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Sample records for bias sampling method

  1. Sampling of temporal networks: Methods and biases

    Science.gov (United States)

    Rocha, Luis E. C.; Masuda, Naoki; Holme, Petter

    2017-11-01

    Temporal networks have been increasingly used to model a diversity of systems that evolve in time; for example, human contact structures over which dynamic processes such as epidemics take place. A fundamental aspect of real-life networks is that they are sampled within temporal and spatial frames. Furthermore, one might wish to subsample networks to reduce their size for better visualization or to perform computationally intensive simulations. The sampling method may affect the network structure and thus caution is necessary to generalize results based on samples. In this paper, we study four sampling strategies applied to a variety of real-life temporal networks. We quantify the biases generated by each sampling strategy on a number of relevant statistics such as link activity, temporal paths and epidemic spread. We find that some biases are common in a variety of networks and statistics, but one strategy, uniform sampling of nodes, shows improved performance in most scenarios. Given the particularities of temporal network data and the variety of network structures, we recommend that the choice of sampling methods be problem oriented to minimize the potential biases for the specific research questions on hand. Our results help researchers to better design network data collection protocols and to understand the limitations of sampled temporal network data.

  2. Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias.

    Science.gov (United States)

    Fourcade, Yoan; Engler, Jan O; Rödder, Dennis; Secondi, Jean

    2014-01-01

    MAXENT is now a common species distribution modeling (SDM) tool used by conservation practitioners for predicting the distribution of a species from a set of records and environmental predictors. However, datasets of species occurrence used to train the model are often biased in the geographical space because of unequal sampling effort across the study area. This bias may be a source of strong inaccuracy in the resulting model and could lead to incorrect predictions. Although a number of sampling bias correction methods have been proposed, there is no consensual guideline to account for it. We compared here the performance of five methods of bias correction on three datasets of species occurrence: one "virtual" derived from a land cover map, and two actual datasets for a turtle (Chrysemys picta) and a salamander (Plethodon cylindraceus). We subjected these datasets to four types of sampling biases corresponding to potential types of empirical biases. We applied five correction methods to the biased samples and compared the outputs of distribution models to unbiased datasets to assess the overall correction performance of each method. The results revealed that the ability of methods to correct the initial sampling bias varied greatly depending on bias type, bias intensity and species. However, the simple systematic sampling of records consistently ranked among the best performing across the range of conditions tested, whereas other methods performed more poorly in most cases. The strong effect of initial conditions on correction performance highlights the need for further research to develop a step-by-step guideline to account for sampling bias. However, this method seems to be the most efficient in correcting sampling bias and should be advised in most cases.

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

    Science.gov (United States)

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

    2015-06-01

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

  4. Regression dilution bias: tools for correction methods and sample size calculation.

    Science.gov (United States)

    Berglund, Lars

    2012-08-01

    Random errors in measurement of a risk factor will introduce downward bias of an estimated association to a disease or a disease marker. This phenomenon is called regression dilution bias. A bias correction may be made with data from a validity study or a reliability study. In this article we give a non-technical description of designs of reliability studies with emphasis on selection of individuals for a repeated measurement, assumptions of measurement error models, and correction methods for the slope in a simple linear regression model where the dependent variable is a continuous variable. Also, we describe situations where correction for regression dilution bias is not appropriate. The methods are illustrated with the association between insulin sensitivity measured with the euglycaemic insulin clamp technique and fasting insulin, where measurement of the latter variable carries noticeable random error. We provide software tools for estimation of a corrected slope in a simple linear regression model assuming data for a continuous dependent variable and a continuous risk factor from a main study and an additional measurement of the risk factor in a reliability study. Also, we supply programs for estimation of the number of individuals needed in the reliability study and for choice of its design. Our conclusion is that correction for regression dilution bias is seldom applied in epidemiological studies. This may cause important effects of risk factors with large measurement errors to be neglected.

  5. Assessing total nitrogen in surface-water samples--precision and bias of analytical and computational methods

    Science.gov (United States)

    Rus, David L.; Patton, Charles J.; Mueller, David K.; Crawford, Charles G.

    2013-01-01

    The characterization of total-nitrogen (TN) concentrations is an important component of many surface-water-quality programs. However, three widely used methods for the determination of total nitrogen—(1) derived from the alkaline-persulfate digestion of whole-water samples (TN-A); (2) calculated as the sum of total Kjeldahl nitrogen and dissolved nitrate plus nitrite (TN-K); and (3) calculated as the sum of dissolved nitrogen and particulate nitrogen (TN-C)—all include inherent limitations. A digestion process is intended to convert multiple species of nitrogen that are present in the sample into one measureable species, but this process may introduce bias. TN-A results can be negatively biased in the presence of suspended sediment, and TN-K data can be positively biased in the presence of elevated nitrate because some nitrate is reduced to ammonia and is therefore counted twice in the computation of total nitrogen. Furthermore, TN-C may not be subject to bias but is comparatively imprecise. In this study, the effects of suspended-sediment and nitrate concentrations on the performance of these TN methods were assessed using synthetic samples developed in a laboratory as well as a series of stream samples. A 2007 laboratory experiment measured TN-A and TN-K in nutrient-fortified solutions that had been mixed with varying amounts of sediment-reference materials. This experiment identified a connection between suspended sediment and negative bias in TN-A and detected positive bias in TN-K in the presence of elevated nitrate. A 2009–10 synoptic-field study used samples from 77 stream-sampling sites to confirm that these biases were present in the field samples and evaluated the precision and bias of TN methods. The precision of TN-C and TN-K depended on the precision and relative amounts of the TN-component species used in their respective TN computations. Particulate nitrogen had an average variability (as determined by the relative standard deviation) of 13

  6. Application of bias factor method using random sampling technique for prediction accuracy improvement of critical eigenvalue of BWR

    International Nuclear Information System (INIS)

    Ito, Motohiro; Endo, Tomohiro; Yamamoto, Akio; Kuroda, Yusuke; Yoshii, Takashi

    2017-01-01

    The bias factor method based on the random sampling technique is applied to the benchmark problem of Peach Bottom Unit 2. Validity and availability of the present method, i.e. correction of calculation results and reduction of uncertainty, are confirmed in addition to features and performance of the present method. In the present study, core characteristics in cycle 3 are corrected with the proposed method using predicted and 'measured' critical eigenvalues in cycles 1 and 2. As the source of uncertainty, variance-covariance of cross sections is considered. The calculation results indicate that bias between predicted and measured results, and uncertainty owing to cross section can be reduced. Extension to other uncertainties such as thermal hydraulics properties will be a future task. (author)

  7. Are most samples of animals systematically biased? Consistent individual trait differences bias samples despite random sampling.

    Science.gov (United States)

    Biro, Peter A

    2013-02-01

    Sampling animals from the wild for study is something nearly every biologist has done, but despite our best efforts to obtain random samples of animals, 'hidden' trait biases may still exist. For example, consistent behavioral traits can affect trappability/catchability, independent of obvious factors such as size and gender, and these traits are often correlated with other repeatable physiological and/or life history traits. If so, systematic sampling bias may exist for any of these traits. The extent to which this is a problem, of course, depends on the magnitude of bias, which is presently unknown because the underlying trait distributions in populations are usually unknown, or unknowable. Indeed, our present knowledge about sampling bias comes from samples (not complete population censuses), which can possess bias to begin with. I had the unique opportunity to create naturalized populations of fish by seeding each of four small fishless lakes with equal densities of slow-, intermediate-, and fast-growing fish. Using sampling methods that are not size-selective, I observed that fast-growing fish were up to two-times more likely to be sampled than slower-growing fish. This indicates substantial and systematic bias with respect to an important life history trait (growth rate). If correlations between behavioral, physiological and life-history traits are as widespread as the literature suggests, then many animal samples may be systematically biased with respect to these traits (e.g., when collecting animals for laboratory use), and affect our inferences about population structure and abundance. I conclude with a discussion on ways to minimize sampling bias for particular physiological/behavioral/life-history types within animal populations.

  8. Sampling methods

    International Nuclear Information System (INIS)

    Loughran, R.J.; Wallbrink, P.J.; Walling, D.E.; Appleby, P.G.

    2002-01-01

    Methods for the collection of soil samples to determine levels of 137 Cs and other fallout radionuclides, such as excess 210 Pb and 7 Be, will depend on the purposes (aims) of the project, site and soil characteristics, analytical capacity, the total number of samples that can be analysed and the sample mass required. The latter two will depend partly on detector type and capabilities. A variety of field methods have been developed for different field conditions and circumstances over the past twenty years, many of them inherited or adapted from soil science and sedimentology. The use of them inherited or adapted from soil science and sedimentology. The use of 137 Cs in erosion studies has been widely developed, while the application of fallout 210 Pb and 7 Be is still developing. Although it is possible to measure these nuclides simultaneously, it is common for experiments to designed around the use of 137 Cs along. Caesium studies typically involve comparison of the inventories found at eroded or sedimentation sites with that of a 'reference' site. An accurate characterization of the depth distribution of these fallout nuclides is often required in order to apply and/or calibrate the conversion models. However, depending on the tracer involved, the depth distribution, and thus the sampling resolution required to define it, differs. For example, a depth resolution of 1 cm is often adequate when using 137 Cs. However, fallout 210 Pb and 7 Be commonly has very strong surface maxima that decrease exponentially with depth, and fine depth increments are required at or close to the soil surface. Consequently, different depth incremental sampling methods are required when using different fallout radionuclides. Geomorphic investigations also frequently require determination of the depth-distribution of fallout nuclides on slopes and depositional sites as well as their total inventories

  9. Sampling bias in climate-conflict research

    Science.gov (United States)

    Adams, Courtland; Ide, Tobias; Barnett, Jon; Detges, Adrien

    2018-03-01

    Critics have argued that the evidence of an association between climate change and conflict is flawed because the research relies on a dependent variable sampling strategy1-4. Similarly, it has been hypothesized that convenience of access biases the sample of cases studied (the `streetlight effect'5). This also gives rise to claims that the climate-conflict literature stigmatizes some places as being more `naturally' violent6-8. Yet there has been no proof of such sampling patterns. Here we test whether climate-conflict research is based on such a biased sample through a systematic review of the literature. We demonstrate that research on climate change and violent conflict suffers from a streetlight effect. Further, studies which focus on a small number of cases in particular are strongly informed by cases where there has been conflict, do not sample on the independent variables (climate impact or risk), and hence tend to find some association between these two variables. These biases mean that research on climate change and conflict primarily focuses on a few accessible regions, overstates the links between both phenomena and cannot explain peaceful outcomes from climate change. This could result in maladaptive responses in those places that are stigmatized as being inherently more prone to climate-induced violence.

  10. Application of bias correction methods to improve U3Si2 sample preparation for quantitative analysis by WDXRF

    International Nuclear Information System (INIS)

    Scapin, Marcos A.; Guilhen, Sabine N.; Azevedo, Luciana C. de; Cotrim, Marycel E.B.; Pires, Maria Ap. F.

    2017-01-01

    The determination of silicon (Si), total uranium (U) and impurities in uranium-silicide (U 3 Si 2 ) samples by wavelength dispersion X-ray fluorescence technique (WDXRF) has been already validated and is currently implemented at IPEN's X-Ray Fluorescence Laboratory (IPEN-CNEN/SP) in São Paulo, Brazil. Sample preparation requires the use of approximately 3 g of H 3 BO 3 as sample holder and 1.8 g of U 3 Si 2 . However, because boron is a neutron absorber, this procedure precludes U 3 Si 2 sample's recovery, which, in time, considering routinely analysis, may account for significant unusable uranium waste. An estimated average of 15 samples per month are expected to be analyzed by WDXRF, resulting in approx. 320 g of U 3 Si 2 that would not return to the nuclear fuel cycle. This not only impacts in production losses, but generates another problem: radioactive waste management. The purpose of this paper is to present the mathematical models that may be applied for the correction of systematic errors when H 3 BO 3 sample holder is substituted by cellulose-acetate {[C 6 H 7 O 2 (OH) 3-m (OOCCH 3 )m], m = 0∼3}, thus enabling U 3 Si 2 sample’s recovery. The results demonstrate that the adopted mathematical model is statistically satisfactory, allowing the optimization of the procedure. (author)

  11. Moment and maximum likelihood estimators for Weibull distributions under length- and area-biased sampling

    Science.gov (United States)

    Jeffrey H. Gove

    2003-01-01

    Many of the most popular sampling schemes used in forestry are probability proportional to size methods. These methods are also referred to as size biased because sampling is actually from a weighted form of the underlying population distribution. Length- and area-biased sampling are special cases of size-biased sampling where the probability weighting comes from a...

  12. Bias Assessment of General Chemistry Analytes using Commutable Samples.

    Science.gov (United States)

    Koerbin, Gus; Tate, Jillian R; Ryan, Julie; Jones, Graham Rd; Sikaris, Ken A; Kanowski, David; Reed, Maxine; Gill, Janice; Koumantakis, George; Yen, Tina; St John, Andrew; Hickman, Peter E; Simpson, Aaron; Graham, Peter

    2014-11-01

    Harmonisation of reference intervals for routine general chemistry analytes has been a goal for many years. Analytical bias may prevent this harmonisation. To determine if analytical bias is present when comparing methods, the use of commutable samples, or samples that have the same properties as the clinical samples routinely analysed, should be used as reference samples to eliminate the possibility of matrix effect. The use of commutable samples has improved the identification of unacceptable analytical performance in the Netherlands and Spain. The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) has undertaken a pilot study using commutable samples in an attempt to determine not only country specific reference intervals but to make them comparable between countries. Australia and New Zealand, through the Australasian Association of Clinical Biochemists (AACB), have also undertaken an assessment of analytical bias using commutable samples and determined that of the 27 general chemistry analytes studied, 19 showed sufficiently small between method biases as to not prevent harmonisation of reference intervals. Application of evidence based approaches including the determination of analytical bias using commutable material is necessary when seeking to harmonise reference intervals.

  13. Adaptive enhanced sampling by force-biasing using neural networks

    Science.gov (United States)

    Guo, Ashley Z.; Sevgen, Emre; Sidky, Hythem; Whitmer, Jonathan K.; Hubbell, Jeffrey A.; de Pablo, Juan J.

    2018-04-01

    A machine learning assisted method is presented for molecular simulation of systems with rugged free energy landscapes. The method is general and can be combined with other advanced sampling techniques. In the particular implementation proposed here, it is illustrated in the context of an adaptive biasing force approach where, rather than relying on discrete force estimates, one can resort to a self-regularizing artificial neural network to generate continuous, estimated generalized forces. By doing so, the proposed approach addresses several shortcomings common to adaptive biasing force and other algorithms. Specifically, the neural network enables (1) smooth estimates of generalized forces in sparsely sampled regions, (2) force estimates in previously unexplored regions, and (3) continuous force estimates with which to bias the simulation, as opposed to biases generated at specific points of a discrete grid. The usefulness of the method is illustrated with three different examples, chosen to highlight the wide range of applicability of the underlying concepts. In all three cases, the new method is found to enhance considerably the underlying traditional adaptive biasing force approach. The method is also found to provide improvements over previous implementations of neural network assisted algorithms.

  14. SURVIVAL ANALYSIS AND LENGTH-BIASED SAMPLING

    Directory of Open Access Journals (Sweden)

    Masoud Asgharian

    2010-12-01

    Full Text Available When survival data are colleted as part of a prevalent cohort study, the recruited cases have already experienced their initiating event. These prevalent cases are then followed for a fixed period of time at the end of which the subjects will either have failed or have been censored. When interests lies in estimating the survival distribution, from onset, of subjects with the disease, one must take into account that the survival times of the cases in a prevalent cohort study are left truncated. When it is possible to assume that there has not been any epidemic of the disease over the past period of time that covers the onset times of the subjects, one may assume that the underlying incidence process that generates the initiating event times is a stationary Poisson process. Under such assumption, the survival times of the recruited subjects are called “lengthbiased”. I discuss the challenges one is faced with in analyzing these type of data. To address the theoretical aspects of the work, I present asymptotic results for the NPMLE of the length-biased as well as the unbiased survival distribution. I also discuss estimating the unbiased survival function using only the follow-up time. This addresses the case that the onset times are either unknown or known with uncertainty. Some of our most recent work and open questions will be presented. These include some aspects of analysis of covariates, strong approximation, functional LIL and density estimation under length-biased sampling with right censoring. The results will be illustrated with survival data from patients with dementia, collected as part of the Canadian Study of Health and Aging (CSHA.

  15. Sampling Realistic Protein Conformations Using Local Structural Bias

    DEFF Research Database (Denmark)

    Hamelryck, Thomas Wim; Kent, John T.; Krogh, A.

    2006-01-01

    The prediction of protein structure from sequence remains a major unsolved problem in biology. The most successful protein structure prediction methods make use of a divide-and-conquer strategy to attack the problem: a conformational sampling method generates plausible candidate structures, which...... are subsequently accepted or rejected using an energy function. Conceptually, this often corresponds to separating local structural bias from the long-range interactions that stabilize the compact, native state. However, sampling protein conformations that are compatible with the local structural bias encoded...... in a given protein sequence is a long-standing open problem, especially in continuous space. We describe an elegant and mathematically rigorous method to do this, and show that it readily generates native-like protein conformations simply by enforcing compactness. Our results have far-reaching implications...

  16. A method of language sampling

    DEFF Research Database (Denmark)

    Rijkhoff, Jan; Bakker, Dik; Hengeveld, Kees

    1993-01-01

    In recent years more attention is paid to the quality of language samples in typological work. Without an adequate sampling strategy, samples may suffer from various kinds of bias. In this article we propose a sampling method in which the genetic criterion is taken as the most important: samples...... to determine how many languages from each phylum should be selected, given any required sample size....

  17. Rational Learning and Information Sampling: On the "Naivety" Assumption in Sampling Explanations of Judgment Biases

    Science.gov (United States)

    Le Mens, Gael; Denrell, Jerker

    2011-01-01

    Recent research has argued that several well-known judgment biases may be due to biases in the available information sample rather than to biased information processing. Most of these sample-based explanations assume that decision makers are "naive": They are not aware of the biases in the available information sample and do not correct for them.…

  18. Heterogeneous Causal Effects and Sample Selection Bias

    DEFF Research Database (Denmark)

    Breen, Richard; Choi, Seongsoo; Holm, Anders

    2015-01-01

    The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists. Recently there has been growing interest not only in estimating the average causal effect of education on outcomes such as earnings, but also in estimating how...... causal effects might vary over individuals or groups. In this paper we point out one of the under-appreciated hazards of seeking to estimate heterogeneous causal effects: conventional selection bias (that is, selection on baseline differences) can easily be mistaken for heterogeneity of causal effects....... This might lead us to find heterogeneous effects when the true effect is homogenous, or to wrongly estimate not only the magnitude but also the sign of heterogeneous effects. We apply a test for the robustness of heterogeneous causal effects in the face of varying degrees and patterns of selection bias...

  19. A method of language sampling

    DEFF Research Database (Denmark)

    Rijkhoff, Jan; Bakker, Dik; Hengeveld, Kees

    1993-01-01

    In recent years more attention is paid to the quality of language samples in typological work. Without an adequate sampling strategy, samples may suffer from various kinds of bias. In this article we propose a sampling method in which the genetic criterion is taken as the most important: samples...... created with this method will reflect optimally the diversity of the languages of the world. On the basis of the internal structure of each genetic language tree a measure is computed that reflects the linguistic diversity in the language families represented by these trees. This measure is used...... to determine how many languages from each phylum should be selected, given any required sample size....

  20. Approach-Induced Biases in Human Information Sampling.

    Directory of Open Access Journals (Sweden)

    Laurence T Hunt

    2016-11-01

    Full Text Available Information sampling is often biased towards seeking evidence that confirms one's prior beliefs. Despite such biases being a pervasive feature of human behavior, their underlying causes remain unclear. Many accounts of these biases appeal to limitations of human hypothesis testing and cognition, de facto evoking notions of bounded rationality, but neglect more basic aspects of behavioral control. Here, we investigated a potential role for Pavlovian approach in biasing which information humans will choose to sample. We collected a large novel dataset from 32,445 human subjects, making over 3 million decisions, who played a gambling task designed to measure the latent causes and extent of information-sampling biases. We identified three novel approach-related biases, formalized by comparing subject behavior to a dynamic programming model of optimal information gathering. These biases reflected the amount of information sampled ("positive evidence approach", the selection of which information to sample ("sampling the favorite", and the interaction between information sampling and subsequent choices ("rejecting unsampled options". The prevalence of all three biases was related to a Pavlovian approach-avoid parameter quantified within an entirely independent economic decision task. Our large dataset also revealed that individual differences in the amount of information gathered are a stable trait across multiple gameplays and can be related to demographic measures, including age and educational attainment. As well as revealing limitations in cognitive processing, our findings suggest information sampling biases reflect the expression of primitive, yet potentially ecologically adaptive, behavioral repertoires. One such behavior is sampling from options that will eventually be chosen, even when other sources of information are more pertinent for guiding future action.

  1. Biased sampling, over-identified parameter problems and beyond

    CERN Document Server

    Qin, Jing

    2017-01-01

    This book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, renewal process and length biased sampling problems, capture and recapture problems, case cohort studies, exponential tilting genetic mixture models etc. The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others. .

  2. Comparison of sampling methods for animal manure

    NARCIS (Netherlands)

    Derikx, P.J.L.; Ogink, N.W.M.; Hoeksma, P.

    1997-01-01

    Currently available and recently developed sampling methods for slurry and solid manure were tested for bias and reproducibility in the determination of total phosphorus and nitrogen content of samples. Sampling methods were based on techniques in which samples were taken either during loading from

  3. Effect of sample size on bias correction performance

    Science.gov (United States)

    Reiter, Philipp; Gutjahr, Oliver; Schefczyk, Lukas; Heinemann, Günther; Casper, Markus C.

    2014-05-01

    The output of climate models often shows a bias when compared to observed data, so that a preprocessing is necessary before using it as climate forcing in impact modeling (e.g. hydrology, species distribution). A common bias correction method is the quantile matching approach, which adapts the cumulative distribution function of the model output to the one of the observed data by means of a transfer function. Especially for precipitation we expect the bias correction performance to strongly depend on sample size, i.e. the length of the period used for calibration of the transfer function. We carry out experiments using the precipitation output of ten regional climate model (RCM) hindcast runs from the EU-ENSEMBLES project and the E-OBS observational dataset for the period 1961 to 2000. The 40 years are split into a 30 year calibration period and a 10 year validation period. In the first step, for each RCM transfer functions are set up cell-by-cell, using the complete 30 year calibration period. The derived transfer functions are applied to the validation period of the respective RCM precipitation output and the mean absolute errors in reference to the observational dataset are calculated. These values are treated as "best fit" for the respective RCM. In the next step, this procedure is redone using subperiods out of the 30 year calibration period. The lengths of these subperiods are reduced from 29 years down to a minimum of 1 year, only considering subperiods of consecutive years. This leads to an increasing number of repetitions for smaller sample sizes (e.g. 2 for a length of 29 years). In the last step, the mean absolute errors are statistically tested against the "best fit" of the respective RCM to compare the performances. In order to analyze if the intensity of the effect of sample size depends on the chosen correction method, four variations of the quantile matching approach (PTF, QUANT/eQM, gQM, GQM) are applied in this study. The experiments are further

  4. Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

    Science.gov (United States)

    Verdery, Ashton M; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J

    2015-01-01

    This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.

  5. Addressing sampling bias in counting forest birds: a West African ...

    African Journals Online (AJOL)

    Addressing sampling bias in counting forest birds: a West African case study. ... result may occur because of the noise they may introduce into the analysis. ... used at all; and for all transects to reach their mid-point at the same time each day, ...

  6. A new configurational bias scheme for sampling supramolecular structures

    Energy Technology Data Exchange (ETDEWEB)

    De Gernier, Robin; Mognetti, Bortolo M., E-mail: bmognett@ulb.ac.be [Center for Nonlinear Phenomena and Complex Systems, Université Libre de Bruxelles, Code Postal 231, Campus Plaine, B-1050 Brussels (Belgium); Curk, Tine [Department of Chemistry, University of Cambridge, Cambridge CB2 1EW (United Kingdom); Dubacheva, Galina V. [Biosurfaces Unit, CIC biomaGUNE, Paseo Miramon 182, 20009 Donostia - San Sebastian (Spain); Richter, Ralf P. [Biosurfaces Unit, CIC biomaGUNE, Paseo Miramon 182, 20009 Donostia - San Sebastian (Spain); Université Grenoble Alpes, DCM, 38000 Grenoble (France); CNRS, DCM, 38000 Grenoble (France); Max Planck Institute for Intelligent Systems, 70569 Stuttgart (Germany)

    2014-12-28

    We present a new simulation scheme which allows an efficient sampling of reconfigurable supramolecular structures made of polymeric constructs functionalized by reactive binding sites. The algorithm is based on the configurational bias scheme of Siepmann and Frenkel and is powered by the possibility of changing the topology of the supramolecular network by a non-local Monte Carlo algorithm. Such a plan is accomplished by a multi-scale modelling that merges coarse-grained simulations, describing the typical polymer conformations, with experimental results accounting for free energy terms involved in the reactions of the active sites. We test the new algorithm for a system of DNA coated colloids for which we compute the hybridisation free energy cost associated to the binding of tethered single stranded DNAs terminated by short sequences of complementary nucleotides. In order to demonstrate the versatility of our method, we also consider polymers functionalized by receptors that bind a surface decorated by ligands. In particular, we compute the density of states of adsorbed polymers as a function of the number of ligand–receptor complexes formed. Such a quantity can be used to study the conformational properties of adsorbed polymers useful when engineering adsorption with tailored properties. We successfully compare the results with the predictions of a mean field theory. We believe that the proposed method will be a useful tool to investigate supramolecular structures resulting from direct interactions between functionalized polymers for which efficient numerical methodologies of investigation are still lacking.

  7. Application of bias correction methods to improve U{sub 3}Si{sub 2} sample preparation for quantitative analysis by WDXRF

    Energy Technology Data Exchange (ETDEWEB)

    Scapin, Marcos A.; Guilhen, Sabine N.; Azevedo, Luciana C. de; Cotrim, Marycel E.B.; Pires, Maria Ap. F., E-mail: mascapin@ipen.br, E-mail: snguilhen@ipen.br, E-mail: lvsantana@ipen.br, E-mail: mecotrim@ipen.br, E-mail: mapires@ipen.br [Instituto de Pesquisas Energéticas e Nucleares (IPEN/CNEN-SP), São Paulo, SP (Brazil)

    2017-07-01

    The determination of silicon (Si), total uranium (U) and impurities in uranium-silicide (U{sub 3}Si{sub 2}) samples by wavelength dispersion X-ray fluorescence technique (WDXRF) has been already validated and is currently implemented at IPEN's X-Ray Fluorescence Laboratory (IPEN-CNEN/SP) in São Paulo, Brazil. Sample preparation requires the use of approximately 3 g of H{sub 3}BO{sub 3} as sample holder and 1.8 g of U{sub 3}Si{sub 2}. However, because boron is a neutron absorber, this procedure precludes U{sub 3}Si{sub 2} sample's recovery, which, in time, considering routinely analysis, may account for significant unusable uranium waste. An estimated average of 15 samples per month are expected to be analyzed by WDXRF, resulting in approx. 320 g of U{sub 3}Si{sub 2} that would not return to the nuclear fuel cycle. This not only impacts in production losses, but generates another problem: radioactive waste management. The purpose of this paper is to present the mathematical models that may be applied for the correction of systematic errors when H{sub 3}BO{sub 3} sample holder is substituted by cellulose-acetate {[C_6H_7O_2(OH)_3_-_m(OOCCH_3)m], m = 0∼3}, thus enabling U{sub 3}Si{sub 2} sample’s recovery. The results demonstrate that the adopted mathematical model is statistically satisfactory, allowing the optimization of the procedure. (author)

  8. Rational learning and information sampling: on the "naivety" assumption in sampling explanations of judgment biases.

    Science.gov (United States)

    Le Mens, Gaël; Denrell, Jerker

    2011-04-01

    Recent research has argued that several well-known judgment biases may be due to biases in the available information sample rather than to biased information processing. Most of these sample-based explanations assume that decision makers are "naive": They are not aware of the biases in the available information sample and do not correct for them. Here, we show that this "naivety" assumption is not necessary. Systematically biased judgments can emerge even when decision makers process available information perfectly and are also aware of how the information sample has been generated. Specifically, we develop a rational analysis of Denrell's (2005) experience sampling model, and we prove that when information search is interested rather than disinterested, even rational information sampling and processing can give rise to systematic patterns of errors in judgments. Our results illustrate that a tendency to favor alternatives for which outcome information is more accessible can be consistent with rational behavior. The model offers a rational explanation for behaviors that had previously been attributed to cognitive and motivational biases, such as the in-group bias or the tendency to prefer popular alternatives. 2011 APA, all rights reserved

  9. Sampling system and method

    Science.gov (United States)

    Decker, David L.; Lyles, Brad F.; Purcell, Richard G.; Hershey, Ronald Lee

    2013-04-16

    The present disclosure provides an apparatus and method for coupling conduit segments together. A first pump obtains a sample and transmits it through a first conduit to a reservoir accessible by a second pump. The second pump further conducts the sample from the reservoir through a second conduit.

  10. Implicit and Explicit Weight Bias in a National Sample of 4732 Medical Students: The Medical Student CHANGES Study

    OpenAIRE

    Phelan, Sean M.; Dovidio, John F.; Puhl, Rebecca M.; Burgess, Diana J.; Nelson, David B.; Yeazel, Mark W.; Hardeman, Rachel; Perry, Sylvia; van Ryn, Michelle

    2014-01-01

    Objective To examine the magnitude of explicit and implicit weight biases compared to biases against other groups; and identify student factors predicting bias in a large national sample of medical students. Design and Methods A web-based survey was completed by 4732 1st year medical students from 49 medical schools as part of a longitudinal study of medical education. The survey included a validated measure of implicit weight bias, the implicit association test, and 2 measures of explicit bi...

  11. CEO emotional bias and investment decision, Bayesian network method

    Directory of Open Access Journals (Sweden)

    Jarboui Anis

    2012-08-01

    Full Text Available This research examines the determinants of firms’ investment introducing a behavioral perspective that has received little attention in corporate finance literature. The following central hypothesis emerges from a set of recently developed theories: Investment decisions are influenced not only by their fundamentals but also depend on some other factors. One factor is the biasness of any CEO to their investment, biasness depends on the cognition and emotions, because some leaders use them as heuristic for the investment decision instead of fundamentals. This paper shows how CEO emotional bias (optimism, loss aversion and overconfidence affects the investment decisions. The proposed model of this paper uses Bayesian Network Method to examine this relationship. Emotional bias has been measured by means of a questionnaire comprising several items. As for the selected sample, it has been composed of some 100 Tunisian executives. Our results have revealed that the behavioral analysis of investment decision implies leader affected by behavioral biases (optimism, loss aversion, and overconfidence adjusts its investment choices based on their ability to assess alternatives (optimism and overconfidence and risk perception (loss aversion to create of shareholder value and ensure its place at the head of the management team.

  12. Sampling bias in an internet treatment trial for depression.

    Science.gov (United States)

    Donkin, L; Hickie, I B; Christensen, H; Naismith, S L; Neal, B; Cockayne, N L; Glozier, N

    2012-10-23

    Internet psychological interventions are efficacious and may reduce traditional access barriers. No studies have evaluated whether any sampling bias exists in these trials that may limit the translation of the results of these trials into real-world application. We identified 7999 potentially eligible trial participants from a community-based health cohort study and invited them to participate in a randomized controlled trial of an online cognitive behavioural therapy programme for people with depression. We compared those who consented to being assessed for trial inclusion with nonconsenters on demographic, clinical and behavioural indicators captured in the health study. Any potentially biasing factors were then assessed for their association with depression outcome among trial participants to evaluate the existence of sampling bias. Of the 35 health survey variables explored, only 4 were independently associated with higher likelihood of consenting-female sex (odds ratio (OR) 1.11, 95% confidence interval (CI) 1.05-1.19), speaking English at home (OR 1.48, 95% CI 1.15-1.90) higher education (OR 1.67, 95% CI 1.46-1.92) and a prior diagnosis of depression (OR 1.37, 95% CI 1.22-1.55). The multivariate model accounted for limited variance (C-statistic 0.6) in explaining participation. These four factors were not significantly associated with either the primary trial outcome measure or any differential impact by intervention arm. This demonstrates that, among eligible trial participants, few factors were associated with the consent to participate. There was no indication that such self-selection biased the trial results or would limit the generalizability and translation into a public or clinical setting.

  13. Technical note: Alternatives to reduce adipose tissue sampling bias.

    Science.gov (United States)

    Cruz, G D; Wang, Y; Fadel, J G

    2014-10-01

    Understanding the mechanisms by which nutritional and pharmaceutical factors can manipulate adipose tissue growth and development in production animals has direct and indirect effects in the profitability of an enterprise. Adipocyte cellularity (number and size) is a key biological response that is commonly measured in animal science research. The variability and sampling of adipocyte cellularity within a muscle has been addressed in previous studies, but no attempt to critically investigate these issues has been proposed in the literature. The present study evaluated 2 sampling techniques (random and systematic) in an attempt to minimize sampling bias and to determine the minimum number of samples from 1 to 15 needed to represent the overall adipose tissue in the muscle. Both sampling procedures were applied on adipose tissue samples dissected from 30 longissimus muscles from cattle finished either on grass or grain. Briefly, adipose tissue samples were fixed with osmium tetroxide, and size and number of adipocytes were determined by a Coulter Counter. These results were then fit in a finite mixture model to obtain distribution parameters of each sample. To evaluate the benefits of increasing number of samples and the advantage of the new sampling technique, the concept of acceptance ratio was used; simply stated, the higher the acceptance ratio, the better the representation of the overall population. As expected, a great improvement on the estimation of the overall adipocyte cellularity parameters was observed using both sampling techniques when sample size number increased from 1 to 15 samples, considering both techniques' acceptance ratio increased from approximately 3 to 25%. When comparing sampling techniques, the systematic procedure slightly improved parameters estimation. The results suggest that more detailed research using other sampling techniques may provide better estimates for minimum sampling.

  14. Independent random sampling methods

    CERN Document Server

    Martino, Luca; Míguez, Joaquín

    2018-01-01

    This book systematically addresses the design and analysis of efficient techniques for independent random sampling. Both general-purpose approaches, which can be used to generate samples from arbitrary probability distributions, and tailored techniques, designed to efficiently address common real-world practical problems, are introduced and discussed in detail. In turn, the monograph presents fundamental results and methodologies in the field, elaborating and developing them into the latest techniques. The theory and methods are illustrated with a varied collection of examples, which are discussed in detail in the text and supplemented with ready-to-run computer code. The main problem addressed in the book is how to generate independent random samples from an arbitrary probability distribution with the weakest possible constraints or assumptions in a form suitable for practical implementation. The authors review the fundamental results and methods in the field, address the latest methods, and emphasize the li...

  15. Health indicators: eliminating bias from convenience sampling estimators.

    Science.gov (United States)

    Hedt, Bethany L; Pagano, Marcello

    2011-02-28

    Public health practitioners are often called upon to make inference about a health indicator for a population at large when the sole available information are data gathered from a convenience sample, such as data gathered on visitors to a clinic. These data may be of the highest quality and quite extensive, but the biases inherent in a convenience sample preclude the legitimate use of powerful inferential tools that are usually associated with a random sample. In general, we know nothing about those who do not visit the clinic beyond the fact that they do not visit the clinic. An alternative is to take a random sample of the population. However, we show that this solution would be wasteful if it excluded the use of available information. Hence, we present a simple annealing methodology that combines a relatively small, and presumably far less expensive, random sample with the convenience sample. This allows us to not only take advantage of powerful inferential tools, but also provides more accurate information than that available from just using data from the random sample alone. Copyright © 2011 John Wiley & Sons, Ltd.

  16. Radioactive air sampling methods

    CERN Document Server

    Maiello, Mark L

    2010-01-01

    Although the field of radioactive air sampling has matured and evolved over decades, it has lacked a single resource that assimilates technical and background information on its many facets. Edited by experts and with contributions from top practitioners and researchers, Radioactive Air Sampling Methods provides authoritative guidance on measuring airborne radioactivity from industrial, research, and nuclear power operations, as well as naturally occuring radioactivity in the environment. Designed for industrial hygienists, air quality experts, and heath physicists, the book delves into the applied research advancing and transforming practice with improvements to measurement equipment, human dose modeling of inhaled radioactivity, and radiation safety regulations. To present a wide picture of the field, it covers the international and national standards that guide the quality of air sampling measurements and equipment. It discusses emergency response issues, including radioactive fallout and the assets used ...

  17. Randomized Controlled Trial of Attention Bias Modification in a Racially Diverse, Socially Anxious, Alcohol Dependent Sample

    Science.gov (United States)

    Clerkin, Elise M.; Magee, Joshua C.; Wells, Tony T.; Beard, Courtney; Barnett, Nancy P.

    2016-01-01

    Objective Attention biases may be an important treatment target for both alcohol dependence and social anxiety. This is the first ABM trial to investigate two (vs. one) targets of attention bias within a sample with co-occurring symptoms of social anxiety and alcohol dependence. Additionally, we used trial-level bias scores (TL-BS) to capture the phenomena of attention bias in a more ecologically valid, dynamic way compared to traditional attention bias scores. Method Adult participants (N=86; 41% Female; 52% African American; 40% White) with elevated social anxiety symptoms and alcohol dependence were randomly assigned to an 8-session training condition in this 2 (Social Anxiety ABM vs. Social Anxiety Control) by 2 (Alcohol ABM vs. Alcohol Control) design. Symptoms of social anxiety, alcohol dependence, and attention bias were assessed across time. Results Multilevel models estimated the trajectories for each measure within individuals, and tested whether these trajectories differed according to the randomized training conditions. Across time, there were significant or trending decreases in all attention TL-BS parameters (but not traditional attention bias scores) and most symptom measures. However, there were not significant differences in the trajectories of change between any ABM and control conditions for any symptom measures. Conclusions These findings add to previous evidence questioning the robustness of ABM and point to the need to extend the effects of ABM to samples that are racially diverse and/or have co-occurring psychopathology. The results also illustrate the potential importance of calculating trial-level attention bias scores rather than only including traditional bias scores. PMID:27591918

  18. Bespoke Bias for Obtaining Free Energy Differences within Variationally Enhanced Sampling.

    Science.gov (United States)

    McCarty, James; Valsson, Omar; Parrinello, Michele

    2016-05-10

    Obtaining efficient sampling of multiple metastable states through molecular dynamics and hence determining free energy differences is central for understanding many important phenomena. Here we present a new biasing strategy, which employs the recent variationally enhanced sampling approach (Valsson and Parrinello Phys. Rev. Lett. 2014, 113, 090601). The bias is constructed from an intuitive model of the local free energy surface describing fluctuations around metastable minima and depends on only a few parameters which are determined variationally such that efficient sampling between states is obtained. The bias constructed in this manner largely reduces the need of finding a set of collective variables that completely spans the conformational space of interest, as they only need to be a locally valid descriptor of the system about its local minimum. We introduce the method and demonstrate its power on two representative examples.

  19. Systematic bias in genomic classification due to contaminating non-neoplastic tissue in breast tumor samples.

    Science.gov (United States)

    Elloumi, Fathi; Hu, Zhiyuan; Li, Yan; Parker, Joel S; Gulley, Margaret L; Amos, Keith D; Troester, Melissa A

    2011-06-30

    Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification. To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors. Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability. Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor.

  20. Bias of shear wave elasticity measurements in thin layer samples and a simple correction strategy.

    Science.gov (United States)

    Mo, Jianqiang; Xu, Hao; Qiang, Bo; Giambini, Hugo; Kinnick, Randall; An, Kai-Nan; Chen, Shigao; Luo, Zongping

    2016-01-01

    Shear wave elastography (SWE) is an emerging technique for measuring biological tissue stiffness. However, the application of SWE in thin layer tissues is limited by bias due to the influence of geometry on measured shear wave speed. In this study, we investigated the bias of Young's modulus measured by SWE in thin layer gelatin-agar phantoms, and compared the result with finite element method and Lamb wave model simulation. The result indicated that the Young's modulus measured by SWE decreased continuously when the sample thickness decreased, and this effect was more significant for smaller thickness. We proposed a new empirical formula which can conveniently correct the bias without the need of using complicated mathematical modeling. In summary, we confirmed the nonlinear relation between thickness and Young's modulus measured by SWE in thin layer samples, and offered a simple and practical correction strategy which is convenient for clinicians to use.

  1. Publication Bias in Psychology: A Diagnosis Based on the Correlation between Effect Size and Sample Size

    Science.gov (United States)

    Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

    2014-01-01

    Background The p value obtained from a significance test provides no information about the magnitude or importance of the underlying phenomenon. Therefore, additional reporting of effect size is often recommended. Effect sizes are theoretically independent from sample size. Yet this may not hold true empirically: non-independence could indicate publication bias. Methods We investigate whether effect size is independent from sample size in psychological research. We randomly sampled 1,000 psychological articles from all areas of psychological research. We extracted p values, effect sizes, and sample sizes of all empirical papers, and calculated the correlation between effect size and sample size, and investigated the distribution of p values. Results We found a negative correlation of r = −.45 [95% CI: −.53; −.35] between effect size and sample size. In addition, we found an inordinately high number of p values just passing the boundary of significance. Additional data showed that neither implicit nor explicit power analysis could account for this pattern of findings. Conclusion The negative correlation between effect size and samples size, and the biased distribution of p values indicate pervasive publication bias in the entire field of psychology. PMID:25192357

  2. Variance bias analysis for the Gelbard's batch method

    Energy Technology Data Exchange (ETDEWEB)

    Seo, Jae Uk; Shim, Hyung Jin [Seoul National Univ., Seoul (Korea, Republic of)

    2014-05-15

    In this paper, variances and the bias will be derived analytically when the Gelbard's batch method is applied. And then, the real variance estimated from this bias will be compared with the real variance calculated from replicas. Variance and the bias were derived analytically when the batch method was applied. If the batch method was applied to calculate the sample variance, covariance terms between tallies which exist in the batch were eliminated from the bias. With the 2 by 2 fission matrix problem, we could calculate real variance regardless of whether or not the batch method was applied. However as batch size got larger, standard deviation of real variance was increased. When we perform a Monte Carlo estimation, we could get a sample variance as the statistical uncertainty of it. However, this value is smaller than the real variance of it because a sample variance is biased. To reduce this bias, Gelbard devised the method which is called the Gelbard's batch method. It has been certificated that a sample variance get closer to the real variance when the batch method is applied. In other words, the bias get reduced. This fact is well known to everyone in the MC field. However, so far, no one has given the analytical interpretation on it.

  3. Correction of sampling bias in a cross-sectional study of post-surgical complications.

    Science.gov (United States)

    Fluss, Ronen; Mandel, Micha; Freedman, Laurence S; Weiss, Inbal Salz; Zohar, Anat Ekka; Haklai, Ziona; Gordon, Ethel-Sherry; Simchen, Elisheva

    2013-06-30

    Cross-sectional designs are often used to monitor the proportion of infections and other post-surgical complications acquired in hospitals. However, conventional methods for estimating incidence proportions when applied to cross-sectional data may provide estimators that are highly biased, as cross-sectional designs tend to include a high proportion of patients with prolonged hospitalization. One common solution is to use sampling weights in the analysis, which adjust for the sampling bias inherent in a cross-sectional design. The current paper describes in detail a method to build weights for a national survey of post-surgical complications conducted in Israel. We use the weights to estimate the probability of surgical site infections following colon resection, and validate the results of the weighted analysis by comparing them with those obtained from a parallel study with a historically prospective design. Copyright © 2012 John Wiley & Sons, Ltd.

  4. The lack of selection bias in a snowball sampled case-control study on drug abuse.

    Science.gov (United States)

    Lopes, C S; Rodrigues, L C; Sichieri, R

    1996-12-01

    Friend controls in matched case-control studies can be a potential source of bias based on the assumption that friends are more likely to share exposure factors. This study evaluates the role of selection bias in a case-control study that used the snowball sampling method based on friendship for the selection of cases and controls. The cases selected fro the study were drug abusers located in the community. Exposure was defined by the presence of at least one psychiatric diagnosis. Psychiatric and drug abuse/dependence diagnoses were made according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R) criteria. Cases and controls were matched on sex, age and friendship. The measurement of selection bias was made through the comparison of the proportion of exposed controls selected by exposed cases (p1) with the proportion of exposed controls selected by unexposed cases (p2). If p1 = p2 then, selection bias should not occur. The observed distribution of the 185 matched pairs having at least one psychiatric disorder showed a p1 value of 0.52 and a p2 value of 0.51, indicating no selection bias in this study. Our findings support the idea that the use of friend controls can produce a valid basis for a case-control study.

  5. An experimental verification of laser-velocimeter sampling bias and its correction

    Science.gov (United States)

    Johnson, D. A.; Modarress, D.; Owen, F. K.

    1982-01-01

    The existence of 'sampling bias' in individual-realization laser velocimeter measurements is experimentally verified and shown to be independent of sample rate. The experiments were performed in a simple two-stream mixing shear flow with the standard for comparison being laser-velocimeter results obtained under continuous-wave conditions. It is also demonstrated that the errors resulting from sampling bias can be removed by a proper interpretation of the sampling statistics. In addition, data obtained in a shock-induced separated flow and in the near-wake of airfoils are presented, both bias-corrected and uncorrected, to illustrate the effects of sampling bias in the extreme.

  6. The Impact of Selection, Gene Conversion, and Biased Sampling on the Assessment of Microbial Demography.

    Science.gov (United States)

    Lapierre, Marguerite; Blin, Camille; Lambert, Amaury; Achaz, Guillaume; Rocha, Eduardo P C

    2016-07-01

    Recent studies have linked demographic changes and epidemiological patterns in bacterial populations using coalescent-based approaches. We identified 26 studies using skyline plots and found that 21 inferred overall population expansion. This surprising result led us to analyze the impact of natural selection, recombination (gene conversion), and sampling biases on demographic inference using skyline plots and site frequency spectra (SFS). Forward simulations based on biologically relevant parameters from Escherichia coli populations showed that theoretical arguments on the detrimental impact of recombination and especially natural selection on the reconstructed genealogies cannot be ignored in practice. In fact, both processes systematically lead to spurious interpretations of population expansion in skyline plots (and in SFS for selection). Weak purifying selection, and especially positive selection, had important effects on skyline plots, showing patterns akin to those of population expansions. State-of-the-art techniques to remove recombination further amplified these biases. We simulated three common sampling biases in microbiological research: uniform, clustered, and mixed sampling. Alone, or together with recombination and selection, they further mislead demographic inferences producing almost any possible skyline shape or SFS. Interestingly, sampling sub-populations also affected skyline plots and SFS, because the coalescent rates of populations and their sub-populations had different distributions. This study suggests that extreme caution is needed to infer demographic changes solely based on reconstructed genealogies. We suggest that the development of novel sampling strategies and the joint analyzes of diverse population genetic methods are strictly necessary to estimate demographic changes in populations where selection, recombination, and biased sampling are present. © The Author 2016. Published by Oxford University Press on behalf of the Society for

  7. Spanish exit polls. Sampling error or nonresponse bias?

    Directory of Open Access Journals (Sweden)

    Pavía, Jose M.

    2016-09-01

    Full Text Available Countless examples of misleading forecasts on behalf of both pre-election and exit polls can be found all over the world. Non-representative samples due to differential nonresponse have been claimed as being the main reason for inaccurate exit-poll projections. In real inference problems, it is seldom possible to compare estimates and true values. Electoral forecasts are an exception. Comparisons between estimates and final outcomes can be carried out once votes have been tallied. In this paper, we examine the raw data collected in seven exit polls conducted in Spain and test the likelihood that the data collected in each sampled voting location can be considered as a random sample of actual results. Knowing the answer to this is relevant for both electoral analysts and forecasters as, if the hypothesis is rejected, the shortcomings of the collected data would need amending. Analysts could improve the quality of their computations by implementing local correction strategies. We find strong evidence of nonsampling error in Spanish exit polls and evidence that the political context matters. Nonresponse bias is larger in polarized elections and in a climate of fearExiste un gran número de ejemplos de predicciones inexactas obtenidas a partir tanto de encuestas pre-electorales como de encuestas a pie de urna a lo largo del mundo. La presencia de tasas de no-respuesta diferencial entre distintos tipos de electores ha sido la principal razón esgrimida para justificar las proyecciones erróneas en las encuestas a pie de urna. En problemas de inferencia rara vez es posible comparar estimaciones y valores reales. Las predicciones electorales son una excepción. La comparación entre estimaciones y resultados finales puede realizarse una vez los votos han sido contabilizados. En este trabajo, examinamos los datos brutos recogidos en siete encuestas a pie de urna realizadas en España y testamos la hipótesis de que los datos recolectados en cada punto

  8. Introducing etch kernels for efficient pattern sampling and etch bias prediction

    Science.gov (United States)

    Weisbuch, François; Lutich, Andrey; Schatz, Jirka

    2018-01-01

    Successful patterning requires good control of the photolithography and etch processes. While compact litho models, mainly based on rigorous physics, can predict very well the contours printed in photoresist, pure empirical etch models are less accurate and more unstable. Compact etch models are based on geometrical kernels to compute the litho-etch biases that measure the distance between litho and etch contours. The definition of the kernels, as well as the choice of calibration patterns, is critical to get a robust etch model. This work proposes to define a set of independent and anisotropic etch kernels-"internal, external, curvature, Gaussian, z_profile"-designed to represent the finest details of the resist geometry to characterize precisely the etch bias at any point along a resist contour. By evaluating the etch kernels on various structures, it is possible to map their etch signatures in a multidimensional space and analyze them to find an optimal sampling of structures. The etch kernels evaluated on these structures were combined with experimental etch bias derived from scanning electron microscope contours to train artificial neural networks to predict etch bias. The method applied to contact and line/space layers shows an improvement in etch model prediction accuracy over standard etch model. This work emphasizes the importance of the etch kernel definition to characterize and predict complex etch effects.

  9. Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies

    Science.gov (United States)

    Theis, Fabian J.

    2017-01-01

    Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package sambia. PMID:29312464

  10. A new method to measure galaxy bias by combining the density and weak lensing fields

    Energy Technology Data Exchange (ETDEWEB)

    Pujol, Arnau; Chang, Chihway; Gaztañaga, Enrique; Amara, Adam; Refregier, Alexandre; Bacon, David J.; Carretero, Jorge; Castander, Francisco J.; Crocce, Martin; Fosalba, Pablo; Manera, Marc; Vikram, Vinu

    2016-07-29

    We present a new method to measure redshift-dependent galaxy bias by combining information from the galaxy density field and the weak lensing field. This method is based on the work of Amara et al., who use the galaxy density field to construct a bias-weighted convergence field κg. The main difference between Amara et al.'s work and our new implementation is that here we present another way to measure galaxy bias, using tomography instead of bias parametrizations. The correlation between κg and the true lensing field κ allows us to measure galaxy bias using different zero-lag correlations, such as <κgκ>/<κκ> or <κgκg>/<κgκ>. Our method measures the linear bias factor on linear scales, under the assumption of no stochasticity between galaxies and matter. We use the Marenostrum Institut de Ciències de l'Espai (MICE) simulation to measure the linear galaxy bias for a flux-limited sample (i < 22.5) in tomographic redshift bins using this method. This article is the first that studies the accuracy and systematic uncertainties associated with the implementation of the method and the regime in which it is consistent with the linear galaxy bias defined by projected two-point correlation functions (2PCF). We find that our method is consistent with a linear bias at the per cent level for scales larger than 30 arcmin, while non-linearities appear at smaller scales. This measurement is a good complement to other measurements of bias, since it does not depend strongly on σ8 as do the 2PCF measurements. We will apply this method to the Dark Energy Survey Science Verification data in a follow-up article.

  11. Semiparametric efficient and robust estimation of an unknown symmetric population under arbitrary sample selection bias

    KAUST Repository

    Ma, Yanyuan

    2013-09-01

    We propose semiparametric methods to estimate the center and shape of a symmetric population when a representative sample of the population is unavailable due to selection bias. We allow an arbitrary sample selection mechanism determined by the data collection procedure, and we do not impose any parametric form on the population distribution. Under this general framework, we construct a family of consistent estimators of the center that is robust to population model misspecification, and we identify the efficient member that reaches the minimum possible estimation variance. The asymptotic properties and finite sample performance of the estimation and inference procedures are illustrated through theoretical analysis and simulations. A data example is also provided to illustrate the usefulness of the methods in practice. © 2013 American Statistical Association.

  12. The Threat of Common Method Variance Bias to Theory Building

    Science.gov (United States)

    Reio, Thomas G., Jr.

    2010-01-01

    The need for more theory building scholarship remains one of the pressing issues in the field of HRD. Researchers can employ quantitative, qualitative, and/or mixed methods to support vital theory-building efforts, understanding however that each approach has its limitations. The purpose of this article is to explore common method variance bias as…

  13. A new method for mapping perceptual biases across visual space.

    Science.gov (United States)

    Finlayson, Nonie J; Papageorgiou, Andriani; Schwarzkopf, D Samuel

    2017-08-01

    How we perceive the environment is not stable and seamless. Recent studies found that how a person qualitatively experiences even simple visual stimuli varies dramatically across different locations in the visual field. Here we use a method we developed recently that we call multiple alternatives perceptual search (MAPS) for efficiently mapping such perceptual biases across several locations. This procedure reliably quantifies the spatial pattern of perceptual biases and also of uncertainty and choice. We show that these measurements are strongly correlated with those from traditional psychophysical methods and that exogenous attention can skew biases without affecting overall task performance. Taken together, MAPS is an efficient method to measure how an individual's perceptual experience varies across space.

  14. A Study of Assimilation Bias in Name-Based Sampling of Migrants

    Directory of Open Access Journals (Sweden)

    Schnell Rainer

    2014-06-01

    Full Text Available The use of personal names for screening is an increasingly popular sampling technique for migrant populations. Although this is often an effective sampling procedure, very little is known about the properties of this method. Based on a large German survey, this article compares characteristics of respondents whose names have been correctly classified as belonging to a migrant population with respondentswho aremigrants and whose names have not been classified as belonging to a migrant population. Although significant differences were found for some variables even with some large effect sizes, the overall bias introduced by name-based sampling (NBS is small as long as procedures with small false-negative rates are employed.

  15. Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

    Science.gov (United States)

    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.

  16. Statistical methods for accurately determining criticality code bias

    International Nuclear Information System (INIS)

    Trumble, E.F.; Kimball, K.D.

    1997-01-01

    A system of statistically treating validation calculations for the purpose of determining computer code bias is provided in this paper. The following statistical treatments are described: weighted regression analysis, lower tolerance limit, lower tolerance band, and lower confidence band. These methods meet the criticality code validation requirements of ANS 8.1. 8 refs., 5 figs., 4 tabs

  17. Characterizing sampling and quality screening biases in infrared and microwave limb sounding

    Science.gov (United States)

    Millán, Luis F.; Livesey, Nathaniel J.; Santee, Michelle L.; von Clarmann, Thomas

    2018-03-01

    This study investigates orbital sampling biases and evaluates the additional impact caused by data quality screening for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Aura Microwave Limb Sounder (MLS). MIPAS acts as a proxy for typical infrared limb emission sounders, while MLS acts as a proxy for microwave limb sounders. These biases were calculated for temperature and several trace gases by interpolating model fields to real sampling patterns and, additionally, screening those locations as directed by their corresponding quality criteria. Both instruments have dense uniform sampling patterns typical of limb emission sounders, producing almost identical sampling biases. However, there is a substantial difference between the number of locations discarded. MIPAS, as a mid-infrared instrument, is very sensitive to clouds, and measurements affected by them are thus rejected from the analysis. For example, in the tropics, the MIPAS yield is strongly affected by clouds, while MLS is mostly unaffected. The results show that upper-tropospheric sampling biases in zonally averaged data, for both instruments, can be up to 10 to 30 %, depending on the species, and up to 3 K for temperature. For MIPAS, the sampling reduction due to quality screening worsens the biases, leading to values as large as 30 to 100 % for the trace gases and expanding the 3 K bias region for temperature. This type of sampling bias is largely induced by the geophysical origins of the screening (e.g. clouds). Further, analysis of long-term time series reveals that these additional quality screening biases may affect the ability to accurately detect upper-tropospheric long-term changes using such data. In contrast, MLS data quality screening removes sufficiently few points that no additional bias is introduced, although its penetration is limited to the upper troposphere, while MIPAS may cover well into the mid-troposphere in cloud-free scenarios. We emphasize that the

  18. ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION

    Energy Technology Data Exchange (ETDEWEB)

    Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J. [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States); Brink, Henrik [Dark Cosmology Centre, Juliane Maries Vej 30, 2100 Copenhagen O (Denmark); Long, James P.; Rice, John, E-mail: jwrichar@stat.berkeley.edu [Statistics Department, University of California, Berkeley, CA 94720-7450 (United States)

    2012-01-10

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL-where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up-is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  19. ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION

    International Nuclear Information System (INIS)

    Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J.; Brink, Henrik; Long, James P.; Rice, John

    2012-01-01

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  20. Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification

    Science.gov (United States)

    Richards, Joseph W.; Starr, Dan L.; Brink, Henrik; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; James, J. Berian; Long, James P.; Rice, John

    2012-01-01

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  1. Biomass and abundance biases in European standard gillnet sampling

    Czech Academy of Sciences Publication Activity Database

    Šmejkal, Marek; Ricard, Daniel; Prchalová, Marie; Říha, Milan; Muška, Milan; Blabolil, Petr; Čech, Martin; Vašek, Mojmír; Jůza, Tomáš; Herreras, A.M.; Encina, L.; Peterka, Jiří; Kubečka, Jan

    2015-01-01

    Roč. 10, č. 3 (2015), e0122437 E-ISSN 1932-6203 R&D Projects: GA MŠk(CZ) EE2.3.20.0204; GA ČR(CZ) GPP505/12/P647; GA MŠk(CZ) EE2.3.30.0032 Institutional support: RVO:60077344 Keywords : fish sampling * gillnets * large meshes * mesh size selectivity * Improvement of European standard EN 14757 * bream (Abramis brama) Subject RIV: GL - Fishing Impact factor: 3.057, year: 2015

  2. Autocalibration method for non-stationary CT bias correction.

    Science.gov (United States)

    Vegas-Sánchez-Ferrero, Gonzalo; Ledesma-Carbayo, Maria J; Washko, George R; Estépar, Raúl San José

    2018-02-01

    Computed tomography (CT) is a widely used imaging modality for screening and diagnosis. However, the deleterious effects of radiation exposure inherent in CT imaging require the development of image reconstruction methods which can reduce exposure levels. The development of iterative reconstruction techniques is now enabling the acquisition of low-dose CT images whose quality is comparable to that of CT images acquired with much higher radiation dosages. However, the characterization and calibration of the CT signal due to changes in dosage and reconstruction approaches is crucial to provide clinically relevant data. Although CT scanners are calibrated as part of the imaging workflow, the calibration is limited to select global reference values and does not consider other inherent factors of the acquisition that depend on the subject scanned (e.g. photon starvation, partial volume effect, beam hardening) and result in a non-stationary noise response. In this work, we analyze the effect of reconstruction biases caused by non-stationary noise and propose an autocalibration methodology to compensate it. Our contributions are: 1) the derivation of a functional relationship between observed bias and non-stationary noise, 2) a robust and accurate method to estimate the local variance, 3) an autocalibration methodology that does not necessarily rely on a calibration phantom, attenuates the bias caused by noise and removes the systematic bias observed in devices from different vendors. The validation of the proposed methodology was performed with a physical phantom and clinical CT scans acquired with different configurations (kernels, doses, algorithms including iterative reconstruction). The results confirmed the suitability of the proposed methods for removing the intra-device and inter-device reconstruction biases. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. SWOT ANALYSIS ON SAMPLING METHOD

    Directory of Open Access Journals (Sweden)

    CHIS ANCA OANA

    2014-07-01

    Full Text Available Audit sampling involves the application of audit procedures to less than 100% of items within an account balance or class of transactions. Our article aims to study audit sampling in audit of financial statements. As an audit technique largely used, in both its statistical and nonstatistical form, the method is very important for auditors. It should be applied correctly for a fair view of financial statements, to satisfy the needs of all financial users. In order to be applied correctly the method must be understood by all its users and mainly by auditors. Otherwise the risk of not applying it correctly would cause loose of reputation and discredit, litigations and even prison. Since there is not a unitary practice and methodology for applying the technique, the risk of incorrectly applying it is pretty high. The SWOT analysis is a technique used that shows the advantages, disadvantages, threats and opportunities. We applied SWOT analysis in studying the sampling method, from the perspective of three players: the audit company, the audited entity and users of financial statements. The study shows that by applying the sampling method the audit company and the audited entity both save time, effort and money. The disadvantages of the method are difficulty in applying and understanding its insight. Being largely used as an audit method and being a factor of a correct audit opinion, the sampling method’s advantages, disadvantages, threats and opportunities must be understood by auditors.

  4. A note on exponential dispersion models which are invariant under length-biased sampling

    NARCIS (Netherlands)

    Bar-Lev, S.K.; van der Duyn Schouten, F.A.

