Network Structure and Biased Variance Estimation in Respondent Driven Sampling

PubMed Central

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. PMID:26679927

Adaptive Biasing Combined with Hamiltonian Replica Exchange to Improve Umbrella Sampling Free Energy Simulations.

PubMed

Zeller, Fabian; Zacharias, Martin

2014-02-11

The accurate calculation of potentials of mean force for ligand-receptor binding is one of the most important applications of molecular simulation techniques. Typically, the separation distance between ligand and receptor is chosen as a reaction coordinate along which a PMF can be calculated with the aid of umbrella sampling (US) techniques. In addition, restraints can be applied on the relative position and orientation of the partner molecules to reduce accessible phase space. An approach combining such phase space reduction with flattening of the free energy landscape and configurational exchanges has been developed, which significantly improves the convergence of PMF calculations in comparison with standard umbrella sampling. The free energy surface along the reaction coordinate is smoothened by iteratively adapting biasing potentials corresponding to previously calculated PMFs. Configurations are allowed to exchange between the umbrella simulation windows via the Hamiltonian replica exchange method. The application to a DNA molecule in complex with a minor groove binding ligand indicates significantly improved convergence and complete reversibility of the sampling along the pathway. The calculated binding free energy is in excellent agreement with experimental results. In contrast, the application of standard US resulted in large differences between PMFs calculated for association and dissociation pathways. The approach could be a useful alternative to standard US for computational studies on biomolecular recognition processes.

Sources of Sampling Bias in Long-Screened Well

EPA Science Inventory

Results obtained from ground-water sampling in long-screened wells are often influenced by physical factors such as geologic heterogeneity and vertical hydraulic gradients. These factors often serve to bias results and increase uncertainty in the representativeness of the sample...

Sampling Biases in MODIS and SeaWiFS Ocean Chlorophyll Data

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Casey, Nancy W.

2007-01-01

Although modem ocean color sensors, such as MODIS and SeaWiFS are often considered global missions, in reality it takes many days, even months, to sample the ocean surface enough to provide complete global coverage. The irregular temporal sampling of ocean color sensors can produce biases in monthly and annual mean chlorophyll estimates. We quantified the biases due to sampling using data assimilation to create a "truth field", which we then sub-sampled using the observational patterns of MODIS and SeaWiFS. Monthly and annual mean chlorophyll estimates from these sub-sampled, incomplete daily fields were constructed and compared to monthly and annual means from the complete daily fields of the assimilation model, at a spatial resolution of 1.25deg longitude by 0.67deg latitude. The results showed that global annual mean biases were positive, reaching nearly 8% (MODIS) and >5% (SeaWiFS). For perspective the maximum interannual variability in the SeaWiFS chlorophyll record was about 3%. Annual mean sampling biases were low (<3%) in the midlatitudes (between -40deg and 40deg). Low interannual variability in the global annual mean sampling biases suggested that global scale trend analyses were valid. High latitude biases were much higher than the global annual means, up to 20% as a basin annual mean, and over 80% in some months. This was the result of the high solar zenith angle exclusion in the processing algorithms. Only data where the solar angle is <75deg are permitted, in contrast to the assimilation which samples regularly over the entire area and month. High solar zenith angles do not facilitate phytoplankton photosynthesis and consequently low chlorophyll concentrations occurring here are missed by the data sets. Ocean color sensors selectively sample in locations and times of favorable phytoplankton growth, producing overestimates of chlorophyll. The biases derived from lack of sampling in the high latitudes varied monthly, leading to artifacts in the apparent

The late Neandertal supraorbital fossils from Vindija Cave, Croatia: a biased sample?

