is based on the consistency of gene-gene correlations. We applied SNAGEE to a compendium of 80 large datasets on 37 platforms, for a total of 24,380 samples, and assessed the signal-to-noise ratio of studies and samples. This allowed us to discover serious issues with three studies. We show that signal-to-noise ratios of both studies and samples are linked to the statistical significance of the biological results. We showed that SNAGEE is an effective way to measure data quality for most types of gene expression studies, and that it often outperforms existing techniques. Furthermore, SNAGEE is platform-independent and does not require raw data files. The SNAGEE R package is available in BioConductor.

Investigation of interpolation techniques for the reconstruction of the first dimension of comprehensive two-dimensional liquid chromatography-diode array detector data.

PubMed

Allen, Robert C; Rutan, Sarah C

2011-10-31

Simulated and experimental data were used to measure the effectiveness of common interpolation techniques during chromatographic alignment of comprehensive two-dimensional liquid chromatography-diode array detector (LC×LC-DAD) data. Interpolation was used to generate a sufficient number of data points in the sampled first chromatographic dimension to allow for alignment of retention times from different injections. Five different interpolation methods, linear interpolation followed by cross correlation, piecewise cubic Hermite interpolating polynomial, cubic spline, Fourier zero-filling, and Gaussian fitting, were investigated. The fully aligned chromatograms, in both the first and second chromatographic dimensions, were analyzed by parallel factor analysis to determine the relative area for each peak in each injection. A calibration curve was generated for the simulated data set. The standard error of prediction and percent relative standard deviation were calculated for the simulated peak for each technique. The Gaussian fitting interpolation technique resulted in the lowest standard error of prediction and average relative standard deviation for the simulated data. However, upon applying the interpolation techniques to the experimental data, most of the interpolation methods were not found to produce statistically different relative peak areas from each other. While most of the techniques were not statistically different, the performance was improved relative to the PARAFAC results obtained when analyzing the unaligned data. Copyright © 2011 Elsevier B.V. All rights reserved.

Navigating complex sample analysis using national survey data.

PubMed

Saylor, Jennifer; Friedmann, Erika; Lee, Hyeon Joo

2012-01-01

The National Center for Health Statistics conducts the National Health and Nutrition Examination Survey and other national surveys with probability-based complex sample designs. Goals of national surveys are to provide valid data for the population of the United States. Analyses of data from population surveys present unique challenges in the research process but are valuable avenues to study the health of the United States population. The aim of this study was to demonstrate the importance of using complex data analysis techniques for data obtained with complex multistage sampling design and provide an example of analysis using the SPSS Complex Samples procedure. Illustration of challenges and solutions specific to secondary data analysis of national databases are described using the National Health and Nutrition Examination Survey as the exemplar. Oversampling of small or sensitive groups provides necessary estimates of variability within small groups. Use of weights without complex samples accurately estimates population means and frequency from the sample after accounting for over- or undersampling of specific groups. Weighting alone leads to inappropriate population estimates of variability, because they are computed as if the measures were from the entire population rather than a sample in the data set. The SPSS Complex Samples procedure allows inclusion of all sampling design elements, stratification, clusters, and weights. Use of national data sets allows use of extensive, expensive, and well-documented survey data for exploratory questions but limits analysis to those variables included in the data set. The large sample permits examination of multiple predictors and interactive relationships. Merging data files, availability of data in several waves of surveys, and complex sampling are techniques used to provide a representative sample but present unique challenges. In sophisticated data analysis techniques, use of these data is optimized.

An improved survivability prognosis of breast cancer by using sampling and feature selection technique to solve imbalanced patient classification data.

PubMed

Wang, Kung-Jeng; Makond, Bunjira; Wang, Kung-Min

2013-11-09

Breast cancer is one of the most critical cancers and is a major cause of cancer death among women. It is essential to know the survivability of the patients in order to ease the decision making process regarding medical treatment and financial preparation. Recently, the breast cancer data sets have been imbalanced (i.e., the number of survival patients outnumbers the number of non-survival patients) whereas the standard classifiers are not applicable for the imbalanced data sets. The methods to improve survivability prognosis of breast cancer need for study. Two well-known five-year prognosis models/classifiers [i.e., logistic regression (LR) and decision tree (DT)] are constructed by combining synthetic minority over-sampling technique (SMOTE), cost-sensitive classifier technique (CSC), under-sampling, bagging, and boosting. The feature selection method is used to select relevant variables, while the pruning technique is applied to obtain low information-burden models. These methods are applied on data obtained from the Surveillance, Epidemiology, and End Results database. The improvements of survivability prognosis of breast cancer are investigated based on the experimental results. Experimental results confirm that the DT and LR models combined with SMOTE, CSC, and under-sampling generate higher predictive performance consecutively than the original ones. Most of the time, DT and LR models combined with SMOTE and CSC use less informative burden/features when a feature selection method and a pruning technique are applied. LR is found to have better statistical power than DT in predicting five-year survivability. CSC is superior to SMOTE, under-sampling, bagging, and boosting to improve the prognostic performance of DT and LR.

An improved survivability prognosis of breast cancer by using sampling and feature selection technique to solve imbalanced patient classification data

PubMed Central

2013-01-01

Background Breast cancer is one of the most critical cancers and is a major cause of cancer death among women. It is essential to know the survivability of the patients in order to ease the decision making process regarding medical treatment and financial preparation. Recently, the breast cancer data sets have been imbalanced (i.e., the number of survival patients outnumbers the number of non-survival patients) whereas the standard classifiers are not applicable for the imbalanced data sets. The methods to improve survivability prognosis of breast cancer need for study. Methods Two well-known five-year prognosis models/classifiers [i.e., logistic regression (LR) and decision tree (DT)] are constructed by combining synthetic minority over-sampling technique (SMOTE) ,cost-sensitive classifier technique (CSC), under-sampling, bagging, and boosting. The feature selection method is used to select relevant variables, while the pruning technique is applied to obtain low information-burden models. These methods are applied on data obtained from the Surveillance, Epidemiology, and End Results database. The improvements of survivability prognosis of breast cancer are investigated based on the experimental results. Results Experimental results confirm that the DT and LR models combined with SMOTE, CSC, and under-sampling generate higher predictive performance consecutively than the original ones. Most of the time, DT and LR models combined with SMOTE and CSC use less informative burden/features when a feature selection method and a pruning technique are applied. Conclusions LR is found to have better statistical power than DT in predicting five-year survivability. CSC is superior to SMOTE, under-sampling, bagging, and boosting to improve the prognostic performance of DT and LR. PMID:24207108

Linking Associations of Rare Low-Abundance Species to Their Environments by Association Networks

DOE PAGES

Karpinets, Tatiana V.; Gopalakrishnan, Vancheswaran; Wargo, Jennifer; ...

2018-03-07

Studies of microbial communities by targeted sequencing of rRNA genes lead to recovering numerous rare low-abundance taxa with unknown biological roles. We propose to study associations of such rare organisms with their environments by a computational framework based on transformation of the data into qualitative variables. Namely, we analyze the sparse table of putative species or OTUs (operational taxonomic units) and samples generated in such studies, also known as an OTU table, by collecting statistics on co-occurrences of the species and on shared species richness across samples. Based on the statistics we built two association networks, of the rare putativemore » species and of the samples respectively, using a known computational technique, Association networks (Anets) developed for analysis of qualitative data. Clusters of samples and clusters of OTUs are then integrated and combined with metadata of the study to produce a map of associated putative species in their environments. We tested and validated the framework on two types of microbiomes, of human body sites and that of the Populus tree root systems. We show that in both studies the associations of OTUs can separate samples according to environmental or physiological characteristics of the studied systems.« less

Linking Associations of Rare Low-Abundance Species to Their Environments by Association Networks

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

Karpinets, Tatiana V.; Gopalakrishnan, Vancheswaran; Wargo, Jennifer

Studies of microbial communities by targeted sequencing of rRNA genes lead to recovering numerous rare low-abundance taxa with unknown biological roles. We propose to study associations of such rare organisms with their environments by a computational framework based on transformation of the data into qualitative variables. Namely, we analyze the sparse table of putative species or OTUs (operational taxonomic units) and samples generated in such studies, also known as an OTU table, by collecting statistics on co-occurrences of the species and on shared species richness across samples. Based on the statistics we built two association networks, of the rare putativemore » species and of the samples respectively, using a known computational technique, Association networks (Anets) developed for analysis of qualitative data. Clusters of samples and clusters of OTUs are then integrated and combined with metadata of the study to produce a map of associated putative species in their environments. We tested and validated the framework on two types of microbiomes, of human body sites and that of the Populus tree root systems. We show that in both studies the associations of OTUs can separate samples according to environmental or physiological characteristics of the studied systems.« less

An Intrinsic Algorithm for Parallel Poisson Disk Sampling on Arbitrary Surfaces.

PubMed

Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying

2013-03-08

Poisson disk sampling plays an important role in a variety of visual computing, due to its useful statistical property in distribution and the absence of aliasing artifacts. While many effective techniques have been proposed to generate Poisson disk distribution in Euclidean space, relatively few work has been reported to the surface counterpart. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. We propose a new technique for parallelizing the dart throwing. Rather than the conventional approaches that explicitly partition the spatial domain to generate the samples in parallel, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. It is worth noting that our algorithm is accurate as the generated Poisson disks are uniformly and randomly distributed without bias. Our method is intrinsic in that all the computations are based on the intrinsic metric and are independent of the embedding space. This intrinsic feature allows us to generate Poisson disk distributions on arbitrary surfaces. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.

Digital Holographic Microscopy, a Method for Detection of Microorganisms in Plume Samples from Enceladus and Other Icy Worlds

PubMed Central

Bedrossian, Manuel; Lindensmith, Chris

2017-01-01

Abstract Detection of extant microbial life on Earth and elsewhere in the Solar System requires the ability to identify and enumerate micrometer-scale, essentially featureless cells. On Earth, bacteria are usually enumerated by culture plating or epifluorescence microscopy. Culture plates require long incubation times and can only count culturable strains, and epifluorescence microscopy requires extensive staining and concentration of the sample and instrumentation that is not readily miniaturized for space. Digital holographic microscopy (DHM) represents an alternative technique with no moving parts and higher throughput than traditional microscopy, making it potentially useful in space for detection of extant microorganisms provided that sufficient numbers of cells can be collected. Because sample collection is expected to be the limiting factor for space missions, especially to outer planets, it is important to quantify the limits of detection of any proposed technique for extant life detection. Here we use both laboratory and field samples to measure the limits of detection of an off-axis digital holographic microscope (DHM). A statistical model is used to estimate any instrument's probability of detection at various bacterial concentrations based on the optical performance characteristics of the instrument, as well as estimate the confidence interval of detection. This statistical model agrees well with the limit of detection of 103 cells/mL that was found experimentally with laboratory samples. In environmental samples, active cells were immediately evident at concentrations of 104 cells/mL. Published estimates of cell densities for Enceladus plumes yield up to 104 cells/mL, which are well within the off-axis DHM's limits of detection to confidence intervals greater than or equal to 95%, assuming sufficient sample volumes can be collected. The quantitative phase imaging provided by DHM allowed minerals to be distinguished from cells. Off-axis DHM's ability for rapid low-level bacterial detection and counting shows its viability as a technique for detection of extant microbial life provided that the cells can be captured intact and delivered to the sample chamber in a sufficient volume of liquid for imaging. Key Words: In situ life detection—Extant microorganisms—Holographic microscopy—Ocean Worlds—Enceladus—Imaging. Astrobiology 17, 913–925. PMID:28708412

Sampling designs for HIV molecular epidemiology with application to Honduras.

PubMed

Shepherd, Bryan E; Rossini, Anthony J; Soto, Ramon Jeremias; De Rivera, Ivette Lorenzana; Mullins, James I

2005-11-01

Proper sampling is essential to characterize the molecular epidemiology of human immunodeficiency virus (HIV). HIV sampling frames are difficult to identify, so most studies use convenience samples. We discuss statistically valid and feasible sampling techniques that overcome some of the potential for bias due to convenience sampling and ensure better representation of the study population. We employ a sampling design called stratified cluster sampling. This first divides the population into geographical and/or social strata. Within each stratum, a population of clusters is chosen from groups, locations, or facilities where HIV-positive individuals might be found. Some clusters are randomly selected within strata and individuals are randomly selected within clusters. Variation and cost help determine the number of clusters and the number of individuals within clusters that are to be sampled. We illustrate the approach through a study designed to survey the heterogeneity of subtype B strains in Honduras.

Establishing homologies in protein sequences

NASA Technical Reports Server (NTRS)

Dayhoff, M. O.; Barker, W. C.; Hunt, L. T.

1983-01-01

Computer-based statistical techniques used to determine homologies between proteins occurring in different species are reviewed. The technique is based on comparison of two protein sequences, either by relating all segments of a given length in one sequence to all segments of the second or by finding the best alignment of the two sequences. Approaches discussed include selection using printed tabulations, identification of very similar sequences, and computer searches of a database. The use of the SEARCH, RELATE, and ALIGN programs (Dayhoff, 1979) is explained; sample data are presented in graphs, diagrams, and tables and the construction of scoring matrices is considered.

[Comparison of the determination of cyclosporin-A in blood samples collected on filter paper and by the ordinary technique].

PubMed

Azevedo, L S; Manrique, R; Sabbaga, E

1995-01-01

Monitoring cyclosporin-A (CsA) blood levels is of utmost importance for the rational use of this drug. Although many centers perform transplants, in Brazil there are few laboratories able to measure CsA blood levels. Therefore making blood samples reach the laboratory emerged as a problem. Collection of blood on filter paper has been a technique used for a long time in special cases. PURPOSE--To confirm the usefulness of measuring CsA blood levels in blood samples collected on filter paper and in the usual way. METHOD--We studied twenty renal cadaver kidney recipients who were receiving CsA, azathioprine and prednisone. Ninety five blood samples were collected and divided into two aliquots. One of them was sent routinely to one laboratory to perform whole blood CsA measurements. From the other aliquot, 20 microliters were pipetted on filter paper. When dried they were mailed to the other laboratory, where, after elution, CsA was measured. In both cases radioimmunoassay with polyclonal antibody was used. RESULTS--Linear correlation between both measurements revealed r = 0.81 with no statistical difference. CONCLUSION--The technique showed to be useful in clinical practice. In countries with continental size, as Brazil, it may be very helpful.

[Potentials in the regionalization of health indicators using small-area estimation methods : Exemplary results based on the 2009, 2010 and 2012 GEDA studies].

PubMed

Kroll, Lars Eric; Schumann, Maria; Müters, Stephan; Lampert, Thomas

2017-12-01

Nationwide health surveys can be used to estimate regional differences in health. Using traditional estimation techniques, the spatial depth for these estimates is limited due to the constrained sample size. So far - without special refreshment samples - results have only been available for larger populated federal states of Germany. An alternative is regression-based small-area estimation techniques. These models can generate smaller-scale data, but are also subject to greater statistical uncertainties because of the model assumptions. In the present article, exemplary regionalized results based on the studies "Gesundheit in Deutschland aktuell" (GEDA studies) 2009, 2010 and 2012, are compared to the self-rated health status of the respondents. The aim of the article is to analyze the range of regional estimates in order to assess the usefulness of the techniques for health reporting more adequately. The results show that the estimated prevalence is relatively stable when using different samples. Important determinants of the variation of the estimates are the achieved sample size on the district level and the type of the district (cities vs. rural regions). Overall, the present study shows that small-area modeling of prevalence is associated with additional uncertainties compared to conventional estimates, which should be taken into account when interpreting the corresponding findings.

Chromatographic-ICPMS methods for trace element and isotope analysis of water and biogenic calcite

NASA Astrophysics Data System (ADS)

Klinkhammer, G. P.; Haley, B. A.; McManus, J.; Palmer, M. R.

2003-04-01

ICP-MS is a powerful technique because of its sensitivity and speed of analysis. This is especially true for refractory elements that are notoriously difficult using TIMS and less energetic techniques. However, as ICP-MS instruments become more sensitive to elements of interest they also become more sensitive to interference. This becomes a pressing issue when analyzing samples with high total dissolved solids. This paper describes two trace element methods that overcome these problems by using chromatographic techniques to precondition samples prior to analysis by ICP-MS: separation of rare earth elements (REEs) from seawater using HPLC-ICPMS, and flow-through dissolution of foraminiferal calcite. Using HPLC in combination with ICP-MS it is possible to isolate the REEs from matrix, other transition elements, and each other. This method has been developed for small volume samples (5ml) making it possible to analyze sediment pore waters. As another example, subjecting foram shells to flow-through reagent addition followed by time-resolved analysis in the ICP-MS allows for systematic cleaning and dissolution of foram shells. This method provides information about the relationship between dissolution tendency and elemental composition. Flow-through is also amenable to automation thus yielding the high sample throughput required for paleoceanography, and produces a highly resolved elemental matrix that can be statistically analyzed.

Improved sample preparation of glyphosate and methylphosphonic acid by EPA method 6800A and time-of-flight mass spectrometry using novel solid-phase extraction.

PubMed

Wagner, Rebecca; Wetzel, Stephanie J; Kern, John; Kingston, H M Skip

2012-02-01

The employment of chemical weapons by rogue states and/or terrorist organizations is an ongoing concern in the United States. The quantitative analysis of nerve agents must be rapid and reliable for use in the private and public sectors. Current methods describe a tedious and time-consuming derivatization for gas chromatography-mass spectrometry and liquid chromatography in tandem with mass spectrometry. Two solid-phase extraction (SPE) techniques for the analysis of glyphosate and methylphosphonic acid are described with the utilization of isotopically enriched analytes for quantitation via atmospheric pressure chemical ionization-quadrupole time-of-flight mass spectrometry (APCI-Q-TOF-MS) that does not require derivatization. Solid-phase extraction-isotope dilution mass spectrometry (SPE-IDMS) involves pre-equilibration of a naturally occurring sample with an isotopically enriched standard. The second extraction method, i-Spike, involves loading an isotopically enriched standard onto the SPE column before the naturally occurring sample. The sample and the spike are then co-eluted from the column enabling precise and accurate quantitation via IDMS. The SPE methods in conjunction with IDMS eliminate concerns of incomplete elution, matrix and sorbent effects, and MS drift. For accurate quantitation with IDMS, the isotopic contribution of all atoms in the target molecule must be statistically taken into account. This paper describes two newly developed sample preparation techniques for the analysis of nerve agent surrogates in drinking water as well as statistical probability analysis for proper molecular IDMS. The methods described in this paper demonstrate accurate molecular IDMS using APCI-Q-TOF-MS with limits of quantitation as low as 0.400 mg/kg for glyphosate and 0.031 mg/kg for methylphosphonic acid. Copyright © 2012 John Wiley & Sons, Ltd.

Image statistics underlying natural texture selectivity of neurons in macaque V4

PubMed Central

Okazawa, Gouki; Tajima, Satohiro; Komatsu, Hidehiko

2015-01-01

Our daily visual experiences are inevitably linked to recognizing the rich variety of textures. However, how the brain encodes and differentiates a plethora of natural textures remains poorly understood. Here, we show that many neurons in macaque V4 selectively encode sparse combinations of higher-order image statistics to represent natural textures. We systematically explored neural selectivity in a high-dimensional texture space by combining texture synthesis and efficient-sampling techniques. This yielded parameterized models for individual texture-selective neurons. The models provided parsimonious but powerful predictors for each neuron’s preferred textures using a sparse combination of image statistics. As a whole population, the neuronal tuning was distributed in a way suitable for categorizing textures and quantitatively predicts human ability to discriminate textures. Together, we suggest that the collective representation of visual image statistics in V4 plays a key role in organizing the natural texture perception. PMID:25535362

Comparative Analysis of Academic Grades in Compulsory Secondary Education in Spain Using Statistical Techniques

ERIC Educational Resources Information Center

Veas, Alejandro; Gilar, Raquel; Miñano, Pablo; Castejón, Juan Luis

2017-01-01

The present study, based on the construct comparability approach, performs a comparative analysis of general points average for seven courses, using exploratory factor analysis (EFA) and the Partial Credit model (PCM) with a sample of 1398 student subjects (M = 12.5, SD = 0.67) from 8 schools in the province of Alicante (Spain). EFA confirmed a…

TQM (Total Quality Management) SPARC (Special Process Action Review Committees) Handbook

DTIC Science & Technology

1989-08-01

This document describes the techniques used to support and guide the Special Process Action Review Committees for accomplishing their goals for Total Quality Management (TQM). It includes concepts and definitions, checklists, sample formats, and assessment criteria. Keywords: Continuous process improvement; Logistics information; Process analysis; Quality control; Quality assurance; Total Quality Management ; Statistical processes; Management Planning and control; Management training; Management information systems.

A method of using cluster analysis to study statistical dependence in multivariate data

NASA Technical Reports Server (NTRS)

Borucki, W. J.; Card, D. H.; Lyle, G. C.

1975-01-01

A technique is presented that uses both cluster analysis and a Monte Carlo significance test of clusters to discover associations between variables in multidimensional data. The method is applied to an example of a noisy function in three-dimensional space, to a sample from a mixture of three bivariate normal distributions, and to the well-known Fisher's Iris data.

Developing Confidence Limits For Reliability Of Software

NASA Technical Reports Server (NTRS)

Hayhurst, Kelly J.

1991-01-01

Technique developed for estimating reliability of software by use of Moranda geometric de-eutrophication model. Pivotal method enables straightforward construction of exact bounds with associated degree of statistical confidence about reliability of software. Confidence limits thus derived provide precise means of assessing quality of software. Limits take into account number of bugs found while testing and effects of sampling variation associated with random order of discovering bugs.

The Power of Doing: A Learning Exercise That Brings the Central Limit Theorem to Life

ERIC Educational Resources Information Center

Price, Barbara A.; Zhang, Xiaolong

2007-01-01

This article demonstrates an active learning technique for teaching the Central Limit Theorem (CLT) in an introductory undergraduate business statistics class. Groups of students carry out one of two experiments in the lab, tossing a die in sets of 5 rolls or tossing a die in sets of 10 rolls. They are asked to calculate the sample average of each…

Cleanroom certification model

NASA Technical Reports Server (NTRS)

Currit, P. A.

1983-01-01

The Cleanroom software development methodology is designed to take the gamble out of product releases for both suppliers and receivers of the software. The ingredients of this procedure are a life cycle of executable product increments, representative statistical testing, and a standard estimate of the MTTF (Mean Time To Failure) of the product at the time of its release. A statistical approach to software product testing using randomly selected samples of test cases is considered. A statistical model is defined for the certification process which uses the timing data recorded during test. A reasonableness argument for this model is provided that uses previously published data on software product execution. Also included is a derivation of the certification model estimators and a comparison of the proposed least squares technique with the more commonly used maximum likelihood estimators.

Grain reconstruction of porous media: application to a low-porosity Fontainebleau sandstone.

PubMed

Thovert, J F; Yousefian, F; Spanne, P; Jacquin, C G; Adler, P M

2001-06-01

The fundamental issue of reconstructing a porous medium is examined anew in this paper, thanks to a sample of low-porosity Fontainebleau sandstone that has been analyzed by computed microtomography. Various geometric properties are determined on the experimental sample. A statistical property, namely, the probability density of the covering radius, is determined. This is used in order to reconstruct a porous medium by means of a Poissonian generation of polydisperse spheres. In a second part, the properties of the real experimental sample and of the reconstructed one are compared. The most important success of the present reconstruction technique is the fact that the numerical sample percolates despite its low porosity. Moreover, other geometrical features and conductivity are found to be in good agreement.

Comparing the Efficiency of Two Different Extraction Techniques in Removal of Maxillary Third Molars: A Randomized Controlled Trial.

PubMed

Edward, Joseph; Aziz, Mubarak A; Madhu Usha, Arjun; Narayanan, Jyothi K

2017-12-01

Extractions are routine procedures in dental surgery. Traditional extraction techniques use a combination of severing the periodontal attachment, luxation with an elevator, and removal with forceps. A new technique of extraction of maxillary third molar is introduced in this study-Joedds technique, which is compared with the conventional technique. One hundred people were included in the study, the people were divided into two groups by means of simple random sampling. In one group conventional technique of maxillary third molar extraction was used and on second Joedds technique was used. Statistical analysis was carried out with student's t test. Analysis of 100 patients based on parameters showed that the novel joedds technique had minimal trauma to surrounding tissues, less tuberosity and root fractures and the time taken for extraction was <2 min while compared to other group of patients. This novel technique has proved to be better than conventional third molar extraction technique, with minimal complications. If Proper selection of cases and right technique are used.

Evaluation of effectiveness of cement removal from implant-retained crowns using a proposed circular crisscross flossing technique.

PubMed

Ferreira, Cimara Fortes; Shafter, Mohamed Amer; Jain, Vinay; Wicks, Russel Anthony; Linder, Erno; Ledo, Carlos Alberto da Silva

2018-02-13

Extruded cement during dental implant crown cementation may cause peri-implant diseases if not removed adequately. Evaluate the efficiency of removal of cement after cementation of implant crowns using an experimental "circular crisscross flossing technique (CCCFT) flossing technique, compared to the conventional "C" shape flossing technique (CSFT). Twenty-four patients rendered 29 experimental and 29 control crowns. Prefabricated abutments were secured to the implant with the margins at least 1 mm subgingivally. The abutments were scanned using CADCAM technology and Emax crowns were fabricated in duplicates. Each crown was cemented separately and excess cement was removed using the CSFT and the CCFT techniques. After completion of cementation was completed, the screw access holes were accessed and the crown was unscrewed along with the abutment. The samples were disinfected using 70% ethanol for 10 minutes. Crowns were divided into 4 parts using a marker in order to facilitate measurement data collection. Vertical and horizontal measurements were made for extruded cement for each control and experimental groups by means of a digital microscope. One-hundred and seventeen measurements were made for each group. Mann-Whitney test was applied to verify statistical significance between the groups. The CCFT showed a highly statistically significant result (104.8 ± 13.66, p<0.0001) for cement removal compared with the CSFT (291.8 ± 21.96, p<0.0001). The vertical lengths of the extruded cement showed a median of 231.1 µm (IQR = 112.79 -398.39) and 43.62 µm (IQR = 0 - 180.21) for the control and the experimental flossing techniques, respectively. The horizontal length of the extruded cement showed a median of 987.1 µm (IQR = 476.7 - 1,933.58) and 139.2 µm (IQR = 0 - 858.28) for the control and the experimental flossing techniques, respectively. The CCFT showed highly statistically significant less cement after implant crowns cementation when compared with the CSFT.

Method matters: Experimental evidence for shorter avian sperm in faecal compared to abdominal massage samples.