    2003-01-01

    Length-biased sampling situations may occur in clinical trials, reliability, queueing models, survival analysis and population studies where a proper sampling frame is absent.In such situations items are sampled at rate proportional to their length so that larger values of the quantity being

  5. Distance sampling methods and applications

    CERN Document Server

    Buckland, S T; Marques, T A; Oedekoven, C S

    2015-01-01

    In this book, the authors cover the basic methods and advances within distance sampling that are most valuable to practitioners and in ecology more broadly. This is the fourth book dedicated to distance sampling. In the decade since the last book published, there have been a number of new developments. The intervening years have also shown which advances are of most use. This self-contained book covers topics from the previous publications, while also including recent developments in method, software and application. Distance sampling refers to a suite of methods, including line and point transect sampling, in which animal density or abundance is estimated from a sample of distances to detected individuals. The book illustrates these methods through case studies; data sets and computer code are supplied to readers through the book’s accompanying website.  Some of the case studies use the software Distance, while others use R code. The book is in three parts.  The first part addresses basic methods, the ...

  6. A method of bias correction for maximal reliability with dichotomous measures.

    Science.gov (United States)

    Penev, Spiridon; Raykov, Tenko

    2010-02-01

    This paper is concerned with the reliability of weighted combinations of a given set of dichotomous measures. Maximal reliability for such measures has been discussed in the past, but the pertinent estimator exhibits a considerable bias and mean squared error for moderate sample sizes. We examine this bias, propose a procedure for bias correction, and develop a more accurate asymptotic confidence interval for the resulting estimator. In most empirically relevant cases, the bias correction and mean squared error correction can be performed simultaneously. We propose an approximate (asymptotic) confidence interval for the maximal reliability coefficient, discuss the implementation of this estimator, and investigate the mean squared error of the associated asymptotic approximation. We illustrate the proposed methods using a numerical example.

  7. Sampling Methods for Wallenius' and Fisher's Noncentral Hypergeometric Distributions

    DEFF Research Database (Denmark)

    Fog, Agner

    2008-01-01

    the mode, ratio-of-uniforms rejection method, and rejection by sampling in the tau domain. Methods for the multivariate distributions include: simulation of urn experiments, conditional method, Gibbs sampling, and Metropolis-Hastings sampling. These methods are useful for Monte Carlo simulation of models...... of biased sampling and models of evolution and for calculating moments and quantiles of the distributions.......Several methods for generating variates with univariate and multivariate Wallenius' and Fisher's noncentral hypergeometric distributions are developed. Methods for the univariate distributions include: simulation of urn experiments, inversion by binary search, inversion by chop-down search from...

  8. RNA preservation agents and nucleic acid extraction method bias perceived bacterial community composition.

    Directory of Open Access Journals (Sweden)

    Ann McCarthy

    Full Text Available Bias is a pervasive problem when characterizing microbial communities. An important source is the difference in lysis efficiencies of different populations, which vary depending on the extraction protocol used. To avoid such biases impacting comparisons between gene and transcript abundances in the environment, the use of one protocol that simultaneously extracts both types of nucleic acids from microbial community samples has gained popularity. However, knowledge regarding tradeoffs to combined nucleic acid extraction protocols is limited, particularly regarding yield and biases in the observed community composition. Here, we evaluated a commercially available protocol for simultaneous extraction of DNA and RNA, which we adapted for freshwater microbial community samples that were collected on filters. DNA and RNA yields were comparable to other commonly used, but independent DNA and RNA extraction protocols. RNA protection agents benefited RNA quality, but decreased DNA yields significantly. Choice of extraction protocol influenced the perceived bacterial community composition, with strong method-dependent biases observed for specific phyla such as the Verrucomicrobia. The combined DNA/RNA extraction protocol detected significantly higher levels of Verrucomicrobia than the other protocols, and those higher numbers were confirmed by microscopic analysis. Use of RNA protection agents as well as independent sequencing runs caused a significant shift in community composition as well, albeit smaller than the shift caused by using different extraction protocols. Despite methodological biases, sample origin was the strongest determinant of community composition. However, when the abundance of specific phylogenetic groups is of interest, researchers need to be aware of the biases their methods introduce. This is particularly relevant if different methods are used for DNA and RNA extraction, in addition to using RNA protection agents only for RNA

  9. Randomized controlled trial of attention bias modification in a racially diverse, socially anxious, alcohol dependent sample.

    Science.gov (United States)

    Clerkin, Elise M; Magee, Joshua C; Wells, Tony T; Beard, Courtney; Barnett, Nancy P

    2016-12-01

    Attention biases may be an important treatment target for both alcohol dependence and social anxiety. This is the first ABM trial to investigate two (vs. one) targets of attention bias within a sample with co-occurring symptoms of social anxiety and alcohol dependence. Additionally, we used trial-level bias scores (TL-BS) to capture the phenomena of attention bias in a more ecologically valid, dynamic way compared to traditional attention bias scores. Adult participants (N = 86; 41% Female; 52% African American; 40% White) with elevated social anxiety symptoms and alcohol dependence were randomly assigned to an 8-session training condition in this 2 (Social Anxiety ABM vs. Social Anxiety Control) by 2 (Alcohol ABM vs. Alcohol Control) design. Symptoms of social anxiety, alcohol dependence, and attention bias were assessed across time. Multilevel models estimated the trajectories for each measure within individuals, and tested whether these trajectories differed according to the randomized training conditions. Across time, there were significant or trending decreases in all attention TL-BS parameters (but not traditional attention bias scores) and most symptom measures. However, there were not significant differences in the trajectories of change between any ABM and control conditions for any symptom measures. These findings add to previous evidence questioning the robustness of ABM and point to the need to extend the effects of ABM to samples that are racially diverse and/or have co-occurring psychopathology. The results also illustrate the potential importance of calculating trial-level attention bias scores rather than only including traditional bias scores. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Estimation of time-delayed mutual information and bias for irregularly and sparsely sampled time-series

    International Nuclear Information System (INIS)

    Albers, D.J.; Hripcsak, George

    2012-01-01

    Highlights: ► Time-delayed mutual information for irregularly sampled time-series. ► Estimation bias for the time-delayed mutual information calculation. ► Fast, simple, PDF estimator independent, time-delayed mutual information bias estimate. ► Quantification of data-set-size limits of the time-delayed mutual calculation. - Abstract: A method to estimate the time-dependent correlation via an empirical bias estimate of the time-delayed mutual information for a time-series is proposed. In particular, the bias of the time-delayed mutual information is shown to often be equivalent to the mutual information between two distributions of points from the same system separated by infinite time. Thus intuitively, estimation of the bias is reduced to estimation of the mutual information between distributions of data points separated by large time intervals. The proposed bias estimation techniques are shown to work for Lorenz equations data and glucose time series data of three patients from the Columbia University Medical Center database.

  11. An improved selective sampling method

    International Nuclear Information System (INIS)

    Miyahara, Hiroshi; Iida, Nobuyuki; Watanabe, Tamaki

    1986-01-01

    The coincidence methods which are currently used for the accurate activity standardisation of radio-nuclides, require dead time and resolving time corrections which tend to become increasingly uncertain as countrates exceed about 10 K. To reduce the dependence on such corrections, Muller, in 1981, proposed the selective sampling method using a fast multichannel analyser (50 ns ch -1 ) for measuring the countrates. It is, in many ways, more convenient and possibly potentially more reliable to replace the MCA with scalers and a circuit is described employing five scalers; two of them serving to measure the background correction. Results of comparisons using our new method and the coincidence method for measuring the activity of 60 Co sources yielded agree-ment within statistical uncertainties. (author)

  12. Personality Traits and Susceptibility to Behavioral Biases among a Sample of Polish Stock Market Investors

    Directory of Open Access Journals (Sweden)

    Rzeszutek Marcin

    2015-09-01

    Full Text Available The aim of this paper is to investigate whether susceptibility to selected behavioral biases (overconfidence, mental accounting and sunk-cost fallacy is correlated with the Eysenck’s [1978] personality traits (impulsivity, venturesomeness, and empathy. This study was conducted on a sample of 90 retail investors frequently investing on the Warsaw Stock Exchange. Participants filled out a survey made up of two parts: 1 three situational exercises, which assessed susceptibility to behavioral biases and 2 an Impulsiveness Questionnaire, which measures impulsivity, venturesomeness, and empathy. The results demonstrated the relationship between venturesomeness and susceptibility to all behavioral biases explored in this study. We find that higher level of venturesomeness was linked with a lower probability of all behavioral biases included in this study.

  13. Common method biases in behavioral research: a critical review of the literature and recommended remedies.

    Science.gov (United States)

    Podsakoff, Philip M; MacKenzie, Scott B; Lee, Jeong-Yeon; Podsakoff, Nathan P

    2003-10-01

    Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.

  14. A "Scientific Diversity" Intervention to Reduce Gender Bias in a Sample of Life Scientists.

    Science.gov (United States)

    Moss-Racusin, Corinne A; van der Toorn, Jojanneke; Dovidio, John F; Brescoll, Victoria L; Graham, Mark J; Handelsman, Jo

    2016-01-01

    Mounting experimental evidence suggests that subtle gender biases favoring men contribute to the underrepresentation of women in science, technology, engineering, and mathematics (STEM), including many subfields of the life sciences. However, there are relatively few evaluations of diversity interventions designed to reduce gender biases within the STEM community. Because gender biases distort the meritocratic evaluation and advancement of students, interventions targeting instructors' biases are particularly needed. We evaluated one such intervention, a workshop called "Scientific Diversity" that was consistent with an established framework guiding the development of diversity interventions designed to reduce biases and was administered to a sample of life science instructors (N = 126) at several sessions of the National Academies Summer Institute for Undergraduate Education held nationwide. Evidence emerged indicating the efficacy of the "Scientific Diversity" workshop, such that participants were more aware of gender bias, expressed less gender bias, and were more willing to engage in actions to reduce gender bias 2 weeks after participating in the intervention compared with 2 weeks before the intervention. Implications for diversity interventions aimed at reducing gender bias and broadening the participation of women in the life sciences are discussed. © 2016 C. A. Moss-Racusin et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  15. Bias in segmented gamma scans arising from size differences between calibration standards and assay samples

    International Nuclear Information System (INIS)

    Sampson, T.E.

    1991-01-01

    Recent advances in segmented gamma scanning have emphasized software corrections for gamma-ray self-adsorption in particulates or lumps of special nuclear material in the sample. another feature of this software is an attenuation correction factor formalism that explicitly accounts for differences in sample container size and composition between the calibration standards and the individual items being measured. Software without this container-size correction produces biases when the unknowns are not packaged in the same containers as the calibration standards. This new software allows the use of different size and composition containers for standards and unknowns, as enormous savings considering the expense of multiple calibration standard sets otherwise needed. This paper presents calculations of the bias resulting from not using this new formalism. These calculations may be used to estimate bias corrections for segmented gamma scanners that do not incorporate these advanced concepts

  16. Approximate Bias Correction in Econometrics

    OpenAIRE

    James G. MacKinnon; Anthony A. Smith Jr.

    1995-01-01

    This paper discusses ways to reduce the bias of consistent estimators that are biased in finite samples. It is necessary that the bias function, which relates parameter values to bias, should be estimable by computer simulation or by some other method. If so, bias can be reduced or, in some cases that may not be unrealistic, even eliminated. In general, several evaluations of the bias function will be required to do this. Unfortunately, reducing bias may increase the variance, or even the mea...

  17. The second Southern African Bird Atlas Project: Causes and consequences of geographical sampling bias.

    Science.gov (United States)

    Hugo, Sanet; Altwegg, Res

    2017-09-01

    Using the Southern African Bird Atlas Project (SABAP2) as a case study, we examine the possible determinants of spatial bias in volunteer sampling effort and how well such biased data represent environmental gradients across the area covered by the atlas. For each province in South Africa, we used generalized linear mixed models to determine the combination of variables that explain spatial variation in sampling effort (number of visits per 5' × 5' grid cell, or "pentad"). The explanatory variables were distance to major road and exceptional birding locations or "sampling hubs," percentage cover of protected, urban, and cultivated area, and the climate variables mean annual precipitation, winter temperatures, and summer temperatures. Further, we used the climate variables and plant biomes to define subsets of pentads representing environmental zones across South Africa, Lesotho, and Swaziland. For each environmental zone, we quantified sampling intensity, and we assessed sampling completeness with species accumulation curves fitted to the asymptotic Lomolino model. Sampling effort was highest close to sampling hubs, major roads, urban areas, and protected areas. Cultivated area and the climate variables were less important. Further, environmental zones were not evenly represented by current data and the zones varied in the amount of sampling required representing the species that are present. SABAP2 volunteers' preferences in birding locations cause spatial bias in the dataset that should be taken into account when analyzing these data. Large parts of South Africa remain underrepresented, which may restrict the kind of ecological questions that may be addressed. However, sampling bias may be improved by directing volunteers toward undersampled regions while taking into account volunteer preferences.

  18. Wrong, but useful: regional species distribution models may not be improved by range-wide data under biased sampling.

    Science.gov (United States)

    El-Gabbas, Ahmed; Dormann, Carsten F

    2018-02-01

    Species distribution modeling (SDM) is an essential method in ecology and conservation. SDMs are often calibrated within one country's borders, typically along a limited environmental gradient with biased and incomplete data, making the quality of these models questionable. In this study, we evaluated how adequate are national presence-only data for calibrating regional SDMs. We trained SDMs for Egyptian bat species at two different scales: only within Egypt and at a species-specific global extent. We used two modeling algorithms: Maxent and elastic net, both under the point-process modeling framework. For each modeling algorithm, we measured the congruence of the predictions of global and regional models for Egypt, assuming that the lower the congruence, the lower the appropriateness of the Egyptian dataset to describe the species' niche. We inspected the effect of incorporating predictions from global models as additional predictor ("prior") to regional models, and quantified the improvement in terms of AUC and the congruence between regional models run with and without priors. Moreover, we analyzed predictive performance improvements after correction for sampling bias at both scales. On average, predictions from global and regional models in Egypt only weakly concur. Collectively, the use of priors did not lead to much improvement: similar AUC and high congruence between regional models calibrated with and without priors. Correction for sampling bias led to higher model performance, whatever prior used, making the use of priors less pronounced. Under biased and incomplete sampling, the use of global bats data did not improve regional model performance. Without enough bias-free regional data, we cannot objectively identify the actual improvement of regional models after incorporating information from the global niche. However, we still believe in great potential for global model predictions to guide future surveys and improve regional sampling in data

  19. When POS datasets don’t add up: Combatting sample bias

    DEFF Research Database (Denmark)

    Hovy, Dirk; Plank, Barbara; Søgaard, Anders

    2014-01-01

    Several works in Natural Language Processing have recently looked into part-of-speech (POS) annotation of Twitter data and typically used their own data sets. Since conventions on Twitter change rapidly, models often show sample bias. Training on a combination of the existing data sets should help...... overcome this bias and produce more robust models than any trained on the individual corpora. Unfortunately, combining the existing corpora proves difficult: many of the corpora use proprietary tag sets that have little or no overlap. Even when mapped to a common tag set, the different corpora...

  20. Coupling methods for multistage sampling

    OpenAIRE

    Chauvet, Guillaume

    2015-01-01

    Multistage sampling is commonly used for household surveys when there exists no sampling frame, or when the population is scattered over a wide area. Multistage sampling usually introduces a complex dependence in the selection of the final units, which makes asymptotic results quite difficult to prove. In this work, we consider multistage sampling with simple random without replacement sampling at the first stage, and with an arbitrary sampling design for further stages. We consider coupling ...

  1. Empirical single sample quantification of bias and variance in Q-ball imaging.

    Science.gov (United States)

    Hainline, Allison E; Nath, Vishwesh; Parvathaneni, Prasanna; Blaber, Justin A; Schilling, Kurt G; Anderson, Adam W; Kang, Hakmook; Landman, Bennett A

    2018-02-06

    The bias and variance of high angular resolution diffusion imaging methods have not been thoroughly explored in the literature and may benefit from the simulation extrapolation (SIMEX) and bootstrap techniques to estimate bias and variance of high angular resolution diffusion imaging metrics. The SIMEX approach is well established in the statistics literature and uses simulation of increasingly noisy data to extrapolate back to a hypothetical case with no noise. The bias of calculated metrics can then be computed by subtracting the SIMEX estimate from the original pointwise measurement. The SIMEX technique has been studied in the context of diffusion imaging to accurately capture the bias in fractional anisotropy measurements in DTI. Herein, we extend the application of SIMEX and bootstrap approaches to characterize bias and variance in metrics obtained from a Q-ball imaging reconstruction of high angular resolution diffusion imaging data. The results demonstrate that SIMEX and bootstrap approaches provide consistent estimates of the bias and variance of generalized fractional anisotropy, respectively. The RMSE for the generalized fractional anisotropy estimates shows a 7% decrease in white matter and an 8% decrease in gray matter when compared with the observed generalized fractional anisotropy estimates. On average, the bootstrap technique results in SD estimates that are approximately 97% of the true variation in white matter, and 86% in gray matter. Both SIMEX and bootstrap methods are flexible, estimate population characteristics based on single scans, and may be extended for bias and variance estimation on a variety of high angular resolution diffusion imaging metrics. © 2018 International Society for Magnetic Resonance in Medicine.

  2. Monitoring the aftermath of Flint drinking water contamination crisis: Another case of sampling bias?

    Science.gov (United States)

    Goovaerts, Pierre

    2017-07-15

    The delay in reporting high levels of lead in Flint drinking water, following the city's switch to the Flint River as its water supply, was partially caused by the biased selection of sampling sites away from the lead pipe network. Since Flint returned to its pre-crisis source of drinking water, the State has been monitoring water lead levels (WLL) at selected "sentinel" sites. In a first phase that lasted two months, 739 residences were sampled, most of them bi-weekly, to determine the general health of the distribution system and to track temporal changes in lead levels. During the same period, water samples were also collected through a voluntary program whereby concerned citizens received free testing kits and conducted sampling on their own. State officials relied on the former data to demonstrate the steady improvement in water quality. A recent analysis of data collected by voluntary sampling revealed, however, an opposite trend with lead levels increasing over time. This paper looks at potential sampling bias to explain such differences. Although houses with higher WLL were more likely to be sampled repeatedly, voluntary sampling turned out to reproduce fairly well the main characteristics (i.e. presence of lead service lines (LSL), construction year) of Flint housing stock. State-controlled sampling was less representative; e.g., sentinel sites with LSL were mostly built between 1935 and 1950 in lower poverty areas, which might hamper our ability to disentangle the effects of LSL and premise plumbing (lead fixtures and pipes present within old houses) on WLL. Also, there was no sentinel site with LSL in two of the most impoverished wards, including where the percentage of children with elevated blood lead levels tripled following the switch in water supply. Correcting for sampling bias narrowed the gap between sampling programs, yet overall temporal trends are still opposite. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Estimating the residential demand function for natural gas in Seoul with correction for sample selection bias

    International Nuclear Information System (INIS)

    Yoo, Seung-Hoon; Lim, Hea-Jin; Kwak, Seung-Jun

    2009-01-01

    Over the last twenty years, the consumption of natural gas in Korea has increased dramatically. This increase has mainly resulted from the rise of consumption in the residential sector. The main objective of the study is to estimate households' demand function for natural gas by applying a sample selection model using data from a survey of households in Seoul. The results show that there exists a selection bias in the sample and that failure to correct for sample selection bias distorts the mean estimate, of the demand for natural gas, downward by 48.1%. In addition, according to the estimation results, the size of the house, the dummy variable for dwelling in an apartment, the dummy variable for having a bed in an inner room, and the household's income all have positive relationships with the demand for natural gas. On the other hand, the size of the family and the price of gas negatively contribute to the demand for natural gas. (author)

  4. Personality, Attentional Biases towards Emotional Faces and Symptoms of Mental Disorders in an Adolescent Sample.

    Science.gov (United States)

    O'Leary-Barrett, Maeve; Pihl, Robert O; Artiges, Eric; Banaschewski, Tobias; Bokde, Arun L W; Büchel, Christian; Flor, Herta; Frouin, Vincent; Garavan, Hugh; Heinz, Andreas; Ittermann, Bernd; Mann, Karl; Paillère-Martinot, Marie-Laure; Nees, Frauke; Paus, Tomas; Pausova, Zdenka; Poustka, Luise; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Ströhle, Andreas; Schumann, Gunter; Conrod, Patricia J

    2015-01-01

    To investigate the role of personality factors and attentional biases towards emotional faces, in establishing concurrent and prospective risk for mental disorder diagnosis in adolescence. Data were obtained as part of the IMAGEN study, conducted across 8 European sites, with a community sample of 2257 adolescents. At 14 years, participants completed an emotional variant of the dot-probe task, as well two personality measures, namely the Substance Use Risk Profile Scale and the revised NEO Personality Inventory. At 14 and 16 years, participants and their parents were interviewed to determine symptoms of mental disorders. Personality traits were general and specific risk indicators for mental disorders at 14 years. Increased specificity was obtained when investigating the likelihood of mental disorders over a 2-year period, with the Substance Use Risk Profile Scale showing incremental validity over the NEO Personality Inventory. Attentional biases to emotional faces did not characterise or predict mental disorders examined in the current sample. Personality traits can indicate concurrent and prospective risk for mental disorders in a community youth sample, and identify at-risk youth beyond the impact of baseline symptoms. This study does not support the hypothesis that attentional biases mediate the relationship between personality and psychopathology in a community sample. Task and sample characteristics that contribute to differing results among studies are discussed.

  5. Sources of method bias in social science research and recommendations on how to control it.

    Science.gov (United States)

    Podsakoff, Philip M; MacKenzie, Scott B; Podsakoff, Nathan P

    2012-01-01

    Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms "method" and "method bias" and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.

  6. Mechanism for and method of biasing magnetic sensor

    Science.gov (United States)

    Kautz, David R.

    2007-12-04

    A magnetic sensor package having a biasing mechanism involving a coil-generated, resistor-controlled magnetic field for providing a desired biasing effect. In a preferred illustrated embodiment, the package broadly comprises a substrate; a magnetic sensor element; a biasing mechanism, including a coil and a first resistance element; an amplification mechanism; a filter capacitor element; and an encapsulant. The sensor is positioned within the coil. A current applied to the coil produces a biasing magnetic field. The biasing magnetic field is controlled by selecting a resistance value for the first resistance element which achieves the desired biasing effect. The first resistance element preferably includes a plurality of selectable resistors, the selection of one or more of which sets the resistance value.

  7. An interactive website for analytical method comparison and bias estimation.

    Science.gov (United States)

    Bahar, Burak; Tuncel, Ayse F; Holmes, Earle W; Holmes, Daniel T

    2017-12-01

    Regulatory standards mandate laboratories to perform studies to ensure accuracy and reliability of their test results. Method comparison and bias estimation are important components of these studies. We developed an interactive website for evaluating the relative performance of two analytical methods using R programming language tools. The website can be accessed at https://bahar.shinyapps.io/method_compare/. The site has an easy-to-use interface that allows both copy-pasting and manual entry of data. It also allows selection of a regression model and creation of regression and difference plots. Available regression models include Ordinary Least Squares, Weighted-Ordinary Least Squares, Deming, Weighted-Deming, Passing-Bablok and Passing-Bablok for large datasets. The server processes the data and generates downloadable reports in PDF or HTML format. Our website provides clinical laboratories a practical way to assess the relative performance of two analytical methods. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  8. Efficient Determination of Free Energy Landscapes in Multiple Dimensions from Biased Umbrella Sampling Simulations Using Linear Regression.

    Science.gov (United States)

    Meng, Yilin; Roux, Benoît

    2015-08-11

    The weighted histogram analysis method (WHAM) is a standard protocol for postprocessing the information from biased umbrella sampling simulations to construct the potential of mean force with respect to a set of order parameters. By virtue of the WHAM equations, the unbiased density of state is determined by satisfying a self-consistent condition through an iterative procedure. While the method works very effectively when the number of order parameters is small, its computational cost grows rapidly in higher dimension. Here, we present a simple and efficient alternative strategy, which avoids solving the self-consistent WHAM equations iteratively. An efficient multivariate linear regression framework is utilized to link the biased probability densities of individual umbrella windows and yield an unbiased global free energy landscape in the space of order parameters. It is demonstrated with practical examples that free energy landscapes that are comparable in accuracy to WHAM can be generated at a small fraction of the cost.

  9. Estimating Sampling Biases and Measurement Uncertainties of AIRS-AMSU-A Temperature and Water Vapor Observations Using MERRA Reanalysis

    Science.gov (United States)

    Hearty, Thomas J.; Savtchenko, Andrey K.; Tian, Baijun; Fetzer, Eric; Yung, Yuk L.; Theobald, Michael; Vollmer, Bruce; Fishbein, Evan; Won, Young-In

    2014-01-01

    We use MERRA (Modern Era Retrospective-Analysis for Research Applications) temperature and water vapor data to estimate the sampling biases of climatologies derived from the AIRS/AMSU-A (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A) suite of instruments. We separate the total sampling bias into temporal and instrumental components. The temporal component is caused by the AIRS/AMSU-A orbit and swath that are not able to sample all of time and space. The instrumental component is caused by scenes that prevent successful retrievals. The temporal sampling biases are generally smaller than the instrumental sampling biases except in regions with large diurnal variations, such as the boundary layer, where the temporal sampling biases of temperature can be +/- 2 K and water vapor can be 10% wet. The instrumental sampling biases are the main contributor to the total sampling biases and are mainly caused by clouds. They are up to 2 K cold and greater than 30% dry over mid-latitude storm tracks and tropical deep convective cloudy regions and up to 20% wet over stratus regions. However, other factors such as surface emissivity and temperature can also influence the instrumental sampling bias over deserts where the biases can be up to 1 K cold and 10% wet. Some instrumental sampling biases can vary seasonally and/or diurnally. We also estimate the combined measurement uncertainties of temperature and water vapor from AIRS/AMSU-A and MERRA by comparing similarly sampled climatologies from both data sets. The measurement differences are often larger than the sampling biases and have longitudinal variations.

  10. Towards Cost-efficient Sampling Methods

    OpenAIRE

    Peng, Luo; Yongli, Li; Chong, Wu

    2014-01-01

    The sampling method has been paid much attention in the field of complex network in general and statistical physics in particular. This paper presents two new sampling methods based on the perspective that a small part of vertices with high node degree can possess the most structure information of a network. The two proposed sampling methods are efficient in sampling the nodes with high degree. The first new sampling method is improved on the basis of the stratified random sampling method and...

  11. A study of total measurement error in tomographic gamma scanning to assay nuclear material with emphasis on a bias issue for low-activity samples

    International Nuclear Information System (INIS)

    Burr, T.L.; Mercer, D.J.; Prettyman, T.H.

    1998-01-01

    Field experience with the tomographic gamma scanner to assay nuclear material suggests that the analysis techniques can significantly impact the assay uncertainty. For example, currently implemented image reconstruction methods exhibit a positive bias for low-activity samples. Preliminary studies indicate that bias reduction could be achieved at the expense of increased random error variance. In this paper, the authors examine three possible bias sources: (1) measurement error in the estimated transmission matrix, (2) the positivity constraint on the estimated mass of nuclear material, and (3) improper treatment of the measurement error structure. The authors present results from many small-scale simulation studies to examine this bias/variance tradeoff for a few image reconstruction methods in the presence of the three possible bias sources

  12. Does duration of untreated psychosis bias study samples of first-episode psychosis?

    DEFF Research Database (Denmark)

    Friis, S; Melle, I; Larsen, T K

    2004-01-01

    OBJECTIVE: While findings are contradictory, many studies report that long Duration of Untreated Psychosis (DUP) correlates with poorer outcome in first episode psychosis. In an outcome study of first-episode psychosis, we compared the patients who refused to participate in a follow-along with th......OBJECTIVE: While findings are contradictory, many studies report that long Duration of Untreated Psychosis (DUP) correlates with poorer outcome in first episode psychosis. In an outcome study of first-episode psychosis, we compared the patients who refused to participate in a follow......-along with those who consented to estimate the importance of this factor in sample recruitment bias. Our questions were: (i) What is the percentage of refusers? (ii) Are there systematic differences between refusers and consenters on DUP and/or other admission variables? (iii) What is the risk of refusal...... for different values of DUP? METHOD: In an unselected group of consecutively admitted patients we compared follow-along refusers and consenters on the following admission variables: sex, age, diagnostic group, substance abuse, being in-patient, coming from an early detection site and DUP. We conducted...

  13. Rovno Amber Ant Assamblage: Bias toward Arboreal Strata or Sampling Effect?

    Directory of Open Access Journals (Sweden)

    Perkovsky E. E.

    2016-06-01

    Full Text Available In 2015 B. Guenard with co-authors indicated that the Rovno amber ant assemblage, as described by G. Dlussky and A. Rasnitsyn (2009, showed modest support for a bias towards arboreal origin comparing the Baltic and Bitterfeld assemblages, although it is not clear whether this reflects a sampling error or a signal of real deviation. Since 2009, the Rovno ant collection has now grown more than twice in volume which makes possible to check if the above inference about the essentially arboreal character of the assemblage is real or due to a sampling error. The comparison provided suggests in favour of the latter reason for the bias revealed by B. Guenard and co-authors. The new and larger data on the Rovno assemblage show that the share of non-arboreal ants is now well comparable with those concerning the Baltic and Bitterfeld assemblages. This holds true for the both total assemblages and subassemblages of worker ants only.

  14. Does volumetric absorptive microsampling eliminate the hematocrit bias for caffeine and paraxanthine in dried blood samples? A comparative study.

    Science.gov (United States)

    De Kesel, Pieter M M; Lambert, Willy E; Stove, Christophe P

    2015-06-30

    Volumetric absorptive microsampling (VAMS) is a novel sampling technique that allows the straightforward collection of an accurate volume of blood (approximately 10μL) from a drop or pool of blood by dipping an absorbent polymeric tip into it. The resulting blood microsample is dried and analyzed as a whole. The aim of this study was to evaluate the potential of VAMS to overcome the hematocrit bias, an important issue in the analysis of dried blood microsamples. An LC-MS/MS method for analysis of the model compounds caffeine and paraxanthine in VAMS samples was fully validated and fulfilled all pre-established criteria. In conjunction with previously validated procedures for dried blood spots (DBS) and blood, this allowed us to set up a meticulous comparative study in which both compounds were determined in over 80 corresponding VAMS, DBS and liquid whole blood samples. These originated from authentic human patient samples, covering a wide hematocrit range (0.21-0.50). By calculating the differences with reference whole blood concentrations, we found that analyte concentrations in VAMS samples were not affected by a bias that changed over the evaluated hematocrit range, in contrast to DBS results. However, VAMS concentrations tend to overestimate whole blood concentrations, as a consistent positive bias was observed. A different behavior of VAMS samples prepared from incurred and spiked blood, combined with a somewhat reduced recovery of caffeine and paraxanthine from VAMS tips at high hematocrit values, an effect that was not observed for DBS using a very similar extraction procedure, was found to be at the basis of the observed VAMS-whole blood deviations. Based on this study, being the first in which the validity and robustness of VAMS is evaluated by analyzing incurred human samples, it can be concluded that VAMS effectively assists in eliminating the effect of hematocrit. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  15. Sample processing device and method

    DEFF Research Database (Denmark)

    2011-01-01

    A sample processing device is disclosed, which sample processing device comprises a first substrate and a second substrate, where the first substrate has a first surface comprising two area types, a first area type with a first contact angle with water and a second area type with a second contact...... angle with water, the first contact angle being smaller than the second contact angle. The first substrate defines an inlet system and a preparation system in areas of the first type which two areas are separated by a barrier system in an area of the second type. The inlet system is adapted to receive...

  16. Pathogen prevalence, group bias, and collectivism in the standard cross-cultural sample.

    Science.gov (United States)

    Cashdan, Elizabeth; Steele, Matthew

    2013-03-01

    It has been argued that people in areas with high pathogen loads will be more likely to avoid outsiders, to be biased in favor of in-groups, and to hold collectivist and conformist values. Cross-national studies have supported these predictions. In this paper we provide new pathogen codes for the 186 cultures of the Standard Cross-Cultural Sample and use them, together with existing pathogen and ethnographic data, to try to replicate these cross-national findings. In support of the theory, we found that cultures in high pathogen areas were more likely to socialize children toward collectivist values (obedience rather than self-reliance). There was some evidence that pathogens were associated with reduced adult dispersal. However, we found no evidence of an association between pathogens and our measures of group bias (in-group loyalty and xenophobia) or intergroup contact.

  17. Lepidosaurian diversity in the Mesozoic-Palaeogene: the potential roles of sampling biases and environmental drivers

    Science.gov (United States)

    Cleary, Terri J.; Benson, Roger B. J.; Evans, Susan E.; Barrett, Paul M.

    2018-03-01

    Lepidosauria is a speciose clade with a long evolutionary history, but there have been few attempts to explore its taxon richness through time. Here we estimate patterns of terrestrial lepidosaur genus diversity for the Triassic-Palaeogene (252-23 Ma), and compare observed and sampling-corrected richness curves generated using Shareholder Quorum Subsampling and classical rarefaction. Generalized least-squares regression (GLS) is used to investigate the relationships between richness, sampling and environmental proxies. We found low levels of richness from the Triassic until the Late Cretaceous (except in the Kimmeridgian-Tithonian of Europe). High richness is recovered for the Late Cretaceous of North America, which declined across the K-Pg boundary but remained relatively high throughout the Palaeogene. Richness decreased following the Eocene-Oligocene Grande Coupure in North America and Europe, but remained high in North America and very high in Europe compared to the Late Cretaceous; elsewhere data are lacking. GLS analyses indicate that sampling biases (particularly, the number of fossil collections per interval) are the best explanation for long-term face-value genus richness trends. The lepidosaur fossil record presents many problems when attempting to reconstruct past diversity, with geographical sampling biases being of particular concern, especially in the Southern Hemisphere.

  18. Species richness in soil bacterial communities: a proposed approach to overcome sample size bias.

    Science.gov (United States)

    Youssef, Noha H; Elshahed, Mostafa S

    2008-09-01

    Estimates of species richness based on 16S rRNA gene clone libraries are increasingly utilized to gauge the level of bacterial diversity within various ecosystems. However, previous studies have indicated that regardless of the utilized approach, species richness estimates obtained are dependent on the size of the analyzed clone libraries. We here propose an approach to overcome sample size bias in species richness estimates in complex microbial communities. Parametric (Maximum likelihood-based and rarefaction curve-based) and non-parametric approaches were used to estimate species richness in a library of 13,001 near full-length 16S rRNA clones derived from soil, as well as in multiple subsets of the original library. Species richness estimates obtained increased with the increase in library size. To obtain a sample size-unbiased estimate of species richness, we calculated the theoretical clone library sizes required to encounter the estimated species richness at various clone library sizes, used curve fitting to determine the theoretical clone library size required to encounter the "true" species richness, and subsequently determined the corresponding sample size-unbiased species richness value. Using this approach, sample size-unbiased estimates of 17,230, 15,571, and 33,912 were obtained for the ML-based, rarefaction curve-based, and ACE-1 estimators, respectively, compared to bias-uncorrected values of 15,009, 11,913, and 20,909.

  19. Assessment of cognitive bias in decision-making and leadership styles among critical care nurses: a mixed methods study.

    Science.gov (United States)

    Lean Keng, Soon; AlQudah, Hani Nawaf Ibrahim

    2017-02-01

    To raise awareness of critical care nurses' cognitive bias in decision-making, its relationship with leadership styles and its impact on care delivery. The relationship between critical care nurses' decision-making and leadership styles in hospitals has been widely studied, but the influence of cognitive bias on decision-making and leadership styles in critical care environments remains poorly understood, particularly in Jordan. Two-phase mixed methods sequential explanatory design and grounded theory. critical care unit, Prince Hamza Hospital, Jordan. Participant sampling: convenience sampling Phase 1 (quantitative, n = 96), purposive sampling Phase 2 (qualitative, n = 20). Pilot tested quantitative survey of 96 critical care nurses in 2012. Qualitative in-depth interviews, informed by quantitative results, with 20 critical care nurses in 2013. Descriptive and simple linear regression quantitative data analyses. Thematic (constant comparative) qualitative data analysis. Quantitative - correlations found between rationality and cognitive bias, rationality and task-oriented leadership styles, cognitive bias and democratic communication styles and cognitive bias and task-oriented leadership styles. Qualitative - 'being competent', 'organizational structures', 'feeling self-confident' and 'being supported' in the work environment identified as key factors influencing critical care nurses' cognitive bias in decision-making and leadership styles. Two-way impact (strengthening and weakening) of cognitive bias in decision-making and leadership styles on critical care nurses' practice performance. There is a need to heighten critical care nurses' consciousness of cognitive bias in decision-making and leadership styles and its impact and to develop organization-level strategies to increase non-biased decision-making. © 2016 John Wiley & Sons Ltd.

  20. Standard methods for sampling and sample preparation for gamma spectroscopy

    International Nuclear Information System (INIS)

    Taskaeva, M.; Taskaev, E.; Nikolov, P.

    1993-01-01

    The strategy for sampling and sample preparation is outlined: necessary number of samples; analysis and treatment of the results received; quantity of the analysed material according to the radionuclide concentrations and analytical methods; the minimal quantity and kind of the data needed for making final conclusions and decisions on the base of the results received. This strategy was tested in gamma spectroscopic analysis of radionuclide contamination of the region of Eleshnitsa Uranium Mines. The water samples was taken and stored according to the ASTM D 3370-82. The general sampling procedures were in conformity with the recommendations of ISO 5667. The radionuclides was concentrated by coprecipitation with iron hydroxide and ion exchange. The sampling of soil samples complied with the rules of ASTM C 998, and their sample preparation - with ASTM C 999. After preparation the samples were sealed hermetically and measured. (author)

  1. The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

    Science.gov (United States)

    Syfert, Mindy M; Smith, Matthew J; Coomes, David A

    2013-01-01

    Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as "feature types" in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.

  2. Implementing a generic method for bias correction in statistical models using random effects, with spatial and population dynamics examples

    DEFF Research Database (Denmark)

    Thorson, James T.; Kristensen, Kasper

    2016-01-01

    Statistical models play an important role in fisheries science when reconciling ecological theory with available data for wild populations or experimental studies. Ecological models increasingly include both fixed and random effects, and are often estimated using maximum likelihood techniques...... configurations of an age-structured population dynamics model. This simulation experiment shows that the epsilon-method and the existing bias-correction method perform equally well in data-rich contexts, but the epsilon-method is slightly less biased in data-poor contexts. We then apply the epsilon......-method to a spatial regression model when estimating an index of population abundance, and compare results with an alternative bias-correction algorithm that involves Markov-chain Monte Carlo sampling. This example shows that the epsilon-method leads to a biologically significant difference in estimates of average...

  3. Method for introducing bias magnetization in ungaped cores

    DEFF Research Database (Denmark)

    Aguilar, Andres Revilla; Munk-Nielsen, Stig

    2014-01-01

    The use of permanent magnets for bias magnetization is a known technique to increase the energy storage capability in DC inductors, resulting in a size reduction or increased current rating. This paper presents a brief introduction on the different permanent magnet inductor’s configurations found...

  4. Temperature effects on pitfall catches of epigeal arthropods: a model and method for bias correction.

    Science.gov (United States)

    Saska, Pavel; van der Werf, Wopke; Hemerik, Lia; Luff, Martin L; Hatten, Timothy D; Honek, Alois; Pocock, Michael

    2013-02-01

    Carabids and other epigeal arthropods make important contributions to biodiversity, food webs and biocontrol of invertebrate pests and weeds. Pitfall trapping is widely used for sampling carabid populations, but this technique yields biased estimates of abundance ('activity-density') because individual activity - which is affected by climatic factors - affects the rate of catch. To date, the impact of temperature on pitfall catches, while suspected to be large, has not been quantified, and no method is available to account for it. This lack of knowledge and the unavailability of a method for bias correction affect the confidence that can be placed on results of ecological field studies based on pitfall data.Here, we develop a simple model for the effect of temperature, assuming a constant proportional change in the rate of catch per °C change in temperature, r , consistent with an exponential Q 10 response to temperature. We fit this model to 38 time series of pitfall catches and accompanying temperature records from the literature, using first differences and other detrending methods to account for seasonality. We use meta-analysis to assess consistency of the estimated parameter r among studies.The mean rate of increase in total catch across data sets was 0·0863 ± 0·0058 per °C of maximum temperature and 0·0497 ± 0·0107 per °C of minimum temperature. Multiple regression analyses of 19 data sets showed that temperature is the key climatic variable affecting total catch. Relationships between temperature and catch were also identified at species level. Correction for temperature bias had substantial effects on seasonal trends of carabid catches. Synthesis and Applications . The effect of temperature on pitfall catches is shown here to be substantial and worthy of consideration when interpreting results of pitfall trapping. The exponential model can be used both for effect estimation and for bias correction of observed data. Correcting for temperature

  5. Toward cost-efficient sampling methods

    Science.gov (United States)

    Luo, Peng; Li, Yongli; Wu, Chong; Zhang, Guijie

    2015-09-01

    The sampling method has been paid much attention in the field of complex network in general and statistical physics in particular. This paper proposes two new sampling methods based on the idea that a small part of vertices with high node degree could possess the most structure information of a complex network. The two proposed sampling methods are efficient in sampling high degree nodes so that they would be useful even if the sampling rate is low, which means cost-efficient. The first new sampling method is developed on the basis of the widely used stratified random sampling (SRS) method and the second one improves the famous snowball sampling (SBS) method. In order to demonstrate the validity and accuracy of two new sampling methods, we compare them with the existing sampling methods in three commonly used simulation networks that are scale-free network, random network, small-world network, and also in two real networks. The experimental results illustrate that the two proposed sampling methods perform much better than the existing sampling methods in terms of achieving the true network structure characteristics reflected by clustering coefficient, Bonacich centrality and average path length, especially when the sampling rate is low.

  6. Small-sample-worth perturbation methods

    International Nuclear Information System (INIS)

    1985-01-01

    It has been assumed that the perturbed region, R/sub p/, is large enough so that: (1) even without a great deal of biasing there is a substantial probability that an average source-neutron will enter it; and (2) once having entered, the neutron is likely to make several collisions in R/sub p/ during its lifetime. Unfortunately neither assumption is valid for the typical configurations one encounters in small-sample-worth experiments. In such experiments one measures the reactivity change which is induced when a very small void in a critical assembly is filled with a sample of some test-material. Only a minute fraction of the fission-source neutrons ever gets into the sample and, of those neutrons that do, most emerge uncollided. Monte Carlo small-sample perturbations computations are described

  7. Bias due to sample selection in propensity score matching for a supportive housing program evaluation in New York City.

    Directory of Open Access Journals (Sweden)

    Sungwoo Lim

    Full Text Available OBJECTIVES: Little is known about influences of sample selection on estimation in propensity score matching. The purpose of the study was to assess potential selection bias using one-to-one greedy matching versus optimal full matching as part of an evaluation of supportive housing in New York City (NYC. STUDY DESIGN AND SETTINGS: Data came from administrative data for 2 groups of applicants who were eligible for an NYC supportive housing program in 2007-09, including chronically homeless adults with a substance use disorder and young adults aging out of foster care. We evaluated the 2 matching methods in their ability to balance covariates and represent the original population, and in how those methods affected outcomes related to Medicaid expenditures. RESULTS: In the population with a substance use disorder, only optimal full matching performed well in balancing covariates, whereas both methods created representative populations. In the young adult population, both methods balanced covariates effectively, but only optimal full matching created representative populations. In the young adult population, the impact of the program on Medicaid expenditures was attenuated when one-to-one greedy matching was used, compared with optimal full matching. CONCLUSION: Given covariate balancing with both methods, attenuated program impacts in the young adult population indicated that one-to-one greedy matching introduced selection bias.

  8. An improved sampling method of complex network

    Science.gov (United States)

    Gao, Qi; Ding, Xintong; Pan, Feng; Li, Weixing

    2014-12-01

    Sampling subnet is an important topic of complex network research. Sampling methods influence the structure and characteristics of subnet. Random multiple snowball with Cohen (RMSC) process sampling which combines the advantages of random sampling and snowball sampling is proposed in this paper. It has the ability to explore global information and discover the local structure at the same time. The experiments indicate that this novel sampling method could keep the similarity between sampling subnet and original network on degree distribution, connectivity rate and average shortest path. This method is applicable to the situation where the prior knowledge about degree distribution of original network is not sufficient.

  9. Precision and Accuracy of k0-NAA Method for Analysis of Multi Elements in Reference Samples

    International Nuclear Information System (INIS)

    Sri-Wardani

    2004-01-01

    Accuracy and precision of k 0 -NAA method could determine in the analysis of multi elements contained in reference samples. The analyzed results of multi elements in SRM 1633b sample were obtained with optimum results in bias of 20% but it is in a good accuracy and precision. The analyzed results of As, Cd and Zn in CCQM-P29 rice flour sample were obtained with very good result in bias of 0.5 - 5.6%. (author)

  10. Predictive Methods for Dense Polymer Networks: Combating Bias with Bio-Based Structures

    Science.gov (United States)

    2016-03-16

    Combating bias with bio - based structures 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Andrew J. Guenthner...unlimited. PA Clearance 16152 Integrity  Service  Excellence Predictive methods for dense polymer networks: Combating bias with bio -based...Architectural Bias • Comparison of Petroleum-Based and Bio -Based Chemical Architectures • Continuing Research on Structure-Property Relationships using

  11. How many dinosaur species were there? Fossil bias and true richness estimated using a Poisson sampling model.

    Science.gov (United States)

    Starrfelt, Jostein; Liow, Lee Hsiang

    2016-04-05

    The fossil record is a rich source of information about biological diversity in the past. However, the fossil record is not only incomplete but has also inherent biases due to geological, physical, chemical and biological factors. Our knowledge of past life is also biased because of differences in academic and amateur interests and sampling efforts. As a result, not all individuals or species that lived in the past are equally likely to be discovered at any point in time or space. To reconstruct temporal dynamics of diversity using the fossil record, biased sampling must be explicitly taken into account. Here, we introduce an approach that uses the variation in the number of times each species is observed in the fossil record to estimate both sampling bias and true richness. We term our technique TRiPS (True Richness estimated using a Poisson Sampling model) and explore its robustness to violation of its assumptions via simulations. We then venture to estimate sampling bias and absolute species richness of dinosaurs in the geological stages of the Mesozoic. Using TRiPS, we estimate that 1936 (1543-2468) species of dinosaurs roamed the Earth during the Mesozoic. We also present improved estimates of species richness trajectories of the three major dinosaur clades: the sauropodomorphs, ornithischians and theropods, casting doubt on the Jurassic-Cretaceous extinction event and demonstrating that all dinosaur groups are subject to considerable sampling bias throughout the Mesozoic. © 2016 The Authors.

  12. Search strategy using LHC pileup interactions as a zero bias sample

    Science.gov (United States)

    Nachman, Benjamin; Rubbo, Francesco

    2018-05-01

    Due to a limited bandwidth and a large proton-proton interaction cross section relative to the rate of interesting physics processes, most events produced at the Large Hadron Collider (LHC) are discarded in real time. A sophisticated trigger system must quickly decide which events should be kept and is very efficient for a broad range of processes. However, there are many processes that cannot be accommodated by this trigger system. Furthermore, there may be models of physics beyond the standard model (BSM) constructed after data taking that could have been triggered, but no trigger was implemented at run time. Both of these cases can be covered by exploiting pileup interactions as an effective zero bias sample. At the end of high-luminosity LHC operations, this zero bias dataset will have accumulated about 1 fb-1 of data from which a bottom line cross section limit of O (1 ) fb can be set for BSM models already in the literature and those yet to come.

  13. Associations between cognitive biases and domains of schizotypy in a non-clinical sample.

    Science.gov (United States)

    Aldebot Sacks, Stephanie; Weisman de Mamani, Amy Gina; Garcia, Cristina Phoenix

    2012-03-30

    Schizotypy is a non-clinical manifestation of the same underlying biological factors that give rise to psychotic disorders (Claridge and Beech, 1995). Research on normative populations scoring high on schizotypy is valuable because it may help elucidate the predisposition to schizophrenia (Jahshan and Sergi, 2007) and because performance is not confounded by issues present in schizophrenia samples. In the current study, a Confirmatory Factor Analysis was conducted using several comprehensive measures of schizotypy. As expected and replicating prior research, a four-factor model of schizotypy emerged including a positive, a negative, a cognitive disorganization, and an impulsive nonconformity factor. We also evaluated how each factor related to distinct cognitive biases. In support of hypotheses, increased self-certainty, decreased theory of mind, and decreased source memory were associated with higher scores on the positive factor; decreased theory of mind was associated with higher scores on the negative factor; and increased self-certainty was associated with greater impulsive nonconformity. Unexpectedly, decreased self-certainty and increased theory of mind were associated with greater cognitive disorganization, and decreased source memory was associated with greater impulsive nonconformity. These findings offer new insights by highlighting cognitive biases that may be risk factors for psychosis. Published by Elsevier Ireland Ltd.

  14. A novel approach to non-biased systematic random sampling: a stereologic estimate of Purkinje cells in the human cerebellum.

    Science.gov (United States)

    Agashiwala, Rajiv M; Louis, Elan D; Hof, Patrick R; Perl, Daniel P

    2008-10-21

    Non-biased systematic sampling using the principles of stereology provides accurate quantitative estimates of objects within neuroanatomic structures. However, the basic principles of stereology are not optimally suited for counting objects that selectively exist within a limited but complex and convoluted portion of the sample, such as occurs when counting cerebellar Purkinje cells. In an effort to quantify Purkinje cells in association with certain neurodegenerative disorders, we developed a new method for stereologic sampling of the cerebellar cortex, involving calculating the volume of the cerebellar tissues, identifying and isolating the Purkinje cell layer and using this information to extrapolate non-biased systematic sampling data to estimate the total number of Purkinje cells in the tissues. Using this approach, we counted Purkinje cells in the right cerebella of four human male control specimens, aged 41, 67, 70 and 84 years, and estimated the total Purkinje cell number for the four entire cerebella to be 27.03, 19.74, 20.44 and 22.03 million cells, respectively. The precision of the method is seen when comparing the density of the cells within the tissue: 266,274, 173,166, 167,603 and 183,575 cells/cm3, respectively. Prior literature documents Purkinje cell counts ranging from 14.8 to 30.5 million cells. These data demonstrate the accuracy of our approach. Our novel approach, which offers an improvement over previous methodologies, is of value for quantitative work of this nature. This approach could be applied to morphometric studies of other similarly complex tissues as well.

  15. The perils of straying from protocol: sampling bias and interviewer effects.

    Directory of Open Access Journals (Sweden)

    Carrie J Ngongo

    Full Text Available Fidelity to research protocol is critical. In a contingent valuation study in an informal urban settlement in Nairobi, Kenya, participants responded differently to the three trained interviewers. Interviewer effects were present during the survey pilot, then magnified at the start of the main survey after a seemingly slight adaptation of the survey sampling protocol allowed interviewers to speak with the "closest neighbor" in the event that no one was home at a selected household. This slight degree of interviewer choice led to inferred sampling bias. Multinomial logistic regression and post-estimation tests revealed that the three interviewers' samples differed significantly from one another according to six demographic characteristics. The two female interviewers were 2.8 and 7.7 times less likely to talk with respondents of low socio-economic status than the male interviewer. Systematic error renders it impossible to determine which of the survey responses might be "correct." This experience demonstrates why researchers must take care to strictly follow sampling protocols, consistently train interviewers, and monitor responses by interview to ensure similarity between interviewers' groups and produce unbiased estimates of the parameters of interest.

  16. Comparison of DNA preservation methods for environmental bacterial community samples.

    Science.gov (United States)

    Gray, Michael A; Pratte, Zoe A; Kellogg, Christina A

    2013-02-01

    Field collections of environmental samples, for example corals, for molecular microbial analyses present distinct challenges. The lack of laboratory facilities in remote locations is common, and preservation of microbial community DNA for later study is critical. A particular challenge is keeping samples frozen in transit. Five nucleic acid preservation methods that do not require cold storage were compared for effectiveness over time and ease of use. Mixed microbial communities of known composition were created and preserved by DNAgard(™), RNAlater(®), DMSO-EDTA-salt (DESS), FTA(®) cards, and FTA Elute(®) cards. Automated ribosomal intergenic spacer analysis and clone libraries were used to detect specific changes in the faux communities over weeks and months of storage. A previously known bias in FTA(®) cards that results in lower recovery of pure cultures of Gram-positive bacteria was also detected in mixed community samples. There appears to be a uniform bias across all five preservation methods against microorganisms with high G + C DNA. Overall, the liquid-based preservatives (DNAgard(™), RNAlater(®), and DESS) outperformed the card-based methods. No single liquid method clearly outperformed the others, leaving method choice to be based on experimental design, field facilities, shipping constraints, and allowable cost. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

  17. Sampling method of environmental radioactivity monitoring

    International Nuclear Information System (INIS)

    1984-01-01

    This manual provides sampling methods of environmental samples of airborne dust, precipitated dust, precipitated water (rain or snow), fresh water, soil, river sediment or lake sediment, discharged water from a nuclear facility, grains, tea, milk, pasture grass, limnetic organisms, daily diet, index organisms, sea water, marine sediment, marine organisms, and that for tritium and radioiodine determination for radiation monitoring from radioactive fallout or radioactivity release by nuclear facilities. This manual aims at the presentation of standard sampling procedures for environmental radioactivity monitoring regardless of monitoring objectives, and shows preservation method of environmental samples acquired at the samplingpoint for radiation counting for those except human body. Sampling techniques adopted in this manual is decided by the criteria that they are suitable for routine monitoring and any special skillfulness is not necessary. Based on the above-mentioned principle, this manual presents outline and aims of sampling, sampling position or object, sampling quantity, apparatus, equipment or vessel for sampling, sampling location, sampling procedures, pretreatment and preparation procedures of a sample for radiation counting, necessary recording items for sampling and sample transportation procedures. Special attention is described in the chapter of tritium and radioiodine because these radionuclides might be lost by the above-mentioned sample preservation method for radiation counting of less volatile radionuclides than tritium or radioiodine. (Takagi, S.)

  18. Biomedical journals lack a consistent method to detect outcome reporting bias: a cross-sectional analysis.

    Science.gov (United States)

    Huan, L N; Tejani, A M; Egan, G

    2014-10-01

    An increasing amount of recently published literature has implicated outcome reporting bias (ORB) as a major contributor to skewing data in both randomized controlled trials and systematic reviews; however, little is known about the current methods in place to detect ORB. This study aims to gain insight into the detection and management of ORB by biomedical journals. This was a cross-sectional analysis involving standardized questions via email or telephone with the top 30 biomedical journals (2012) ranked by impact factor. The Cochrane Database of Systematic Reviews was excluded leaving 29 journals in the sample. Of 29 journals, 24 (83%) responded to our initial inquiry of which 14 (58%) answered our questions and 10 (42%) declined participation. Five (36%) of the responding journals indicated they had a specific method to detect ORB, whereas 9 (64%) did not have a specific method in place. The prevalence of ORB in the review process seemed to differ with 4 (29%) journals indicating ORB was found commonly, whereas 7 (50%) indicated ORB was uncommon or never detected by their journal previously. The majority (n = 10/14, 72%) of journals were unwilling to report or make discrepancies found in manuscripts available to the public. Although the minority, there were some journals (n = 4/14, 29%) which described thorough methods to detect ORB. Many journals seemed to lack a method with which to detect ORB and its estimated prevalence was much lower than that reported in literature suggesting inadequate detection. There exists a potential for overestimation of treatment effects of interventions and unclear risks. Fortunately, there are journals within this sample which appear to utilize comprehensive methods for detection of ORB, but overall, the data suggest improvements at the biomedical journal level for detecting and minimizing the effect of this bias are needed. © 2014 John Wiley & Sons Ltd.

  19. RCP: a novel probe design bias correction method for Illumina Methylation BeadChip.

    Science.gov (United States)

    Niu, Liang; Xu, Zongli; Taylor, Jack A

    2016-09-01

    The Illumina HumanMethylation450 BeadChip has been extensively utilized in epigenome-wide association studies. This array and its successor, the MethylationEPIC array, use two types of probes-Infinium I (type I) and Infinium II (type II)-in order to increase genome coverage but differences in probe chemistries result in different type I and II distributions of methylation values. Ignoring the difference in distributions between the two probe types may bias downstream analysis. Here, we developed a novel method, called Regression on Correlated Probes (RCP), which uses the existing correlation between pairs of nearby type I and II probes to adjust the beta values of all type II probes. We evaluate the effect of this adjustment on reducing probe design type bias, reducing technical variation in duplicate samples, improving accuracy of measurements against known standards, and retention of biological signal. We find that RCP is statistically significantly better than unadjusted data or adjustment with alternative methods including SWAN and BMIQ. We incorporated the method into the R package ENmix, which is freely available from the Bioconductor website (https://www.bioconductor.org/packages/release/bioc/html/ENmix.html). niulg@ucmail.uc.edu Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.

  20. Bias lighting in a radiographic apparatus and method

    International Nuclear Information System (INIS)

    Mcbride, T.R.; Richey, J.B.

    1982-01-01

    The radiographic system includes an x-ray source for irradiating a patient with x-radiation. An image intensifier receives the xradiation which has traversed the patient and produces an optical image of a radiation shadowgraph of the examined area of the patient. A television camera converts the optical image into a video signal. An image processor stores each frame of the video signal generated by the television camera as an electronic image of the optical image viewed on the image intensifier. Alternately , a plurality of frames from the television camera may be combined to produce a composite image. A bias light is provided adjacent the target of a television camera to illuminate the target before an optical image from the image intensifier is monitored by the television camera. This improves the linearity of the response of the television camera, particularly to low amplitude light intensities on the first few video frames generated by the camera

  1. Mixed Methods Sampling: A Typology with Examples

    Science.gov (United States)

    Teddlie, Charles; Yu, Fen

    2007-01-01

    This article presents a discussion of mixed methods (MM) sampling techniques. MM sampling involves combining well-established qualitative and quantitative techniques in creative ways to answer research questions posed by MM research designs. Several issues germane to MM sampling are presented including the differences between probability and…

  2. The effect of DNA degradation bias in passive sampling devices on metabarcoding studies of arthropod communities and their associated microbiota.

    Science.gov (United States)

    Krehenwinkel, Henrik; Fong, Marisa; Kennedy, Susan; Huang, Edward Greg; Noriyuki, Suzuki; Cayetano, Luis; Gillespie, Rosemary

    2018-01-01

    PCR amplification bias is a well-known problem in metagenomic analysis of arthropod communities. In contrast, variation of DNA degradation rates is a largely neglected source of bias. Differential degradation of DNA molecules could cause underrepresentation of taxa in a community sequencing sample. Arthropods are often collected by passive sampling devices, like malaise traps. Specimens in such a trap are exposed to varying periods of suboptimal storage and possibly different rates of DNA degradation. Degradation bias could thus be a significant issue, skewing diversity estimates. Here, we estimate the effect of differential DNA degradation on the recovery of community diversity of Hawaiian arthropods and their associated microbiota. We use a simple DNA size selection protocol to test for degradation bias in mock communities, as well as passively collected samples from actual Malaise traps. We compare the effect of DNA degradation to that of varying PCR conditions, including primer choice, annealing temperature and cycle number. Our results show that DNA degradation does indeed bias community analyses. However, the effect of this bias is of minor importance compared to that induced by changes in PCR conditions. Analyses of the macro and microbiome from passively collected arthropod samples are thus well worth pursuing.

  3. ALARA ASSESSMENT OF SETTLER SLUDGE SAMPLING METHODS

    International Nuclear Information System (INIS)

    Nelsen, L.A.

    2009-01-01

    The purpose of this assessment is to compare underwater and above water settler sludge sampling methods to determine if the added cost for underwater sampling for the sole purpose of worker dose reductions is justified. Initial planning for sludge sampling included container, settler and knock-out-pot (KOP) sampling. Due to the significantly higher dose consequence of KOP sludge, a decision was made to sample KOP underwater to achieve worker dose reductions. Additionally, initial plans were to utilize the underwater sampling apparatus for settler sludge. Since there are no longer plans to sample KOP sludge, the decision for underwater sampling for settler sludge needs to be revisited. The present sampling plan calls for spending an estimated $2,500,000 to design and construct a new underwater sampling system (per A21 C-PL-001 RevOE). This evaluation will compare and contrast the present method of above water sampling to the underwater method that is planned by the Sludge Treatment Project (STP) and determine if settler samples can be taken using the existing sampling cart (with potentially minor modifications) while maintaining doses to workers As Low As Reasonably Achievable (ALARA) and eliminate the need for costly redesigns, testing and personnel retraining

  4. ALARA ASSESSMENT OF SETTLER SLUDGE SAMPLING METHODS

    Energy Technology Data Exchange (ETDEWEB)

    NELSEN LA

    2009-01-30

    The purpose of this assessment is to compare underwater and above water settler sludge sampling methods to determine if the added cost for underwater sampling for the sole purpose of worker dose reductions is justified. Initial planning for sludge sampling included container, settler and knock-out-pot (KOP) sampling. Due to the significantly higher dose consequence of KOP sludge, a decision was made to sample KOP underwater to achieve worker dose reductions. Additionally, initial plans were to utilize the underwater sampling apparatus for settler sludge. Since there are no longer plans to sample KOP sludge, the decision for underwater sampling for settler sludge needs to be revisited. The present sampling plan calls for spending an estimated $2,500,000 to design and construct a new underwater sampling system (per A21 C-PL-001 RevOE). This evaluation will compare and contrast the present method of above water sampling to the underwater method that is planned by the Sludge Treatment Project (STP) and determine if settler samples can be taken using the existing sampling cart (with potentially minor modifications) while maintaining doses to workers As Low As Reasonably Achievable (ALARA) and eliminate the need for costly redesigns, testing and personnel retraining.