PubMed

Ahern, James C M; Lee, Sang-Hee; Hawks, John D

2002-09-01

The late Neandertal sample from Vindija (Croatia) has been described as transitional between the earlier Central European Neandertals from Krapina (Croatia) and modern humans. However, the morphological differences indicating this transition may rather be the result of different sex and/or age compositions between the samples. This study tests the hypothesis that the metric differences between the Krapina and Vindija supraorbital samples are due to sampling bias. We focus upon the supraorbital region because past studies have posited this region as particularly indicative of the Vindija sample's transitional nature. Furthermore, the supraorbital region varies significantly with both age and sex. We analyzed four chords and two derived indices of supraorbital torus form as defined by Smith & Ranyard (1980, Am. J. phys. Anthrop.93, pp. 589-610). For each variable, we analyzed relative sample bias of the Krapina and Vindija samples using three sampling methods. In order to test the hypothesis that the Vindija sample contains an over-representation of females and/or young while the Krapina sample is normal or also female/young biased, we determined the probability of drawing a sample of the same size as and with a mean equal to or less than Vindija's from a Krapina-based population. In order to test the hypothesis that the Vindija sample is female/young biased while the Krapina sample is male/old biased, we determined the probability of drawing a sample of the same size as and with a mean equal or less than Vindija's from a generated population whose mean is halfway between Krapina's and Vindija's. Finally, in order to test the hypothesis that the Vindija sample is normal while the Krapina sample contains an over-representation of males and/or old, we determined the probability of drawing a sample of the same size as and with a mean equal to or greater than Krapina's from a Vindija-based population. Unless we assume that the Vindija sample is female/young and the

Collecting a better water-quality sample: Reducing vertical stratification bias in open and closed channels

USGS Publications Warehouse

Selbig, William R.

2017-01-01

Collection of water-quality samples that accurately characterize average particle concentrations and distributions in channels can be complicated by large sources of variability. The U.S. Geological Survey (USGS) developed a fully automated Depth-Integrated Sample Arm (DISA) as a way to reduce bias and improve accuracy in water-quality concentration data. The DISA was designed to integrate with existing autosampler configurations commonly used for the collection of water-quality samples in vertical profile thereby providing a better representation of average suspended sediment and sediment-associated pollutant concentrations and distributions than traditional fixed-point samplers. In controlled laboratory experiments, known concentrations of suspended sediment ranging from 596 to 1,189 mg/L were injected into a 3 foot diameter closed channel (circular pipe) with regulated flows ranging from 1.4 to 27.8 ft3 /s. Median suspended sediment concentrations in water-quality samples collected using the DISA were within 7 percent of the known, injected value compared to 96 percent for traditional fixed-point samplers. Field evaluation of this technology in open channel fluvial systems showed median differences between paired DISA and fixed-point samples to be within 3 percent. The range of particle size measured in the open channel was generally that of clay and silt. Differences between the concentration and distribution measured between the two sampler configurations could potentially be much larger in open channels that transport larger particles, such as sand.

Adaptive enhanced sampling by force-biasing using neural networks

NASA Astrophysics Data System (ADS)

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.

Field reversed configuration confinement enhancement through edge biasing and neutral beam injection.

PubMed

Tuszewski, M; Smirnov, A; Thompson, M C; Korepanov, S; Akhmetov, T; Ivanov, A; Voskoboynikov, R; Schmitz, L; Barnes, D; Binderbauer, M W; Brown, R; Bui, D Q; Clary, R; Conroy, K D; Deng, B H; Dettrick, S A; Douglass, J D; Garate, E; Glass, F J; Gota, H; Guo, H Y; Gupta, D; Gupta, S; Kinley, J S; Knapp, K; Longman, A; Hollins, M; Li, X L; Luo, Y; Mendoza, R; Mok, Y; Necas, A; Primavera, S; Ruskov, E; Schroeder, J H; Sevier, L; Sibley, A; Song, Y; Sun, X; Trask, E; Van Drie, A D; Walters, J K; Wyman, M D

2012-06-22

Field reversed configurations (FRCs) with high confinement are obtained in the C-2 device by combining plasma gun edge biasing and neutral beam injection. The plasma gun creates an inward radial electric field that counters the usual FRC spin-up. The n = 2 rotational instability is stabilized without applying quadrupole magnetic fields. The FRCs are nearly axisymmetric, which enables fast ion confinement. The plasma gun also produces E × B shear in the FRC edge layer, which may explain the observed improved particle transport. The FRC confinement times are improved by factors 2 to 4, and the plasma lifetimes are extended from 1 to up to 4 ms.