PubMed

Girndt, Antje; Cockburn, Glenn; Sánchez-Tójar, Alfredo; Løvlie, Hanne; Schroeder, Julia

2017-01-01

Birds are model organisms in sperm biology. Previous work in zebra finches, suggested that sperm sampled from males' faeces and ejaculates do not differ in size. Here, we tested this assumption in a captive population of house sparrows, Passer domesticus. We compared sperm length in samples from three collection techniques: female dummy, faecal and abdominal massage samples. We found that sperm were significantly shorter in faecal than abdominal massage samples, which was explained by shorter heads and midpieces, but not flagella. This result might indicate that faecal sampled sperm could be less mature than sperm collected by abdominal massage. The female dummy method resulted in an insufficient number of experimental ejaculates because most males ignored it. In light of these results, we recommend using abdominal massage as a preferred method for avian sperm sampling. Where avian sperm cannot be collected by abdominal massage alone, we advise controlling for sperm sampling protocol statistically.

The structure of polarization maps of skin histological sections in the Fourier domain for the tasks of benign and malignant formations differentiation

NASA Astrophysics Data System (ADS)

Ushenko, V. A.; Dubolazov, A. V.; Savich, V. O.; Novakovskaya, O. Y.; Olar, O. V.; Marchuk, Y. F.

2015-02-01

The optical model of birefringent networks of biological tissues is presented. The technique of Fourier polarimetry for selection of manifestations of linear and circular birefringence of protein fibrils is suggested. The results of investigations of statistical (statistical moments of the 1st-4th orders), correlation (dispersion and excess of autocorrelation functions) and scalar-self-similar (logarithmic dependencies of power spectra) structure of Fourier spectra of polarization azimuths distribution of laser images of skin samples are presented. The criteria of differentiation of postoperative biopsy of benign (keratoma) and malignant (adenocarcinoma) skin tumors are determined.

Software for Data Analysis with Graphical Models

NASA Technical Reports Server (NTRS)

Buntine, Wray L.; Roy, H. Scott

1994-01-01

Probabilistic graphical models are being used widely in artificial intelligence and statistics, for instance, in diagnosis and expert systems, as a framework for representing and reasoning with probabilities and independencies. They come with corresponding algorithms for performing statistical inference. This offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper illustrates the framework with an example and then presents some basic techniques for the task: problem decomposition and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.

Reducing the orientation influence of Mueller matrix measurements for anisotropic scattering media

NASA Astrophysics Data System (ADS)

Sun, Minghao; He, Honghui; Zeng, Nan; Du, E.; He, Yonghong; Ma, Hui

2014-09-01

Mueller matrix polarimetry techniques contain rich micro-structural information of samples, such as the sizes and refractive indices of scatterers. Recently, Mueller matrix imaging methods have shown great potentials as powerful tools for biomedical diagnosis. However, the orientations of anisotropic fibrous structures in tissues have prominent influence on Mueller matrix measurements, resulting in difficulties for extracting micro-structural information effectively. In this paper, we apply the backscattering Mueller matrix imaging technique to biological samples with different microstructures, such as chicken heart muscle, bovine skeletal muscle, porcine liver and fat tissues. Experimental results show that the directions of the muscle fibers have prominent influence on the Mueller matrix elements. In order to reduce the orientation influence, we adopt the rotation-independent MMT and RLPI parameters, which were proposed in our previous studies, to the tissue samples. Preliminary results in this paper show that the orientation-independent parameters and their statistic features are helpful for analyzing the tissues to obtain their micro-structural properties. Since the micro-structure variations are often related to the pathological changes, the method can be applied to microscope imaging techniques and used to detect abnormal tissues such as cancer and other lesions for diagnosis purposes.

Chemometric compositional analysis of phenolic compounds in fermenting samples and wines using different infrared spectroscopy techniques.

PubMed

Aleixandre-Tudo, Jose Luis; Nieuwoudt, Helene; Aleixandre, Jose Luis; du Toit, Wessel

2018-01-01

The wine industry requires reliable methods for the quantification of phenolic compounds during the winemaking process. Infrared spectroscopy appears as a suitable technique for process control and monitoring. The ability of Fourier transform near infrared (FT-NIR), attenuated total reflectance mid infrared (ATR-MIR) and Fourier transform infrared (FT-IR) spectroscopies to predict compositional phenolic levels during red wine fermentation and aging was investigated. Prediction models containing a large number of samples collected over two vintages from several industrial fermenting tanks as well as wine samples covering a varying number of vintages were validated. FT-NIR appeared as the most accurate technique to predict the phenolic content. Although slightly less accurate models were observed, ATR-MIR and FT-IR can also be used for the prediction of the majority of phenolic measurements. Additionally, the slope and intercept test indicated a systematic error for the three spectroscopies which seems to be slightly more pronounced for HPLC generated phenolics data than for the spectrophotometric parameters. However, the results also showed that the predictions made with the three instruments are statistically comparable. The robustness of the prediction models was also investigated and discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Hudson, W.G.

Scapteriscus vicinus is the most important pest of turf and pasture grasses in Florida. This study develops a method of correlating sample results with true population density and provides the first quantitative information on spatial distribution and movement patterns of mole crickets. Three basic techniques for sampling mole crickets were compared: soil flushes, soil corer, and pitfall trapping. No statistical difference was found between the soil corer and soil flushing. Soil flushing was shown to be more sensitive to changes in population density than pitfall trapping. No technique was effective for sampling adults. Regression analysis provided a means of adjustingmore » for the effects of soil moisture and showed soil temperature to be unimportant in predicting efficiency of flush sampling. Cesium-137 was used to label females for subsequent location underground. Comparison of mean distance to nearest neighbor with the distance predicted by a random distribution model showed that the observed distance in the spring was significantly greater than hypothesized (Student's T-test, p < 0.05). Fall adult nearest neighbor distance was not different than predicted by the random distribution hypothesis.« less

Space-Time Data fusion for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Braverman, Amy; Nguyen, H.; Cressie, N.

2011-01-01

NASA has been collecting massive amounts of remote sensing data about Earth's systems for more than a decade. Missions are selected to be complementary in quantities measured, retrieval techniques, and sampling characteristics, so these datasets are highly synergistic. To fully exploit this, a rigorous methodology for combining data with heterogeneous sampling characteristics is required. For scientific purposes, the methodology must also provide quantitative measures of uncertainty that propagate input-data uncertainty appropriately. We view this as a statistical inference problem. The true but notdirectly- observed quantities form a vector-valued field continuous in space and time. Our goal is to infer those true values or some function of them, and provide to uncertainty quantification for those inferences. We use a spatiotemporal statistical model that relates the unobserved quantities of interest at point-level to the spatially aggregated, observed data. We describe and illustrate our method using CO2 data from two NASA data sets.

Load research manual. Volume 2. Fundamentals of implementing load research procedures

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

Brandenburg, L.; Clarkson, G.; Grund, Jr., C.

This three-volume manual presents technical guidelines for electric utility load research. Special attention is given to issues raised by the load data reporting requirements of the Public Utility Regulatory Policies Act of 1978 and to problems faced by smaller utilities that are initiating load research programs. In Volumes 1 and 2, procedures are suggested for determining data requirements for load research, establishing the size and customer composition of a load survey sample, selecting and using equipment to record customer electricity usage, processing data tapes from the recording equipment, and analyzing the data. Statistical techniques used in customer sampling are discussedmore » in detail. The costs of load research also are estimated, and ongoing load research programs at three utilities are described. The manual includes guides to load research literature and glossaries of load research and statistical terms.« less

Genetic Programming as Alternative for Predicting Development Effort of Individual Software Projects

PubMed Central

Chavoya, Arturo; Lopez-Martin, Cuauhtemoc; Andalon-Garcia, Irma R.; Meda-Campaña, M. E.

2012-01-01

Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects. Accuracy obtained from a genetic programming model was compared against one generated from the application of a statistical regression model. A sample of 219 projects developed by 71 practitioners was used for generating the two models, whereas another sample of 130 projects developed by 38 practitioners was used for validating them. The models used two kinds of lines of code as well as programming language experience as independent variables. Accuracy results from the model obtained with genetic programming suggest that it could be used to predict the software development effort of individual projects when these projects have been developed in a disciplined manner within a development-controlled environment. PMID:23226305

Integrated Assessment and Improvement of the Quality Assurance System for the Cosworth Casting Process

NASA Astrophysics Data System (ADS)

Yousif, Dilon

The purpose of this study was to improve the Quality Assurance (QA) System at the Nemak Windsor Aluminum Plant (WAP). The project used Six Sigma method based on Define, Measure, Analyze, Improve, and Control (DMAIC). Analysis of in process melt at WAP was based on chemical, thermal, and mechanical testing. The control limits for the W319 Al Alloy were statistically recalculated using the composition measured under stable conditions. The "Chemistry Viewer" software was developed for statistical analysis of alloy composition. This software features the Silicon Equivalency (SiBQ) developed by the IRC. The Melt Sampling Device (MSD) was designed and evaluated at WAP to overcome traditional sampling limitations. The Thermal Analysis "Filters" software was developed for cooling curve analysis of the 3XX Al Alloy(s) using IRC techniques. The impact of low melting point impurities on the start of melting was evaluated using the Universal Metallurgical Simulator and Analyzer (UMSA).

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.

Effect of autogenic relaxation on depression among menopausal women in rural areas of Thiruvallur District (Tamil Nadu).

PubMed

Sujithra, S

2014-01-01

An experimental study was conducted among 60 menopausal women, 30 each in experimental and control group who met inclusion criteria. The menopausal women were identified in both the groups and level of depression was assessed using Cornell Dysthmia rating scale. Simple random sampling technique by lottery method was used for selecting the sample. Autogenic relaxation was practiced by the menopausal women for four weeks. The findings revealed that in experimental group, after intervention of autogenic relaxation on depression among menopausal women, 23 (76.7%) had mild depression. There was a statistically significant effectiveness in experimental group at the level of p < 0.05. There was a statistically significant association between the effectiveness of autogenic relaxation on depression among menopausal women in the post-experimental group with the type of family at the level of p < 0.05.

Computed Tomography to Estimate the Representative Elementary Area for Soil Porosity Measurements

PubMed Central

Borges, Jaqueline Aparecida Ribaski; Pires, Luiz Fernando; Belmont Pereira, André

2012-01-01

Computed tomography (CT) is a technique that provides images of different solid and porous materials. CT could be an ideal tool to study representative sizes of soil samples because of the noninvasive characteristic of this technique. The scrutiny of such representative elementary sizes (RESs) has been the target of attention of many researchers related to soil physics field owing to the strong relationship between physical properties and size of the soil sample. In the current work, data from gamma-ray CT were used to assess RES in measurements of soil porosity (ϕ). For statistical analysis, a study on the full width at a half maximum (FWHM) of the adjustment of distribution of ϕ at different areas (1.2 to 1162.8 mm2) selected inside of tomographic images was proposed herein. The results obtained point out that samples with a section area corresponding to at least 882.1 mm2 were the ones that provided representative values of ϕ for the studied Brazilian tropical soil. PMID:22666133

Atmospheric heavy metal deposition in Northern Vietnam: Hanoi and Thainguyen case study using the moss biomonitoring technique, INAA and AAS.

PubMed

Viet, Hung Nguyen; Frontasyeva, Marina Vladimirovna; Thi, Thu My Trinh; Gilbert, Daniel; Bernard, Nadine

2010-06-01

The moss technique is widely used to monitor atmospheric deposition of heavy metals in many countries in Europe, whereas this technique is scarcely used in Asia. To implement this international reliable and cheap methodology in the Asian countries, it is necessary to find proper moss types typical for the Asian environment and suitable for the biomonitoring purposes. Such a case study was undertaken in Vietnam for assessing the environmental situation in strongly contaminated areas using local species of moss Barbula indica. The study is focused on two areas characterized by different pollution sources: the Hanoi urban area and the Thainguyen metallurgical zone. Fifty-four moss samples were collected there according to standard sampling procedure adopted in Europe. Two complementary analytical techniques, atomic absorption spectrometry (AAS) and instrumental neutron activation analysis (INAA), were used for determination of elemental concentrations in moss samples. To characterize the pollution sources, multivariate statistical analysis was applied. A total of 38 metal elements were determined in the moss by the two analytical techniques. The results of descriptive statistics of metal concentration in moss from the city center and periphery of Hanoi determined by AAS are presented. The similar results for moss from Thainguyen province determined by INAA and AAS are given also. A comparison of mean elemental concentrations in moss of this work with those in different environmental conditions of other authors provides reasonable information on heavy metal atmospheric deposition levels. Factor loadings and factor scores were used to identify and apportion contamination sources at the sampling sites. The values of percentage of total of factors show two highly different types of pollution in the two examined areas-the Hanoi pollution composition with high portion of urban-traffic activity and soil dust (62%), and the one of Thainguyen with factors related to industrial activities (75%). Besides, the scatter of factors in factor planes represents the greater diversity of activities in Hanoi than in Thainguyen. Good relationship between the result of factor analysis and the pollution sources evidences that the moss technique is a potential method to assess the air quality in Vietnam. Moss B. indica widely distributed in Vietnam and Indo-China is shown to be a reliable bryophyte for biomonitoring purposes in sub-tropic and tropic climate. However, the necessity of moss interspecies calibration is obvious for further studies in the area to provide results compatible with those for other Asian countries and Europe.

Eye-gaze determination of user intent at the computer interface

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

Goldberg, J.H.; Schryver, J.C.

1993-12-31

Determination of user intent at the computer interface through eye-gaze monitoring can significantly aid applications for the disabled, as well as telerobotics and process control interfaces. Whereas current eye-gaze control applications are limited to object selection and x/y gazepoint tracking, a methodology was developed here to discriminate a more abstract interface operation: zooming-in or out. This methodology first collects samples of eve-gaze location looking at controlled stimuli, at 30 Hz, just prior to a user`s decision to zoom. The sample is broken into data frames, or temporal snapshots. Within a data frame, all spatial samples are connected into a minimummore » spanning tree, then clustered, according to user defined parameters. Each cluster is mapped to one in the prior data frame, and statistics are computed from each cluster. These characteristics include cluster size, position, and pupil size. A multiple discriminant analysis uses these statistics both within and between data frames to formulate optimal rules for assigning the observations into zooming, zoom-out, or no zoom conditions. The statistical procedure effectively generates heuristics for future assignments, based upon these variables. Future work will enhance the accuracy and precision of the modeling technique, and will empirically test users in controlled experiments.« less

Development of a solid-phase microextraction-based method for sampling of persistent chlorinated hydrocarbons in an urbanized coastal environment.

PubMed

Zeng, Eddy Y; Tsukada, David; Diehl, Dario W

2004-11-01

Solid-phase microextraction (SPME) has been used as an in situ sampling technique for a wide range of volatile organic chemicals, but SPME field sampling of nonvolatile organic pollutants has not been reported. This paper describes the development of an SPME-based sampling method employing a poly(dimethylsiloxane) (PDMS)-coated (100-microm thickness) fiber as the sorbent phase. The laboratory-calibrated PDMS-coated fibers were used to construct SPME samplers, and field tests were conducted at three coastal locations off southern California to determine the equilibrium sampling time and compare the efficacy of the SPME samplers with that of an Infiltrex 100 water pumping system (Axys Environmental Systems Ltd., Sidney, British Columbia, Canada). p,p'-DDE and o,p'-DDE were the components consistently detected in the SPME samples among 42 polychlorinated biphenyl congeners and 17 chlorinated pesticidestargeted. SPME samplers deployed attwo locations with moderate and high levels of contamination for 18 and 30 d, respectively, attained statistically identical concentrations of p,p'-DDE and o,p'-DDE. In addition, SPME samplers deployed for 23 and 43 d, respectively, at a location of low contamination also contained statistically identical concentrations of p,p'-DDE. These results indicate that equilibrium could be reached within 18 to 23 d. The concentrations of p,p'-DDE, o,p'-DDE, or p,p'-DDD obtained with the SPME samplers and the Infiltrex 100 system were virtually identical. In particular, two water column concentration profiles of p,p'-DDE and o,p'-DDE acquired by the SPME samplers at a highly contaminated site on the Palos Verdes Shelf overlapped with the profiles obtained by the Infiltrex 100 system in 1997. The field tests not only reveal the advantages of the SPME samplers compared to the Infiltrex 100 system and other integrative passive devices but also indicate the need to improve the sensitivity of the SPME-based sampling technique.

Measurement of surface microtopography

NASA Technical Reports Server (NTRS)

Wall, S. D.; Farr, T. G.; Muller, J.-P.; Lewis, P.; Leberl, F. W.

1991-01-01

Acquisition of ground truth data for use in microwave interaction modeling requires measurement of surface roughness sampled at intervals comparable to a fraction of the microwave wavelength and extensive enough to adequately represent the statistics of a surface unit. Sub-centimetric measurement accuracy is thus required over large areas, and existing techniques are usually inadequate. A technique is discussed for acquiring the necessary photogrammetric data using twin film cameras mounted on a helicopter. In an attempt to eliminate tedious data reduction, an automated technique was applied to the helicopter photographs, and results were compared to those produced by conventional stereogrammetry. Derived root-mean-square (RMS) roughness for the same stereo-pair was 7.5 cm for the automated technique versus 6.5 cm for the manual method. The principal source of error is probably due to vegetation in the scene, which affects the automated technique but is ignored by a human operator.

Bayesian inference for the spatio-temporal invasion of alien species.

PubMed

Cook, Alex; Marion, Glenn; Butler, Adam; Gibson, Gavin

2007-08-01

In this paper we develop a Bayesian approach to parameter estimation in a stochastic spatio-temporal model of the spread of invasive species across a landscape. To date, statistical techniques, such as logistic and autologistic regression, have outstripped stochastic spatio-temporal models in their ability to handle large numbers of covariates. Here we seek to address this problem by making use of a range of covariates describing the bio-geographical features of the landscape. Relative to regression techniques, stochastic spatio-temporal models are more transparent in their representation of biological processes. They also explicitly model temporal change, and therefore do not require the assumption that the species' distribution (or other spatial pattern) has already reached equilibrium as is often the case with standard statistical approaches. In order to illustrate the use of such techniques we apply them to the analysis of data detailing the spread of an invasive plant, Heracleum mantegazzianum, across Britain in the 20th Century using geo-referenced covariate information describing local temperature, elevation and habitat type. The use of Markov chain Monte Carlo sampling within a Bayesian framework facilitates statistical assessments of differences in the suitability of different habitat classes for H. mantegazzianum, and enables predictions of future spread to account for parametric uncertainty and system variability. Our results show that ignoring such covariate information may lead to biased estimates of key processes and implausible predictions of future distributions.

Analyzing Large Gene Expression and Methylation Data Profiles Using StatBicRM: Statistical Biclustering-Based Rule Mining

PubMed Central

Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

2015-01-01

Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data-matrix. Finally, we have also included the integrated analysis of gene expression and methylation for determining epigenetic effect (viz., effect of methylation) on gene expression level. PMID:25830807

Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

PubMed

Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

2015-01-01

Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data-matrix. Finally, we have also included the integrated analysis of gene expression and methylation for determining epigenetic effect (viz., effect of methylation) on gene expression level.

Assessment of Coronal Spinal Alignment for Adult Spine Deformity Cases After Intraoperative T Square Shaped Use.

PubMed

Kurra, Swamy; Metkar, Umesh; Yirenkyi, Henaku; Tallarico, Richard A; Lavelle, William F

Retrospectively reviewed surgeries between 2011 and 2015 of patients who underwent posterior spinal deformity instrumentation with constructs involving fusions to pelvis and encompassing at least five levels. Measure the radiographic outcomes of coronal malalignment (CM) after use of an intraoperative T square shaped instrument in posterior spinal deformity surgeries with at least five levels of fusion and extension to pelvis. Neuromuscular children found to benefit from intraoperative T square technique to help achieve proper coronal spinal balance with extensive fusions. This intraoperative technique used in our posterior spine deformity instrumentation surgeries with the aforementioned parameters. There were 50 patients: n = 16 with intraoperative T square and n = 34 no-T square shaped device. Subgroups divided based on greater than 20 mm displacement and greater than 40 mm displacement of the C7 plumb line to the central sacral vertical line on either side in preoperative radiographs. We analyzed the demographics and the pre- and postoperative radiographic parameters of standing films: standing CM (displacement of C7 plumb line to central sacral vertical line), and major coronal Cobb angles in total sample and subgroups and compared T square shaped device with no-T square shaped device use by analysis of variance. A p value ≤.05 is statistically significant. In the total sample, though postoperative CM mean was not statistically different, we observed greater CM corrections in patients where a T square shaped device was used (70%) versus no-T square shaped device used (18%). In >20 mm and >40 mm subgroups, the postoperative mean CM values were statistically lower for the patients where a T square shaped device was used, p = .016 and p = .003, respectively. Cobb corrections were statistically higher for T square shaped device use in both >20 mm and >40 mm subgroups, 68%, respectively. The intraoperative T square shaped device technique had a positive effect on the amount of spine coronal malalignment correction after its use and for lumbar and thoracic coronal Cobb angles. Level III. Copyright © 2017 Scoliosis Research Society. Published by Elsevier Inc. All rights reserved.

Decision rules for unbiased inventory estimates

NASA Technical Reports Server (NTRS)

Argentiero, P. D.; Koch, D.

1979-01-01

An efficient and accurate procedure for estimating inventories from remote sensing scenes is presented. In place of the conventional and expensive full dimensional Bayes decision rule, a one-dimensional feature extraction and classification technique was employed. It is shown that this efficient decision rule can be used to develop unbiased inventory estimates and that for large sample sizes typical of satellite derived remote sensing scenes, resulting accuracies are comparable or superior to more expensive alternative procedures. Mathematical details of the procedure are provided in the body of the report and in the appendix. Results of a numerical simulation of the technique using statistics obtained from an observed LANDSAT scene are included. The simulation demonstrates the effectiveness of the technique in computing accurate inventory estimates.

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

Hiller, Mauritius M.; Veinot, Kenneth G.; Easterly, Clay E.

In this study, methods are addressed to reduce the computational time to compute organ-dose rate coefficients using Monte Carlo techniques. Several variance reduction techniques are compared including the reciprocity method, importance sampling, weight windows and the use of the ADVANTG software package. For low-energy photons, the runtime was reduced by a factor of 10 5 when using the reciprocity method for kerma computation for immersion of a phantom in contaminated water. This is particularly significant since impractically long simulation times are required to achieve reasonable statistical uncertainties in organ dose for low-energy photons in this source medium and geometry. Althoughmore » the MCNP Monte Carlo code is used in this paper, the reciprocity technique can be used equally well with other Monte Carlo codes.« less

A retrospective analysis of mathieu and tip urethroplasty techniques for distal hypospadias repair; A 20 year experience.

PubMed

Oztorun, Kenan; Bagbanci, Sahin; Dadali, Mumtaz; Emir, Levent; Karabulut, Ayhan

2017-09-01

We aimed to identify the changes in the application rate of two surgical techniques in distal hypospadias repair in years and compare the most popular two surgical repair techniques for distal hypospadias in terms of surgical outcomes, the factors that affect the outcomes, which were performed over a 20 year period. In this study, the records of 492 consecutive patients that had undergone an operation for distal hypospadias in the urology clinic of Ankara between May 1990 and December 2010 using either Mathieu or TIPU surgical techniques were reviewed retrospectively. The patients who had glanular, coronal, and subcoronal meatus, were accepted as distal hypospadias cases. Among the 492 examined medical records, it was revealed that 331 and 161 surgical interventions were performed by using the Mathieu urethroplasty technique (Group-1) and TIP urethroplasty technique (Group-2), respectively. Group-1 was divided into two subgroups; namely Group-1a (patients with primary hypospadias) and Group-1b (patients with previous hypospadias operation). Likewise, Group-2 was divided into two subgroups; namely group-2a and group-2b. The patients' ages, number of previously urethroplasty operations, localization of the external urethral meatus prior to the operation, chordee state, length of the newly formed urethra, whether urinary diversion was done or not, post-operative complications and data regarding the follow-up period were evaluated, and the effects of these variables on the surgical outcome were investigated via statistical analyses. The primary objective of this study is to identify the changes in the application rate of two surgical techniques in distal hypospadias repair over the a 20 year period, and the secondary objectives are to compare the most popular two surgical repair techniques for distal hypospadias in terms of surgical outcomes, and the factors affecting the outcomes. Independent samples t test and Pearson's Chisquare test was used for statistical analysis. p<0.05 was considered as statistically significant. There were no statistically significant differences between the subgroups in terms of age, length of the neo-urethra, number of previously performed urethroplasty operations, surgical success rates, or complications (p>0.05). The concurrent utilization of the cystostomy and urethral stent was significantly more frequent in group-1 (p<0.05; Pearson's Chi-square test). It was determined that over time, TIP urethroplasty has become a more preferred technique for the repair of distal hypospadias. Both surgical techniques have similar success rates in distal hypospadias cases. TIP urethroplasty has become the method of choice over time.

Tissue dissolution ability of sodium hypochlorite activated by photon-initiated photoacoustic streaming technique.

PubMed

Guneser, Mehmet Burak; Arslan, Dilara; Usumez, Aslihan

2015-05-01

The aim of this study was to evaluate the effect of the photon-initiated photoacoustic streaming (PIPS) technique on the pulp tissue-dissolving capacity of sodium hypochlorite (NaOCl) and compare it with the EndoActivator System (Dentsply Tulsa Dental Specialties, Tulsa, OK) and the Er:YAG laser with an endodontic fiber tip. Bovine pulp tissue samples (45 ± 15 mg) and dentin powder (10 mg) were placed in 1.5-mL Eppendorf tubes with 1 mL 5.25% NaOCl (Wizard; Rehber Kimya, Istanbul, Turkey) or distilled water (control) for 5 minutes with activation by the EndoActivator System, the Er:YAG laser with an endodontic fiber tip, and the PIPS technique. Nonactivated NaOCl served as the positive control. All testing procedures were performed at room temperature. The tissue samples were weighed before and after treatment, and the percentage of weight loss was calculated. The differences were statistically analyzed. The highest rate of tissue dissolution was observed in the NaOCl + Er:YAG group (P < .05). The NaOCl + PIPS group dissolved more bovine pulp tissue than the nonactivated NaOCl group (P < .05). There was no statistically significant difference between the rates of tissue dissolution of the NaOCl + EA and the nonactivated NaOCl groups (P > .05). NaOCl activation with the Er:YAG laser with an endodontic fiber tip was the most effective in bovine pulp tissue dissolution. The PIPS technique also promoted superior tissue-dissolving effects when compared with no activation. However, the EndoActivator System had no direct effect on tissue dissolution. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Application of Digital Image Analysis to Determine Pancreatic Islet Mass and Purity in Clinical Islet Isolation and Transplantation

PubMed Central

Wang, Ling-jia; Kissler, Hermann J; Wang, Xiaojun; Cochet, Olivia; Krzystyniak, Adam; Misawa, Ryosuke; Golab, Karolina; Tibudan, Martin; Grzanka, Jakub; Savari, Omid; Grose, Randall; Kaufman, Dixon B; Millis, Michael; Witkowski, Piotr

2015-01-01

Pancreatic islet mass, represented by islet equivalent (IEQ), is the most important parameter in decision making for clinical islet transplantation. To obtain IEQ, the sample of islets is routinely counted manually under a microscope and discarded thereafter. Islet purity, another parameter in islet processing, is routinely acquired by estimation only. In this study, we validated our digital image analysis (DIA) system developed using the software of Image Pro Plus for islet mass and purity assessment. Application of the DIA allows to better comply with current good manufacturing practice (cGMP) standards. Human islet samples were captured as calibrated digital images for the permanent record. Five trained technicians participated in determination of IEQ and purity by manual counting method and DIA. IEQ count showed statistically significant correlations between the manual method and DIA in all sample comparisons (r >0.819 and p < 0.0001). Statistically significant difference in IEQ between both methods was found only in High purity 100μL sample group (p = 0.029). As far as purity determination, statistically significant differences between manual assessment and DIA measurement was found in High and Low purity 100μL samples (p<0.005), In addition, islet particle number (IPN) and the IEQ/IPN ratio did not differ statistically between manual counting method and DIA. In conclusion, the DIA used in this study is a reliable technique in determination of IEQ and purity. Islet sample preserved as a digital image and results produced by DIA can be permanently stored for verification, technical training and islet information exchange between different islet centers. Therefore, DIA complies better with cGMP requirements than the manual counting method. We propose DIA as a quality control tool to supplement the established standard manual method for islets counting and purity estimation. PMID:24806436

T1-weighted brain imaging with a 32-channel coil at 3T using TurboFLASH BLADE compared with standard cartesian k-space sampling.