  5. Characteristics of bias-based harassment incidents reported by a national sample of U.S. adolescents.

    Science.gov (United States)

    Jones, Lisa M; Mitchell, Kimberly J; Turner, Heather A; Ybarra, Michele L

    2018-06-01

    Using a national sample of youth from the U.S., this paper examines incidents of bias-based harassment by peers that include language about victims' perceived sexual orientation, race/ethnicity, religion, weight or height, or intelligence. Telephone interviews were conducted with youth who were 10-20 years old (n = 791). One in six youth (17%) reported at least one experience with bias-based harassment in the past year. Bias language was a part of over half (52%) of all harassment incidents experienced by youth. Perpetrators of bias-based harassment were similar demographically to perpetrators of non-biased harassment. However, bias-based incidents were more likely to involve multiple perpetrators, longer timeframes and multiple harassment episodes. Even controlling for these related characteristics, the use of bias language in incidents of peer harassment resulted in significantly greater odds that youth felt sad as a result of the victimization, skipped school, avoided school activities, and lost friends, compared to non-biased harassment incidents. Copyright © 2018 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

  6. DOE methods for evaluating environmental and waste management samples

    International Nuclear Information System (INIS)

    Goheen, S.C.; McCulloch, M.; Thomas, B.L.; Riley, R.G.; Sklarew, D.S.; Mong, G.M.; Fadeff, S.K.

    1994-04-01

    DOE Methods for Evaluating Environmental and Waste Management Samples (DOE Methods) is a resource intended to support sampling and analytical activities for the evaluation of environmental and waste management samples from U.S. Department of Energy (DOE) sites. DOE Methods is the result of extensive cooperation from all DOE analytical laboratories. All of these laboratories have contributed key information and provided technical reviews as well as significant moral support leading to the success of this document. DOE Methods is designed to encompass methods for collecting representative samples and for determining the radioisotope activity and organic and inorganic composition of a sample. These determinations will aid in defining the type and breadth of contamination and thus determine the extent of environmental restoration or waste management actions needed, as defined by the DOE, the U.S. Environmental Protection Agency, or others. The development of DOE Methods is supported by the Laboratory Management Division of the DOE. Methods are prepared for entry into DOE Methods as chapter editors, together with DOE and other participants in this program, identify analytical and sampling method needs. Unique methods or methods consolidated from similar procedures in the DOE Procedures Database are selected for potential inclusion in this document. Initial selection is based largely on DOE needs and procedure applicability and completeness. Methods appearing in this document are one of two types. open-quotes Draftclose quotes or open-quotes Verified.close quotes. open-quotes Draftclose quotes methods that have been reviewed internally and show potential for eventual verification are included in this document, but they have not been reviewed externally, and their precision and bias may not be known. open-quotes Verifiedclose quotes methods in DOE Methods have been reviewed by volunteers from various DOE sites and private corporations

  7. Is the Positive Bias an ADHD Phenomenon? Reexamining the Positive Bias and its Correlates in a Heterogeneous Sample of Children.

    Science.gov (United States)

    Bourchtein, Elizaveta; Owens, Julie S; Dawson, Anne E; Evans, Steven W; Langberg, Joshua M; Flory, Kate; Lorch, Elizabeth P

    2017-11-25

    The goals of this study were to (a) evaluate the presence of the positive bias (PB) in elementary-school-aged children with and without ADHD when PB is defined at the individual level through latent profile analysis and (b) examine the extent to which several correlates (i.e., social functioning, aggression, depression, and anxiety) are associated with the PB. Participants were 233 youth (30% female; 8 to 10 years of age), 51% of whom met criteria for ADHD. During an individual evaluation, children and parents completed a battery of questionnaires to assess child competence, depression, anxiety, and aggression. Children also participated in a novel group session with same-sex unfamiliar peers (half of the group was comprised of children with ADHD) to engage in group problem-solving tasks and free play activities. After the group session, peers and staff completed ratings of each child's behavior (e.g., likeability, rule following). The best fitting LPA model for parent and self-ratings of competence revealed four profiles: High Competence/Self-Aware; Variable Competence/Self-Aware; Low Competence/Self-Aware; and Low Competence/PB, in which the PB was present across domains. Only 10% of youth showed a PB and youth with ADHD were no more likely to display the PB than their non-ADHD peers with similar levels of low competence. Lastly, the Low Competence/Self-Aware profile demonstrated higher levels of anxiety and depression than the Low Competence/PB profile; the profiles did not differ on aggression or peer or staff ratings of social/behavioral functioning. Implications for understanding the PB in children with and without ADHD are discussed.

  8. Forms of Attrition in a Longitudinal Study of Religion and Health in Older Adults and Implications for Sample Bias.

    Science.gov (United States)

    Hayward, R David; Krause, Neal

    2016-02-01

    The use of longitudinal designs in the field of religion and health makes it important to understand how attrition bias may affect findings in this area. This study examines attrition in a 4-wave, 8-year study of older adults. Attrition resulted in a sample biased toward more educated and more religiously involved individuals. Conditional linear growth curve models found that trajectories of change for some variables differed among attrition categories. Ineligibles had worsening depression, declining control, and declining attendance. Mortality was associated with worsening religious coping styles. Refusers experienced worsening depression. Nevertheless, there was no evidence of bias in the key religion and health results.

  9. Measurement of the Tracer Gradient and Sampling System Bias of the Hot Fuel Examination Facility Stack Air Monitoring System

    Energy Technology Data Exchange (ETDEWEB)

    Glissmeyer, John A.; Flaherty, Julia E.

    2011-07-20

    This report describes tracer gas uniformity and bias measurements made in the exhaust air discharge of the Hot Fuel Examination Facility at Idaho National Laboratory. The measurements were a follow-up on earlier measurements which indicated a lack of mixing of the two ventilation streams being discharged via a common stack. The lack of mixing is detrimental to the accuracy of air emission measurements. The lack of mixing was confirmed in these new measurements. The air sampling probe was found to be out of alignment and that was corrected. The suspected sampling bias in the air sample stream was disproved.

  10. Effects of social organization, trap arrangement and density, sampling scale, and population density on bias in population size estimation using some common mark-recapture estimators.

    Directory of Open Access Journals (Sweden)

    Manan Gupta

    Full Text Available Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates

  11. The persistent sampling bias in developmental psychology: A call to action.

    Science.gov (United States)

    Nielsen, Mark; Haun, Daniel; Kärtner, Joscha; Legare, Cristine H

    2017-10-01

    Psychology must confront the bias in its broad literature toward the study of participants developing in environments unrepresentative of the vast majority of the world's population. Here, we focus on the implications of addressing this challenge, highlight the need to address overreliance on a narrow participant pool, and emphasize the value and necessity of conducting research with diverse populations. We show that high-impact-factor developmental journals are heavily skewed toward publishing articles with data from WEIRD (Western, educated, industrialized, rich, and democratic) populations. Most critically, despite calls for change and supposed widespread awareness of this problem, there is a habitual dependence on convenience sampling and little evidence that the discipline is making any meaningful movement toward drawing from diverse samples. Failure to confront the possibility that culturally specific findings are being misattributed as universal traits has broad implications for the construction of scientifically defensible theories and for the reliable public dissemination of study findings. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Sample normalization methods in quantitative metabolomics.

    Science.gov (United States)

    Wu, Yiman; Li, Liang

    2016-01-22

    To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Evaluation of bias-correction methods for ensemble streamflow volume forecasts

    Directory of Open Access Journals (Sweden)

    T. Hashino

    2007-01-01

    Full Text Available Ensemble prediction systems are used operationally to make probabilistic streamflow forecasts for seasonal time scales. However, hydrological models used for ensemble streamflow prediction often have simulation biases that degrade forecast quality and limit the operational usefulness of the forecasts. This study evaluates three bias-correction methods for ensemble streamflow volume forecasts. All three adjust the ensemble traces using a transformation derived with simulated and observed flows from a historical simulation. The quality of probabilistic forecasts issued when using the three bias-correction methods is evaluated using a distributions-oriented verification approach. Comparisons are made of retrospective forecasts of monthly flow volumes for a north-central United States basin (Des Moines River, Iowa, issued sequentially for each month over a 48-year record. The results show that all three bias-correction methods significantly improve forecast quality by eliminating unconditional biases and enhancing the potential skill. Still, subtle differences in the attributes of the bias-corrected forecasts have important implications for their use in operational decision-making. Diagnostic verification distinguishes these attributes in a context meaningful for decision-making, providing criteria to choose among bias-correction methods with comparable skill.

  14. A Method for Estimating BeiDou Inter-frequency Satellite Clock Bias

    Directory of Open Access Journals (Sweden)

    LI Haojun

    2016-02-01

    Full Text Available A new method for estimating the BeiDou inter-frequency satellite clock bias is proposed, considering the shortage of the current methods. The constant and variable parts of the inter-frequency satellite clock bias are considered in the new method. The data from 10 observation stations are processed to validate the new method. The characterizations of the BeiDou inter-frequency satellite clock bias are also analyzed using the computed results. The results of the BeiDou inter-frequency satellite clock bias indicate that it is stable in the short term. The estimated BeiDou inter-frequency satellite clock bias results are molded. The model results show that the 10 parameters of model for each satellite can express the BeiDou inter-frequency satellite clock bias well and the accuracy reaches cm level. When the model parameters of the first day are used to compute the BeiDou inter-frequency satellite clock bias of the second day, the accuracy also reaches cm level. Based on the stability and modeling, a strategy for the BeiDou satellite clock service is presented to provide the reference of our BeiDou.

  15. Fluidics platform and method for sample preparation

    Science.gov (United States)

    Benner, Henry W.; Dzenitis, John M.

    2016-06-21

    Provided herein are fluidics platforms and related methods for performing integrated sample collection and solid-phase extraction of a target component of the sample all in one tube. The fluidics platform comprises a pump, particles for solid-phase extraction and a particle-holding means. The method comprises contacting the sample with one or more reagents in a pump, coupling a particle-holding means to the pump and expelling the waste out of the pump while the particle-holding means retains the particles inside the pump. The fluidics platform and methods herein described allow solid-phase extraction without pipetting and centrifugation.

  16. A scanning tunneling microscope break junction method with continuous bias modulation.

    Science.gov (United States)

    Beall, Edward; Yin, Xing; Waldeck, David H; Wierzbinski, Emil

    2015-09-28

    Single molecule conductance measurements on 1,8-octanedithiol were performed using the scanning tunneling microscope break junction method with an externally controlled modulation of the bias voltage. Application of an AC voltage is shown to improve the signal to noise ratio of low current (low conductance) measurements as compared to the DC bias method. The experimental results show that the current response of the molecule(s) trapped in the junction and the solvent media to the bias modulation can be qualitatively different. A model RC circuit which accommodates both the molecule and the solvent is proposed to analyze the data and extract a conductance for the molecule.

  17. Method for exploiting bias in factor analysis using constrained alternating least squares algorithms

    Science.gov (United States)

    Keenan, Michael R.

    2008-12-30

    Bias plays an important role in factor analysis and is often implicitly made use of, for example, to constrain solutions to factors that conform to physical reality. However, when components are collinear, a large range of solutions may exist that satisfy the basic constraints and fit the data equally well. In such cases, the introduction of mathematical bias through the application of constraints may select solutions that are less than optimal. The biased alternating least squares algorithm of the present invention can offset mathematical bias introduced by constraints in the standard alternating least squares analysis to achieve factor solutions that are most consistent with physical reality. In addition, these methods can be used to explicitly exploit bias to provide alternative views and provide additional insights into spectral data sets.

  18. DOE methods for evaluating environmental and waste management samples

    International Nuclear Information System (INIS)

    Goheen, S.C.; McCulloch, M.; Thomas, B.L.; Riley, R.G.; Sklarew, D.S.; Mong, G.M.; Fadeff, S.K.

    1994-10-01

    DOE Methods for Evaluating Environmental and Waste Management Samples (DOE Methods) is a resource intended to support sampling and analytical activities for the evaluation of environmental and waste management samples from U.S. Department of Energy (DOE) sites. DOE Methods is the result of extensive cooperation from all DOE analytical laboratories. All of these laboratories have contributed key information and provided technical reviews as well as significant moral support leading to the success of this document. DOE Methods is designed to encompass methods for collecting representative samples and for determining the radioisotope activity and organic and inorganic composition of a sample. These determinations will aid in defining the type and breadth of contamination and thus determine the extent of environmental restoration or waste management actions needed, as defined by the DOE, the U.S. Environmental Protection Agency, or others. The development of DOE Methods is supported by the Analytical Services Division of DOE. Unique methods or methods consolidated from similar procedures in the DOE Procedures Database are selected for potential inclusion in this document. Initial selection is based largely on DOE needs and procedure applicability and completeness. Methods appearing in this document are one of two types, open-quotes Draftclose quotes or open-quotes Verifiedclose quotes. open-quotes Draftclose quotes methods that have been reviewed internally and show potential for eventual verification are included in this document, but they have not been reviewed externally, and their precision and bias may not be known. open-quotes Verifiedclose quotes methods in DOE Methods have been reviewed by volunteers from various DOE sites and private corporations. These methods have delineated measures of precision and accuracy

  19. DOE methods for evaluating environmental and waste management samples

    Energy Technology Data Exchange (ETDEWEB)

    Goheen, S.C.; McCulloch, M.; Thomas, B.L.; Riley, R.G.; Sklarew, D.S.; Mong, G.M.; Fadeff, S.K. [eds.

    1994-10-01

    DOE Methods for Evaluating Environmental and Waste Management Samples (DOE Methods) is a resource intended to support sampling and analytical activities for the evaluation of environmental and waste management samples from U.S. Department of Energy (DOE) sites. DOE Methods is the result of extensive cooperation from all DOE analytical laboratories. All of these laboratories have contributed key information and provided technical reviews as well as significant moral support leading to the success of this document. DOE Methods is designed to encompass methods for collecting representative samples and for determining the radioisotope activity and organic and inorganic composition of a sample. These determinations will aid in defining the type and breadth of contamination and thus determine the extent of environmental restoration or waste management actions needed, as defined by the DOE, the U.S. Environmental Protection Agency, or others. The development of DOE Methods is supported by the Analytical Services Division of DOE. Unique methods or methods consolidated from similar procedures in the DOE Procedures Database are selected for potential inclusion in this document. Initial selection is based largely on DOE needs and procedure applicability and completeness. Methods appearing in this document are one of two types, {open_quotes}Draft{close_quotes} or {open_quotes}Verified{close_quotes}. {open_quotes}Draft{close_quotes} methods that have been reviewed internally and show potential for eventual verification are included in this document, but they have not been reviewed externally, and their precision and bias may not be known. {open_quotes}Verified{close_quotes} methods in DOE Methods have been reviewed by volunteers from various DOE sites and private corporations. These methods have delineated measures of precision and accuracy.

  20. Comparison of Parametric and Nonparametric Methods for Analyzing the Bias of a Numerical Model

    Directory of Open Access Journals (Sweden)

    Isaac Mugume

    2016-01-01

    Full Text Available Numerical models are presently applied in many fields for simulation and prediction, operation, or research. The output from these models normally has both systematic and random errors. The study compared January 2015 temperature data for Uganda as simulated using the Weather Research and Forecast model with actual observed station temperature data to analyze the bias using parametric (the root mean square error (RMSE, the mean absolute error (MAE, mean error (ME, skewness, and the bias easy estimate (BES and nonparametric (the sign test, STM methods. The RMSE normally overestimates the error compared to MAE. The RMSE and MAE are not sensitive to direction of bias. The ME gives both direction and magnitude of bias but can be distorted by extreme values while the BES is insensitive to extreme values. The STM is robust for giving the direction of bias; it is not sensitive to extreme values but it does not give the magnitude of bias. The graphical tools (such as time series and cumulative curves show the performance of the model with time. It is recommended to integrate parametric and nonparametric methods along with graphical methods for a comprehensive analysis of bias of a numerical model.

  1. Innovative methods for inorganic sample preparation

    Energy Technology Data Exchange (ETDEWEB)

    Essling, A.M.; Huff, E.A.; Graczyk, D.G.

    1992-04-01

    Procedures and guidelines are given for the dissolution of a variety of selected materials using fusion, microwave, and Parr bomb techniques. These materials include germanium glass, corium-concrete mixtures, and zeolites. Emphasis is placed on sample-preparation approaches that produce a single master solution suitable for complete multielement characterization of the sample. In addition, data are presented on the soil microwave digestion method approved by the Environmental Protection Agency (EPA). Advantages and disadvantages of each sample-preparation technique are summarized.

  2. Innovative methods for inorganic sample preparation

    International Nuclear Information System (INIS)

    Essling, A.M.; Huff, E.A.; Graczyk, D.G.

    1992-04-01

    Procedures and guidelines are given for the dissolution of a variety of selected materials using fusion, microwave, and Parr bomb techniques. These materials include germanium glass, corium-concrete mixtures, and zeolites. Emphasis is placed on sample-preparation approaches that produce a single master solution suitable for complete multielement characterization of the sample. In addition, data are presented on the soil microwave digestion method approved by the Environmental Protection Agency (EPA). Advantages and disadvantages of each sample-preparation technique are summarized

  3. New methods for sampling sparse populations

    Science.gov (United States)

    Anna Ringvall

    2007-01-01

    To improve surveys of sparse objects, methods that use auxiliary information have been suggested. Guided transect sampling uses prior information, e.g., from aerial photographs, for the layout of survey strips. Instead of being laid out straight, the strips will wind between potentially more interesting areas. 3P sampling (probability proportional to prediction) uses...

  4. A "Scientific Diversity" Intervention to Reduce Gender Bias in a Sample of Life Scientists

    Science.gov (United States)

    Moss-Racusin, Corinne A.; van der Toorn, Jojanneke; Dovidio, John F.; Brescoll, Victoria L.; Graham, Mark J.; Handelsman, Jo

    2016-01-01

    Mounting experimental evidence suggests that subtle gender biases favoring men contribute to the underrepresentation of women in science, technology, engineering, and mathematics (STEM), including many subfields of the life sciences. However, there are relatively few evaluations of diversity interventions designed to reduce gender biases within…

  5. Sample preparation method for scanning force microscopy

    CERN Document Server

    Jankov, I R; Szente, R N; Carreno, M N P; Swart, J W; Landers, R

    2001-01-01

    We present a method of sample preparation for studies of ion implantation on metal surfaces. The method, employing a mechanical mask, is specially adapted for samples analysed by Scanning Force Microscopy. It was successfully tested on polycrystalline copper substrates implanted with phosphorus ions at an acceleration voltage of 39 keV. The changes of the electrical properties of the surface were measured by Kelvin Probe Force Microscopy and the surface composition was analysed by Auger Electron Spectroscopy.

  6. Selection bias in population-based cancer case-control studies due to incomplete sampling frame coverage.

    Science.gov (United States)

    Walsh, Matthew C; Trentham-Dietz, Amy; Gangnon, Ronald E; Nieto, F Javier; Newcomb, Polly A; Palta, Mari

    2012-06-01

    Increasing numbers of individuals are choosing to opt out of population-based sampling frames due to privacy concerns. This is especially a problem in the selection of controls for case-control studies, as the cases often arise from relatively complete population-based registries, whereas control selection requires a sampling frame. If opt out is also related to risk factors, bias can arise. We linked breast cancer cases who reported having a valid driver's license from the 2004-2008 Wisconsin women's health study (N = 2,988) with a master list of licensed drivers from the Wisconsin Department of Transportation (WDOT). This master list excludes Wisconsin drivers that requested their information not be sold by the state. Multivariate-adjusted selection probability ratios (SPR) were calculated to estimate potential bias when using this driver's license sampling frame to select controls. A total of 962 cases (32%) had opted out of the WDOT sampling frame. Cases age <40 (SPR = 0.90), income either unreported (SPR = 0.89) or greater than $50,000 (SPR = 0.94), lower parity (SPR = 0.96 per one-child decrease), and hormone use (SPR = 0.93) were significantly less likely to be covered by the WDOT sampling frame (α = 0.05 level). Our results indicate the potential for selection bias due to differential opt out between various demographic and behavioral subgroups of controls. As selection bias may differ by exposure and study base, the assessment of potential bias needs to be ongoing. SPRs can be used to predict the direction of bias when cases and controls stem from different sampling frames in population-based case-control studies.

  7. Method and apparatus for sampling atmospheric mercury

    Science.gov (United States)

    Trujillo, Patricio E.; Campbell, Evan E.; Eutsler, Bernard C.

    1976-01-20

    A method of simultaneously sampling particulate mercury, organic mercurial vapors, and metallic mercury vapor in the working and occupational environment and determining the amount of mercury derived from each such source in the sampled air. A known volume of air is passed through a sampling tube containing a filter for particulate mercury collection, a first adsorber for the selective adsorption of organic mercurial vapors, and a second adsorber for the adsorption of metallic mercury vapor. Carbon black molecular sieves are particularly useful as the selective adsorber for organic mercurial vapors. The amount of mercury adsorbed or collected in each section of the sampling tube is readily quantitatively determined by flameless atomic absorption spectrophotometry.

  8. Subrandom methods for multidimensional nonuniform sampling.

    Science.gov (United States)

    Worley, Bradley

    2016-08-01

    Methods of nonuniform sampling that utilize pseudorandom number sequences to select points from a weighted Nyquist grid are commonplace in biomolecular NMR studies, due to the beneficial incoherence introduced by pseudorandom sampling. However, these methods require the specification of a non-arbitrary seed number in order to initialize a pseudorandom number generator. Because the performance of pseudorandom sampling schedules can substantially vary based on seed number, this can complicate the task of routine data collection. Approaches such as jittered sampling and stochastic gap sampling are effective at reducing random seed dependence of nonuniform sampling schedules, but still require the specification of a seed number. This work formalizes the use of subrandom number sequences in nonuniform sampling as a means of seed-independent sampling, and compares the performance of three subrandom methods to their pseudorandom counterparts using commonly applied schedule performance metrics. Reconstruction results using experimental datasets are also provided to validate claims made using these performance metrics. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. A method for the quantification of biased signalling at constitutively active receptors.

    Science.gov (United States)

    Hall, David A; Giraldo, Jesús

    2018-06-01

    Biased agonism, the ability of an agonist to differentially activate one of several signal transduction pathways when acting at a given receptor, is an increasingly recognized phenomenon at many receptors. The Black and Leff operational model lacks a way to describe constitutive receptor activity and hence inverse agonism. Thus, it is impossible to analyse the biased signalling of inverse agonists using this model. In this theoretical work, we develop and illustrate methods for the analysis of biased inverse agonism. Methods were derived for quantifying biased signalling in systems that demonstrate constitutive activity using the modified operational model proposed by Slack and Hall. The methods were illustrated using Monte Carlo simulations. The Monte Carlo simulations demonstrated that, with an appropriate experimental design, the model parameters are 'identifiable'. The method is consistent with methods based on the measurement of intrinsic relative activity (RA i ) (ΔΔlogR or ΔΔlog(τ/K a )) proposed by Ehlert and Kenakin and their co-workers but has some advantages. In particular, it allows the quantification of ligand bias independently of 'system bias' removing the requirement to normalize to a standard ligand. In systems with constitutive activity, the Slack and Hall model provides methods for quantifying the absolute bias of agonists and inverse agonists. This provides an alternative to methods based on RA i and is complementary to the ΔΔlog(τ/K a ) method of Kenakin et al. in systems where use of that method is inappropriate due to the presence of constitutive activity. © 2018 The British Pharmacological Society.

  10. A sequential sampling account of response bias and speed-accuracy tradeoffs in a conflict detection task.

    Science.gov (United States)

    Vuckovic, Anita; Kwantes, Peter J; Humphreys, Michael; Neal, Andrew

    2014-03-01

    Signal Detection Theory (SDT; Green & Swets, 1966) is a popular tool for understanding decision making. However, it does not account for the time taken to make a decision, nor why response bias might change over time. Sequential sampling models provide a way of accounting for speed-accuracy trade-offs and response bias shifts. In this study, we test the validity of a sequential sampling model of conflict detection in a simulated air traffic control task by assessing whether two of its key parameters respond to experimental manipulations in a theoretically consistent way. Through experimental instructions, we manipulated participants' response bias and the relative speed or accuracy of their responses. The sequential sampling model was able to replicate the trends in the conflict responses as well as response time across all conditions. Consistent with our predictions, manipulating response bias was associated primarily with changes in the model's Criterion parameter, whereas manipulating speed-accuracy instructions was associated with changes in the Threshold parameter. The success of the model in replicating the human data suggests we can use the parameters of the model to gain an insight into the underlying response bias and speed-accuracy preferences common to dynamic decision-making tasks. © 2013 American Psychological Association

  11. Biasing transition rate method based on direct MC simulation for probabilistic safety assessment

    Institute of Scientific and Technical Information of China (English)

    Xiao-Lei Pan; Jia-Qun Wang; Run Yuan; Fang Wang; Han-Qing Lin; Li-Qin Hu; Jin Wang

    2017-01-01

    Direct Monte Carlo (MC) simulation is a powerful probabilistic safety assessment method for accounting dynamics of the system.But it is not efficient at simulating rare events.A biasing transition rate method based on direct MC simulation is proposed to solve the problem in this paper.This method biases transition rates of the components by adding virtual components to them in series to increase the occurrence probability of the rare event,hence the decrease in the variance of MC estimator.Several cases are used to benchmark this method.The results show that the method is effective at modeling system failure and is more efficient at collecting evidence of rare events than the direct MC simulation.The performance is greatly improved by the biasing transition rate method.

  12. Exploring Gender Biases in a General Methods Class.

    Science.gov (United States)

    Quinn, Robert J.; Obenchain, Kathryn M.

    1999-01-01

    Describes how students in a general secondary methods course responded to a gender-neutral exam question by consistently assuming that the student in the hypothetical scenario was male. Describes the follow-up class discussion, noting students' assumptions, defensive responses, subconscious decision making, and awareness/nonawareness of their own…

  13. Inviting parents to take part in paediatric palliative care research: A mixed-methods examination of selection bias

    OpenAIRE

    Crocker, Joanna C; Beecham, Emma; Kelly, Paula; Dinsdale, Andrew P; Hemsley, June; Jones, Louise; Bluebond-Langner, Myra

    2015-01-01

    Background: Recruitment to paediatric palliative care research is challenging, with high rates of non-invitation of eligible families by clinicians. The impact on sample characteristics is unknown. Aim: To investigate, using mixed methods, non-invitation of eligible families and ensuing selection bias in an interview study about parents? experiences of advance care planning (ACP). Design: We examined differences between eligible families invited and not invited to participate by clinicians us...

  14. RELIC: a novel dye-bias correction method for Illumina Methylation BeadChip.

    Science.gov (United States)

    Xu, Zongli; Langie, Sabine A S; De Boever, Patrick; Taylor, Jack A; Niu, Liang

    2017-01-03

    The Illumina Infinium HumanMethylation450 BeadChip and its successor, Infinium MethylationEPIC BeadChip, have been extensively utilized in epigenome-wide association studies. Both arrays use two fluorescent dyes (Cy3-green/Cy5-red) to measure methylation level at CpG sites. However, performance difference between dyes can result in biased estimates of methylation levels. Here we describe a novel method, called REgression on Logarithm of Internal Control probes (RELIC) to correct for dye bias on whole array by utilizing the intensity values of paired internal control probes that monitor the two color channels. We evaluate the method in several datasets against other widely used dye-bias correction methods. Results on data quality improvement showed that RELIC correction statistically significantly outperforms alternative dye-bias correction methods. We incorporated the method into the R package ENmix, which is freely available from the Bioconductor website ( https://www.bioconductor.org/packages/release/bioc/html/ENmix.html ). RELIC is an efficient and robust method to correct for dye-bias in Illumina Methylation BeadChip data. It outperforms other alternative methods and conveniently implemented in R package ENmix to facilitate DNA methylation studies.

  15. A “scientific diversity” intervention to reduce gender bias in a sample of life scientists

    NARCIS (Netherlands)

    Moss-Racusin, C. A.; van der Toorn, J.; Dovidio, J. F.; Brescoli, V. L.; Graham, M. J.; Handelsman, J.

    2016-01-01

    Mounting experimental evidence suggests that subtle gender biases favoring men contribute to the underrepresentation of women in science, technology, engineering, and mathematics (STEM), including many subfields of the life sciences. However, there are relatively few evaluations of diversity

  16. A Quantile Mapping Bias Correction Method Based on Hydroclimatic Classification of the Guiana Shield.

    Science.gov (United States)

    Ringard, Justine; Seyler, Frederique; Linguet, Laurent

    2017-06-16

    Satellite precipitation products (SPPs) provide alternative precipitation data for regions with sparse rain gauge measurements. However, SPPs are subject to different types of error that need correction. Most SPP bias correction methods use the statistical properties of the rain gauge data to adjust the corresponding SPP data. The statistical adjustment does not make it possible to correct the pixels of SPP data for which there is no rain gauge data. The solution proposed in this article is to correct the daily SPP data for the Guiana Shield using a novel two set approach, without taking into account the daily gauge data of the pixel to be corrected, but the daily gauge data from surrounding pixels. In this case, a spatial analysis must be involved. The first step defines hydroclimatic areas using a spatial classification that considers precipitation data with the same temporal distributions. The second step uses the Quantile Mapping bias correction method to correct the daily SPP data contained within each hydroclimatic area. We validate the results by comparing the corrected SPP data and daily rain gauge measurements using relative RMSE and relative bias statistical errors. The results show that analysis scale variation reduces rBIAS and rRMSE significantly. The spatial classification avoids mixing rainfall data with different temporal characteristics in each hydroclimatic area, and the defined bias correction parameters are more realistic and appropriate. This study demonstrates that hydroclimatic classification is relevant for implementing bias correction methods at the local scale.

  17. Bias-correction of CORDEX-MENA projections using the Distribution Based Scaling method

    Science.gov (United States)

    Bosshard, Thomas; Yang, Wei; Sjökvist, Elin; Arheimer, Berit; Graham, L. Phil

    2014-05-01

    Within the Regional Initiative for the Assessment of the Impact of Climate Change on Water Resources and Socio-Economic Vulnerability in the Arab Region (RICCAR) lead by UN ESCWA, CORDEX RCM projections for the Middle East Northern Africa (MENA) domain are used to drive hydrological impacts models. Bias-correction of newly available CORDEX-MENA projections is a central part of this project. In this study, the distribution based scaling (DBS) method has been applied to 6 regional climate model projections driven by 2 RCP emission scenarios. The DBS method uses a quantile mapping approach and features a conditional temperature correction dependent on the wet/dry state in the climate model data. The CORDEX-MENA domain is particularly challenging for bias-correction as it spans very diverse climates showing pronounced dry and wet seasons. Results show that the regional climate models simulate too low temperatures and often have a displaced rainfall band compared to WATCH ERA-Interim forcing data in the reference period 1979-2008. DBS is able to correct the temperature biases as well as some aspects of the precipitation biases. Special focus is given to the analysis of the influence of the dry-frequency bias (i.e. climate models simulating too few rain days) on the bias-corrected projections and on the modification of the climate change signal by the DBS method.

  18. [Case-non case studies: Principles, methods, bias and interpretation].

    Science.gov (United States)

    Faillie, Jean-Luc

    2017-10-31

    Case-non case studies belongs to the methods assessing drug safety by analyzing the disproportionality of notifications of adverse drug reactions in pharmacovigilance databases. Used for the first time in the 1980s, the last few decades have seen a significant increase in the use of this design. The principle of the case-non case study is to compare drug exposure in cases of a studied adverse reaction with that of cases of other reported adverse reactions and called "non cases". Results are presented in the form of a reporting odds ratio (ROR), the interpretation of which makes it possible to identify drug safety signals. This article describes the principle of the case-non case study, the method of calculating the ROR and its confidence interval, the different modalities of analysis and how to interpret its results with regard to the advantages and limitations of this design. Copyright © 2017 Société française de pharmacologie et de thérapeutique. Published by Elsevier Masson SAS. All rights reserved.

  19. Addressing small sample size bias in multiple-biomarker trials: Inclusion of biomarker-negative patients and Firth correction.

    Science.gov (United States)

    Habermehl, Christina; Benner, Axel; Kopp-Schneider, Annette

    2018-03-01

    In recent years, numerous approaches for biomarker-based clinical trials have been developed. One of these developments are multiple-biomarker trials, which aim to investigate multiple biomarkers simultaneously in independent subtrials. For low-prevalence biomarkers, small sample sizes within the subtrials have to be expected, as well as many biomarker-negative patients at the screening stage. The small sample sizes may make it unfeasible to analyze the subtrials individually. This imposes the need to develop new approaches for the analysis of such trials. With an expected large group of biomarker-negative patients, it seems reasonable to explore options to benefit from including them in such trials. We consider advantages and disadvantages of the inclusion of biomarker-negative patients in a multiple-biomarker trial with a survival endpoint. We discuss design options that include biomarker-negative patients in the study and address the issue of small sample size bias in such trials. We carry out a simulation study for a design where biomarker-negative patients are kept in the study and are treated with standard of care. We compare three different analysis approaches based on the Cox model to examine if the inclusion of biomarker-negative patients can provide a benefit with respect to bias and variance of the treatment effect estimates. We apply the Firth correction to reduce the small sample size bias. The results of the simulation study suggest that for small sample situations, the Firth correction should be applied to adjust for the small sample size bias. Additional to the Firth penalty, the inclusion of biomarker-negative patients in the analysis can lead to further but small improvements in bias and standard deviation of the estimates. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Characterizing lentic freshwater fish assemblages using multiple sampling methods

    Science.gov (United States)

    Fischer, Jesse R.; Quist, Michael C.

    2014-01-01

    Characterizing fish assemblages in lentic ecosystems is difficult, and multiple sampling methods are almost always necessary to gain reliable estimates of indices such as species richness. However, most research focused on lentic fish sampling methodology has targeted recreationally important species, and little to no information is available regarding the influence of multiple methods and timing (i.e., temporal variation) on characterizing entire fish assemblages. Therefore, six lakes and impoundments (48–1,557 ha surface area) were sampled seasonally with seven gear types to evaluate the combined influence of sampling methods and timing on the number of species and individuals sampled. Probabilities of detection for species indicated strong selectivities and seasonal trends that provide guidance on optimal seasons to use gears when targeting multiple species. The evaluation of species richness and number of individuals sampled using multiple gear combinations demonstrated that appreciable benefits over relatively few gears (e.g., to four) used in optimal seasons were not present. Specifically, over 90 % of the species encountered with all gear types and season combinations (N = 19) from six lakes and reservoirs were sampled with nighttime boat electrofishing in the fall and benthic trawling, modified-fyke, and mini-fyke netting during the summer. Our results indicated that the characterization of lentic fish assemblages was highly influenced by the selection of sampling gears and seasons, but did not appear to be influenced by waterbody type (i.e., natural lake, impoundment). The standardization of data collected with multiple methods and seasons to account for bias is imperative to monitoring of lentic ecosystems and will provide researchers with increased reliability in their interpretations and decisions made using information on lentic fish assemblages.

  1. Communication: Estimating the initial biasing potential for λ-local-elevation umbrella-sampling (λ-LEUS) simulations via slow growth

    International Nuclear Information System (INIS)

    Bieler, Noah S.; Hünenberger, Philippe H.

    2014-01-01

    In a recent article [Bieler et al., J. Chem. Theory Comput. 10, 3006–3022 (2014)], we introduced a combination of the λ-dynamics (λD) approach for calculating alchemical free-energy differences and of the local-elevation umbrella-sampling (LEUS) memory-based biasing method to enhance the sampling along the alchemical coordinate. The combined scheme, referred to as λ-LEUS, was applied to the perturbation of hydroquinone to benzene in water as a test system, and found to represent an improvement over thermodynamic integration (TI) in terms of sampling efficiency at equivalent accuracy. However, the preoptimization of the biasing potential required in the λ-LEUS method requires “filling up” all the basins in the potential of mean force. This introduces a non-productive pre-sampling time that is system-dependent, and generally exceeds the corresponding equilibration time in a TI calculation. In this letter, a remedy is proposed to this problem, termed the slow growth memory guessing (SGMG) approach. Instead of initializing the biasing potential to zero at the start of the preoptimization, an approximate potential of mean force is estimated from a short slow growth calculation, and its negative used to construct the initial memory. Considering the same test system as in the preceding article, it is shown that of the application of SGMG in λ-LEUS permits to reduce the preoptimization time by about a factor of four

  2. Communication: Estimating the initial biasing potential for λ-local-elevation umbrella-sampling (λ-LEUS) simulations via slow growth

    Energy Technology Data Exchange (ETDEWEB)

    Bieler, Noah S.; Hünenberger, Philippe H., E-mail: phil@igc.phys.chem.ethz.ch [Laboratory of Physical Chemistry, ETH Zürich, CH-8093 Zürich (Switzerland)

    2014-11-28

    In a recent article [Bieler et al., J. Chem. Theory Comput. 10, 3006–3022 (2014)], we introduced a combination of the λ-dynamics (λD) approach for calculating alchemical free-energy differences and of the local-elevation umbrella-sampling (LEUS) memory-based biasing method to enhance the sampling along the alchemical coordinate. The combined scheme, referred to as λ-LEUS, was applied to the perturbation of hydroquinone to benzene in water as a test system, and found to represent an improvement over thermodynamic integration (TI) in terms of sampling efficiency at equivalent accuracy. However, the preoptimization of the biasing potential required in the λ-LEUS method requires “filling up” all the basins in the potential of mean force. This introduces a non-productive pre-sampling time that is system-dependent, and generally exceeds the corresponding equilibration time in a TI calculation. In this letter, a remedy is proposed to this problem, termed the slow growth memory guessing (SGMG) approach. Instead of initializing the biasing potential to zero at the start of the preoptimization, an approximate potential of mean force is estimated from a short slow growth calculation, and its negative used to construct the initial memory. Considering the same test system as in the preceding article, it is shown that of the application of SGMG in λ-LEUS permits to reduce the preoptimization time by about a factor of four.

  3. Biased representation of disturbance rates in the roadside sampling frame in boreal forests: implications for monitoring design

    Directory of Open Access Journals (Sweden)

    Steven L. Van Wilgenburg

    2015-12-01

    Full Text Available The North American Breeding Bird Survey (BBS is the principal source of data to inform researchers about the status of and trend for boreal forest birds. Unfortunately, little BBS coverage is available in the boreal forest, where increasing concern over the status of species breeding there has increased interest in northward expansion of the BBS. However, high disturbance rates in the boreal forest may complicate roadside monitoring. If the roadside sampling frame does not capture variation in disturbance rates because of either road placement or the use of roads for resource extraction, biased trend estimates might result. In this study, we examined roadside bias in the proportional representation of habitat disturbance via spatial data on forest "loss," forest fires, and anthropogenic disturbance. In each of 455 BBS routes, the area disturbed within multiple buffers away from the road was calculated and compared against the area disturbed in degree blocks and BBS strata. We found a nonlinear relationship between bias and distance from the road, suggesting forest loss and forest fires were underrepresented below 75 and 100 m, respectively. In contrast, anthropogenic disturbance was overrepresented at distances below 500 m and underrepresented thereafter. After accounting for distance from road, BBS routes were reasonably representative of the degree blocks they were within, with only a few strata showing biased representation. In general, anthropogenic disturbance is overrepresented in southern strata, and forest fires are underrepresented in almost all strata. Similar biases exist when comparing the entire road network and the subset sampled by BBS routes against the amount of disturbance within BBS strata; however, the magnitude of biases differed. Based on our results, we recommend that spatial stratification and rotating panel designs be used to spread limited BBS and off-road sampling effort in an unbiased fashion and that new BBS routes

  4. Chapter 12. Sampling and analytical methods

    International Nuclear Information System (INIS)

    Busenberg, E.; Plummer, L.N.; Cook, P.G.; Solomon, D.K.; Han, L.F.; Groening, M.; Oster, H.

    2006-01-01

    When water samples are taken for the analysis of CFCs, regardless of the sampling method used, contamination of samples by contact with atmospheric air (with its 'high' CFC concentrations) is a major concern. This is because groundwaters usually have lower CFC concentrations than those waters which have been exposed to the modern air. Some groundwaters might not contain CFCs and, therefore, are most sensitive to trace contamination by atmospheric air. Thus, extreme precautions are needed to obtain uncontaminated samples when groundwaters, particularly those with older ages, are sampled. It is recommended at the start of any CFC investigation that samples from a CFC-free source be collected and analysed, as a check upon the sampling equipment and methodology. The CFC-free source might be a deep monitoring well or, alternatively, CFC-free water could be carefully prepared in the laboratory. It is especially important that all tubing, pumps and connection that will be used in the sampling campaign be checked in this manner

  5. Biased Brownian dynamics for rate constant calculation.

    OpenAIRE

    Zou, G; Skeel, R D; Subramaniam, S

    2000-01-01

    An enhanced sampling method-biased Brownian dynamics-is developed for the calculation of diffusion-limited biomolecular association reaction rates with high energy or entropy barriers. Biased Brownian dynamics introduces a biasing force in addition to the electrostatic force between the reactants, and it associates a probability weight with each trajectory. A simulation loses weight when movement is along the biasing force and gains weight when movement is against the biasing force. The sampl...

  6. Evaluation of ACCMIP ozone simulations and ozonesonde sampling biases using a satellite-based multi-constituent chemical reanalysis

    Science.gov (United States)

    Miyazaki, Kazuyuki; Bowman, Kevin

    2017-07-01

    The Atmospheric Chemistry Climate Model Intercomparison Project (ACCMIP) ensemble ozone simulations for the present day from the 2000 decade simulation results are evaluated by a state-of-the-art multi-constituent atmospheric chemical reanalysis that ingests multiple satellite data including the Tropospheric Emission Spectrometer (TES), the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), and the Measurement of Pollution in the Troposphere (MOPITT) for 2005-2009. Validation of the chemical reanalysis against global ozonesondes shows good agreement throughout the free troposphere and lower stratosphere for both seasonal and year-to-year variations, with an annual mean bias of less than 0.9 ppb in the middle and upper troposphere at the tropics and mid-latitudes. The reanalysis provides comprehensive spatiotemporal evaluation of chemistry-model performance that compliments direct ozonesonde comparisons, which are shown to suffer from significant sampling bias. The reanalysis reveals that the ACCMIP ensemble mean overestimates ozone in the northern extratropics by 6-11 ppb while underestimating by up to 18 ppb in the southern tropics over the Atlantic in the lower troposphere. Most models underestimate the spatial variability of the annual mean lower tropospheric concentrations in the extratropics of both hemispheres by up to 70 %. The ensemble mean also overestimates the seasonal amplitude by 25-70 % in the northern extratropics and overestimates the inter-hemispheric gradient by about 30 % in the lower and middle troposphere. A part of the discrepancies can be attributed to the 5-year reanalysis data for the decadal model simulations. However, these differences are less evident with the current sonde network. To estimate ozonesonde sampling biases, we computed model bias separately for global coverage and the ozonesonde network. The ozonesonde sampling bias in the evaluated model bias for the seasonal mean concentration relative to global

  7. Sampling and examination methods used for TMI-2 samples

    International Nuclear Information System (INIS)

    Marley, A.W.; Akers, D.W.; McIsaac, C.V.

    1988-01-01

    The purpose of this paper is to summarize the sampling and examination techniques that were used in the collection and analysis of TMI-2 samples. Samples ranging from auxiliary building air to core debris were collected and analyzed. Handling of the larger samples and many of the smaller samples had to be done remotely and many standard laboratory analytical techniques were modified to accommodate the extremely high radiation fields associated with these samples. The TMI-2 samples presented unique problems with sampling and the laboratory analysis of prior molten fuel debris. 14 refs., 8 figs

  8. Final Sampling Bias in Haptic Judgments: How Final Touch Affects Decision-Making.

    Science.gov (United States)

    Mitsuda, Takashi; Yoshioka, Yuichi

    2018-01-01

    When people make a choice between multiple items, they usually evaluate each item one after the other repeatedly. The effect of the order and number of evaluating items on one's choices is essential to understanding the decision-making process. Previous studies have shown that when people choose a favorable item from two items, they tend to choose the item that they evaluated last. This tendency has been observed regardless of sensory modalities. This study investigated the origin of this bias by using three experiments involving two-alternative forced-choice tasks using handkerchiefs. First, the bias appeared in a smoothness discrimination task, which indicates that the bias was not based on judgments of preference. Second, the handkerchief that was touched more often tended to be chosen more frequently in the preference task, but not in the smoothness discrimination task, indicating that a mere exposure effect enhanced the bias. Third, in the condition where the number of touches did not differ between handkerchiefs, the bias appeared when people touched a handkerchief they wanted to touch last, but not when people touched the handkerchief that was predetermined. This finding suggests a direct coupling between final voluntary touching and judgment.

  9. Sampling methods for terrestrial amphibians and reptiles.

    Science.gov (United States)

    Paul Stephen Corn; R. Bruce. Bury

    1990-01-01

    Methods described for sampling amphibians and reptiles in Douglas-fir forests in the Pacific Northwest include pitfall trapping, time-constrained collecting, and surveys of coarse woody debris. The herpetofauna of this region differ in breeding and nonbreeding habitats and vagility, so that no single technique is sufficient for a community study. A combination of...

  10. Passive sampling methods for contaminated sediments

    DEFF Research Database (Denmark)

    Peijnenburg, Willie J.G.M.; Teasdale, Peter R.; Reible, Danny

    2014-01-01

    “Dissolved” concentrations of contaminants in sediment porewater (Cfree) provide a more relevant exposure metric for risk assessment than do total concentrations. Passive sampling methods (PSMs) for estimating Cfree offer the potential for cost-efficient and accurate in situ characterization...

  11. Turbidity threshold sampling: Methods and instrumentation

    Science.gov (United States)

    Rand Eads; Jack Lewis

    2001-01-01

    Traditional methods for determining the frequency of suspended sediment sample collection often rely on measurements, such as water discharge, that are not well correlated to sediment concentration. Stream power is generally not a good predictor of sediment concentration for rivers that transport the bulk of their load as fines, due to the highly variable routing of...

  12. Statistical sampling method for releasing decontaminated vehicles

    International Nuclear Information System (INIS)

    Lively, J.W.; Ware, J.A.

    1996-01-01

    Earth moving vehicles (e.g., dump trucks, belly dumps) commonly haul radiologically contaminated materials from a site being remediated to a disposal site. Traditionally, each vehicle must be surveyed before being released. The logistical difficulties of implementing the traditional approach on a large scale demand that an alternative be devised. A statistical method (MIL-STD-105E, open-quotes Sampling Procedures and Tables for Inspection by Attributesclose quotes) for assessing product quality from a continuous process was adapted to the vehicle decontamination process. This method produced a sampling scheme that automatically compensates and accommodates fluctuating batch sizes and changing conditions without the need to modify or rectify the sampling scheme in the field. Vehicles are randomly selected (sampled) upon completion of the decontamination process to be surveyed for residual radioactive surface contamination. The frequency of sampling is based on the expected number of vehicles passing through the decontamination process in a given period and the confidence level desired. This process has been successfully used for 1 year at the former uranium mill site in Monticello, Utah (a CERCLA regulated clean-up site). The method forces improvement in the quality of the decontamination process and results in a lower likelihood that vehicles exceeding the surface contamination standards are offered for survey. Implementation of this statistical sampling method on Monticello Projects has resulted in more efficient processing of vehicles through decontamination and radiological release, saved hundreds of hours of processing time, provided a high level of confidence that release limits are met, and improved the radiological cleanliness of vehicles leaving the controlled site

  13. Soybean yield modeling using bootstrap methods for small samples

    Energy Technology Data Exchange (ETDEWEB)

    Dalposso, G.A.; Uribe-Opazo, M.A.; Johann, J.A.

    2016-11-01

    One of the problems that occur when working with regression models is regarding the sample size; once the statistical methods used in inferential analyzes are asymptotic if the sample is small the analysis may be compromised because the estimates will be biased. An alternative is to use the bootstrap methodology, which in its non-parametric version does not need to guess or know the probability distribution that generated the original sample. In this work we used a set of soybean yield data and physical and chemical soil properties formed with fewer samples to determine a multiple linear regression model. Bootstrap methods were used for variable selection, identification of influential points and for determination of confidence intervals of the model parameters. The results showed that the bootstrap methods enabled us to select the physical and chemical soil properties, which were significant in the construction of the soybean yield regression model, construct the confidence intervals of the parameters and identify the points that had great influence on the estimated parameters. (Author)

  14. The Satellite Clock Bias Prediction Method Based on Takagi-Sugeno Fuzzy Neural Network

    Science.gov (United States)

    Cai, C. L.; Yu, H. G.; Wei, Z. C.; Pan, J. D.

    2017-05-01

    The continuous improvement of the prediction accuracy of Satellite Clock Bias (SCB) is the key problem of precision navigation. In order to improve the precision of SCB prediction and better reflect the change characteristics of SCB, this paper proposes an SCB prediction method based on the Takagi-Sugeno fuzzy neural network. Firstly, the SCB values are pre-treated based on their characteristics. Then, an accurate Takagi-Sugeno fuzzy neural network model is established based on the preprocessed data to predict SCB. This paper uses the precise SCB data with different sampling intervals provided by IGS (International Global Navigation Satellite System Service) to realize the short-time prediction experiment, and the results are compared with the ARIMA (Auto-Regressive Integrated Moving Average) model, GM(1,1) model, and the quadratic polynomial model. The results show that the Takagi-Sugeno fuzzy neural network model is feasible and effective for the SCB short-time prediction experiment, and performs well for different types of clocks. The prediction results for the proposed method are better than the conventional methods obviously.

  15. THE NONLINEAR BIASING OF THE zCOSMOS GALAXIES UP TO z ∼ 1 FROM THE 10k SAMPLE

    International Nuclear Information System (INIS)

    Kovac, K.; Porciani, C.; Lilly, S. J.; Oesch, P.; Peng, Y.; Carollo, C. M.; Marinoni, C.; Guzzo, L.; Iovino, A.; Cucciati, O.; Kneib, J.-P.; Le Fevre, O.; Zamorani, G.; Bolzonella, M.; Zucca, E.; Bardelli, S.; Meneux, B.; Contini, T.; Mainieri, V.; Renzini, A.

    2011-01-01

    We use the zCOSMOS galaxy overdensity field to study the biasing of galaxies in the COSMOS field. By comparing the probability distribution function of the galaxy density contrast δ g to the lognormal approximation of the mass density contrast δ, we obtain the mean biasing function b(δ, z, R) between the galaxy and matter overdensity fields and its second moments b-hat and b-tilde. Over the redshift interval 0.4 g |δ) = b(δ, z, R)δ is of a characteristic shape, requiring nonlinear biasing in the most overdense and underdense regions. Taking into account the uncertainties due to cosmic variance, we do not detect any significant evolution in the (δ g |δ) function, but we do detect a significant redshift evolution in the linear biasing parameter b-hat from 1.23 ± 0.11 at z ∼ 0.55 to 1.62 ± 0.14 at z ∼ 0.75, for a luminosity-complete sample of M B -1 Mpc, but increases systematically with luminosity (at 2σ-3σ significance between the M B B B 12 M sun with a small dependence on the adopted bias-mass relation. Our detailed error analysis and comparison with previous studies lead us to conclude that cosmic variance is the main contributor to the differences in the linear bias measured from different surveys. While our results support the general picture of biased galaxy formation up to z ∼ 1, the fine-tuning of the galaxy formation models is still limited by the restrictions of the current spectroscopic surveys at these redshifts.

  16. N3 Bias Field Correction Explained as a Bayesian Modeling Method

    DEFF Research Database (Denmark)

    Larsen, Christian Thode; Iglesias, Juan Eugenio; Van Leemput, Koen

    2014-01-01

    Although N3 is perhaps the most widely used method for MRI bias field correction, its underlying mechanism is in fact not well understood. Specifically, the method relies on a relatively heuristic recipe of alternating iterative steps that does not optimize any particular objective function. In t...

  17. New method for eliminating the statistical bias in highly turbulent flow measurements

    International Nuclear Information System (INIS)

    Nakao, S.I.; Terao, Y.; Hirata, K.I.; Kitakyushu Industrial Research Institute, Fukuoka, Japan)

    1987-01-01

    A simple method was developed for eliminating statistical bias which can be applied to highly turbulent flows with the sparse and nonuniform seeding conditions. Unlike the method proposed so far, a weighting function was determined based on the idea that the statistical bias could be eliminated if the asymmetric form of the probability density function of the velocity data were corrected. Moreover, the data more than three standard deviations away from the mean were discarded to remove the apparent turbulent intensity resulting from noise. The present method was applied to data obtained in the wake of a block, which provided local turbulent intensities up to about 120 percent, it was found to eliminate the statistical bias with high accuracy. 9 references

  18. A two-phase sampling survey for nonresponse and its paradata to correct nonresponse bias in a health surveillance survey.

    Science.gov (United States)

    Santin, G; Bénézet, L; Geoffroy-Perez, B; Bouyer, J; Guéguen, A

    2017-02-01

    The decline in participation rates in surveys, including epidemiological surveillance surveys, has become a real concern since it may increase nonresponse bias. The aim of this study is to estimate the contribution of a complementary survey among a subsample of nonrespondents, and the additional contribution of paradata in correcting for nonresponse bias in an occupational health surveillance survey. In 2010, 10,000 workers were randomly selected and sent a postal questionnaire. Sociodemographic data were available for the whole sample. After data collection of the questionnaires, a complementary survey among a random subsample of 500 nonrespondents was performed using a questionnaire administered by an interviewer. Paradata were collected for the complete subsample of the complementary survey. Nonresponse bias in the initial sample and in the combined samples were assessed using variables from administrative databases available for the whole sample, not subject to differential measurement errors. Corrected prevalences by reweighting technique were estimated by first using the initial survey alone and then the initial and complementary surveys combined, under several assumptions regarding the missing data process. Results were compared by computing relative errors. The response rates of the initial and complementary surveys were 23.6% and 62.6%, respectively. For the initial and the combined surveys, the relative errors decreased after correction for nonresponse on sociodemographic variables. For the combined surveys without paradata, relative errors decreased compared with the initial survey. The contribution of the paradata was weak. When a complex descriptive survey has a low response rate, a short complementary survey among nonrespondents with a protocol which aims to maximize the response rates, is useful. The contribution of sociodemographic variables in correcting for nonresponse bias is important whereas the additional contribution of paradata in

  19. Plant Disease Severity Assessment-How Rater Bias, Assessment Method, and Experimental Design Affect Hypothesis Testing and Resource Use Efficiency.

    Science.gov (United States)

    Chiang, Kuo-Szu; Bock, Clive H; Lee, I-Hsuan; El Jarroudi, Moussa; Delfosse, Philippe

    2016-12-01

    The effect of rater bias and assessment method on hypothesis testing was studied for representative experimental designs for plant disease assessment using balanced and unbalanced data sets. Data sets with the same number of replicate estimates for each of two treatments are termed "balanced" and those with unequal numbers of replicate estimates are termed "unbalanced". The three assessment methods considered were nearest percent estimates (NPEs), an amended 10% incremental scale, and the Horsfall-Barratt (H-B) scale. Estimates of severity of Septoria leaf blotch on leaves of winter wheat were used to develop distributions for a simulation model. The experimental designs are presented here in the context of simulation experiments which consider the optimal design for the number of specimens (individual units sampled) and the number of replicate estimates per specimen for a fixed total number of observations (total sample size for the treatments being compared). The criterion used to gauge each method was the power of the hypothesis test. As expected, at a given fixed number of observations, the balanced experimental designs invariably resulted in a higher power compared with the unbalanced designs at different disease severity means, mean differences, and variances. Based on these results, with unbiased estimates using NPE, the recommended number of replicate estimates taken per specimen is 2 (from a sample of specimens of at least 30), because this conserves resources. Furthermore, for biased estimates, an apparent difference in the power of the hypothesis test was observed between assessment methods and between experimental designs. Results indicated that, regardless of experimental design or rater bias, an amended 10% incremental scale has slightly less power compared with NPEs, and that the H-B scale is more likely than the others to cause a type II error. These results suggest that choice of assessment method, optimizing sample number and number of replicate

  20. Eating disorder symptoms and autobiographical memory bias in an analogue sample

    NARCIS (Netherlands)

    Wessel, Ineke; Huntjens, Rafaële

    2016-01-01

    Cognitive theories hold that dysfunctional cognitive schemas and associated information-processing biases are involved in the maintenance of psychopathology. In eating disorders (ED), these schemas would consist of self-evaluative representations, in which the importance of controlling eating, shape

  1. A New Navigation Satellite Clock Bias Prediction Method Based on Modified Clock-bias Quadratic Polynomial Model

    Science.gov (United States)

    Wang, Y. P.; Lu, Z. P.; Sun, D. S.; Wang, N.

    2016-01-01

    In order to better express the characteristics of satellite clock bias (SCB) and improve SCB prediction precision, this paper proposed a new SCB prediction model which can take physical characteristics of space-borne atomic clock, the cyclic variation, and random part of SCB into consideration. First, the new model employs a quadratic polynomial model with periodic items to fit and extract the trend term and cyclic term of SCB; then based on the characteristics of fitting residuals, a time series ARIMA ~(Auto-Regressive Integrated Moving Average) model is used to model the residuals; eventually, the results from the two models are combined to obtain final SCB prediction values. At last, this paper uses precise SCB data from IGS (International GNSS Service) to conduct prediction tests, and the results show that the proposed model is effective and has better prediction performance compared with the quadratic polynomial model, grey model, and ARIMA model. In addition, the new method can also overcome the insufficiency of the ARIMA model in model recognition and order determination.

  2. Statistical methods for elimination of guarantee-time bias in cohort studies: a simulation study

    Directory of Open Access Journals (Sweden)

    In Sung Cho

    2017-08-01

    Full Text Available Abstract Background Aspirin has been considered to be beneficial in preventing cardiovascular diseases and cancer. Several pharmaco-epidemiology cohort studies have shown protective effects of aspirin on diseases using various statistical methods, with the Cox regression model being the most commonly used approach. However, there are some inherent limitations to the conventional Cox regression approach such as guarantee-time bias, resulting in an overestimation of the drug effect. To overcome such limitations, alternative approaches, such as the time-dependent Cox model and landmark methods have been proposed. This study aimed to compare the performance of three methods: Cox regression, time-dependent Cox model and landmark method with different landmark times in order to address the problem of guarantee-time bias. Methods Through statistical modeling and simulation studies, the performance of the above three methods were assessed in terms of type I error, bias, power, and mean squared error (MSE. In addition, the three statistical approaches were applied to a real data example from the Korean National Health Insurance Database. Effect of cumulative rosiglitazone dose on the risk of hepatocellular carcinoma was used as an example for illustration. Results In the simulated data, time-dependent Cox regression outperformed the landmark method in terms of bias and mean squared error but the type I error rates were similar. The results from real-data example showed the same patterns as the simulation findings. Conclusions While both time-dependent Cox regression model and landmark analysis are useful in resolving the problem of guarantee-time bias, time-dependent Cox regression is the most appropriate method for analyzing cumulative dose effects in pharmaco-epidemiological studies.

  3. A forecasting method to reduce estimation bias in self-reported cell phone data.

    Science.gov (United States)

    Redmayne, Mary; Smith, Euan; Abramson, Michael J

    2013-01-01

    There is ongoing concern that extended exposure to cell phone electromagnetic radiation could be related to an increased risk of negative health effects. Epidemiological studies seek to assess this risk, usually relying on participants' recalled use, but recall is notoriously poor. Our objectives were primarily to produce a forecast method, for use by such studies, to reduce estimation bias in the recalled extent of cell phone use. The method we developed, using Bayes' rule, is modelled with data we collected in a cross-sectional cluster survey exploring cell phone user-habits among New Zealand adolescents. Participants recalled their recent extent of SMS-texting and retrieved from their provider the current month's actual use-to-date. Actual use was taken as the gold standard in the analyses. Estimation bias arose from a large random error, as observed in all cell phone validation studies. We demonstrate that this seriously exaggerates upper-end forecasts of use when used in regression models. This means that calculations using a regression model will lead to underestimation of heavy-users' relative risk. Our Bayesian method substantially reduces estimation bias. In cases where other studies' data conforms to our method's requirements, application should reduce estimation bias, leading to a more accurate relative risk calculation for mid-to-heavy users.

  4. Are Teacher Course Evaluations Biased against Faculty That Teach Quantitative Methods Courses?

    Science.gov (United States)

    Royal, Kenneth D.; Stockdale, Myrah R.

    2015-01-01

    The present study investigated graduate students' responses to teacher/course evaluations (TCE) to determine if students' responses were inherently biased against faculty who teach quantitative methods courses. Item response theory (IRT) and Differential Item Functioning (DIF) techniques were utilized for data analysis. Results indicate students…

  5. A brain MRI bias field correction method created in the Gaussian multi-scale space

    Science.gov (United States)

    Chen, Mingsheng; Qin, Mingxin

    2017-07-01

    A pre-processing step is needed to correct for the bias field signal before submitting corrupted MR images to such image-processing algorithms. This study presents a new bias field correction method. The method creates a Gaussian multi-scale space by the convolution of the inhomogeneous MR image with a two-dimensional Gaussian function. In the multi-Gaussian space, the method retrieves the image details from the differentiation of the original image and convolution image. Then, it obtains an image whose inhomogeneity is eliminated by the weighted sum of image details in each layer in the space. Next, the bias field-corrected MR image is retrieved after the Υ correction, which enhances the contrast and brightness of the inhomogeneity-eliminated MR image. We have tested the approach on T1 MRI and T2 MRI with varying bias field levels and have achieved satisfactory results. Comparison experiments with popular software have demonstrated superior performance of the proposed method in terms of quantitative indices, especially an improvement in subsequent image segmentation.