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

NASA Astrophysics Data System (ADS)

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

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

Treesearch

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...

Bootstrap Estimation of Sample Statistic Bias in Structural Equation Modeling.

ERIC Educational Resources Information Center

Thompson, Bruce; Fan, Xitao

This study empirically investigated bootstrap bias estimation in the area of structural equation modeling (SEM). Three correctly specified SEM models were used under four different sample size conditions. Monte Carlo experiments were carried out to generate the criteria against which bootstrap bias estimation should be judged. For SEM fit indices,…

Specific and Non-Specific Protein Association in Solution: Computation of Solvent Effects and Prediction of First-Encounter Modes for Efficient Configurational Bias Monte Carlo Simulations

PubMed Central

Cardone, Antonio; Pant, Harish; Hassan, Sergio A.

2013-01-01

Weak and ultra-weak protein-protein association play a role in molecular recognition, and can drive spontaneous self-assembly and aggregation. Such interactions are difficult to detect experimentally, and are a challenge to the force field and sampling technique. A method is proposed to identify low-population protein-protein binding modes in aqueous solution. The method is designed to identify preferential first-encounter complexes from which the final complex(es) at equilibrium evolves. A continuum model is used to represent the effects of the solvent, which accounts for short- and long-range effects of water exclusion and for liquid-structure forces at protein/liquid interfaces. These effects control the behavior of proteins in close proximity and are optimized based on binding enthalpy data and simulations. An algorithm is described to construct a biasing function for self-adaptive configurational-bias Monte Carlo of a set of interacting proteins. The function allows mixing large and local changes in the spatial distribution of proteins, thereby enhancing sampling of relevant microstates. The method is applied to three binary systems. Generalization to multiprotein complexes is discussed. PMID:24044772

On sampling biases arising from insufficient bottle flushing

NASA Astrophysics Data System (ADS)

Codispoti, L. A.; Paver, C. R.

2016-02-01

Collection of representative water samples using carousel bottles is important for accurately determining biological and chemical gradients. The development of more technologically advanced instrumentation and sampling apparatus causes sampling packages to increase and "soak times" to decrease, increasing the probability that insufficient bottle flushing will produce biased results. Qualitative evidence from various expeditions suggest that insufficient flushing may be a problem. Here we report on multiple field experiments that were conducted to better quantify the errors that can arise from insufficient bottle flushing. Our experiments suggest that soak times of more than 2 minutes are sometimes required to collect a representative sample.

Control of ion gyroscale fluctuations via electrostatic biasing and sheared E×B flow in the C-2 field reversed configuration

NASA Astrophysics Data System (ADS)

Schmitz, L.; Ruskov, E.; Deng, B. H.; Binderbauer, M.; Tajima, T.; Gota, H.; Tuszewski, M.

2016-03-01

Control of radial particle and thermal transport is instrumental for achieving and sustaining well-confined high-β plasma in a Field-Reversed Configuration (FRC). Radial profiles of low frequency ion gyro-scale density fluctuations (0.5≤kρs≤40), consistent with drift- or drift-interchange modes, have been measured in the scrape-off layer (SOL) and core of the C-2 Field-Reversed Configuration (FRC), together with the toroidal E×B velocity. It is shown here that axial electrostatic SOL biasing controls and reduces gyro-scale density fluctuations, resulting in very low FRC core fluctuation levels. When the radial E×B flow shearing rate decreases below the turbulence decorrelation rate, fluctuation levels increase substantially, concomitantly with onset of the n=2 instability and rapid loss of diamagnetism. Low turbulence levels, improved energy/particle confinement and substantially increased FRC life times are achieved when E×B shear near the separatrix is maintained via axial SOL biasing using an annular washer gun.