PubMed

Attenberger, Ulrike I; Runge, Val M; Williams, Kenneth D; Stemmer, Alto; Michaely, Henrik J; Schoenberg, Stefan O; Reiser, Maximilian F; Wintersperger, Bernd J

2009-03-01

Motion artifacts often markedly degrade image quality in clinical scans. The BLADE technique offers an alternative k-space sampling scheme reducing the effect of patient related motion on image quality. The purpose of this study is the comparison of imaging artifacts, signal-to-noise (SNR), and contrast-to-noise ratio (CNR) of a new turboFLASH BLADE k-space trajectory with the standard Cartesian k-space sampling for brain imaging, using a 32-channel coil at 3T. The results from 32 patients included after informed consent are reported. This study was performed with a 32-channel head coil on a 3T scanner. Sagittal and axial T1-weighted FLASH sequences (TR/TE 250/2.46 milliseconds, flip angle 70-degree), acquired with Cartesian k-space sampling and T1-weighted turboFLASH sequences (TR/TE/TIsag/TIax 3200/2.77/1144/1056 milliseconds, flip angle 20-degree), using PROPELLER (BLADE) k-space trajectory, were compared. SNR and CNR were evaluated using a paired student t test. The frequency of motion artifacts was assessed in a blinded read. To analyze the differences between both techniques a McNemar test was performed. A P value <0.05 was considered statistically significant. From the blinded read, the overall preference in terms of diagnostic image quality was statistically significant in favor of the BLADE turboFLASH data sets, compared with standard FLASH for both sagittal (P < 0.0001) and axial (P < 0.0001) planes. The frequency of motion artifacts from the scalp was higher for standard FLASH sequences than for BLADE sequences on both axial (47%, P < 0.0003) and sagittal (69%, P < 0.0001) planes. BLADE was preferred in 100% (sagittal plane) and 80% (axial plane) of in-patient data sets and in 68% (sagittal plane) and 73% (axial plane) of out-patient data sets.The BLADE T1 scan did have lower SNRmean (BLADEax 179 +/- 98, Cartesianax 475 +/- 145, BLADEsag 171 +/- 51, and Cartesiansag 697 +/- 129) with P values indicating accordingly a statistically significant difference (Pax <0.0001, Psag < 0.0001), because of the fundamental difference in imaging approach (FLASH vs. turboFLASH). Differences for CNR were also statistically significant, independent of imaging plane (Pax = 0.001, Psag = 0.02). Results demonstrate that turboFLASH BLADE is applicable at 3T with a 32-channel head coil for T1-weighted imaging, with reduced ghost artifacts. This approach offers the first truly clinically applicable T1-weighted BLADE technique for brain imaging at 3T, with consistent excellent image quality.

Rapid Analysis of Carbohydrates in Bioprocess Samples: An Evaluation of the CarboPac SA10 for HPAE-PAD Analysis by Interlaboratory Comparison

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

Sevcik, R. S.; Hyman, D. A.; Basumallich, L.

2013-01-01

A technique for carbohydrate analysis for bioprocess samples has been developed, providing reduced analysis time compared to current practice in the biofuels R&D community. The Thermofisher CarboPac SA10 anion-exchange column enables isocratic separation of monosaccharides, sucrose and cellobiose in approximately 7 minutes. Additionally, use of a low-volume (0.2 mL) injection valve in combination with a high-volume detection cell minimizes the extent of sample dilution required to bring sugar concentrations into the linear range of the pulsed amperometric detector (PAD). Three laboratories, representing academia, industry, and government, participated in an interlaboratory study which analyzed twenty-one opportunistic samples representing biomass pretreatment, enzymaticmore » saccharification, and fermentation samples. The technique's robustness, linearity, and interlaboratory reproducibility were evaluated and showed excellent-to-acceptable characteristics. Additionally, quantitation by the CarboPac SA10/PAD was compared with the current practice method utilizing a HPX-87P/RID. While these two methods showed good agreement a statistical comparison found significant quantitation difference between them, highlighting the difference between selective and universal detection modes.« less

Comparison of Solomon technique with selective laser ablation for twin-twin transfusion syndrome: a systematic review.

PubMed

Dhillon, R K; Hillman, S C; Pounds, R; Morris, R K; Kilby, M D

2015-11-01

To compare the Solomon and selective techniques for fetoscopic laser ablation (FLA) for the treatment of twin-twin transfusion syndrome (TTTS) in monochorionic-diamniotic twin pregnancies. This was a systematic review conducted in accordance with the PRISMA statement. Electronic searches were performed for relevant citations published from inception to September 2014. Selected studies included pregnancies undergoing FLA for TTTS that reported on recurrence of TTTS, occurrence of twin anemia-polycythemia sequence (TAPS) or survival. From 270 possible citations, three studies were included, two cohort studies and one randomized controlled trial (RCT), which directly compared the Solomon and selective techniques for FLA. The odds ratios (OR) of recurrent TTTS when using the Solomon vs the selective technique in the two cohort studies (n = 249) were 0.30 (95% CI, 0.00-4.46) and 0.45 (95% CI, 0.07-2.20). The RCT (n = 274) demonstrated a statistically significant reduction in risk of recurrent TTTS with the Solomon technique (OR, 0.21 (95% CI, 0.04-0.98); P = 0.03). The ORs for the development of TAPS following the Solomon and the selective techniques were 0.20 (95% CI, 0.00-2.46) and 0.61 (95% CI, 0.05-5.53) in the cohort studies and 0.16 (95% CI, 0.05-0.49) in the RCT, with statistically significant differences for the RCT only (P < 0.001). Observational evidence suggested overall better survival with the Solomon technique, which was statistically significant for survival of at least one twin. The RCT did not demonstrate a significant difference in survival between the two techniques, most probably owing to the small sample size and lack of power. This systematic review of observational, comparative cohort and RCT data suggests a trend towards a reduction in TAPS and recurrent TTTS and an increase in twin survival, with no increase in the occurrence of complications or adverse events, when using the Solomon compared to the selective technique for the treatment of TTTS. These findings need to be confirmed by an appropriately-powered RCT with long-term neurological follow-up. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

Introducer curving technique for the prevention of tilting of transfemoral Günther Tulip inferior vena cava filter.

PubMed

Xiao, Liang; Huang, De-sheng; Shen, Jing; Tong, Jia-jie

2012-01-01

To determine whether the introducer curving technique is useful in decreasing the degree of tilting of transfemoral Tulip filters. The study sample group consisted of 108 patients with deep vein thrombosis who were enrolled and planned to undergo thrombolysis, and who accepted transfemoral Tulip filter insertion procedure. The patients were randomly divided into Group C and Group T. The introducer curving technique was Adopted in Group T. The post-implantation filter tilting angle (ACF) was measured in an anteroposterior projection. The retrieval hook adhering to the vascular wall was measured via tangential cavogram during retrieval. The overall average ACF was 5.8 ± 4.14 degrees. In Group C, the average ACF was 7.1 ± 4.52 degrees. In Group T, the average ACF was 4.4 ± 3.20 degrees. The groups displayed a statistically significant difference (t = 3.573, p = 0.001) in ACF. Additionally, the difference of ACF between the left and right approaches turned out to be statistically significant (7.1 ± 4.59 vs. 5.1 ± 3.82, t = 2.301, p = 0.023). The proportion of severe tilt (ACF ≥ 10°) in Group T was significantly lower than that in Group C (9.3% vs. 24.1%, χ(2) = 4.267, p = 0.039). Between the groups, the difference in the rate of the retrieval hook adhering to the vascular wall was also statistically significant (2.9% vs. 24.2%, χ(2) = 5.030, p = 0.025). The introducer curving technique appears to minimize the incidence and extent of transfemoral Tulip filter tilting.

Crop identification and area estimation over large geographic areas using LANDSAT MSS data

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator)

1977-01-01

The author has identified the following significant results. LANDSAT MSS data was adequate to accurately identify wheat in Kansas; corn and soybean estimates in Indiana were less accurate. Computer-aided analysis techniques were effectively used to extract crop identification information from LANDSAT data. Systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county, district, and state levels. Training statistics were successfully extended from one county to other counties having similar crops and soils if the training areas sampled the total variation of the area to be classified.

Driven-dissipative quantum Monte Carlo method for open quantum systems

NASA Astrophysics Data System (ADS)

Nagy, Alexandra; Savona, Vincenzo

2018-05-01

We develop a real-time full configuration-interaction quantum Monte Carlo approach to model driven-dissipative open quantum systems with Markovian system-bath coupling. The method enables stochastic sampling of the Liouville-von Neumann time evolution of the density matrix thanks to a massively parallel algorithm, thus providing estimates of observables on the nonequilibrium steady state. We present the underlying theory and introduce an initiator technique and importance sampling to reduce the statistical error. Finally, we demonstrate the efficiency of our approach by applying it to the driven-dissipative two-dimensional X Y Z spin-1/2 model on a lattice.

On evaluating compliance with air pollution levels 'not to be exceeded more than once per year'

NASA Technical Reports Server (NTRS)

Neustadter, H. E.; Sidik, S. M.

1974-01-01

The point of view taken is that the Environmental Protection Agency (EPA) Air Quality Standards (AQS) represent conditions which must be made to exist in the ambient environment. The statistical techniques developed should serve as tools for measuring the closeness to achieving the desired quality of air. It is shown that the sampling frequency recommended by EPA is inadequate to meet these objectives when the standard is expressed as a level not to be exceeded more than once per year and sampling frequency is once every three days or less frequent.

Different protocols for cryobiopsy versus forceps biopsy in diagnosis of patients with endobronchial tumors.

PubMed

Jabari, Hamidreza; Sami, Ramin; Fakhri, Mohammad; Kiani, Arda

2012-01-01

Forceps biopsy is the standard procedure to obtain specimens in endobronchial lesions. New studies have proposed flexible cryoprobe as an accepted alternative method for this technique. Although diagnostic use of the cryobiopsy is confirmed in few studies, there is paucity of data with regard to an optimum protocol for this method since one of the main considerations in cryobiopsy is the freezing time. To evaluate diagnostic yield and safety of endobronchial biopsies using the flexible cryoprobe. Moreover, different freezing times were assessed to propose an optimized protocol for this diagnostic modality. For each patient with a confirmed intrabronchial lesion, diagnostic o value of forceps biopsy, cryobiopsy in three seconds, cryobiopsy in five seconds and combined results of cryobiopsy in both timings were recorded. A total of 60 patients (39 males and 21 females; Mean age 56.7 +/- 13.3) were included. Specimens that were obtained by cryobiopsy in five seconds were significantly larger than those of forceps biopsy and cryobiopsy in three seconds (p < 0.001). We showed that the achieved diagnostic yields for all three methods were not statistically different (p > 0.05). Simultaneous usage of samples produced in both cryobiopsies can significantly improve the diagnostic yield (p = 0.02). Statistical analysis showed that there were no significant differences in case of bleeding frequency among the three sampling methods. This study confirmed safety and feasibility of cryobiopsy. Additionally, combination of sampling with two different cold induction timings would significantly increase sensitivity of this emerging technique..

Evaluation of C-reactive protein and interleukin-6 in the peripheral blood of patients with chronic periodontitis

PubMed Central

Gani, Dhruva Kumar; Lakshmi, Deepa; Krishnan, Rama; Emmadi, Pamela

2009-01-01

Aims and Objectives: The aim of the present study was to investigate systemic levels of inflammatory markers of cardiovascular diseases like C-reactive protein and interleukin-6 in patients with chronic periodontitis, in comparison to periodontally healthy individuals. Materials and Methods: A total of 42 individuals, both males and females above the age of 30 years, were included in the study. Healthy controls (Group I, n = 14), chronic localized periodontitis (Group II, n = 14), and chronic generalized periodontitis (Group III, n = 14), all without any medical disorder, were recruited. Peripheral blood samples were taken and C-reactive protein (CRP) levels were estimated in the serum samples by using the Particle-Enhanced Turbidimetric Immunoassay (PETIA) technique. Serum samples of Interleukin-6 (IL-6) were assayed by using the Chemiluminescent Immunoassay (IMMULITE) technique. Results: When mean CRP levels were compared between the groups, group III showed statistical significance when compared to group I (P = 0.04). Group III had a higher median IL-6 level (6.35 pg/mL) than Group II (< 5.0 pg/mL) and group I (< 5.0 pg/mL). Differences in median values of IL-6 were not statistically significant in any group (P = 0.29). Conclusion: Periodontitis results in higher systemic levels of CRP and IL-6. These elevated inflammatory factors may increase inflammatory activity in atherosclerotic lesions and potentially increasing the risk for cardiovascular events. PMID:20407653

Techniques for estimating health care costs with censored data: an overview for the health services researcher

PubMed Central

Wijeysundera, Harindra C; Wang, Xuesong; Tomlinson, George; Ko, Dennis T; Krahn, Murray D

2012-01-01

Objective The aim of this study was to review statistical techniques for estimating the mean population cost using health care cost data that, because of the inability to achieve complete follow-up until death, are right censored. The target audience is health service researchers without an advanced statistical background. Methods Data were sourced from longitudinal heart failure costs from Ontario, Canada, and administrative databases were used for estimating costs. The dataset consisted of 43,888 patients, with follow-up periods ranging from 1 to 1538 days (mean 576 days). The study was designed so that mean health care costs over 1080 days of follow-up were calculated using naïve estimators such as full-sample and uncensored case estimators. Reweighted estimators – specifically, the inverse probability weighted estimator – were calculated, as was phase-based costing. Costs were adjusted to 2008 Canadian dollars using the Bank of Canada consumer price index (http://www.bankofcanada.ca/en/cpi.html). Results Over the restricted follow-up of 1080 days, 32% of patients were censored. The full-sample estimator was found to underestimate mean cost ($30,420) compared with the reweighted estimators ($36,490). The phase-based costing estimate of $37,237 was similar to that of the simple reweighted estimator. Conclusion The authors recommend against the use of full-sample or uncensored case estimators when censored data are present. In the presence of heavy censoring, phase-based costing is an attractive alternative approach. PMID:22719214

Autonomous spatially adaptive sampling in experiments based on curvature, statistical error and sample spacing with applications in LDA measurements

NASA Astrophysics Data System (ADS)

Theunissen, Raf; Kadosh, Jesse S.; Allen, Christian B.

2015-06-01

Spatially varying signals are typically sampled by collecting uniformly spaced samples irrespective of the signal content. For signals with inhomogeneous information content, this leads to unnecessarily dense sampling in regions of low interest or insufficient sample density at important features, or both. A new adaptive sampling technique is presented directing sample collection in proportion to local information content, capturing adequately the short-period features while sparsely sampling less dynamic regions. The proposed method incorporates a data-adapted sampling strategy on the basis of signal curvature, sample space-filling, variable experimental uncertainty and iterative improvement. Numerical assessment has indicated a reduction in the number of samples required to achieve a predefined uncertainty level overall while improving local accuracy for important features. The potential of the proposed method has been further demonstrated on the basis of Laser Doppler Anemometry experiments examining the wake behind a NACA0012 airfoil and the boundary layer characterisation of a flat plate.

Growth, Characterization and Applications of Beta-Barium Borate and Related Crystals

DTIC Science & Technology

1993-10-31

Crystal symmetry determines the form of the second order polarization tensor. The second order polarizability tensor is defined by the piezoelectric...cold finger. A temperature oscillation technique1 I was used to limit the number of nuclei formed . These experiments typically yielded thin crystal...statistically sampled to determine the optimal seeding orientation. % was reasoned that the large crystal plates were formed from nucleii which had a favorable

A Study of the Work of Daniel Starch: A Chapter in the History of the Application of Psychology and Statistics to Education and Other Areas.

ERIC Educational Resources Information Center

Johanningmeier, Erwin V.

This document examines the work of Daniel Starch, emphasizing his work in educational psychology and advertising. After earning his doctorate in psychology (1906), Starch attempted to apply the findings of the new science to education and to advertising. This application met with much success. In advertising, he devised new sampling techniques and…

The influence of the microbial quality of wastewater, lettuce cultivars and enumeration technique when estimating the microbial contamination of wastewater-irrigated lettuce.

PubMed

Makkaew, P; Miller, M; Cromar, N J; Fallowfield, H J

2017-04-01

This study investigated the volume of wastewater retained on the surface of three different varieties of lettuce, Iceberg, Cos, and Oak leaf, following submersion in wastewater of different microbial qualities (10, 10 2 , 10 3 , and 10 4 E. coli MPN/100 mL) as a surrogate method for estimation of contamination of spray-irrigated lettuce. Uniquely, Escherichia coli was enumerated, after submersion, on both the outer and inner leaves and in a composite sample of lettuce. E. coli were enumerated using two techniques. Firstly, from samples of leaves - the direct method. Secondly, using an indirect method, where the E. coli concentrations were estimated from the volume of wastewater retained by the lettuce and the E. coli concentration of the wastewater. The results showed that different varieties of lettuce retained significantly different volumes of wastewater (p < 0.01). No statistical differences (p > 0.01) were detected between E. coli counts obtained from different parts of lettuce, nor between the direct and indirect enumeration methods. Statistically significant linear relationships were derived relating the E. coli concentration of the wastewater in which the lettuces were submerged to the subsequent E. coli count on each variety the lettuce.

Model Checking Techniques for Assessing Functional Form Specifications in Censored Linear Regression Models.

PubMed

León, Larry F; Cai, Tianxi

2012-04-01

In this paper we develop model checking techniques for assessing functional form specifications of covariates in censored linear regression models. These procedures are based on a censored data analog to taking cumulative sums of "robust" residuals over the space of the covariate under investigation. These cumulative sums are formed by integrating certain Kaplan-Meier estimators and may be viewed as "robust" censored data analogs to the processes considered by Lin, Wei & Ying (2002). The null distributions of these stochastic processes can be approximated by the distributions of certain zero-mean Gaussian processes whose realizations can be generated by computer simulation. Each observed process can then be graphically compared with a few realizations from the Gaussian process. We also develop formal test statistics for numerical comparison. Such comparisons enable one to assess objectively whether an apparent trend seen in a residual plot reects model misspecification or natural variation. We illustrate the methods with a well known dataset. In addition, we examine the finite sample performance of the proposed test statistics in simulation experiments. In our simulation experiments, the proposed test statistics have good power of detecting misspecification while at the same time controlling the size of the test.

Multivariate model of female black bear habitat use for a Geographic Information System

USGS Publications Warehouse

Clark, Joseph D.; Dunn, James E.; Smith, Kimberly G.

1993-01-01

Simple univariate statistical techniques may not adequately assess the multidimensional nature of habitats used by wildlife. Thus, we developed a multivariate method to model habitat-use potential using a set of female black bear (Ursus americanus) radio locations and habitat data consisting of forest cover type, elevation, slope, aspect, distance to roads, distance to streams, and forest cover type diversity score in the Ozark Mountains of Arkansas. The model is based on the Mahalanobis distance statistic coupled with Geographic Information System (GIS) technology. That statistic is a measure of dissimilarity and represents a standardized squared distance between a set of sample variates and an ideal based on the mean of variates associated with animal observations. Calculations were made with the GIS to produce a map containing Mahalanobis distance values within each cell on a 60- × 60-m grid. The model identified areas of high habitat use potential that could not otherwise be identified by independent perusal of any single map layer. This technique avoids many pitfalls that commonly affect typical multivariate analyses of habitat use and is a useful tool for habitat manipulation or mitigation to favor terrestrial vertebrates that use habitats on a landscape scale.

Staging Liver Fibrosis with Statistical Observers

NASA Astrophysics Data System (ADS)

Brand, Jonathan Frieman

Chronic liver disease is a worldwide health problem, and hepatic fibrosis (HF) is one of the hallmarks of the disease. Pathology diagnosis of HF is based on textural change in the liver as a lobular collagen network that develops within portal triads. The scale of collagen lobules is characteristically on order of 1mm, which close to the resolution limit of in vivo Gd-enhanced MRI. In this work the methods to collect training and testing images for a Hotelling observer are covered. An observer based on local texture analysis is trained and tested using wet-tissue phantoms. The technique is used to optimize the MRI sequence based on task performance. The final method developed is a two stage model observer to classify fibrotic and healthy tissue in both phantoms and in vivo MRI images. The first stage observer tests for the presence of local texture. Test statistics from the first observer are used to train the second stage observer to globally sample the local observer results. A decision of the disease class is made for an entire MRI image slice using test statistics collected from the second observer. The techniques are tested on wet-tissue phantoms and in vivo clinical patient data.

Sulfur and ash reduction potential and selected chemical and physical properties of United States coals. [Contains glossary

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

Cavallaro, J.A.; Deurbrouck, A.W.; Killmeyer, R.P.

1991-02-01

This report presents the washability and comprehensive characterization results of 184 raw coal channel samples, including anthracite, bituminous and lignite coals, collected from the Central Region of the United States. This is the second of a three volume report on the coals of the United States. All the data are presented in six appendices. Statistical techniques and definitions are presented in Appendix A, and a glossary of terms is presented in Appendix B. The complete washability data and an in-depth characterization of each sample are presented alphabetically by state in Appendix C. In Appendix D, a statistical evaluation is givenmore » for the composited washability data, selected chemical and physical properties and washability data interpolated at various levels of Btu recovery. This presentation is shown by state, section, and region where four or more samples were collected. Appendix E presents coalbed codes and names for the Central Region coals. Graphical summations are presented by state, section and region showing the effects of crushing on impurity reductions, and the distribution of raw and clean coal samples meeting various levels of SO{sub 2} emissions. 35 figs., 5 tabs.« less

Evaluation of implant osseointegration with different regeneration techniques in the treatment of bone defects around implants: an experimental study in a rabbit model.

PubMed

Guerra, Isabel; Morais Branco, Fernando; Vasconcelos, Mário; Afonso, Américo; Figueiral, Helena; Zita, Raquel

2011-03-01

The aim of this study was to evaluate the osseointegration of implants placed in areas with artificially created bone defects, using three bone regeneration techniques. The experimental model was the rabbit femur (16), where bone defects were created and implants were placed. The peri-implant bone defects were filled with a deproteinized bovine bone mineral, NuOss™ (N), NuOss™ combined with plasma rich in growth factors (PRGF) (N+PRGF), NuOss™ covered by an RCM(6) membrane (N+M), or remained unfilled (control group [C]). After 4 and 8 weeks, the animals were euthanized and bone tissue blocks with the implants and the surrounding bone tissue were removed and processed according to a histological protocol for hard tissues on non-decalcified ground sections. The samples were studied by light and electron scanning microscopy, histometric analysis was performed to assess the percentage of bone in direct contact with the implant surface and a statistical analysis of the results was performed. In the samples analyzed 4 weeks after implantation, the percentage of bone tissue in direct contact with the implant surface for the four groups were 57.66±24.39% (N), 58.62±20.37% (N+PRGF), 70.82±20.34 % (N+M) and 33.07±5.49% (C). In the samples with 8 weeks of implantation time, the percentage of bone in direct contact was 63.35±27.69% (N), 58.42±24.77% (N+PRGF), 78.02±15.13% (N+M) and 40.28±27.32% (C). In terms of the percentage of bone contact, groups N and N+M presented statistically significant differences from group C in the 4-week trial test (P<0.05; ANOVA). For the 8-week results, only group N+M showed statistically significant differences when compared with group C (P<0.05; ANOVA). In conclusion, the NuOss™ granules/RCM(6) membrane combination presented a percentage of bone contact with the implant surface statistically greater than in the other groups. © 2010 John Wiley & Sons A/S.

Preserving the distribution of inorganic arsenic species in groundwater and acid mine drainage samples

USGS Publications Warehouse

Bednar, A.J.; Garbarino, J.R.; Ranville, J.F.; Wildeman, T.R.

2002-01-01

The distribution of inorganic arsenic species must be preserved in the field to eliminate changes caused by metal oxyhydroxide precipitation, photochemical oxidation, and redox reactions. Arsenic species sorb to iron and manganese oxyhydroxide precipitates, and arsenite can be oxidized to arsenate by photolytically produced free radicals in many sample matrices. Several preservatives were evaluated to minimize metal oxyhydroxide precipitation, such as inorganic acids and ethylenediaminetetraacetic acid (EDTA). EDTA was found to work best for all sample matrices tested. Storing samples in opaque polyethylene bottles eliminated the effects of photochemical reactions. The preservation technique was tested on 71 groundwater and six acid mine drainage samples. Concentrations in groundwater samples reached 720 ??g-As/L for arsenite and 1080 ??g-As/L for arsenate, and acid mine drainage samples reached 13 000 ??g-As/L for arsenite and 3700 ??g-As/L for arsenate. The arsenic species distribution in the samples ranged from 0 to 90% arsenite. The stability of the preservation technique was established by comparing laboratory arsenic speciation results for samples preserved in the field to results for subsamples speciated onsite. Statistical analyses indicated that the difference between arsenite and arsenate concentrations for samples preserved with EDTA in opaque bottles and field speciation results were analytically insignificant. The percentage change in arsenite:arsenate ratios for a preserved acid mine drainage sample and groundwater sample during a 3-month period was -5 and +3%, respectively.