  6. Sampling trace organic compounds in water: a comparison of a continuous active sampler to continuous passive and discrete sampling methods.

    Science.gov (United States)

    Coes, Alissa L; Paretti, Nicholas V; Foreman, William T; Iverson, Jana L; Alvarez, David A

    2014-03-01

    A continuous active sampling method was compared to continuous passive and discrete sampling methods for the sampling of trace organic compounds (TOCs) in water. Results from each method are compared and contrasted in order to provide information for future investigators to use while selecting appropriate sampling methods for their research. The continuous low-level aquatic monitoring (CLAM) sampler (C.I.Agent® Storm-Water Solutions) is a submersible, low flow-rate sampler, that continuously draws water through solid-phase extraction media. CLAM samplers were deployed at two wastewater-dominated stream field sites in conjunction with the deployment of polar organic chemical integrative samplers (POCIS) and the collection of discrete (grab) water samples. All samples were analyzed for a suite of 69 TOCs. The CLAM and POCIS samples represent time-integrated samples that accumulate the TOCs present in the water over the deployment period (19-23 h for CLAM and 29 days for POCIS); the discrete samples represent only the TOCs present in the water at the time and place of sampling. Non-metric multi-dimensional scaling and cluster analysis were used to examine patterns in both TOC detections and relative concentrations between the three sampling methods. A greater number of TOCs were detected in the CLAM samples than in corresponding discrete and POCIS samples, but TOC concentrations in the CLAM samples were significantly lower than in the discrete and (or) POCIS samples. Thirteen TOCs of varying polarity were detected by all of the three methods. TOC detections and concentrations obtained by the three sampling methods, however, are dependent on multiple factors. This study found that stream discharge, constituent loading, and compound type all affected TOC concentrations detected by each method. In addition, TOC detections and concentrations were affected by the reporting limits, bias, recovery, and performance of each method. Published by Elsevier B.V.

  7. Sampling trace organic compounds in water: a comparison of a continuous active sampler to continuous passive and discrete sampling methods

    Science.gov (United States)

    Coes, Alissa L.; Paretti, Nicholas V.; Foreman, William T.; Iverson, Jana L.; Alvarez, David A.

    2014-01-01

    A continuous active sampling method was compared to continuous passive and discrete sampling methods for the sampling of trace organic compounds (TOCs) in water. Results from each method are compared and contrasted in order to provide information for future investigators to use while selecting appropriate sampling methods for their research. The continuous low-level aquatic monitoring (CLAM) sampler (C.I.Agent® Storm-Water Solutions) is a submersible, low flow-rate sampler, that continuously draws water through solid-phase extraction media. CLAM samplers were deployed at two wastewater-dominated stream field sites in conjunction with the deployment of polar organic chemical integrative samplers (POCIS) and the collection of discrete (grab) water samples. All samples were analyzed for a suite of 69 TOCs. The CLAM and POCIS samples represent time-integrated samples that accumulate the TOCs present in the water over the deployment period (19–23 h for CLAM and 29 days for POCIS); the discrete samples represent only the TOCs present in the water at the time and place of sampling. Non-metric multi-dimensional scaling and cluster analysis were used to examine patterns in both TOC detections and relative concentrations between the three sampling methods. A greater number of TOCs were detected in the CLAM samples than in corresponding discrete and POCIS samples, but TOC concentrations in the CLAM samples were significantly lower than in the discrete and (or) POCIS samples. Thirteen TOCs of varying polarity were detected by all of the three methods. TOC detections and concentrations obtained by the three sampling methods, however, are dependent on multiple factors. This study found that stream discharge, constituent loading, and compound type all affected TOC concentrations detected by each method. In addition, TOC detections and concentrations were affected by the reporting limits, bias, recovery, and performance of each method.

  8. SAMPLING IN EXTERNAL AUDIT - THE MONETARY UNIT SAMPLING METHOD

    Directory of Open Access Journals (Sweden)

    E. Dascalu

    2016-12-01

    Full Text Available This article approaches the general issue of diminishing the evidence investigation space in audit activities, by means of sampling techniques, given that in the instance of a significant data volume an exhaustive examination of the assessed popula¬tion is not possible and/or effective. The general perspective of the presentation involves dealing with sampling risk, in essence, the risk that a selected sample may not be representative for the overall population, in correlation with the audit risk model and with the component parts of this model (inherent risk, control risk and non detection risk and highlights the inter-conditionings between these two models.

  9. Different methods for volatile sampling in mammals.

    Directory of Open Access Journals (Sweden)

    Marlen Kücklich

    Full Text Available Previous studies showed that olfactory cues are important for mammalian communication. However, many specific compounds that convey information between conspecifics are still unknown. To understand mechanisms and functions of olfactory cues, olfactory signals such as volatile compounds emitted from individuals need to be assessed. Sampling of animals with and without scent glands was typically conducted using cotton swabs rubbed over the skin or fur and analysed by gas chromatography-mass spectrometry (GC-MS. However, this method has various drawbacks, including a high level of contaminations. Thus, we adapted two methods of volatile sampling from other research fields and compared them to sampling with cotton swabs. To do so we assessed the body odor of common marmosets (Callithrix jacchus using cotton swabs, thermal desorption (TD tubes and, alternatively, a mobile GC-MS device containing a thermal desorption trap. Overall, TD tubes comprised most compounds (N = 113, with half of those compounds being volatile (N = 52. The mobile GC-MS captured the fewest compounds (N = 35, of which all were volatile. Cotton swabs contained an intermediate number of compounds (N = 55, but very few volatiles (N = 10. Almost all compounds found with the mobile GC-MS were also captured with TD tubes (94%. Hence, we recommend TD tubes for state of the art sampling of body odor of mammals or other vertebrates, particularly for field studies, as they can be easily transported, stored and analysed with high performance instruments in the lab. Nevertheless, cotton swabs capture compounds which still may contribute to the body odor, e.g. after bacterial fermentation, while profiles from mobile GC-MS include only the most abundant volatiles of the body odor.

  10. An improved level set method for brain MR images segmentation and bias correction.

    Science.gov (United States)

    Chen, Yunjie; Zhang, Jianwei; Macione, Jim

    2009-10-01

    Intensity inhomogeneities cause considerable difficulty in the quantitative analysis of magnetic resonance (MR) images. Thus, bias field estimation is a necessary step before quantitative analysis of MR data can be undertaken. This paper presents a variational level set approach to bias correction and segmentation for images with intensity inhomogeneities. Our method is based on an observation that intensities in a relatively small local region are separable, despite of the inseparability of the intensities in the whole image caused by the overall intensity inhomogeneity. We first define a localized K-means-type clustering objective function for image intensities in a neighborhood around each point. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. The objective function is then integrated over the entire domain to define the data term into the level set framework. Our method is able to capture bias of quite general profiles. Moreover, it is robust to initialization, and thereby allows fully automated applications. The proposed method has been used for images of various modalities with promising results.

  11. Method and apparatus for continuous sampling

    International Nuclear Information System (INIS)

    Marcussen, C.

    1982-01-01

    An apparatus and method for continuously sampling a pulverous material flow includes means for extracting a representative subflow from a pulverous material flow. A screw conveyor is provided to cause the extracted subflow to be pushed upwardly through a duct to an overflow. Means for transmitting a radiation beam transversely to the subflow in the duct, and means for sensing the transmitted beam through opposite pairs of windows in the duct are provided to measure the concentration of one or more constituents in the subflow. (author)

  12. Comparisons of methods for generating conditional Poisson samples and Sampford samples

    OpenAIRE

    Grafström, Anton

    2005-01-01

    Methods for conditional Poisson sampling (CP-sampling) and Sampford sampling are compared and the focus is on the efficiency of the methods. The efficiency is investigated by simulation in different sampling situations. It was of interest to compare methods since new methods for both CP-sampling and Sampford sampling were introduced by Bondesson, Traat & Lundqvist in 2004. The new methods are acceptance rejection methods that use the efficient Pareto sampling method. They are found to be ...

  13. A forward bias method for lag correction of an a-Si flat panel detector

    International Nuclear Information System (INIS)

    Starman, Jared; Tognina, Carlo; Partain, Larry; Fahrig, Rebecca

    2012-01-01

    Purpose: Digital a-Si flat panel (FP) x-ray detectors can exhibit detector lag, or residual signal, of several percent that can cause ghosting in projection images or severe shading artifacts, known as the radar artifact, in cone-beam computed tomography (CBCT) reconstructions. A major contributor to detector lag is believed to be defect states, or traps, in the a-Si layer of the FP. Software methods to characterize and correct for the detector lag exist, but they may make assumptions such as system linearity and time invariance, which may not be true. The purpose of this work is to investigate a new hardware based method to reduce lag in an a-Si FP and to evaluate its effectiveness at removing shading artifacts in CBCT reconstructions. The feasibility of a novel, partially hardware based solution is also examined. Methods: The proposed hardware solution for lag reduction requires only a minor change to the FP. For pulsed irradiation, the proposed method inserts a new operation step between the readout and data collection stages. During this new stage the photodiode is operated in a forward bias mode, which fills the defect states with charge. A Varian 4030CB panel was modified to allow for operation in the forward bias mode. The contrast of residual lag ghosts was measured for lag frames 2 and 100 after irradiation ceased for standard and forward bias modes. Detector step response, lag, SNR, modulation transfer function (MTF), and detective quantum efficiency (DQE) measurements were made with standard and forward bias firmware. CBCT data of pelvic and head phantoms were also collected. Results: Overall, the 2nd and 100th detector lag frame residual signals were reduced 70%-88% using the new method. SNR, MTF, and DQE measurements show a small decrease in collected signal and a small increase in noise. The forward bias hardware successfully reduced the radar artifact in the CBCT reconstruction of the pelvic and head phantoms by 48%-81%. Conclusions: Overall, the

  14. Methods of Reducing Bias in Combined Thermal/Epithermal Neutron (CTEN) Assays of Heterogeneous Waste

    Energy Technology Data Exchange (ETDEWEB)

    Estep, R.J.; Melton, S.; Miko, D.

    1998-11-17

    We examined the effectiveness of two different methods for correcting CTEN passive and active assays for bias due to variations in the source position in different drum types. Both use the same drum-averaged correction determined from a neural network trained to active flux monitor ratios as a starting point. One method then uses a neural network to obtain a spatial correction factor sensitive to the source location. The other method uses emission tomography. Both methods were found to give significantly improved assay accuracy over the drum-averaged correction, although more study is needed to determine which method works better.

  15. Methods of Reducing Bias in Combined Thermal/Epithermal Neutron (CTEN) Assays of Heterogeneous Waste

    International Nuclear Information System (INIS)

    Estep, R.J.; Melton, S.; Miko, D.

    1998-01-01

    We examined the effectiveness of two different methods for correcting CTEN passive and active assays for bias due to variations in the source position in different drum types. Both use the same drum-averaged correction determined from a neural network trained to active flux monitor ratios as a starting point. One method then uses a neural network to obtain a spatial correction factor sensitive to the source location. The other method uses emission tomography. Both methods were found to give significantly improved assay accuracy over the drum-averaged correction, although more study is needed to determine which method works better

  16. A Novel Bias Correction Method for Soil Moisture and Ocean Salinity (SMOS Soil Moisture: Retrieval Ensembles

    Directory of Open Access Journals (Sweden)

    Ju Hyoung Lee

    2015-12-01

    Full Text Available Bias correction is a very important pre-processing step in satellite data assimilation analysis, as data assimilation itself cannot circumvent satellite biases. We introduce a retrieval algorithm-specific and spatially heterogeneous Instantaneous Field of View (IFOV bias correction method for Soil Moisture and Ocean Salinity (SMOS soil moisture. To the best of our knowledge, this is the first paper to present the probabilistic presentation of SMOS soil moisture using retrieval ensembles. We illustrate that retrieval ensembles effectively mitigated the overestimation problem of SMOS soil moisture arising from brightness temperature errors over West Africa in a computationally efficient way (ensemble size: 12, no time-integration. In contrast, the existing method of Cumulative Distribution Function (CDF matching considerably increased the SMOS biases, due to the limitations of relying on the imperfect reference data. From the validation at two semi-arid sites, Benin (moderately wet and vegetated area and Niger (dry and sandy bare soils, it was shown that the SMOS errors arising from rain and vegetation attenuation were appropriately corrected by ensemble approaches. In Benin, the Root Mean Square Errors (RMSEs decreased from 0.1248 m3/m3 for CDF matching to 0.0678 m3/m3 for the proposed ensemble approach. In Niger, the RMSEs decreased from 0.14 m3/m3 for CDF matching to 0.045 m3/m3 for the ensemble approach.

  17. Can bias correction and statistical downscaling methods improve the skill of seasonal precipitation forecasts?

    Science.gov (United States)

    Manzanas, R.; Lucero, A.; Weisheimer, A.; Gutiérrez, J. M.

    2018-02-01

    Statistical downscaling methods are popular post-processing tools which are widely used in many sectors to adapt the coarse-resolution biased outputs from global climate simulations to the regional-to-local scale typically required by users. They range from simple and pragmatic Bias Correction (BC) methods, which directly adjust the model outputs of interest (e.g. precipitation) according to the available local observations, to more complex Perfect Prognosis (PP) ones, which indirectly derive local predictions (e.g. precipitation) from appropriate upper-air large-scale model variables (predictors). Statistical downscaling methods have been extensively used and critically assessed in climate change applications; however, their advantages and limitations in seasonal forecasting are not well understood yet. In particular, a key problem in this context is whether they serve to improve the forecast quality/skill of raw model outputs beyond the adjustment of their systematic biases. In this paper we analyze this issue by applying two state-of-the-art BC and two PP methods to downscale precipitation from a multimodel seasonal hindcast in a challenging tropical region, the Philippines. To properly assess the potential added value beyond the reduction of model biases, we consider two validation scores which are not sensitive to changes in the mean (correlation and reliability categories). Our results show that, whereas BC methods maintain or worsen the skill of the raw model forecasts, PP methods can yield significant skill improvement (worsening) in cases for which the large-scale predictor variables considered are better (worse) predicted by the model than precipitation. For instance, PP methods are found to increase (decrease) model reliability in nearly 40% of the stations considered in boreal summer (autumn). Therefore, the choice of a convenient downscaling approach (either BC or PP) depends on the region and the season.

  18. A New Online Calibration Method Based on Lord's Bias-Correction.

    Science.gov (United States)

    He, Yinhong; Chen, Ping; Li, Yong; Zhang, Shumei

    2017-09-01

    Online calibration technique has been widely employed to calibrate new items due to its advantages. Method A is the simplest online calibration method and has attracted many attentions from researchers recently. However, a key assumption of Method A is that it treats person-parameter estimates θ ^ s (obtained by maximum likelihood estimation [MLE]) as their true values θ s , thus the deviation of the estimated θ ^ s from their true values might yield inaccurate item calibration when the deviation is nonignorable. To improve the performance of Method A, a new method, MLE-LBCI-Method A, is proposed. This new method combines a modified Lord's bias-correction method (named as maximum likelihood estimation-Lord's bias-correction with iteration [MLE-LBCI]) with the original Method A in an effort to correct the deviation of θ ^ s which may adversely affect the item calibration precision. Two simulation studies were carried out to explore the performance of both MLE-LBCI and MLE-LBCI-Method A under several scenarios. Simulation results showed that MLE-LBCI could make a significant improvement over the ML ability estimates, and MLE-LBCI-Method A did outperform Method A in almost all experimental conditions.

  19. Can health workers reliably assess their own work? A test-retest study of bias among data collectors conducting a Lot Quality Assurance Sampling survey in Uganda.

    Science.gov (United States)

    Beckworth, Colin A; Davis, Rosemary H; Faragher, Brian; Valadez, Joseph J

    2015-03-01

    Lot Quality Assurance Sampling (LQAS) is a classification method that enables local health staff to assess health programmes for which they are responsible. While LQAS has been favourably reviewed by the World Bank and World Health Organization (WHO), questions remain about whether using local health staff as data collectors can lead to biased data. In this test-retest research, Pallisa Health District in Uganda is subdivided into four administrative units called supervision areas (SA). Data collectors from each SA conducted an LQAS survey. A week later, the data collectors were swapped to a different SA, outside their area of responsibility, to repeat the LQAS survey with the same respondents. The two data sets were analysed for agreement using Cohens' kappa coefficient and disagreements were analysed. Kappa values ranged from 0.19 to 0.97. On average, there was a moderate degree of agreement for knowledge indicators and a substantial level for practice indicators. Respondents were found to be systematically more knowledgeable on retest indicating bias favouring the retest, although no evidence of bias was found for practices indicators. In this initial study, using local health care providers to collect data did not bias data collection. The bias observed in the knowledge indicators is most likely due to the 'practice effect', whereby respondents increased their knowledge as a result of completing the first survey, as no corresponding effect was seen in the practices indicators. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2014; all rights reserved.

  20. Hydrological modeling as an evaluation tool of EURO-CORDEX climate projections and bias correction methods

    Science.gov (United States)

    Hakala, Kirsti; Addor, Nans; Seibert, Jan

    2017-04-01

    Streamflow stemming from Switzerland's mountainous landscape will be influenced by climate change, which will pose significant challenges to the water management and policy sector. In climate change impact research, the determination of future streamflow is impeded by different sources of uncertainty, which propagate through the model chain. In this research, we explicitly considered the following sources of uncertainty: (1) climate models, (2) downscaling of the climate projections to the catchment scale, (3) bias correction method and (4) parameterization of the hydrological model. We utilize climate projections at the 0.11 degree 12.5 km resolution from the EURO-CORDEX project, which are the most recent climate projections for the European domain. EURO-CORDEX is comprised of regional climate model (RCM) simulations, which have been downscaled from global climate models (GCMs) from the CMIP5 archive, using both dynamical and statistical techniques. Uncertainties are explored by applying a modeling chain involving 14 GCM-RCMs to ten Swiss catchments. We utilize the rainfall-runoff model HBV Light, which has been widely used in operational hydrological forecasting. The Lindström measure, a combination of model efficiency and volume error, was used as an objective function to calibrate HBV Light. Ten best sets of parameters are then achieved by calibrating using the genetic algorithm and Powell optimization (GAP) method. The GAP optimization method is based on the evolution of parameter sets, which works by selecting and recombining high performing parameter sets with each other. Once HBV is calibrated, we then perform a quantitative comparison of the influence of biases inherited from climate model simulations to the biases stemming from the hydrological model. The evaluation is conducted over two time periods: i) 1980-2009 to characterize the simulation realism under the current climate and ii) 2070-2099 to identify the magnitude of the projected change of

  1. A Bayesian Method for Weighted Sampling

    OpenAIRE

    Lo, Albert Y.

    1993-01-01

    Bayesian statistical inference for sampling from weighted distribution models is studied. Small-sample Bayesian bootstrap clone (BBC) approximations to the posterior distribution are discussed. A second-order property for the BBC in unweighted i.i.d. sampling is given. A consequence is that BBC approximations to a posterior distribution of the mean and to the sampling distribution of the sample average, can be made asymptotically accurate by a proper choice of the random variables that genera...

  2. 40 CFR Appendix I to Part 261 - Representative Sampling Methods

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 25 2010-07-01 2010-07-01 false Representative Sampling Methods I...—Representative Sampling Methods The methods and equipment used for sampling waste materials will vary with the form and consistency of the waste materials to be sampled. Samples collected using the sampling...

  3. Performance of bias-correction methods for exposure measurement error using repeated measurements with and without missing data.

    Science.gov (United States)

    Batistatou, Evridiki; McNamee, Roseanne

    2012-12-10

    It is known that measurement error leads to bias in assessing exposure effects, which can however, be corrected if independent replicates are available. For expensive replicates, two-stage (2S) studies that produce data 'missing by design', may be preferred over a single-stage (1S) study, because in the second stage, measurement of replicates is restricted to a sample of first-stage subjects. Motivated by an occupational study on the acute effect of carbon black exposure on respiratory morbidity, we compare the performance of several bias-correction methods for both designs in a simulation study: an instrumental variable method (EVROS IV) based on grouping strategies, which had been recommended especially when measurement error is large, the regression calibration and the simulation extrapolation methods. For the 2S design, either the problem of 'missing' data was ignored or the 'missing' data were imputed using multiple imputations. Both in 1S and 2S designs, in the case of small or moderate measurement error, regression calibration was shown to be the preferred approach in terms of root mean square error. For 2S designs, regression calibration as implemented by Stata software is not recommended in contrast to our implementation of this method; the 'problematic' implementation of regression calibration although substantially improved with use of multiple imputations. The EVROS IV method, under a good/fairly good grouping, outperforms the regression calibration approach in both design scenarios when exposure mismeasurement is severe. Both in 1S and 2S designs with moderate or large measurement error, simulation extrapolation severely failed to correct for bias. Copyright © 2012 John Wiley & Sons, Ltd.

  4. An Importance Sampling Simulation Method for Bayesian Decision Feedback Equalizers

    OpenAIRE

    Chen, S.; Hanzo, L.

    2000-01-01

    An importance sampling (IS) simulation technique is presented for evaluating the lower-bound bit error rate (BER) of the Bayesian decision feedback equalizer (DFE) under the assumption of correct decisions being fed back. A design procedure is developed, which chooses appropriate bias vectors for the simulation density to ensure asymptotic efficiency of the IS simulation.

  5. A New Variational Method for Bias Correction and Its Applications to Rodent Brain Extraction.

    Science.gov (United States)

    Chang, Huibin; Huang, Weimin; Wu, Chunlin; Huang, Su; Guan, Cuntai; Sekar, Sakthivel; Bhakoo, Kishore Kumar; Duan, Yuping

    2017-03-01

    Brain extraction is an important preprocessing step for further analysis of brain MR images. Significant intensity inhomogeneity can be observed in rodent brain images due to the high-field MRI technique. Unlike most existing brain extraction methods that require bias corrected MRI, we present a high-order and L 0 regularized variational model for bias correction and brain extraction. The model is composed of a data fitting term, a piecewise constant regularization and a smooth regularization, which is constructed on a 3-D formulation for medical images with anisotropic voxel sizes. We propose an efficient multi-resolution algorithm for fast computation. At each resolution layer, we solve an alternating direction scheme, all subproblems of which have the closed-form solutions. The method is tested on three T2 weighted acquisition configurations comprising a total of 50 rodent brain volumes, which are with the acquisition field strengths of 4.7 Tesla, 9.4 Tesla and 17.6 Tesla, respectively. On one hand, we compare the results of bias correction with N3 and N4 in terms of the coefficient of variations on 20 different tissues of rodent brain. On the other hand, the results of brain extraction are compared against manually segmented gold standards, BET, BSE and 3-D PCNN based on a number of metrics. With the high accuracy and efficiency, our proposed method can facilitate automatic processing of large-scale brain studies.

  6. Log sampling methods and software for stand and landscape analyses.

    Science.gov (United States)

    Lisa J. Bate; Torolf R. Torgersen; Michael J. Wisdom; Edward O. Garton; Shawn C. Clabough

    2008-01-01

    We describe methods for efficient, accurate sampling of logs at landscape and stand scales to estimate density, total length, cover, volume, and weight. Our methods focus on optimizing the sampling effort by choosing an appropriate sampling method and transect length for specific forest conditions and objectives. Sampling methods include the line-intersect method and...

  7. Comparability of river suspended-sediment sampling and laboratory analysis methods

    Science.gov (United States)

    Groten, Joel T.; Johnson, Gregory D.

    2018-03-06

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

  8. A method of estimating GPS instrumental biases with a convolution algorithm

    Science.gov (United States)

    Li, Qi; Ma, Guanyi; Lu, Weijun; Wan, Qingtao; Fan, Jiangtao; Wang, Xiaolan; Li, Jinghua; Li, Changhua

    2018-03-01

    This paper presents a method of deriving the instrumental differential code biases (DCBs) of GPS satellites and dual frequency receivers. Considering that the total electron content (TEC) varies smoothly over a small area, one ionospheric pierce point (IPP) and four more nearby IPPs were selected to build an equation with a convolution algorithm. In addition, unknown DCB parameters were arranged into a set of equations with GPS observations in a day unit by assuming that DCBs do not vary within a day. Then, the DCBs of satellites and receivers were determined by solving the equation set with the least-squares fitting technique. The performance of this method is examined by applying it to 361 days in 2014 using the observation data from 1311 GPS Earth Observation Network (GEONET) receivers. The result was crosswise-compared with the DCB estimated by the mesh method and the IONEX products from the Center for Orbit Determination in Europe (CODE). The DCB values derived by this method agree with those of the mesh method and the CODE products, with biases of 0.091 ns and 0.321 ns, respectively. The convolution method's accuracy and stability were quite good and showed improvements over the mesh method.

  9. Can Memory Bias be Modified? The Effects of an Explicit Cued-Recall Training in Two Independent Samples

    NARCIS (Netherlands)

    Vrijsen, J.N.; Becker, E.S.; Rinck, M.; Oostrom, I.I.H. van; Speckens, A.E.M.; Whitmer, A.; Gotlib, I.H.

    2014-01-01

    Cognitive bias modification (CBM) has been found to be effective in modifying information-processing biases and in reducing emotional reactivity to stress. Although modification of attention and interpretation biases has frequently been studied, it is not clear whether memory bias can be manipulated

  10. Sampling for Patient Exit Interviews: Assessment of Methods Using Mathematical Derivation and Computer Simulations.

    Science.gov (United States)

    Geldsetzer, Pascal; Fink, Günther; Vaikath, Maria; Bärnighausen, Till

    2018-02-01

    (1) To evaluate the operational efficiency of various sampling methods for patient exit interviews; (2) to discuss under what circumstances each method yields an unbiased sample; and (3) to propose a new, operationally efficient, and unbiased sampling method. Literature review, mathematical derivation, and Monte Carlo simulations. Our simulations show that in patient exit interviews it is most operationally efficient if the interviewer, after completing an interview, selects the next patient exiting the clinical consultation. We demonstrate mathematically that this method yields a biased sample: patients who spend a longer time with the clinician are overrepresented. This bias can be removed by selecting the next patient who enters, rather than exits, the consultation room. We show that this sampling method is operationally more efficient than alternative methods (systematic and simple random sampling) in most primary health care settings. Under the assumption that the order in which patients enter the consultation room is unrelated to the length of time spent with the clinician and the interviewer, selecting the next patient entering the consultation room tends to be the operationally most efficient unbiased sampling method for patient exit interviews. © 2016 The Authors. Health Services Research published by Wiley Periodicals, Inc. on behalf of Health Research and Educational Trust.

  11. Detecting evidence for CO2 fertilization from tree ring studies: The potential role of sampling biases

    NARCIS (Netherlands)

    Brienen, R.J.W.; Gloor, E.; Zuidema, P.A.

    2012-01-01

    Tree ring analysis allows reconstructing historical growth rates over long periods. Several studies have reported an increasing trend in ring widths, often attributed to growth stimulation by increasing atmospheric CO2 concentration. However, these trends may also have been caused by sampling

  12. The proportionator: unbiased stereological estimation using biased automatic image analysis and non-uniform probability proportional to size sampling

    DEFF Research Database (Denmark)

    Gardi, Jonathan Eyal; Nyengaard, Jens Randel; Gundersen, Hans Jørgen Gottlieb

    2008-01-01

    examined, which in turn leads to any of the known stereological estimates, including size distributions and spatial distributions. The unbiasedness is not a function of the assumed relation between the weight and the structure, which is in practice always a biased relation from a stereological (integral......, the desired number of fields are sampled automatically with probability proportional to the weight and presented to the expert observer. Using any known stereological probe and estimator, the correct count in these fields leads to a simple, unbiased estimate of the total amount of structure in the sections...... geometric) point of view. The efficiency of the proportionator depends, however, directly on this relation to be positive. The sampling and estimation procedure is simulated in sections with characteristics and various kinds of noises in possibly realistic ranges. In all cases examined, the proportionator...

  13. Statistical sampling methods for soils monitoring

    Science.gov (United States)

    Ann M. Abbott

    2010-01-01

    Development of the best sampling design to answer a research question should be an interactive venture between the land manager or researcher and statisticians, and is the result of answering various questions. A series of questions that can be asked to guide the researcher in making decisions that will arrive at an effective sampling plan are described, and a case...

  14. Survey research with a random digit dial national mobile phone sample in Ghana: Methods and sample quality

    Science.gov (United States)

    Sefa, Eunice; Adimazoya, Edward Akolgo; Yartey, Emmanuel; Lenzi, Rachel; Tarpo, Cindy; Heward-Mills, Nii Lante; Lew, Katherine; Ampeh, Yvonne

    2018-01-01

    Introduction Generating a nationally representative sample in low and middle income countries typically requires resource-intensive household level sampling with door-to-door data collection. High mobile phone penetration rates in developing countries provide new opportunities for alternative sampling and data collection methods, but there is limited information about response rates and sample biases in coverage and nonresponse using these methods. We utilized data from an interactive voice response, random-digit dial, national mobile phone survey in Ghana to calculate standardized response rates and assess representativeness of the obtained sample. Materials and methods The survey methodology was piloted in two rounds of data collection. The final survey included 18 demographic, media exposure, and health behavior questions. Call outcomes and response rates were calculated according to the American Association of Public Opinion Research guidelines. Sample characteristics, productivity, and costs per interview were calculated. Representativeness was assessed by comparing data to the Ghana Demographic and Health Survey and the National Population and Housing Census. Results The survey was fielded during a 27-day period in February-March 2017. There were 9,469 completed interviews and 3,547 partial interviews. Response, cooperation, refusal, and contact rates were 31%, 81%, 7%, and 39% respectively. Twenty-three calls were dialed to produce an eligible contact: nonresponse was substantial due to the automated calling system and dialing of many unassigned or non-working numbers. Younger, urban, better educated, and male respondents were overrepresented in the sample. Conclusions The innovative mobile phone data collection methodology yielded a large sample in a relatively short period. Response rates were comparable to other surveys, although substantial coverage bias resulted from fewer women, rural, and older residents completing the mobile phone survey in

  15. Practical Bias Correction in Aerial Surveys of Large Mammals: Validation of Hybrid Double-Observer with Sightability Method against Known Abundance of Feral Horse (Equus caballus) Populations.

    Science.gov (United States)

    Lubow, Bruce C; Ransom, Jason I

    2016-01-01

    Reliably estimating wildlife abundance is fundamental to effective management. Aerial surveys are one of the only spatially robust tools for estimating large mammal populations, but statistical sampling methods are required to address detection biases that affect accuracy and precision of the estimates. Although various methods for correcting aerial survey bias are employed on large mammal species around the world, these have rarely been rigorously validated. Several populations of feral horses (Equus caballus) in the western United States have been intensively studied, resulting in identification of all unique individuals. This provided a rare opportunity to test aerial survey bias correction on populations of known abundance. We hypothesized that a hybrid method combining simultaneous double-observer and sightability bias correction techniques would accurately estimate abundance. We validated this integrated technique on populations of known size and also on a pair of surveys before and after a known number was removed. Our analysis identified several covariates across the surveys that explained and corrected biases in the estimates. All six tests on known populations produced estimates with deviations from the known value ranging from -8.5% to +13.7% and corrected by our statistical models. Our results validate the hybrid method, highlight its potentially broad applicability, identify some limitations, and provide insight and guidance for improving survey designs.

  16. Bias correction for estimated QTL effects using the penalized maximum likelihood method.

    Science.gov (United States)

    Zhang, J; Yue, C; Zhang, Y-M

    2012-04-01

    A penalized maximum likelihood method has been proposed as an important approach to the detection of epistatic quantitative trait loci (QTL). However, this approach is not optimal in two special situations: (1) closely linked QTL with effects in opposite directions and (2) small-effect QTL, because the method produces downwardly biased estimates of QTL effects. The present study aims to correct the bias by using correction coefficients and shifting from the use of a uniform prior on the variance parameter of a QTL effect to that of a scaled inverse chi-square prior. The results of Monte Carlo simulation experiments show that the improved method increases the power from 25 to 88% in the detection of two closely linked QTL of equal size in opposite directions and from 60 to 80% in the identification of QTL with small effects (0.5% of the total phenotypic variance). We used the improved method to detect QTL responsible for the barley kernel weight trait using 145 doubled haploid lines developed in the North American Barley Genome Mapping Project. Application of the proposed method to other shrinkage estimation of QTL effects is discussed.

  17. Serum chromium levels sampled with steel needle versus plastic IV cannula. Does method matter?

    DEFF Research Database (Denmark)

    Penny, Jeannette Ø; Overgaard, Søren

    2010-01-01

    PURPOSE: Modern metal-on-metal (MoM) joint articulations releases metal ions to the body. Research tries to establish how much this elevates metal ion levels and whether it causes adverse effects. The steel needle that samples the blood may introduce additional chromium to the sample thereby...... causing bias. This study aimed to test that theory. METHODS: We compared serum chromium values for two sampling methods, steel needle and IV plastic cannula, as well as sampling sequence in 16 healthy volunteers. RESULTS: We found statistically significant chromium contamination from the steel needle...... with mean differences between the two methods of 0.073 ng/mL, for the first sample, and 0.033 ng/mL for the second. No difference was found between the first and second plastic sample. The first steel needle sample contained an average of 0.047 ng/mL more than the second. This difference was only borderline...

  18. A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

    Science.gov (United States)

    Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

    2011-01-01

    Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

  19. Evaluation of Sampling Methods for Bacillus Spore ...

    Science.gov (United States)

    Journal Article Following a wide area release of biological materials, mapping the extent of contamination is essential for orderly response and decontamination operations. HVAC filters process large volumes of air and therefore collect highly representative particulate samples in buildings. HVAC filter extraction may have great utility in rapidly estimating the extent of building contamination following a large-scale incident. However, until now, no studies have been conducted comparing the two most appropriate sampling approaches for HVAC filter materials: direct extraction and vacuum-based sampling.

  20. Multiple histogram method and static Monte Carlo sampling

    NARCIS (Netherlands)

    Inda, M.A.; Frenkel, D.

    2004-01-01

    We describe an approach to use multiple-histogram methods in combination with static, biased Monte Carlo simulations. To illustrate this, we computed the force-extension curve of an athermal polymer from multiple histograms constructed in a series of static Rosenbluth Monte Carlo simulations. From

  1. Experimental determination of isotope enrichment factors – bias from mass removal by repetitive sampling

    DEFF Research Database (Denmark)

    Buchner, Daniel; Jin, Biao; Ebert, Karin

    2017-01-01

    to account for mass removal and for volatilization into the headspace. In this study we use both synthetic and experimental data to demonstrate that the determination of ε-values according to current correction methods is prone to considerable systematic errors even in well-designed experimental setups....... Application of inappropriate methods may lead to incorrect and inconsistent ε-values entailing misinterpretations regarding the processes underlying isotope fractionation. In fact, our results suggest that artifacts arising from inappropriate data evaluation might contribute to the variability of published ε...

  2. Exponentially Biased Ground-State Sampling of Quantum Annealing Machines with Transverse-Field Driving Hamiltonians.

    Science.gov (United States)

    Mandrà, Salvatore; Zhu, Zheng; Katzgraber, Helmut G

    2017-02-17

    We study the performance of the D-Wave 2X quantum annealing machine on systems with well-controlled ground-state degeneracy. While obtaining the ground state of a spin-glass benchmark instance represents a difficult task, the gold standard for any optimization algorithm or machine is to sample all solutions that minimize the Hamiltonian with more or less equal probability. Our results show that while naive transverse-field quantum annealing on the D-Wave 2X device can find the ground-state energy of the problems, it is not well suited in identifying all degenerate ground-state configurations associated with a particular instance. Even worse, some states are exponentially suppressed, in agreement with previous studies on toy model problems [New J. Phys. 11, 073021 (2009)NJOPFM1367-263010.1088/1367-2630/11/7/073021]. These results suggest that more complex driving Hamiltonians are needed in future quantum annealing machines to ensure a fair sampling of the ground-state manifold.

  3. Survey research with a random digit dial national mobile phone sample in Ghana: Methods and sample quality.

    Science.gov (United States)

    L'Engle, Kelly; Sefa, Eunice; Adimazoya, Edward Akolgo; Yartey, Emmanuel; Lenzi, Rachel; Tarpo, Cindy; Heward-Mills, Nii Lante; Lew, Katherine; Ampeh, Yvonne

    2018-01-01

    Generating a nationally representative sample in low and middle income countries typically requires resource-intensive household level sampling with door-to-door data collection. High mobile phone penetration rates in developing countries provide new opportunities for alternative sampling and data collection methods, but there is limited information about response rates and sample biases in coverage and nonresponse using these methods. We utilized data from an interactive voice response, random-digit dial, national mobile phone survey in Ghana to calculate standardized response rates and assess representativeness of the obtained sample. The survey methodology was piloted in two rounds of data collection. The final survey included 18 demographic, media exposure, and health behavior questions. Call outcomes and response rates were calculated according to the American Association of Public Opinion Research guidelines. Sample characteristics, productivity, and costs per interview were calculated. Representativeness was assessed by comparing data to the Ghana Demographic and Health Survey and the National Population and Housing Census. The survey was fielded during a 27-day period in February-March 2017. There were 9,469 completed interviews and 3,547 partial interviews. Response, cooperation, refusal, and contact rates were 31%, 81%, 7%, and 39% respectively. Twenty-three calls were dialed to produce an eligible contact: nonresponse was substantial due to the automated calling system and dialing of many unassigned or non-working numbers. Younger, urban, better educated, and male respondents were overrepresented in the sample. The innovative mobile phone data collection methodology yielded a large sample in a relatively short period. Response rates were comparable to other surveys, although substantial coverage bias resulted from fewer women, rural, and older residents completing the mobile phone survey in comparison to household surveys. Random digit dialing of mobile

  4. Survey research with a random digit dial national mobile phone sample in Ghana: Methods and sample quality.

    Directory of Open Access Journals (Sweden)

    Kelly L'Engle

    Full Text Available Generating a nationally representative sample in low and middle income countries typically requires resource-intensive household level sampling with door-to-door data collection. High mobile phone penetration rates in developing countries provide new opportunities for alternative sampling and data collection methods, but there is limited information about response rates and sample biases in coverage and nonresponse using these methods. We utilized data from an interactive voice response, random-digit dial, national mobile phone survey in Ghana to calculate standardized response rates and assess representativeness of the obtained sample.The survey methodology was piloted in two rounds of data collection. The final survey included 18 demographic, media exposure, and health behavior questions. Call outcomes and response rates were calculated according to the American Association of Public Opinion Research guidelines. Sample characteristics, productivity, and costs per interview were calculated. Representativeness was assessed by comparing data to the Ghana Demographic and Health Survey and the National Population and Housing Census.The survey was fielded during a 27-day period in February-March 2017. There were 9,469 completed interviews and 3,547 partial interviews. Response, cooperation, refusal, and contact rates were 31%, 81%, 7%, and 39% respectively. Twenty-three calls were dialed to produce an eligible contact: nonresponse was substantial due to the automated calling system and dialing of many unassigned or non-working numbers. Younger, urban, better educated, and male respondents were overrepresented in the sample.The innovative mobile phone data collection methodology yielded a large sample in a relatively short period. Response rates were comparable to other surveys, although substantial coverage bias resulted from fewer women, rural, and older residents completing the mobile phone survey in comparison to household surveys. Random digit

  5. Active Search on Carcasses versus Pitfall Traps: a Comparison of Sampling Methods.

    Science.gov (United States)

    Zanetti, N I; Camina, R; Visciarelli, E C; Centeno, N D

    2016-04-01

    The study of insect succession in cadavers and the classification of arthropods have mostly been done by placing a carcass in a cage, protected from vertebrate scavengers, which is then visited periodically. An alternative is to use specific traps. Few studies on carrion ecology and forensic entomology involving the carcasses of large vertebrates have employed pitfall traps. The aims of this study were to compare both sampling methods (active search on a carcass and pitfall trapping) for each coleopteran family, and to establish whether there is a discrepancy (underestimation and/or overestimation) in the presence of each family by either method. A great discrepancy was found for almost all families with some of them being more abundant in samples obtained through active search on carcasses and others in samples from traps, whereas two families did not show any bias towards a given sampling method. The fact that families may be underestimated or overestimated by the type of sampling technique highlights the importance of combining both methods, active search on carcasses and pitfall traps, in order to obtain more complete information on decomposition, carrion habitat and cadaveric families or species. Furthermore, a hypothesis advanced on the reasons for the underestimation by either sampling method showing biases towards certain families. Information about the sampling techniques indicating which would be more appropriate to detect or find a particular family is provided.

  6. A High Precision Laser-Based Autofocus Method Using Biased Image Plane for Microscopy

    Directory of Open Access Journals (Sweden)

    Chao-Chen Gu

    2018-01-01

    Full Text Available This study designs and accomplishes a high precision and robust laser-based autofocusing system, in which a biased image plane is applied. In accordance to the designed optics, a cluster-based circle fitting algorithm is proposed to calculate the radius of the detecting spot from the reflected laser beam as an essential factor to obtain the defocus value. The experiment conduct on the experiment device achieved novel performance of high precision and robustness. Furthermore, the low demand of assembly accuracy makes the proposed method a low-cost and realizable solution for autofocusing technique.

  7. Comparison of some biased estimation methods (including ordinary subset regression) in the linear model

    Science.gov (United States)

    Sidik, S. M.

    1975-01-01

    Ridge, Marquardt's generalized inverse, shrunken, and principal components estimators are discussed in terms of the objectives of point estimation of parameters, estimation of the predictive regression function, and hypothesis testing. It is found that as the normal equations approach singularity, more consideration must be given to estimable functions of the parameters as opposed to estimation of the full parameter vector; that biased estimators all introduce constraints on the parameter space; that adoption of mean squared error as a criterion of goodness should be independent of the degree of singularity; and that ordinary least-squares subset regression is the best overall method.

  8. Sample Size Calculations for Population Size Estimation Studies Using Multiplier Methods With Respondent-Driven Sampling Surveys.

    Science.gov (United States)

    Fearon, Elizabeth; Chabata, Sungai T; Thompson, Jennifer A; Cowan, Frances M; Hargreaves, James R

    2017-09-14

    While guidance exists for obtaining population size estimates using multiplier methods with respondent-driven sampling surveys, we lack specific guidance for making sample size decisions. To guide the design of multiplier method population size estimation studies using respondent-driven sampling surveys to reduce the random error around the estimate obtained. The population size estimate is obtained by dividing the number of individuals receiving a service or the number of unique objects distributed (M) by the proportion of individuals in a representative survey who report receipt of the service or object (P). We have developed an approach to sample size calculation, interpreting methods to estimate the variance around estimates obtained using multiplier methods in conjunction with research into design effects and respondent-driven sampling. We describe an application to estimate the number of female sex workers in Harare, Zimbabwe. There is high variance in estimates. Random error around the size estimate reflects uncertainty from M and P, particularly when the estimate of P in the respondent-driven sampling survey is low. As expected, sample size requirements are higher when the design effect of the survey is assumed to be greater. We suggest a method for investigating the effects of sample size on the precision of a population size estimate obtained using multipler methods and respondent-driven sampling. Uncertainty in the size estimate is high, particularly when P is small, so balancing against other potential sources of bias, we advise researchers to consider longer service attendance reference periods and to distribute more unique objects, which is likely to result in a higher estimate of P in the respondent-driven sampling survey. ©Elizabeth Fearon, Sungai T Chabata, Jennifer A Thompson, Frances M Cowan, James R Hargreaves. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.09.2017.

  9. 19 CFR 151.70 - Method of sampling by Customs.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 2 2010-04-01 2010-04-01 false Method of sampling by Customs. 151.70 Section 151... THE TREASURY (CONTINUED) EXAMINATION, SAMPLING, AND TESTING OF MERCHANDISE Wool and Hair § 151.70 Method of sampling by Customs. A general sample shall be taken from each sampling unit, unless it is not...

  10. An Improved Dynamical Downscaling Method with GCM Bias Corrections and Its Validation with 30 Years of Climate Simulations

    KAUST Repository

    Xu, Zhongfeng; Yang, Zong-Liang

    2012-01-01

    An improved dynamical downscaling method (IDD) with general circulation model (GCM) bias corrections is developed and assessed over North America. A set of regional climate simulations is performed with the Weather Research and Forecasting Model

  11. [The importance of memory bias in obtaining age of menarche by recall method in Brazilian adolescents].

    Science.gov (United States)

    Castilho, Silvia Diez; Nucci, Luciana Bertoldi; Assuino, Samanta Ramos; Hansen, Lucca Ortolan

    2014-06-01

    To compare the age at menarche obtained by recall method according to the time elapsed since the event, in order to verify the importance of the recall bias. Were evaluated 1,671 girls (7-18 years) at schools in Campinas-SP regarding the occurrence of menarche by the status quo method (menarche: yes or no) and the recall method (date of menarche, for those who mentioned it). The age at menarche obtained by the status quo method was calculated by logit, which considers the whole group, and the age obtained by the recall method was calculated as the average of the mentioned age at menarche. In this group, the age at menarche was obtained by the difference between the date of the event and the date of birth. Girls who reported menarche (883, 52.8%) were divided into four groups according to the time elapsed since the event. To analyze the results, we used ANOVA and logistic regression for the analysis, with a significance level of 0.05. The age at menarche calculated by logit was 12.14 y/o (95% CI 12.08 to 12.20). Mean ages obtained by recall were: for those who experienced menarche within the previous year 12.26 y/o (±1.14), between > 1-2 years before, 12.29 y (±1.22); between > 2-3 years before, 12.23 y/o (±1.27); and more than 3 years before, 11.55y/o (±1.24), p recall method was similar for girls who menstruated within the previous 3 years (and approaches the age calculated by logit); when more than 3 years have passed, the recall bias was significant.

  12. Perpendicular distance sampling: an alternative method for sampling downed coarse woody debris

    Science.gov (United States)

    Michael S. Williams; Jeffrey H. Gove

    2003-01-01

    Coarse woody debris (CWD) plays an important role in many forest ecosystem processes. In recent years, a number of new methods have been proposed to sample CWD. These methods select individual logs into the sample using some form of unequal probability sampling. One concern with most of these methods is the difficulty in estimating the volume of each log. A new method...

  13. Phylogenetic uncertainty can bias the number of evolutionary transitions estimated from ancestral state reconstruction methods.

    Science.gov (United States)

    Duchêne, Sebastian; Lanfear, Robert

    2015-09-01

    Ancestral state reconstruction (ASR) is a popular method for exploring the evolutionary history of traits that leave little or no trace in the fossil record. For example, it has been used to test hypotheses about the number of evolutionary origins of key life-history traits such as oviparity, or key morphological structures such as wings. Many studies that use ASR have suggested that the number of evolutionary origins of such traits is higher than was previously thought. The scope of such inferences is increasing rapidly, facilitated by the construction of very large phylogenies and life-history databases. In this paper, we use simulations to show that the number of evolutionary origins of a trait tends to be overestimated when the phylogeny is not perfect. In some cases, the estimated number of transitions can be several fold higher than the true value. Furthermore, we show that the bias is not always corrected by standard approaches to account for phylogenetic uncertainty, such as repeating the analysis on a large collection of possible trees. These findings have important implications for studies that seek to estimate the number of origins of a trait, particularly those that use large phylogenies that are associated with considerable uncertainty. We discuss the implications of this bias, and methods to ameliorate it. © 2015 Wiley Periodicals, Inc.

  14. Cluster Sampling Bias in Government-Sponsored Evaluations: A Correlational Study of Employment and Welfare Pilots in England.

    Science.gov (United States)

    Vaganay, Arnaud

    2016-01-01

    For pilot or experimental employment programme results to apply beyond their test bed, researchers must select 'clusters' (i.e. the job centres delivering the new intervention) that are reasonably representative of the whole territory. More specifically, this requirement must account for conditions that could artificially inflate the effect of a programme, such as the fluidity of the local labour market or the performance of the local job centre. Failure to achieve representativeness results in Cluster Sampling Bias (CSB). This paper makes three contributions to the literature. Theoretically, it approaches the notion of CSB as a human behaviour. It offers a comprehensive theory, whereby researchers with limited resources and conflicting priorities tend to oversample 'effect-enhancing' clusters when piloting a new intervention. Methodologically, it advocates for a 'narrow and deep' scope, as opposed to the 'wide and shallow' scope, which has prevailed so far. The PILOT-2 dataset was developed to test this idea. Empirically, it provides evidence on the prevalence of CSB. In conditions similar to the PILOT-2 case study, investigators (1) do not sample clusters with a view to maximise generalisability; (2) do not oversample 'effect-enhancing' clusters; (3) consistently oversample some clusters, including those with higher-than-average client caseloads; and (4) report their sampling decisions in an inconsistent and generally poor manner. In conclusion, although CSB is prevalent, it is still unclear whether it is intentional and meant to mislead stakeholders about the expected effect of the intervention or due to higher-level constraints or other considerations.

  15. Sampling pig farms at the abattoir in a cross-sectional study - Evaluation of a sampling method.

    Science.gov (United States)

    Birkegård, Anna Camilla; Halasa, Tariq; Toft, Nils

    2017-09-15

    A cross-sectional study design is relatively inexpensive, fast and easy to conduct when compared to other study designs. Careful planning is essential to obtaining a representative sample of the population, and the recommended approach is to use simple random sampling from an exhaustive list of units in the target population. This approach is rarely feasible in practice, and other sampling procedures must often be adopted. For example, when slaughter pigs are the target population, sampling the pigs on the slaughter line may be an alternative to on-site sampling at a list of farms. However, it is difficult to sample a large number of farms from an exact predefined list, due to the logistics and workflow of an abattoir. Therefore, it is necessary to have a systematic sampling procedure and to evaluate the obtained sample with respect to the study objective. We propose a method for 1) planning, 2) conducting, and 3) evaluating the representativeness and reproducibility of a cross-sectional study when simple random sampling is not possible. We used an example of a cross-sectional study with the aim of quantifying the association of antimicrobial resistance and antimicrobial consumption in Danish slaughter pigs. It was not possible to visit farms within the designated timeframe. Therefore, it was decided to use convenience sampling at the abattoir. Our approach was carried out in three steps: 1) planning: using data from meat inspection to plan at which abattoirs and how many farms to sample; 2) conducting: sampling was carried out at five abattoirs; 3) evaluation: representativeness was evaluated by comparing sampled and non-sampled farms, and the reproducibility of the study was assessed through simulated sampling based on meat inspection data from the period where the actual data collection was carried out. In the cross-sectional study samples were taken from 681 Danish pig farms, during five weeks from February to March 2015. The evaluation showed that the sampling

  16. Worry or craving? A selective review of evidence for food-related attention biases in obese individuals, eating-disorder patients, restrained eaters and healthy samples.

    Science.gov (United States)

    Werthmann, Jessica; Jansen, Anita; Roefs, Anne

    2015-05-01

    Living in an 'obesogenic' environment poses a serious challenge for weight maintenance. However, many people are able to maintain a healthy weight indicating that not everybody is equally susceptible to the temptations of this food environment. The way in which someone perceives and reacts to food cues, that is, cognitive processes, could underlie differences in susceptibility. An attention bias for food could be such a cognitive factor that contributes to overeating. However, an attention bias for food has also been implicated with restrained eating and eating-disorder symptomatology. The primary aim of the present review was to determine whether an attention bias for food is specifically related to obesity while also reviewing evidence for attention biases in eating-disorder patients, restrained eaters and healthy-weight individuals. Another aim was to systematically examine how selective attention for food relates (causally) to eating behaviour. Current empirical evidence on attention bias for food within obese samples, eating-disorder patients, and, even though to a lesser extent, in restrained eaters is contradictory. However, present experimental studies provide relatively consistent evidence that an attention bias for food contributes to subsequent food intake. This review highlights the need to distinguish not only between different (temporal) attention bias components, but also to take different motivations (craving v. worry) and their impact on attentional processing into account. Overall, the current state of research suggests that biased attention could be one important cognitive mechanism by which the food environment tempts us into overeating.

  17. Inviting parents to take part in paediatric palliative care research: a mixed-methods examination of selection bias.

    Science.gov (United States)

    Crocker, Joanna C; Beecham, Emma; Kelly, Paula; Dinsdale, Andrew P; Hemsley, June; Jones, Louise; Bluebond-Langner, Myra

    2015-03-01

    Recruitment to paediatric palliative care research is challenging, with high rates of non-invitation of eligible families by clinicians. The impact on sample characteristics is unknown. To investigate, using mixed methods, non-invitation of eligible families and ensuing selection bias in an interview study about parents' experiences of advance care planning (ACP). We examined differences between eligible families invited and not invited to participate by clinicians using (1) field notes of discussions with clinicians during the invitation phase and (2) anonymised information from the service's clinical database. Families were eligible for the ACP study if their child was receiving care from a UK-based tertiary palliative care service (Group A; N = 519) or had died 6-10 months previously having received care from the service (Group B; N = 73). Rates of non-invitation to the ACP study were high. A total of 28 (5.4%) Group A families and 21 (28.8%) Group B families (p research findings. Non-invitation and selection bias should be considered, assessed and reported in palliative care studies. © The Author(s) 2014.

  18. A method for additive bias correction in cross-cultural surveys

    DEFF Research Database (Denmark)

    Scholderer, Joachim; Grunert, Klaus G.; Brunsø, Karen

    2001-01-01

    additive bias from cross-cultural data. The procedure involves four steps: (1) embed a potentially biased item in a factor-analytic measurement model, (2) test for the existence of additive bias between populations, (3) use the factor-analytic model to estimate the magnitude of the bias, and (4) replace......Measurement bias in cross-cultural surveys can seriously threaten the validity of hypothesis tests. Direct comparisons of means depend on the assumption that differences in observed variables reflect differences in the underlying constructs, and not an additive bias that may be caused by cultural...... differences in the understanding of item wording or response category labels. However, experience suggests that additive bias can be found more often than not. Based on the concept of partial measurement invariance (Byrne, Shavelson and Muthén, 1989), the present paper develops a procedure for eliminating...

  19. Analysis of inconsistent source sampling in monte carlo weight-window variance reduction methods

    Directory of Open Access Journals (Sweden)

    David P. Griesheimer

    2017-09-01

    Full Text Available The application of Monte Carlo (MC to large-scale fixed-source problems has recently become possible with new hybrid methods that automate generation of parameters for variance reduction techniques. Two common variance reduction techniques, weight windows and source biasing, have been automated and popularized by the consistent adjoint-driven importance sampling (CADIS method. This method uses the adjoint solution from an inexpensive deterministic calculation to define a consistent set of weight windows and source particles for a subsequent MC calculation. One of the motivations for source consistency is to avoid the splitting or rouletting of particles at birth, which requires computational resources. However, it is not always possible or desirable to implement such consistency, which results in inconsistent source biasing. This paper develops an original framework that mathematically expresses the coupling of the weight window and source biasing techniques, allowing the authors to explore the impact of inconsistent source sampling on the variance of MC results. A numerical experiment supports this new framework and suggests that certain classes of problems may be relatively insensitive to inconsistent source sampling schemes with moderate levels of splitting and rouletting.

  20. Codon usage bias: causative factors, quantification methods and genome-wide patterns: with emphasis on insect genomes.

    Science.gov (United States)

    Behura, Susanta K; Severson, David W

    2013-02-01

    Codon usage bias refers to the phenomenon where specific codons are used more often than other synonymous codons during translation of genes, the extent of which varies within and among species. Molecular evolutionary investigations suggest that codon bias is manifested as a result of balance between mutational and translational selection of such genes and that this phenomenon is widespread across species and may contribute to genome evolution in a significant manner. With the advent of whole-genome sequencing of numerous species, both prokaryotes and eukaryotes, genome-wide patterns of codon bias are emerging in different organisms. Various factors such as expression level, GC content, recombination rates, RNA stability, codon position, gene length and others (including environmental stress and population size) can influence codon usage bias within and among species. Moreover, there has been a continuous quest towards developing new concepts and tools to measure the extent of codon usage bias of genes. In this review, we outline the fundamental concepts of evolution of the genetic code, discuss various factors that may influence biased usage of synonymous codons and then outline different principles and methods of measurement of codon usage bias. Finally, we discuss selected studies performed using whole-genome sequences of different insect species to show how codon bias patterns vary within and among genomes. We conclude with generalized remarks on specific emerging aspects of codon bias studies and highlight the recent explosion of genome-sequencing efforts on arthropods (such as twelve Drosophila species, species of ants, honeybee, Nasonia and Anopheles mosquitoes as well as the recent launch of a genome-sequencing project involving 5000 insects and other arthropods) that may help us to understand better the evolution of codon bias and its biological significance. © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society.

  1. Using Data-Dependent Priors to Mitigate Small Sample Bias in Latent Growth Models: A Discussion and Illustration Using M"plus"

    Science.gov (United States)

    McNeish, Daniel M.

    2016-01-01

    Mixed-effects models (MEMs) and latent growth models (LGMs) are often considered interchangeable save the discipline-specific nomenclature. Software implementations of these models, however, are not interchangeable, particularly with small sample sizes. Restricted maximum likelihood estimation that mitigates small sample bias in MEMs has not been…

  2. FFT swept filtering: a bias-free method for processing fringe signals in absolute gravimeters

    Science.gov (United States)

    Křen, Petr; Pálinkáš, Vojtech; Mašika, Pavel; Val'ko, Miloš

    2018-05-01

    Absolute gravimeters, based on laser interferometry, are widely used for many applications in geoscience and metrology. Although currently the most accurate FG5 and FG5X gravimeters declare standard uncertainties at the level of 2-3 μGal, their inherent systematic errors affect the gravity reference determined by international key comparisons based predominately on the use of FG5-type instruments. The measurement results for FG5-215 and FG5X-251 clearly showed that the measured g-values depend on the size of the fringe signal and that this effect might be approximated by a linear regression with a slope of up to 0.030 μGal/mV . However, these empirical results do not enable one to identify the source of the effect or to determine a reasonable reference fringe level for correcting g-values in an absolute sense. Therefore, both gravimeters were equipped with new measuring systems (according to Křen et al. in Metrologia 53:27-40, 2016. https://doi.org/10.1088/0026-1394/53/1/27 applied for FG5), running in parallel with the original systems. The new systems use an analogue-to-digital converter HS5 to digitize the fringe signal and a new method of fringe signal analysis based on FFT swept bandpass filtering. We demonstrate that the source of the fringe size effect is connected to a distortion of the fringe signal due to the electronic components used in the FG5(X) gravimeters. To obtain a bias-free g-value, the FFT swept method should be applied for the determination of zero-crossings. A comparison of g-values obtained from the new and the original systems clearly shows that the original system might be biased by approximately 3-5 μGal due to improperly distorted fringe signal processing.

  3. The impact of non-response bias due to sampling in public health studies: A comparison of voluntary versus mandatory recruitment in a Dutch national survey on adolescent health.

    Science.gov (United States)

    Cheung, Kei Long; Ten Klooster, Peter M; Smit, Cees; de Vries, Hein; Pieterse, Marcel E

    2017-03-23

    In public health monitoring of young people it is critical to understand the effects of selective non-response, in particular when a controversial topic is involved like substance abuse or sexual behaviour. Research that is dependent upon voluntary subject participation is particularly vulnerable to sampling bias. As respondents whose participation is hardest to elicit on a voluntary basis are also more likely to report risk behaviour, this potentially leads to underestimation of risk factor prevalence. Inviting adolescents to participate in a home-sent postal survey is a typical voluntary recruitment strategy with high non-response, as opposed to mandatory participation during school time. This study examines the extent to which prevalence estimates of adolescent health-related characteristics are biased due to different sampling methods, and whether this also biases within-subject analyses. Cross-sectional datasets collected in 2011 in Twente and IJsselland, two similar and adjacent regions in the Netherlands, were used. In total, 9360 youngsters in a mandatory sample (Twente) and 1952 youngsters in a voluntary sample (IJsselland) participated in the study. To test whether the samples differed on health-related variables, we conducted both univariate and multivariable logistic regression analyses controlling for any demographic difference between the samples. Additional multivariable logistic regressions were conducted to examine moderating effects of sampling method on associations between health-related variables. As expected, females, older individuals, as well as individuals with higher education levels, were over-represented in the voluntary sample, compared to the mandatory sample. Respondents in the voluntary sample tended to smoke less, consume less alcohol (ever, lifetime, and past four weeks), have better mental health, have better subjective health status, have more positive school experiences and have less sexual intercourse than respondents in the

  4. Theoretical study on new bias factor methods to effectively use critical experiments for improvement of prediction accuracy of neutronic characteristics

    International Nuclear Information System (INIS)

    Kugo, Teruhiko; Mori, Takamasa; Takeda, Toshikazu

    2007-01-01

    Extended bias factor methods are proposed with two new concepts, the LC method and the PE method, in order to effectively use critical experiments and to enhance the applicability of the bias factor method for the improvement of the prediction accuracy of neutronic characteristics of a target core. Both methods utilize a number of critical experimental results and produce a semifictitious experimental value with them. The LC and PE methods define the semifictitious experimental values by a linear combination of experimental values and the product of exponentiated experimental values, respectively, and the corresponding semifictitious calculation values by those of calculation values. A bias factor is defined by the ratio of the semifictitious experimental value to the semifictitious calculation value in both methods. We formulate how to determine weights for the LC method and exponents for the PE method in order to minimize the variance of the design prediction value obtained by multiplying the design calculation value by the bias factor. From a theoretical comparison of these new methods with the conventional method which utilizes a single experimental result and the generalized bias factor method which was previously proposed to utilize a number of experimental results, it is concluded that the PE method is the most useful method for improving the prediction accuracy. The main advantages of the PE method are summarized as follows. The prediction accuracy is necessarily improved compared with the design calculation value even when experimental results include large experimental errors. This is a special feature that the other methods do not have. The prediction accuracy is most effectively improved by utilizing all the experimental results. From these facts, it can be said that the PE method effectively utilizes all the experimental results and has a possibility to make a full-scale-mockup experiment unnecessary with the use of existing and future benchmark

  5. On Angular Sampling Methods for 3-D Spatial Channel Models

    DEFF Research Database (Denmark)

    Fan, Wei; Jämsä, Tommi; Nielsen, Jesper Ødum

    2015-01-01

    This paper discusses generating three dimensional (3D) spatial channel models with emphasis on the angular sampling methods. Three angular sampling methods, i.e. modified uniform power sampling, modified uniform angular sampling, and random pairing methods are proposed and investigated in detail....... The random pairing method, which uses only twenty sinusoids in the ray-based model for generating the channels, presents good results if the spatial channel cluster is with a small elevation angle spread. For spatial clusters with large elevation angle spreads, however, the random pairing method would fail...... and the other two methods should be considered....