Sampling bias in blending validation and a different approach to homogeneity assessment.

PubMed

Kraemer, J; Svensson, J R; Melgaard, H

1999-02-01

Sampling of batches studied for validation is reported. A thief particularly suited for granules, rather than cohesive powders, was used in the study. It is shown, as has been demonstrated in the past, that traditional 1x to 3x thief sampling of a blend is biased, and that the bias decreases as the sample size increases. It is shown that taking 50 samples of tablets after blending and testing this subpopulation for normality is a discriminating manner of testing for homogeneity. As a criterion, it is better than sampling at mixer or drum stage would be even if an unbiased sampling device were available.

Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach

PubMed Central

Risso, Davide; Taglioli, Luca; De Iasio, Sergio; Gueresi, Paola; Alfani, Guido; Nelli, Sergio; Rossi, Paolo; Paoli, Giorgio; Tofanelli, Sergio

2015-01-01

This research is the first empirical attempt to calculate the various components of the hidden bias associated with the sampling strategies routinely-used in human genetics, with special reference to surname-based strategies. We reconstructed surname distributions of 26 Italian communities with different demographic features across the last six centuries (years 1447–2001). The degree of overlapping between "reference founding core" distributions and the distributions obtained from sampling the present day communities by probabilistic and selective methods was quantified under different conditions and models. When taking into account only one individual per surname (low kinship model), the average discrepancy was 59.5%, with a peak of 84% by random sampling. When multiple individuals per surname were considered (high kinship model), the discrepancy decreased by 8–30% at the cost of a larger variance. Criteria aimed at maximizing locally-spread patrilineages and long-term residency appeared to be affected by recent gene flows much more than expected. Selection of the more frequent family names following low kinship criteria proved to be a suitable approach only for historically stable communities. In any other case true random sampling, despite its high variance, did not return more biased estimates than other selective methods. Our results indicate that the sampling of individuals bearing historically documented surnames (founders' method) should be applied, especially when studying the male-specific genome, to prevent an over-stratification of ancient and recent genetic components that heavily biases inferences and statistics. PMID:26452043

Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach.

PubMed

Risso, Davide; Taglioli, Luca; De Iasio, Sergio; Gueresi, Paola; Alfani, Guido; Nelli, Sergio; Rossi, Paolo; Paoli, Giorgio; Tofanelli, Sergio

2015-01-01

This research is the first empirical attempt to calculate the various components of the hidden bias associated with the sampling strategies routinely-used in human genetics, with special reference to surname-based strategies. We reconstructed surname distributions of 26 Italian communities with different demographic features across the last six centuries (years 1447-2001). The degree of overlapping between "reference founding core" distributions and the distributions obtained from sampling the present day communities by probabilistic and selective methods was quantified under different conditions and models. When taking into account only one individual per surname (low kinship model), the average discrepancy was 59.5%, with a peak of 84% by random sampling. When multiple individuals per surname were considered (high kinship model), the discrepancy decreased by 8-30% at the cost of a larger variance. Criteria aimed at maximizing locally-spread patrilineages and long-term residency appeared to be affected by recent gene flows much more than expected. Selection of the more frequent family names following low kinship criteria proved to be a suitable approach only for historically stable communities. In any other case true random sampling, despite its high variance, did not return more biased estimates than other selective methods. Our results indicate that the sampling of individuals bearing historically documented surnames (founders' method) should be applied, especially when studying the male-specific genome, to prevent an over-stratification of ancient and recent genetic components that heavily biases inferences and statistics.

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

NASA Technical Reports Server (NTRS)

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.