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data

PubMed Central

Dazard, Jean-Eudes; Rao, J. Sunil

2012-01-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput “omics” data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel “similarity statistic”-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called ‘MVR’ (‘Mean-Variance Regularization’), downloadable from the CRAN website. PMID:22711950

Comparison of Logistic Regression and Random Forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)

NASA Astrophysics Data System (ADS)

Trigila, Alessandro; Iadanza, Carla; Esposito, Carlo; Scarascia-Mugnozza, Gabriele

2015-11-01

The aim of this work is to define reliable susceptibility models for shallow landslides using Logistic Regression and Random Forests multivariate statistical techniques. The study area, located in North-East Sicily, was hit on October 1st 2009 by a severe rainstorm (225 mm of cumulative rainfall in 7 h) which caused flash floods and more than 1000 landslides. Several small villages, such as Giampilieri, were hit with 31 fatalities, 6 missing persons and damage to buildings and transportation infrastructures. Landslides, mainly types such as earth and debris translational slides evolving into debris flows, were triggered on steep slopes and involved colluvium and regolith materials which cover the underlying metamorphic bedrock. The work has been carried out with the following steps: i) realization of a detailed event landslide inventory map through field surveys coupled with observation of high resolution aerial colour orthophoto; ii) identification of landslide source areas; iii) data preparation of landslide controlling factors and descriptive statistics based on a bivariate method (Frequency Ratio) to get an initial overview on existing relationships between causative factors and shallow landslide source areas; iv) choice of criteria for the selection and sizing of the mapping unit; v) implementation of 5 multivariate statistical susceptibility models based on Logistic Regression and Random Forests techniques and focused on landslide source areas; vi) evaluation of the influence of sample size and type of sampling on results and performance of the models; vii) evaluation of the predictive capabilities of the models using ROC curve, AUC and contingency tables; viii) comparison of model results and obtained susceptibility maps; and ix) analysis of temporal variation of landslide susceptibility related to input parameter changes. Models based on Logistic Regression and Random Forests have demonstrated excellent predictive capabilities. Land use and wildfire variables were found to have a strong control on the occurrence of very rapid shallow landslides.

A Practical Guide for the Preparation of Specimens for X-ray Fluorescence and X-ray Diffraction Analysis (by V. E. Buhrke, R. Jenkins, and D. K. Smith)

NASA Astrophysics Data System (ADS)

Rudman, Reuben

1999-06-01

Wiley-VCH: New York, 1998. xxiv + 333 pp. ISBN 0-471-19458-1. $79.95. I would have subtitled this book "All You Ever Wanted To Know about ...Sample Preparation". Although its principal thrust is geared towards the analytical chemist in an X-ray diffraction (XRD) or X-ray fluorescence (XRF) service laboratory, this text will be of use primarily as a reference source in all milieus dealing with undergraduate research projects and advanced laboratory courses in physical and analytical chemistry. It contains dozens of suggestions for preparing randomly oriented small samples of nearly anything. For example, rocks and minerals, soft organics and hard ceramics, radioactive and liquid materials, metals and oils are all treated. As the availability of XRD and XRF equipment has increased, so has the use of these techniques in the teaching schedule. Many undergraduate laboratory and research projects utilizing these methods have been described in the literature and are found in laboratory textbooks. Very often, especially with the increasingly common use of automated computer-controlled instrumentation, sample preparation has become the key experimental technique required for successful data collection. However, it is not always easy to prepare the statistically random distribution of small particles (crystallites) that is required by these methods. A multitude of techniques have been developed over the past 70 years, but many of them have been handed down by word of mouth or are scattered throughout the literature. This book represents an attempt to systematically describe the theory and practice of sample preparation. This excellent guide to the intricacies of sample preparation begins with a description of statistical sampling methods and the principles of grinding techniques. After a discussion of XRF specimen preparation, which includes pressing pellets, fusion methods, crucible selection and handling very small samples, detailed descriptions for handling rocks, minerals, cements, metals, oils, and vegetation [sic] are given. The preparation of XRD samples is described for various diffraction equipment geometries (utilizing both counter and film detectors), including specific information regarding the use of flat specimens and slurries, the use of internal standards, and the effects of crystallite size on the diffraction pattern. Methods for handling ceramics, clays, zeolites, air-sensitive samples, thin films, and plastics are described, along with the special handling requirements for materials to be studied by high-pressure, high-temperature, or low-temperature techniques. One whole chapter is devoted to the equipment used in specimen preparation, including grinders, pulverizers, presses, specimen holders, repair of platinumware, and sources of all types of special equipment. Did you ever want to know where to get a Plattner steel mortar or a micronizing mill or soft-glass capillary tubes with 0.01-mm wall thickness? It's all here in this monograph. The book ends with a good glossary of terms, a general bibliography in addition to the extensive list of references following each of its 9 chapters, and an index. It will be of help in many areas of spectroscopy and analytical chemistry, as well as in XRD and XRF analyses.

Protecting High Energy Barriers: A New Equation to Regulate Boost Energy in Accelerated Molecular Dynamics Simulations.

PubMed

Sinko, William; de Oliveira, César Augusto F; Pierce, Levi C T; McCammon, J Andrew

2012-01-10

Molecular dynamics (MD) is one of the most common tools in computational chemistry. Recently, our group has employed accelerated molecular dynamics (aMD) to improve the conformational sampling over conventional molecular dynamics techniques. In the original aMD implementation, sampling is greatly improved by raising energy wells below a predefined energy level. Recently, our group presented an alternative aMD implementation where simulations are accelerated by lowering energy barriers of the potential energy surface. When coupled with thermodynamic integration simulations, this implementation showed very promising results. However, when applied to large systems, such as proteins, the simulation tends to be biased to high energy regions of the potential landscape. The reason for this behavior lies in the boost equation used since the highest energy barriers are dramatically more affected than the lower ones. To address this issue, in this work, we present a new boost equation that prevents oversampling of unfavorable high energy conformational states. The new boost potential provides not only better recovery of statistics throughout the simulation but also enhanced sampling of statistically relevant regions in explicit solvent MD simulations.

Surveying Europe’s Only Cave-Dwelling Chordate Species (Proteus anguinus) Using Environmental DNA

PubMed Central

Márton, Orsolya; Schmidt, Benedikt R.; Gál, Júlia Tünde; Jelić, Dušan

2017-01-01

In surveillance of subterranean fauna, especially in the case of rare or elusive aquatic species, traditional techniques used for epigean species are often not feasible. We developed a non-invasive survey method based on environmental DNA (eDNA) to detect the presence of the red-listed cave-dwelling amphibian, Proteus anguinus, in the caves of the Dinaric Karst. We tested the method in fifteen caves in Croatia, from which the species was previously recorded or expected to occur. We successfully confirmed the presence of P. anguinus from ten caves and detected the species for the first time in five others. Using a hierarchical occupancy model we compared the availability and detection probability of eDNA of two water sampling methods, filtration and precipitation. The statistical analysis showed that both availability and detection probability depended on the method and estimates for both probabilities were higher using filter samples than for precipitation samples. Combining reliable field and laboratory methods with robust statistical modeling will give the best estimates of species occurrence. PMID:28129383

Fission gas bubble identification using MATLAB's image processing toolbox

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

Collette, R.; King, J.; Keiser, Jr., D.

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

Fission gas bubble identification using MATLAB's image processing toolbox

DOE PAGES

Collette, R.; King, J.; Keiser, Jr., D.; ...

2016-06-08

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

Electromigration kinetics and critical current of Pb-free interconnects

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

Lu, Minhua; Rosenberg, Robert

2014-04-07

Electromigration kinetics of Pb-free solder bump interconnects have been studied using a single bump parameter sweep technique. By removing bump to bump variations in structure, texture, and composition, the single bump sweep technique has provided both activation energy and power exponents that reflect atomic migration and interface reactions with fewer samples, shorter stress time, and better statistics than standard failure testing procedures. Contact metallurgies based on Cu and Ni have been studied. Critical current, which corresponds to the Blech limit, was found to exist in the Ni metallurgy, but not in the Cu metallurgy. A temperature dependence of critical currentmore » was also observed.« less

A method for the measurement and analysis of ride vibrations of transportation systems

NASA Technical Reports Server (NTRS)

Catherines, J. J.; Clevenson, S. A.; Scholl, H. F.

1972-01-01

The measurement and recording of ride vibrations which affect passenger comfort in transportation systems and the subsequent data-reduction methods necessary for interpreting the data present exceptional instrumentation requirements and necessitate the use of computers for specialized analysis techniques. A method is presented for both measuring and analyzing ride vibrations of the type encountered in ground and air transportation systems. A portable system for measuring and recording low-frequency, low-amplitude accelerations and specialized data-reduction procedures are described. Sample vibration measurements in the form of statistical parameters representative of typical transportation systems are also presented to demonstrate the utility of the techniques.

Analysis of teaching materials of civic education is characterized by the value of character in building an anti-corruption culture

NASA Astrophysics Data System (ADS)

Sarmini; Suyanto, Totok; Nadiroh, Ulin

2018-01-01

In general, corruption is very harmful to society. One of the efforts in preventing corruption is by the culture of Anti-Corruption Education in the young generation through teaching materials in schools. The research method used is qualitative description. The sample in this research is 60 junior high school teachers of Citizenship Education in Surabaya. Data analysis technique used in this research is descriptive statistic with percentage technique. The result of this research is that it is very important that the value of the character of anti-corruption education in teaching materials to grow in the young generation.

Serum proteins by capillary zone electrophoresis: approaches to the definition of reference values.

PubMed

Petrini, C; Alessio, M G; Scapellato, L; Brambilla, S; Franzini, C

1999-10-01

The Paragon CZE 2000 (Beckman Analytical, Milan, Italy) is an automatic dedicated capillary zone electrophoresis (CZE) system, producing a five-zone serum protein pattern with quantitative estimation of the zones. With the view of substituting this instrument for two previously used serum protein electrophoresis techniques, we planned to produce reference values for the "new" systems leading to compatible interpretation of the results. High resolution cellulose acetate electrophoresis with visual inspection and descriptive reporting (HR-CAE) and five-zone cellulose acetate electrophoresis with densitometry (CAE-D) were the previously used techniques. Serum samples (n = 167) giving "normal pattern" with HR-CAE were assayed with the CZE system, and the results were statistically assessed to yield 0.95 reference intervals. One thousand normal and pathological serum samples were then assayed with the CAE-D and the CZE techniques, and the regression equations of the CAE-D values over the CZE values for the five zones were used to transform the CAE-D reference limits into the CZE reference limits. The two sets of reference values thereby produced were in good agreement with each other and also with reference values previously reported for the CZE system. Thus, reference values for the CZE techniques permit interpretation of results coherent with the previously used techniques and reporting modes.

FabricS: A user-friendly, complete and robust software for particle shape-fabric analysis

NASA Astrophysics Data System (ADS)

Moreno Chávez, G.; Castillo Rivera, F.; Sarocchi, D.; Borselli, L.; Rodríguez-Sedano, L. A.

2018-06-01

Shape-fabric is a textural parameter related to the spatial arrangement of elongated particles in geological samples. Its usefulness spans a range from sedimentary petrology to igneous and metamorphic petrology. Independently of the process being studied, when a material flows, the elongated particles are oriented with the major axis in the direction of flow. In sedimentary petrology this information has been used for studies of paleo-flow direction of turbidites, the origin of quartz sediments, and locating ignimbrite vents, among others. In addition to flow direction and its polarity, the method enables flow rheology to be inferred. The use of shape-fabric has been limited due to the difficulties of automatically measuring particles and analyzing them with reliable circular statistics programs. This has dampened interest in the method for a long time. Shape-fabric measurement has increased in popularity since the 1980s thanks to the development of new image analysis techniques and circular statistics software. However, the programs currently available are unreliable, old and are incompatible with newer operating systems, or require programming skills. The goal of our work is to develop a user-friendly program, in the MATLAB environment, with a graphical user interface, that can process images and includes editing functions, and thresholds (elongation and size) for selecting a particle population and analyzing it with reliable circular statistics algorithms. Moreover, the method also has to produce rose diagrams, orientation vectors, and a complete series of statistical parameters. All these requirements are met by our new software. In this paper, we briefly explain the methodology from collection of oriented samples in the field to the minimum number of particles needed to obtain reliable fabric data. We obtained the data using specific statistical tests and taking into account the degree of iso-orientation of the samples and the required degree of reliability. The program has been verified by means of several simulations performed using appropriately designed features and by analyzing real samples.

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

Solc, J.

The reclamation effort typically deals with consequences of mining activity instead of being planned well before the mining. Detailed assessment of principal hydro- and geochemical processes participating in pore and groundwater chemistry evolution was carried out at three surface mine localities in North Dakota-the Fritz mine, the Indian Head mine, and the Velva mine. The geochemical model MINTEQUA2 and advanced statistical analysis coupled with traditional interpretive techniques were used to determine site-specific environmental characteristics and to compare the differences between study sites. Multivariate statistical analysis indicates that sulfate, magnesium, calcium, the gypsum saturation index, and sodium contribute the most tomore » overall differences in groundwater chemistry between study sites. Soil paste extract pH and EC measurements performed on over 3700 samples document extremely acidic soils at the Fritz mine. The number of samples with pH <5.5 reaches 80%-90% of total samples from discrete depth near the top of the soil profile at the Fritz mine. Soil samples from Indian Head and Velva do not indicate the acidity below the pH of 5.5 limit. The percentage of samples with EC > 3 mS cm{sup -1} is between 20% and 40% at the Fritz mine and below 20% for samples from Indian Head and Velva. The results of geochemical modeling indicate an increased tendency for gypsum saturation within the vadose zone, particularly within the lands disturbed by mining activity. This trend is directly associated with increased concentrations of sulfate anions as a result of mineral oxidation. Geochemical modeling, statistical analysis, and soil extract pH and EC measurements proved to be reliable, fast, and relatively cost-effective tools for the assessment of soil acidity, the extent of the oxidation zone, and the potential for negative impact on pore and groundwater chemistry.« less

Statistical Methods in Ai: Rare Event Learning Using Associative Rules and Higher-Order Statistics

NASA Astrophysics Data System (ADS)

Iyer, V.; Shetty, S.; Iyengar, S. S.

2015-07-01

Rare event learning has not been actively researched since lately due to the unavailability of algorithms which deal with big samples. The research addresses spatio-temporal streams from multi-resolution sensors to find actionable items from a perspective of real-time algorithms. This computing framework is independent of the number of input samples, application domain, labelled or label-less streams. A sampling overlap algorithm such as Brooks-Iyengar is used for dealing with noisy sensor streams. We extend the existing noise pre-processing algorithms using Data-Cleaning trees. Pre-processing using ensemble of trees using bagging and multi-target regression showed robustness to random noise and missing data. As spatio-temporal streams are highly statistically correlated, we prove that a temporal window based sampling from sensor data streams converges after n samples using Hoeffding bounds. Which can be used for fast prediction of new samples in real-time. The Data-cleaning tree model uses a nonparametric node splitting technique, which can be learned in an iterative way which scales linearly in memory consumption for any size input stream. The improved task based ensemble extraction is compared with non-linear computation models using various SVM kernels for speed and accuracy. We show using empirical datasets the explicit rule learning computation is linear in time and is only dependent on the number of leafs present in the tree ensemble. The use of unpruned trees (t) in our proposed ensemble always yields minimum number (m) of leafs keeping pre-processing computation to n × t log m compared to N2 for Gram Matrix. We also show that the task based feature induction yields higher Qualify of Data (QoD) in the feature space compared to kernel methods using Gram Matrix.

Inverse statistical physics of protein sequences: a key issues review.

PubMed

Cocco, Simona; Feinauer, Christoph; Figliuzzi, Matteo; Monasson, Rémi; Weigt, Martin

2018-03-01

In the course of evolution, proteins undergo important changes in their amino acid sequences, while their three-dimensional folded structure and their biological function remain remarkably conserved. Thanks to modern sequencing techniques, sequence data accumulate at unprecedented pace. This provides large sets of so-called homologous, i.e. evolutionarily related protein sequences, to which methods of inverse statistical physics can be applied. Using sequence data as the basis for the inference of Boltzmann distributions from samples of microscopic configurations or observables, it is possible to extract information about evolutionary constraints and thus protein function and structure. Here we give an overview over some biologically important questions, and how statistical-mechanics inspired modeling approaches can help to answer them. Finally, we discuss some open questions, which we expect to be addressed over the next years.

Inverse statistical physics of protein sequences: a key issues review

NASA Astrophysics Data System (ADS)

Cocco, Simona; Feinauer, Christoph; Figliuzzi, Matteo; Monasson, Rémi; Weigt, Martin

2018-03-01

In the course of evolution, proteins undergo important changes in their amino acid sequences, while their three-dimensional folded structure and their biological function remain remarkably conserved. Thanks to modern sequencing techniques, sequence data accumulate at unprecedented pace. This provides large sets of so-called homologous, i.e. evolutionarily related protein sequences, to which methods of inverse statistical physics can be applied. Using sequence data as the basis for the inference of Boltzmann distributions from samples of microscopic configurations or observables, it is possible to extract information about evolutionary constraints and thus protein function and structure. Here we give an overview over some biologically important questions, and how statistical-mechanics inspired modeling approaches can help to answer them. Finally, we discuss some open questions, which we expect to be addressed over the next years.

Statistical Analysis of a Round-Robin Measurement Survey of Two Candidate Materials for a Seebeck Coefficient Standard Reference Material

PubMed Central

Lu, Z. Q. J.; Lowhorn, N. D.; Wong-Ng, W.; Zhang, W.; Thomas, E. L.; Otani, M.; Green, M. L.; Tran, T. N.; Caylor, C.; Dilley, N. R.; Downey, A.; Edwards, B.; Elsner, N.; Ghamaty, S.; Hogan, T.; Jie, Q.; Li, Q.; Martin, J.; Nolas, G.; Obara, H.; Sharp, J.; Venkatasubramanian, R.; Willigan, R.; Yang, J.; Tritt, T.

2009-01-01

In an effort to develop a Standard Reference Material (SRM™) for Seebeck coefficient, we have conducted a round-robin measurement survey of two candidate materials—undoped Bi2Te3 and Constantan (55 % Cu and 45 % Ni alloy). Measurements were performed in two rounds by twelve laboratories involved in active thermoelectric research using a number of different commercial and custom-built measurement systems and techniques. In this paper we report the detailed statistical analyses on the interlaboratory measurement results and the statistical methodology for analysis of irregularly sampled measurement curves in the interlaboratory study setting. Based on these results, we have selected Bi2Te3 as the prototype standard material. Once available, this SRM will be useful for future interlaboratory data comparison and instrument calibrations. PMID:27504212

Survey of statistical techniques used in validation studies of air pollution prediction models

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

Bornstein, R D; Anderson, S F

1979-03-01

Statistical techniques used by meteorologists to validate predictions made by air pollution models are surveyed. Techniques are divided into the following three groups: graphical, tabular, and summary statistics. Some of the practical problems associated with verification are also discussed. Characteristics desired in any validation program are listed and a suggested combination of techniques that possesses many of these characteristics is presented.

Color quality of pigments in cochineals (Dactylopius coccus Costa). Geographical origin characterization using multivariate statistical analysis.

PubMed

Méndez, Jesús; González, Mónica; Lobo, M Gloria; Carnero, Aurelio

2004-03-10

The commercial value of a cochineal (Dactylopius coccus Costa) sample is associated with its color quality. Because the cochineal is a legal food colorant, its color quality is generally understood as its pigment content. Simply put, the higher this content, the more valuable the sample is to the market. In an effort to devise a way to measure the color quality of a cochineal, the present study evaluates different parameters of color measurement such as chromatic attributes (L*, and a*), percentage of carminic acid, tint determination, and chromatographic profile of pigments. Tint determination did not achieve this objective because this parameter does not correlate with carminic acid content. On the other hand, carminic acid showed a highly significant correlation (r = - 0.922, p = 0.000) with L* values determined from powdered cochineal samples. The combination of the information from the spectrophotometric determination of carminic acid with that of the pigment profile acquired by liquid chromatography (LC) and the composition of the red and yellow pigment groups, also acquired by LC, enables greater accuracy in judging the quality of the final sample. As a result of this study, it was possible to achieve the separation of cochineal samples according to geographical origin using two statistical techniques: cluster analysis and principal component analysis.

Protein Multiplexed Immunoassay Analysis with R.

PubMed

Breen, Edmond J

2017-01-01

Plasma samples from 177 control and type 2 diabetes patients collected at three Australian hospitals are screened for 14 analytes using six custom-made multiplex kits across 60 96-well plates. In total 354 samples were collected from the patients, representing one baseline and one end point sample from each patient. R methods and source code for analyzing the analyte fluorescence response obtained from these samples by Luminex Bio-Plex ® xMap multiplexed immunoassay technology are disclosed. Techniques and R procedures for reading Bio-Plex ® result files for statistical analysis and data visualization are also presented. The need for technical replicates and the number of technical replicates are addressed as well as plate layout design strategies. Multinomial regression is used to determine plate to sample covariate balance. Methods for matching clinical covariate information to Bio-Plex ® results and vice versa are given. As well as methods for measuring and inspecting the quality of the fluorescence responses are presented. Both fixed and mixed-effect approaches for immunoassay statistical differential analysis are presented and discussed. A random effect approach to outlier analysis and detection is also shown. The bioinformatics R methodology present here provides a foundation for rigorous and reproducible analysis of the fluorescence response obtained from multiplexed immunoassays.

Experiments on Nucleation in Different Flow Regimes

NASA Technical Reports Server (NTRS)

Bayuzick, R. J.; Hofmeister, W. H.; Morton, C. M.; Robinson, M. B.

1999-01-01

The vast majority of metallic engineering materials are solidified from the liquid phase. Understanding the solidification process is essential to control microstructure, which in turn, determines the properties of materials. The genesis of solidification is nucleation, where the first stable solid forms from the liquid phase. Nucleation kinetics determine the degree of undercooling and phase selection. As such, it is important to understand nucleation phenomena in order to control solidification or glass formation in metals and alloys. Early experiments in nucleation kinetics were accomplished by droplet dispersion methods. Dilatometry was used by Turnbull and others, and more recently differential thermal analysis and differential scanning calorimetry have been used for kinetic studies. These techniques have enjoyed success; however, there are difficulties with these experiments. Since materials are dispersed in a medium, the character of the emulsion/metal interface affects the nucleation behavior. Statistics are derived from the large number of particles observed in a single experiment, but dispersions have a finite size distribution which adds to the uncertainty of the kinetic determinations. Even though temperature can be controlled quite well before the onset of nucleation, the release of the latent heat of fusion during nucleation of particles complicates the assumption of isothermality during these experiments. Containerless processing has enabled another approach to the study of nucleation kinetics. With levitation techniques it is possible to undercool one sample to nucleation repeatedly in a controlled manner, such that the statistics of the nucleation process can be derived from multiple experiments on a single sample. The authors have fully developed the analysis of nucleation experiments on single samples following the suggestions of Skripov. The advantage of these experiments is that the samples are directly observable. The nucleation temperature can be measured by noncontact optical pyrometry, the mass of the sample is known, and post processing analysis can be conducted on the sample. The disadvantages are that temperature measurement must have exceptionally high precision, and it is not possible to isolate specific heterogeneous sites as in droplet dispersions.

Comparison of methods for determination of total oil sands-derived naphthenic acids in water samples.

PubMed

Hughes, Sarah A; Huang, Rongfu; Mahaffey, Ashley; Chelme-Ayala, Pamela; Klamerth, Nikolaus; Meshref, Mohamed N A; Ibrahim, Mohamed D; Brown, Christine; Peru, Kerry M; Headley, John V; Gamal El-Din, Mohamed

2017-11-01

There are several established methods for the determination of naphthenic acids (NAs) in waters associated with oil sands mining operations. Due to their highly complex nature, measured concentration and composition of NAs vary depending on the method used. This study compared different common sample preparation techniques, analytical instrument methods, and analytical standards to measure NAs in groundwater and process water samples collected from an active oil sands operation. In general, the high- and ultrahigh-resolution methods, namely high performance liquid chromatography time-of-flight mass spectrometry (UPLC-TOF-MS) and Orbitrap mass spectrometry (Orbitrap-MS), were within an order of magnitude of the Fourier transform infrared spectroscopy (FTIR) methods. The gas chromatography mass spectrometry (GC-MS) methods consistently had the highest NA concentrations and greatest standard error. Total NAs concentration was not statistically different between sample preparation of solid phase extraction and liquid-liquid extraction. Calibration standards influenced quantitation results. This work provided a comprehensive understanding of the inherent differences in the various techniques available to measure NAs and hence the potential differences in measured amounts of NAs in samples. Results from this study will contribute to the analytical method standardization for NA analysis in oil sands related water samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

NASA Astrophysics Data System (ADS)

Fort, G.; Jourdain, B.; Lelièvre, T.; Stoltz, G.

2018-04-01

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang-Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

Comparing geological and statistical approaches for element selection in sediment tracing research

NASA Astrophysics Data System (ADS)

Laceby, J. Patrick; McMahon, Joe; Evrard, Olivier; Olley, Jon

2015-04-01

Elevated suspended sediment loads reduce reservoir capacity and significantly increase the cost of operating water treatment infrastructure, making the management of sediment supply to reservoirs of increasingly importance. Sediment fingerprinting techniques can be used to determine the relative contributions of different sources of sediment accumulating in reservoirs. The objective of this research is to compare geological and statistical approaches to element selection for sediment fingerprinting modelling. Time-integrated samplers (n=45) were used to obtain source samples from four major subcatchments flowing into the Baroon Pocket Dam in South East Queensland, Australia. The geochemistry of potential sources were compared to the geochemistry of sediment cores (n=12) sampled in the reservoir. The geochemical approach selected elements for modelling that provided expected, observed and statistical discrimination between sediment sources. Two statistical approaches selected elements for modelling with the Kruskal-Wallis H-test and Discriminatory Function Analysis (DFA). In particular, two different significance levels (0.05 & 0.35) for the DFA were included to investigate the importance of element selection on modelling results. A distribution model determined the relative contributions of different sources to sediment sampled in the Baroon Pocket Dam. Elemental discrimination was expected between one subcatchment (Obi Obi Creek) and the remaining subcatchments (Lexys, Falls and Bridge Creek). Six major elements were expected to provide discrimination. Of these six, only Fe2O3 and SiO2 provided expected, observed and statistical discrimination. Modelling results with this geological approach indicated 36% (+/- 9%) of sediment sampled in the reservoir cores were from mafic-derived sources and 64% (+/- 9%) were from felsic-derived sources. The geological and the first statistical approach (DFA0.05) differed by only 1% (σ 5%) for 5 out of 6 model groupings with only the Lexys Creek modelling results differing significantly (35%). The statistical model with expanded elemental selection (DFA0.35) differed from the geological model by an average of 30% for all 6 models. Elemental selection for sediment fingerprinting therefore has the potential to impact modeling results. Accordingly is important to incorporate both robust geological and statistical approaches when selecting elements for sediment fingerprinting. For the Baroon Pocket Dam, management should focus on reducing the supply of sediments derived from felsic sources in each of the subcatchments.