  6. Parkinson's disease and occupation: differences in associations by case identification method suggest referral bias.

    Science.gov (United States)

    Teschke, Kay; Marion, Stephen A; Tsui, Joseph K C; Shen, Hui; Rugbjerg, Kathrine; Harris, M Anne

    2014-02-01

    We used a population-based sample of 403 Parkinson's disease cases and 405 controls to examine risks by occupation. Results were compared to a previous clinic-based analysis. With censoring of jobs held within 10 years of diagnosis, the following had significantly or strongly increased risks: social science, law and library jobs (OR = 1.8); farming and horticulture jobs (OR = 2.0); gas station jobs (OR = 2.6); and welders (OR = 3.0). The following had significantly decreased risks: management and administration jobs (OR = 0.70); and other health care jobs (OR = 0.44). These results were consistent with other findings for social science and farming occupations. Risks for teaching, medicine and health occupations were not elevated, unlike our previous clinic-based study. This underscores the value of population-based over clinic-based samples. Occupational studies may be particularly susceptible to referral bias because social networks may spread preferentially via jobs. © 2013 Wiley Periodicals, Inc.

  7. Some connections between importance sampling and enhanced sampling methods in molecular dynamics.

    Science.gov (United States)

    Lie, H C; Quer, J

    2017-11-21

    In molecular dynamics, enhanced sampling methods enable the collection of better statistics of rare events from a reference or target distribution. We show that a large class of these methods is based on the idea of importance sampling from mathematical statistics. We illustrate this connection by comparing the Hartmann-Schütte method for rare event simulation (J. Stat. Mech. Theor. Exp. 2012, P11004) and the Valsson-Parrinello method of variationally enhanced sampling [Phys. Rev. Lett. 113, 090601 (2014)]. We use this connection in order to discuss how recent results from the Monte Carlo methods literature can guide the development of enhanced sampling methods.

  8. An improved bias correction method of daily rainfall data using a sliding window technique for climate change impact assessment

    Science.gov (United States)

    Smitha, P. S.; Narasimhan, B.; Sudheer, K. P.; Annamalai, H.

    2018-01-01

    Regional climate models (RCMs) are used to downscale the coarse resolution General Circulation Model (GCM) outputs to a finer resolution for hydrological impact studies. However, RCM outputs often deviate from the observed climatological data, and therefore need bias correction before they are used for hydrological simulations. While there are a number of methods for bias correction, most of them use monthly statistics to derive correction factors, which may cause errors in the rainfall magnitude when applied on a daily scale. This study proposes a sliding window based daily correction factor derivations that help build reliable daily rainfall data from climate models. The procedure is applied to five existing bias correction methods, and is tested on six watersheds in different climatic zones of India for assessing the effectiveness of the corrected rainfall and the consequent hydrological simulations. The bias correction was performed on rainfall data downscaled using Conformal Cubic Atmospheric Model (CCAM) to 0.5° × 0.5° from two different CMIP5 models (CNRM-CM5.0, GFDL-CM3.0). The India Meteorological Department (IMD) gridded (0.25° × 0.25°) observed rainfall data was considered to test the effectiveness of the proposed bias correction method. The quantile-quantile (Q-Q) plots and Nash Sutcliffe efficiency (NSE) were employed for evaluation of different methods of bias correction. The analysis suggested that the proposed method effectively corrects the daily bias in rainfall as compared to using monthly factors. The methods such as local intensity scaling, modified power transformation and distribution mapping, which adjusted the wet day frequencies, performed superior compared to the other methods, which did not consider adjustment of wet day frequencies. The distribution mapping method with daily correction factors was able to replicate the daily rainfall pattern of observed data with NSE value above 0.81 over most parts of India. Hydrological

  9. Sampling Methods in Cardiovascular Nursing Research: An Overview.

    Science.gov (United States)

    Kandola, Damanpreet; Banner, Davina; O'Keefe-McCarthy, Sheila; Jassal, Debbie

    2014-01-01

    Cardiovascular nursing research covers a wide array of topics from health services to psychosocial patient experiences. The selection of specific participant samples is an important part of the research design and process. The sampling strategy employed is of utmost importance to ensure that a representative sample of participants is chosen. There are two main categories of sampling methods: probability and non-probability. Probability sampling is the random selection of elements from the population, where each element of the population has an equal and independent chance of being included in the sample. There are five main types of probability sampling including simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. Non-probability sampling methods are those in which elements are chosen through non-random methods for inclusion into the research study and include convenience sampling, purposive sampling, and snowball sampling. Each approach offers distinct advantages and disadvantages and must be considered critically. In this research column, we provide an introduction to these key sampling techniques and draw on examples from the cardiovascular research. Understanding the differences in sampling techniques may aid nurses in effective appraisal of research literature and provide a reference pointfor nurses who engage in cardiovascular research.

  10. 19 CFR 151.83 - Method of sampling.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 2 2010-04-01 2010-04-01 false Method of sampling. 151.83 Section 151.83 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) EXAMINATION, SAMPLING, AND TESTING OF MERCHANDISE Cotton § 151.83 Method of sampling. For...

  11. 7 CFR 29.110 - Method of sampling.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Method of sampling. 29.110 Section 29.110 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing... INSPECTION Regulations Inspectors, Samplers, and Weighers § 29.110 Method of sampling. In sampling tobacco...

  12. Understanding attributional biases, emotions and self-esteem in 'poor me' paranoia: findings from an early psychosis sample.

    Science.gov (United States)

    Fornells-Ambrojo, M; Garety, P A

    2009-06-01

    Trower and Chadwick's (1995) theory of two types of paranoia ('poor me' and 'bad me') provides a framework for understanding the seemingly contradictory evidence on persecutory delusions. Paranoia has been argued to defend against low self-esteem, but people with persecutory delusions report high levels of emotional distress and, in some instances, low self-worth. The current study investigates attributions and emotions in a sample of people with early psychosis who have persecutory delusions. 'Poor me' paranoia has been found to be more frequent than 'bad me' paranoia in the early stages of psychosis. Anger and a tendency to blame other people are hypothesized to characterize 'poor me' paranoia. The study had a cross-sectional design. Twenty individuals with early psychosis, 21 clinical controls with depression and 32 healthy volunteers completed a thorough assessment of emotions and attributions. The 'poor me' paranoia group showed higher levels of anger, anxiety and depression than the non-clinical control group. Self-esteem and guilt were however preserved. A tendency to blame others but not themselves was characteristic of the 'poor me' paranoia group whereas people in the clinical control group tended to self-blame for failures. Anger, but not self-esteem, was associated with an attributional bias characterized by blaming other people instead of oneself. In conclusion, anger, a previously overlooked emotion in the study of persecutory delusions, warrants further attention. The other-directed nature of this emotion highlights the potential role of interpersonal schemas in understanding paranoia.

  13. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

    Science.gov (United States)

    Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

    2016-06-15

    With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

  14. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

    Directory of Open Access Journals (Sweden)

    Haris Akram Bhatti

    2016-06-01

    Full Text Available With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA Climate Prediction Centre (CPC morphing technique (CMORPH satellite rainfall product (CMORPH in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW sizes and for sequential windows (SW’s of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE. To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r and standard deviation (SD. Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

  15. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

    Science.gov (United States)

    Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

    2016-01-01

    With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363

  16. Validation of EIA sampling methods - bacterial and biochemical analysis

    Digital Repository Service at National Institute of Oceanography (India)

    Sheelu, G.; LokaBharathi, P.A.; Nair, S.; Raghukumar, C.; Mohandass, C.

    to temporal factors. Paired T-test between pre- and post-disturbance samples suggested that the above methods of sampling and variables like TC, protein and TOC could be used for monitoring disturbance....

  17. New adaptive sampling method in particle image velocimetry

    International Nuclear Information System (INIS)

    Yu, Kaikai; Xu, Jinglei; Tang, Lan; Mo, Jianwei

    2015-01-01

    This study proposes a new adaptive method to enable the number of interrogation windows and their positions in a particle image velocimetry (PIV) image interrogation algorithm to become self-adapted according to the seeding density. The proposed method can relax the constraint of uniform sampling rate and uniform window size commonly adopted in the traditional PIV algorithm. In addition, the positions of the sampling points are redistributed on the basis of the spring force generated by the sampling points. The advantages include control of the number of interrogation windows according to the local seeding density and smoother distribution of sampling points. The reliability of the adaptive sampling method is illustrated by processing synthetic and experimental images. The synthetic example attests to the advantages of the sampling method. Compared with that of the uniform interrogation technique in the experimental application, the spatial resolution is locally enhanced when using the proposed sampling method. (technical design note)

  18. A flexible method for multi-level sample size determination

    International Nuclear Information System (INIS)

    Lu, Ming-Shih; Sanborn, J.B.; Teichmann, T.

    1997-01-01

    This paper gives a flexible method to determine sample sizes for both systematic and random error models (this pertains to sampling problems in nuclear safeguard questions). In addition, the method allows different attribute rejection limits. The new method could assist achieving a higher detection probability and enhance inspection effectiveness

  19. Bias Correction Methods Explain Much of the Variation Seen in Breast Cancer Risks of BRCA1/2 Mutation Carriers.

    Science.gov (United States)

    Vos, Janet R; Hsu, Li; Brohet, Richard M; Mourits, Marian J E; de Vries, Jakob; Malone, Kathleen E; Oosterwijk, Jan C; de Bock, Geertruida H

    2015-08-10

    Recommendations for treating patients who carry a BRCA1/2 gene are mainly based on cumulative lifetime risks (CLTRs) of breast cancer determined from retrospective cohorts. These risks vary widely (27% to 88%), and it is important to understand why. We analyzed the effects of methods of risk estimation and bias correction and of population factors on CLTRs in this retrospective clinical cohort of BRCA1/2 carriers. The following methods to estimate the breast cancer risk of BRCA1/2 carriers were identified from the literature: Kaplan-Meier, frailty, and modified segregation analyses with bias correction consisting of including or excluding index patients combined with including or excluding first-degree relatives (FDRs) or different conditional likelihoods. These were applied to clinical data of BRCA1/2 families derived from our family cancer clinic for whom a simulation was also performed to evaluate the methods. CLTRs and 95% CIs were estimated and compared with the reference CLTRs. CLTRs ranged from 35% to 83% for BRCA1 and 41% to 86% for BRCA2 carriers at age 70 years width of 95% CIs: 10% to 35% and 13% to 46%, respectively). Relative bias varied from -38% to +16%. Bias correction with inclusion of index patients and untested FDRs gave the smallest bias: +2% (SD, 2%) in BRCA1 and +0.9% (SD, 3.6%) in BRCA2. Much of the variation in breast cancer CLTRs in retrospective clinical BRCA1/2 cohorts is due to the bias-correction method, whereas a smaller part is due to population differences. Kaplan-Meier analyses with bias correction that includes index patients and a proportion of untested FDRs provide suitable CLTRs for carriers counseled in the clinic. © 2015 by American Society of Clinical Oncology.

  20. A Realization of Bias Correction Method in the GMAO Coupled System

    Science.gov (United States)

    Chang, Yehui; Koster, Randal; Wang, Hailan; Schubert, Siegfried; Suarez, Max

    2018-01-01

    Over the past several decades, a tremendous effort has been made to improve model performance in the simulation of the climate system. The cold or warm sea surface temperature (SST) bias in the tropics is still a problem common to most coupled ocean atmosphere general circulation models (CGCMs). The precipitation biases in CGCMs are also accompanied by SST and surface wind biases. The deficiencies and biases over the equatorial oceans through their influence on the Walker circulation likely contribute the precipitation biases over land surfaces. In this study, we introduce an approach in the CGCM modeling to correct model biases. This approach utilizes the history of the model's short-term forecasting errors and their seasonal dependence to modify model's tendency term and to minimize its climate drift. The study shows that such an approach removes most of model climate biases. A number of other aspects of the model simulation (e.g. extratropical transient activities) are also improved considerably due to the imposed pre-processed initial 3-hour model drift corrections. Because many regional biases in the GEOS-5 CGCM are common amongst other current models, our approaches and findings are applicable to these other models as well.

  1. A comparison of four gravimetric fine particle sampling methods.

    Science.gov (United States)

    Yanosky, J D; MacIntosh, D L

    2001-06-01

    A study was conducted to compare four gravimetric methods of measuring fine particle (PM2.5) concentrations in air: the BGI, Inc. PQ200 Federal Reference Method PM2.5 (FRM) sampler; the Harvard-Marple Impactor (HI); the BGI, Inc. GK2.05 KTL Respirable/Thoracic Cyclone (KTL); and the AirMetrics MiniVol (MiniVol). Pairs of FRM, HI, and KTL samplers and one MiniVol sampler were collocated and 24-hr integrated PM2.5 samples were collected on 21 days from January 6 through April 9, 2000. The mean and standard deviation of PM2.5 levels from the FRM samplers were 13.6 and 6.8 microg/m3, respectively. Significant systematic bias was found between mean concentrations from the FRM and the MiniVol (1.14 microg/m3, p = 0.0007), the HI and the MiniVol (0.85 microg/m3, p = 0.0048), and the KTL and the MiniVol (1.23 microg/m3, p = 0.0078) according to paired t test analyses. Linear regression on all pairwise combinations of the sampler types was used to evaluate measurements made by the samplers. None of the regression intercepts was significantly different from 0, and only two of the regression slopes were significantly different from 1, that for the FRM and the MiniVol [beta1 = 0.91, 95% CI (0.83-0.99)] and that for the KTL and the MiniVol [beta1 = 0.88, 95% CI (0.78-0.98)]. Regression R2 terms were 0.96 or greater between all pairs of samplers, and regression root mean square error terms (RMSE) were 1.65 microg/m3 or less. These results suggest that the MiniVol will underestimate measurements made by the FRM, the HI, and the KTL by an amount proportional to PM2.5 concentration. Nonetheless, these results indicate that all of the sampler types are comparable if approximately 10% variation on the mean levels and on individual measurement levels is considered acceptable and the actual concentration is within the range of this study (5-35 microg/m3).

  2. Enhanced Sampling in Free Energy Calculations: Combining SGLD with the Bennett's Acceptance Ratio and Enveloping Distribution Sampling Methods.

    Science.gov (United States)

    König, Gerhard; Miller, Benjamin T; Boresch, Stefan; Wu, Xiongwu; Brooks, Bernard R

    2012-10-09

    One of the key requirements for the accurate calculation of free energy differences is proper sampling of conformational space. Especially in biological applications, molecular dynamics simulations are often confronted with rugged energy surfaces and high energy barriers, leading to insufficient sampling and, in turn, poor convergence of the free energy results. In this work, we address this problem by employing enhanced sampling methods. We explore the possibility of using self-guided Langevin dynamics (SGLD) to speed up the exploration process in free energy simulations. To obtain improved free energy differences from such simulations, it is necessary to account for the effects of the bias due to the guiding forces. We demonstrate how this can be accomplished for the Bennett's acceptance ratio (BAR) and the enveloping distribution sampling (EDS) methods. While BAR is considered among the most efficient methods available for free energy calculations, the EDS method developed by Christ and van Gunsteren is a promising development that reduces the computational costs of free energy calculations by simulating a single reference state. To evaluate the accuracy of both approaches in connection with enhanced sampling, EDS was implemented in CHARMM. For testing, we employ benchmark systems with analytical reference results and the mutation of alanine to serine. We find that SGLD with reweighting can provide accurate results for BAR and EDS where conventional molecular dynamics simulations fail. In addition, we compare the performance of EDS with other free energy methods. We briefly discuss the implications of our results and provide practical guidelines for conducting free energy simulations with SGLD.

  3. Systems and methods for self-synchronized digital sampling

    Science.gov (United States)

    Samson, Jr., John R. (Inventor)

    2008-01-01

    Systems and methods for self-synchronized data sampling are provided. In one embodiment, a system for capturing synchronous data samples is provided. The system includes an analog to digital converter adapted to capture signals from one or more sensors and convert the signals into a stream of digital data samples at a sampling frequency determined by a sampling control signal; and a synchronizer coupled to the analog to digital converter and adapted to receive a rotational frequency signal from a rotating machine, wherein the synchronizer is further adapted to generate the sampling control signal, and wherein the sampling control signal is based on the rotational frequency signal.

  4. Bats from Fazenda Intervales, Southeastern Brazil: species account and comparison between different sampling methods

    Directory of Open Access Journals (Sweden)

    Christine V. Portfors

    2000-06-01

    Full Text Available Assessing the composition of an area's bat fauna is typically accomplished by using captures or by monitoring echolocation calls with bat detectors. The two methods may not provide the same data regarding species composition. Mist nets and harp traps may be biased towards sampling low flying species, and bat detectors biased towards detecting high intensity echolocators. A comparison of the bat fauna of Fazenda Intervales, southeastern Brazil, as revealed by mist nets and harp trap captures, checking roosts and by monitoring echolocation calls of flying bats illustrates this point. A total of 17 species of bats was sampled. Fourteen bat species were captured and the echolocation calls of 12 species were recorded, three of them not revealed by mist nets or harp traps. The different sampling methods provided different pictures of the bat fauna. Phyllostomid bats dominated the catches in mist nets, but in the field their echolocation calls were never detected. No single sampling approach provided a complete assessment of the bat fauna in the study area. In general, bats producing low intensity echolocation calls, such as phyllostomids, are more easily assessed by netting, and bats producing high intensity echolocation calls are better surveyed by bat detectors. The results demonstrate that a combined and varied approach to sampling is required for a complete assessment of the bat fauna of an area.

  5. DOE methods for evaluating environmental and waste management samples

    International Nuclear Information System (INIS)

    Goheen, S.C.; McCulloch, M.; Thomas, B.L.; Riley, R.G.; Sklarew, D.S.; Mong, G.M.; Fadeff, S.K.

    1993-03-01

    DOE Methods for Evaluating Environmental and Waste Management Samples (DOE Methods) provides applicable methods in use by. the US Department of Energy (DOE) laboratories for sampling and analyzing constituents of waste and environmental samples. The development of DOE Methods is supported by the Laboratory Management Division (LMD) of the DOE. This document contains chapters and methods that are proposed for use in evaluating components of DOE environmental and waste management samples. DOE Methods is a resource intended to support sampling and analytical activities that will aid in defining the type and breadth of contamination and thus determine the extent of environmental restoration or waste management actions needed, as defined by the DOE, the US Environmental Protection Agency (EPA), or others

  6. DOE methods for evaluating environmental and waste management samples.

    Energy Technology Data Exchange (ETDEWEB)

    Goheen, S C; McCulloch, M; Thomas, B L; Riley, R G; Sklarew, D S; Mong, G M; Fadeff, S K [eds.; Pacific Northwest Lab., Richland, WA (United States)

    1994-04-01

    DOE Methods for Evaluating Environmental and Waste Management Samples (DOE Methods) provides applicable methods in use by. the US Department of Energy (DOE) laboratories for sampling and analyzing constituents of waste and environmental samples. The development of DOE Methods is supported by the Laboratory Management Division (LMD) of the DOE. This document contains chapters and methods that are proposed for use in evaluating components of DOE environmental and waste management samples. DOE Methods is a resource intended to support sampling and analytical activities that will aid in defining the type and breadth of contamination and thus determine the extent of environmental restoration or waste management actions needed, as defined by the DOE, the US Environmental Protection Agency (EPA), or others.

  7. Bias in calculated keff from subcritical measurements by the 252Cf-source-driven noise analysis method

    International Nuclear Information System (INIS)

    Mihalczo, J.T.; Valentine, T.E.

    1995-01-01

    The development of MCNP-DSP, which allows direct calculation of the measured time and frequency analysis parameters from subcritical measurements using the 252 Cf-source-driven noise analysis method, permits the validation of calculational methods for criticality safety with in-plant subcritical measurements. In addition, a method of obtaining the bias in the calculations, which is essential to the criticality safety specialist, is illustrated using the results of measurements with 17.771-cm-diam, enriched (93.15), unreflected, and unmoderated uranium metal cylinders. For these uranium metal cylinders the bias obtained using MCNP-DSP and ENDF/B-V cross-section data increased with subcriticality. For a critical experiment [height (h) = 12.629 cm], it was -0.0061 ± 0.0003. For a 10.16-cm-high cylinder (k ∼ 0.93), it was 0.0060 ± 0.0016, and for a subcritical cylinder (h = 8.13 cm, k ∼ 0.85), the bias was -0.0137 ± 0.0037, more than a factor of 2 larger in magnitude. This method allows the nuclear criticality safety specialist to establish the bias in calculational methods for criticality safety from in-plant subcritical measurements by the 252 Cf-source-driven noise analysis method

  8. Sampling methods for amphibians in streams in the Pacific Northwest.

    Science.gov (United States)

    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...

  9. A random spatial sampling method in a rural developing nation

    Science.gov (United States)

    Michelle C. Kondo; Kent D.W. Bream; Frances K. Barg; Charles C. Branas

    2014-01-01

    Nonrandom sampling of populations in developing nations has limitations and can inaccurately estimate health phenomena, especially among hard-to-reach populations such as rural residents. However, random sampling of rural populations in developing nations can be challenged by incomplete enumeration of the base population. We describe a stratified random sampling method...

  10. Multielement methods of atomic fluorescence analysis of enviromental samples

    International Nuclear Information System (INIS)

    Rigin, V.I.

    1985-01-01

    A multielement method of atomic fluorescence analysis of environmental samples based on sample decomposition by autoclave fluorination and gas-phase atomization of volatile compounds in inductive araon plasma using a nondispersive polychromator is suggested. Detection limits of some elements (Be, Sr, Cd, V, Mo, Te, Ru etc.) for different sample forms introduced in to an analyzer are given

  11. Sampling bee communities using pan traps: alternative methods increase sample size

    Science.gov (United States)

    Monitoring of the status of bee populations and inventories of bee faunas require systematic sampling. Efficiency and ease of implementation has encouraged the use of pan traps to sample bees. Efforts to find an optimal standardized sampling method for pan traps have focused on pan trap color. Th...

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

    Science.gov (United States)

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

    2015-01-01

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

  13. THE USE OF RANKING SAMPLING METHOD WITHIN MARKETING RESEARCH

    Directory of Open Access Journals (Sweden)

    CODRUŢA DURA

    2011-01-01

    Full Text Available Marketing and statistical literature available to practitioners provides a wide range of sampling methods that can be implemented in the context of marketing research. Ranking sampling method is based on taking apart the general population into several strata, namely into several subdivisions which are relatively homogenous regarding a certain characteristic. In fact, the sample will be composed by selecting, from each stratum, a certain number of components (which can be proportional or non-proportional to the size of the stratum until the pre-established volume of the sample is reached. Using ranking sampling within marketing research requires the determination of some relevant statistical indicators - average, dispersion, sampling error etc. To that end, the paper contains a case study which illustrates the actual approach used in order to apply the ranking sample method within a marketing research made by a company which provides Internet connection services, on a particular category of customers – small and medium enterprises.

  14. An efficient method for sampling the essential subspace of proteins

    NARCIS (Netherlands)

    Amadei, A; Linssen, A.B M; de Groot, B.L.; van Aalten, D.M.F.; Berendsen, H.J.C.

    A method is presented for a more efficient sampling of the configurational space of proteins as compared to conventional sampling techniques such as molecular dynamics. The method is based on the large conformational changes in proteins revealed by the ''essential dynamics'' analysis. A form of

  15. Neonatal blood gas sampling methods | Goenka | South African ...

    African Journals Online (AJOL)

    There is little published guidance that systematically evaluates the different methods of neonatal blood gas sampling, where each method has its individual benefits and risks. This review critically surveys the available evidence to generate a comparison between arterial and capillary blood gas sampling, focusing on their ...

  16. A Mixed Methods Sampling Methodology for a Multisite Case Study

    Science.gov (United States)

    Sharp, Julia L.; Mobley, Catherine; Hammond, Cathy; Withington, Cairen; Drew, Sam; Stringfield, Sam; Stipanovic, Natalie

    2012-01-01

    The flexibility of mixed methods research strategies makes such approaches especially suitable for multisite case studies. Yet the utilization of mixed methods to select sites for these studies is rarely reported. The authors describe their pragmatic mixed methods approach to select a sample for their multisite mixed methods case study of a…

  17. Some Insights into Analytical Bias Involved in the Application of Grab Sampling for Volatile Organic Compounds: A Case Study against Used Tedlar Bags

    Science.gov (United States)

    Ghosh, Samik; Kim, Ki-Hyun; Sohn, Jong Ryeul

    2011-01-01

    In this study, we have examined the patterns of VOCs released from used Tedlar bags that were once used for the collection under strong source activities. In this way, we attempted to account for the possible bias associated with the repetitive use of Tedlar bags. To this end, we selected the bags that were never heated. All of these target bags were used in ambient temperature (typically at or below 30°C). These bags were also dealt carefully to avoid any mechanical abrasion. This study will provide the essential information regarding the interaction between VOCs and Tedlar bag materials as a potential source of bias in bag sampling approaches. PMID:22235175

  18. Present status of NMCC and sample preparation method for bio-samples

    International Nuclear Information System (INIS)

    Futatsugawa, S.; Hatakeyama, S.; Saitou, S.; Sera, K.

    1993-01-01

    In NMCC(Nishina Memorial Cyclotron Center) we are doing researches on PET of nuclear medicine (Positron Emission Computed Tomography) and PIXE analysis (Particle Induced X-ray Emission) using a small cyclotron of compactly designed. The NMCC facilities have been opened to researchers of other institutions since April 1993. The present status of NMCC is described. Bio-samples (medical samples, plants, animals and environmental samples) have mainly been analyzed by PIXE in NMCC. Small amounts of bio-samples for PIXE are decomposed quickly and easily in a sealed PTFE (polytetrafluoroethylene) vessel with a microwave oven. This sample preparation method of bio-samples also is described. (author)

  19. Implicit and explicit anti-fat bias among a large sample of medical doctors by BMI, race/ethnicity and gender.

    Directory of Open Access Journals (Sweden)

    Janice A Sabin

    Full Text Available Overweight patients report weight discrimination in health care settings and subsequent avoidance of routine preventive health care. The purpose of this study was to examine implicit and explicit attitudes about weight among a large group of medical doctors (MDs to determine the pervasiveness of negative attitudes about weight among MDs. Test-takers voluntarily accessed a public Web site, known as Project Implicit®, and opted to complete the Weight Implicit Association Test (IAT (N = 359,261. A sub-sample identified their highest level of education as MD (N = 2,284. Among the MDs, 55% were female, 78% reported their race as white, and 62% had a normal range BMI. This large sample of test-takers showed strong implicit anti-fat bias (Cohen's d = 1.0. MDs, on average, also showed strong implicit anti-fat bias (Cohen's d = 0.93. All test-takers and the MD sub-sample reported a strong preference for thin people rather than fat people or a strong explicit anti-fat bias. We conclude that strong implicit and explicit anti-fat bias is as pervasive among MDs as it is among the general public. An important area for future research is to investigate the association between providers' implicit and explicit attitudes about weight, patient reports of weight discrimination in health care, and quality of care delivered to overweight patients.

  20. Evaluation of common methods for sampling invertebrate pollinator assemblages: net sampling out-perform pan traps.

    Directory of Open Access Journals (Sweden)

    Tony J Popic

    Full Text Available Methods for sampling ecological assemblages strive to be efficient, repeatable, and representative. Unknowingly, common methods may be limited in terms of revealing species function and so of less value for comparative studies. The global decline in pollination services has stimulated surveys of flower-visiting invertebrates, using pan traps and net sampling. We explore the relative merits of these two methods in terms of species discovery, quantifying abundance, function, and composition, and responses of species to changing floral resources. Using a spatially-nested design we sampled across a 5000 km(2 area of arid grasslands, including 432 hours of net sampling and 1296 pan trap-days, between June 2010 and July 2011. Net sampling yielded 22% more species and 30% higher abundance than pan traps, and better reflected the spatio-temporal variation of floral resources. Species composition differed significantly between methods; from 436 total species, 25% were sampled by both methods, 50% only by nets, and the remaining 25% only by pans. Apart from being less comprehensive, if pan traps do not sample flower-visitors, the link to pollination is questionable. By contrast, net sampling functionally linked species to pollination through behavioural observations of flower-visitation interaction frequency. Netted specimens are also necessary for evidence of pollen transport. Benefits of net-based sampling outweighed minor differences in overall sampling effort. As pan traps and net sampling methods are not equivalent for sampling invertebrate-flower interactions, we recommend net sampling of invertebrate pollinator assemblages, especially if datasets are intended to document declines in pollination and guide measures to retain this important ecosystem service.

  1. Evaluation of common methods for sampling invertebrate pollinator assemblages: net sampling out-perform pan traps.

    Science.gov (United States)

    Popic, Tony J; Davila, Yvonne C; Wardle, Glenda M

    2013-01-01

    Methods for sampling ecological assemblages strive to be efficient, repeatable, and representative. Unknowingly, common methods may be limited in terms of revealing species function and so of less value for comparative studies. The global decline in pollination services has stimulated surveys of flower-visiting invertebrates, using pan traps and net sampling. We explore the relative merits of these two methods in terms of species discovery, quantifying abundance, function, and composition, and responses of species to changing floral resources. Using a spatially-nested design we sampled across a 5000 km(2) area of arid grasslands, including 432 hours of net sampling and 1296 pan trap-days, between June 2010 and July 2011. Net sampling yielded 22% more species and 30% higher abundance than pan traps, and better reflected the spatio-temporal variation of floral resources. Species composition differed significantly between methods; from 436 total species, 25% were sampled by both methods, 50% only by nets, and the remaining 25% only by pans. Apart from being less comprehensive, if pan traps do not sample flower-visitors, the link to pollination is questionable. By contrast, net sampling functionally linked species to pollination through behavioural observations of flower-visitation interaction frequency. Netted specimens are also necessary for evidence of pollen transport. Benefits of net-based sampling outweighed minor differences in overall sampling effort. As pan traps and net sampling methods are not equivalent for sampling invertebrate-flower interactions, we recommend net sampling of invertebrate pollinator assemblages, especially if datasets are intended to document declines in pollination and guide measures to retain this important ecosystem service.

  2. Multi-frequency direct sampling method in inverse scattering problem

    Science.gov (United States)

    Kang, Sangwoo; Lambert, Marc; Park, Won-Kwang

    2017-10-01

    We consider the direct sampling method (DSM) for the two-dimensional inverse scattering problem. Although DSM is fast, stable, and effective, some phenomena remain unexplained by the existing results. We show that the imaging function of the direct sampling method can be expressed by a Bessel function of order zero. We also clarify the previously unexplained imaging phenomena and suggest multi-frequency DSM to overcome traditional DSM. Our method is evaluated in simulation studies using both single and multiple frequencies.

  3. Substrate bias effect on crystallinity of polycrystalline silicon thin films prepared by pulsed ion-beam evaporation method

    Energy Technology Data Exchange (ETDEWEB)

    Ali, Fazlat; Gunji, Michiharu; Yang, Sung-Chae; Suzuki, Tsuneo; Suematsu, Hisayuki; Jiang, Weihua; Yatsui, Kiyoshi [Nagaoka Univ. of Technology, Extreme Energy-Density Research Inst., Nagaoka, Niigata (Japan)

    2002-06-01

    The deposition of polycrystalline silicon thin films has been tried by a pulsed ion-beam evaporation method, where high crystallinity and deposition rate have been achieved without heating the substrate. The crystallinity and the deposition rate were improved by applying bias voltage to the substrate, where instantaneous substrate heating might have occurred by ion-bombardment. (author)

  4. Substrate bias effect on crystallinity of polycrystalline silicon thin films prepared by pulsed ion-beam evaporation method

    International Nuclear Information System (INIS)

    Ali, Fazlat; Gunji, Michiharu; Yang, Sung-Chae; Suzuki, Tsuneo; Suematsu, Hisayuki; Jiang, Weihua; Yatsui, Kiyoshi

    2002-01-01

    The deposition of polycrystalline silicon thin films has been tried by a pulsed ion-beam evaporation method, where high crystallinity and deposition rate have been achieved without heating the substrate. The crystallinity and the deposition rate were improved by applying bias voltage to the substrate, where instantaneous substrate heating might have occurred by ion-bombardment. (author)

  5. Phylogenetic representativeness: a new method for evaluating taxon sampling in evolutionary studies

    Directory of Open Access Journals (Sweden)

    Passamonti Marco

    2010-04-01

    Full Text Available Abstract Background Taxon sampling is a major concern in phylogenetic studies. Incomplete, biased, or improper taxon sampling can lead to misleading results in reconstructing evolutionary relationships. Several theoretical methods are available to optimize taxon choice in phylogenetic analyses. However, most involve some knowledge about the genetic relationships of the group of interest (i.e., the ingroup, or even a well-established phylogeny itself; these data are not always available in general phylogenetic applications. Results We propose a new method to assess taxon sampling developing Clarke and Warwick statistics. This method aims to measure the "phylogenetic representativeness" of a given sample or set of samples and it is based entirely on the pre-existing available taxonomy of the ingroup, which is commonly known to investigators. Moreover, our method also accounts for instability and discordance in taxonomies. A Python-based script suite, called PhyRe, has been developed to implement all analyses we describe in this paper. Conclusions We show that this method is sensitive and allows direct discrimination between representative and unrepresentative samples. It is also informative about the addition of taxa to improve taxonomic coverage of the ingroup. Provided that the investigators' expertise is mandatory in this field, phylogenetic representativeness makes up an objective touchstone in planning phylogenetic studies.

  6. Treatment biases in traumatic neurosurgical care: a retrospective study of the Nationwide Inpatient Sample from 1998 to 2009.

    Science.gov (United States)

    McCutcheon, Brandon A; Chang, David C; Marcus, Logan; Gonda, David D; Noorbakhsh, Abraham; Chen, Clark C; Talamini, Mark A; Carter, Bob S

    2015-08-01

    This study was designed to assess the relationship between insurance status and likelihood of receiving a neurosurgical procedure following admission for either extraaxial intracranial hemorrhage or spinal vertebral fracture. A retrospective analysis of the Nationwide Inpatient Sample (NIS; 1998-2009) was performed. Cases of traumatic extraaxial intracranial hematoma and spinal vertebral fracture were identified using International Classification of Diseases, Ninth Revision (ICD-9) diagnosis codes. Within this cohort, those patients receiving a craniotomy or spinal fusion and/or decompression in the context of an admission for traumatic brain or spine injury, respectively, were identified using the appropriate ICD-9 procedure codes. A total of 190,412 patients with extraaxial intracranial hematoma were identified between 1998 and 2009. Within this cohort, 37,434 patients (19.7%) received a craniotomy. A total of 477,110 patients with spinal vertebral fracture were identified. Of these, 37,302 (7.8%) received a spinal decompression and/or fusion. On multivariate analysis controlling for patient demographics, severity of injuries, comorbidities, hospital volume, and hospital characteristics, uninsured patients had a reduced likelihood of receiving a craniotomy (odds ratio [OR] 0.76, 95% confidence interval [CI] 0.71-0.82) and spinal fusion (OR 0.67, 95% CI 0.64-0.71) relative to insured patients. This statistically significant trend persisted when uninsured and insured patients were matched on the basis of mortality propensity score. Uninsured patients demonstrated an elevated risk-adjusted mortality rate relative to insured patients in cases of extraaxial intracranial hematoma. Among patients with spinal injury, mortality rates were similar between patients with and without insurance. In this study, uninsured patients were consistently less likely to receive a craniotomy or spinal fusion for traumatic intracranial extraaxial hemorrhage and spinal vertebral fracture

  7. Interval sampling methods and measurement error: a computer simulation.

    Science.gov (United States)

    Wirth, Oliver; Slaven, James; Taylor, Matthew A

    2014-01-01

    A simulation study was conducted to provide a more thorough account of measurement error associated with interval sampling methods. A computer program simulated the application of momentary time sampling, partial-interval recording, and whole-interval recording methods on target events randomly distributed across an observation period. The simulation yielded measures of error for multiple combinations of observation period, interval duration, event duration, and cumulative event duration. The simulations were conducted up to 100 times to yield measures of error variability. Although the present simulation confirmed some previously reported characteristics of interval sampling methods, it also revealed many new findings that pertain to each method's inherent strengths and weaknesses. The analysis and resulting error tables can help guide the selection of the most appropriate sampling method for observation-based behavioral assessments. © Society for the Experimental Analysis of Behavior.

  8. Direct sampling methods for inverse elastic scattering problems

    Science.gov (United States)

    Ji, Xia; Liu, Xiaodong; Xi, Yingxia

    2018-03-01

    We consider the inverse elastic scattering of incident plane compressional and shear waves from the knowledge of the far field patterns. Specifically, three direct sampling methods for location and shape reconstruction are proposed using the different component of the far field patterns. Only inner products are involved in the computation, thus the novel sampling methods are very simple and fast to be implemented. With the help of the factorization of the far field operator, we give a lower bound of the proposed indicator functionals for sampling points inside the scatterers. While for the sampling points outside the scatterers, we show that the indicator functionals decay like the Bessel functions as the sampling point goes away from the boundary of the scatterers. We also show that the proposed indicator functionals continuously dependent on the far field patterns, which further implies that the novel sampling methods are extremely stable with respect to data error. For the case when the observation directions are restricted into the limited aperture, we firstly introduce some data retrieval techniques to obtain those data that can not be measured directly and then use the proposed direct sampling methods for location and shape reconstructions. Finally, some numerical simulations in two dimensions are conducted with noisy data, and the results further verify the effectiveness and robustness of the proposed sampling methods, even for multiple multiscale cases and limited-aperture problems.

  9. Sampling and analysis methods for geothermal fluids and gases

    Energy Technology Data Exchange (ETDEWEB)

    Watson, J.C.

    1978-07-01

    The sampling procedures for geothermal fluids and gases include: sampling hot springs, fumaroles, etc.; sampling condensed brine and entrained gases; sampling steam-lines; low pressure separator systems; high pressure separator systems; two-phase sampling; downhole samplers; and miscellaneous methods. The recommended analytical methods compiled here cover physical properties, dissolved solids, and dissolved and entrained gases. The sequences of methods listed for each parameter are: wet chemical, gravimetric, colorimetric, electrode, atomic absorption, flame emission, x-ray fluorescence, inductively coupled plasma-atomic emission spectroscopy, ion exchange chromatography, spark source mass spectrometry, neutron activation analysis, and emission spectrometry. Material on correction of brine component concentrations for steam loss during flashing is presented. (MHR)

  10. Item bias detection in the Hospital Anxiety and Depression Scale using structural equation modeling: comparison with other item bias detection methods

    NARCIS (Netherlands)

    Verdam, M.G.E.; Oort, F.J.; Sprangers, M.A.G.

    Purpose Comparison of patient-reported outcomes may be invalidated by the occurrence of item bias, also known as differential item functioning. We show two ways of using structural equation modeling (SEM) to detect item bias: (1) multigroup SEM, which enables the detection of both uniform and

  11. Field Sample Preparation Method Development for Isotope Ratio Mass Spectrometry

    International Nuclear Information System (INIS)

    Leibman, C.; Weisbrod, K.; Yoshida, T.

    2015-01-01

    Non-proliferation and International Security (NA-241) established a working group of researchers from Los Alamos National Laboratory (LANL), Pacific Northwest National Laboratory (PNNL) and Savannah River National Laboratory (SRNL) to evaluate the utilization of in-field mass spectrometry for safeguards applications. The survey of commercial off-the-shelf (COTS) mass spectrometers (MS) revealed no instrumentation existed capable of meeting all the potential safeguards requirements for performance, portability, and ease of use. Additionally, fieldable instruments are unlikely to meet the International Target Values (ITVs) for accuracy and precision for isotope ratio measurements achieved with laboratory methods. The major gaps identified for in-field actinide isotope ratio analysis were in the areas of: 1. sample preparation and/or sample introduction, 2. size reduction of mass analyzers and ionization sources, 3. system automation, and 4. decreased system cost. Development work in 2 through 4, numerated above continues, in the private and public sector. LANL is focusing on developing sample preparation/sample introduction methods for use with the different sample types anticipated for safeguard applications. Addressing sample handling and sample preparation methods for MS analysis will enable use of new MS instrumentation as it becomes commercially available. As one example, we have developed a rapid, sample preparation method for dissolution of uranium and plutonium oxides using ammonium bifluoride (ABF). ABF is a significantly safer and faster alternative to digestion with boiling combinations of highly concentrated mineral acids. Actinides digested with ABF yield fluorides, which can then be analyzed directly or chemically converted and separated using established column chromatography techniques as needed prior to isotope analysis. The reagent volumes and the sample processing steps associated with ABF sample digestion lend themselves to automation and field

  12. A method to correct sampling ghosts in historic near-infrared Fourier transform spectrometer (FTS) measurements

    Science.gov (United States)

    Dohe, S.; Sherlock, V.; Hase, F.; Gisi, M.; Robinson, J.; Sepúlveda, E.; Schneider, M.; Blumenstock, T.

    2013-08-01

    The Total Carbon Column Observing Network (TCCON) has been established to provide ground-based remote sensing measurements of the column-averaged dry air mole fractions (DMF) of key greenhouse gases. To ensure network-wide consistency, biases between Fourier transform spectrometers at different sites have to be well controlled. Errors in interferogram sampling can introduce significant biases in retrievals. In this study we investigate a two-step scheme to correct these errors. In the first step the laser sampling error (LSE) is estimated by determining the sampling shift which minimises the magnitude of the signal intensity in selected, fully absorbed regions of the solar spectrum. The LSE is estimated for every day with measurements which meet certain selection criteria to derive the site-specific time series of the LSEs. In the second step, this sequence of LSEs is used to resample all the interferograms acquired at the site, and hence correct the sampling errors. Measurements acquired at the Izaña and Lauder TCCON sites are used to demonstrate the method. At both sites the sampling error histories show changes in LSE due to instrument interventions (e.g. realignment). Estimated LSEs are in good agreement with sampling errors inferred from the ratio of primary and ghost spectral signatures in optically bandpass-limited tungsten lamp spectra acquired at Lauder. The original time series of Xair and XCO2 (XY: column-averaged DMF of the target gas Y) at both sites show discrepancies of 0.2-0.5% due to changes in the LSE associated with instrument interventions or changes in the measurement sample rate. After resampling, discrepancies are reduced to 0.1% or less at Lauder and 0.2% at Izaña. In the latter case, coincident changes in interferometer alignment may also have contributed to the residual difference. In the future the proposed method will be used to correct historical spectra at all TCCON sites.

  13. A method to correct sampling ghosts in historic near-infrared Fourier transform spectrometer (FTS measurements

    Directory of Open Access Journals (Sweden)

    S. Dohe

    2013-08-01

    Full Text Available The Total Carbon Column Observing Network (TCCON has been established to provide ground-based remote sensing measurements of the column-averaged dry air mole fractions (DMF of key greenhouse gases. To ensure network-wide consistency, biases between Fourier transform spectrometers at different sites have to be well controlled. Errors in interferogram sampling can introduce significant biases in retrievals. In this study we investigate a two-step scheme to correct these errors. In the first step the laser sampling error (LSE is estimated by determining the sampling shift which minimises the magnitude of the signal intensity in selected, fully absorbed regions of the solar spectrum. The LSE is estimated for every day with measurements which meet certain selection criteria to derive the site-specific time series of the LSEs. In the second step, this sequence of LSEs is used to resample all the interferograms acquired at the site, and hence correct the sampling errors. Measurements acquired at the Izaña and Lauder TCCON sites are used to demonstrate the method. At both sites the sampling error histories show changes in LSE due to instrument interventions (e.g. realignment. Estimated LSEs are in good agreement with sampling errors inferred from the ratio of primary and ghost spectral signatures in optically bandpass-limited tungsten lamp spectra acquired at Lauder. The original time series of Xair and XCO2 (XY: column-averaged DMF of the target gas Y at both sites show discrepancies of 0.2–0.5% due to changes in the LSE associated with instrument interventions or changes in the measurement sample rate. After resampling, discrepancies are reduced to 0.1% or less at Lauder and 0.2% at Izaña. In the latter case, coincident changes in interferometer alignment may also have contributed to the residual difference. In the future the proposed method will be used to correct historical spectra at all TCCON sites.

  14. Abstract analysis method facilitates filtering low-methodological quality and high-bias risk systematic reviews on psoriasis interventions.

    Science.gov (United States)

    Gómez-García, Francisco; Ruano, Juan; Aguilar-Luque, Macarena; Alcalde-Mellado, Patricia; Gay-Mimbrera, Jesús; Hernández-Romero, José Luis; Sanz-Cabanillas, Juan Luis; Maestre-López, Beatriz; González-Padilla, Marcelino; Carmona-Fernández, Pedro J; García-Nieto, Antonio Vélez; Isla-Tejera, Beatriz

    2017-12-29

    Article summaries' information and structure may influence researchers/clinicians' decisions to conduct deeper full-text analyses. Specifically, abstracts of systematic reviews (SRs) and meta-analyses (MA) should provide structured summaries for quick assessment. This study explored a method for determining the methodological quality and bias risk of full-text reviews using abstract information alone. Systematic literature searches for SRs and/or MA about psoriasis were undertaken on MEDLINE, EMBASE, and Cochrane database. For each review, quality, abstract-reporting completeness, full-text methodological quality, and bias risk were evaluated using Preferred Reporting Items for Systematic Reviews and Meta-analyses for abstracts (PRISMA-A), Assessing the Methodological Quality of Systematic Reviews (AMSTAR), and ROBIS tools, respectively. Article-, author-, and journal-derived metadata were systematically extracted from eligible studies using a piloted template, and explanatory variables concerning abstract-reporting quality were assessed using univariate and multivariate-regression models. Two classification models concerning SRs' methodological quality and bias risk were developed based on per-item and total PRISMA-A scores and decision-tree algorithms. This work was supported, in part, by project ICI1400136 (JR). No funding was received from any pharmaceutical company. This study analysed 139 SRs on psoriasis interventions. On average, they featured 56.7% of PRISMA-A items. The mean total PRISMA-A score was significantly higher for high-methodological-quality SRs than for moderate- and low-methodological-quality reviews. SRs with low-bias risk showed higher total PRISMA-A values than reviews with high-bias risk. In the final model, only 'authors per review > 6' (OR: 1.098; 95%CI: 1.012-1.194), 'academic source of funding' (OR: 3.630; 95%CI: 1.788-7.542), and 'PRISMA-endorsed journal' (OR: 4.370; 95%CI: 1.785-10.98) predicted PRISMA-A variability. Reviews with a

  15. A direct sampling method to an inverse medium scattering problem

    KAUST Repository

    Ito, Kazufumi; Jin, Bangti; Zou, Jun

    2012-01-01

    In this work we present a novel sampling method for time harmonic inverse medium scattering problems. It provides a simple tool to directly estimate the shape of the unknown scatterers (inhomogeneous media), and it is applicable even when

  16. A direct sampling method for inverse electromagnetic medium scattering

    KAUST Repository

    Ito, Kazufumi; Jin, Bangti; Zou, Jun

    2013-01-01

    In this paper, we study the inverse electromagnetic medium scattering problem of estimating the support and shape of medium scatterers from scattered electric/magnetic near-field data. We shall develop a novel direct sampling method based

  17. Evaluation of the point-centred-quarter method of sampling ...

    African Journals Online (AJOL)

    -quarter method.The parameter which was most efficiently sampled was species composition relativedensity) with 90% replicate similarity being achieved with 100 point-centred-quarters. However, this technique cannot be recommended, even ...

  18. Field evaluation of personal sampling methods for multiple bioaerosols.

    Science.gov (United States)

    Wang, Chi-Hsun; Chen, Bean T; Han, Bor-Cheng; Liu, Andrew Chi-Yeu; Hung, Po-Chen; Chen, Chih-Yong; Chao, Hsing Jasmine

    2015-01-01

    Ambient bioaerosols are ubiquitous in the daily environment and can affect health in various ways. However, few studies have been conducted to comprehensively evaluate personal bioaerosol exposure in occupational and indoor environments because of the complex composition of bioaerosols and the lack of standardized sampling/analysis methods. We conducted a study to determine the most efficient collection/analysis method for the personal exposure assessment of multiple bioaerosols. The sampling efficiencies of three filters and four samplers were compared. According to our results, polycarbonate (PC) filters had the highest relative efficiency, particularly for bacteria. Side-by-side sampling was conducted to evaluate the three filter samplers (with PC filters) and the NIOSH Personal Bioaerosol Cyclone Sampler. According to the results, the Button Aerosol Sampler and the IOM Inhalable Dust Sampler had the highest relative efficiencies for fungi and bacteria, followed by the NIOSH sampler. Personal sampling was performed in a pig farm to assess occupational bioaerosol exposure and to evaluate the sampling/analysis methods. The Button and IOM samplers yielded a similar performance for personal bioaerosol sampling at the pig farm. However, the Button sampler is more likely to be clogged at high airborne dust concentrations because of its higher flow rate (4 L/min). Therefore, the IOM sampler is a more appropriate choice for performing personal sampling in environments with high dust levels. In summary, the Button and IOM samplers with PC filters are efficient sampling/analysis methods for the personal exposure assessment of multiple bioaerosols.

  19. Adaptive cluster sampling: An efficient method for assessing inconspicuous species

    Science.gov (United States)

    Andrea M. Silletti; Joan Walker

    2003-01-01

    Restorationistis typically evaluate the success of a project by estimating the population sizes of species that have been planted or seeded. Because total census is raely feasible, they must rely on sampling methods for population estimates. However, traditional random sampling designs may be inefficient for species that, for one reason or another, are challenging to...

  20. Field evaluation of personal sampling methods for multiple bioaerosols.

    Directory of Open Access Journals (Sweden)

    Chi-Hsun Wang

    Full Text Available Ambient bioaerosols are ubiquitous in the daily environment and can affect health in various ways. However, few studies have been conducted to comprehensively evaluate personal bioaerosol exposure in occupational and indoor environments because of the complex composition of bioaerosols and the lack of standardized sampling/analysis methods. We conducted a study to determine the most efficient collection/analysis method for the personal exposure assessment of multiple bioaerosols. The sampling efficiencies of three filters and four samplers were compared. According to our results, polycarbonate (PC filters had the highest relative efficiency, particularly for bacteria. Side-by-side sampling was conducted to evaluate the three filter samplers (with PC filters and the NIOSH Personal Bioaerosol Cyclone Sampler. According to the results, the Button Aerosol Sampler and the IOM Inhalable Dust Sampler had the highest relative efficiencies for fungi and bacteria, followed by the NIOSH sampler. Personal sampling was performed in a pig farm to assess occupational bioaerosol exposure and to evaluate the sampling/analysis methods. The Button and IOM samplers yielded a similar performance for personal bioaerosol sampling at the pig farm. However, the Button sampler is more likely to be clogged at high airborne dust concentrations because of its higher flow rate (4 L/min. Therefore, the IOM sampler is a more appropriate choice for performing personal sampling in environments with high dust levels. In summary, the Button and IOM samplers with PC filters are efficient sampling/analysis methods for the personal exposure assessment of multiple bioaerosols.

  1. Global metabolite analysis of yeast: evaluation of sample preparation methods

    DEFF Research Database (Denmark)

    Villas-Bôas, Silas Granato; Højer-Pedersen, Jesper; Åkesson, Mats Fredrik

    2005-01-01

    Sample preparation is considered one of the limiting steps in microbial metabolome analysis. Eukaryotes and prokaryotes behave very differently during the several steps of classical sample preparation methods for analysis of metabolites. Even within the eukaryote kingdom there is a vast diversity...

  2. A distance limited method for sampling downed coarse woody debris

    Science.gov (United States)

    Jeffrey H. Gove; Mark J. Ducey; Harry T. Valentine; Michael S. Williams

    2012-01-01

    A new sampling method for down coarse woody debris is proposed based on limiting the perpendicular distance from individual pieces to a randomly chosen sample point. Two approaches are presented that allow different protocols to be used to determine field measurements; estimators for each protocol are also developed. Both protocols are compared via simulation against...

  3. A comprehensive comparison of perpendicular distance sampling methods for sampling downed coarse woody debris

    Science.gov (United States)

    Jeffrey H. Gove; Mark J. Ducey; Harry T. Valentine; Michael S. Williams

    2013-01-01

    Many new methods for sampling down coarse woody debris have been proposed in the last dozen or so years. One of the most promising in terms of field application, perpendicular distance sampling (PDS), has several variants that have been progressively introduced in the literature. In this study, we provide an overview of the different PDS variants and comprehensive...

  4. Approximation of the exponential integral (well function) using sampling methods

    Science.gov (United States)

    Baalousha, Husam Musa

    2015-04-01

    Exponential integral (also known as well function) is often used in hydrogeology to solve Theis and Hantush equations. Many methods have been developed to approximate the exponential integral. Most of these methods are based on numerical approximations and are valid for a certain range of the argument value. This paper presents a new approach to approximate the exponential integral. The new approach is based on sampling methods. Three different sampling methods; Latin Hypercube Sampling (LHS), Orthogonal Array (OA), and Orthogonal Array-based Latin Hypercube (OA-LH) have been used to approximate the function. Different argument values, covering a wide range, have been used. The results of sampling methods were compared with results obtained by Mathematica software, which was used as a benchmark. All three sampling methods converge to the result obtained by Mathematica, at different rates. It was found that the orthogonal array (OA) method has the fastest convergence rate compared with LHS and OA-LH. The root mean square error RMSE of OA was in the order of 1E-08. This method can be used with any argument value, and can be used to solve other integrals in hydrogeology such as the leaky aquifer integral.

  5. A Novel Method to Handle the Effect of Uneven Sampling Effort in Biodiversity Databases

    Science.gov (United States)

    Pardo, Iker; Pata, María P.; Gómez, Daniel; García, María B.

    2013-01-01

    How reliable are results on spatial distribution of biodiversity based on databases? Many studies have evidenced the uncertainty related to this kind of analysis due to sampling effort bias and the need for its quantification. Despite that a number of methods are available for that, little is known about their statistical limitations and discrimination capability, which could seriously constrain their use. We assess for the first time the discrimination capacity of two widely used methods and a proposed new one (FIDEGAM), all based on species accumulation curves, under different scenarios of sampling exhaustiveness using Receiver Operating Characteristic (ROC) analyses. Additionally, we examine to what extent the output of each method represents the sampling completeness in a simulated scenario where the true species richness is known. Finally, we apply FIDEGAM to a real situation and explore the spatial patterns of plant diversity in a National Park. FIDEGAM showed an excellent discrimination capability to distinguish between well and poorly sampled areas regardless of sampling exhaustiveness, whereas the other methods failed. Accordingly, FIDEGAM values were strongly correlated with the true percentage of species detected in a simulated scenario, whereas sampling completeness estimated with other methods showed no relationship due to null discrimination capability. Quantifying sampling effort is necessary to account for the uncertainty in biodiversity analyses, however, not all proposed methods are equally reliable. Our comparative analysis demonstrated that FIDEGAM was the most accurate discriminator method in all scenarios of sampling exhaustiveness, and therefore, it can be efficiently applied to most databases in order to enhance the reliability of biodiversity analyses. PMID:23326357

  6. Neutron activation analysis of certified samples by the absolute method

    Science.gov (United States)

    Kadem, F.; Belouadah, N.; Idiri, Z.

    2015-07-01

    The nuclear reactions analysis technique is mainly based on the relative method or the use of activation cross sections. In order to validate nuclear data for the calculated cross section evaluated from systematic studies, we used the neutron activation analysis technique (NAA) to determine the various constituent concentrations of certified samples for animal blood, milk and hay. In this analysis, the absolute method is used. The neutron activation technique involves irradiating the sample and subsequently performing a measurement of the activity of the sample. The fundamental equation of the activation connects several physical parameters including the cross section that is essential for the quantitative determination of the different elements composing the sample without resorting to the use of standard sample. Called the absolute method, it allows a measurement as accurate as the relative method. The results obtained by the absolute method showed that the values are as precise as the relative method requiring the use of standard sample for each element to be quantified.

  7. Does ignoring multidestination trips in the travel cost method cause a systematic bias?

    NARCIS (Netherlands)

    Kuosmanen, T.K.; Nillesen, E.E.M.; Wesseler, J.H.H.

    2004-01-01

    The present paper demonstrates that treating multidestination trips (MDT) as single-destination trips does not involve any systematic upward or downward bias in consumer surplus (CS) estimates because the direct negative effect of a price increase (treating MDT as a single-destination trip) is

  8. On-capillary sample cleanup method for the electrophoretic determination of carbohydrates in juice samples.

    Science.gov (United States)

    Morales-Cid, Gabriel; Simonet, Bartolomé M; Cárdenas, Soledad; Valcárcel, Miguel

    2007-05-01

    On many occasions, sample treatment is a critical step in electrophoretic analysis. As an alternative to batch procedures, in this work, a new strategy is presented with a view to develop an on-capillary sample cleanup method. This strategy is based on the partial filling of the capillary with carboxylated single-walled carbon nanotube (c-SWNT). The nanoparticles retain interferences from the matrix allowing the determination and quantification of carbohydrates (viz glucose, maltose and fructose). The precision of the method for the analysis of real samples ranged from 5.3 to 6.4%. The proposed method was compared with a method based on a batch filtration of the juice sample through diatomaceous earth and further electrophoretic determination. This method was also validated in this work. The RSD for this other method ranged from 5.1 to 6%. The results obtained by both methods were statistically comparable demonstrating the accuracy of the proposed methods and their effectiveness. Electrophoretic separation of carbohydrates was achieved using 200 mM borate solution as a buffer at pH 9.5 and applying 15 kV. During separation, the capillary temperature was kept constant at 40 degrees C. For the on-capillary cleanup method, a solution containing 50 mg/L of c-SWNTs prepared in 300 mM borate solution at pH 9.5 was introduced for 60 s into the capillary just before sample introduction. For the electrophoretic analysis of samples cleaned in batch with diatomaceous earth, it is also recommended to introduce into the capillary, just before the sample, a 300 mM borate solution as it enhances the sensitivity and electrophoretic resolution.

  9. Validation of method in instrumental NAA for food products sample

    International Nuclear Information System (INIS)

    Alfian; Siti Suprapti; Setyo Purwanto

    2010-01-01

    NAA is a method of testing that has not been standardized. To affirm and confirm that this method is valid. it must be done validation of the method with various sample standard reference materials. In this work. the validation is carried for food product samples using NIST SRM 1567a (wheat flour) and NIST SRM 1568a (rice flour). The results show that the validation method for testing nine elements (Al, K, Mg, Mn, Na, Ca, Fe, Se and Zn) in SRM 1567a and eight elements (Al, K, Mg, Mn, Na, Ca, Se and Zn ) in SRM 1568a pass the test of accuracy and precision. It can be conclude that this method has power to give valid result in determination element of the food products samples. (author)

  10. Respondent driven sampling: determinants of recruitment and a method to improve point estimation.

    Directory of Open Access Journals (Sweden)

    Nicky McCreesh

    Full Text Available Respondent-driven sampling (RDS is a variant of a link-tracing design intended for generating unbiased estimates of the composition of hidden populations that typically involves giving participants several coupons to recruit their peers into the study. RDS may generate biased estimates if coupons are distributed non-randomly or if potential recruits present for interview non-randomly. We explore if biases detected in an RDS study were due to either of these mechanisms, and propose and apply weights to reduce bias due to non-random presentation for interview.Using data from the total population, and the population to whom recruiters offered their coupons, we explored how age and socioeconomic status were associated with being offered a coupon, and, if offered a coupon, with presenting for interview. Population proportions were estimated by weighting by the assumed inverse probabilities of being offered a coupon (as in existing RDS methods, and also of presentation for interview if offered a coupon by age and socioeconomic status group.Younger men were under-recruited primarily because they were less likely to be offered coupons. The under-recruitment of higher socioeconomic status men was due in part to them being less likely to present for interview. Consistent with these findings, weighting for non-random presentation for interview by age and socioeconomic status group greatly improved the estimate of the proportion of men in the lowest socioeconomic group, reducing the root-mean-squared error of RDS estimates of socioeconomic status by 38%, but had little effect on estimates for age. The weighting also improved estimates for tribe and religion (reducing root-mean-squared-errors by 19-29%, but had little effect for sexual activity or HIV status.Data collected from recruiters on the characteristics of men to whom they offered coupons may be used to reduce bias in RDS studies. Further evaluation of this new method is required.