System and circuitry to provide stable transconductance for biasing

NASA Technical Reports Server (NTRS)

Garverick, Steven L. (Inventor); Yu, Xinyu (Inventor)

2012-01-01

An amplifier system can include an input amplifier configured to receive an analog input signal and provide an amplified signal corresponding to the analog input signal. A tracking loop is configured to employ delta modulation for tracking the amplified signal, the tracking loop providing a corresponding output signal. A biasing circuit is configured to adjust a bias current to maintain stable transconductance over temperature variations, the biasing circuit providing at least one bias signal for biasing at least one of the input amplifier and the tracking loop, whereby the circuitry receiving the at least one bias signal exhibits stable performance over the temperature variations. In another embodiment the biasing circuit can be utilized in other applications.

Increasingly minimal bias routing

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

Bataineh, Abdulla; Court, Thomas; Roweth, Duncan

2017-02-21

A system and algorithm configured to generate diversity at the traffic source so that packets are uniformly distributed over all of the available paths, but to increase the likelihood of taking a minimal path with each hop the packet takes. This is achieved by configuring routing biases so as to prefer non-minimal paths at the injection point, but increasingly prefer minimal paths as the packet proceeds, referred to herein as Increasing Minimal Bias (IMB).

Application of Biased Metropolis Algorithms: From protons to proteins

PubMed Central

Bazavov, Alexei; Berg, Bernd A.; Zhou, Huan-Xiang

2015-01-01

We show that sampling with a biased Metropolis scheme is essentially equivalent to using the heatbath algorithm. However, the biased Metropolis method can also be applied when an efficient heatbath algorithm does not exist. This is first illustrated with an example from high energy physics (lattice gauge theory simulations). We then illustrate the Rugged Metropolis method, which is based on a similar biased updating scheme, but aims at very different applications. The goal of such applications is to locate the most likely configurations in a rugged free energy landscape, which is most relevant for simulations of biomolecules. PMID:26612967

BIASES IN CASTNET FILTER PACK RESULTS ASSOCIATED WITH SAMPLING PROTOCOL

EPA Science Inventory

In the current study, single filter weekly (w) results are compared with weekly results aggregated from day and night (dn) weekly samples. Comparisons of the two sampling protocols for all major constituents (SO42-, NO3-, NH4+, HNO3, and SO2) show median bias (MB) of < 5 nmol m-3...

Sample Size Bias in Judgments of Perceptual Averages

ERIC Educational Resources Information Center

Price, Paul C.; Kimura, Nicole M.; Smith, Andrew R.; Marshall, Lindsay D.

2014-01-01

Previous research has shown that people exhibit a sample size bias when judging the average of a set of stimuli on a single dimension. The more stimuli there are in the set, the greater people judge the average to be. This effect has been demonstrated reliably for judgments of the average likelihood that groups of people will experience negative,…

Effects of Sample Selection Bias on the Accuracy of Population Structure and Ancestry Inference

PubMed Central

Shringarpure, Suyash; Xing, Eric P.

2014-01-01

Population stratification is an important task in genetic analyses. It provides information about the ancestry of individuals and can be an important confounder in genome-wide association studies. Public genotyping projects have made a large number of datasets available for study. However, practical constraints dictate that of a geographical/ethnic population, only a small number of individuals are genotyped. The resulting data are a sample from the entire population. If the distribution of sample sizes is not representative of the populations being sampled, the accuracy of population stratification analyses of the data could be affected. We attempt to understand the effect of biased sampling on the accuracy of population structure analysis and individual ancestry recovery. We examined two commonly used methods for analyses of such datasets, ADMIXTURE and EIGENSOFT, and found that the accuracy of recovery of population structure is affected to a large extent by the sample used for analysis and how representative it is of the underlying populations. Using simulated data and real genotype data from cattle, we show that sample selection bias can affect the results of population structure analyses. We develop a mathematical framework for sample selection bias in models for population structure and also proposed a correction for sample selection bias using auxiliary information about the sample. We demonstrate that such a correction is effective in practice using simulated and real data. PMID:24637351

Sampling bias in an internet treatment trial for depression.