Information theoretic partitioning and confidence based weight assignment for multi-classifier decision level fusion in hyperspectral target recognition applications

NASA Astrophysics Data System (ADS)

Prasad, S.; Bruce, L. M.

2007-04-01

There is a growing interest in using multiple sources for automatic target recognition (ATR) applications. One approach is to take multiple, independent observations of a phenomenon and perform a feature level or a decision level fusion for ATR. This paper proposes a method to utilize these types of multi-source fusion techniques to exploit hyperspectral data when only a small number of training pixels are available. Conventional hyperspectral image based ATR techniques project the high dimensional reflectance signature onto a lower dimensional subspace using techniques such as Principal Components Analysis (PCA), Fisher's linear discriminant analysis (LDA), subspace LDA and stepwise LDA. While some of these techniques attempt to solve the curse of dimensionality, or small sample size problem, these are not necessarily optimal projections. In this paper, we present a divide and conquer approach to address the small sample size problem. The hyperspectral space is partitioned into contiguous subspaces such that the discriminative information within each subspace is maximized, and the statistical dependence between subspaces is minimized. We then treat each subspace as a separate source in a multi-source multi-classifier setup and test various decision fusion schemes to determine their efficacy. Unlike previous approaches which use correlation between variables for band grouping, we study the efficacy of higher order statistical information (using average mutual information) for a bottom up band grouping. We also propose a confidence measure based decision fusion technique, where the weights associated with various classifiers are based on their confidence in recognizing the training data. To this end, training accuracies of all classifiers are used for weight assignment in the fusion process of test pixels. The proposed methods are tested using hyperspectral data with known ground truth, such that the efficacy can be quantitatively measured in terms of target recognition accuracies.

42 CFR 402.109 - Statistical sampling.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Statistical sampling. 402.109 Section 402.109... Statistical sampling. (a) Purpose. CMS or OIG may introduce the results of a statistical sampling study to... or caused to be presented. (b) Prima facie evidence. The results of the statistical sampling study...

42 CFR 402.109 - Statistical sampling.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Statistical sampling. 402.109 Section 402.109... Statistical sampling. (a) Purpose. CMS or OIG may introduce the results of a statistical sampling study to... or caused to be presented. (b) Prima facie evidence. The results of the statistical sampling study...

Active Sphagnum girgensohnii Russow Moss Biomonitoring of an Industrial Site in Romania: Temporal Variation in the Elemental Content.

PubMed

Culicov, Otilia A; Zinicovscaia, Inga; Duliu, O G

2016-05-01

The moss-bag transplant technique was used to investigate the kinetics of the accumulation of 38 elements in Sphagnum girgensohni moss samples in the highly polluted municipality of Baia Mare, Romania. The moss samples collected from the unpolluted Vitosha Mountain Natural Reserve, Bulgaria, were analyzed after 1, 2, 3, and 4 months of exposure, respectively. The ANOVA method was used to assay the statistical significance of the observed changes in elemental content, as determined by neutron activation analysis. The content of Zn, Se, As, Ag, Cd, and Sb increased steadily, while that of physiologically active K and Cl, as well as Rb and Cs, decreased exponentially. The study showed that an adequate application of the moss transplant technique in an urban environment should consider the exposure time as a critical parameter, since particular elements are depleted in the moss at sites with high atmospheric loading of metals.

Exploitation of immunofluorescence for the quantification and characterization of small numbers of Pasteuria endospores.

PubMed

Costa, Sofia R; Kerry, Brian R; Bardgett, Richard D; Davies, Keith G

2006-12-01

The Pasteuria group of endospore-forming bacteria has been studied as a biocontrol agent of plant-parasitic nematodes. Techniques have been developed for its detection and quantification in soil samples, and these mainly focus on observations of endospore attachment to nematodes. Characterization of Pasteuria populations has recently been performed with DNA-based techniques, which usually require the extraction of large numbers of spores. We describe a simple immunological method for the quantification and characterization of Pasteuria populations. Bayesian statistics were used to determine an extraction efficiency of 43% and a threshold of detection of 210 endospores g(-1) sand. This provided a robust means of estimating numbers of endospores in small-volume samples from a natural system. Based on visual assessment of endospore fluorescence, a quantitative method was developed to characterize endospore populations, which were shown to vary according to their host.

Assessment of higher order structure comparability in therapeutic proteins using nuclear magnetic resonance spectroscopy.

PubMed

Amezcua, Carlos A; Szabo, Christina M

2013-06-01

In this work, we applied nuclear magnetic resonance (NMR) spectroscopy to rapidly assess higher order structure (HOS) comparability in protein samples. Using a variation of the NMR fingerprinting approach described by Panjwani et al. [2010. J Pharm Sci 99(8):3334-3342], three nonglycosylated proteins spanning a molecular weight range of 6.5-67 kDa were analyzed. A simple statistical method termed easy comparability of HOS by NMR (ECHOS-NMR) was developed. In this method, HOS similarity between two samples is measured via the correlation coefficient derived from linear regression analysis of binned NMR spectra. Applications of this method include HOS comparability assessment during new product development, manufacturing process changes, supplier changes, next-generation products, and the development of biosimilars to name just a few. We foresee ECHOS-NMR becoming a routine technique applied to comparability exercises used to complement data from other analytical techniques. Copyright © 2013 Wiley Periodicals, Inc.

Multiple sensitive estimation and optimal sample size allocation in the item sum technique.

PubMed

Perri, Pier Francesco; Rueda García, María Del Mar; Cobo Rodríguez, Beatriz

2018-01-01

For surveys of sensitive issues in life sciences, statistical procedures can be used to reduce nonresponse and social desirability response bias. Both of these phenomena provoke nonsampling errors that are difficult to deal with and can seriously flaw the validity of the analyses. The item sum technique (IST) is a very recent indirect questioning method derived from the item count technique that seeks to procure more reliable responses on quantitative items than direct questioning while preserving respondents' anonymity. This article addresses two important questions concerning the IST: (i) its implementation when two or more sensitive variables are investigated and efficient estimates of their unknown population means are required; (ii) the determination of the optimal sample size to achieve minimum variance estimates. These aspects are of great relevance for survey practitioners engaged in sensitive research and, to the best of our knowledge, were not studied so far. In this article, theoretical results for multiple estimation and optimal allocation are obtained under a generic sampling design and then particularized to simple random sampling and stratified sampling designs. Theoretical considerations are integrated with a number of simulation studies based on data from two real surveys and conducted to ascertain the efficiency gain derived from optimal allocation in different situations. One of the surveys concerns cannabis consumption among university students. Our findings highlight some methodological advances that can be obtained in life sciences IST surveys when optimal allocation is achieved. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.

PubMed

duVerle, David A; Yotsukura, Sohiya; Nomura, Seitaro; Aburatani, Hiroyuki; Tsuda, Koji

2016-09-13

Single-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths. Here we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biological insights. With cellTree, we provide experimentalists with an easy-to-use tool, based on statistically and biologically-sound algorithms, to efficiently explore and visualise single-cell RNA data. The cellTree package is publicly available in the online Bionconductor repository at: http://bioconductor.org/packages/cellTree/ .

A statistical approach to combining multisource information in one-class classifiers

DOE PAGES

Simonson, Katherine M.; Derek West, R.; Hansen, Ross L.; ...

2017-06-08

A new method is introduced in this paper for combining information from multiple sources to support one-class classification. The contributing sources may represent measurements taken by different sensors of the same physical entity, repeated measurements by a single sensor, or numerous features computed from a single measured image or signal. The approach utilizes the theory of statistical hypothesis testing, and applies Fisher's technique for combining p-values, modified to handle nonindependent sources. Classifier outputs take the form of fused p-values, which may be used to gauge the consistency of unknown entities with one or more class hypotheses. The approach enables rigorousmore » assessment of classification uncertainties, and allows for traceability of classifier decisions back to the constituent sources, both of which are important for high-consequence decision support. Application of the technique is illustrated in two challenge problems, one for skin segmentation and the other for terrain labeling. Finally, the method is seen to be particularly effective for relatively small training samples.« less

A statistical approach to combining multisource information in one-class classifiers

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

Simonson, Katherine M.; Derek West, R.; Hansen, Ross L.

A new method is introduced in this paper for combining information from multiple sources to support one-class classification. The contributing sources may represent measurements taken by different sensors of the same physical entity, repeated measurements by a single sensor, or numerous features computed from a single measured image or signal. The approach utilizes the theory of statistical hypothesis testing, and applies Fisher's technique for combining p-values, modified to handle nonindependent sources. Classifier outputs take the form of fused p-values, which may be used to gauge the consistency of unknown entities with one or more class hypotheses. The approach enables rigorousmore » assessment of classification uncertainties, and allows for traceability of classifier decisions back to the constituent sources, both of which are important for high-consequence decision support. Application of the technique is illustrated in two challenge problems, one for skin segmentation and the other for terrain labeling. Finally, the method is seen to be particularly effective for relatively small training samples.« less

Learning planar Ising models

DOE PAGES

Johnson, Jason K.; Oyen, Diane Adele; Chertkov, Michael; ...

2016-12-01

Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the bestmore » planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.« less

Learning planar Ising models

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

Johnson, Jason K.; Oyen, Diane Adele; Chertkov, Michael

Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the bestmore » planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.« less

Gaussian process regression for sensor networks under localization uncertainty

USGS Publications Warehouse

Jadaliha, M.; Xu, Yunfei; Choi, Jongeun; Johnson, N.S.; Li, Weiming

2013-01-01

In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.

Practical no-gold-standard evaluation framework for quantitative imaging methods: application to lesion segmentation in positron emission tomography

PubMed Central

Jha, Abhinav K.; Mena, Esther; Caffo, Brian; Ashrafinia, Saeed; Rahmim, Arman; Frey, Eric; Subramaniam, Rathan M.

2017-01-01

Abstract. Recently, a class of no-gold-standard (NGS) techniques have been proposed to evaluate quantitative imaging methods using patient data. These techniques provide figures of merit (FoMs) quantifying the precision of the estimated quantitative value without requiring repeated measurements and without requiring a gold standard. However, applying these techniques to patient data presents several practical difficulties including assessing the underlying assumptions, accounting for patient-sampling-related uncertainty, and assessing the reliability of the estimated FoMs. To address these issues, we propose statistical tests that provide confidence in the underlying assumptions and in the reliability of the estimated FoMs. Furthermore, the NGS technique is integrated within a bootstrap-based methodology to account for patient-sampling-related uncertainty. The developed NGS framework was applied to evaluate four methods for segmenting lesions from F-Fluoro-2-deoxyglucose positron emission tomography images of patients with head-and-neck cancer on the task of precisely measuring the metabolic tumor volume. The NGS technique consistently predicted the same segmentation method as the most precise method. The proposed framework provided confidence in these results, even when gold-standard data were not available. The bootstrap-based methodology indicated improved performance of the NGS technique with larger numbers of patient studies, as was expected, and yielded consistent results as long as data from more than 80 lesions were available for the analysis. PMID:28331883

Large ensemble modeling of the last deglacial retreat of the West Antarctic Ice Sheet: comparison of simple and advanced statistical techniques

NASA Astrophysics Data System (ADS)

Pollard, David; Chang, Won; Haran, Murali; Applegate, Patrick; DeConto, Robert

2016-05-01

A 3-D hybrid ice-sheet model is applied to the last deglacial retreat of the West Antarctic Ice Sheet over the last ˜ 20 000 yr. A large ensemble of 625 model runs is used to calibrate the model to modern and geologic data, including reconstructed grounding lines, relative sea-level records, elevation-age data and uplift rates, with an aggregate score computed for each run that measures overall model-data misfit. Two types of statistical methods are used to analyze the large-ensemble results: simple averaging weighted by the aggregate score, and more advanced Bayesian techniques involving Gaussian process-based emulation and calibration, and Markov chain Monte Carlo. The analyses provide sea-level-rise envelopes with well-defined parametric uncertainty bounds, but the simple averaging method only provides robust results with full-factorial parameter sampling in the large ensemble. Results for best-fit parameter ranges and envelopes of equivalent sea-level rise with the simple averaging method agree well with the more advanced techniques. Best-fit parameter ranges confirm earlier values expected from prior model tuning, including large basal sliding coefficients on modern ocean beds.

Estimation of plant sampling uncertainty: an example based on chemical analysis of moss samples.

PubMed

Dołęgowska, Sabina

2016-11-01

In order to estimate the level of uncertainty arising from sampling, 54 samples (primary and duplicate) of the moss species Pleurozium schreberi (Brid.) Mitt. were collected within three forested areas (Wierna Rzeka, Piaski, Posłowice Range) in the Holy Cross Mountains (south-central Poland). During the fieldwork, each primary sample composed of 8 to 10 increments (subsamples) was taken over an area of 10 m 2 whereas duplicate samples were collected in the same way at a distance of 1-2 m. Subsequently, all samples were triple rinsed with deionized water, dried, milled, and digested (8 mL HNO 3 (1:1) + 1 mL 30 % H 2 O 2 ) in a closed microwave system Multiwave 3000. The prepared solutions were analyzed twice for Cu, Fe, Mn, and Zn using FAAS and GFAAS techniques. All datasets were checked for normality and for normally distributed elements (Cu from Piaski, Zn from Posłowice, Fe, Zn from Wierna Rzeka). The sampling uncertainty was computed with (i) classical ANOVA, (ii) classical RANOVA, (iii) modified RANOVA, and (iv) range statistics. For the remaining elements, the sampling uncertainty was calculated with traditional and/or modified RANOVA (if the amount of outliers did not exceed 10 %) or classical ANOVA after Box-Cox transformation (if the amount of outliers exceeded 10 %). The highest concentrations of all elements were found in moss samples from Piaski, whereas the sampling uncertainty calculated with different statistical methods ranged from 4.1 to 22 %.

Assessing the independent contribution of maternal educational expectations to children's educational attainment in early adulthood: a propensity score matching analysis.

PubMed

Pingault, Jean Baptiste; Côté, Sylvana M; Petitclerc, Amélie; Vitaro, Frank; Tremblay, Richard E

2015-01-01

Parental educational expectations have been associated with children's educational attainment in a number of long-term longitudinal studies, but whether this relationship is causal has long been debated. The aims of this prospective study were twofold: 1) test whether low maternal educational expectations contributed to failure to graduate from high school; and 2) compare the results obtained using different strategies for accounting for confounding variables (i.e. multivariate regression and propensity score matching). The study sample included 1,279 participants from the Quebec Longitudinal Study of Kindergarten Children. Maternal educational expectations were assessed when the participants were aged 12 years. High school graduation—measuring educational attainment—was determined through the Quebec Ministry of Education when the participants were aged 22-23 years. Findings show that when using the most common statistical approach (i.e. multivariate regressions to adjust for a restricted set of potential confounders) the contribution of low maternal educational expectations to failure to graduate from high school was statistically significant. However, when using propensity score matching, the contribution of maternal expectations was reduced and remained statistically significant only for males. The results of this study are consistent with the possibility that the contribution of parental expectations to educational attainment is overestimated in the available literature. This may be explained by the use of a restricted range of potential confounding variables as well as the dearth of studies using appropriate statistical techniques and study designs in order to minimize confounding. Each of these techniques and designs, including propensity score matching, has its strengths and limitations: A more comprehensive understanding of the causal role of parental expectations will stem from a convergence of findings from studies using different techniques and designs.

The application of compressed sensing to long-term acoustic emission-based structural health monitoring

NASA Astrophysics Data System (ADS)

Cattaneo, Alessandro; Park, Gyuhae; Farrar, Charles; Mascareñas, David

2012-04-01

The acoustic emission (AE) phenomena generated by a rapid release in the internal stress of a material represent a promising technique for structural health monitoring (SHM) applications. AE events typically result in a discrete number of short-time, transient signals. The challenge associated with capturing these events using classical techniques is that very high sampling rates must be used over extended periods of time. The result is that a very large amount of data is collected to capture a phenomenon that rarely occurs. Furthermore, the high energy consumption associated with the required high sampling rates makes the implementation of high-endurance, low-power, embedded AE sensor nodes difficult to achieve. The relatively rare occurrence of AE events over long time scales implies that these measurements are inherently sparse in the spike domain. The sparse nature of AE measurements makes them an attractive candidate for the application of compressed sampling techniques. Collecting compressed measurements of sparse AE signals will relax the requirements on the sampling rate and memory demands. The focus of this work is to investigate the suitability of compressed sensing techniques for AE-based SHM. The work explores estimating AE signal statistics in the compressed domain for low-power classification applications. In the event compressed classification finds an event of interest, ι1 norm minimization will be used to reconstruct the measurement for further analysis. The impact of structured noise on compressive measurements is specifically addressed. The suitability of a particular algorithm, called Justice Pursuit, to increase robustness to a small amount of arbitrary measurement corruption is investigated.

Effect of Instrumentation Techniques and Preparation Taper on Apical Extrusion of Bacteria.

PubMed

Aksel, Hacer; Küçükkaya Eren, Selen; Çakar, Aslı; Serper, Ahmet; Özkuyumcu, Cumhur; Azim, Adham A

2017-06-01

The aim of this in vitro study was to evaluate the effects of different root canal instrumentation techniques and preparation tapers on the amount of apically extruded bacteria. The root canals of 98 extracted human mandibular incisors were contaminated with Enterococcus faecalis suspension. After incubation at 37°C for 24 hours, the root canals were instrumented with K3 rotary files in a crown-down (CD) or full-length linear instrumentation technique (FL) by using 3 different root canal tapers (0.02, 0.04, and 0.06). During instrumentation, apically extruded bacteria were collected into vials containing saline solution. The microbiological samples were taken from the vials and incubated in brain-heart agar medium for 24 hours, and the numbers of colony-forming units (CFUs) were determined. The obtained results were analyzed with t test and one-way analysis of variance for the comparisons between the instrumentation techniques (CD and FL) and the preparation tapers (0.02, 0.04, and 0.06), respectively. Tukey honestly significant difference test was used for pairwise comparisons. The preparation taper had no effect on the number of CFUs when a FL instrumentation technique was used (P > .05). There was a statistically significant difference in the CFUs between FL and CD techniques when the preparation taper was 0.02 (P < .05). There was no statistically significant difference between the 0.04 and 0.06 preparation tapers in any of the instrumentation techniques (P > .05). Using a 0.02 taper in a CD manner results in the least amount of bacterial extrusion. The instrumentation technique did not seem to affect the amount of bacterial extrusion when 0.04 and 0.06 taper instruments were used for cleaning and shaping the root canal space. Published by Elsevier Inc.

Multiple Point Statistics algorithm based on direct sampling and multi-resolution images

NASA Astrophysics Data System (ADS)

Julien, S.; Renard, P.; Chugunova, T.

2017-12-01

Multiple Point Statistics (MPS) has become popular for more than one decade in Earth Sciences, because these methods allow to generate random fields reproducing highly complex spatial features given in a conceptual model, the training image, while classical geostatistics techniques based on bi-point statistics (covariance or variogram) fail to generate realistic models. Among MPS methods, the direct sampling consists in borrowing patterns from the training image to populate a simulation grid. This latter is sequentially filled by visiting each of these nodes in a random order, and then the patterns, whose the number of nodes is fixed, become narrower during the simulation process, as the simulation grid is more densely informed. Hence, large scale structures are caught in the beginning of the simulation and small scale ones in the end. However, MPS may mix spatial characteristics distinguishable at different scales in the training image, and then loose the spatial arrangement of different structures. To overcome this limitation, we propose to perform MPS simulation using a decomposition of the training image in a set of images at multiple resolutions. Applying a Gaussian kernel onto the training image (convolution) results in a lower resolution image, and iterating this process, a pyramid of images depicting fewer details at each level is built, as it can be done in image processing for example to lighten the space storage of a photography. The direct sampling is then employed to simulate the lowest resolution level, and then to simulate each level, up to the finest resolution, conditioned to the level one rank coarser. This scheme helps reproduce the spatial structures at any scale of the training image and then generate more realistic models. We illustrate the method with aerial photographies (satellite images) and natural textures. Indeed, these kinds of images often display typical structures at different scales and are well-suited for MPS simulation techniques.

Towards an automatic wind speed and direction profiler for Wide Field adaptive optics systems

NASA Astrophysics Data System (ADS)

Sivo, G.; Turchi, A.; Masciadri, E.; Guesalaga, A.; Neichel, B.

2018-05-01

Wide Field Adaptive Optics (WFAO) systems are among the most sophisticated adaptive optics (AO) systems available today on large telescopes. Knowledge of the vertical spatio-temporal distribution of wind speed (WS) and direction (WD) is fundamental to optimize the performance of such systems. Previous studies already proved that the Gemini Multi-Conjugated AO system (GeMS) is able to retrieve measurements of the WS and WD stratification using the SLOpe Detection And Ranging (SLODAR) technique and to store measurements in the telemetry data. In order to assess the reliability of these estimates and of the SLODAR technique applied to such complex AO systems, in this study we compared WS and WD values retrieved from GeMS with those obtained with the atmospheric model Meso-NH on a rich statistical sample of nights. It has previously been proved that the latter technique provided excellent agreement with a large sample of radiosoundings, both in statistical terms and on individual flights. It can be considered, therefore, as an independent reference. The excellent agreement between GeMS measurements and the model that we find in this study proves the robustness of the SLODAR approach. To bypass the complex procedures necessary to achieve automatic measurements of the wind with GeMS, we propose a simple automatic method to monitor nightly WS and WD using Meso-NH model estimates. Such a method can be applied to whatever present or new-generation facilities are supported by WFAO systems. The interest of this study is, therefore, well beyond the optimization of GeMS performance.

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

The plpdfa software is a product of an LDRD project at LLNL entitked "Adaptive Sampling for Very High Throughput Data Streams" (tracking number 11-ERD-035). This software was developed by a graduate student summer intern, Chris Challis, who worked under project PI Dan Merl furing the summer of 2011. The software the source code is implementing is a statistical analysis technique for clustering and classification of text-valued data. The method had been previously published by the PI in the open literature.

A statistical evaluation of non-ergodic variogram estimators

USGS Publications Warehouse

Curriero, F.C.; Hohn, M.E.; Liebhold, A.M.; Lele, S.R.

2002-01-01

Geostatistics is a set of statistical techniques that is increasingly used to characterize spatial dependence in spatially referenced ecological data. A common feature of geostatistics is predicting values at unsampled locations from nearby samples using the kriging algorithm. Modeling spatial dependence in sampled data is necessary before kriging and is usually accomplished with the variogram and its traditional estimator. Other types of estimators, known as non-ergodic estimators, have been used in ecological applications. Non-ergodic estimators were originally suggested as a method of choice when sampled data are preferentially located and exhibit a skewed frequency distribution. Preferentially located samples can occur, for example, when areas with high values are sampled more intensely than other areas. In earlier studies the visual appearance of variograms from traditional and non-ergodic estimators were compared. Here we evaluate the estimators' relative performance in prediction. We also show algebraically that a non-ergodic version of the variogram is equivalent to the traditional variogram estimator. Simulations, designed to investigate the effects of data skewness and preferential sampling on variogram estimation and kriging, showed the traditional variogram estimator outperforms the non-ergodic estimators under these conditions. We also analyzed data on carabid beetle abundance, which exhibited large-scale spatial variability (trend) and a skewed frequency distribution. Detrending data followed by robust estimation of the residual variogram is demonstrated to be a successful alternative to the non-ergodic approach.

The Characterization of Biosignatures in Caves Using an Instrument Suite

NASA Astrophysics Data System (ADS)

Uckert, Kyle; Chanover, Nancy J.; Getty, Stephanie; Voelz, David G.; Brinckerhoff, William B.; McMillan, Nancy; Xiao, Xifeng; Boston, Penelope J.; Li, Xiang; McAdam, Amy; Glenar, David A.; Chavez, Arriana

2017-12-01

The search for life and habitable environments on other Solar System bodies is a major motivator for planetary exploration. Due to the difficulty and significance of detecting extant or extinct extraterrestrial life in situ, several independent measurements from multiple instrument techniques will bolster the community's confidence in making any such claim. We demonstrate the detection of subsurface biosignatures using a suite of instrument techniques including IR reflectance spectroscopy, laser-induced breakdown spectroscopy, and scanning electron microscopy/energy dispersive X-ray spectroscopy. We focus our measurements on subterranean calcium carbonate field samples, whose biosignatures are analogous to those that might be expected on some high-interest astrobiology targets. In this work, we discuss the feasibility and advantages of using each of the aforementioned instrument techniques for the in situ search for biosignatures and present results on the autonomous characterization of biosignatures using multivariate statistical analysis techniques.

The Characterization of Biosignatures in Caves Using an Instrument Suite.

PubMed

Uckert, Kyle; Chanover, Nancy J; Getty, Stephanie; Voelz, David G; Brinckerhoff, William B; McMillan, Nancy; Xiao, Xifeng; Boston, Penelope J; Li, Xiang; McAdam, Amy; Glenar, David A; Chavez, Arriana

2017-12-01

The search for life and habitable environments on other Solar System bodies is a major motivator for planetary exploration. Due to the difficulty and significance of detecting extant or extinct extraterrestrial life in situ, several independent measurements from multiple instrument techniques will bolster the community's confidence in making any such claim. We demonstrate the detection of subsurface biosignatures using a suite of instrument techniques including IR reflectance spectroscopy, laser-induced breakdown spectroscopy, and scanning electron microscopy/energy dispersive X-ray spectroscopy. We focus our measurements on subterranean calcium carbonate field samples, whose biosignatures are analogous to those that might be expected on some high-interest astrobiology targets. In this work, we discuss the feasibility and advantages of using each of the aforementioned instrument techniques for the in situ search for biosignatures and present results on the autonomous characterization of biosignatures using multivariate statistical analysis techniques. Key Words: Biosignature suites-Caves-Mars-Life detection. Astrobiology 17, 1203-1218.

Hydrogeochemistry and water quality of the Kordkandi-Duzduzan plain, NW Iran: application of multivariate statistical analysis and PoS index.