  11. Transformation-cost time-series method for analyzing irregularly sampled data.

    Science.gov (United States)

    Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G Baris; Kurths, Jürgen

    2015-06-01

    Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations-with associated costs-to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.

  12. Transformation-cost time-series method for analyzing irregularly sampled data

    Science.gov (United States)

    Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G. Baris; Kurths, Jürgen

    2015-06-01

    Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations—with associated costs—to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.

  13. Extending the alias Monte Carlo sampling method to general distributions

    International Nuclear Information System (INIS)

    Edwards, A.L.; Rathkopf, J.A.; Smidt, R.K.

    1991-01-01

    The alias method is a Monte Carlo sampling technique that offers significant advantages over more traditional methods. It equals the accuracy of table lookup and the speed of equal probable bins. The original formulation of this method sampled from discrete distributions and was easily extended to histogram distributions. We have extended the method further to applications more germane to Monte Carlo particle transport codes: continuous distributions. This paper presents the alias method as originally derived and our extensions to simple continuous distributions represented by piecewise linear functions. We also present a method to interpolate accurately between distributions tabulated at points other than the point of interest. We present timing studies that demonstrate the method's increased efficiency over table lookup and show further speedup achieved through vectorization. 6 refs., 12 figs., 2 tabs

  14. Soil separator and sampler and method of sampling

    Science.gov (United States)

    O'Brien, Barry H [Idaho Falls, ID; Ritter, Paul D [Idaho Falls, ID

    2010-02-16

    A soil sampler includes a fluidized bed for receiving a soil sample. The fluidized bed may be in communication with a vacuum for drawing air through the fluidized bed and suspending particulate matter of the soil sample in the air. In a method of sampling, the air may be drawn across a filter, separating the particulate matter. Optionally, a baffle or a cyclone may be included within the fluidized bed for disentrainment, or dedusting, so only the finest particulate matter, including asbestos, will be trapped on the filter. The filter may be removable, and may be tested to determine the content of asbestos and other hazardous particulate matter in the soil sample.

  15. Antiretroviral treatment cohort analysis using time-updated CD4 counts: assessment of bias with different analytic methods.

    Directory of Open Access Journals (Sweden)

    Katharina Kranzer

    Full Text Available Survival analysis using time-updated CD4+ counts during antiretroviral therapy is frequently employed to determine risk of clinical events. The time-point when the CD4+ count is assumed to change potentially biases effect estimates but methods used to estimate this are infrequently reported.This study examined the effect of three different estimation methods: assuming i a constant CD4+ count from date of measurement until the date of next measurement, ii a constant CD4+ count from the midpoint of the preceding interval until the midpoint of the subsequent interval and iii a linear interpolation between consecutive CD4+ measurements to provide additional midpoint measurements. Person-time, tuberculosis rates and hazard ratios by CD4+ stratum were compared using all available CD4+ counts (measurement frequency 1-3 months and 6 monthly measurements from a clinical cohort. Simulated data were used to compare the extent of bias introduced by these methods.The midpoint method gave the closest fit to person-time spent with low CD4+ counts and for hazard ratios for outcomes both in the clinical dataset and the simulated data.The midpoint method presents a simple option to reduce bias in time-updated CD4+ analysis, particularly at low CD4 cell counts and rapidly increasing counts after ART initiation.

  16. Methods of human body odor sampling: the effect of freezing.

    Science.gov (United States)

    Lenochova, Pavlina; Roberts, S Craig; Havlicek, Jan

    2009-02-01

    Body odor sampling is an essential tool in human chemical ecology research. However, methodologies of individual studies vary widely in terms of sampling material, length of sampling, and sample processing. Although these differences might have a critical impact on results obtained, almost no studies test validity of current methods. Here, we focused on the effect of freezing samples between collection and use in experiments involving body odor perception. In 2 experiments, we tested whether axillary odors were perceived differently by raters when presented fresh or having been frozen and whether several freeze-thaw cycles affected sample quality. In the first experiment, samples were frozen for 2 weeks, 1 month, or 4 months. We found no differences in ratings of pleasantness, attractiveness, or masculinity between fresh and frozen samples. Similarly, almost no differences between repeatedly thawed and fresh samples were found. We found some variations in intensity; however, this was unrelated to length of storage. The second experiment tested differences between fresh samples and those frozen for 6 months. Again no differences in subjective ratings were observed. These results suggest that freezing has no significant effect on perceived odor hedonicity and that samples can be reliably used after storage for relatively long periods.

  17. Probability Sampling Method for a Hidden Population Using Respondent-Driven Sampling: Simulation for Cancer Survivors.

    Science.gov (United States)

    Jung, Minsoo

    2015-01-01

    When there is no sampling frame within a certain group or the group is concerned that making its population public would bring social stigma, we say the population is hidden. It is difficult to approach this kind of population survey-methodologically because the response rate is low and its members are not quite honest with their responses when probability sampling is used. The only alternative known to address the problems caused by previous methods such as snowball sampling is respondent-driven sampling (RDS), which was developed by Heckathorn and his colleagues. RDS is based on a Markov chain, and uses the social network information of the respondent. This characteristic allows for probability sampling when we survey a hidden population. We verified through computer simulation whether RDS can be used on a hidden population of cancer survivors. According to the simulation results of this thesis, the chain-referral sampling of RDS tends to minimize as the sample gets bigger, and it becomes stabilized as the wave progresses. Therefore, it shows that the final sample information can be completely independent from the initial seeds if a certain level of sample size is secured even if the initial seeds were selected through convenient sampling. Thus, RDS can be considered as an alternative which can improve upon both key informant sampling and ethnographic surveys, and it needs to be utilized for various cases domestically as well.

  18. Effect of additional sample bias in Meshed Plasma Immersion Ion Deposition (MPIID) on microstructural, surface and mechanical properties of Si-DLC films

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Mingzhong [State Key Laboratory of Advanced Welding & Joining, Harbin Institute of Technology, Harbin 150001 (China); School of Materials Science & Engineering, Jiamusi University, Jiamusi 154007 (China); Tian, Xiubo, E-mail: xiubotian@163.com [State Key Laboratory of Advanced Welding & Joining, Harbin Institute of Technology, Harbin 150001 (China); Li, Muqin [School of Materials Science & Engineering, Jiamusi University, Jiamusi 154007 (China); Gong, Chunzhi [State Key Laboratory of Advanced Welding & Joining, Harbin Institute of Technology, Harbin 150001 (China); Wei, Ronghua [Southwest Research Institute, San Antonio, TX 78238 (United States)

    2016-07-15

    Highlights: • A novel Meshed Plasma Immersion Ion Deposition is proposed. • The deposited Si-DLC films possess denser structures and high deposition rate. • It is attributed to ion bombardment of the deposited films. • The ion energy can be independently controlled by an additional bias (novel set up). - Abstract: Meshed Plasma Immersion Ion Deposition (MPIID) using cage-like hollow cathode discharge is a modified process of conventional PIID, but it allows the deposition of thick diamond-like carbon (DLC) films (up to 50 μm) at a high deposition rate (up to 6.5 μm/h). To further improve the DLC film properties, a new approach to the MPIID process is proposed, in which the energy of ions incident to the sample surface can be independently controlled by an additional voltage applied between the samples and the metal meshed cage. In this study, the meshed cage was biased with a pulsed DC power supply at −1350 V peak voltage for the plasma generation, while the samples inside the cage were biased with a DC voltage from 0 V to −500 V with respect to the cage to study its effect. Si-DLC films were synthesized with a mixture of Ar, C{sub 2}H{sub 2} and tetramethylsilane (TMS). After the depositions, scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray photoelectrons spectroscopy (XPS), Raman spectroscopy and nanoindentation were used to study the morphology, surface roughness, chemical bonding and structure, and the surface hardness as well as the modulus of elasticity of the Si-DLC films. It was observed that the intense ion bombardment significantly densified the films, reduced the surface roughness, reduced the H and Si contents, and increased the nanohardness (H) and modulus of elasticity (E), whereas the deposition rate decreased slightly. Using the H and E data, high values of H{sup 3}/E{sup 2} and H/E were obtained on the biased films, indicating the potential excellent mechanical and tribological properties of the films. In this

  19. Method of separate determination of high-ohmic sample resistance and contact resistance

    Directory of Open Access Journals (Sweden)

    Vadim A. Golubiatnikov

    2015-09-01

    Full Text Available A method of separate determination of two-pole sample volume resistance and contact resistance is suggested. The method is applicable to high-ohmic semiconductor samples: semi-insulating gallium arsenide, detector cadmium-zinc telluride (CZT, etc. The method is based on near-contact region illumination by monochromatic radiation of variable intensity from light emitting diodes with quantum energies exceeding the band gap of the material. It is necessary to obtain sample photo-current dependence upon light emitting diode current and to find the linear portion of this dependence. Extrapolation of this linear portion to the Y-axis gives the cut-off current. As the bias voltage is known, it is easy to calculate sample volume resistance. Then, using dark current value, one can determine the total contact resistance. The method was tested for n-type semi-insulating GaAs. The contact resistance value was shown to be approximately equal to the sample volume resistance. Thus, the influence of contacts must be taken into account when electrophysical data are analyzed.

  20. Efficiency of snake sampling methods in the Brazilian semiarid region.

    Science.gov (United States)

    Mesquita, Paula C M D; Passos, Daniel C; Cechin, Sonia Z

    2013-09-01

    The choice of sampling methods is a crucial step in every field survey in herpetology. In countries where time and financial support are limited, the choice of the methods is critical. The methods used to sample snakes often lack objective criteria, and the traditional methods have apparently been more important when making the choice. Consequently researches using not-standardized methods are frequently found in the literature. We have compared four commonly used methods for sampling snake assemblages in a semiarid area in Brazil. We compared the efficacy of each method based on the cost-benefit regarding the number of individuals and species captured, time, and financial investment. We found that pitfall traps were the less effective method in all aspects that were evaluated and it was not complementary to the other methods in terms of abundance of species and assemblage structure. We conclude that methods can only be considered complementary if they are standardized to the objectives of the study. The use of pitfall traps in short-term surveys of the snake fauna in areas with shrubby vegetation and stony soil is not recommended.

  1. Standard methods for sampling North American freshwater fishes

    Science.gov (United States)

    Bonar, Scott A.; Hubert, Wayne A.; Willis, David W.

    2009-01-01

    This important reference book provides standard sampling methods recommended by the American Fisheries Society for assessing and monitoring freshwater fish populations in North America. Methods apply to ponds, reservoirs, natural lakes, and streams and rivers containing cold and warmwater fishes. Range-wide and eco-regional averages for indices of abundance, population structure, and condition for individual species are supplied to facilitate comparisons of standard data among populations. Provides information on converting nonstandard to standard data, statistical and database procedures for analyzing and storing standard data, and methods to prevent transfer of invasive species while sampling.

  2. A multi-dimensional sampling method for locating small scatterers

    International Nuclear Information System (INIS)

    Song, Rencheng; Zhong, Yu; Chen, Xudong

    2012-01-01

    A multiple signal classification (MUSIC)-like multi-dimensional sampling method (MDSM) is introduced to locate small three-dimensional scatterers using electromagnetic waves. The indicator is built with the most stable part of signal subspace of the multi-static response matrix on a set of combinatorial sampling nodes inside the domain of interest. It has two main advantages compared to the conventional MUSIC methods. First, the MDSM is more robust against noise. Second, it can work with a single incidence even for multi-scatterers. Numerical simulations are presented to show the good performance of the proposed method. (paper)

  3. Advanced Markov chain Monte Carlo methods learning from past samples

    CERN Document Server

    Liang, Faming; Carrol, Raymond J

    2010-01-01

    This book provides comprehensive coverage of simulation of complex systems using Monte Carlo methods. Developing algorithms that are immune to the local trap problem has long been considered as the most important topic in MCMC research. Various advanced MCMC algorithms which address this problem have been developed include, the modified Gibbs sampler, the methods based on auxiliary variables and the methods making use of past samples. The focus of this book is on the algorithms that make use of past samples. This book includes the multicanonical algorithm, dynamic weighting, dynamically weight

  4. Comparison of Different Sample Preparation Protocols Reveals Lysis Buffer-Specific Extraction Biases in Gram-Negative Bacteria and Human Cells.

    Science.gov (United States)

    Glatter, Timo; Ahrné, Erik; Schmidt, Alexander

    2015-11-06

    We evaluated different in-solution and FASP-based sample preparation strategies for absolute protein quantification. Label-free quantification (LFQ) was employed to compare different sample preparation strategies in the bacterium Pseudomonas aeruginosa and human embryonic kidney cells (HEK), and organismal-specific differences in general performance and enrichment of specific protein classes were noted. The original FASP protocol globally enriched for most proteins in the bacterial sample, whereas the sodium deoxycholate in-solution strategy was more efficient with HEK cells. Although detergents were found to be highly suited for global proteome analysis, higher intensities were obtained for high-abundant nucleic acid-associated protein complexes, like the ribosome and histone proteins, using guanidine hydrochloride. Importantly, we show for the first time that the observable total proteome mass of a sample strongly depends on the sample preparation protocol, with some protocols resulting in a significant underestimation of protein mass due to incomplete protein extraction of biased protein groups. Furthermore, we demonstrate that some of the observed abundance biases can be overcome by incorporating a nuclease treatment step or, alternatively, a correction factor for complementary sample preparation approaches.

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

    Directory of Open Access Journals (Sweden)

    João Fabrício Mota Rodrigues

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

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

    Science.gov (United States)

    Rodrigues, João Fabrício Mota; Coelho, Marco Túlio Pacheco

    2016-01-01

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

  7. Development of sample preparation method for honey analysis using PIXE

    International Nuclear Information System (INIS)

    Saitoh, Katsumi; Chiba, Keiko; Sera, Koichiro

    2008-01-01

    We developed an original preparation method for honey samples (samples in paste-like state) specifically designed for PIXE analysis. The results of PIXE analysis of thin targets prepared by adding a standard containing nine elements to honey samples demonstrated that the preparation method bestowed sufficient accuracy on quantitative values. PIXE analysis of 13 kinds of honey was performed, and eight mineral components (Si, P, S, K, Ca, Mn, Cu and Zn) were detected in all honey samples. The principal mineral components were K and Ca, and the quantitative value for K accounted for the majority of the total value for mineral components. K content in honey varies greatly depending on the plant source. Chestnuts had the highest K content. In fact, it was 2-3 times that of Manuka, which is known as a high quality honey. K content of false-acacia, which is produced in the greatest abundance, was 1/20 that of chestnuts. (author)

  8. Validation of single-sample doubly labeled water method

    International Nuclear Information System (INIS)

    Webster, M.D.; Weathers, W.W.

    1989-01-01

    We have experimentally validated a single-sample variant of the doubly labeled water method for measuring metabolic rate and water turnover in a very small passerine bird, the verdin (Auriparus flaviceps). We measured CO 2 production using the Haldane gravimetric technique and compared these values with estimates derived from isotopic data. Doubly labeled water results based on the one-sample calculations differed from Haldane values by less than 0.5% on average (range -8.3 to 11.2%, n = 9). Water flux computed by the single-sample method differed by -1.5% on average from results for the same birds based on the standard, two-sample technique (range -13.7 to 2.0%, n = 9)

  9. Examination of Hydrate Formation Methods: Trying to Create Representative Samples

    Energy Technology Data Exchange (ETDEWEB)

    Kneafsey, T.J.; Rees, E.V.L.; Nakagawa, S.; Kwon, T.-H.

    2011-04-01

    Forming representative gas hydrate-bearing laboratory samples is important so that the properties of these materials may be measured, while controlling the composition and other variables. Natural samples are rare, and have often experienced pressure and temperature changes that may affect the property to be measured [Waite et al., 2008]. Forming methane hydrate samples in the laboratory has been done a number of ways, each having advantages and disadvantages. The ice-to-hydrate method [Stern et al., 1996], contacts melting ice with methane at the appropriate pressure to form hydrate. The hydrate can then be crushed and mixed with mineral grains under controlled conditions, and then compacted to create laboratory samples of methane hydrate in a mineral medium. The hydrate in these samples will be part of the load-bearing frame of the medium. In the excess gas method [Handa and Stupin, 1992], water is distributed throughout a mineral medium (e.g. packed moist sand, drained sand, moistened silica gel, other porous media) and the mixture is brought to hydrate-stable conditions (chilled and pressurized with gas), allowing hydrate to form. This method typically produces grain-cementing hydrate from pendular water in sand [Waite et al., 2004]. In the dissolved gas method [Tohidi et al., 2002], water with sufficient dissolved guest molecules is brought to hydrate-stable conditions where hydrate forms. In the laboratory, this is can be done by pre-dissolving the gas of interest in water and then introducing it to the sample under the appropriate conditions. With this method, it is easier to form hydrate from more soluble gases such as carbon dioxide. It is thought that this method more closely simulates the way most natural gas hydrate has formed. Laboratory implementation, however, is difficult, and sample formation is prohibitively time consuming [Minagawa et al., 2005; Spangenberg and Kulenkampff, 2005]. In another version of this technique, a specified quantity of gas

  10. Standard methods for sampling freshwater fishes: opportunities for international collaboration

    OpenAIRE

    Bonar, Scott A.; Mercado-Silva, Norman; Hubert, Wayne A.; Beard, T. Douglas; Dave, Göran; Kubečka, Jan; Graeb, Brian D.S.; Lester, Nigel P.; Porath, Mark; Winfield, Ian J.

    2017-01-01

    With publication of Standard Methods for Sampling North American Freshwater Fishes in 2009, the American Fisheries Society (AFS) recommended standard procedures for North America. To explore interest in standardizing at intercontinental scales, a symposium attended by international specialists in freshwater fish sampling was convened at the 145th Annual AFS Meeting in Portland, Oregon, in August 2015. Participants represented all continents except Australia and Antarctica and were employed by...

  11. A polar-region-adaptable systematic bias collaborative measurement method for shipboard redundant rotational inertial navigation systems

    Science.gov (United States)

    Wang, Lin; Wu, Wenqi; Wei, Guo; Lian, Junxiang; Yu, Ruihang

    2018-05-01

    The shipboard redundant rotational inertial navigation system (RINS) configuration, including a dual-axis RINS and a single-axis RINS, can satisfy the demand of marine INSs of especially high reliability as well as achieving trade-off between position accuracy and cost. Generally, the dual-axis RINS is the master INS, and the single-axis RINS is the hot backup INS for high reliability purposes. An integrity monitoring system performs a fault detection function to ensure sailing safety. However, improving the accuracy of the backup INS in case of master INS failure has not been given enough attention. Without the aid of any external information, a systematic bias collaborative measurement method based on an augmented Kalman filter is proposed for the redundant RINSs. Estimates of inertial sensor biases can be used by the built-in integrity monitoring system to monitor the RINS running condition. On the other hand, a position error prediction model is designed for the single-axis RINS to estimate the systematic error caused by its azimuth gyro bias. After position error compensation, the position information provided by the single-axis RINS still remains highly accurate, even if the integrity monitoring system detects a dual-axis RINS fault. Moreover, use of a grid frame as a navigation frame makes the proposed method applicable in any area, including the polar regions. Semi-physical simulation and experiments including sea trials verify the validity of the method.

  12. Bias correction method for climate change impact assessment at a basin scale

    Science.gov (United States)

    Nyunt, C.; Jaranilla-sanchez, P. A.; Yamamoto, A.; Nemoto, T.; Kitsuregawa, M.; Koike, T.

    2012-12-01

    Climate change impact studies are mainly based on the general circulation models GCM and these studies play an important role to define suitable adaptation strategies for resilient environment in a basin scale management. For this purpose, this study summarized how to select appropriate GCM to decrease the certain uncertainty amount in analysis. This was applied to the Pampanga, Angat and Kaliwa rivers in Luzon Island, the main island of Philippine and these three river basins play important roles in irrigation water supply, municipal water source for Metro Manila. According to the GCM scores of both seasonal evolution of Asia summer monsoon and spatial correlation and root mean squared error of atmospheric variables over the region, finally six GCM is chosen. Next, we develop a complete, efficient and comprehensive statistical bias correction scheme covering extremes events, normal rainfall and frequency of dry period. Due to the coarse resolution and parameterization scheme of GCM, extreme rainfall underestimation, too many rain days with low intensity and poor representation of local seasonality have been known as bias of GCM. Extreme rainfall has unusual characteristics and it should be focused specifically. Estimated maximum extreme rainfall is crucial for planning and design of infrastructures in river basin. Developing countries have limited technical, financial and management resources for implementing adaptation measures and they need detailed information of drought and flood for near future. Traditionally, the analysis of extreme has been examined using annual maximum series (AMS) adjusted to a Gumbel or Lognormal distribution. The drawback is the loss of the second, third etc, largest rainfall. Another approach is partial duration series (PDS) constructed using the values above a selected threshold and permit more than one event per year. The generalized Pareto distribution (GPD) has been used to model PDS and it is the series of excess over a threshold

  13. Fluidics platform and method for sample preparation and analysis

    Science.gov (United States)

    Benner, W. Henry; Dzenitis, John M.; Bennet, William J.; Baker, Brian R.

    2014-08-19

    Herein provided are fluidics platform and method for sample preparation and analysis. The fluidics platform is capable of analyzing DNA from blood samples using amplification assays such as polymerase-chain-reaction assays and loop-mediated-isothermal-amplification assays. The fluidics platform can also be used for other types of assays and analyzes. In some embodiments, a sample in a sealed tube can be inserted directly. The following isolation, detection, and analyzes can be performed without a user's intervention. The disclosed platform may also comprises a sample preparation system with a magnetic actuator, a heater, and an air-drying mechanism, and fluid manipulation processes for extraction, washing, elution, assay assembly, assay detection, and cleaning after reactions and between samples.

  14. Adaptive sampling method in deep-penetration particle transport problem

    International Nuclear Information System (INIS)

    Wang Ruihong; Ji Zhicheng; Pei Lucheng

    2012-01-01

    Deep-penetration problem has been one of the difficult problems in shielding calculation with Monte Carlo method for several decades. In this paper, a kind of particle transport random walking system under the emission point as a sampling station is built. Then, an adaptive sampling scheme is derived for better solution with the achieved information. The main advantage of the adaptive scheme is to choose the most suitable sampling number from the emission point station to obtain the minimum value of the total cost in the process of the random walk. Further, the related importance sampling method is introduced. Its main principle is to define the importance function due to the particle state and to ensure the sampling number of the emission particle is proportional to the importance function. The numerical results show that the adaptive scheme under the emission point as a station could overcome the difficulty of underestimation of the result in some degree, and the adaptive importance sampling method gets satisfied results as well. (authors)

  15. Methods for Sampling and Measurement of Compressed Air Contaminants

    International Nuclear Information System (INIS)

    Stroem, L.

    1976-10-01

    In order to improve the technique for measuring oil and water entrained in a compressed air stream, a laboratory study has been made of some methods for sampling and measurement. For this purpose water or oil as artificial contaminants were injected in thin streams into a test loop, carrying dry compressed air. Sampling was performed in a vertical run, down-stream of the injection point. Wall attached liquid, coarse droplet flow, and fine droplet flow were sampled separately. The results were compared with two-phase flow theory and direct observation of liquid behaviour. In a study of sample transport through narrow tubes, it was observed that, below a certain liquid loading, the sample did not move, the liquid remaining stationary on the tubing wall. The basic analysis of the collected samples was made by gravimetric methods. Adsorption tubes were used with success to measure water vapour. A humidity meter with a sensor of the aluminium oxide type was found to be unreliable. Oil could be measured selectively by a flame ionization detector, the sample being pretreated in an evaporation- condensation unit

  16. Methods for Sampling and Measurement of Compressed Air Contaminants

    Energy Technology Data Exchange (ETDEWEB)

    Stroem, L

    1976-10-15

    In order to improve the technique for measuring oil and water entrained in a compressed air stream, a laboratory study has been made of some methods for sampling and measurement. For this purpose water or oil as artificial contaminants were injected in thin streams into a test loop, carrying dry compressed air. Sampling was performed in a vertical run, down-stream of the injection point. Wall attached liquid, coarse droplet flow, and fine droplet flow were sampled separately. The results were compared with two-phase flow theory and direct observation of liquid behaviour. In a study of sample transport through narrow tubes, it was observed that, below a certain liquid loading, the sample did not move, the liquid remaining stationary on the tubing wall. The basic analysis of the collected samples was made by gravimetric methods. Adsorption tubes were used with success to measure water vapour. A humidity meter with a sensor of the aluminium oxide type was found to be unreliable. Oil could be measured selectively by a flame ionization detector, the sample being pretreated in an evaporation- condensation unit

  17. Sampling and sample preparation methods for the analysis of trace elements in biological material

    International Nuclear Information System (INIS)

    Sansoni, B.; Iyengar, V.

    1978-05-01

    The authors attempt to give a most systamtic possible treatment of the sample taking and sample preparation of biological material (particularly in human medicine) for trace analysis (e.g. neutron activation analysis, atomic absorption spectrometry). Contamination and loss problems are discussed as well as the manifold problems of the different consistency of solid and liquid biological materials, as well as the stabilization of the sample material. The process of dry and wet ashing is particularly dealt with, where new methods are also described. (RB) [de

  18. A new bias field correction method combining N3 and FCM for improved segmentation of breast density on MRI.

    Science.gov (United States)

    Lin, Muqing; Chan, Siwa; Chen, Jeon-Hor; Chang, Daniel; Nie, Ke; Chen, Shih-Ting; Lin, Cheng-Ju; Shih, Tzu-Ching; Nalcioglu, Orhan; Su, Min-Ying

    2011-01-01

    Quantitative breast density is known as a strong risk factor associated with the development of breast cancer. Measurement of breast density based on three-dimensional breast MRI may provide very useful information. One important step for quantitative analysis of breast density on MRI is the correction of field inhomogeneity to allow an accurate segmentation of the fibroglandular tissue (dense tissue). A new bias field correction method by combining the nonparametric nonuniformity normalization (N3) algorithm and fuzzy-C-means (FCM)-based inhomogeneity correction algorithm is developed in this work. The analysis is performed on non-fat-sat T1-weighted images acquired using a 1.5 T MRI scanner. A total of 60 breasts from 30 healthy volunteers was analyzed. N3 is known as a robust correction method, but it cannot correct a strong bias field on a large area. FCM-based algorithm can correct the bias field on a large area, but it may change the tissue contrast and affect the segmentation quality. The proposed algorithm applies N3 first, followed by FCM, and then the generated bias field is smoothed using Gaussian kernal and B-spline surface fitting to minimize the problem of mistakenly changed tissue contrast. The segmentation results based on the N3+FCM corrected images were compared to the N3 and FCM alone corrected images and another method, coherent local intensity clustering (CLIC), corrected images. The segmentation quality based on different correction methods were evaluated by a radiologist and ranked. The authors demonstrated that the iterative N3+FCM correction method brightens the signal intensity of fatty tissues and that separates the histogram peaks between the fibroglandular and fatty tissues to allow an accurate segmentation between them. In the first reading session, the radiologist found (N3+FCM > N3 > FCM) ranking in 17 breasts, (N3+FCM > N3 = FCM) ranking in 7 breasts, (N3+FCM = N3 > FCM) in 32 breasts, (N3+FCM = N3 = FCM) in 2 breasts, and (N3 > N3

  19. An algorithm to improve sampling efficiency for uncertainty propagation using sampling based method

    International Nuclear Information System (INIS)

    Campolina, Daniel; Lima, Paulo Rubens I.; Pereira, Claubia; Veloso, Maria Auxiliadora F.

    2015-01-01

    Sample size and computational uncertainty were varied in order to investigate sample efficiency and convergence of the sampling based method for uncertainty propagation. Transport code MCNPX was used to simulate a LWR model and allow the mapping, from uncertain inputs of the benchmark experiment, to uncertain outputs. Random sampling efficiency was improved through the use of an algorithm for selecting distributions. Mean range, standard deviation range and skewness were verified in order to obtain a better representation of uncertainty figures. Standard deviation of 5 pcm in the propagated uncertainties for 10 n-samples replicates was adopted as convergence criterion to the method. Estimation of 75 pcm uncertainty on reactor k eff was accomplished by using sample of size 93 and computational uncertainty of 28 pcm to propagate 1σ uncertainty of burnable poison radius. For a fixed computational time, in order to reduce the variance of the uncertainty propagated, it was found, for the example under investigation, it is preferable double the sample size than double the amount of particles followed by Monte Carlo process in MCNPX code. (author)

  20. Evaluation of Stress Loaded Steel Samples Using Selected Electromagnetic Methods

    International Nuclear Information System (INIS)

    Chady, T.

    2004-01-01

    In this paper the magnetic leakage flux and eddy current method were used to evaluate changes of materials' properties caused by stress. Seven samples made of ferromagnetic material with different level of applied stress were prepared. First, the leakage magnetic fields were measured by scanning the surface of the specimens with GMR gradiometer. Next, the same samples were evaluated using an eddy current sensor. A comparison between results obtained from both methods was carried out. Finally, selected parameters of the measured signal were calculated and utilized to evaluate level of the applied stress. A strong coincidence between amount of the applied stress and the maximum amplitude of the derivative was confirmed

  1. On the Exploitation of Sensitivity Derivatives for Improving Sampling Methods

    Science.gov (United States)

    Cao, Yanzhao; Hussaini, M. Yousuff; Zang, Thomas A.

    2003-01-01

    Many application codes, such as finite-element structural analyses and computational fluid dynamics codes, are capable of producing many sensitivity derivatives at a small fraction of the cost of the underlying analysis. This paper describes a simple variance reduction method that exploits such inexpensive sensitivity derivatives to increase the accuracy of sampling methods. Three examples, including a finite-element structural analysis of an aircraft wing, are provided that illustrate an order of magnitude improvement in accuracy for both Monte Carlo and stratified sampling schemes.

  2. [Progress in sample preparation and analytical methods for trace polar small molecules in complex samples].

    Science.gov (United States)

    Zhang, Qianchun; Luo, Xialin; Li, Gongke; Xiao, Xiaohua

    2015-09-01

    Small polar molecules such as nucleosides, amines, amino acids are important analytes in biological, food, environmental, and other fields. It is necessary to develop efficient sample preparation and sensitive analytical methods for rapid analysis of these polar small molecules in complex matrices. Some typical materials in sample preparation, including silica, polymer, carbon, boric acid and so on, are introduced in this paper. Meanwhile, the applications and developments of analytical methods of polar small molecules, such as reversed-phase liquid chromatography, hydrophilic interaction chromatography, etc., are also reviewed.

  3. Correction for the Hematocrit Bias in Dried Blood Spot Analysis Using a Nondestructive, Single-Wavelength Reflectance-Based Hematocrit Prediction Method.

    Science.gov (United States)

    Capiau, Sara; Wilk, Leah S; De Kesel, Pieter M M; Aalders, Maurice C G; Stove, Christophe P

    2018-02-06

    The hematocrit (Hct) effect is one of the most important hurdles currently preventing more widespread implementation of quantitative dried blood spot (DBS) analysis in a routine context. Indeed, the Hct may affect both the accuracy of DBS methods as well as the interpretation of DBS-based results. We previously developed a method to determine the Hct of a DBS based on its hemoglobin content using noncontact diffuse reflectance spectroscopy. Despite the ease with which the analysis can be performed (i.e., mere scanning of the DBS) and the good results that were obtained, the method did require a complicated algorithm to derive the total hemoglobin content from the DBS's reflectance spectrum. As the total hemoglobin was calculated as the sum of oxyhemoglobin, methemoglobin, and hemichrome, the three main hemoglobin derivatives formed in DBS upon aging, the reflectance spectrum needed to be unmixed to determine the quantity of each of these derivatives. We now simplified the method by only using the reflectance at a single wavelength, located at a quasi-isosbestic point in the reflectance curve. At this wavelength, assuming 1-to-1 stoichiometry of the aging reaction, the reflectance is insensitive to the hemoglobin degradation and only scales with the total amount of hemoglobin and, hence, the Hct. This simplified method was successfully validated. At each quality control level as well as at the limits of quantitation (i.e., 0.20 and 0.67) bias, intra- and interday imprecision were within 10%. Method reproducibility was excellent based on incurred sample reanalysis and surpassed the reproducibility of the original method. Furthermore, the influence of the volume spotted, the measurement location within the spot, as well as storage time and temperature were evaluated, showing no relevant impact of these parameters. Application to 233 patient samples revealed a good correlation between the Hct determined on whole blood and the predicted Hct determined on venous DBS. The

  4. Estimation of creatinine in Urine sample by Jaffe's method

    International Nuclear Information System (INIS)

    Wankhede, Sonal; Arunkumar, Suja; Sawant, Pramilla D.; Rao, B.B.

    2012-01-01

    In-vitro bioassay monitoring is based on the determination of activity concentrations in biological samples excreted from the body and is most suitable for alpha and beta emitters. A truly representative bioassay sample is the one having all the voids collected during a 24-h period however, this being technically difficult, overnight urine samples collected by the workers are analyzed. These overnight urine samples are collected for 10-16 h, however in the absence of any specific information, 12 h duration is assumed and the observed results are then corrected accordingly obtain the daily excretion rate. To reduce the uncertainty due to unknown duration of sample collection, IAEA has recommended two methods viz., measurement of specific gravity and creatinine excretion rate in urine sample. Creatinine is a final metabolic product creatinine phosphate in the body and is excreted at a steady rate for people with normally functioning kidneys. It is, therefore, often used as a normalization factor for estimation of duration of sample collection. The present study reports the chemical procedure standardized and its application for the estimation of creatinine in urine samples collected from occupational workers. Chemical procedure for estimation of creatinine in bioassay samples was standardized and applied successfully for its estimation in bioassay samples collected from the workers. The creatinine excretion rate observed for these workers is lower than observed in literature. Further, work is in progress to generate a data bank of creatinine excretion rate for most of the workers and also to study the variability in creatinine coefficient for the same individual based on the analysis of samples collected for different duration

  5. Sampling methods for low-frequency electromagnetic imaging

    International Nuclear Information System (INIS)

    Gebauer, Bastian; Hanke, Martin; Schneider, Christoph

    2008-01-01

    For the detection of hidden objects by low-frequency electromagnetic imaging the linear sampling method works remarkably well despite the fact that the rigorous mathematical justification is still incomplete. In this work, we give an explanation for this good performance by showing that in the low-frequency limit the measurement operator fulfils the assumptions for the fully justified variant of the linear sampling method, the so-called factorization method. We also show how the method has to be modified in the physically relevant case of electromagnetic imaging with divergence-free currents. We present numerical results to illustrate our findings, and to show that similar performance can be expected for the case of conducting objects and layered backgrounds

  6. Comparison of sampling methods for radiocarbon dating of carbonyls in air samples via accelerator mass spectrometry

    Science.gov (United States)

    Schindler, Matthias; Kretschmer, Wolfgang; Scharf, Andreas; Tschekalinskij, Alexander

    2016-05-01

    Three new methods to sample and prepare various carbonyl compounds for radiocarbon measurements were developed and tested. Two of these procedures utilized the Strecker synthetic method to form amino acids from carbonyl compounds with either sodium cyanide or trimethylsilyl cyanide. The third procedure used semicarbazide to form crystalline carbazones with the carbonyl compounds. The resulting amino acids and semicarbazones were then separated and purified using thin layer chromatography. The separated compounds were then combusted to CO2 and reduced to graphite to determine 14C content by accelerator mass spectrometry (AMS). All of these methods were also compared with the standard carbonyl compound sampling method wherein a compound is derivatized with 2,4-dinitrophenylhydrazine and then separated by high-performance liquid chromatography (HPLC).

  7. Comparison of sampling methods for radiocarbon dating of carbonyls in air samples via accelerator mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Schindler, Matthias, E-mail: matthias.schindler@physik.uni-erlangen.de; Kretschmer, Wolfgang; Scharf, Andreas; Tschekalinskij, Alexander

    2016-05-15

    Three new methods to sample and prepare various carbonyl compounds for radiocarbon measurements were developed and tested. Two of these procedures utilized the Strecker synthetic method to form amino acids from carbonyl compounds with either sodium cyanide or trimethylsilyl cyanide. The third procedure used semicarbazide to form crystalline carbazones with the carbonyl compounds. The resulting amino acids and semicarbazones were then separated and purified using thin layer chromatography. The separated compounds were then combusted to CO{sub 2} and reduced to graphite to determine {sup 14}C content by accelerator mass spectrometry (AMS). All of these methods were also compared with the standard carbonyl compound sampling method wherein a compound is derivatized with 2,4-dinitrophenylhydrazine and then separated by high-performance liquid chromatography (HPLC).

  8. Uncertainty in biological monitoring: a framework for data collection and analysis to account for multiple sources of sampling bias

    Science.gov (United States)

    Ruiz-Gutierrez, Viviana; Hooten, Melvin B.; Campbell Grant, Evan H.

    2016-01-01

    Biological monitoring programmes are increasingly relying upon large volumes of citizen-science data to improve the scope and spatial coverage of information, challenging the scientific community to develop design and model-based approaches to improve inference.Recent statistical models in ecology have been developed to accommodate false-negative errors, although current work points to false-positive errors as equally important sources of bias. This is of particular concern for the success of any monitoring programme given that rates as small as 3% could lead to the overestimation of the occurrence of rare events by as much as 50%, and even small false-positive rates can severely bias estimates of occurrence dynamics.We present an integrated, computationally efficient Bayesian hierarchical model to correct for false-positive and false-negative errors in detection/non-detection data. Our model combines independent, auxiliary data sources with field observations to improve the estimation of false-positive rates, when a subset of field observations cannot be validated a posteriori or assumed as perfect. We evaluated the performance of the model across a range of occurrence rates, false-positive and false-negative errors, and quantity of auxiliary data.The model performed well under all simulated scenarios, and we were able to identify critical auxiliary data characteristics which resulted in improved inference. We applied our false-positive model to a large-scale, citizen-science monitoring programme for anurans in the north-eastern United States, using auxiliary data from an experiment designed to estimate false-positive error rates. Not correcting for false-positive rates resulted in biased estimates of occupancy in 4 of the 10 anuran species we analysed, leading to an overestimation of the average number of occupied survey routes by as much as 70%.The framework we present for data collection and analysis is able to efficiently provide reliable inference for

  9. Experiment of bias probe method at NIRS-18 GHz ECR ion source

    Energy Technology Data Exchange (ETDEWEB)

    Jincho, Kaoru; Yamamoto, Mitsugu; Okada, Takanori; Takasugi, Wataru; Sakuma, Tetsuya; Miyoshi, Tomohiro [Accelerator Engineering Corp., Chiba (Japan); Kitagawa, Atsushi; Muramatsu, Masayuki [National Inst. of Radiological Sciences, Chiba (Japan); Biri, Sandor [Institute of Nuclear Research (ATOMKI), Debrecen (Hungary)

    2000-11-01

    An 18 GHz ECR ion source (NIRS-HEC) has been developed to produce highly charged heavy ions from Ar to Xe. In order to increase the beam intensity of highly charged ion, we tried a technique of supplying cold electrons into the ECR plasma. In this paper, enhancement of the beam intensity is discussed in detail. The bias voltage is applied on the probe to repel cold electrons which flow from a plasma. The output beam current is 130 e{mu}A for Ar{sup 11+}. (J.P.N.)

  10. Experiment of bias probe method at NIRS-18 GHz ECR ion source

    International Nuclear Information System (INIS)

    Jincho, Kaoru; Yamamoto, Mitsugu; Okada, Takanori; Takasugi, Wataru; Sakuma, Tetsuya; Miyoshi, Tomohiro; Kitagawa, Atsushi; Muramatsu, Masayuki; Biri, Sandor

    2000-01-01

    An 18 GHz ECR ion source (NIRS-HEC) has been developed to produce highly charged heavy ions from Ar to Xe. In order to increase the beam intensity of highly charged ion, we tried a technique of supplying cold electrons into the ECR plasma. In this paper, enhancement of the beam intensity is discussed in detail. The bias voltage is applied on the probe to repel cold electrons which flow from a plasma. The output beam current is 130 eμA for Ar 11+ . (J.P.N.)

  11. Standard guide for preparing and interpreting precision and bias statements in test method standards used in the nuclear industry

    CERN Document Server

    American Society for Testing and Materials. Philadelphia

    1992-01-01

    1.1 This guide covers terminology useful for the preparation and interpretation of precision and bias statements. 1.2 In formulating precision and bias statements, it is important to understand the statistical concepts involved and to identify the major sources of variation that affect results. Appendix X1 provides a brief summary of these concepts. 1.3 To illustrate the statistical concepts and to demonstrate some sources of variation, a hypothetical data set has been analyzed in Appendix X2. Reference to this example is made throughout this guide. 1.4 It is difficult and at times impossible to ship nuclear materials for interlaboratory testing. Thus, precision statements for test methods relating to nuclear materials will ordinarily reflect only within-laboratory variation.

  12. Methods for Characterisation of unknown Suspect Radioactive Samples

    International Nuclear Information System (INIS)

    Sahagia, M.; Grigorescu, E.L.; Luca, A.; Razdolescu, A.C.; Ivan, C.

    2001-01-01

    Full text: The paper presents various identification and measurement methods, used for the expertise of a wide variety of suspect radioactive materials, whose circulation was not legally stated. The main types of examined samples were: radioactive sources, illegally trafficked; suspect radioactive materials or radioactively contaminated devices; uranium tablets; fire detectors containing 241 Am sources; osmium samples containing radioactive 185 Os or enriched 187 Os. The types of analyses and determination methods were as follows: the chemical composition was determined by using identification reagents or by neutron activation analysis; the radionuclide composition was determined by using gamma-ray spectrometry; the activity and particle emission rates were determined by using calibrated radiometric equipment; the absorbed dose rate at the wall of all types of containers and samples was determined by using calibrated dose ratemeters. The radiation exposure risk for population, due to these radioactive materials, was evaluated for every case. (author)

  13. Sampling and analysis methods for geothermal fluids and gases

    Energy Technology Data Exchange (ETDEWEB)

    Shannon, D. W.

    1978-01-01

    The data obtained for the first round robin sample collected at Mesa 6-2 wellhead, East Mesa Test Site, Imperial Valley are summarized. Test results are listed by method used for cross reference to the analytic methods section. Results obtained for radioactive isotopes present in the brine sample are tabulated. The data obtained for the second round robin sample collected from the Woolsey No. 1 first stage flash unit, San Diego Gas and Electric Niland Test Facility are presented in the same manner. Lists of the participants of the two round robins are given. Data from miscellaneous analyses are included. Summaries of values derived from the round robin raw data are presented. (MHR)

  14. Microbial diversity in fecal samples depends on DNA extraction method

    DEFF Research Database (Denmark)

    Mirsepasi, Hengameh; Persson, Søren; Struve, Carsten

    2014-01-01

    was to evaluate two different DNA extraction methods in order to choose the most efficient method for studying intestinal bacterial diversity using Denaturing Gradient Gel Electrophoresis (DGGE). FINDINGS: In this study, a semi-automatic DNA extraction system (easyMag®, BioMérieux, Marcy I'Etoile, France......BACKGROUND: There are challenges, when extracting bacterial DNA from specimens for molecular diagnostics, since fecal samples also contain DNA from human cells and many different substances derived from food, cell residues and medication that can inhibit downstream PCR. The purpose of the study...... by easyMag® from the same fecal samples. Furthermore, DNA extracts obtained using easyMag® seemed to contain inhibitory compounds, since in order to perform a successful PCR-analysis, the sample should be diluted at least 10 times. DGGE performed on PCR from DNA extracted by QIAamp DNA Stool Mini Kit DNA...

  15. A Frequency Domain Design Method For Sampled-Data Compensators

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Jannerup, Ole Erik

    1990-01-01

    A new approach to the design of a sampled-data compensator in the frequency domain is investigated. The starting point is a continuous-time compensator for the continuous-time system which satisfy specific design criteria. The new design method will graphically show how the discrete...

  16. Phosphorus analysis in milk samples by neutron activation analysis method

    International Nuclear Information System (INIS)

    Oliveira, R.M. de; Cunha, I.I.L.

    1991-01-01

    The determination of phosphorus in milk samples by instrumental thermal neutron activation analysis is described. The procedure involves a short irradiation in a nuclear reactor and measurement of the beta radiation emitted by phosphorus - 32 after a suitable decay period. The sources of error were studied and the established method was applied to standard reference materials of known phosphorus content. (author)

  17. Sampling point selection for energy estimation in the quasicontinuum method

    NARCIS (Netherlands)

    Beex, L.A.A.; Peerlings, R.H.J.; Geers, M.G.D.

    2010-01-01

    The quasicontinuum (QC) method reduces computational costs of atomistic calculations by using interpolation between a small number of so-called repatoms to represent the displacements of the complete lattice and by selecting a small number of sampling atoms to estimate the total potential energy of

  18. A General Linear Method for Equating with Small Samples

    Science.gov (United States)

    Albano, Anthony D.

    2015-01-01

    Research on equating with small samples has shown that methods with stronger assumptions and fewer statistical estimates can lead to decreased error in the estimated equating function. This article introduces a new approach to linear observed-score equating, one which provides flexible control over how form difficulty is assumed versus estimated…

  19. Performance of sampling methods to estimate log characteristics for wildlife.

    Science.gov (United States)

    Lisa J. Bate; Torolf R. Torgersen; Michael J. Wisdom; Edward O. Garton

    2004-01-01

    Accurate estimation of the characteristics of log resources, or coarse woody debris (CWD), is critical to effective management of wildlife and other forest resources. Despite the importance of logs as wildlife habitat, methods for sampling logs have traditionally focused on silvicultural and fire applications. These applications have emphasized estimates of log volume...

  20. Effect of method of sample preparation on ruminal in situ ...

    African Journals Online (AJOL)

    Midmar) was harvested at three and four weeks after cutting and fertilizing with 200 kg nitrogen (N)/ha. Freshly cut herbage was used to investigate the following four sample preparation methods. In trial 1, herbage was (1) chopped with a paper-cutting guillotine into 5-10 mm lengths, representing fresh (FR) herbage; ...

  1. Sample processing method for the determination of perchlorate in milk

    International Nuclear Information System (INIS)

    Dyke, Jason V.; Kirk, Andrea B.; Kalyani Martinelango, P.; Dasgupta, Purnendu K.

    2006-01-01

    In recent years, many different water sources and foods have been reported to contain perchlorate. Studies indicate that significant levels of perchlorate are present in both human and dairy milk. The determination of perchlorate in milk is particularly important due to its potential health impact on infants and children. As for many other biological samples, sample preparation is more time consuming than the analysis itself. The concurrent presence of large amounts of fats, proteins, carbohydrates, etc., demands some initial cleanup; otherwise the separation column lifetime and the limit of detection are both greatly compromised. Reported milk processing methods require the addition of chemicals such as ethanol, acetic acid or acetonitrile. Reagent addition is undesirable in trace analysis. We report here an essentially reagent-free sample preparation method for the determination of perchlorate in milk. Milk samples are spiked with isotopically labeled perchlorate and centrifuged to remove lipids. The resulting liquid is placed in a disposable centrifugal ultrafilter device with a molecular weight cutoff of 10 kDa, and centrifuged. Approximately 5-10 ml of clear liquid, ready for analysis, is obtained from a 20 ml milk sample. Both bovine and human milk samples have been successfully processed and analyzed by ion chromatography-mass spectrometry (IC-MS). Standard addition experiments show good recoveries. The repeatability of the analytical result for the same sample in multiple sample cleanup runs ranged from 3 to 6% R.S.D. This processing technique has also been successfully applied for the determination of iodide and thiocyanate in milk

  2. Sampling methods for the study of pneumococcal carriage: a systematic review.

    Science.gov (United States)

    Gladstone, R A; Jefferies, J M; Faust, S N; Clarke, S C

    2012-11-06

    Streptococcus pneumoniae is an important pathogen worldwide. Accurate sampling of S. pneumoniae carriage is central to surveillance studies before and following conjugate vaccination programmes to combat pneumococcal disease. Any bias introduced during sampling will affect downstream recovery and typing. Many variables exist for the method of collection and initial processing, which can make inter-laboratory or international comparisons of data complex. In February 2003, a World Health Organisation working group published a standard method for the detection of pneumococcal carriage for vaccine trials to reduce or eliminate variability. We sought to describe the variables associated with the sampling of S. pneumoniae from collection to storage in the context of the methods recommended by the WHO and those used in pneumococcal carriage studies since its publication. A search of published literature in the online PubMed database was performed on the 1st June 2012, to identify published studies that collected pneumococcal carriage isolates, conducted after the publication of the WHO standard method. After undertaking a systematic analysis of the literature, we show that a number of differences in pneumococcal sampling protocol continue to exist between studies since the WHO publication. The majority of studies sample from the nasopharynx, but the choice of swab and swab transport media is more variable between studies. At present there is insufficient experimental data that supports the optimal sensitivity of any standard method. This may have contributed to incomplete adoption of the primary stages of the WHO detection protocol, alongside pragmatic or logistical issues associated with study design. Consequently studies may not provide a true estimate of pneumococcal carriage. Optimal sampling of carriage could lead to improvements in downstream analysis and the evaluation of pneumococcal vaccine impact and extrapolation to pneumococcal disease control therefore

  3. Optical methods for microstructure determination of doped samples

    Science.gov (United States)

    Ciosek, Jerzy F.

    2008-12-01

    The optical methods to determine refractive index profile of layered materials are commonly used with spectroscopic ellipsometry or transmittance/reflectance spectrometry. Measurements of spectral reflection and transmission usually permit to characterize optical materials and determine their refractive index. However, it is possible to characterize of samples with dopants, impurities as well as defects using optical methods. Microstructures of a hydrogenated crystalline Si wafer and a layer of SiO2 - ZrO2 composition are investigated. The first sample is a Si(001):H Czochralski grown single crystalline wafer with 50 nm thick surface Si02 layer. Hydrogen dose implantation (D continue to be an important issue in microelectronic device and sensor fabrication. Hydrogen-implanted silicon (Si: H) has become a topic of remarkable interest, mostly because of the potential of implantation-induced platelets and micro-cavities for the creation of gettering -active areas and for Si layer splitting. Oxygen precipitation and atmospheric impurity are analysed. The second sample is the layer of co-evaporated SiO2 and ZrO2 materials using simultaneously two electron beam guns in reactive evaporation methods. The composition structure was investigated by X-Ray photoelectron spectroscopy (XPS), and spectroscopic ellipsometry methods. A non-uniformity and composition of layer are analysed using average density method.

  4. Transuranic waste characterization sampling and analysis methods manual. Revision 1

    International Nuclear Information System (INIS)

    Suermann, J.F.

    1996-04-01

    This Methods Manual provides a unified source of information on the sampling and analytical techniques that enable Department of Energy (DOE) facilities to comply with the requirements established in the current revision of the Transuranic Waste Characterization Quality Assurance Program Plan (QAPP) for the Waste Isolation Pilot Plant (WIPP) Transuranic (TRU) Waste Characterization Program (the Program) and the WIPP Waste Analysis Plan. This Methods Manual includes all of the testing, sampling, and analytical methodologies accepted by DOE for use in implementing the Program requirements specified in the QAPP and the WIPP Waste Analysis Plan. The procedures in this Methods Manual are comprehensive and detailed and are designed to provide the necessary guidance for the preparation of site-specific procedures. With some analytical methods, such as Gas Chromatography/Mass Spectrometry, the Methods Manual procedures may be used directly. With other methods, such as nondestructive characterization, the Methods Manual provides guidance rather than a step-by-step procedure. Sites must meet all of the specified quality control requirements of the applicable procedure. Each DOE site must document the details of the procedures it will use and demonstrate the efficacy of such procedures to the Manager, National TRU Program Waste Characterization, during Waste Characterization and Certification audits

  5. Non-uniform sampling and wide range angular spectrum method

    International Nuclear Information System (INIS)

    Kim, Yong-Hae; Byun, Chun-Won; Oh, Himchan; Lee, JaeWon; Pi, Jae-Eun; Heon Kim, Gi; Lee, Myung-Lae; Ryu, Hojun; Chu, Hye-Yong; Hwang, Chi-Sun

    2014-01-01

    A novel method is proposed for simulating free space field propagation from a source plane to a destination plane that is applicable for both small and large propagation distances. The angular spectrum method (ASM) was widely used for simulating near field propagation, but it caused a numerical error when the propagation distance was large because of aliasing due to under sampling. Band limited ASM satisfied the Nyquist condition on sampling by limiting a bandwidth of a propagation field to avoid an aliasing error so that it could extend the applicable propagation distance of the ASM. However, the band limited ASM also made an error due to the decrease of an effective sampling number in a Fourier space when the propagation distance was large. In the proposed wide range ASM, we use a non-uniform sampling in a Fourier space to keep a constant effective sampling number even though the propagation distance is large. As a result, the wide range ASM can produce simulation results with high accuracy for both far and near field propagation. For non-paraxial wave propagation, we applied the wide range ASM to a shifted destination plane as well. (paper)

  6. Standard methods for sampling freshwater fishes: Opportunities for international collaboration

    Science.gov (United States)

    Bonar, Scott A.; Mercado-Silva, Norman; Hubert, Wayne A.; Beard, Douglas; Dave, Göran; Kubečka, Jan; Graeb, Brian D. S.; Lester, Nigel P.; Porath, Mark T.; Winfield, Ian J.

    2017-01-01

    With publication of Standard Methods for Sampling North American Freshwater Fishes in 2009, the American Fisheries Society (AFS) recommended standard procedures for North America. To explore interest in standardizing at intercontinental scales, a symposium attended by international specialists in freshwater fish sampling was convened at the 145th Annual AFS Meeting in Portland, Oregon, in August 2015. Participants represented all continents except Australia and Antarctica and were employed by state and federal agencies, universities, nongovernmental organizations, and consulting businesses. Currently, standardization is practiced mostly in North America and Europe. Participants described how standardization has been important for management of long-term data sets, promoting fundamental scientific understanding, and assessing efficacy of large spatial scale management strategies. Academics indicated that standardization has been useful in fisheries education because time previously used to teach how sampling methods are developed is now more devoted to diagnosis and treatment of problem fish communities. Researchers reported that standardization allowed increased sample size for method validation and calibration. Group consensus was to retain continental standards where they currently exist but to further explore international and intercontinental standardization, specifically identifying where synergies and bridges exist, and identify means to collaborate with scientists where standardization is limited but interest and need occur.

  7. A novel method for fission product noble gas sampling

    International Nuclear Information System (INIS)

    Jain, S.K.; Prakash, Vivek; Singh, G.K.; Vinay, Kr.; Awsthi, A.; Bihari, K.; Joyson, R.; Manu, K.; Gupta, Ashok

    2008-01-01

    Noble gases occur to some extent in the Earth's atmosphere, but the concentrations of all but argon are exceedingly low. Argon is plentiful, constituting almost 1 % of the air. Fission Product Noble Gases (FPNG) are produced by nuclear fission and large parts of FPNG is produced in Nuclear reactions. FPNG are b-j emitters and contributing significantly in public dose. During normal operation of reactor release of FPNG is negligible but its release increases in case of fuel failure. Xenon, a member of FPNG family helps in identification of fuel failure and its extent in PHWRs. Due to above reasons it becomes necessary to assess the FPNG release during operation of NPPs. Presently used methodology of assessment of FPNG, at almost all power stations is Computer based gamma ray spectrometry. This provides fission product Noble gases nuclide identification through peak search of spectra. The air sample for the same is collected by grab sampling method, which has inherent disadvantages. An alternate method was developed at Rajasthan Atomic Power Station (RAPS) - 3 and 4 for assessment of FPNG, which uses adsorption phenomena for collection of air samples. This report presents details of sampling method for FPNG and noble gases in different systems of Nuclear Power Plant. (author)

  8. Correcting for Systematic Bias in Sample Estimates of Population Variances: Why Do We Divide by n-1?

    Science.gov (United States)

    Mittag, Kathleen Cage

    An important topic presented in introductory statistics courses is the estimation of population parameters using samples. Students learn that when estimating population variances using sample data, we always get an underestimate of the population variance if we divide by n rather than n-1. One implication of this correction is that the degree of…

  9. Analytic continuation of quantum Monte Carlo data. Stochastic sampling method

    Energy Technology Data Exchange (ETDEWEB)

    Ghanem, Khaldoon; Koch, Erik [Institute for Advanced Simulation, Forschungszentrum Juelich, 52425 Juelich (Germany)

    2016-07-01

    We apply Bayesian inference to the analytic continuation of quantum Monte Carlo (QMC) data from the imaginary axis to the real axis. Demanding a proper functional Bayesian formulation of any analytic continuation method leads naturally to the stochastic sampling method (StochS) as the Bayesian method with the simplest prior, while it excludes the maximum entropy method and Tikhonov regularization. We present a new efficient algorithm for performing StochS that reduces computational times by orders of magnitude in comparison to earlier StochS methods. We apply the new algorithm to a wide variety of typical test cases: spectral functions and susceptibilities from DMFT and lattice QMC calculations. Results show that StochS performs well and is able to resolve sharp features in the spectrum.

  10. Nonequilibrium Kondo effect by the equilibrium numerical renormalization group method: The hybrid Anderson model subject to a finite spin bias

    Science.gov (United States)

    Fang, Tie-Feng; Guo, Ai-Min; Sun, Qing-Feng

    2018-06-01

    We investigate Kondo correlations in a quantum dot with normal and superconducting electrodes, where a spin bias voltage is applied across the device and the local interaction U is either attractive or repulsive. When the spin current is blockaded in the large-gap regime, this nonequilibrium strongly correlated problem maps into an equilibrium model solvable by the numerical renormalization group method. The Kondo spectra with characteristic splitting due to the nonequilibrium spin accumulation are thus obtained at high precision. It is shown that while the bias-induced decoherence of the spin Kondo effect is partially compensated by the superconductivity, the charge Kondo effect is enhanced out of equilibrium and undergoes an additional splitting by the superconducting proximity effect, yielding four Kondo peaks in the local spectral density. In the charge Kondo regime, we find a universal scaling of charge conductance in this hybrid device under different spin biases. The universal conductance as a function of the coupling to the superconducting lead is peaked at and hence directly measures the Kondo temperature. Our results are of direct relevance to recent experiments realizing a negative-U charge Kondo effect in hybrid oxide quantum dots [Nat. Commun. 8, 395 (2017), 10.1038/s41467-017-00495-7].

  11. An Improved Dynamical Downscaling Method with GCM Bias Corrections and Its Validation with 30 Years of Climate Simulations

    KAUST Repository

    Xu, Zhongfeng

    2012-09-01

    An improved dynamical downscaling method (IDD) with general circulation model (GCM) bias corrections is developed and assessed over North America. A set of regional climate simulations is performed with the Weather Research and Forecasting Model (WRF) version 3.3 embedded in the National Center for Atmospheric Research\\'s (NCAR\\'s) Community Atmosphere Model (CAM). The GCM climatological means and the amplitudes of interannual variations are adjusted based on the National Centers for Environmental Prediction (NCEP)-NCAR global reanalysis products (NNRP) before using them to drive WRF. In this study, the WRF downscaling experiments are identical except the initial and lateral boundary conditions derived from the NNRP, original GCM output, and bias-corrected GCM output, respectively. The analysis finds that the IDD greatly improves the downscaled climate in both climatological means and extreme events relative to the traditional dynamical downscaling approach (TDD). The errors of downscaled climatological mean air temperature, geopotential height, wind vector, moisture, and precipitation are greatly reduced when the GCM bias corrections are applied. In the meantime, IDD also improves the downscaled extreme events characterized by the reduced errors in 2-yr return levels of surface air temperature and precipitation. In comparison with TDD, IDD is also able to produce a more realistic probability distribution in summer daily maximum temperature over the central U.S.-Canada region as well as in summer and winter daily precipitation over the middle and eastern United States. © 2012 American Meteorological Society.

  12. Entropic sampling in the path integral Monte Carlo method

    International Nuclear Information System (INIS)

    Vorontsov-Velyaminov, P N; Lyubartsev, A P

    2003-01-01

    We have extended the entropic sampling Monte Carlo method to the case of path integral representation of a quantum system. A two-dimensional density of states is introduced into path integral form of the quantum canonical partition function. Entropic sampling technique within the algorithm suggested recently by Wang and Landau (Wang F and Landau D P 2001 Phys. Rev. Lett. 86 2050) is then applied to calculate the corresponding entropy distribution. A three-dimensional quantum oscillator is considered as an example. Canonical distributions for a wide range of temperatures are obtained in a single simulation run, and exact data for the energy are reproduced

  13. Rapid screening method for plutonium in mixed waste samples

    International Nuclear Information System (INIS)

    Somers, W.; Culp, T.; Miller, R.