PubMed

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.

Bennett's acceptance ratio and histogram analysis methods enhanced by umbrella sampling along a reaction coordinate in configurational space.

PubMed

Kim, Ilsoo; Allen, Toby W

2012-04-28

Free energy perturbation, a method for computing the free energy difference between two states, is often combined with non-Boltzmann biased sampling techniques in order to accelerate the convergence of free energy calculations. Here we present a new extension of the Bennett acceptance ratio (BAR) method by combining it with umbrella sampling (US) along a reaction coordinate in configurational space. In this approach, which we call Bennett acceptance ratio with umbrella sampling (BAR-US), the conditional histogram of energy difference (a mapping of the 3N-dimensional configurational space via a reaction coordinate onto 1D energy difference space) is weighted for marginalization with the associated population density along a reaction coordinate computed by US. This procedure produces marginal histograms of energy difference, from forward and backward simulations, with higher overlap in energy difference space, rendering free energy difference estimations using BAR statistically more reliable. In addition to BAR-US, two histogram analysis methods, termed Bennett overlapping histograms with US (BOH-US) and Bennett-Hummer (linear) least square with US (BHLS-US), are employed as consistency and convergence checks for free energy difference estimation by BAR-US. The proposed methods (BAR-US, BOH-US, and BHLS-US) are applied to a 1-dimensional asymmetric model potential, as has been used previously to test free energy calculations from non-equilibrium processes. We then consider the more stringent test of a 1-dimensional strongly (but linearly) shifted harmonic oscillator, which exhibits no overlap between two states when sampled using unbiased Brownian dynamics. We find that the efficiency of the proposed methods is enhanced over the original Bennett's methods (BAR, BOH, and BHLS) through fast uniform sampling of energy difference space via US in configurational space. We apply the proposed methods to the calculation of the electrostatic contribution to the absolute

Origin of tensile strength of a woven sample cut in bias directions

PubMed Central

Pan, Ning; Kovar, Radko; Dolatabadi, Mehdi Kamali; Wang, Ping; Zhang, Diantang; Sun, Ying; Chen, Li

2015-01-01

Textile fabrics are highly anisotropic, so that their mechanical properties including strengths are a function of direction. An extreme case is when a woven fabric sample is cut in such a way where the bias angle and hence the tension loading direction is around 45° relative to the principal directions. Then, once loaded, no yarn in the sample is held at both ends, so the yarns have to build up their internal tension entirely via yarn–yarn friction at the interlacing points. The overall fabric strength in such a sample is a result of contributions from the yarns being pulled out and those broken during the process, and thus becomes a function of the bias direction angle θ, sample width W and length L, along with other factors known to affect fabric strength tested in principal directions. Furthermore, in such a bias sample when the major parameters, e.g. the sample width W, change, not only the resultant strengths differ, but also the strength generating mechanisms (or failure types) vary. This is an interesting problem and is analysed in this study. More specifically, the issues examined in this paper include the exact mechanisms and details of how each interlacing point imparts the frictional constraint for a yarn to acquire tension to the level of its strength when both yarn ends were not actively held by the testing grips; the theoretical expression of the critical yarn length for a yarn to be able to break rather than be pulled out, as a function of the related factors; and the general relations between the tensile strength of such a bias sample and its structural properties. At the end, theoretical predictions are compared with our experimental data. PMID:26064655

Improved variance estimation of classification performance via reduction of bias caused by small sample size.