PubMed

Soltani, Shahla; Asghari Moghaddam, Asghar; Barzegar, Rahim; Kazemian, Naeimeh; Tziritis, Evangelos

2017-08-18

Kordkandi-Duzduzan plain is one of the fertile plains of East Azarbaijan Province, NW of Iran. Groundwater is an important resource for drinking and agricultural purposes due to the lack of surface water resources in the region. The main objectives of the present study are to identify the hydrogeochemical processes and the potential sources of major, minor, and trace metals and metalloids such as Cr, Mn, Cd, Fe, Al, and As by using joint hydrogeochemical techniques and multivariate statistical analysis and to evaluate groundwater quality deterioration with the use of PoS environmental index. To achieve these objectives, 23 groundwater samples were collected in September 2015. Piper diagram shows that the mixed Ca-Mg-Cl is the dominant groundwater type, and some of the samples have Ca-HCO 3 , Ca-Cl, and Na-Cl types. Multivariate statistical analyses indicate that weathering and dissolution of different rocks and minerals, e.g., silicates, gypsum, and halite, ion exchange, and agricultural activities influence the hydrogeochemistry of the study area. The cluster analysis divides the samples into two distinct clusters which are completely different in EC (and its dependent variables such as Na + , K + , Ca 2+ , Mg 2+ , SO 4 2- , and Cl - ), Cd, and Cr variables according to the ANOVA statistical test. Based on the median values, the concentrations of pH, NO 3 - , SiO 2 , and As in cluster 1 are elevated compared with those of cluster 2, while their maximum values occur in cluster 2. According to the PoS index, the dominant parameter that controls quality deterioration is As, with 60% of contribution. Samples of lowest PoS values are located in the southern and northern parts (recharge area) while samples of the highest values are located in the discharge area and the eastern part.

Statistical methods for investigating quiescence and other temporal seismicity patterns

USGS Publications Warehouse

Matthews, M.V.; Reasenberg, P.A.

1988-01-01

We propose a statistical model and a technique for objective recognition of one of the most commonly cited seismicity patterns:microearthquake quiescence. We use a Poisson process model for seismicity and define a process with quiescence as one with a particular type of piece-wise constant intensity function. From this model, we derive a statistic for testing stationarity against a 'quiescence' alternative. The large-sample null distribution of this statistic is approximated from simulated distributions of appropriate functionals applied to Brownian bridge processes. We point out the restrictiveness of the particular model we propose and of the quiescence idea in general. The fact that there are many point processes which have neither constant nor quiescent rate functions underscores the need to test for and describe nonuniformity thoroughly. We advocate the use of the quiescence test in conjunction with various other tests for nonuniformity and with graphical methods such as density estimation. ideally these methods may promote accurate description of temporal seismicity distributions and useful characterizations of interesting patterns. ?? 1988 Birkha??user Verlag.

Kappa statistic for clustered matched-pair data.

PubMed

Yang, Zhao; Zhou, Ming

2014-07-10

Kappa statistic is widely used to assess the agreement between two procedures in the independent matched-pair data. For matched-pair data collected in clusters, on the basis of the delta method and sampling techniques, we propose a nonparametric variance estimator for the kappa statistic without within-cluster correlation structure or distributional assumptions. The results of an extensive Monte Carlo simulation study demonstrate that the proposed kappa statistic provides consistent estimation and the proposed variance estimator behaves reasonably well for at least a moderately large number of clusters (e.g., K ≥50). Compared with the variance estimator ignoring dependence within a cluster, the proposed variance estimator performs better in maintaining the nominal coverage probability when the intra-cluster correlation is fair (ρ ≥0.3), with more pronounced improvement when ρ is further increased. To illustrate the practical application of the proposed estimator, we analyze two real data examples of clustered matched-pair data. Copyright © 2014 John Wiley & Sons, Ltd.

Nevada Applied Ecology Group procedures handbook for environmental transuranics

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

White, M.G.; Dunaway, P.B.

The activities of the Nevada Applied Ecology Group (NAEG) integrated research studies of environmental plutonium and other transuranics at the Nevada Test Site have required many standardized field and laboratory procedures. These include sampling techniques, collection and preparation, radiochemical and wet chemistry analysis, data bank storage and reporting, and statistical considerations for environmental samples of soil, vegetation, resuspended particles, animals, and others. This document, printed in two volumes, includes most of the Nevada Applied Ecology Group standard procedures, with explanations as to the specific applications involved in the environmental studies. Where there is more than one document concerning a procedure,more » it has been included to indicate special studies or applications perhaps more complex than the routine standard sampling procedures utilized.« less

Nevada Applied Ecology Group procedures handbook for environmental transuranics

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

White, M.G.; Dunaway, P.B.

The activities of the Nevada Applied Ecology Group (NAEG) integrated research studies of environmental plutonium and other transuranics at the Nevada Test Site have required many standardized field and laboratory procedures. These include sampling techniques, collection and preparation, radiochemical and wet chemistry analysis, data bank storage and reporting, and statistical considerations for environmental samples of soil, vegetation, resuspended particles, animals, and other biological material. This document, printed in two volumes, includes most of the Nevada Applied Ecology Group standard procedures, with explanations as to the specific applications involved in the environmental studies. Where there is more than one document concerningmore » a procedure, it has been included to indicate special studies or applications more complex than the routine standard sampling procedures utilized.« less

Potential, velocity, and density fields from sparse and noisy redshift-distance samples - Method

NASA Technical Reports Server (NTRS)

Dekel, Avishai; Bertschinger, Edmund; Faber, Sandra M.

1990-01-01

A method for recovering the three-dimensional potential, velocity, and density fields from large-scale redshift-distance samples is described. Galaxies are taken as tracers of the velocity field, not of the mass. The density field and the initial conditions are calculated using an iterative procedure that applies the no-vorticity assumption at an initial time and uses the Zel'dovich approximation to relate initial and final positions of particles on a grid. The method is tested using a cosmological N-body simulation 'observed' at the positions of real galaxies in a redshift-distance sample, taking into account their distance measurement errors. Malmquist bias and other systematic and statistical errors are extensively explored using both analytical techniques and Monte Carlo simulations.

Structural parameters of young star clusters: fractal analysis

NASA Astrophysics Data System (ADS)

Hetem, A.

2017-07-01

A unified view of star formation in the Universe demand detailed and in-depth studies of young star clusters. This work is related to our previous study of fractal statistics estimated for a sample of young stellar clusters (Gregorio-Hetem et al. 2015, MNRAS 448, 2504). The structural properties can lead to significant conclusions about the early stages of cluster formation: 1) virial conditions can be used to distinguish warm collapsed; 2) bound or unbound behaviour can lead to conclusions about expansion; and 3) fractal statistics are correlated to the dynamical evolution and age. The technique of error bars estimation most used in the literature is to adopt inferential methods (like bootstrap) to estimate deviation and variance, which are valid only for an artificially generated cluster. In this paper, we expanded the number of studied clusters, in order to enhance the investigation of the cluster properties and dynamic evolution. The structural parameters were compared with fractal statistics and reveal that the clusters radial density profile show a tendency of the mean separation of the stars increase with the average surface density. The sample can be divided into two groups showing different dynamic behaviour, but they have the same dynamic evolution, since the entire sample was revealed as being expanding objects, for which the substructures do not seem to have been completely erased. These results are in agreement with the simulations adopting low surface densities and supervirial conditions.

An information-theoretic approach to the modeling and analysis of whole-genome bisulfite sequencing data.

PubMed

Jenkinson, Garrett; Abante, Jordi; Feinberg, Andrew P; Goutsias, John

2018-03-07

DNA methylation is a stable form of epigenetic memory used by cells to control gene expression. Whole genome bisulfite sequencing (WGBS) has emerged as a gold-standard experimental technique for studying DNA methylation by producing high resolution genome-wide methylation profiles. Statistical modeling and analysis is employed to computationally extract and quantify information from these profiles in an effort to identify regions of the genome that demonstrate crucial or aberrant epigenetic behavior. However, the performance of most currently available methods for methylation analysis is hampered by their inability to directly account for statistical dependencies between neighboring methylation sites, thus ignoring significant information available in WGBS reads. We present a powerful information-theoretic approach for genome-wide modeling and analysis of WGBS data based on the 1D Ising model of statistical physics. This approach takes into account correlations in methylation by utilizing a joint probability model that encapsulates all information available in WGBS methylation reads and produces accurate results even when applied on single WGBS samples with low coverage. Using the Shannon entropy, our approach provides a rigorous quantification of methylation stochasticity in individual WGBS samples genome-wide. Furthermore, it utilizes the Jensen-Shannon distance to evaluate differences in methylation distributions between a test and a reference sample. Differential performance assessment using simulated and real human lung normal/cancer data demonstrate a clear superiority of our approach over DSS, a recently proposed method for WGBS data analysis. Critically, these results demonstrate that marginal methods become statistically invalid when correlations are present in the data. This contribution demonstrates clear benefits and the necessity of modeling joint probability distributions of methylation using the 1D Ising model of statistical physics and of quantifying methylation stochasticity using concepts from information theory. By employing this methodology, substantial improvement of DNA methylation analysis can be achieved by effectively taking into account the massive amount of statistical information available in WGBS data, which is largely ignored by existing methods.

Evaluation of statistical treatments of left-censored environmental data using coincident uncensored data sets: I. Summary statistics

USGS Publications Warehouse

Antweiler, Ronald C.; Taylor, Howard E.

2008-01-01

The main classes of statistical treatment of below-detection limit (left-censored) environmental data for the determination of basic statistics that have been used in the literature are substitution methods, maximum likelihood, regression on order statistics (ROS), and nonparametric techniques. These treatments, along with using all instrument-generated data (even those below detection), were evaluated by examining data sets in which the true values of the censored data were known. It was found that for data sets with less than 70% censored data, the best technique overall for determination of summary statistics was the nonparametric Kaplan-Meier technique. ROS and the two substitution methods of assigning one-half the detection limit value to censored data or assigning a random number between zero and the detection limit to censored data were adequate alternatives. The use of these two substitution methods, however, requires a thorough understanding of how the laboratory censored the data. The technique of employing all instrument-generated data - including numbers below the detection limit - was found to be less adequate than the above techniques. At high degrees of censoring (greater than 70% censored data), no technique provided good estimates of summary statistics. Maximum likelihood techniques were found to be far inferior to all other treatments except substituting zero or the detection limit value to censored data.

Time-reversal imaging for classification of submerged elastic targets via Gibbs sampling and the Relevance Vector Machine.

PubMed

Dasgupta, Nilanjan; Carin, Lawrence

2005-04-01

Time-reversal imaging (TRI) is analogous to matched-field processing, although TRI is typically very wideband and is appropriate for subsequent target classification (in addition to localization). Time-reversal techniques, as applied to acoustic target classification, are highly sensitive to channel mismatch. Hence, it is crucial to estimate the channel parameters before time-reversal imaging is performed. The channel-parameter statistics are estimated here by applying a geoacoustic inversion technique based on Gibbs sampling. The maximum a posteriori (MAP) estimate of the channel parameters are then used to perform time-reversal imaging. Time-reversal implementation requires a fast forward model, implemented here by a normal-mode framework. In addition to imaging, extraction of features from the time-reversed images is explored, with these applied to subsequent target classification. The classification of time-reversed signatures is performed by the relevance vector machine (RVM). The efficacy of the technique is analyzed on simulated in-channel data generated by a free-field finite element method (FEM) code, in conjunction with a channel propagation model, wherein the final classification performance is demonstrated to be relatively insensitive to the associated channel parameters. The underlying theory of Gibbs sampling and TRI are presented along with the feature extraction and target classification via the RVM.

Design of partially supervised classifiers for multispectral image data

NASA Technical Reports Server (NTRS)

Jeon, Byeungwoo; Landgrebe, David

1993-01-01

A partially supervised classification problem is addressed, especially when the class definition and corresponding training samples are provided a priori only for just one particular class. In practical applications of pattern classification techniques, a frequently observed characteristic is the heavy, often nearly impossible requirements on representative prior statistical class characteristics of all classes in a given data set. Considering the effort in both time and man-power required to have a well-defined, exhaustive list of classes with a corresponding representative set of training samples, this 'partially' supervised capability would be very desirable, assuming adequate classifier performance can be obtained. Two different classification algorithms are developed to achieve simplicity in classifier design by reducing the requirement of prior statistical information without sacrificing significant classifying capability. The first one is based on optimal significance testing, where the optimal acceptance probability is estimated directly from the data set. In the second approach, the partially supervised classification is considered as a problem of unsupervised clustering with initially one known cluster or class. A weighted unsupervised clustering procedure is developed to automatically define other classes and estimate their class statistics. The operational simplicity thus realized should make these partially supervised classification schemes very viable tools in pattern classification.

Method matters: Experimental evidence for shorter avian sperm in faecal compared to abdominal massage samples

PubMed Central

Cockburn, Glenn; Sánchez-Tójar, Alfredo; Løvlie, Hanne; Schroeder, Julia

2017-01-01

Birds are model organisms in sperm biology. Previous work in zebra finches, suggested that sperm sampled from males' faeces and ejaculates do not differ in size. Here, we tested this assumption in a captive population of house sparrows, Passer domesticus. We compared sperm length in samples from three collection techniques: female dummy, faecal and abdominal massage samples. We found that sperm were significantly shorter in faecal than abdominal massage samples, which was explained by shorter heads and midpieces, but not flagella. This result might indicate that faecal sampled sperm could be less mature than sperm collected by abdominal massage. The female dummy method resulted in an insufficient number of experimental ejaculates because most males ignored it. In light of these results, we recommend using abdominal massage as a preferred method for avian sperm sampling. Where avian sperm cannot be collected by abdominal massage alone, we advise controlling for sperm sampling protocol statistically. PMID:28813481

Quality of stormwater runoff discharged from Massachusetts highways, 2005-07

USGS Publications Warehouse

Smith, Kirk P.; Granato, Gregory E.

2010-01-01

The U.S. Geological Survey (USGS), in cooperation with U.S. Department of Transportation Federal Highway Administration and the Massachusetts Department of Transportation, conducted a field study from September 2005 through September 2007 to characterize the quality of highway runoff for a wide range of constituents. The highways studied had annual average daily traffic (AADT) volumes from about 3,000 to more than 190,000 vehicles per day. Highway-monitoring stations were installed at 12 locations in Massachusetts on 8 highways. The 12 monitoring stations were subdivided into 4 primary, 4 secondary, and 4 test stations. Each site contained a 100-percent impervious drainage area that included two or more catch basins sharing a common outflow pipe. Paired primary and secondary stations were located within a few miles of each other on a limited-access section of the same highway. Most of the data were collected at the primary and secondary stations, which were located on four principal highways (Route 119, Route 2, Interstate 495, and Interstate 95). The secondary stations were operated simultaneously with the primary stations for at least a year. Data from the four test stations (Route 8, Interstate 195, Interstate 190, and Interstate 93) were used to determine the transferability of the data collected from the principal highways to other highways characterized by different construction techniques, land use, and geography. Automatic-monitoring techniques were used to collect composite samples of highway runoff and make continuous measurements of several physical characteristics. Flowweighted samples of highway runoff were collected automatically during approximately 140 rain and mixed rain, sleet, and snowstorms. These samples were analyzed for physical characteristics and concentrations of 6 dissolved major ions, total nutrients, 8 total-recoverable metals, suspended sediment, and 85 semivolatile organic compounds (SVOCs), which include priority polyaromatic hydrocarbons (PAHs), phthalate esters, and other anthropogenic or naturally occurring organic compounds. The distribution of particle size of suspended sediment also was determined for composite samples of highway runoff. Samples of highway runoff were collected year round and under various dry antecedent conditions throughout the 2-year sampling period. In addition to samples of highway runoff, supplemental samples also were collected of sediment in highway runoff, background soils, berm materials, maintenance sands, deicing compounds, and vegetation matter. These additional samples were collected near or on the highways to support data analysis. There were few statistically significant differences between populations of constituent concentrations in samples from the primary and secondary stations on the same principal highways (Mann-Whitney test, 95-percent confidence level). Similarly, there were few statistically significant differences between populations of constituent concentrations for the four principal highways (data from the paired primary and secondary stations for each principal highway) and populations for test stations with similar AADT volumes. Exceptions to this include several total-recoverable metals for stations on Route 2 and Interstate 195 (highways with moderate AADT volumes), and for stations on Interstate 95 and Interstate 93 (highways with high AADT volumes). Supplemental data collected during this study indicate that many of these differences may be explained by the quantity, as well as the quality, of the sediment in samples of highway runoff. Nonparametric statistical methods also were used to test for differences between populations of sample constituent concentrations among the four principal highways that differed mainly in traffic volume. These results indicate that there were few statistically significant differences (Mann-Whitney test, 95-percent confidence level) for populations of concentrations of most total-recoverable metals

Correlations of fatty acid supplementation, aeroallergens, shampoo, and ear cleanser with multiple parameters in pruritic dogs.

PubMed

Nesbitt, Gene H; Freeman, Lisa M; Hannah, Steven S

2004-01-01

Seventy-two pruritic dogs were fed one of four diets controlled for n-6:n-3 fatty acid ratios and total dietary intake of fatty acids. Multiple parameters were evaluated, including clinical and cytological findings, aeroallergen testing, microbial sampling techniques, and effects of an anti-fungal/antibacterial shampoo and ear cleanser. Significant correlations were observed between many clinical parameters, anatomical sampling sites, and microbial counts when data from the diet groups was combined. There were no statistically significant differences between individual diets for any of the clinical parameters. The importance of total clinical management in the control of pruritus was demonstrated.

Comparison of two sperm processing techniques for low complexity assisted fertilization: sperm washing followed by swim-up and discontinuous density gradient centrifugation.

PubMed

Fácio, Cássio L; Previato, Lígia F; Machado-Paula, Ligiane A; Matheus, Paulo Cs; Araújo, Edilberto

2016-12-01

This study aimed to assess and compare sperm motility, concentration, and morphology recovery rates, before and after processing through sperm washing followed by swim-up or discontinuous density gradient centrifugation in normospermic individuals. Fifty-eight semen samples were used in double intrauterine insemination procedures; 17 samples (group 1) were prepared with sperm washing followed by swim-up, and 41 (group 2) by discontinuous density gradient centrifugation. This prospective non-randomized study assessed seminal parameters before and after semen processing. A dependent t-test was used for the same technique to analyze seminal parameters before and after semen processing; an independent t-test was used to compare the results before and after processing for both techniques. The two techniques produced decreases in sample concentration (sperm washing followed by swim-up: P<0.000006; discontinuous density gradient centrifugation: P=0.008457) and increases in motility and normal morphology sperm rates after processing. The difference in sperm motility between the two techniques was not statistically significant. Sperm washing followed by swim-up had better morphology recovery rates than discontinuous density gradient centrifugation (P=0.0095); and the density gradient group had better concentration recovery rates than the swim-up group (P=0.0027). The two methods successfully recovered the minimum sperm values needed to perform intrauterine insemination. Sperm washing followed by swim-up is indicated for semen with high sperm concentration and better morphology recovery rates. Discontinuous density gradient centrifugation produced improved concentration recovery rates.

CAPSAS: Computer Assisted Program for the Selection of Appropriate Statistics.

ERIC Educational Resources Information Center

Shermis, Mark D.; Albert, Susan L.

A computer-assisted program has been developed for the selection of statistics or statistical techniques by both students and researchers. Based on Andrews, Klem, Davidson, O'Malley and Rodgers "A Guide for Selecting Statistical Techniques for Analyzing Social Science Data," this FORTRAN-compiled interactive computer program was…

Data analysis techniques

NASA Technical Reports Server (NTRS)

Park, Steve

1990-01-01

A large and diverse number of computational techniques are routinely used to process and analyze remotely sensed data. These techniques include: univariate statistics; multivariate statistics; principal component analysis; pattern recognition and classification; other multivariate techniques; geometric correction; registration and resampling; radiometric correction; enhancement; restoration; Fourier analysis; and filtering. Each of these techniques will be considered, in order.

USE OF NATURAL WATERS AS U. S. GEOLOGICAL SURVEY REFERENCE SAMPLES.

USGS Publications Warehouse

Janzer, Victor J.

1985-01-01

The U. S. Geological Survey conducts research and collects hydrologic data relating to the Nation's water resources. Seven types of natural matrix reference water samples are prepared for use in the Survey's quality assurance program. These include samples containing major constituents, trace metals, nutrients, herbicides, insecticides, trace metals in a water and suspended-sediment mixture, and precipitation (snowmelt). To prepare these reference samples, natural water is collected in plastic drums and the sediment is allowed to settle. The water is then filtered, selected constituents are added, and if necessary the water is acidified and sterilized by ultraviolet irradiation before bottling in plastic or glass. These reference samples are distributed twice yearly to more than 100 laboratories for chemical analysis. The most probable values for each constituent are determined by evaluating the data submitted by the laboratories using statistical techniques recommended by ASTM.

Determination of ABO blood grouping and Rhesus factor from tooth material.

PubMed

Kumar, Pooja Vijay; Vanishree, M; Anila, K; Hunasgi, Santosh; Suryadevra, Sri Sujan; Kardalkar, Swetha

2016-01-01

The aim of the study was to determine blood groups and Rhesus factor from dentin and pulp using absorption-elution (AE) technique in different time periods at 0, 3, 6, 9 and 12 months, respectively. A total of 150 cases, 30 patients each at 0, 3, 6, 9 and 12 months were included in the study. The samples consisted of males and females with age ranging 13-60 years. Patient's blood group was checked and was considered as "control." The dentin and pulp of extracted teeth were tested for the presence of ABO/Rh antigen, at respective time periods by AE technique. Data were analyzed in proportion. For comparison, Chi-square test or Fisher's exact test was used for the small sample. Blood group antigens of ABO and Rh factor were detected in dentin and pulp up to 12 months. For both ABO and Rh factor, dentin and pulp showed 100% sensitivity for the samples tested at 0 month and showed a gradual decrease in the sensitivity as time period increased. The sensitivity of pulp was better than dentin for both the blood grouping systems and ABO blood group antigens were better detected than Rh antigens. In dentin and pulp, the antigens of ABO and Rh factor were detected up to 12 months but showed a progressive decrease in the antigenicity as the time period increased. When compared the results obtained of dentin and pulp in ABO and Rh factor grouping showed similar results with no statistical significance. The sensitivity of ABO blood grouping was better than Rh factor blood grouping and showed a statistically significant result.

Reconstruction of three-dimensional porous media using a single thin section

NASA Astrophysics Data System (ADS)

Tahmasebi, Pejman; Sahimi, Muhammad

2012-06-01

The purpose of any reconstruction method is to generate realizations of two- or multiphase disordered media that honor limited data for them, with the hope that the realizations provide accurate predictions for those properties of the media for which there are no data available, or their measurement is difficult. An important example of such stochastic systems is porous media for which the reconstruction technique must accurately represent their morphology—the connectivity and geometry—as well as their flow and transport properties. Many of the current reconstruction methods are based on low-order statistical descriptors that fail to provide accurate information on the properties of heterogeneous porous media. On the other hand, due to the availability of high resolution two-dimensional (2D) images of thin sections of a porous medium, and at the same time, the high cost, computational difficulties, and even unavailability of complete 3D images, the problem of reconstructing porous media from 2D thin sections remains an outstanding unsolved problem. We present a method based on multiple-point statistics in which a single 2D thin section of a porous medium, represented by a digitized image, is used to reconstruct the 3D porous medium to which the thin section belongs. The method utilizes a 1D raster path for inspecting the digitized image, and combines it with a cross-correlation function, a grid splitting technique for deciding the resolution of the computational grid used in the reconstruction, and the Shannon entropy as a measure of the heterogeneity of the porous sample, in order to reconstruct the 3D medium. It also utilizes an adaptive technique for identifying the locations and optimal number of hard (quantitative) data points that one can use in the reconstruction process. The method is tested on high resolution images for Berea sandstone and a carbonate rock sample, and the results are compared with the data. To make the comparison quantitative, two sets of statistical tests consisting of the autocorrelation function, histogram matching of the local coordination numbers, the pore and throat size distributions, multiple-points connectivity, and single- and two-phase flow permeabilities are used. The comparison indicates that the proposed method reproduces the long-range connectivity of the porous media, with the computed properties being in good agreement with the data for both porous samples. The computational efficiency of the method is also demonstrated.

Laser Welding and Syncristallization Techniques Comparison: In Vitro Study

PubMed Central

Fornaini, C.; Merigo, E.; Vescovi, P.; Meleti, M.; Nammour, S.

2012-01-01

Background. Laser welding was first reported in 1967 and for many years it has been used in dental laboratories with several advantages versus the conventional technique. Authors described, in previous works, the possibility of using also chair-side Nd : YAG laser device (Fotona Fidelis III, λ = 1064 nm) for welding metallic parts of prosthetic appliances directly in the dental office, extra- and also intra-orally. Syncristallisation is a soldering technique based on the creation of an electric arc between two electrodes and used to connect implants to bars intra-orally. Aim. The aim of this study was to compare two different laser welding devices with a soldering machine, all of these used in prosthetic dentistry. Material and Methods. In-lab Nd : YAG laser welding (group A = 12 samples), chair-side Nd : YAG laser welding (group B = 12 samples), and electrowelder (group C = 12 samples) were used. The tests were performed on 36 CrCoMo plates and the analysis consisted in evaluation, by microscopic observation, of the number of fissures in welded areas of groups A and B and in measurement of the welding strength in all the groups. The results were statistically analysed by means of one-way ANOVA and Tukey-Kramer multiple comparison tests. Results. The means and standard deviations for the number of fissures in welded areas were 8.12 ± 2.59 for group A and 5.20 ± 1.38 for group B. The difference was statistical significant (P = 0.0023 at the level 95%). On the other hand, the means and standard deviations for the traction tests were 1185.50 ± 288.56 N for group A, 896.41 ± 120.84 N for group B, and 283.58 ± 84.98 N for group C. The difference was statistical significant (P = 0.01 at the level 95%). Conclusion. The joint obtained by welding devices had a significant higher strength compared with that obtained by the electrowelder, and the comparison between the two laser devices used demonstrated that the chair-side Nd : YAG, even giving a lower strength to the joints, produced the lowest number of fissures in the welded area. PMID:22778737

An Independent Filter for Gene Set Testing Based on Spectral Enrichment.

PubMed

Frost, H Robert; Li, Zhigang; Asselbergs, Folkert W; Moore, Jason H

2015-01-01

Gene set testing has become an indispensable tool for the analysis of high-dimensional genomic data. An important motivation for testing gene sets, rather than individual genomic variables, is to improve statistical power by reducing the number of tested hypotheses. Given the dramatic growth in common gene set collections, however, testing is often performed with nearly as many gene sets as underlying genomic variables. To address the challenge to statistical power posed by large gene set collections, we have developed spectral gene set filtering (SGSF), a novel technique for independent filtering of gene set collections prior to gene set testing. The SGSF method uses as a filter statistic the p-value measuring the statistical significance of the association between each gene set and the sample principal components (PCs), taking into account the significance of the associated eigenvalues. Because this filter statistic is independent of standard gene set test statistics under the null hypothesis but dependent under the alternative, the proportion of enriched gene sets is increased without impacting the type I error rate. As shown using simulated and real gene expression data, the SGSF algorithm accurately filters gene sets unrelated to the experimental outcome resulting in significantly increased gene set testing power.

Pointwise probability reinforcements for robust statistical inference.