    1987-01-01

    A waste stream sampling program was undertaken to determine those waste streams which contained hazardous constituents, and would therefore be regulated as a hazardous waste under the Resource Conservation and Recovery Act. The waste streams also had the potential of containing radioactive material, either plutonium, americium, or depleted uranium. Because of the potential for contamination with radioactive material, a method of rapidly screening the liquid samples for radioactive material was required. A counting technique was devised to count a small aliquot of a sample, determine plutonium concentration, and allow the sample to be shipped the same day they were collected. This technique utilized the low energy photons (x-rays) that accompany α decay. This direct, non-destructive x-ray analysis was applied to quantitatively determine Pu-239 concentrations in industrial samples. Samples contained a Pu-239, Am-241 mixture; the ratio and/or concentrations of these two radionuclides was not constant. A computer program was designed and implemented to calculate Pu-239 activity and concentration (g/ml) using the 59.5 keV Am-241 peak to determine Am-241's contribution to the 17 keV region. Am's contribution was subtracted, yielding net counts in the 17 keV region due to Pu. 2 figs., 1 tab

  14. A method for sampling microbial aerosols using high altitude balloons.

    Science.gov (United States)

    Bryan, N C; Stewart, M; Granger, D; Guzik, T G; Christner, B C

    2014-12-01

    Owing to the challenges posed to microbial aerosol sampling at high altitudes, very little is known about the abundance, diversity, and extent of microbial taxa in the Earth-atmosphere system. To directly address this knowledge gap, we designed, constructed, and tested a system that passively samples aerosols during ascent through the atmosphere while tethered to a helium-filled latex sounding balloon. The sampling payload is ~ 2.7 kg and comprised of an electronics box and three sampling chambers (one serving as a procedural control). Each chamber is sealed with retractable doors that can be commanded to open and close at designated altitudes. The payload is deployed together with radio beacons that transmit GPS coordinates (latitude, longitude and altitude) in real time for tracking and recovery. A cut mechanism separates the payload string from the balloon at any desired altitude, returning all equipment safely to the ground on a parachute. When the chambers are opened, aerosol sampling is performed using the Rotorod® collection method (40 rods per chamber), with each rod passing through 0.035 m3 per km of altitude sampled. Based on quality control measurements, the collection of ~ 100 cells rod(-1) provided a 3-sigma confidence level of detection. The payload system described can be mated with any type of balloon platform and provides a tool for characterizing the vertical distribution of microorganisms in the troposphere and stratosphere. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Sample selection may bias the outcome of an adolescent mental health survey: results from a five-year follow-up of 4171 adolescents.

    Science.gov (United States)

    Kekkonen, V; Kivimäki, P; Valtonen, H; Hintikka, J; Tolmunen, T; Lehto, S M; Laukkanen, E

    2015-02-01

    The representativeness of the data is one of the main issues in evaluating the significance of research findings. Dropping out is common in adolescent mental health research, and may distort the results. Nevertheless, very little is known about the types of systematic bias that may affect studies in a) the informed consent phase and b) later in follow-up phases. The authors addressed this gap in knowledge in a five-year follow-up study on a sample of adolescents aged 13-18 years. The data were collected using self-report questionnaires. The baseline sample consisted of 4171 adolescents, 1827 (43.8%) of whom gave consent to be contacted for a follow-up survey, but only 797 (19.1%) participated in the follow-up. Binary logistic regression models were used to explain the participation. Young age, female gender, a high number of hobbies, good performance at school in the native language and general subjects, family disintegration such as divorce, high parental employment, and symptoms of depression and anxiety were associated with both consent and participation. However, the effect of mental health aspects was smaller than the effect of age and gender. This study confirmed the possibility of systematic selection bias by adolescents' sociodemographic characteristics. The representativeness of the study sample might have been improved by more intense recruitment strategies. Copyright © 2014 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  16. A Method for Choosing the Best Samples for Mars Sample Return.

    Science.gov (United States)

    Gordon, Peter R; Sephton, Mark A

    2018-05-01

    Success of a future Mars Sample Return mission will depend on the correct choice of samples. Pyrolysis-FTIR can be employed as a triage instrument for Mars Sample Return. The technique can thermally dissociate minerals and organic matter for detection. Identification of certain mineral types can determine the habitability of the depositional environment, past or present, while detection of organic matter may suggest past or present habitation. In Mars' history, the Theiikian era represents an attractive target for life search missions and the acquisition of samples. The acidic and increasingly dry Theiikian may have been habitable and followed a lengthy neutral and wet period in Mars' history during which life could have originated and proliferated to achieve relatively abundant levels of biomass with a wide distribution. Moreover, the sulfate minerals produced in the Theiikian are also known to be good preservers of organic matter. We have used pyrolysis-FTIR and samples from a Mars analog ferrous acid stream with a thriving ecosystem to test the triage concept. Pyrolysis-FTIR identified those samples with the greatest probability of habitability and habitation. A three-tier scoring system was developed based on the detection of (i) organic signals, (ii) carbon dioxide and water, and (iii) sulfur dioxide. The presence of each component was given a score of A, B, or C depending on whether the substance had been detected, tentatively detected, or not detected, respectively. Single-step (for greatest possible sensitivity) or multistep (for more diagnostic data) pyrolysis-FTIR methods informed the assignments. The system allowed the highest-priority samples to be categorized as AAA (or A*AA if the organic signal was complex), while the lowest-priority samples could be categorized as CCC. Our methods provide a mechanism with which to rank samples and identify those that should take the highest priority for return to Earth during a Mars Sample Return mission. Key Words

  17. Reducing bias in population and landscape genetic inferences: the effects of sampling related individuals and multiple life stages.

    Science.gov (United States)

    Peterman, William; Brocato, Emily R; Semlitsch, Raymond D; Eggert, Lori S

    2016-01-01

    In population or landscape genetics studies, an unbiased sampling scheme is essential for generating accurate results, but logistics may lead to deviations from the sample design. Such deviations may come in the form of sampling multiple life stages. Presently, it is largely unknown what effect sampling different life stages can have on population or landscape genetic inference, or how mixing life stages can affect the parameters being measured. Additionally, the removal of siblings from a data set is considered best-practice, but direct comparisons of inferences made with and without siblings are limited. In this study, we sampled embryos, larvae, and adult Ambystoma maculatum from five ponds in Missouri, and analyzed them at 15 microsatellite loci. We calculated allelic richness, heterozygosity and effective population sizes for each life stage at each pond and tested for genetic differentiation (F ST and D C ) and isolation-by-distance (IBD) among ponds. We tested for differences in each of these measures between life stages, and in a pooled population of all life stages. All calculations were done with and without sibling pairs to assess the effect of sibling removal. We also assessed the effect of reducing the number of microsatellites used to make inference. No statistically significant differences were found among ponds or life stages for any of the population genetic measures, but patterns of IBD differed among life stages. There was significant IBD when using adult samples, but tests using embryos, larvae, or a combination of the three life stages were not significant. We found that increasing the ratio of larval or embryo samples in the analysis of genetic distance weakened the IBD relationship, and when using D C , the IBD was no longer significant when larvae and embryos exceeded 60% of the population sample. Further, power to detect an IBD relationship was reduced when fewer microsatellites were used in the analysis.

  18. Reducing bias in population and landscape genetic inferences: the effects of sampling related individuals and multiple life stages

    Directory of Open Access Journals (Sweden)

    William Peterman

    2016-03-01

    Full Text Available In population or landscape genetics studies, an unbiased sampling scheme is essential for generating accurate results, but logistics may lead to deviations from the sample design. Such deviations may come in the form of sampling multiple life stages. Presently, it is largely unknown what effect sampling different life stages can have on population or landscape genetic inference, or how mixing life stages can affect the parameters being measured. Additionally, the removal of siblings from a data set is considered best-practice, but direct comparisons of inferences made with and without siblings are limited. In this study, we sampled embryos, larvae, and adult Ambystoma maculatum from five ponds in Missouri, and analyzed them at 15 microsatellite loci. We calculated allelic richness, heterozygosity and effective population sizes for each life stage at each pond and tested for genetic differentiation (FST and DC and isolation-by-distance (IBD among ponds. We tested for differences in each of these measures between life stages, and in a pooled population of all life stages. All calculations were done with and without sibling pairs to assess the effect of sibling removal. We also assessed the effect of reducing the number of microsatellites used to make inference. No statistically significant differences were found among ponds or life stages for any of the population genetic measures, but patterns of IBD differed among life stages. There was significant IBD when using adult samples, but tests using embryos, larvae, or a combination of the three life stages were not significant. We found that increasing the ratio of larval or embryo samples in the analysis of genetic distance weakened the IBD relationship, and when using DC, the IBD was no longer significant when larvae and embryos exceeded 60% of the population sample. Further, power to detect an IBD relationship was reduced when fewer microsatellites were used in the analysis.

  19. Empirical method for matrix effects correction in liquid samples

    International Nuclear Information System (INIS)

    Vigoda de Leyt, Dora; Vazquez, Cristina

    1987-01-01

    A simple method for the determination of Cr, Ni and Mo in stainless steels is presented. In order to minimize the matrix effects, the conditions of liquid system to dissolve stainless steels chips has been developed. Pure element solutions were used as standards. Preparation of synthetic solutions with all the elements of steel and also mathematic corrections are avoided. It results in a simple chemical operation which simplifies the method of analysis. The variance analysis of the results obtained with steel samples show that the three elements may be determined from the comparison with the analytical curves obtained with the pure elements if the same parameters in the calibration curves are used. The accuracy and the precision were checked against other techniques using the British Chemical Standards of the Bureau of Anlysed Samples Ltd. (England). (M.E.L.) [es

  20. Harmonisation of microbial sampling and testing methods for distillate fuels

    Energy Technology Data Exchange (ETDEWEB)

    Hill, G.C.; Hill, E.C. [ECHA Microbiology Ltd., Cardiff (United Kingdom)

    1995-05-01

    Increased incidence of microbial infection in distillate fuels has led to a demand for organisations such as the Institute of Petroleum to propose standards for microbiological quality, based on numbers of viable microbial colony forming units. Variations in quality requirements, and in the spoilage significance of contaminating microbes plus a tendency for temporal and spatial changes in the distribution of microbes, makes such standards difficult to implement. The problem is compounded by a diversity in the procedures employed for sampling and testing for microbial contamination and in the interpretation of the data obtained. The following paper reviews these problems and describes the efforts of The Institute of Petroleum Microbiology Fuels Group to address these issues and in particular to bring about harmonisation of sampling and testing methods. The benefits and drawbacks of available test methods, both laboratory based and on-site, are discussed.

  1. A direct sampling method to an inverse medium scattering problem

    KAUST Repository

    Ito, Kazufumi

    2012-01-10

    In this work we present a novel sampling method for time harmonic inverse medium scattering problems. It provides a simple tool to directly estimate the shape of the unknown scatterers (inhomogeneous media), and it is applicable even when the measured data are only available for one or two incident directions. A mathematical derivation is provided for its validation. Two- and three-dimensional numerical simulations are presented, which show that the method is accurate even with a few sets of scattered field data, computationally efficient, and very robust with respect to noises in the data. © 2012 IOP Publishing Ltd.

  2. Rock sampling. [method for controlling particle size distribution

    Science.gov (United States)

    Blum, P. (Inventor)

    1971-01-01

    A method for sampling rock and other brittle materials and for controlling resultant particle sizes is described. The method involves cutting grooves in the rock surface to provide a grouping of parallel ridges and subsequently machining the ridges to provide a powder specimen. The machining step may comprise milling, drilling, lathe cutting or the like; but a planing step is advantageous. Control of the particle size distribution is effected primarily by changing the height and width of these ridges. This control exceeds that obtainable by conventional grinding.

  3. Characterization of hazardous waste sites: a methods manual. Volume 2. Available sampling methods (second edition)

    International Nuclear Information System (INIS)

    Ford, P.J.; Turina, P.J.; Seely, D.E.

    1984-12-01

    Investigations at hazardous waste sites and sites of chemical spills often require on-site measurements and sampling activities to assess the type and extent of contamination. This document is a compilation of sampling methods and materials suitable to address most needs that arise during routine waste site and hazardous spill investigations. The sampling methods presented in this document are compiled by media, and were selected on the basis of practicality, economics, representativeness, compatability with analytical considerations, and safety, as well as other criteria. In addition to sampling procedures, sample handling and shipping, chain-of-custody procedures, instrument certification, equipment fabrication, and equipment decontamination procedures are described. Sampling methods for soil, sludges, sediments, and bulk materials cover the solids medium. Ten methods are detailed for surface waters, groundwater and containerized liquids; twelve are presented for ambient air, soil gases and vapors, and headspace gases. A brief discussion of ionizing radiation survey instruments is also provided

  4. The experience sampling method: Investigating students' affective experience

    Science.gov (United States)

    Nissen, Jayson M.; Stetzer, MacKenzie R.; Shemwell, Jonathan T.

    2013-01-01

    Improving non-cognitive outcomes such as attitudes, efficacy, and persistence in physics courses is an important goal of physics education. This investigation implemented an in-the-moment surveying technique called the Experience Sampling Method (ESM) [1] to measure students' affective experience in physics. Measurements included: self-efficacy, cognitive efficiency, activation, intrinsic motivation, and affect. Data are presented that show contrasts in students' experiences (e.g., in physics vs. non-physics courses).

  5. Test of methods for retrospective activity size distribution determination from filter samples

    International Nuclear Information System (INIS)

    Meisenberg, Oliver; Tschiersch, Jochen

    2015-01-01

    Determining the activity size distribution of radioactive aerosol particles requires sophisticated and heavy equipment, which makes measurements at large number of sites difficult and expensive. Therefore three methods for a retrospective determination of size distributions from aerosol filter samples in the laboratory were tested for their applicability. Extraction into a carrier liquid with subsequent nebulisation showed size distributions with a slight but correctable bias towards larger diameters compared with the original size distribution. Yields in the order of magnitude of 1% could be achieved. Sonication-assisted extraction into a carrier liquid caused a coagulation mode to appear in the size distribution. Sonication-assisted extraction into the air did not show acceptable results due to small yields. The method of extraction into a carrier liquid without sonication was applied to aerosol samples from Chernobyl in order to calculate inhalation dose coefficients for 137 Cs based on the individual size distribution. The effective dose coefficient is about half of that calculated with a default reference size distribution. - Highlights: • Activity size distributions can be recovered after aerosol sampling on filters. • Extraction into a carrier liquid and subsequent nebulisation is appropriate. • This facilitates the determination of activity size distributions for individuals. • Size distributions from this method can be used for individual dose coefficients. • Dose coefficients were calculated for the workers at the new Chernobyl shelter

  6. Method for evaluation of radiative properties of glass samples

    Energy Technology Data Exchange (ETDEWEB)

    Mohelnikova, Jitka [Faculty of Civil Engineering, Brno University of Technology, Veveri 95, 602 00 Brno (Czech Republic)], E-mail: mohelnikova.j@fce.vutbr.cz

    2008-04-15

    The paper presents a simple calculation method which serves for an evaluation of radiative properties of window glasses. The method is based on a computer simulation model of the energy balance of a thermally insulated box with selected glass samples. A temperature profile of the air inside of the box with a glass sample exposed to affecting radiation was determined for defined boundary conditions. The spectral range of the radiation was considered in the interval between 280 and 2500 nm. This interval is adequate to the spectral range of solar radiation affecting windows in building facades. The air temperature rise within the box was determined in a response to the affecting radiation in the time between the beginning of the radiation exposition and the time of steady-state thermal conditions. The steady state temperature inside of the insulated box serves for the evaluation of the box energy balance and determination of the glass sample radiative properties. These properties are represented by glass characteristics as mean values of transmittance, reflectance and absorptance calculated for a defined spectral range. The data of the computer simulations were compared to experimental measurements on a real model of the insulated box. Results of both the calculations and measurements are in a good compliance. The method is recommended for preliminary evaluation of window glass radiative properties which serve as data for energy evaluation of buildings.

  7. A simple method to identify radiation and annealing biases that lead to worst-case CMOS static RAM postirradiation response

    International Nuclear Information System (INIS)

    Fleetwood, D.M.; Dressendorfer, P.V.

    1987-01-01

    The authors illustrate a simple method to identify bias conditions that lead to worst-case postirradiation speed and timing response for SRAMs. Switching cell states between radiation and anneal should lead to maximum speed and timing degradation for many hardened designs and technologies. The greatest SRAM cell imbalance is also established by these radiation and annealing conditions for the hardened and commercial parts that we have examined. These results should provide insight into the behavior of SRAMs during and after irradiation. The results should also be useful to establishing guidelines for integrated-circuit functionality testing, and SEU and dose-rate upset testing, after total-dose irradiation

  8. An Improved BeiDou-2 Satellite-Induced Code Bias Estimation Method

    Directory of Open Access Journals (Sweden)

    Jingyang Fu

    2018-04-01

    Full Text Available Different from GPS, GLONASS, GALILEO and BeiDou-3, it is confirmed that the code multipath bias (CMB, which originate from the satellite end and can be over 1 m, are commonly found in the code observations of BeiDou-2 (BDS IGSO and MEO satellites. In order to mitigate their adverse effects on absolute precise applications which use the code measurements, we propose in this paper an improved correction model to estimate the CMB. Different from the traditional model which considering the correction values are orbit-type dependent (estimating two sets of values for IGSO and MEO, respectively and modeling the CMB as a piecewise linear function with a elevation node separation of 10°, we estimate the corrections for each BDS IGSO + MEO satellite on one hand, and a denser elevation node separation of 5° is used to model the CMB variations on the other hand. Currently, the institutions such as IGS-MGEX operate over 120 stations which providing the daily BDS observations. These large amounts of data provide adequate support to refine the CMB estimation satellite by satellite in our improved model. One month BDS observations from MGEX are used for assessing the performance of the improved CMB model by means of precise point positioning (PPP. Experimental results show that for the satellites on the same orbit type, obvious differences can be found in the CMB at the same node and frequency. Results show that the new correction model can improve the wide-lane (WL ambiguity usage rate for WL fractional cycle bias estimation, shorten the WL and narrow-lane (NL time to first fix (TTFF in PPP ambiguity resolution (AR as well as improve the PPP positioning accuracy. With our improved correction model, the usage of WL ambiguity is increased from 94.1% to 96.0%, the WL and NL TTFF of PPP AR is shorten from 10.6 to 9.3 min, 67.9 to 63.3 min, respectively, compared with the traditional correction model. In addition, both the traditional and improved CMB model have

  9. Radiochemistry methods in DOE methods for evaluating environmental and waste management samples

    International Nuclear Information System (INIS)

    Fadeff, S.K.; Goheen, S.C.

    1994-08-01

    Current standard sources of radiochemistry methods are often inappropriate for use in evaluating US Department of Energy environmental and waste management (DOE/EW) samples. Examples of current sources include EPA, ASTM, Standard Methods for the Examination of Water and Wastewater and HASL-300. Applicability of these methods is limited to specific matrices (usually water), radiation levels (usually environmental levels), and analytes (limited number). Radiochemistry methods in DOE Methods for Evaluating Environmental and Waste Management Samples (DOE Methods) attempt to fill the applicability gap that exists between standard methods and those needed for DOE/EM activities. The Radiochemistry chapter in DOE Methods includes an ''analysis and reporting'' guidance section as well as radiochemistry methods. A basis for identifying the DOE/EM radiochemistry needs is discussed. Within this needs framework, the applicability of standard methods and targeted new methods is identified. Sources of new methods (consolidated methods from DOE laboratories and submissions from individuals) and the methods review process will be discussed. The processes involved in generating consolidated methods add editing individually submitted methods will be compared. DOE Methods is a living document and continues to expand by adding various kinds of methods. Radiochemistry methods are highlighted in this paper. DOE Methods is intended to be a resource for methods applicable to DOE/EM problems. Although it is intended to support DOE, the guidance and methods are not necessarily exclusive to DOE. The document is available at no cost through the Laboratory Management Division of DOE, Office of Technology Development

  10. Evaluation of statistical methods for quantifying fractal scaling in water-quality time series with irregular sampling

    Directory of Open Access Journals (Sweden)

    Q. Zhang

    2018-02-01

    Full Text Available River water-quality time series often exhibit fractal scaling, which here refers to autocorrelation that decays as a power law over some range of scales. Fractal scaling presents challenges to the identification of deterministic trends because (1 fractal scaling has the potential to lead to false inference about the statistical significance of trends and (2 the abundance of irregularly spaced data in water-quality monitoring networks complicates efforts to quantify fractal scaling. Traditional methods for estimating fractal scaling – in the form of spectral slope (β or other equivalent scaling parameters (e.g., Hurst exponent – are generally inapplicable to irregularly sampled data. Here we consider two types of estimation approaches for irregularly sampled data and evaluate their performance using synthetic time series. These time series were generated such that (1 they exhibit a wide range of prescribed fractal scaling behaviors, ranging from white noise (β  =  0 to Brown noise (β  =  2 and (2 their sampling gap intervals mimic the sampling irregularity (as quantified by both the skewness and mean of gap-interval lengths in real water-quality data. The results suggest that none of the existing methods fully account for the effects of sampling irregularity on β estimation. First, the results illustrate the danger of using interpolation for gap filling when examining autocorrelation, as the interpolation methods consistently underestimate or overestimate β under a wide range of prescribed β values and gap distributions. Second, the widely used Lomb–Scargle spectral method also consistently underestimates β. A previously published modified form, using only the lowest 5 % of the frequencies for spectral slope estimation, has very poor precision, although the overall bias is small. Third, a recent wavelet-based method, coupled with an aliasing filter, generally has the smallest bias and root-mean-squared error among

  11. Evaluation of statistical methods for quantifying fractal scaling in water-quality time series with irregular sampling

    Science.gov (United States)

    Zhang, Qian; Harman, Ciaran J.; Kirchner, James W.

    2018-02-01

    River water-quality time series often exhibit fractal scaling, which here refers to autocorrelation that decays as a power law over some range of scales. Fractal scaling presents challenges to the identification of deterministic trends because (1) fractal scaling has the potential to lead to false inference about the statistical significance of trends and (2) the abundance of irregularly spaced data in water-quality monitoring networks complicates efforts to quantify fractal scaling. Traditional methods for estimating fractal scaling - in the form of spectral slope (β) or other equivalent scaling parameters (e.g., Hurst exponent) - are generally inapplicable to irregularly sampled data. Here we consider two types of estimation approaches for irregularly sampled data and evaluate their performance using synthetic time series. These time series were generated such that (1) they exhibit a wide range of prescribed fractal scaling behaviors, ranging from white noise (β = 0) to Brown noise (β = 2) and (2) their sampling gap intervals mimic the sampling irregularity (as quantified by both the skewness and mean of gap-interval lengths) in real water-quality data. The results suggest that none of the existing methods fully account for the effects of sampling irregularity on β estimation. First, the results illustrate the danger of using interpolation for gap filling when examining autocorrelation, as the interpolation methods consistently underestimate or overestimate β under a wide range of prescribed β values and gap distributions. Second, the widely used Lomb-Scargle spectral method also consistently underestimates β. A previously published modified form, using only the lowest 5 % of the frequencies for spectral slope estimation, has very poor precision, although the overall bias is small. Third, a recent wavelet-based method, coupled with an aliasing filter, generally has the smallest bias and root-mean-squared error among all methods for a wide range of

  12. Application of WSP method in analysis of environmental samples

    International Nuclear Information System (INIS)

    Stacho, M.; Slugen, V.; Hinca, R.; Sojak, S.; Krnac, S.

    2014-01-01

    Detection of activity in natural samples is specific especially because of its low level and high background interferences. Reduction of background interferences could be reached using low background chamber. Measurement geometry in shape of Marinelli beaker is commonly used according to low level of activity in natural samples. The Peak Net Area (PNA) method is the world-wide accepted technique for analysis of gamma-ray spectra. It is based on the net area calculation of the full energy peak, therefore, it takes into account only a fraction of measured gamma-ray spectrum. On the other hand, the Whole Spectrum Processing (WSP) approach to the gamma analysis makes possible to use entire information being in the spectrum. This significantly raises efficiency and improves energy resolution of the analysis. A principal step for the WSP application is building up the suitable response operator. Problems are put in an appearance when suitable standard calibration sources are unavailable. It may be occurred in the case of large volume samples and/or in the analysis of high energy range. Combined experimental and mathematical calibration may be a suitable solution. Many different detectors have been used to register the gamma ray and its energy. HPGe detectors produce the highest resolution commonly available today. Therefore they are they the most often used detectors in natural samples activity analysis. Scintillation detectors analysed using PNA method could be also used in simple cases, but for complicated spectra are practically inapplicable. WSP approach improves resolution of scintillation detectors and expands their applicability. WSP method allowed significant improvement of the energetic resolution and separation of "1"3"7Cs 661 keV peak from "2"1"4Bi 609 keV peak. At the other hand the statistical fluctuations in the lower part of the spectrum highlighted by background subtraction causes that this part is still not reliably analyzable. (authors)

  13. Analytical Method to Estimate the Complex Permittivity of Oil Samples

    Directory of Open Access Journals (Sweden)

    Lijuan Su

    2018-03-01

    Full Text Available In this paper, an analytical method to estimate the complex dielectric constant of liquids is presented. The method is based on the measurement of the transmission coefficient in an embedded microstrip line loaded with a complementary split ring resonator (CSRR, which is etched in the ground plane. From this response, the dielectric constant and loss tangent of the liquid under test (LUT can be extracted, provided that the CSRR is surrounded by such LUT, and the liquid level extends beyond the region where the electromagnetic fields generated by the CSRR are present. For that purpose, a liquid container acting as a pool is added to the structure. The main advantage of this method, which is validated from the measurement of the complex dielectric constant of olive and castor oil, is that reference samples for calibration are not required.

  14. Method for fractional solid-waste sampling and chemical analysis

    DEFF Research Database (Denmark)

    Riber, Christian; Rodushkin, I.; Spliid, Henrik

    2007-01-01

    four subsampling methods and five digestion methods, paying attention to the heterogeneity and the material characteristics of the waste fractions, it was possible to determine 61 substances with low detection limits, reasonable variance, and high accuracy. For most of the substances of environmental...... of variance (20-85% of the overall variation). Only by increasing the sample size significantly can this variance be reduced. The accuracy and short-term reproducibility of the chemical characterization were good, as determined by the analysis of several relevant certified reference materials. Typically, six...... to eight different certified reference materials representing a range of concentrations levels and matrix characteristics were included. Based on the documentation provided, the methods introduced were considered satisfactory for characterization of the chemical composition of waste-material fractions...

  15. Comparison between powder and slices diffraction methods in teeth samples

    Energy Technology Data Exchange (ETDEWEB)

    Colaco, Marcos V.; Barroso, Regina C. [Universidade do Estado do Rio de Janeiro (IF/UERJ), RJ (Brazil). Inst. de Fisica. Dept. de Fisica Aplicada; Porto, Isabel M. [Universidade Estadual de Campinas (FOP/UNICAMP), Piracicaba, SP (Brazil). Fac. de Odontologia. Dept. de Morfologia; Gerlach, Raquel F. [Universidade de Sao Paulo (FORP/USP), Rieirao Preto, SP (Brazil). Fac. de Odontologia. Dept. de Morfologia, Estomatologia e Fisiologia; Costa, Fanny N. [Coordenacao dos Programas de Pos-Graduacao de Engenharia (LIN/COPPE/UFRJ), RJ (Brazil). Lab. de Instrumentacao Nuclear

    2011-07-01

    Propose different methods to obtain crystallographic information about biological materials are important since powder method is a nondestructive method. Slices are an approximation of what would be an in vivo analysis. Effects of samples preparation cause differences in scattering profiles compared with powder method. The main inorganic component of bones and teeth is a calcium phosphate mineral whose structure closely resembles hydroxyapatite (HAp). The hexagonal symmetry, however, seems to work well with the powder diffraction data, and the crystal structure of HAp is usually described in space group P63/m. Were analyzed ten third molar teeth. Five teeth were separated in enamel, detin and circumpulpal detin powder and five in slices. All the scattering profile measurements were carried out at the X-ray diffraction beamline (XRD1) at the National Synchrotron Light Laboratory - LNLS, Campinas, Brazil. The LNLS synchrotron light source is composed of a 1.37 GeV electron storage ring, delivering approximately 4x10{sup -1}0 photons/s at 8 keV. A double-crystal Si(111) pre-monochromator, upstream of the beamline, was used to select a small energy bandwidth at 11 keV . Scattering signatures were obtained at intervals of 0.04 deg for angles from 24 deg to 52 deg. The human enamel experimental crystallite size obtained in this work were 30(3)nm (112 reflection) and 30(3)nm (300 reflection). These values were obtained from measurements of powdered enamel. When comparing the slice obtained 58(8)nm (112 reflection) and 37(7)nm (300 reflection) enamel diffraction patterns with those generated by the powder specimens, a few differences emerge. This work shows differences between powder and slices methods, separating characteristics of sample of the method's influence. (author)

  16. Comparison between powder and slices diffraction methods in teeth samples

    International Nuclear Information System (INIS)

    Colaco, Marcos V.; Barroso, Regina C.; Porto, Isabel M.; Gerlach, Raquel F.; Costa, Fanny N.

    2011-01-01

    Propose different methods to obtain crystallographic information about biological materials are important since powder method is a nondestructive method. Slices are an approximation of what would be an in vivo analysis. Effects of samples preparation cause differences in scattering profiles compared with powder method. The main inorganic component of bones and teeth is a calcium phosphate mineral whose structure closely resembles hydroxyapatite (HAp). The hexagonal symmetry, however, seems to work well with the powder diffraction data, and the crystal structure of HAp is usually described in space group P63/m. Were analyzed ten third molar teeth. Five teeth were separated in enamel, detin and circumpulpal detin powder and five in slices. All the scattering profile measurements were carried out at the X-ray diffraction beamline (XRD1) at the National Synchrotron Light Laboratory - LNLS, Campinas, Brazil. The LNLS synchrotron light source is composed of a 1.37 GeV electron storage ring, delivering approximately 4x10 -1 0 photons/s at 8 keV. A double-crystal Si(111) pre-monochromator, upstream of the beamline, was used to select a small energy bandwidth at 11 keV . Scattering signatures were obtained at intervals of 0.04 deg for angles from 24 deg to 52 deg. The human enamel experimental crystallite size obtained in this work were 30(3)nm (112 reflection) and 30(3)nm (300 reflection). These values were obtained from measurements of powdered enamel. When comparing the slice obtained 58(8)nm (112 reflection) and 37(7)nm (300 reflection) enamel diffraction patterns with those generated by the powder specimens, a few differences emerge. This work shows differences between powder and slices methods, separating characteristics of sample of the method's influence. (author)

  17. Path integral methods for primordial density perturbations - sampling of constrained Gaussian random fields

    International Nuclear Information System (INIS)

    Bertschinger, E.

    1987-01-01

    Path integrals may be used to describe the statistical properties of a random field such as the primordial density perturbation field. In this framework the probability distribution is given for a Gaussian random field subjected to constraints such as the presence of a protovoid or supercluster at a specific location in the initial conditions. An algorithm has been constructed for generating samples of a constrained Gaussian random field on a lattice using Monte Carlo techniques. The method makes possible a systematic study of the density field around peaks or other constrained regions in the biased galaxy formation scenario, and it is effective for generating initial conditions for N-body simulations with rare objects in the computational volume. 21 references

  18. Developing a Method for Resolving NOx Emission Inventory Biases Using Discrete Kalman Filter Inversion, Direct Sensitivities, and Satellite-Based Columns

    Science.gov (United States)

    An inverse method was developed to integrate satellite observations of atmospheric pollutant column concentrations and direct sensitivities predicted by a regional air quality model in order to discern biases in the emissions of the pollutant precursors.

  19. Radiochemistry methods in DOE Methods for Evaluating Environmental and Waste Management Samples: Addressing new challenges

    International Nuclear Information System (INIS)

    Fadeff, S.K.; Goheen, S.C.; Riley, R.G.

    1994-01-01

    Radiochemistry methods in Department of Energy Methods for Evaluating Environmental and Waste Management Samples (DOE Methods) add to the repertoire of other standard methods in support of U.S. Department of Energy environmental restoration and waste management (DOE/EM) radiochemical characterization activities. Current standard sources of radiochemistry methods are not always applicable for evaluating DOE/EM samples. Examples of current sources include those provided by the US Environmental Protection Agency, the American Society for Testing and Materials, Standard Methods for the Examination of Water and Wastewater, and Environmental Measurements Laboratory Procedures Manual (HASL-300). The applicability of these methods is generally limited to specific matrices (usually water), low-level radioactive samples, and a limited number of analytes. DOE Methods complements these current standard methods by addressing the complexities of EM characterization needs. The process for determining DOE/EM radiochemistry characterization needs is discussed. In this context of DOE/EM needs, the applicability of other sources of standard radiochemistry methods is defined, and gaps in methodology are identified. Current methods in DOE Methods and the EM characterization needs they address are discussed. Sources of new methods and the methods incorporation process are discussed. The means for individuals to participate in (1) identification of DOE/EM needs, (2) the methods incorporation process, and (3) submission of new methods are identified

  20. A direct sampling method for inverse electromagnetic medium scattering

    KAUST Repository

    Ito, Kazufumi

    2013-09-01

    In this paper, we study the inverse electromagnetic medium scattering problem of estimating the support and shape of medium scatterers from scattered electric/magnetic near-field data. We shall develop a novel direct sampling method based on an analysis of electromagnetic scattering and the behavior of the fundamental solution. It is applicable to a few incident fields and needs only to compute inner products of the measured scattered field with the fundamental solutions located at sampling points. Hence, it is strictly direct, computationally very efficient and highly robust to the presence of data noise. Two- and three-dimensional numerical experiments indicate that it can provide reliable support estimates for multiple scatterers in the case of both exact and highly noisy data. © 2013 IOP Publishing Ltd.

  1. Monte Carlo burnup codes acceleration using the correlated sampling method

    International Nuclear Information System (INIS)

    Dieudonne, C.

    2013-01-01

    For several years, Monte Carlo burnup/depletion codes have appeared, which couple Monte Carlo codes to simulate the neutron transport to deterministic methods, which handle the medium depletion due to the neutron flux. Solving Boltzmann and Bateman equations in such a way allows to track fine 3-dimensional effects and to get rid of multi-group hypotheses done by deterministic solvers. The counterpart is the prohibitive calculation time due to the Monte Carlo solver called at each time step. In this document we present an original methodology to avoid the repetitive and time-expensive Monte Carlo simulations, and to replace them by perturbation calculations: indeed the different burnup steps may be seen as perturbations of the isotopic concentration of an initial Monte Carlo simulation. In a first time we will present this method, and provide details on the perturbative technique used, namely the correlated sampling. In a second time we develop a theoretical model to study the features of the correlated sampling method to understand its effects on depletion calculations. In a third time the implementation of this method in the TRIPOLI-4 code will be discussed, as well as the precise calculation scheme used to bring important speed-up of the depletion calculation. We will begin to validate and optimize the perturbed depletion scheme with the calculation of a REP-like fuel cell depletion. Then this technique will be used to calculate the depletion of a REP-like assembly, studied at beginning of its cycle. After having validated the method with a reference calculation we will show that it can speed-up by nearly an order of magnitude standard Monte-Carlo depletion codes. (author) [fr

  2. TU-H-CAMPUS-IeP1-01: Bias and Computational Efficiency of Variance Reduction Methods for the Monte Carlo Simulation of Imaging Detectors

    Energy Technology Data Exchange (ETDEWEB)

    Sharma, D; Badano, A [Division of Imaging, Diagnostics and Software Reliability, OSEL/CDRH, Food & Drug Administration, MD (United States); Sempau, J [Technical University of Catalonia, Barcelona (Spain)

    2016-06-15

    Purpose: Variance reduction techniques (VRTs) are employed in Monte Carlo simulations to obtain estimates with reduced statistical uncertainty for a given simulation time. In this work, we study the bias and efficiency of a VRT for estimating the response of imaging detectors. Methods: We implemented Directed Sampling (DS), preferentially directing a fraction of emitted optical photons directly towards the detector by altering the isotropic model. The weight of each optical photon is appropriately modified to maintain simulation estimates unbiased. We use a Monte Carlo tool called fastDETECT2 (part of the hybridMANTIS open-source package) for optical transport, modified for VRT. The weight of each photon is calculated as the ratio of original probability (no VRT) and the new probability for a particular direction. For our analysis of bias and efficiency, we use pulse height spectra, point response functions, and Swank factors. We obtain results for a variety of cases including analog (no VRT, isotropic distribution), and DS with 0.2 and 0.8 optical photons directed towards the sensor plane. We used 10,000, 25-keV primaries. Results: The Swank factor for all cases in our simplified model converged fast (within the first 100 primaries) to a stable value of 0.9. The root mean square error per pixel for DS VRT for the point response function between analog and VRT cases was approximately 5e-4. Conclusion: Our preliminary results suggest that DS VRT does not affect the estimate of the mean for the Swank factor. Our findings indicate that it may be possible to design VRTs for imaging detector simulations to increase computational efficiency without introducing bias.

  3. A GPU code for analytic continuation through a sampling method

    Directory of Open Access Journals (Sweden)

    Johan Nordström

    2016-01-01

    Full Text Available We here present a code for performing analytic continuation of fermionic Green’s functions and self-energies as well as bosonic susceptibilities on a graphics processing unit (GPU. The code is based on the sampling method introduced by Mishchenko et al. (2000, and is written for the widely used CUDA platform from NVidia. Detailed scaling tests are presented, for two different GPUs, in order to highlight the advantages of this code with respect to standard CPU computations. Finally, as an example of possible applications, we provide the analytic continuation of model Gaussian functions, as well as more realistic test cases from many-body physics.

  4. Methods of scaling threshold color difference using printed samples

    Science.gov (United States)

    Huang, Min; Cui, Guihua; Liu, Haoxue; Luo, M. Ronnier

    2012-01-01

    A series of printed samples on substrate of semi-gloss paper and with the magnitude of threshold color difference were prepared for scaling the visual color difference and to evaluate the performance of different method. The probabilities of perceptibly was used to normalized to Z-score and different color differences were scaled to the Z-score. The visual color difference was got, and checked with the STRESS factor. The results indicated that only the scales have been changed but the relative scales between pairs in the data are preserved.

  5. Statistical methods to correct for verification bias in diagnostic studies are inadequate when there are few false negatives: a simulation study

    Directory of Open Access Journals (Sweden)

    Vickers Andrew J

    2008-11-01

    Full Text Available Abstract Background A common feature of diagnostic research is that results for a diagnostic gold standard are available primarily for patients who are positive for the test under investigation. Data from such studies are subject to what has been termed "verification bias". We evaluated statistical methods for verification bias correction when there are few false negatives. Methods A simulation study was conducted of a screening study subject to verification bias. We compared estimates of the area-under-the-curve (AUC corrected for verification bias varying both the rate and mechanism of verification. Results In a single simulated data set, varying false negatives from 0 to 4 led to verification bias corrected AUCs ranging from 0.550 to 0.852. Excess variation associated with low numbers of false negatives was confirmed in simulation studies and by analyses of published studies that incorporated verification bias correction. The 2.5th – 97.5th centile range constituted as much as 60% of the possible range of AUCs for some simulations. Conclusion Screening programs are designed such that there are few false negatives. Standard statistical methods for verification bias correction are inadequate in this circumstance.

  6. Application of bias factor method with use of virtual experimental value to prediction uncertainty reduction in void reactivity worth of breeding light water reactor

    International Nuclear Information System (INIS)

    Kugo, Teruhiko; Mori, Takamasa; Kojima, Kensuke; Takeda, Toshikazu

    2007-01-01

    We have carried out the critical experiments for the MOX fueled tight lattice LWR cores using FCA facility and constructed the XXII-1 series cores. Utilizing the critical experiments carried out at FCA, we have evaluated the reduction of prediction uncertainty in the coolant void reactivity worth of the breeding LWR core based on the bias factor method with focusing on the prediction uncertainty due to cross section errors. In the present study, we have introduced a concept of a virtual experimental value into the conventional bias factor method to overcome a problem caused by the conventional bias factor method in which the prediction uncertainty increases in the case that the experimental core has the opposite reactivity worth and the consequent opposite sensitivity coefficients to the real core. To extend the applicability of the bias factor method, we have adopted an exponentiated experimental value as the virtual experimental value and formulated the prediction uncertainty reduction by the use of the bias factor method extended by the concept of the virtual experimental value. From the numerical evaluation, it has been shown that the prediction uncertainty due to cross section errors has been reduced by the use of the concept of the virtual experimental value. It is concluded that the introduction of virtual experimental value can effectively utilize experimental data and extend applicability of the bias factor method. (author)

  7. National comparison on volume sample activity measurement methods

    International Nuclear Information System (INIS)

    Sahagia, M.; Grigorescu, E.L.; Popescu, C.; Razdolescu, C.

    1992-01-01

    A national comparison on volume sample activity measurements methods may be regarded as a step toward accomplishing the traceability of the environmental and food chain activity measurements to national standards. For this purpose, the Radionuclide Metrology Laboratory has distributed 137 Cs and 134 Cs water-equivalent solid standard sources to 24 laboratories having responsibilities in this matter. Every laboratory has to measure the activity of the received source(s) by using its own standards, equipment and methods and report the obtained results to the organizer. The 'measured activities' will be compared with the 'true activities'. A final report will be issued, which plans to evaluate the national level of precision of such measurements and give some suggestions for improvement. (Author)

  8. A simple cleanup method for the isolation of nitrate from natural water samples for O isotopes analysis

    International Nuclear Information System (INIS)

    Haberhauer, G.; Blochberger, K.

    1999-09-01

    The analysis of O-isotopic composition of nitrate has many potential applications in studies of environmental processes. O-isotope nitrate analysis require sample free of other oxygen-containing compounds. More than 100 % of non-NO 3 - oxygen relative to NO 3 - oxygen can still be found in forest soil water samples after cleanup if improper cleanup strategies, e.g., adsorption onto activated carbon, are used. Such non-NO 3 - oxygen compounds will bias O-isotropic data. Therefore, an efficient cleanup method was developed to isolate nitrate from natural water samples. In a multistep cleanup procedure using adsorption onto water-insoluble poly(vinylpyrrolidone), removal of almost all other oxygen-containing compounds, such as fulvic acids, and isolation of nitrate was achieved. The method supplied samples free of non-NO 3 - oxygen which can be directly combusted to CO 2 for subsequent O-isotope analysis. (author)

  9. The power grid AGC frequency bias coefficient online identification method based on wide area information

    Science.gov (United States)

    Wang, Zian; Li, Shiguang; Yu, Ting

    2015-12-01

    This paper propose online identification method of regional frequency deviation coefficient based on the analysis of interconnected grid AGC adjustment response mechanism of regional frequency deviation coefficient and the generator online real-time operation state by measured data through PMU, analyze the optimization method of regional frequency deviation coefficient in case of the actual operation state of the power system and achieve a more accurate and efficient automatic generation control in power system. Verify the validity of the online identification method of regional frequency deviation coefficient by establishing the long-term frequency control simulation model of two-regional interconnected power system.

  10. Evaluating outcome-correlated recruitment and geographic recruitment bias in a respondent-driven sample of people who inject drugs in Tijuana, Mexico.

    Science.gov (United States)

    Rudolph, Abby E; Gaines, Tommi L; Lozada, Remedios; Vera, Alicia; Brouwer, Kimberly C

    2014-12-01

    Respondent-driven sampling's (RDS) widespread use and reliance on untested assumptions suggests a need for new exploratory/diagnostic tests. We assessed geographic recruitment bias and outcome-correlated recruitment among 1,048 RDS-recruited people who inject drugs (Tijuana, Mexico). Surveys gathered demographics, drug/sex behaviors, activity locations, and recruiter-recruit pairs. Simulations assessed geographic and network clustering of active syphilis (RPR titers ≥1:8). Gender-specific predicted probabilities were estimated using logistic regression with GEE and robust standard errors. Active syphilis prevalence was 7 % (crude: men = 5.7 % and women = 16.6 %; RDS-adjusted: men = 6.7 % and women = 7.6 %). Syphilis clustered in the Zona Norte, a neighborhood known for drug and sex markets. Network simulations revealed geographic recruitment bias and non-random recruitment by syphilis status. Gender-specific prevalence estimates accounting for clustering were highest among those living/working/injecting/buying drugs in the Zona Norte and directly/indirectly connected to syphilis cases (men: 15.9 %, women: 25.6 %) and lowest among those with neither exposure (men: 3.0 %, women: 6.1 %). Future RDS analyses should assess/account for network and spatial dependencies.

  11. Verification of spectrophotometric method for nitrate analysis in water samples

    Science.gov (United States)

    Kurniawati, Puji; Gusrianti, Reny; Dwisiwi, Bledug Bernanti; Purbaningtias, Tri Esti; Wiyantoko, Bayu

    2017-12-01

    The aim of this research was to verify the spectrophotometric method to analyze nitrate in water samples using APHA 2012 Section 4500 NO3-B method. The verification parameters used were: linearity, method detection limit, level of quantitation, level of linearity, accuracy and precision. Linearity was obtained by using 0 to 50 mg/L nitrate standard solution and the correlation coefficient of standard calibration linear regression equation was 0.9981. The method detection limit (MDL) was defined as 0,1294 mg/L and limit of quantitation (LOQ) was 0,4117 mg/L. The result of a level of linearity (LOL) was 50 mg/L and nitrate concentration 10 to 50 mg/L was linear with a level of confidence was 99%. The accuracy was determined through recovery value was 109.1907%. The precision value was observed using % relative standard deviation (%RSD) from repeatability and its result was 1.0886%. The tested performance criteria showed that the methodology was verified under the laboratory conditions.

  12. Methods to maximise recovery of environmental DNA from water samples.

    Directory of Open Access Journals (Sweden)

    Rheyda Hinlo

    Full Text Available The environmental DNA (eDNA method is a detection technique that is rapidly gaining credibility as a sensitive tool useful in the surveillance and monitoring of invasive and threatened species. Because eDNA analysis often deals with small quantities of short and degraded DNA fragments, methods that maximize eDNA recovery are required to increase detectability. In this study, we performed experiments at different stages of the eDNA analysis to show which combinations of methods give the best recovery rate for eDNA. Using Oriental weatherloach (Misgurnus anguillicaudatus as a study species, we show that various combinations of DNA capture, preservation and extraction methods can significantly affect DNA yield. Filtration using cellulose nitrate filter paper preserved in ethanol or stored in a -20°C freezer and extracted with the Qiagen DNeasy kit outperformed other combinations in terms of cost and efficiency of DNA recovery. Our results support the recommendation to filter water samples within 24hours but if this is not possible, our results suggest that refrigeration may be a better option than freezing for short-term storage (i.e., 3-5 days. This information is useful in designing eDNA detection of low-density invasive or threatened species, where small variations in DNA recovery can signify the difference between detection success or failure.

  13. BMAA extraction of cyanobacteria samples: which method to choose?

    Science.gov (United States)

    Lage, Sandra; Burian, Alfred; Rasmussen, Ulla; Costa, Pedro Reis; Annadotter, Heléne; Godhe, Anna; Rydberg, Sara

    2016-01-01

    β-N-Methylamino-L-alanine (BMAA), a neurotoxin reportedly produced by cyanobacteria, diatoms and dinoflagellates, is proposed to be linked to the development of neurological diseases. BMAA has been found in aquatic and terrestrial ecosystems worldwide, both in its phytoplankton producers and in several invertebrate and vertebrate organisms that bioaccumulate it. LC-MS/MS is the most frequently used analytical technique in BMAA research due to its high selectivity, though consensus is lacking as to the best extraction method to apply. This study accordingly surveys the efficiency of three extraction methods regularly used in BMAA research to extract BMAA from cyanobacteria samples. The results obtained provide insights into possible reasons for the BMAA concentration discrepancies in previous publications. In addition and according to the method validation guidelines for analysing cyanotoxins, the TCA protein precipitation method, followed by AQC derivatization and LC-MS/MS analysis, is now validated for extracting protein-bound (after protein hydrolysis) and free BMAA from cyanobacteria matrix. BMAA biological variability was also tested through the extraction of diatom and cyanobacteria species, revealing a high variance in BMAA levels (0.0080-2.5797 μg g(-1) DW).

  14. Influence of sampling frequency and load calculation methods on quantification of annual river nutrient and suspended solids loads.

    Science.gov (United States)

    Elwan, Ahmed; Singh, Ranvir; Patterson, Maree; Roygard, Jon; Horne, Dave; Clothier, Brent; Jones, Geoffrey

    2018-01-11

    Better management of water quality in streams, rivers and lakes requires precise and accurate estimates of different contaminant loads. We assessed four sampling frequencies (2 days, weekly, fortnightly and monthly) and five load calculation methods (global mean (GM), rating curve (RC), ratio estimator (RE), flow-stratified (FS) and flow-weighted (FW)) to quantify loads of nitrate-nitrogen (NO 3 - -N), soluble inorganic nitrogen (SIN), total nitrogen (TN), dissolved reactive phosphorus (DRP), total phosphorus (TP) and total suspended solids (TSS), in the Manawatu River, New Zealand. The estimated annual river loads were compared to the reference 'true' loads, calculated using daily measurements of flow and water quality from May 2010 to April 2011, to quantify bias (i.e. accuracy) and root mean square error 'RMSE' (i.e. accuracy and precision). The GM method resulted into relatively higher RMSE values and a consistent negative bias (i.e. underestimation) in estimates of annual river loads across all sampling frequencies. The RC method resulted in the lowest RMSE for TN, TP and TSS at monthly sampling frequency. Yet, RC highly overestimated the loads for parameters that showed dilution effect such as NO 3 - -N and SIN. The FW and RE methods gave similar results, and there was no essential improvement in using RE over FW. In general, FW and RE performed better than FS in terms of bias, but FS performed slightly better than FW and RE in terms of RMSE for most of the water quality parameters (DRP, TP, TN and TSS) using a monthly sampling frequency. We found no significant decrease in RMSE values for estimates of NO 3 - N, SIN, TN and DRP loads when the sampling frequency was increased from monthly to fortnightly. The bias and RMSE values in estimates of TP and TSS loads (estimated by FW, RE and FS), however, showed a significant decrease in the case of weekly or 2-day sampling. This suggests potential for a higher sampling frequency during flow peaks for more precise

  15. THE ACCURACY AND BIAS EVALUATION OF THE USA UNEMPLOYMENT RATE FORECASTS. METHODS TO IMPROVE THE FORECASTS ACCURACY

    Directory of Open Access Journals (Sweden)

    MIHAELA BRATU (SIMIONESCU

    2012-12-01

    Full Text Available In this study some alternative forecasts for the unemployment rate of USA made by four institutions (International Monetary Fund (IMF, Organization for Economic Co-operation and Development (OECD, Congressional Budget Office (CBO and Blue Chips (BC are evaluated regarding the accuracy and the biasness. The most accurate predictions on the forecasting horizon 201-2011 were provided by IMF, followed by OECD, CBO and BC.. These results were gotten using U1 Theil’s statistic and a new method that has not been used before in literature in this context. The multi-criteria ranking was applied to make a hierarchy of the institutions regarding the accuracy and five important accuracy measures were taken into account at the same time: mean errors, mean squared error, root mean squared error, U1 and U2 statistics of Theil. The IMF, OECD and CBO predictions are unbiased. The combined forecasts of institutions’ predictions are a suitable strategy to improve the forecasts accuracy of IMF and OECD forecasts when all combination schemes are used, but INV one is the best. The filtered and smoothed original predictions based on Hodrick-Prescott filter, respectively Holt-Winters technique are a good strategy of improving only the BC expectations. The proposed strategies to improve the accuracy do not solve the problem of biasness. The assessment and improvement of forecasts accuracy have an important contribution in growing the quality of decisional process.

  16. Evaluating the impact of method bias in health behaviour research: a meta-analytic examination of studies utilising the theories of reasoned action and planned behaviour.

    Science.gov (United States)

    McDermott, Máirtín S; Sharma, Rajeev

    2017-12-01

    The methods employed to measure behaviour in research testing the theories of reasoned action/planned behaviour (TRA/TPB) within the context of health behaviours have the potential to significantly bias findings. One bias yet to be examined in that literature is that due to common method variance (CMV). CMV introduces a variance in scores attributable to the method used to measure a construct, rather than the construct it represents. The primary aim of this study was to evaluate the impact of method bias on the associations of health behaviours with TRA/TPB variables. Data were sourced from four meta-analyses (177 studies). The method used to measure behaviour for each effect size was coded for susceptibility to bias. The moderating impact of method type was assessed using meta-regression. Method type significantly moderated the associations of intentions, attitudes and social norms with behaviour, but not that between perceived behavioural control and behaviour. The magnitude of the moderating effect of method type appeared consistent between cross-sectional and prospective studies, but varied across behaviours. The current findings strongly suggest that method bias significantly inflates associations in TRA/TPB research, and poses a potentially serious validity threat to the cumulative findings reported in that field.

  17. Methods for sampling geographically mobile female traders in an East African market setting

    Science.gov (United States)

    Achiro, Lillian; Kwena, Zachary A.; McFarland, Willi; Neilands, Torsten B.; Cohen, Craig R.; Bukusi, Elizabeth A.; Camlin, Carol S.

    2018-01-01

    Background The role of migration in the spread of HIV in sub-Saharan Africa is well-documented. Yet migration and HIV research have often focused on HIV risks to male migrants and their partners, or migrants overall, often failing to measure the risks to women via their direct involvement in migration. Inconsistent measures of mobility, gender biases in those measures, and limited data sources for sex-specific population-based estimates of mobility have contributed to a paucity of research on the HIV prevention and care needs of migrant and highly mobile women. This study addresses an urgent need for novel methods for developing probability-based, systematic samples of highly mobile women, focusing on a population of female traders operating out of one of the largest open air markets in East Africa. Our method involves three stages: 1.) identification and mapping of all market stall locations using Global Positioning System (GPS) coordinates; 2.) using female market vendor stall GPS coordinates to build the sampling frame using replicates; and 3.) using maps and GPS data for recruitment of study participants. Results The location of 6,390 vendor stalls were mapped using GPS. Of these, 4,064 stalls occupied by women (63.6%) were used to draw four replicates of 128 stalls each, and a fifth replicate of 15 pre-selected random alternates for a total of 527 stalls assigned to one of five replicates. Staff visited 323 stalls from the first three replicates and from these successfully recruited 306 female vendors into the study for a participation rate of 94.7%. Mobilization strategies and involving traders association representatives in participant recruitment were critical to the study’s success. Conclusion The study’s high participation rate suggests that this geospatial sampling method holds promise for development of probability-based samples in other settings that serve as transport hubs for highly mobile populations. PMID:29324780

  18. Combination of biased forecasts: Bias correction or bias based weights?

    OpenAIRE

    Wenzel, Thomas

    1999-01-01

    Most of the literature on combination of forecasts deals with the assumption of unbiased individual forecasts. Here, we consider the case of biased forecasts and discuss two different combination techniques resulting in an unbiased forecast. On the one hand we correct the individual forecasts, and on the other we calculate bias based weights. A simulation study gives some insight in the situations where we should use the different methods.

  19. Clustering Methods with Qualitative Data: a Mixed-Methods Approach for Prevention Research with Small Samples.

    Science.gov (United States)

    Henry, David; Dymnicki, Allison B; Mohatt, Nathaniel; Allen, James; Kelly, James G

    2015-10-01

    Qualitative methods potentially add depth to prevention research but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed-methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed-methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-means clustering, and latent class analysis produced similar levels of accuracy with binary data and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a "real-world" example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities.

  20. Clustering Methods with Qualitative Data: A Mixed Methods Approach for Prevention Research with Small Samples

    Science.gov (United States)

    Henry, David; Dymnicki, Allison B.; Mohatt, Nathaniel; Allen, James; Kelly, James G.

    2016-01-01

    Qualitative methods potentially add depth to prevention research, but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data, but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-Means clustering, and latent class analysis produced similar levels of accuracy with binary data, and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a “real-world” example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities. PMID:25946969

  1. CPI Bias in Korea

    Directory of Open Access Journals (Sweden)

    Chul Chung

    2007-12-01

    Full Text Available We estimate the CPI bias in Korea by employing the approach of Engel’s Law as suggested by Hamilton (2001. This paper is the first attempt to estimate the bias using Korean panel data, Korean Labor and Income Panel Study(KLIPS. Following Hamilton’s model with non­linear specification correction, our estimation result shows that the cumulative CPI bias over the sample period (2000-2005 was 0.7 percent annually. This CPI bias implies that about 21 percent of the inflation rate during the period can be attributed to the bias. In light of purchasing power parity, we provide an interpretation of the estimated bias.

  2. Biases of chamber methods for measuring soil CO2 efflux demonstrated with a laboratory apparatus.

    Science.gov (United States)

    S. Mark Nay; Kim G. Mattson; Bernard T. Bormann

    1994-01-01

    Investigators have historically measured soil CO2 efflux as an indicator of soil microbial and root activity and more recently in calculations of carbon budgets. The most common methods estimate CO2 efflux by placing a chamber over the soil surface and quantifying the amount of CO2 entering the...

  3. A New Method for Negative Bias Temperature Instability Assessment in P-Channel Metal Oxide Semiconductor Transistors

    Science.gov (United States)

    Djezzar, Boualem; Tahi, Hakim; Benabdelmoumene, Abdelmadjid; Chenouf, Amel; Kribes, Youcef

    2012-11-01

    In this paper, we present a new method, named on the fly oxide trap (OTFOT), to extract the bias temperature instability (BTI) in MOS transistors. The OTFOT method is based on charge pumping technique (CP) at low and high frequencies. We emphasize on the theoretical-based concept, giving a clear insight on the easy-use of the OTFOT methodology and demonstrating its viability to characterize the negative BTI (NBTI). Using alternatively high and low frequencies, OTFOT method separates the interface-traps (ΔNit) and border-trap (ΔNbt) (switching oxide-trap) densities independently and also their contributions to the threshold voltage shift (ΔVth), without needing additional methods. The experimental results, from two experimental scenarios, showing the extraction of NBTI-induced shifts caused by interface- and oxide-trap increases are also presented. In the first scenario, all stresses are performed on the same transistor. It exhibits an artifact value of exponent n. In the second scenario, each voltage stress is applied only on one transistor. Its results show an average n of 0.16, 0.05, and 0.11 for NBTI-induced ΔNit, ΔNbt, ΔVth, respectively. Therefore, OTFOT method can contribute to further understand the behavior of the NBTI degradation, especially through the threshold voltage shift components such as ΔVit and ΔVot caused by interface-trap and border-trap, respectively.

  4. An adaptive sampling and windowing interrogation method in PIV

    Science.gov (United States)

    Theunissen, R.; Scarano, F.; Riethmuller, M. L.

    2007-01-01

    This study proposes a cross-correlation based PIV image interrogation algorithm that adapts the number of interrogation windows and their size to the image properties and to the flow conditions. The proposed methodology releases the constraint of uniform sampling rate (Cartesian mesh) and spatial resolution (uniform window size) commonly adopted in PIV interrogation. Especially in non-optimal experimental conditions where the flow seeding is inhomogeneous, this leads either to loss of robustness (too few particles per window) or measurement precision (too large or coarsely spaced interrogation windows). Two criteria are investigated, namely adaptation to the local signal content in the image and adaptation to local flow conditions. The implementation of the adaptive criteria within a recursive interrogation method is described. The location and size of the interrogation windows are locally adapted to the image signal (i.e., seeding density). Also the local window spacing (commonly set by the overlap factor) is put in relation with the spatial variation of the velocity field. The viability of the method is illustrated over two experimental cases where the limitation of a uniform interrogation approach appears clearly: a shock-wave-boundary layer interaction and an aircraft vortex wake. The examples show that the spatial sampling rate can be adapted to the actual flow features and that the interrogation window size can be arranged so as to follow the spatial distribution of seeding particle images and flow velocity fluctuations. In comparison with the uniform interrogation technique, the spatial resolution is locally enhanced while in poorly seeded regions the level of robustness of the analysis (signal-to-noise ratio) is kept almost constant.

  5. Fundamentals of bias temperature instability in MOS transistors characterization methods, process and materials impact, DC and AC modeling

    CERN Document Server

    2016-01-01

    This book aims to cover different aspects of Bias Temperature Instability (BTI). BTI remains as an important reliability concern for CMOS transistors and circuits. Development of BTI resilient technology relies on utilizing artefact-free stress and measurement methods and suitable physics-based models for accurate determination of degradation at end-of-life, and understanding the gate insulator process impact on BTI. This book discusses different ultra-fast characterization techniques for recovery artefact free BTI measurements. It also covers different direct measurements techniques to access pre-existing and newly generated gate insulator traps responsible for BTI. The book provides a consistent physical framework for NBTI and PBTI respectively for p- and n- channel MOSFETs, consisting of trap generation and trapping. A physics-based compact model is presented to estimate measured BTI degradation in planar Si MOSFETs having differently processed SiON and HKMG gate insulators, in planar SiGe MOSFETs and also...

  6. Quantitative evaluation of automated skull-stripping methods applied to contemporary and legacy images: effects of diagnosis, bias correction, and slice location

    DEFF Research Database (Denmark)

    Fennema-Notestine, Christine; Ozyurt, I Burak; Clark, Camellia P

    2006-01-01

    Extractor (BSE, Sandor and Leahy [1997] IEEE Trans Med Imag 16:41-54; Shattuck et al. [2001] Neuroimage 13:856-876) to manually stripped images. The methods were applied to uncorrected and bias-corrected datasets; Legacy and Contemporary T1-weighted image sets; and four diagnostic groups (depressed...... distances, and an Expectation-Maximization algorithm. Methods tended to perform better on contemporary datasets; bias correction did not significantly improve method performance. Mesial sections were most difficult for all methods. Although AD image sets were most difficult to strip, HWA and BSE were more...

  7. Martian Radiative Transfer Modeling Using the Optimal Spectral Sampling Method

    Science.gov (United States)

    Eluszkiewicz, J.; Cady-Pereira, K.; Uymin, G.; Moncet, J.-L.

    2005-01-01

    The large volume of existing and planned infrared observations of Mars have prompted the development of a new martian radiative transfer model that could be used in the retrievals of atmospheric and surface properties. The model is based on the Optimal Spectral Sampling (OSS) method [1]. The method is a fast and accurate monochromatic technique applicable to a wide range of remote sensing platforms (from microwave to UV) and was originally developed for the real-time processing of infrared and microwave data acquired by instruments aboard the satellites forming part of the next-generation global weather satellite system NPOESS (National Polarorbiting Operational Satellite System) [2]. As part of our on-going research related to the radiative properties of the martian polar caps, we have begun the development of a martian OSS model with the goal of using it to perform self-consistent atmospheric corrections necessary to retrieve caps emissivity from the Thermal Emission Spectrometer (TES) spectra. While the caps will provide the initial focus area for applying the new model, it is hoped that the model will be of interest to the wider Mars remote sensing community.

  8. Method for estimating modulation transfer function from sample images.

    Science.gov (United States)

    Saiga, Rino; Takeuchi, Akihisa; Uesugi, Kentaro; Terada, Yasuko; Suzuki, Yoshio; Mizutani, Ryuta

    2018-02-01

    The modulation transfer function (MTF) represents the frequency domain response of imaging modalities. Here, we report a method for estimating the MTF from sample images. Test images were generated from a number of images, including those taken with an electron microscope and with an observation satellite. These original images were convolved with point spread functions (PSFs) including those of circular apertures. The resultant test images were subjected to a Fourier transformation. The logarithm of the squared norm of the Fourier transform was plotted against the squared distance from the origin. Linear correlations were observed in the logarithmic plots, indicating that the PSF of the test images can be approximated with a Gaussian. The MTF was then calculated from the Gaussian-approximated PSF. The obtained MTF closely coincided with the MTF predicted from the original PSF. The MTF of an x-ray microtomographic section of a fly brain was also estimated with this method. The obtained MTF showed good agreement with the MTF determined from an edge profile of an aluminum test object. We suggest that this approach is an alternative way of estimating the MTF, independently of the image type. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. The grid-scan. A novel method for a less biased broadband SED modeling

    Energy Technology Data Exchange (ETDEWEB)

    Doert, Marlene [Ruhr-Universitaet Bochum (Germany); Paneque, David [Max-Planck-Institut fuer Physik, Muenchen (Germany)

    2016-07-01

    We present a novel strategy for the modeling of blazar SEDs in the scope of current emission models: the grid-scan modeling. With an unbiased and uniform scan of the multi-dimensional parameter space of current emission models, e.g. the SSC model, and an a posteriori evaluation of the model-to-data agreement, independent sets of equally good model representations can be found. This variety of models generally includes different valid physical scenarios, which offer a more complete picture than single ''best'' solutions found by minimizers or the often-practised ''eyeball-fit''. Additionally, the grid-scan also allows to quantify how well the individual model parameters get constrained by any given experimental data set. The method will be introduced using the example of multi-wavelength spectral measurements of the blazar Markarian 501.

  10. Failure Probability Calculation Method Using Kriging Metamodel-based Importance Sampling Method

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seunggyu [Korea Aerospace Research Institue, Daejeon (Korea, Republic of); Kim, Jae Hoon [Chungnam Nat’l Univ., Daejeon (Korea, Republic of)

    2017-05-15

    The kernel density was determined based on sampling points obtained in a Markov chain simulation and was assumed to be an important sampling function. A Kriging metamodel was constructed in more detail in the vicinity of a limit state. The failure probability was calculated based on importance sampling, which was performed for the Kriging metamodel. A pre-existing method was modified to obtain more sampling points for a kernel density in the vicinity of a limit state. A stable numerical method was proposed to find a parameter of the kernel density. To assess the completeness of the Kriging metamodel, the possibility of changes in the calculated failure probability due to the uncertainty of the Kriging metamodel was calculated.

  11. Method and apparatus for sensing a desired component of an incident magnetic field using magneto resistive elements biased in different directions

    Science.gov (United States)

    Pant, Bharat B. (Inventor); Wan, Hong (Inventor)

    1999-01-01

    A method and apparatus for sensing a desired component of a magnetic field using an isotropic magnetoresistive material. This is preferably accomplished by providing a bias field that is parallel to the desired component of the applied magnetic field. The bias field is applied in a first direction relative to a first set of magnetoresistive sensor elements, and in an opposite direction relative to a second set of magnetoresistive sensor elements. In this configuration, the desired component of the incident magnetic field adds to the bias field incident on the first set of magnetoresistive sensor elements, and subtracts from the bias field incident on the second set of magnetoresistive sensor elements. The magnetic field sensor may then sense the desired component of the incident magnetic field by simply sensing the difference in resistance of the first set of magnetoresistive sensor elements and the second set of magnetoresistive sensor elements.

  12. Sequential sampling: a novel method in farm animal welfare assessment.

    Science.gov (United States)

    Heath, C A E; Main, D C J; Mullan, S; Haskell, M J; Browne, W J

    2016-02-01

    Lameness in dairy cows is an important welfare issue. As part of a welfare assessment, herd level lameness prevalence can be estimated from scoring a sample of animals, where higher levels of accuracy are associated with larger sample sizes. As the financial cost is related to the number of cows sampled, smaller samples are preferred. Sequential sampling schemes have been used for informing decision making in clinical trials. Sequential sampling involves taking samples in stages, where sampling can stop early depending on the estimated lameness prevalence. When welfare assessment is used for a pass/fail decision, a similar approach could be applied to reduce the overall sample size. The sampling schemes proposed here apply the principles of sequential sampling within a diagnostic testing framework. This study develops three sequential sampling schemes of increasing complexity to classify 80 fully assessed UK dairy farms, each with known lameness prevalence. Using the Welfare Quality herd-size-based sampling scheme, the first 'basic' scheme involves two sampling events. At the first sampling event half the Welfare Quality sample size is drawn, and then depending on the outcome, sampling either stops or is continued and the same number of animals is sampled again. In the second 'cautious' scheme, an adaptation is made to ensure that correctly classifying a farm as 'bad' is done with greater certainty. The third scheme is the only scheme to go beyond lameness as a binary measure and investigates the potential for increasing accuracy by incorporating the number of severely lame cows into the decision. The three schemes are evaluated with respect to accuracy and average sample size by running 100 000 simulations for each scheme, and a comparison is made with the fixed size Welfare Quality herd-size-based sampling scheme. All three schemes performed almost as well as the fixed size scheme but with much smaller average sample sizes. For the third scheme, an overall

  13. Investigation of the UK37' vs. SST relationship for Atlantic Ocean suspended particulate alkenones: An alternative regression model and discussion of possible sampling bias

    Science.gov (United States)

    Gould, Jessica; Kienast, Markus; Dowd, Michael

    2017-05-01

    Alkenone unsaturation, expressed as the UK37' index, is closely related to growth temperature of prymnesiophytes, thus providing a reliable proxy to infer past sea surface temperatures (SSTs). Here we address two lingering uncertainties related to this SST proxy. First, calibration models developed for core-top sediments and those developed for surface suspended particulates organic material (SPOM) show systematic offsets, raising concerns regarding the transfer of the primary signal into the sedimentary record. Second, questions remain regarding changes in slope of the UK37' vs. growth temperature relationship at the temperature extremes. Based on (re)analysis of 31 new and 394 previously published SPOM UK37' data from the Atlantic Ocean, a new regression model to relate UK37' to SST is introduced; the Richards curve (Richards, 1959). This non-linear regression model provides a robust calibration of the UK37' vs. SST relationship for Atlantic SPOM samples and uniquely accounts for both the fact that the UK37' index is a proportion, and so must lie between 0 and 1, as well as for the observed reduction in slope at the warm and cold ends of the temperature range. As with prior fits of SPOM UK37' vs. SST, the Richards model is offset from traditional regression models of sedimentary UK37' vs. SST. We posit that (some of) this offset can be attributed to the seasonally and depth biased sampling of SPOM material.

  14. Discrete- vs. Continuous-Time Modeling of Unequally Spaced Experience Sampling Method Data

    Directory of Open Access Journals (Sweden)

    Silvia de Haan-Rietdijk

    2017-10-01

    Full Text Available The Experience Sampling Method is a common approach in psychological research for collecting intensive longitudinal data with high ecological validity. One characteristic of ESM data is that it is often unequally spaced, because the measurement intervals within a day are deliberately varied, and measurement continues over several days. This poses a problem for discrete-time (DT modeling approaches, which are based on the assumption that all measurements are equally spaced. Nevertheless, DT approaches such as (vector autoregressive modeling are often used to analyze ESM data, for instance in the context of affective dynamics research. There are equivalent continuous-time (CT models, but they are more difficult to implement. In this paper we take a pragmatic approach and evaluate the practical relevance of the violated model assumption in DT AR(1 and VAR(1 models, for the N = 1 case. We use simulated data under an ESM measurement design to investigate the bias in the parameters of interest under four different model implementations, ranging from the true CT model that accounts for all the exact measurement times, to the crudest possible DT model implementation, where even the nighttime is treated as a regular interval. An analysis of empirical affect data illustrates how the differences between DT and CT modeling can play out in practice. We find that the size and the direction of the bias in DT (VAR models for unequally spaced ESM data depend quite strongly on the true parameter in addition to data characteristics. Our recommendation is to use CT modeling whenever possible, especially now that new software implementations have become available.

  15. Estimation bias and bias correction in reduced rank autoregressions

    DEFF Research Database (Denmark)

    Nielsen, Heino Bohn

    2017-01-01

    This paper characterizes the finite-sample bias of the maximum likelihood estimator (MLE) in a reduced rank vector autoregression and suggests two simulation-based bias corrections. One is a simple bootstrap implementation that approximates the bias at the MLE. The other is an iterative root...

  16. Comparison of diffusion- and pumped-sampling methods to monitor volatile organic compounds in ground water, Massachusetts Military Reservation, Cape Cod, Massachusetts, July 1999-December 2002

    Science.gov (United States)

    Archfield, Stacey A.; LeBlanc, Denis R.

    2005-01-01

    To evaluate diffusion sampling as an alternative method to monitor volatile organic compound (VOC) concentrations in ground water, concentrations in samples collected by traditional pumped-sampling methods were compared to concentrations in samples collected by diffusion-sampling methods for 89 monitoring wells at or near the Massachusetts Military Reservation, Cape Cod. Samples were analyzed for 36 VOCs. There was no substantial difference between the utility of diffusion and pumped samples to detect the presence or absence of a VOC. In wells where VOCs were detected, diffusion-sample concentrations of tetrachloroethene (PCE) and trichloroethene (TCE) were significantly lower than pumped-sample concentrations. Because PCE and TCE concentrations detected in the wells dominated the calculation of many of the total VOC concentrations, when VOC concentrations were summed and compared by sampling method, visual inspection also showed a downward concentration bias in the diffusion-sample concentration. The degree to which pumped- and diffusion-sample concentrations agreed was not a result of variability inherent within the sampling methods or the diffusion process itself. A comparison of the degree of agreement in the results from the two methods to 13 quantifiable characteristics external to the sampling methods offered only well-screen length as being related to the degree of agreement between the methods; however, there is also evidence to indicate that the flushing rate of water through the well screen affected the agreement between the sampling methods. Despite poor agreement between the concentrations obtained by the two methods at some wells, the degree to which the concentrations agree at a given well is repeatable. A one-time, well-bywell comparison between diffusion- and pumped-sampling methods could determine which wells are good candidates for the use of diffusion samplers. For wells with good method agreement, the diffusion-sampling method is a time

  17. AST: an automated sequence-sampling method for improving the taxonomic diversity of gene phylogenetic trees.

    Science.gov (United States)

    Zhou, Chan; Mao, Fenglou; Yin, Yanbin; Huang, Jinling; Gogarten, Johann Peter; Xu, Ying

    2014-01-01

    A challenge in phylogenetic inference of gene trees is how to properly sample a large pool of homologous sequences to derive a good representative subset of sequences. Such a need arises in various applications, e.g. when (1) accuracy-oriented phylogenetic reconstruction methods may not be able to deal with a large pool of sequences due to their high demand in computing resources; (2) applications analyzing a collection of gene trees may prefer to use trees with fewer operational taxonomic units (OTUs), for instance for the detection of horizontal gene transfer events by identifying phylogenetic conflicts; and (3) the pool of available sequences is biased towards extensively studied species. In the past, the creation of subsamples often relied on manual selection. Here we present an Automated sequence-Sampling method for improving the Taxonomic diversity of gene phylogenetic trees, AST, to obtain representative sequences that maximize the taxonomic diversity of the sampled sequences. To demonstrate the effectiveness of AST, we have tested it to solve four problems, namely, inference of the evolutionary histories of the small ribosomal subunit protein S5 of E. coli, 16 S ribosomal RNAs and glycosyl-transferase gene family 8, and a study of ancient horizontal gene transfers from bacteria to plants. Our results show that the resolution of our computational results is almost as good as that of manual inference by domain experts, hence making the tool generally useful to phylogenetic studies by non-phylogeny specialists. The program is available at http://csbl.bmb.uga.edu/~zhouchan/AST.php.

  18. Nonlinear vs. linear biasing in Trp-cage folding simulations

    Energy Technology Data Exchange (ETDEWEB)

    Spiwok, Vojtěch, E-mail: spiwokv@vscht.cz; Oborský, Pavel; Králová, Blanka [Department of Biochemistry and Microbiology, University of Chemistry and Technology, Prague, Technická 3, Prague 6 166 28 (Czech Republic); Pazúriková, Jana [Institute of Computer Science, Masaryk University, Botanická 554/68a, 602 00 Brno (Czech Republic); Křenek, Aleš [Institute of Computer Science, Masaryk University, Botanická 554/68a, 602 00 Brno (Czech Republic); Center CERIT-SC, Masaryk Univerzity, Šumavská 416/15, 602 00 Brno (Czech Republic)

    2015-03-21

    Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.

  19. The Roche Immunoturbidimetric Albumin Method on Cobas c 501 Gives Higher Values Than the Abbott and Roche BCP Methods When Analyzing Patient Plasma Samples.

    Science.gov (United States)

    Helmersson-Karlqvist, Johanna; Flodin, Mats; Havelka, Aleksandra Mandic; Xu, Xiao Yan; Larsson, Anders

    2016-09-01

    Serum/plasma albumin is an important and widely used laboratory marker and it is important that we measure albumin correctly without bias. We had indications that the immunoturbidimetric method on Cobas c 501 and the bromocresol purple (BCP) method on Architect 16000 differed, so we decided to study these methods more closely. A total of 1,951 patient requests with albumin measured with both the Architect BCP and Cobas immunoturbidimetric methods were extracted from the laboratory system. A comparison with fresh plasma samples was also performed that included immunoturbidimetric and BCP methods on Cobas c 501 and analysis of the international protein calibrator ERM-DA470k/IFCC. The median difference between the Abbott BCP and Roche immunoturbidimetric methods was 3.3 g/l and the Roche method overestimated ERM-DA470k/IFCC by 2.2 g/l. The Roche immunoturbidimetric method gave higher values than the Roche BCP method: y = 1.111x - 0.739, R² = 0.971. The Roche immunoturbidimetric albumin method gives clearly higher values than the Abbott and Roche BCP methods when analyzing fresh patient samples. The differences between the two methods were similar at normal and low albumin levels. © 2016 Wiley Periodicals, Inc.

  20. Interval estimation methods of the mean in small sample situation and the results' comparison

    International Nuclear Information System (INIS)

    Wu Changli; Guo Chunying; Jiang Meng; Lin Yuangen

    2009-01-01

    The methods of the sample mean's interval estimation, namely the classical method, the Bootstrap method, the Bayesian Bootstrap method, the Jackknife method and the spread method of the Empirical Characteristic distribution function are described. Numerical calculation on the samples' mean intervals is carried out where the numbers of the samples are 4, 5, 6 respectively. The results indicate the Bootstrap method and the Bayesian Bootstrap method are much more appropriate than others in small sample situation. (authors)

  1. Sympathetic bias.

    Science.gov (United States)

    Levy, David M; Peart, Sandra J

    2008-06-01

    We wish to deal with investigator bias in a statistical context. We sketch how a textbook solution to the problem of "outliers" which avoids one sort of investigator bias, creates the temptation for another sort. We write down a model of the approbation seeking statistician who is tempted by sympathy for client to violate the disciplinary standards. We give a simple account of one context in which we might expect investigator bias to flourish. Finally, we offer tentative suggestions to deal with the problem of investigator bias which follow from our account. As we have given a very sparse and stylized account of investigator bias, we ask what might be done to overcome this limitation.

  2. Improvement of the detection limits in radio-frequency-powered glow discharge optical emission spectrometry associated with bias-current conduction method; Jiko bias denryu donyuho ni yoru koshuha glow hoden hakko bunseki ni okeru kenshutsu genkai no kaizen

    Energy Technology Data Exchange (ETDEWEB)

    Wagatsuma, K. [Tohoku University, Sendai (Japan). Research Institute for Materials

    1999-01-01

    A d.c. bias current driven by the self-bias voltage which is conducted through the r.f.-powered glow discharge plasma varies the emission characteristics drastically, leading to improvement of the detection power in the optical emission spectrometry. By conducting the bias currents of 20-30 mA, the emission intensities of the atomic resonance lines were 10-20 times larger than those obtained with conventional r.t.- powered plasmas. The detection limits for determination of alloyed elements in the re-based binary alloy samples were estimated to be l.6 x 10{sup -3}% Cr for CrI 425.43nm, 7 x 10{sup -4}% Mn for MnI 403.10nm, 1.9>10{sup -3}% Cu for CuI 327.40nm, 1.1 x 10{sup -3}% Al for AlI 396.16nm, and 6.6 x 10{sup -3}% Ni for NiI 352.45 nm. (author)

  3. Sampling in Qualitative Research: Rationale, Issues, and Methods

    OpenAIRE

    LUBORSKY, MARK R.; RUBINSTEIN, ROBERT L.

    1995-01-01

    In gerontology the most recognized and elaborate discourse about sampling is generally thought to be in quantitative research associated with survey research and medical research. But sampling has long been a central concern in the social and humanistic inquiry, albeit in a different guise suited to the different goals. There is a need for more explicit discussion of qualitative sampling issues. This article will outline the guiding principles and rationales, features, and practices of sampli...

  4. On-line sample processing methods in flow analysis

    DEFF Research Database (Denmark)

    Miró, Manuel; Hansen, Elo Harald

    2008-01-01

    In this chapter, the state of the art of flow injection and related approaches thereof for automation and miniaturization of sample processing regardless of the aggregate state of the sample medium is overviewed. The potential of the various generation of flow injection for implementation of in...

  5. Acoustically levitated droplets: a contactless sampling method for fluorescence studies.

    Science.gov (United States)

    Leiterer, Jork; Grabolle, Markus; Rurack, Knut; Resch-Genger, Ute; Ziegler, Jan; Nann, Thomas; Panne, Ulrich

    2008-01-01

    Acoustic levitation is used as a new tool to study concentration-dependent processes in fluorescence spectroscopy. With this technique, small amounts of liquid and solid samples can be measured without the need for sample supports or containers, which often limits signal acquisition and can even alter sample properties due to interactions with the support material. We demonstrate that, because of the small sample volume, fluorescence measurements at high concentrations of an organic dye are possible without the limitation of inner-filter effects, which hamper such experiments in conventional, cuvette-based measurements. Furthermore, we show that acoustic levitation of liquid samples provides an experimentally simple way to study distance-dependent fluorescence modulations in semiconductor nanocrystals. The evaporation of the solvent during levitation leads to a continuous increase of solute concentration and can easily be monitored by laser-induced fluorescence.

  6. Method for Hot Real-Time Sampling of Gasification Products

    Energy Technology Data Exchange (ETDEWEB)

    Pomeroy, Marc D [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-09-29

    The Thermochemical Process Development Unit (TCPDU) at the National Renewable Energy Laboratory (NREL) is a highly instrumented half-ton/day pilot scale plant capable of demonstrating industrially relevant thermochemical technologies from lignocellulosic biomass conversion, including gasification. Gasification creates primarily Syngas (a mixture of Hydrogen and Carbon Monoxide) that can be utilized with synthesis catalysts to form transportation fuels and other valuable chemicals. Biomass derived gasification products are a very complex mixture of chemical components that typically contain Sulfur and Nitrogen species that can act as catalysis poisons for tar reforming and synthesis catalysts. Real-time hot online sampling techniques, such as Molecular Beam Mass Spectrometry (MBMS), and Gas Chromatographs with Sulfur and Nitrogen specific detectors can provide real-time analysis providing operational indicators for performance. Sampling typically requires coated sampling lines to minimize trace sulfur interactions with steel surfaces. Other materials used inline have also shown conversion of sulfur species into new components and must be minimized. Sample line Residence time within the sampling lines must also be kept to a minimum to reduce further reaction chemistries. Solids from ash and char contribute to plugging and must be filtered at temperature. Experience at NREL has shown several key factors to consider when designing and installing an analytical sampling system for biomass gasification products. They include minimizing sampling distance, effective filtering as close to source as possible, proper line sizing, proper line materials or coatings, even heating of all components, minimizing pressure drops, and additional filtering or traps after pressure drops.

  7. The influence of common method bias on the relationship of the socio-ecological model in predicting physical activity behavior

    Science.gov (United States)

    Wingate, Savanna; Sng, Eveleen; Loprinzi, Paul D.

    2018-01-01

    Background: The purpose of this study was to evaluate the extent, if any, that the association between socio-ecological parameters and physical activity may be influenced by common method bias (CMB). Methods: This study took place between February and May of 2017 at a Southeastern University in the United States. A randomized controlled experiment was employed among 119 young adults.Participants were randomized into either group 1 (the group we attempted to minimize CMB)or group 2 (control group). In group 1, CMB was minimized via various procedural remedies,such as separating the measurement of predictor and criterion variables by introducing a time lag (temporal; 2 visits several days apart), creating a cover story (psychological), and approximating measures to have data collected in different media (computer-based vs. paper and pencil) and different locations to control method variance when collecting self-report measures from the same source. Socio-ecological parameters (self-efficacy; friend support; family support)and physical activity were self-reported. Results: Exercise self-efficacy was significantly associated with physical activity. This association (β = 0.74, 95% CI: 0.33-1.1; P = 0.001) was only observed in group 2 (control), but not in group 1 (experimental group) (β = 0.03; 95% CI: -0.57-0.63; P = 0.91). The difference in these coefficients (i.e., β = 0.74 vs. β = 0.03) was statistically significant (P = 0.04). Conclusion: Future research in this field, when feasible, may wish to consider employing procedural and statistical remedies to minimize CMB. PMID:29423361

  8. A test of Hartnett's revisions to the pubic symphysis and fourth rib methods on a modern sample.

    Science.gov (United States)

    Merritt, Catherine E

    2014-05-01

    Estimating age at death is one of the most important aspects of creating a biological profile. Most adult age estimation methods were developed on North American skeletal collections from the early to mid-20th century, and their applicability to modern populations has been questioned. In 2010, Hartnett used a modern skeletal collection from the Maricopia County Forensic Science Centre to revise the Suchey-Brooks pubic symphysis method and the İşcan et al. fourth rib methods. The current study tests Hartnett's revised methods as well as the original Suchey-Brooks and İşcan et al. methods on a modern sample from the William Bass Skeletal Collection (N = 313, mean age = 58.5, range 19-92). Results show that the Suchey-Brooks and İşcan et al. methods assign individuals to the correct phase 70.8% and 57.5% of the time compared with Hartnett's revised methods at 58.1% and 29.7%, respectively, with correctness scores based on one standard deviation of the mean rather than the entire age range. Accuracy and bias scores are significantly improved for Hartnett's revised pubic symphysis method and marginally better for Hartnett's revised fourth rib method, suggesting that the revised mean ages at death of Hartnett's phases better reflect this modern population. Overall, both Hartnett's revised methods are reliable age estimation methods. For the pubic symphysis, there are significant improvements in accuracy and bias scores, especially for older individuals; however, for the fourth rib, the results are comparable to the original İşcan et al. methods, with some improvement for older individuals. © 2014 American Academy of Forensic Sciences.

  9. Reliability of a method of sampling stream invertebrates

    CSIR Research Space (South Africa)

    Chutter, FM

    1966-05-01

    Full Text Available In field ecological studies inferences must often be drawn from dissimilarities in numbers and species of organisms found in biological samples collected at different times and under various conditions....

  10. Summary Report for Evaluation of Compost Sample Drying Methods

    National Research Council Canada - National Science Library

    Frye, Russell

    1994-01-01

    .... Previous work in Support of these efforts developed a compost sample preparation scheme, consisting of air drying followed by milling, to reduce analytical variability in the heterogeneous compost matrix...

  11. Development and application of spatial and temporal statistical methods for unbiased wildlife sampling

    NARCIS (Netherlands)

    Khaemba, W.M.

    2000-01-01

    Current methods of obtaining information on wildlife populations are based on monitoring programmes using periodic surveys. In most cases aerial techniques are applied. Reported numbers are, however, often biased and imprecise, making it difficult to use this information for management

  12. The Difference-in-Difference Method: Assessing the Selection Bias in the Effects of Neighborhood Environment on Health

    Science.gov (United States)

    Grafova, Irina; Freedman, Vicki; Lurie, Nicole; Kumar, Rizie; Rogowski, Jeannette

    2013-01-01

    This paper uses the difference-in-difference estimation approach to explore the self-selection bias in estimating the effect of neighborhood economic environment on self-assessed health among older adults. The results indicate that there is evidence of downward bias in the conventional estimates of the effect of neighborhood economic disadvantage on self-reported health, representing a lower bound of the true effect. PMID:23623818

  13. The effect of sample preparation methods on glass performance

    International Nuclear Information System (INIS)

    Oh, M.S.; Oversby, V.M.

    1990-01-01

    A series of experiments was conducted using SRL 165 synthetic waste glass to investigate the effects of surface preparation and leaching solution composition on the alteration of the glass. Samples of glass with as-cast surfaces produced smooth reaction layers and some evidence for precipitation of secondary phases from solution. Secondary phases were more abundant in samples reacted in deionized water than for those reacted in a silicate solution. Samples with saw-cut surfaces showed a large reduction in surface roughness after 7 days of reaction in either solution. Reaction in silicate solution for up to 91 days produced no further change in surface morphology, while reaction in DIW produced a spongy surface that formed the substrate for further surface layer development. The differences in the surface morphology of the samples may create microclimates that control the details of development of alteration layers on the glass; however, the concentrations of elements in leaching solutions show differences of 50% or less between samples prepared with different surface conditions for tests of a few months duration. 6 refs., 7 figs., 1 tab

  14. Statistical Methods and Tools for Hanford Staged Feed Tank Sampling

    Energy Technology Data Exchange (ETDEWEB)

    Fountain, Matthew S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Brigantic, Robert T. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Peterson, Reid A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2013-10-01

    This report summarizes work conducted by Pacific Northwest National Laboratory to technically evaluate the current approach to staged feed sampling of high-level waste (HLW) sludge to meet waste acceptance criteria (WAC) for transfer from tank farms to the Hanford Waste Treatment and Immobilization Plant (WTP). The current sampling and analysis approach is detailed in the document titled Initial Data Quality Objectives for WTP Feed Acceptance Criteria, 24590-WTP-RPT-MGT-11-014, Revision 0 (Arakali et al. 2011). The goal of this current work is to evaluate and provide recommendations to support a defensible, technical and statistical basis for the staged feed sampling approach that meets WAC data quality objectives (DQOs).

  15. Method for validating radiobiological samples using a linear accelerator

    International Nuclear Information System (INIS)

    Brengues, Muriel; Liu, David; Korn, Ronald; Zenhausern, Frederic

    2014-01-01

    There is an immediate need for rapid triage of the population in case of a large scale exposure to ionizing radiation. Knowing the dose absorbed by the body will allow clinicians to administer medical treatment for the best chance of recovery for the victim. In addition, today's radiotherapy treatment could benefit from additional information regarding the patient's sensitivity to radiation before starting the treatment. As of today, there is no system in place to respond to this demand. This paper will describe specific procedures to mimic the effects of human exposure to ionizing radiation creating the tools for optimization of administered radiation dosimetry for radiotherapy and/or to estimate the doses of radiation received accidentally during a radiation event that could pose a danger to the public. In order to obtain irradiated biological samples to study ionizing radiation absorbed by the body, we performed ex-vivo irradiation of human blood samples using the linear accelerator (LINAC). The LINAC was implemented and calibrated for irradiating human whole blood samples. To test the calibration, a 2 Gy test run was successfully performed on a tube filled with water with an accuracy of 3% in dose distribution. To validate our technique the blood samples were ex-vivo irradiated and the results were analyzed using a gene expression assay to follow the effect of the ionizing irradiation by characterizing dose responsive biomarkers from radiobiological assays. The response of 5 genes was monitored resulting in expression increase with the dose of radiation received. The blood samples treated with the LINAC can provide effective irradiated blood samples suitable for molecular profiling to validate radiobiological measurements via the gene-expression based biodosimetry tools. (orig.)

  16. Method for validating radiobiological samples using a linear accelerator.

    Science.gov (United States)

    Brengues, Muriel; Liu, David; Korn, Ronald; Zenhausern, Frederic

    2014-04-29

    There is an immediate need for rapid triage of the population in case of a large scale exposure to ionizing radiation. Knowing the dose absorbed by the body will allow clinicians to administer medical treatment for the best chance of recovery for the victim. In addition, today's radiotherapy treatment could benefit from additional information regarding the patient's sensitivity to radiation before starting the treatment. As of today, there is no system in place to respond to this demand. This paper will describe specific procedures to mimic the effects of human exposure to ionizing radiation creating the tools for optimization of administered radiation dosimetry for radiotherapy and/or to estimate the doses of radiation received accidentally during a radiation event that could pose a danger to the public. In order to obtain irradiated biological samples to study ionizing radiation absorbed by the body, we performed ex-vivo irradiation of human blood samples using the linear accelerator (LINAC). The LINAC was implemented and calibrated for irradiating human whole blood samples. To test the calibration, a 2 Gy test run was successfully performed on a tube filled with water with an accuracy of 3% in dose distribution. To validate our technique the blood samples were ex-vivo irradiated and the results were analyzed using a gene expression assay to follow the effect of the ionizing irradiation by characterizing dose responsive biomarkers from radiobiological assays. The response of 5 genes was monitored resulting in expression increase with the dose of radiation received. The blood samples treated with the LINAC can provide effective irradiated blood samples suitable for molecular profiling to validate radiobiological measurements via the gene-expression based biodosimetry tools.

  17. A bias-corrected CMIP5 dataset for Africa using the CDF-t method - a contribution to agricultural impact studies

    Science.gov (United States)

    Moise Famien, Adjoua; Janicot, Serge; Delfin Ochou, Abe; Vrac, Mathieu; Defrance, Dimitri; Sultan, Benjamin; Noël, Thomas

    2018-03-01

    The objective of this paper is to present a new dataset of bias-corrected CMIP5 global climate model (GCM) daily data over Africa. This dataset was obtained using the cumulative distribution function transform (CDF-t) method, a method that has been applied to several regions and contexts but never to Africa. Here CDF-t has been applied over the period 1950-2099 combining Historical runs and climate change scenarios for six variables: precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. WFDEI has been used as the reference dataset to correct the GCMs. Evaluation of the results over West Africa has been carried out on a list of priority user-based metrics that were discussed and selected with stakeholders. It includes simulated yield using a crop model simulating maize growth. These bias-corrected GCM data have been compared with another available dataset of bias-corrected GCMs using WATCH Forcing Data as the reference dataset. The impact of WFD, WFDEI, and also EWEMBI reference datasets has been also examined in detail. It is shown that CDF-t is very effective at removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets. This is particularly true for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields. Projections of future yields over West Africa are quite different, depending on the bias-correction method used. However all these projections show a similar relative decreasing trend over the 21st century.

  18. A One-Sample Test for Normality with Kernel Methods

    OpenAIRE

    Kellner , Jérémie; Celisse , Alain

    2015-01-01

    We propose a new one-sample test for normality in a Reproducing Kernel Hilbert Space (RKHS). Namely, we test the null-hypothesis of belonging to a given family of Gaussian distributions. Hence our procedure may be applied either to test data for normality or to test parameters (mean and covariance) if data are assumed Gaussian. Our test is based on the same principle as the MMD (Maximum Mean Discrepancy) which is usually used for two-sample tests such as homogeneity or independence testing. O...

  19. Comparison of indoor air sampling and dust collection methods for fungal exposure assessment using quantitative PCR

    Science.gov (United States)

    Evaluating fungal contamination indoors is complicated because of the many different sampling methods utilized. In this study, fungal contamination was evaluated using five sampling methods and four matrices for results. The five sampling methods were a 48 hour indoor air sample ...

  20. 40 CFR 80.8 - Sampling methods for gasoline and diesel fuel.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Sampling methods for gasoline and... PROGRAMS (CONTINUED) REGULATION OF FUELS AND FUEL ADDITIVES General Provisions § 80.8 Sampling methods for gasoline and diesel fuel. The sampling methods specified in this section shall be used to collect samples...

  1. Comparison of T-Square, Point Centered Quarter, and N-Tree Sampling Methods in Pittosporum undulatum Invaded Woodlands

    Directory of Open Access Journals (Sweden)

    Lurdes Borges Silva

    2017-01-01

    Full Text Available Tree density is an important parameter affecting ecosystems functions and management decisions, while tree distribution patterns affect sampling design. Pittosporum undulatum stands in the Azores are being targeted with a biomass valorization program, for which efficient tree density estimators are required. We compared T-Square sampling, Point Centered Quarter Method (PCQM, and N-tree sampling with benchmark quadrat (QD sampling in six 900 m2 plots established at P. undulatum stands in São Miguel Island. A total of 15 estimators were tested using a data resampling approach. The estimated density range (344–5056 trees/ha was found to agree with previous studies using PCQM only. Although with a tendency to underestimate tree density (in comparison with QD, overall, T-Square sampling appeared to be the most accurate and precise method, followed by PCQM. Tree distribution pattern was found to be slightly aggregated in 4 of the 6 stands. Considering (1 the low level of bias and high precision, (2 the consistency among three estimators, (3 the possibility of use with aggregated patterns, and (4 the possibility of obtaining a larger number of independent tree parameter estimates, we recommend the use of T-Square sampling in P. undulatum stands within the framework of a biomass valorization program.

  2. Rapid methods for measuring radionuclides in food and environmental samples

    International Nuclear Information System (INIS)

    Perkins, Richard W.

    1995-01-01

    The application of ICP/mass spectrometry for the isotopic analysis of environmental samples, the use of drum assayers for measuring radionuclides in food and a rapid procedure for the measurement of the transuranic elements and thorium, performed at the Pacific Northwest Laboratory are discussed

  3. Modern methods of sample preparation for GC analysis

    NARCIS (Netherlands)

    de Koning, S.; Janssen, H.-G.; Brinkman, U.A.Th.

    2009-01-01

    Today, a wide variety of techniques is available for the preparation of (semi-) solid, liquid and gaseous samples, prior to their instrumental analysis by means of capillary gas chromatography (GC) or, increasingly, comprehensive two-dimensional GC (GC × GC). In the past two decades, a large number

  4. an assessment of methods for sampling carabid beetles

    African Journals Online (AJOL)

    Mgina

    collection of epigaeic (ground-dwelling) invertebrates (Southwood and Henderson,. 2000). It has been widely used for sampling carabid beetles in biodiversity inventories. (Niemela et al. 1994, Davies 2000, Nyundo. 2002), population and community ecology. (Greenslade 1968, Refseth, 1980,. Niemela1988, Niemela et al.

  5. Post-Decontamination Vapor Sampling and Analytical Test Methods

    Science.gov (United States)

    2015-08-12

    is decontaminated that could pose an exposure hazard to unprotected personnel. The chemical contaminants may include chemical warfare agents (CWAs... decontamination process. Chemical contaminants can include chemical warfare agents (CWAs) or their simulants, nontraditional agents (NTAs), toxic industrial...a range of test articles from coupons, panels, and small fielded equipment items. 15. SUBJECT TERMS Vapor hazard; vapor sampling; chemical warfare

  6. Vegetation Sampling for Wetland Delineation: A Review and Synthesis of Methods and Sampling Issues

    Science.gov (United States)

    2010-07-01

    which trees are sampled via use of an angle gauge or basal area prism (Husch et al. 2003; Packard and Radtke 2007). Basal area data can be used to...refuges from fungal pathogens for seeds of eastern hemlock (Tsuga canadensis). Ecology 85(1): 284– 289. Packard, K. C., and P. J. Radtke . 2007. Forest

  7. Method for Hot Real-Time Sampling of Pyrolysis Vapors

    Energy Technology Data Exchange (ETDEWEB)

    Pomeroy, Marc D [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-09-29

    Biomass Pyrolysis has been an increasing topic of research, in particular as a replacement for crude oil. This process utilizes moderate temperatures to thermally deconstruct the biomass which is then condensed into a mixture of liquid oxygenates to be used as fuel precursors. Pyrolysis oils contain more than 400 compounds, up to 60 percent of which do not re-volatilize for subsequent chemical analysis. Vapor chemical composition is also complicated as additional condensation reactions occur during the condensation and collection of the product. Due to the complexity of the pyrolysis oil, and a desire to catalytically upgrade the vapor composition before condensation, online real-time analytical techniques such as Molecular Beam Mass Spectrometry (MBMS) are of great use. However, in order to properly sample hot pyrolysis vapors, many challenges must be overcome. Sampling must occur within a narrow range of temperatures to reduce product composition changes from overheating or partial condensation or plugging of lines from condensed products. Residence times must be kept at a minimum to reduce further reaction chemistries. Pyrolysis vapors also form aerosols that are carried far downstream and can pass through filters resulting in build-up in downstream locations. The co-produced bio-char and ash from the pyrolysis process can lead to plugging of the sample lines, and must be filtered out at temperature, even with the use of cyclonic separators. A practical approach for considerations and sampling system design, as well as lessons learned are integrated into the hot analytical sampling system of the National Renewable Energy Laboratory's (NREL) Thermochemical Process Development Unit (TCPDU) to provide industrially relevant demonstrations of thermochemical transformations of biomass feedstocks at the pilot scale.

  8. A New Method for Re-Analyzing Evaluation Bias: Piecewise Growth Curve Modeling Reveals an Asymmetry in the Evaluation of Pro and Con Arguments.

    Directory of Open Access Journals (Sweden)

    Jens Jirschitzka

    Full Text Available In four studies we tested a new methodological approach to the investigation of evaluation bias. The usage of piecewise growth curve modeling allowed for investigation into the impact of people's attitudes on their persuasiveness ratings of pro- and con-arguments, measured over the whole range of the arguments' polarity from an extreme con to an extreme pro position. Moreover, this method provided the opportunity to test specific hypotheses about the course of the evaluation bias within certain polarity ranges. We conducted two field studies with users of an existing online information portal (Studies 1a and 2a as participants, and two Internet laboratory studies with mostly student participants (Studies 1b and 2b. In each of these studies we presented pro- and con-arguments, either for the topic of MOOCs (massive open online courses, Studies 1a and 1b or for the topic of M-learning (mobile learning, Studies 2a and 2b. Our results indicate that using piecewise growth curve models is more appropriate than simpler approaches. An important finding of our studies was an asymmetry of the evaluation bias toward pro- or con-arguments: the evaluation bias appeared over the whole polarity range of pro-arguments and increased with more and more extreme polarity. This clear-cut result pattern appeared only on the pro-argument side. For the con-arguments, in contrast, the evaluation bias did not feature such a systematic picture.

  9. Familial transmission of a body-related attentional bias - An eye-tracking study in a nonclinical sample of female adolescents and their mothers.

    Directory of Open Access Journals (Sweden)

    Anika Bauer

    Full Text Available Previous research indicates that body image disturbance is transmitted from mother to daughter via modeling of maternal body-related behaviors and attitudes (indirect transmission and via maternal body-related feedback (direct transmission. So far, the transmission of body-related attentional biases, which according to cognitive-behavioral theories play a prominent role in the development and maintenance of eating disorders, has not been analyzed. The current eye-tracking study applied the concepts of direct and indirect transmission to body-related attentional biases by examining body-related viewing patterns on self- and other-pictures within mother-daughter dyads.Eye movements of N = 82 participants (n = 41 healthy female adolescents, mean age 15.82 years, SD = 1.80, and their mothers, mean age 47.78 years, SD = 4.52 were recorded while looking at whole-body pictures of themselves and a control peer. Based on fixations on self-defined attractive and unattractive body areas, visual attention bias scores were calculated for mothers and daughters, representing the pattern of body-related attention allocation. Based on mothers' fixations on their own daughter's and the adolescent peer's body, a second visual attention bias score was calculated, reflecting the mothers' viewing pattern on their own daughter.Analysis of variance revealed an attentional bias for self-defined unattractive body areas in adolescents. The girls' visual attention bias score correlated significantly with their mothers' bias score, indicating indirect transmission, and with their mothers' second bias score, indicating direct transmission. Moreover, the girls' bias score correlated significantly with negative body-related feedback from their mothers.Female adolescents show a deficit-oriented attentional bias for one's own and a peer's body. The correlated body-related attention patterns imply that attentional biases might be transmitted directly and indirectly from mothers

  10. Air sampling methods to evaluate microbial contamination in operating theatres: results of a comparative study in an orthopaedics department.

    Science.gov (United States)

    Napoli, C; Tafuri, S; Montenegro, L; Cassano, M; Notarnicola, A; Lattarulo, S; Montagna, M T; Moretti, B

    2012-02-01

    To evaluate the level of microbial contamination of air in operating theatres using active [i.e. surface air system (SAS)] and passive [i.e. index of microbial air contamination (IMA) and nitrocellulose membranes positioned near the wound] sampling systems. Sampling was performed between January 2010 and January 2011 in the operating theatre of the orthopaedics department in a university hospital in Southern Italy. During surgery, the mean bacterial loads recorded were 2232.9 colony-forming units (cfu)/m(2)/h with the IMA method, 123.2 cfu/m(3) with the SAS method and 2768.2 cfu/m(2)/h with the nitrocellulose membranes. Correlation was found between the results of the three methods. Staphylococcus aureus was detected in 12 of 60 operations (20%) with the membranes, five (8.3%) operations with the SAS method, and three operations (5%) with the IMA method. Use of nitrocellulose membranes placed near a wound is a valid method for measuring the microbial contamination of air. This method was more sensitive than the IMA method and was not subject to any calibration bias, unlike active air monitoring systems. Copyright © 2011 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

  11. Method for spiking soil samples with organic compounds

    DEFF Research Database (Denmark)

    Brinch, Ulla C; Ekelund, Flemming; Jacobsen, Carsten S

    2002-01-01

    We examined the harmful side effects on indigenous soil microorganisms of two organic solvents, acetone and dichloromethane, that are normally used for spiking of soil with polycyclic aromatic hydrocarbons for experimental purposes. The solvents were applied in two contamination protocols to either...... higher than in control soil, probably due mainly to release of predation from indigenous protozoa. In order to minimize solvent effects on indigenous soil microorganisms when spiking native soil samples with compounds having a low water solubility, we propose a common protocol in which the contaminant...... tagged with luxAB::Tn5. For both solvents, application to the whole sample resulted in severe side effects on both indigenous protozoa and bacteria. Application of dichloromethane to the whole soil volume immediately reduced the number of protozoa to below the detection limit. In one of the soils...

  12. Exploring biomolecular dynamics and interactions using advanced sampling methods

    International Nuclear Information System (INIS)

    Luitz, Manuel; Bomblies, Rainer; Ostermeir, Katja; Zacharias, Martin

    2015-01-01

    Molecular dynamics (MD) and Monte Carlo (MC) simulations have emerged as a valuable tool to investigate statistical mechanics and kinetics of biomolecules and synthetic soft matter materials. However, major limitations for routine applications are due to the accuracy of the molecular mechanics force field and due to the maximum simulation time that can be achieved in current simulations studies. For improving the sampling a number of advanced sampling approaches have been designed in recent years. In particular, variants of the parallel tempering replica-exchange methodology are widely used in many simulation studies. Recent methodological advancements and a discussion of specific aims and advantages are given. This includes improved free energy simulation approaches and conformational search applications. (topical review)

  13. A machine learning model with human cognitive biases capable of learning from small and biased datasets.

    Science.gov (United States)

    Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro

    2018-05-09

    Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.

  14. Sample preparation method for induced mutation on orchid

    International Nuclear Information System (INIS)

    Suhaimi Musa; Sakinah Ariffin

    2005-01-01

    Studies on the induction of mutation in Dendrobium orchid at MINT has produced a number of new orchid mutant cultivars. Tissue culture techniques on orchid seeds and meristem cloning are employed in preparing the samples for the mutation induction. Solid medium based on the Murashige and Skoog (1962) and liquid medium based on Vacin and Went (1949) were found to be suitable in producing protocorm like bodies (PLBs) that are required for the irradiation treatment. (Author)

  15. Improvement of correlated sampling Monte Carlo methods for reactivity calculations

    International Nuclear Information System (INIS)

    Nakagawa, Masayuki; Asaoka, Takumi

    1978-01-01

    Two correlated Monte Carlo methods, the similar flight path and the identical flight path methods, have been improved to evaluate up to the second order change of the reactivity perturbation. Secondary fission neutrons produced by neutrons having passed through perturbed regions in both unperturbed and perturbed systems are followed in a way to have a strong correlation between secondary neutrons in both the systems. These techniques are incorporated into the general purpose Monte Carlo code MORSE, so as to be able to estimate also the statistical error of the calculated reactivity change. The control rod worths measured in the FCA V-3 assembly are analyzed with the present techniques, which are shown to predict the measured values within the standard deviations. The identical flight path method has revealed itself more useful than the similar flight path method for the analysis of the control rod worth. (auth.)

  16. Summary Report for Evaluation of Compost Sample Drying Methods

    National Research Council Canada - National Science Library

    Frye, Russell

    1994-01-01

    The U.S. Army Environmental Center (USAEC), formerly the U.S. Army Toxic and Hazardous Materials Agency, has evaluated composting methods for treatment of explosive-contaminated soils and sediments at Army installations...

  17. The method of Sample Management in Neutron Activation Analysis Laboratory-Serpong

    International Nuclear Information System (INIS)

    Elisabeth-Ratnawati

    2005-01-01

    In the testing laboratory used by neutron activation analysis method, sample preparation is the main factor and it can't be neglect. The error in the sample preparation can give result with lower accuracy. In this article is explained the scheme of sample preparation i.e sample receive administration, the separate of sample, fluid and solid sample preparation, sample grouping, irradiation, sample counting and holding the sample post irradiation. If the management of samples were good application based on Standard Operation Procedure, therefore each samples has good traceability. To optimize the management of samples is needed the trained and skilled personal and good facility. (author)

  18. Methodical bias for comparison of periodontal ligament injection and local infiltration anesthesia for routine extractions in the maxilla

    Directory of Open Access Journals (Sweden)

    Kämmerer PW

    2018-03-01

    Full Text Available Peer W Kämmerer, Monika Daubländer Department of Oral, Maxillofacial and Facial Plastic Surgery, University Medical Centre Mainz, Mainz, GermanyWe read the article by Al-Shayyab1 with great interest, though we think that there is a methodical bias. Usage of standard dental syringes with 27-gauge needles is not recommended for periodontal ligament (PDL injections as they are very unlikely to achieve the correct pressure needed for successful single tooth anesthesia. In accordance with this, specialized syringes with short 30-gauge needles are commonly used all over the literature.2 The author addresses this in the “Discussion” section and writes that “a standard conventional dental syringe was used in the present study, not a special PDL syringe, since the former is readily available in the clinic and proves equally successful when a standard 27-gauge short needle was used,” citing Malamed from 1982 (a time during which the modern PDL syringes were not developed yet3 and Madan et al who write that “intraligamentary injection technique is equally effective when a standard 27-gauge needle is used”.4 The second assumption refers to the needle only, not the syringe. In addition, this needle issue is not proven by any reference or study. Therefore, one might come to the conclusion that PDL was not carried out correctly. Also, the authors did not evaluate pulp or tissue anesthesia and started the extraction procedure after a latency period of 5 minutes in all cases. In accordance with this, the success rates of the PDL injection cannot be given, but would be of interest.View the original paper by Al-Shayyab and colleagues.

  19. On the computational assessment of white matter hyperintensity progression: difficulties in method selection and bias field correction performance on images with significant white matter pathology

    Energy Technology Data Exchange (ETDEWEB)

    Valdes Hernandez, Maria del C.; Gonzalez-Castro, Victor; Wang, Xin; Doubal, Fergus; Munoz Maniega, Susana; Wardlaw, Joanna M. [Centre for Clinical Brian Sciences, Department of Neuroimaging Sciences, Edinburgh (United Kingdom); Ghandour, Dina T. [University of Edinburgh, College of Medicine and Veterinary Medicine, Edinburgh (United Kingdom); Armitage, Paul A. [University of Sheffield, Department of Cardiovascular Sciences, Sheffield (United Kingdom)

    2016-05-15

    Subtle inhomogeneities in the scanner's magnetic fields (B{sub 0} and B{sub 1}) alter the intensity levels of the structural magnetic resonance imaging (MRI) affecting the volumetric assessment of WMH changes. Here, we investigate the influence that (1) correcting the images for the B{sub 1} inhomogeneities (i.e. bias field correction (BFC)) and (2) selection of the WMH change assessment method can have on longitudinal analyses of WMH progression and discuss possible solutions. We used brain structural MRI from 46 mild stroke patients scanned at stroke onset and 3 years later. We tested three BFC approaches: FSL-FAST, N4 and exponentially entropy-driven homomorphic unsharp masking (E{sup 2}D-HUM) and analysed their effect on the measured WMH change. Separately, we tested two methods to assess WMH changes: measuring WMH volumes independently at both time points semi-automatically (MCMxxxVI) and subtracting intensity-normalised FLAIR images at both time points following image gamma correction. We then combined the BFC with the computational method that performed best across the whole sample to assess WMH changes. Analysis of the difference in the variance-to-mean intensity ratio in normal tissue between BFC and uncorrected images and visual inspection showed that all BFC methods altered the WMH appearance and distribution, but FSL-FAST in general performed more consistently across the sample and MRI modalities. The WMH volume change over 3 years obtained with MCMxxxVI with vs. without FSL-FAST BFC did not significantly differ (medians(IQR)(with BFC) = 3.2(6.3) vs. 2.9(7.4)ml (without BFC), p = 0.5), but both differed significantly from the WMH volume change obtained from subtracting post-processed FLAIR images (without BFC)(7.6(8.2)ml, p < 0.001). This latter method considerably inflated the WMH volume change as subtle WMH at baseline that became more intense at follow-up were counted as increase in the volumetric change. Measurement of WMH volume change remains

  20. Two methods of self-sampling compared to clinician sampling to detect reproductive tract infections in Gugulethu, South Africa

    NARCIS (Netherlands)

    van de Wijgert, Janneke; Altini, Lydia; Jones, Heidi; de Kock, Alana; Young, Taryn; Williamson, Anna-Lise; Hoosen, Anwar; Coetzee, Nicol

    2006-01-01

    To assess the validity, feasibility, and acceptability of 2 methods of self-sampling compared to clinician sampling during a speculum examination. To improve screening for reproductive tract infections (RTIs) in resource-poor settings. In a public clinic in Cape Town, 450 women underwent a speculum

  1. A simulation study of how simple mark-recapture methods can be combined with destructive sub-sampling to facilitate surveys of flying insects

    DEFF Research Database (Denmark)

    Nachman, Gøsta Støger; Skovgård, Henrik; Pedersen, Henrik Skovgård

    2012-01-01

    Mark-recapture techniques are used for studies of animal populations. With only three sampling occasions, both Bailey's triple-catch (BTC) and Jolly-Seber's (J-S) stochastic method can be applied. As marking and handling of fragile organisms may harm them, and thereby affect their chances of being...... to compare the subsampling method with the ordinary mark-recapture methods. Model-generated populations were sampled with and without subsampling to provide estimates of population size, loss, and dilution rates. The estimated parameters were compared with their true values to identify biases associated...... with the sampling methods, using 81 different combinations of population size, dilution rate, loss rate, and sampling effort. Each combination was replicated 1,000 times. In no cases did subsampling perform more poorly than the ordinary methods. J-S was slightly more accurate than BTC to estimate the population...

  2. Comparison of methods for the quantification of the different carbon fractions in atmospheric aerosol samples

    Science.gov (United States)

    Nunes, Teresa; Mirante, Fátima; Almeida, Elza; Pio, Casimiro

    2010-05-01

    to evaluate the possibility of continue using, for trend analysis, the historical data set, we performed an inter-comparison between our method and an adaptation of EUSAAR-2 protocol, taking into account that this last protocol will possibly be recommended for analysing carbonaceous aerosols at European sites. In this inter-comparison we tested different types of samples (PM2,5, PM2,5-10, PM10) with large spectra of carbon loadings, with and without pre-treatment acidification. For a reduced number of samples, five replicates of each one were analysed by each method for statistical purposes. The inter-comparison study revealed that when the sample analysis were performed in similar room conditions, the two thermo-optic methods give similar results for TC, OC and EC, without significant differences at a 95% confidence level. The correlation between the methods, DAO and EUSAAR-2 for EC is smaller than for TC and OC, although showing a coefficient correlation over 0,95, with a slope close to one. For samples performed in different periods, room temperatures seem to have a significant effect over OC quantification. The sample pre-treatment with HCl fumigation tends to decrease TC quantification, mainly due to the more volatile organic fraction release during the first heating step. For a set of 20 domestic biomass burning samples analyzed by the DAO method we observed an average decrease in TC quantification of 3,7 % in relation to non-acidified samples, even though this decrease is accompanied by an average increase in the less volatile organic fraction. The indirect measurement of carbon carbonate, usually a minor carbon component in the carbonaceous aerosol, based on the difference between TC measured by TOM of acidified and non-acidified samples is not a robust measurement, considering the biases affecting his quantification. The present study show that the two thermo-optic temperature program used for OC and EC quantification give similar results, and if in the

  3. Genetic analysis of bulimia nervosa: methods and sample description.

    Science.gov (United States)

    Kaye, Walter H; Devlin, Bernie; Barbarich, Nicole; Bulik, Cynthia M; Thornton, Laura; Bacanu, Silviu-Alin; Fichter, Manfred M; Halmi, Katherine A; Kaplan, Allan S; Strober, Michael; Woodside, D Blake; Bergen, Andrew W; Crow, Scott; Mitchell, James; Rotondo, Alessandro; Mauri, Mauro; Cassano, Giovanni; Keel, Pamela; Plotnicov, Katherine; Pollice, Christine; Klump, Kelly L; Lilenfeld, Lisa R; Ganjei, J Kelly; Quadflieg, Norbert; Berrettini, Wade H

    2004-05-01

    Twin and family studies suggest that genetic variants contribute to the pathogenesis of bulimia nervosa (BN) and anorexia nervosa (AN). The Price Foundation has supported an international, multisite study of families with these disorders to identify these genetic variations. The current study presents the clinical characteristics of this sample as well as a description of the study methodology. All probands met modified criteria for BN or bulimia nervosa with a history of AN (BAN) as defined in the 4th ed. of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association, 1994). All affected relatives met DSM-IV criteria for BN, AN, BAN, or eating disorders not otherwise specified (EDNOS). Probands and affected relatives were assessed diagnostically using both trained-rater and self-report assessments. DNA samples were collected from probands, affected relatives, and available biologic parents. Assessments were obtained from 163 BN probands and 165 BAN probands. Overall, there were 365 relative pairs available for linkage analysis. Of the affected relatives of BN probands, 62 were diagnosed as BN (34.8%), 49 as BAN (27.5%), 35 as AN (19.7%), and 32 as EDNOS (18.0%). For the relatives of BAN probands, 42 were diagnosed as BN (22.5%), 67 as BAN (35.8%), 48 as AN (25.7%), and 30 as EDNOS (16.0%). This study represents the largest genetic study of eating disorders to date. Clinical data indicate that although there are a large number of individuals with BN disorders, a range of eating pathology is represented in the sample, allowing for the examination of several different phenotypes in molecular genetic analyses. Copyright 2004 by Wiley Periodicals, Inc. Int J Eat Disord 35: 556-570, 2004.

  4. Efficient Multilevel and Multi-index Sampling Methods in Stochastic Differential Equations

    KAUST Repository

    Haji-Ali, Abdul Lateef

    2016-05-22

    Most problems in engineering and natural sciences involve parametric equations in which the parameters are not known exactly due to measurement errors, lack of measurement data, or even intrinsic variability. In such problems, one objective is to compute point or aggregate values, called “quantities of interest”. A rapidly growing research area that tries to tackle this problem is Uncertainty Quantification (UQ). As the name suggests, UQ aims to accurately quantify the uncertainty in quantities of interest. To that end, the approach followed in this thesis is to describe the parameters using probabilistic measures and then to employ probability theory to approximate the probabilistic information of the quantities of interest. In this approach, the parametric equations must be accurately solved for multiple values of the parameters to explore the dependence of the quantities of interest on these parameters, using various so-called “sampling methods”. In almost all cases, the parametric equations cannot be solved exactly and suitable numerical discretization methods are required. The high computational complexity of these numerical methods coupled with the fact that the parametric equations must be solved for multiple values of the parameters make UQ problems computationally intensive, particularly when the dimensionality of the underlying problem and/or the parameter space is high. This thesis is concerned with optimizing existing sampling methods and developing new ones. Starting with the Multilevel Monte Carlo (MLMC) estimator, we first prove its normality using the Lindeberg-Feller CLT theorem. We then design the Continuation Multilevel Monte Carlo (CMLMC) algorithm that efficiently approximates the parameters required to run MLMC. We also optimize the hierarchies of one-dimensional discretization parameters that are used in MLMC and analyze the tolerance splitting parameter between the statistical error and the bias constraints. An important contribution

  5. Designing waveforms for temporal encoding using a frequency sampling method

    DEFF Research Database (Denmark)

    Gran, Fredrik; Jensen, Jørgen Arendt

    2007-01-01

    was compared to a linear frequency modulated signal with amplitude tapering, previously used in clinical studies for synthetic transmit aperture imaging. The latter had a relatively flat spectrum which implied that the waveform tried to excite all frequencies including ones with low amplification. The proposed......In this paper a method for designing waveforms for temporal encoding in medical ultrasound imaging is described. The method is based on least squares optimization and is used to design nonlinear frequency modulated signals for synthetic transmit aperture imaging. By using the proposed design method...... waveform, on the other hand, was designed so that only frequencies where the transducer had a large amplification were excited. Hereby, unnecessary heating of the transducer could be avoided and the signal-tonoise ratio could be increased. The experimental ultrasound scanner RASMUS was used to evaluate...

  6. Bias aware Kalman filters

    DEFF Research Database (Denmark)

    Drecourt, J.-P.; Madsen, H.; Rosbjerg, Dan

    2006-01-01

    This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model state....... The colored noise filter formulation is extended to correct both time correlated and uncorrelated model error components. A more stable version of the separate filter without feedback is presented. The filters are implemented in an ensemble framework using Latin hypercube sampling. The techniques...... are illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 2005 Elsevier Ltd. All rights reserved....

  7. A destructive sample preparation method for radioactive waste characterization

    International Nuclear Information System (INIS)

    Olteanu, M.; Bucur, C.

    2015-01-01

    Acid digestion, using the microwave power, was applied for ''dissolution'' of different materials corresponding to the radioactive waste matrices resulted from a nuclear power plant operation, including exchange resin (cationic and mixed), concrete, paper, textile and activated charcoals. A small aliquot of solid sample (0.1-0.5g) was mixed with a known volume of digestion reagents (HNO3 67% - H2O2 30% or HNO3 67% - HCl 37%, with HF addition if the SiO2 was present in matrices) in a 100 ml PTFE vessel and it was mineralized using a Berghof digestion system, Speedwave 4. Starting from the manufacturer procedures, the technical parameters (temperature and mineralization time), the types and quantities of digestion reagents were optimized. After the mineralization process, the samples were transferred in centrifuge tubes, separated at 3500 rot/min and visually analysed. The obtained solutions were clear, without suspended or deposed materials and separated phases, ready for future separation processes of the ''difficult to measure'' radioisotopes. (authors)

  8. COMPARISON OF LARGE RIVER SAMPLING METHODS ON ALGAL METRICS

    Science.gov (United States)

    We compared the results of four methods used to assess the algal communities at 60 sites distributed among four rivers. Based on Principle Component Analysis of physical habitat data collected concomitantly with the algal data, sites were separated into those with a mean thalweg...

  9. COMPARISON OF LARGE RIVER SAMPLING METHOD USING DIATOM METRICS

    Science.gov (United States)

    We compared the results of four methods used to assess the algal communities at 60 sites distributed among four rivers. Based on Principle Component Analysis of physical habitat data collected concomitantly with the algal data, sites were separated into those with a mean thalweg...

  10. Sample preparation method for ICP-MS measurement of 99Tc in a large amount of environmental samples

    International Nuclear Information System (INIS)

    Kondo, M.