PubMed

Frénay, Benoît; Verleysen, Michel

2014-02-01

Statistical inference using machine learning techniques may be difficult with small datasets because of abnormally frequent data (AFDs). AFDs are observations that are much more frequent in the training sample that they should be, with respect to their theoretical probability, and include e.g. outliers. Estimates of parameters tend to be biased towards models which support such data. This paper proposes to introduce pointwise probability reinforcements (PPRs): the probability of each observation is reinforced by a PPR and a regularisation allows controlling the amount of reinforcement which compensates for AFDs. The proposed solution is very generic, since it can be used to robustify any statistical inference method which can be formulated as a likelihood maximisation. Experiments show that PPRs can be easily used to tackle regression, classification and projection: models are freed from the influence of outliers. Moreover, outliers can be filtered manually since an abnormality degree is obtained for each observation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Noninformative prior in the quantum statistical model of pure states

NASA Astrophysics Data System (ADS)

Tanaka, Fuyuhiko

2012-06-01

In the present paper, we consider a suitable definition of a noninformative prior on the quantum statistical model of pure states. While the full pure-states model is invariant under unitary rotation and admits the Haar measure, restricted models, which we often see in quantum channel estimation and quantum process tomography, have less symmetry and no compelling rationale for any choice. We adopt a game-theoretic approach that is applicable to classical Bayesian statistics and yields a noninformative prior for a general class of probability distributions. We define the quantum detection game and show that there exist noninformative priors for a general class of a pure-states model. Theoretically, it gives one of the ways that we represent ignorance on the given quantum system with partial information. Practically, our method proposes a default distribution on the model in order to use the Bayesian technique in the quantum-state tomography with a small sample.

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator); Knowlton, D. J.; Dean, M. E.

1981-01-01

A set of training statistics for the 30 meter resolution simulated thematic mapper MSS data was generated based on land use/land cover classes. In addition to this supervised data set, a nonsupervised multicluster block of training statistics is being defined in order to compare the classification results and evaluate the effect of the different training selection methods on classification performance. Two test data sets, defined using a stratified sampling procedure incorporating a grid system with dimensions of 50 lines by 50 columns, and another set based on an analyst supervised set of test fields were used to evaluate the classifications of the TMS data. The supervised training data set generated training statistics, and a per point Gaussian maximum likelihood classification of the 1979 TMS data was obtained. The August 1980 MSS data was radiometrically adjusted. The SAR data was redigitized and the SAR imagery was qualitatively analyzed.

The application of the statistical classifying models for signal evaluation of the gas sensors analyzing mold contamination of the building materials

NASA Astrophysics Data System (ADS)

Majerek, Dariusz; Guz, Łukasz; Suchorab, Zbigniew; Łagód, Grzegorz; Sobczuk, Henryk

2017-07-01

Mold that develops on moistened building barriers is a major cause of the Sick Building Syndrome (SBS). Fungal contamination is normally evaluated using standard biological methods which are time-consuming and require a lot of manual labor. Fungi emit Volatile Organic Compounds (VOC) that can be detected in the indoor air using several techniques of detection e.g. chromatography. VOCs can be also detected using gas sensors arrays. All array sensors generate particular voltage signals that ought to be analyzed using properly selected statistical methods of interpretation. This work is focused on the attempt to apply statistical classifying models in evaluation of signals from gas sensors matrix to analyze the air sampled from the headspace of various types of the building materials at different level of contamination but also clean reference materials.

A New Femtosecond Laser-Based Three-Dimensional Tomography Technique

NASA Astrophysics Data System (ADS)

Echlin, McLean P.

2011-12-01

Tomographic imaging has dramatically changed science, most notably in the fields of medicine and biology, by producing 3D views of structures which are too complex to understand in any other way. Current tomographic techniques require extensive time both for post-processing and data collection. Femtosecond laser based tomographic techniques have been developed in both standard atmosphere (femtosecond laser-based serial sectioning technique - FSLSS) and in vacuum (Tri-Beam System) for the fast collection (10 5mum3/s) of mm3 sized 3D datasets. Both techniques use femtosecond laser pulses to selectively remove layer-by-layer areas of material with low collateral damage and a negligible heat affected zone. To the authors knowledge, femtosecond lasers have never been used to serial section and these techniques have been entirely and uniquely developed by the author and his collaborators at the University of Michigan and University of California Santa Barbara. The FSLSS was applied to measure the 3D distribution of TiN particles in a 4330 steel. Single pulse ablation morphologies and rates were measured and collected from literature. Simultaneous two-phase ablation of TiN and steel matrix was shown to occur at fluences of 0.9-2 J/cm2. Laser scanning protocols were developed minimizing surface roughness to 0.1-0.4 mum for laser-based sectioning. The FSLSS technique was used to section and 3D reconstruct titanium nitride (TiN) containing 4330 steel. Statistical analysis of 3D TiN particle sizes, distribution parameters, and particle density were measured. A methodology was developed to use the 3D datasets to produce statistical volume elements (SVEs) for toughness modeling. Six FSLSS TiN datasets were sub-sampled into 48 SVEs for statistical analysis and toughness modeling using the Rice-Tracey and Garrison-Moody models. A two-parameter Weibull analysis was performed and variability in the toughness data agreed well with Ruggieri et al. bulk toughness measurements. The Tri-Beam system combines the benefits of laser based material removal (speed, low-damage, automated) with detectors that collect chemical, structural, and topological information. Multi-modal sectioning information was collected after many laser scanning passes demonstrating the capability of the Tri-Beam system.

Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant.

PubMed

Zamani, Abbas Ali; Yaftian, Mohammad Reza; Parizanganeh, Abdolhossein

2012-12-17

The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarography (DPP). Although, cobalt, copper and zinc were found correspondingly in 47.8%, 100.0%, and 100.0% of the samples, they did not contain these metals above their maximum contaminant levels (MCLs). Cadmium was detected in 65.2% of the samples and 17.4% of them were polluted by this metal. All samples contained detectable levels of lead and iron with 8.7% and 13.0% of the samples higher than their MCLs. Nickel was also found in 78.3% of the samples, out of which 8.7% were polluted. In general, the results revealed the contamination of groundwater sources in the studied zone. The higher health risks are related to lead, nickel, and cadmium ions. Multivariate statistical techniques were applied for interpreting the experimental data and giving a description for the sources. The data analysis showed correlations and similarities between investigated heavy metals and helps to classify these ion groups. Cluster analysis identified five clusters among the studied heavy metals. Cluster 1 consisted of Pb, Cu, and cluster 3 included Cd, Fe; also each of the elements Zn, Co and Ni was located in groups with single member. The same results were obtained by factor analysis. Statistical investigations revealed that anthropogenic factors and notably lead and zinc plant and pedo-geochemical pollution sources are influencing water quality in the studied area.

Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant

PubMed Central

2012-01-01

The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarography (DPP). Although, cobalt, copper and zinc were found correspondingly in 47.8%, 100.0%, and 100.0% of the samples, they did not contain these metals above their maximum contaminant levels (MCLs). Cadmium was detected in 65.2% of the samples and 17.4% of them were polluted by this metal. All samples contained detectable levels of lead and iron with 8.7% and 13.0% of the samples higher than their MCLs. Nickel was also found in 78.3% of the samples, out of which 8.7% were polluted. In general, the results revealed the contamination of groundwater sources in the studied zone. The higher health risks are related to lead, nickel, and cadmium ions. Multivariate statistical techniques were applied for interpreting the experimental data and giving a description for the sources. The data analysis showed correlations and similarities between investigated heavy metals and helps to classify these ion groups. Cluster analysis identified five clusters among the studied heavy metals. Cluster 1 consisted of Pb, Cu, and cluster 3 included Cd, Fe; also each of the elements Zn, Co and Ni was located in groups with single member. The same results were obtained by factor analysis. Statistical investigations revealed that anthropogenic factors and notably lead and zinc plant and pedo-geochemical pollution sources are influencing water quality in the studied area. PMID:23369182

Testing for X-Ray–SZ Differences and Redshift Evolution in the X-Ray Morphology of Galaxy Clusters

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

Nurgaliev, D.; McDonald, M.; Benson, B. A.

We present a quantitative study of the X-ray morphology of galaxy clusters, as a function of their detection method and redshift. We analyze two separate samples of galaxy clusters: a sample of 36 clusters atmore » $$0.35\\lt z\\lt 0.9$$ selected in the X-ray with the ROSAT PSPC 400 deg(2) survey, and a sample of 90 clusters at $$0.25\\lt z\\lt 1.2$$ selected via the Sunyaev–Zel’dovich (SZ) effect with the South Pole Telescope. Clusters from both samples have similar-quality Chandra observations, which allow us to quantify their X-ray morphologies via two distinct methods: centroid shifts (w) and photon asymmetry ($${A}_{\\mathrm{phot}}$$). The latter technique provides nearly unbiased morphology estimates for clusters spanning a broad range of redshift and data quality. We further compare the X-ray morphologies of X-ray- and SZ-selected clusters with those of simulated clusters. We do not find a statistically significant difference in the measured X-ray morphology of X-ray and SZ-selected clusters over the redshift range probed by these samples, suggesting that the two are probing similar populations of clusters. We find that the X-ray morphologies of simulated clusters are statistically indistinguishable from those of X-ray- or SZ-selected clusters, implying that the most important physics for dictating the large-scale gas morphology (outside of the core) is well-approximated in these simulations. Finally, we find no statistically significant redshift evolution in the X-ray morphology (both for observed and simulated clusters), over the range of $$z\\sim 0.3$$ to $$z\\sim 1$$, seemingly in contradiction with the redshift-dependent halo merger rate predicted by simulations.« less

Testing for X-Ray–SZ Differences and Redshift Evolution in the X-Ray Morphology of Galaxy Clusters

DOE PAGES

Nurgaliev, D.; McDonald, M.; Benson, B. A.; ...

2017-05-16

We present a quantitative study of the X-ray morphology of galaxy clusters, as a function of their detection method and redshift. We analyze two separate samples of galaxy clusters: a sample of 36 clusters atmore » $$0.35\\lt z\\lt 0.9$$ selected in the X-ray with the ROSAT PSPC 400 deg(2) survey, and a sample of 90 clusters at $$0.25\\lt z\\lt 1.2$$ selected via the Sunyaev–Zel’dovich (SZ) effect with the South Pole Telescope. Clusters from both samples have similar-quality Chandra observations, which allow us to quantify their X-ray morphologies via two distinct methods: centroid shifts (w) and photon asymmetry ($${A}_{\\mathrm{phot}}$$). The latter technique provides nearly unbiased morphology estimates for clusters spanning a broad range of redshift and data quality. We further compare the X-ray morphologies of X-ray- and SZ-selected clusters with those of simulated clusters. We do not find a statistically significant difference in the measured X-ray morphology of X-ray and SZ-selected clusters over the redshift range probed by these samples, suggesting that the two are probing similar populations of clusters. We find that the X-ray morphologies of simulated clusters are statistically indistinguishable from those of X-ray- or SZ-selected clusters, implying that the most important physics for dictating the large-scale gas morphology (outside of the core) is well-approximated in these simulations. Finally, we find no statistically significant redshift evolution in the X-ray morphology (both for observed and simulated clusters), over the range of $$z\\sim 0.3$$ to $$z\\sim 1$$, seemingly in contradiction with the redshift-dependent halo merger rate predicted by simulations.« less

Inference for multivariate regression model based on multiply imputed synthetic data generated via posterior predictive sampling

NASA Astrophysics Data System (ADS)

Moura, Ricardo; Sinha, Bimal; Coelho, Carlos A.

2017-06-01

The recent popularity of the use of synthetic data as a Statistical Disclosure Control technique has enabled the development of several methods of generating and analyzing such data, but almost always relying in asymptotic distributions and in consequence being not adequate for small sample datasets. Thus, a likelihood-based exact inference procedure is derived for the matrix of regression coefficients of the multivariate regression model, for multiply imputed synthetic data generated via Posterior Predictive Sampling. Since it is based in exact distributions this procedure may even be used in small sample datasets. Simulation studies compare the results obtained from the proposed exact inferential procedure with the results obtained from an adaptation of Reiters combination rule to multiply imputed synthetic datasets and an application to the 2000 Current Population Survey is discussed.

Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much.

PubMed

He, Bryan; De Sa, Christopher; Mitliagkas, Ioannis; Ré, Christopher

2016-01-01

Gibbs sampling is a Markov Chain Monte Carlo sampling technique that iteratively samples variables from their conditional distributions. There are two common scan orders for the variables: random scan and systematic scan. Due to the benefits of locality in hardware, systematic scan is commonly used, even though most statistical guarantees are only for random scan. While it has been conjectured that the mixing times of random scan and systematic scan do not differ by more than a logarithmic factor, we show by counterexample that this is not the case, and we prove that that the mixing times do not differ by more than a polynomial factor under mild conditions. To prove these relative bounds, we introduce a method of augmenting the state space to study systematic scan using conductance.

Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much

PubMed Central

He, Bryan; De Sa, Christopher; Mitliagkas, Ioannis; Ré, Christopher

2016-01-01

Gibbs sampling is a Markov Chain Monte Carlo sampling technique that iteratively samples variables from their conditional distributions. There are two common scan orders for the variables: random scan and systematic scan. Due to the benefits of locality in hardware, systematic scan is commonly used, even though most statistical guarantees are only for random scan. While it has been conjectured that the mixing times of random scan and systematic scan do not differ by more than a logarithmic factor, we show by counterexample that this is not the case, and we prove that that the mixing times do not differ by more than a polynomial factor under mild conditions. To prove these relative bounds, we introduce a method of augmenting the state space to study systematic scan using conductance. PMID:28344429

Forest inventory using multistage sampling with probability proportional to size. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Lee, D. C. L.; Hernandezfilho, P.; Shimabukuro, Y. E.; Deassis, O. R.; Demedeiros, J. S.

1984-01-01

A multistage sampling technique, with probability proportional to size, for forest volume inventory using remote sensing data is developed and evaluated. The study area is located in the Southeastern Brazil. The LANDSAT 4 digital data of the study area are used in the first stage for automatic classification of reforested areas. Four classes of pine and eucalypt with different tree volumes are classified utilizing a maximum likelihood classification algorithm. Color infrared aerial photographs are utilized in the second stage of sampling. In the third state (ground level) the time volume of each class is determined. The total time volume of each class is expanded through a statistical procedure taking into account all the three stages of sampling. This procedure results in an accurate time volume estimate with a smaller number of aerial photographs and reduced time in field work.

Data exploration of social client relationship management (CRM 2.0) adoption in the Nigerian construction business.

PubMed

Ojelabi, Rapheal A; Afolabi, Adedeji O; Oyeyipo, Opeyemi O; Tunji-Olayeni, Patience F; Adewale, Bukola A

2018-06-01

Integrating social client relationship management (CRM 2.0) in the built environment can enhance the relationship between construction organizations and client towards sustaining a long and lasting collaboration. The data exploration analyzed the e-readiness of contracting and consulting construction firms in the uptake of CRM 2.0 and the barriers encountered in the adoption of the modern business tool. The targeted organizations consist of seventy five (75) construction businesses operating in Lagos State which were selected from a pool of registered contracting and consulting construction firms using random sampling technique. Descriptive statistics of the e-readiness of contracting and consulting construction firms for CRM 2.0 adoption and barriers limiting its uptake were analyzed. Also, inferential analysis using Mann-Whitney U statistical and independent sample t-test was performed on the dataset obtained. The data generated will support construction firms on the necessity to engage in client social relationship management in ensuring sustainable client relationship management in the built environment.

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

Sil’chenko, Olga K., E-mail: olga@sai.msu.su; Isaac Newton Institute, Chile, Moscow Branch

I analyze statistics of the stellar population properties for stellar nuclei and bulges of nearby lenticular galaxies in different environments by using panoramic spectral data of the integral-field spectrograph SAURON retrieved from the open archive of the Isaac Newton Group. I also estimate the fraction of nearby lenticular galaxies having inner polar gaseous disks by exploring the volume-limited sample of early-type galaxies of the ATLAS-3D survey. By inspecting the two-dimensional velocity fields of the stellar and gaseous components with the running tilted-ring technique, I have found seven new cases of inner polar disks. Together with those, the frequency of inner polar disks in nearby S0 galaxiesmore » reaches 10%, which is much higher than the frequency of large-scale polar rings. Interestingly, the properties of the nuclear stellar populations in the inner polar ring hosts are statistically the same as those in the whole S0 sample, implying similar histories of multiple gas-accretion events from various directions.« less

Cannabis, motivation, and life satisfaction in an internet sample

PubMed Central

Barnwell, Sara Smucker; Earleywine, Mitch; Wilcox, Rand

2006-01-01

Although little evidence supports cannabis-induced amotivational syndrome, sources continue to assert that the drug saps motivation [1], which may guide current prohibitions. Few studies report low motivation in chronic users; another reveals that they have higher subjective wellbeing. To assess differences in motivation and subjective wellbeing, we used a large sample (N = 487) and strict definitions of cannabis use (7 days/week) and abstinence (never). Standard statistical techniques showed no differences. Robust statistical methods controlling for heteroscedasticity, non-normality and extreme values found no differences in motivation but a small difference in subjective wellbeing. Medical users of cannabis reporting health problems tended to account for a significant portion of subjective wellbeing differences, suggesting that illness decreased wellbeing. All p-values were above p = .05. Thus, daily use of cannabis does not impair motivation. Its impact on subjective wellbeing is small and may actually reflect lower wellbeing due to medical symptoms rather than actual consumption of the plant. PMID:16722561

Wang-Landau Reaction Ensemble Method: Simulation of Weak Polyelectrolytes and General Acid-Base Reactions.

PubMed

Landsgesell, Jonas; Holm, Christian; Smiatek, Jens

2017-02-14

We present a novel method for the study of weak polyelectrolytes and general acid-base reactions in molecular dynamics and Monte Carlo simulations. The approach combines the advantages of the reaction ensemble and the Wang-Landau sampling method. Deprotonation and protonation reactions are simulated explicitly with the help of the reaction ensemble method, while the accurate sampling of the corresponding phase space is achieved by the Wang-Landau approach. The combination of both techniques provides a sufficient statistical accuracy such that meaningful estimates for the density of states and the partition sum can be obtained. With regard to these estimates, several thermodynamic observables like the heat capacity or reaction free energies can be calculated. We demonstrate that the computation times for the calculation of titration curves with a high statistical accuracy can be significantly decreased when compared to the original reaction ensemble method. The applicability of our approach is validated by the study of weak polyelectrolytes and their thermodynamic properties.

SPICE: exploration and analysis of post-cytometric complex multivariate datasets.

PubMed

Roederer, Mario; Nozzi, Joshua L; Nason, Martha C

2011-02-01

Polychromatic flow cytometry results in complex, multivariate datasets. To date, tools for the aggregate analysis of these datasets across multiple specimens grouped by different categorical variables, such as demographic information, have not been optimized. Often, the exploration of such datasets is accomplished by visualization of patterns with pie charts or bar charts, without easy access to statistical comparisons of measurements that comprise multiple components. Here we report on algorithms and a graphical interface we developed for these purposes. In particular, we discuss thresholding necessary for accurate representation of data in pie charts, the implications for display and comparison of normalized versus unnormalized data, and the effects of averaging when samples with significant background noise are present. Finally, we define a statistic for the nonparametric comparison of complex distributions to test for difference between groups of samples based on multi-component measurements. While originally developed to support the analysis of T cell functional profiles, these techniques are amenable to a broad range of datatypes. Published 2011 Wiley-Liss, Inc.

Metamodels for Computer-Based Engineering Design: Survey and Recommendations

NASA Technical Reports Server (NTRS)

Simpson, Timothy W.; Peplinski, Jesse; Koch, Patrick N.; Allen, Janet K.

1997-01-01

The use of statistical techniques to build approximations of expensive computer analysis codes pervades much of todays engineering design. These statistical approximations, or metamodels, are used to replace the actual expensive computer analyses, facilitating multidisciplinary, multiobjective optimization and concept exploration. In this paper we review several of these techniques including design of experiments, response surface methodology, Taguchi methods, neural networks, inductive learning, and kriging. We survey their existing application in engineering design and then address the dangers of applying traditional statistical techniques to approximate deterministic computer analysis codes. We conclude with recommendations for the appropriate use of statistical approximation techniques in given situations and how common pitfalls can be avoided.

Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands.

PubMed

Pérez, Germán M; Salomón, Luis A; Montero-Cabrera, Luis A; de la Vega, José M García; Mascini, Marcello

2016-05-01

A novel heuristic using an iterative select-and-purge strategy is proposed. It combines statistical techniques for sampling and classification by rigid molecular docking through an inverse virtual screening scheme. This approach aims to the de novo discovery of short peptides that may act as docking receptors for small target molecules when there are no data available about known association complexes between them. The algorithm performs an unbiased stochastic exploration of the sample space, acting as a binary classifier when analyzing the entire peptides population. It uses a novel and effective criterion for weighting the likelihood of a given peptide to form an association complex with a particular ligand molecule based on amino acid sequences. The exploratory analysis relies on chemical information of peptides composition, sequence patterns, and association free energies (docking scores) in order to converge to those peptides forming the association complexes with higher affinities. Statistical estimations support these results providing an association probability by improving predictions accuracy even in cases where only a fraction of all possible combinations are sampled. False positives/false negatives ratio was also improved with this method. A simple rigid-body docking approach together with the proper information about amino acid sequences was used. The methodology was applied in a retrospective docking study to all 8000 possible tripeptide combinations using the 20 natural amino acids, screened against a training set of 77 different ligands with diverse functional groups. Afterward, all tripeptides were screened against a test set of 82 ligands, also containing different functional groups. Results show that our integrated methodology is capable of finding a representative group of the top-scoring tripeptides. The associated probability of identifying the best receptor or a group of the top-ranked receptors is more than double and about 10 times higher, respectively, when compared to classical random sampling methods.

Approximation of Confidence Limits on Sample Semivariograms From Single Realizations of Spatially Correlated Random Fields

NASA Astrophysics Data System (ADS)

Shafer, J. M.; Varljen, M. D.

1990-08-01

A fundamental requirement for geostatistical analyses of spatially correlated environmental data is the estimation of the sample semivariogram to characterize spatial correlation. Selecting an underlying theoretical semivariogram based on the sample semivariogram is an extremely important and difficult task that is subject to a great deal of uncertainty. Current standard practice does not involve consideration of the confidence associated with semivariogram estimates, largely because classical statistical theory does not provide the capability to construct confidence limits from single realizations of correlated data, and multiple realizations of environmental fields are not found in nature. The jackknife method is a nonparametric statistical technique for parameter estimation that may be used to estimate the semivariogram. When used in connection with standard confidence procedures, it allows for the calculation of closely approximate confidence limits on the semivariogram from single realizations of spatially correlated data. The accuracy and validity of this technique was verified using a Monte Carlo simulation approach which enabled confidence limits about the semivariogram estimate to be calculated from many synthetically generated realizations of a random field with a known correlation structure. The synthetically derived confidence limits were then compared to jackknife estimates from single realizations with favorable results. Finally, the methodology for applying the jackknife method to a real-world problem and an example of the utility of semivariogram confidence limits were demonstrated by constructing confidence limits on seasonal sample variograms of nitrate-nitrogen concentrations in shallow groundwater in an approximately 12-mi2 (˜30 km2) region in northern Illinois. In this application, the confidence limits on sample semivariograms from different time periods were used to evaluate the significance of temporal change in spatial correlation. This capability is quite important as it can indicate when a spatially optimized monitoring network would need to be reevaluated and thus lead to more robust monitoring strategies.

Evaluation of Lysis Methods for the Extraction of Bacterial DNA for Analysis of the Vaginal Microbiota.

PubMed

Gill, Christina; van de Wijgert, Janneke H H M; Blow, Frances; Darby, Alistair C

2016-01-01

Recent studies on the vaginal microbiota have employed molecular techniques such as 16S rRNA gene sequencing to describe the bacterial community as a whole. These techniques require the lysis of bacterial cells to release DNA before purification and PCR amplification of the 16S rRNA gene. Currently, methods for the lysis of bacterial cells are not standardised and there is potential for introducing bias into the results if some bacterial species are lysed less efficiently than others. This study aimed to compare the results of vaginal microbiota profiling using four different pretreatment methods for the lysis of bacterial samples (30 min of lysis with lysozyme, 16 hours of lysis with lysozyme, 60 min of lysis with a mixture of lysozyme, mutanolysin and lysostaphin and 30 min of lysis with lysozyme followed by bead beating) prior to chemical and enzyme-based DNA extraction with a commercial kit. After extraction, DNA yield did not significantly differ between methods with the exception of lysis with lysozyme combined with bead beating which produced significantly lower yields when compared to lysis with the enzyme cocktail or 30 min lysis with lysozyme only. However, this did not result in a statistically significant difference in the observed alpha diversity of samples. The beta diversity (Bray-Curtis dissimilarity) between different lysis methods was statistically significantly different, but this difference was small compared to differences between samples, and did not affect the grouping of samples with similar vaginal bacterial community structure by hierarchical clustering. An understanding of how laboratory methods affect the results of microbiota studies is vital in order to accurately interpret the results and make valid comparisons between studies. Our results indicate that the choice of lysis method does not prevent the detection of effects relating to the type of vaginal bacterial community one of the main outcome measures of epidemiological studies. However, we recommend that the same method is used on all samples within a particular study.

Determining Individual Grains' Magnetic Moments by Micromagnetic Tomography

NASA Astrophysics Data System (ADS)

de Groot, L. V.; Fabian, K.; Béguin, A.; Reith, P.; Rastogi, A.; Barnhoorn, A.; Hilgenkamp, H.

2017-12-01

Methods to derive paleodirections or paleointensities from rocks currently rely on measurements of bulk samples (typically 10 cc). These samples contain many millions of magnetic remanence carrying grains, their statistical assemblage gives rise to a net magnetic moment for the entire sample. The magnetic properties of these grains, however, differ because of their sizes, shapes, and chemical composition. When dealing with lavas this complex magnetic behavior often hampers paleointensity experiments; while occasionally a reliable paleodirection is obscured. If we would be able to isolate the contribution of each magnetic grain in a sample to the bulk magnetic moment of that sample, a wealth of opportunities for highly detailed magnetic analysis would be opened, possibly leading to an entirely new approach in retrieving paleomagnetic signals from complex mineralogies. Here we take the first practical steps towards this goal by developing a new technique: 'micromagnetic tomography'. Firstly, the distribution and volume of the remanence carrying grains in the sample must be assessed; this is done using a MicroCT scanner capable of detecting grains 1 micron. Secondly, the magnetic stray field perpendicular to the surface of a thin sample is measured using a high-resolution DC SQUID microscope. A mathematical inversion of these measurements yields the isolated direction and magnitude of the magnetic moment of individual grains in the sample. As the measured strength of the magnetic field decreases with the third power as function of distance to the exerting grain (as a result of decay in three dimensions), grains in the top 30-40 microns of our synthetic sample with a relatively low dispersion of grains in a matrix can be assessed reliably. We will discuss the potential of our new inversion scheme, and current challenges we need to overcome for both the scanning SQUID and MicroCT techniques before we can analyse 'real' volcanic samples with our technique.

Comparison between mechanical freezer and conventional freezing using liquid nitrogen in normozoospermia.

PubMed

Rahana, A R; Ng, S P; Leong, C F; Rahimah, M D

2011-10-01

This study evaluated the effect of human semen cryopreservation using an ultra-low temperature technique with a mechanical freezer at -85°C as an alternative method to the conventional liquid nitrogen technique at -196°C. This was a prospective experimental study conducted in the Medically Assisted Conception unit, Department of Obstetrics and Gynaecology, National University Hospital, Malaysia from January 1, 2006 to April 30, 2007. All normozoospermic semen samples were included in the study. The concentration, motility and percentage of intact DNA of each semen sample were assessed before and after freezing and thawing on Days 7 and 30 post freezing. Sperm cryopreservation at -85°C was comparable to the conventional liquid nitrogen technique for a period of up to 30 days in a normozoospermic sample. There was no statistical difference in concentration (Day 7 p-value is 0.1, Day 30 p-value is 0.2), motility (Day 7 p-value is 0.9, Day 30 p-value is 0.5) and proportion of intact DNA (Day 7 p-value is 0.1, Day 30 p-value is 0.2) between the ultra-low temperature technique and conventional liquid nitrogen cryopreservation at Days 7 and 30 post thawing. This study clearly demonstrates that short-term storage of sperm at -85°C could be a viable alternative to conventional liquid nitrogen cryopreservation at -196°C due to their comparable post-thaw results.

Impact of multicollinearity on small sample hydrologic regression models

NASA Astrophysics Data System (ADS)

Kroll, Charles N.; Song, Peter

2013-06-01

Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.

Forensic DNA testing.

PubMed

Butler, John M

2011-12-01

Forensic DNA testing has a number of applications, including parentage testing, identifying human remains from natural or man-made disasters or terrorist attacks, and solving crimes. This article provides background information followed by an overview of the process of forensic DNA testing, including sample collection, DNA extraction, PCR amplification, short tandem repeat (STR) allele separation and sizing, typing and profile interpretation, statistical analysis, and quality assurance. The article concludes with discussions of possible problems with the data and other forensic DNA testing techniques.

A Review of Calibration Transfer Practices and Instrument Differences in Spectroscopy.

PubMed

Workman, Jerome J

2018-03-01

Calibration transfer for use with spectroscopic instruments, particularly for near-infrared, infrared, and Raman analysis, has been the subject of multiple articles, research papers, book chapters, and technical reviews. There has been a myriad of approaches published and claims made for resolving the problems associated with transferring calibrations; however, the capability of attaining identical results over time from two or more instruments using an identical calibration still eludes technologists. Calibration transfer, in a precise definition, refers to a series of analytical approaches or chemometric techniques used to attempt to apply a single spectral database, and the calibration model developed using that database, for two or more instruments, with statistically retained accuracy and precision. Ideally, one would develop a single calibration for any particular application, and move it indiscriminately across instruments and achieve identical analysis or prediction results. There are many technical aspects involved in such precision calibration transfer, related to the measuring instrument reproducibility and repeatability, the reference chemical values used for the calibration, the multivariate mathematics used for calibration, and sample presentation repeatability and reproducibility. Ideally, a multivariate model developed on a single instrument would provide a statistically identical analysis when used on other instruments following transfer. This paper reviews common calibration transfer techniques, mostly related to instrument differences, and the mathematics of the uncertainty between instruments when making spectroscopic measurements of identical samples. It does not specifically address calibration maintenance or reference laboratory differences.

Remote sensing new model for monitoring the east Asian migratory locust infections based on its breeding circle

NASA Astrophysics Data System (ADS)

Han, Xiuzhen; Ma, Jianwen; Bao, Yuhai

2006-12-01

Currently the function of operational locust monitor system mainly focused on after-hazards monitoring and assessment, and to found the way effectively to perform early warning and prediction has more practical meaning. Through 2001, 2002 two years continuously field sample and statistics for locusts eggs hatching, nymph growth, adults 3 phases observation, sample statistics and calculation, spectral measurements as well as synchronically remote sensing data processing we raise the view point of Remote Sensing three stage monitor the locust hazards. Based on the point of view we designed remote sensing monitor in three stages: (1) during the egg hitching phase remote sensing can retrieve parameters of land surface temperature (LST) and soil moisture; (2) during nymph growth phase locust increases appetite greatly and remote sensing can calculate vegetation index, leaf area index, vegetation cover and analysis changes; (3) during adult phase the locust move and assembly towards ponds and water ditches as well as less than 75% vegetation cover areas and remote sensing combination with field data can monitor and predicts potential areas for adult locusts to assembly. In this way the priority of remote sensing technology is elaborated effectively and it also provides technique support for the locust monitor system. The idea and techniques used in the study can also be used as reference for other plant diseases and insect pests.

Spatial characterization of dissolved trace elements and heavy metals in the upper Han River (China) using multivariate statistical techniques.

PubMed

Li, Siyue; Zhang, Quanfa

2010-04-15

A data matrix (4032 observations), obtained during a 2-year monitoring period (2005-2006) from 42 sites in the upper Han River is subjected to various multivariate statistical techniques including cluster analysis, principal component analysis (PCA), factor analysis (FA), correlation analysis and analysis of variance to determine the spatial characterization of dissolved trace elements and heavy metals. Our results indicate that waters in the upper Han River are primarily polluted by Al, As, Cd, Pb, Sb and Se, and the potential pollutants include Ba, Cr, Hg, Mn and Ni. Spatial distribution of trace metals indicates the polluted sections mainly concentrate in the Danjiang, Danjiangkou Reservoir catchment and Hanzhong Plain, and the most contaminated river is in the Hanzhong Plain. Q-model clustering depends on geographical location of sampling sites and groups the 42 sampling sites into four clusters, i.e., Danjiang, Danjiangkou Reservoir region (lower catchment), upper catchment and one river in headwaters pertaining to water quality. The headwaters, Danjiang and lower catchment, and upper catchment correspond to very high polluted, moderate polluted and relatively low polluted regions, respectively. Additionally, PCA/FA and correlation analysis demonstrates that Al, Cd, Mn, Ni, Fe, Si and Sr are controlled by natural sources, whereas the other metals appear to be primarily controlled by anthropogenic origins though geogenic source contributing to them. 2009 Elsevier B.V. All rights reserved.

Quantifying Trace Amounts of Aggregates in Biopharmaceuticals Using Analytical Ultracentrifugation Sedimentation Velocity: Bayesian Analyses and F Statistics.

PubMed

Wafer, Lucas; Kloczewiak, Marek; Luo, Yin

2016-07-01

Analytical ultracentrifugation-sedimentation velocity (AUC-SV) is often used to quantify high molar mass species (HMMS) present in biopharmaceuticals. Although these species are often present in trace quantities, they have received significant attention due to their potential immunogenicity. Commonly, AUC-SV data is analyzed as a diffusion-corrected, sedimentation coefficient distribution, or c(s), using SEDFIT to numerically solve Lamm-type equations. SEDFIT also utilizes maximum entropy or Tikhonov-Phillips regularization to further allow the user to determine relevant sample information, including the number of species present, their sedimentation coefficients, and their relative abundance. However, this methodology has several, often unstated, limitations, which may impact the final analysis of protein therapeutics. These include regularization-specific effects, artificial "ripple peaks," and spurious shifts in the sedimentation coefficients. In this investigation, we experimentally verified that an explicit Bayesian approach, as implemented in SEDFIT, can largely correct for these effects. Clear guidelines on how to implement this technique and interpret the resulting data, especially for samples containing micro-heterogeneity (e.g., differential glycosylation), are also provided. In addition, we demonstrated how the Bayesian approach can be combined with F statistics to draw more accurate conclusions and rigorously exclude artifactual peaks. Numerous examples with an antibody and an antibody-drug conjugate were used to illustrate the strengths and drawbacks of each technique.

Quantification of rare earth elements using laser-induced breakdown spectroscopy

DOE PAGES

Martin, Madhavi; Martin, Rodger C.; Allman, Steve; ...

2015-10-21

In this paper, a study of the optical emission as a function of concentration of laser-ablated yttrium (Y) and of six rare earth elements, europium (Eu), gadolinium (Gd), lanthanum (La), praseodymium (Pr), neodymium (Nd), and samarium (Sm), has been evaluated using the laser-induced breakdown spectroscopy (LIBS) technique. Statistical methodology using multivariate analysis has been used to obtain the sampling errors, coefficient of regression, calibration, and cross-validation of measurements as they relate to the LIBS analysis in graphite-matrix pellets that were doped with elements at several concentrations. Each element (in oxide form) was mixed in the graphite matrix in percentages rangingmore » from 1% to 50% by weight and the LIBS spectra obtained for each composition as well as for pure oxide samples. Finally, a single pellet was mixed with all the elements in equal oxide masses to determine if we can identify the elemental peaks in a mixed pellet. This dataset is relevant for future application to studies of fission product content and distribution in irradiated nuclear fuels. These results demonstrate that LIBS technique is inherently well suited for the future challenge of in situ analysis of nuclear materials. Finally, these studies also show that LIBS spectral analysis using statistical methodology can provide quantitative results and suggest an approach in future to the far more challenging multielemental analysis of ~ 20 primary elements in high-burnup nuclear reactor fuel.« less

C3H7NO2S effect on concrete steel-rebar corrosion in 0.5 M H2SO4 simulating industrial/microbial environment

NASA Astrophysics Data System (ADS)

Okeniyi, Joshua Olusegun; Nwadialo, Christopher Chukwuweike; Olu-Steven, Folusho Emmanuel; Ebinne, Samaru Smart; Coker, Taiwo Ebenezer; Okeniyi, Elizabeth Toyin; Ogbiye, Adebanji Samuel; Durotoye, Taiwo Omowunmi; Badmus, Emmanuel Omotunde Oluwasogo

2017-02-01

This paper investigates C3H7NO2S (Cysteine) effect on the inhibition of reinforcing steel corrosion in concrete immersed in 0.5 M H2SO4, for simulating industrial/microbial environment. Different C3H7NO2S concentrations were admixed, in duplicates, in steel-reinforced concrete samples that were partially immersed in the acidic sulphate environment. Electrochemical monitoring techniques of open circuit potential, as per ASTM C876-91 R99, and corrosion rate, by linear polarization resistance, were then employed for studying anticorrosion effect in steel-reinforced concrete samples by the organic hydrocarbon admixture. Analyses of electrochemical test-data followed ASTM G16-95 R04 prescriptions including probability distribution modeling with significant testing by Kolmogorov-Smirnov and student's t-tests statistics. Results established that all datasets of corrosion potential distributed like the Normal, the Gumbel and the Weibull distributions but that only the Weibull model described all the corrosion rate datasets in the study, as per the Kolmogorov-Smirnov test-statistics. Results of the student's t-test showed that differences of corrosion test-data between duplicated samples with the same C3H7NO2S concentrations were not statistically significant. These results indicated that 0.06878 M C3H7NO2S exhibited optimal inhibition efficiency η = 90.52±1.29% on reinforcing steel corrosion in the concrete samples immersed in 0.5 M H2SO4, simulating industrial/microbial service-environment.

Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy

PubMed Central

Barish, Syndi; Ochs, Michael F.; Sontag, Eduardo D.; Gevertz, Jana L.

2017-01-01

Cancer is a highly heterogeneous disease, exhibiting spatial and temporal variations that pose challenges for designing robust therapies. Here, we propose the VEPART (Virtual Expansion of Populations for Analyzing Robustness of Therapies) technique as a platform that integrates experimental data, mathematical modeling, and statistical analyses for identifying robust optimal treatment protocols. VEPART begins with time course experimental data for a sample population, and a mathematical model fit to aggregate data from that sample population. Using nonparametric statistics, the sample population is amplified and used to create a large number of virtual populations. At the final step of VEPART, robustness is assessed by identifying and analyzing the optimal therapy (perhaps restricted to a set of clinically realizable protocols) across each virtual population. As proof of concept, we have applied the VEPART method to study the robustness of treatment response in a mouse model of melanoma subject to treatment with immunostimulatory oncolytic viruses and dendritic cell vaccines. Our analysis (i) showed that every scheduling variant of the experimentally used treatment protocol is fragile (nonrobust) and (ii) discovered an alternative region of dosing space (lower oncolytic virus dose, higher dendritic cell dose) for which a robust optimal protocol exists. PMID:28716945

Non-targeted 1H NMR fingerprinting and multivariate statistical analyses for the characterisation of the geographical origin of Italian sweet cherries.

PubMed

Longobardi, F; Ventrella, A; Bianco, A; Catucci, L; Cafagna, I; Gallo, V; Mastrorilli, P; Agostiano, A

2013-12-01

In this study, non-targeted (1)H NMR fingerprinting was used in combination with multivariate statistical techniques for the classification of Italian sweet cherries based on their different geographical origins (Emilia Romagna and Puglia). As classification techniques, Soft Independent Modelling of Class Analogy (SIMCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Linear Discriminant Analysis (LDA) were carried out and the results were compared. For LDA, before performing a refined selection of the number/combination of variables, two different strategies for a preliminary reduction of the variable number were tested. The best average recognition and CV prediction abilities (both 100.0%) were obtained for all the LDA models, although PLS-DA also showed remarkable performances (94.6%). All the statistical models were validated by observing the prediction abilities with respect to an external set of cherry samples. The best result (94.9%) was obtained with LDA by performing a best subset selection procedure on a set of 30 principal components previously selected by a stepwise decorrelation. The metabolites that mostly contributed to the classification performances of such LDA model, were found to be malate, glucose, fructose, glutamine and succinate. Copyright © 2013 Elsevier Ltd. All rights reserved.

A comparison of impact force reduction by polymer materials used for mouthguard fabrication.

PubMed

Gawlak, Dominika; Mańka-Malara, Katarzyna; Mierzwińska-Nastalska, Elżbieta; Gieleta, Roman; Kamiński, Tomasz; Łuniewska, Magdalena

2017-01-01

The essential function of mouthguards is protection against the effects of injuries sustained during sports activities. This purpose will be successfully achieved if appropriate materials ensuring sufficient reduction of the injury force are used for mouthguard fabrication. The objective of the study was to investigate the force reduction capability of selected materials as well as to identify which material reduces the impact force to the highest degree. The material for the study were samples of polymers (6 samples in total), obtained during the process of deep pressing (2 samples), flasking (3 samples) and thermal injection (1 sample), which were tested for impact force damping using an impact device - Charpy impact hammer. The control group comprised of the ceramic material samples subjected to the hammer impact. The statistical analysis applied in this study were one-way Welch ANOVA with post-hoc Games-Howell pairwise comparisons. The test materials reduced the impact force of the impact hammer to varying degrees. The greatest damping capability was demonstrated for the following materials: Impak with 1:1 powder-to-liquid weight ratio polymerized with the conventional flasking technique, and Corflex Orthodontic used in the thermal injection technique of mouthguard fabrication. Impak with 1:1 weight ratio and Corflex Orthodontic should be recommended for the fabrication of mouthguards since they demonstrated the most advantageous damping properties.

Variations in the Rate of Infestations of Dogs with Zoonotic Nematodes and the Contamination of Soil in Different Environments

PubMed Central

Demkowska-Kutrzepa, Marta; Borecka, Anna; Meisner, Michał; Tomczuk, Krzysztof; Roczeń-Karczmarz, Monika; Kłapeć, Teresa; Abbass, Zahrai; Cholewa, Alicja

2017-01-01

Companion animals are an important aspect in human life. However, they may also be considered a source of pathogens. An example of zoonotic parasitoses is toxocarosis or cutaneous larva migrans (CLM). The aim of the study was to detect zoonotic nematodes of dogs living in different areas and the intensity of contamination in parasite polluted environments that are hazardous to human health. The fecal samples were examined using standard flotation and decantation methods as well as McMaster’s quantitative technique. The soil samples in urban and rural areas were examined using a modified flotation method as described by Quinn et al. Statistical analyses were performed by IBM SPSS Statistics Version 23. The overall prevalence of parasites in dogs was 38%, 17.02% and 56.60% from urban and rural areas, respectively. The percentage values of nematodes important for human health (Toxocara canis, Ancylostomatidae, Trichuris vulpis) remained at the same level (16%). The infected dogs were dominated by a single parasite species, the main was T. canis (28.95%). In total, 54.30% of the soil samples were contaminated with parasite eggs. The contamination of urban and rural sandpits was 40% and 60%, respectively. The molecular examinations of soil samples using LAMP (loop-mediated isothermal amplification) confirmed the presence of nematode eggs of the species T. canis in all samples previously classified as positive PMID:28862690

Variations in the Rate of Infestations of Dogs with Zoonotic Nematodes and the Contamination of Soil in Different Environments.

PubMed

Studzińska, Maria Bernadeta; Demkowska-Kutrzepa, Marta; Borecka, Anna; Meisner, Michał; Tomczuk, Krzysztof; Roczeń-Karczmarz, Monika; Kłapeć, Teresa; Abbass, Zahrai; Cholewa, Alicja

2017-09-01

Companion animals are an important aspect in human life. However, they may also be considered a source of pathogens. An example of zoonotic parasitoses is toxocarosis or cutaneous larva migrans (CLM). The aim of the study was to detect zoonotic nematodes of dogs living in different areas and the intensity of contamination in parasite polluted environments that are hazardous to human health. The fecal samples were examined using standard flotation and decantation methods as well as McMaster's quantitative technique. The soil samples in urban and rural areas were examined using a modified flotation method as described by Quinn et al. Statistical analyses were performed by IBM SPSS Statistics Version 23. The overall prevalence of parasites in dogs was 38%, 17.02% and 56.60% from urban and rural areas, respectively. The percentage values of nematodes important for human health ( Toxocara canis , Ancylostomatidae, Trichuris vulpis ) remained at the same level (16%). The infected dogs were dominated by a single parasite species, the main was T. canis (28.95%). In total, 54.30% of the soil samples were contaminated with parasite eggs. The contamination of urban and rural sandpits was 40% and 60%, respectively. The molecular examinations of soil samples using LAMP (loop-mediated isothermal amplification) confirmed the presence of nematode eggs of the species T. canis in all samples previously classified as positive.

Development of a low-cost method of analysis for the qualitative and quantitative analysis of butyltins in environmental samples.

PubMed

Bangkedphol, Sornnarin; Keenan, Helen E; Davidson, Christine; Sakultantimetha, Arthit; Songsasen, Apisit

2008-12-01

Most analytical methods for butyltins are based on high resolution techniques with complicated sample preparation. For this study, a simple application of an analytical method was developed using High Performance Liquid Chromatography (HPLC) with UV detection. The developed method was studied to determine tributyltin (TBT), dibutyltin (DBT) and monobutyltin (MBT) in sediment and water samples. The separation was performed in isocratic mode on an ultra cyanopropyl column with a mobile phase of hexane containing 5% THF and 0.03% acetic acid. This method was confirmed using standard GC/MS techniques and verified by statistical paired t-test method. Under the experimental conditions used, the limit of detection (LOD) of TBT and DBT were 0.70 and 0.50 microg/mL, respectively. The optimised extraction method for butyltins in water and sediment samples involved using hexane containing 0.05-0.5% tropolone and 0.2% sodium chloride in water at pH 1.7. The quantitative extraction of butyltin compounds in a certified reference material (BCR-646) and naturally contaminated samples was achieved with recoveries ranging from 95 to 108% and at %RSD 0.02-1.00%. This HPLC method and optimum extraction conditions were used to determine the contamination level of butyltins in environmental samples collected from the Forth and Clyde canal, Scotland, UK. The values obtained severely exceeded the Environmental Quality Standard (EQS) values. Although high resolution methods are utilised extensively for this type of research, the developed method is cheaper in both terms of equipment and running costs, faster in analysis time and has comparable detection limits to the alternative methods. This is advantageous not just as a confirmatory technique but also to enable further research in this field.

Machine learning techniques applied to the determination of road suitability for the transportation of dangerous substances.

PubMed

Matías, J M; Taboada, J; Ordóñez, C; Nieto, P G

2007-08-17

This article describes a methodology to model the degree of remedial action required to make short stretches of a roadway suitable for dangerous goods transport (DGT), particularly pollutant substances, using different variables associated with the characteristics of each segment. Thirty-one factors determining the impact of an accident on a particular stretch of road were identified and subdivided into two major groups: accident probability factors and accident severity factors. Given the number of factors determining the state of a particular road segment, the only viable statistical methods for implementing the model were machine learning techniques, such as multilayer perceptron networks (MLPs), classification trees (CARTs) and support vector machines (SVMs). The results produced by these techniques on a test sample were more favourable than those produced by traditional discriminant analysis, irrespective of whether dimensionality reduction techniques were applied. The best results were obtained using SVMs specifically adapted to ordinal data. This technique takes advantage of the ordinal information contained in the data without penalising the computational load. Furthermore, the technique permits the estimation of the utility function that is latent in expert knowledge.

Identification of Atherosclerotic Plaques in Carotid Artery by Fluorescence Spectroscopy

NASA Astrophysics Data System (ADS)

Rocha, Rick; Villaverde, Antonio Balbin; Silveira, Landulfo; Costa, Maricília Silva; Alves, Leandro Procópio; Pasqualucci, Carlos Augusto; Brugnera, Aldo

2008-04-01

The aim of this work was to identify the presence of atherosclerotic plaques in carotid artery using the Fluorescence Spectroscopy. The most important pathogeny in the cardiovascular disorders is the atherosclerosis, which may affect even younger individuals. With approximately 1.2 million heart attacks and 750,000 strokes afflicting an aging American population each year, cardiovascular disease remains the number one cause of death. Carotid artery samples were obtained from the Autopsy Service at the University of São Paulo (São Paulo, SP, Brazil) taken from cadavers. After a histopathological analysis the 60 carotid artery samples were divided into two groups: normal (26) and atherosclerotic plaques (34). Samples were irradiated with the wavelength of 488 nm from an Argon laser. A 600 μm core optical fiber, coupled to the Argon laser, was used for excitation of the sample, whereas another 600 optical fiber, coupled to the spectrograph entrance slit, was used for collecting the fluorescence from the sample. Measurements were taken at different points on each sample and then averaged. Fluorescence spectra showed a single broad line centered at 549 nm. The fluorescence intensity for each sample was calculated by subtracting the intensity at the peak (550 nm) and at the bottom (510 nm) and then data were statistically analyzed, looking for differences between both groups of samples. ANOVA statistical test showed a significant difference (p<0,05) between both types of tissues, with regard to the fluorescence peak intensities. Our results indicate that this technique could be used to detect the presence of the atherosclerotic in carotid tissue.

Tools based on multivariate statistical analysis for classification of soil and groundwater in Apulian agricultural sites.

PubMed

Ielpo, Pierina; Leardi, Riccardo; Pappagallo, Giuseppe; Uricchio, Vito Felice

2017-06-01

In this paper, the results obtained from multivariate statistical techniques such as PCA (Principal component analysis) and LDA (Linear discriminant analysis) applied to a wide soil data set are presented. The results have been compared with those obtained on a groundwater data set, whose samples were collected together with soil ones, within the project "Improvement of the Regional Agro-meteorological Monitoring Network (2004-2007)". LDA, applied to soil data, has allowed to distinguish the geographical origin of the sample from either one of the two macroaeras: Bari and Foggia provinces vs Brindisi, Lecce e Taranto provinces, with a percentage of correct prediction in cross validation of 87%. In the case of the groundwater data set, the best classification was obtained when the samples were grouped into three macroareas: Foggia province, Bari province and Brindisi, Lecce and Taranto provinces, by reaching a percentage of correct predictions in cross validation of 84%. The obtained information can be very useful in supporting soil and water resource management, such as the reduction of water consumption and the reduction of energy and chemical (nutrients and pesticides) inputs in agriculture.

Assessment of physicochemical and antioxidant characteristics of Quercus pyrenaica honeydew honeys.

PubMed

Shantal Rodríguez Flores, M; Escuredo, Olga; Carmen Seijo, M

2015-01-01

Consumers are exhibiting increasing interest in honeydew honey, principally due to its functional properties. Some plants can be sources of honeydew honey, but in north-western Spain, this honey type only comes from Quercus pyrenaica. In the present study, the melissopalynological and physicochemical characteristics and the antioxidant properties of 32 honeydew honey samples are described. Q. pyrenaica honeydew honey was defined by its colour, high pH, phenols and flavonoids. Multivariate statistical techniques were used to analyse the influence of the production year on the honey's physicochemical parameters and polyphenol content. Differences among the honey samples were found, showing that weather affected the physicochemical composition of the honey samples. Optimal conditions for oak growth favoured the production of honeydew honey. Copyright © 2014 Elsevier Ltd. All rights reserved.

The potential of composite cognitive scores for tracking progression in Huntington's disease.

PubMed

Jones, Rebecca; Stout, Julie C; Labuschagne, Izelle; Say, Miranda; Justo, Damian; Coleman, Allison; Dumas, Eve M; Hart, Ellen; Owen, Gail; Durr, Alexandra; Leavitt, Blair R; Roos, Raymund; O'Regan, Alison; Langbehn, Doug; Tabrizi, Sarah J; Frost, Chris

2014-01-01

Composite scores derived from joint statistical modelling of individual risk factors are widely used to identify individuals who are at increased risk of developing disease or of faster disease progression. We investigated the ability of composite measures developed using statistical models to differentiate progressive cognitive deterioration in Huntington's disease (HD) from natural decline in healthy controls. Using longitudinal data from TRACK-HD, the optimal combinations of quantitative cognitive measures to differentiate premanifest and early stage HD individuals respectively from controls was determined using logistic regression. Composite scores were calculated from the parameters of each statistical model. Linear regression models were used to calculate effect sizes (ES) quantifying the difference in longitudinal change over 24 months between premanifest and early stage HD groups respectively and controls. ES for the composites were compared with ES for individual cognitive outcomes and other measures used in HD research. The 0.632 bootstrap was used to eliminate biases which result from developing and testing models in the same sample. In early HD, the composite score from the HD change prediction model produced an ES for difference in rate of 24-month change relative to controls of 1.14 (95% CI: 0.90 to 1.39), larger than the ES for any individual cognitive outcome and UHDRS Total Motor Score and Total Functional Capacity. In addition, this composite gave a statistically significant difference in rate of change in premanifest HD compared to controls over 24-months (ES: 0.24; 95% CI: 0.04 to 0.44), even though none of the individual cognitive outcomes produced statistically significant ES over this period. Composite scores developed using appropriate statistical modelling techniques have the potential to materially reduce required sample sizes for randomised controlled trials.