PubMed

Wickenberg-Bolin, Ulrika; Göransson, Hanna; Fryknäs, Mårten; Gustafsson, Mats G; Isaksson, Anders

2006-03-13

Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm that the classifier is robust with good generalization performance to new examples, or at least that it performs better than random guessing. A suggested alternative is to obtain a confidence interval of the error rate using repeated design and test sets selected from available examples. However, it is known that even in the ideal situation of repeated designs and tests with completely novel samples in each cycle, a small test set size leads to a large bias in the estimate of the true variance between design sets. Therefore different methods for small sample performance estimation such as a recently proposed procedure called Repeated Random Sampling (RSS) is also expected to result in heavily biased estimates, which in turn translates into biased confidence intervals. Here we explore such biases and develop a refined algorithm called Repeated Independent Design and Test (RIDT). Our simulations reveal that repeated designs and tests based on resampling in a fixed bag of samples yield a biased variance estimate. We also demonstrate that it is possible to obtain an improved variance estimate by means of a procedure that explicitly models how this bias depends on the number of samples used for testing. For the special case of repeated designs and tests using new samples for each design and test, we present an exact analytical expression for how the expected value of the bias decreases with the size of the test set. We show that via modeling and subsequent reduction of the small sample bias, it is possible to obtain an improved estimate of the variance of classifier performance between design sets. However, the uncertainty of the variance estimate is large in the simulations performed indicating that the method in its present form cannot be directly applied to small data sets.

Electric shielding films for biased TEM samples and their application to in situ electron holography.

PubMed

Nomura, Yuki; Yamamoto, Kazuo; Hirayama, Tsukasa; Saitoh, Koh

2018-06-01

We developed a novel sample preparation method for transmission electron microscopy (TEM) to suppress superfluous electric fields leaked from biased TEM samples. In this method, a thin TEM sample is first coated with an insulating amorphous aluminum oxide (AlOx) film with a thickness of about 20 nm. Then, the sample is coated with a conductive amorphous carbon film with a thickness of about 10 nm, and the film is grounded. This technique was applied to a model sample of a metal electrode/Li-ion-conductive-solid-electrolyte/metal electrode for biasing electron holography. We found that AlOx film with a thickness of 10 nm has a large withstand voltage of about 8 V and that double layers of AlOx and carbon act as a 'nano-shield' to suppress 99% of the electric fields outside of the sample. We also found an asymmetry potential distribution between high and low potential electrodes in biased solid-electrolyte, indicating different accumulation behaviors of lithium-ions (Li+) and lithium-ion vacancies (VLi-) in the biased solid-electrolyte.

Anticipation or ascertainment bias in schizophrenia? Penrose`s familial mental illness sample

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

Bassett, A.S.; Husted, J.

Several studies have observed anticipation (earlier age at onset [AAO] in successive generations) in familial schizophrenia. However, whether true anticipation or ascertainment bias is the principal originating mechanism remains unclear. In 1944 L.S. Penrose collected AAO data on a large, representative sample of familial mental illness, using a broad ascertainment strategy. These data allowed examination of anticipation and ascertainment biases in five two-generation samples of affected relative pairs. The median intergenerational difference (MID) in AAO was used to assess anticipation. Results showed significant anticipation in parent-offspring pairs with schizophrenia (n = 137 pairs; MID 15 years; P = .0001) andmore » in a positive control sample with Huntington disease (n = 11; P = .01). Broadening the diagnosis of the schizophrenia sample suggested anticipation of severity of illness. However, other analyses provided evidence for ascertainment bias, especially in later-AAO parents, in parent-offspring pairs. Aunt/uncle-niece/nephew schizophrenia pairs showed anticipation (n = 111; P = .0001), but the MID was 8 years and aunts/uncles had earlier median AAO than parents. Anticipation effects were greatest in pairs with late-AAO parents but remained significant in a subgroup of schizophrenia pairs with early parental AAO (n = 31; P = .03). A small control sample of other diseases had MID of 5 years but no significant anticipation (n = 9; F = .38). These results suggest that, although ascertainment-bias effects were observed in parent-offspring pairs, true anticipation appears to be inherent in the transmission of familial schizophrenia. The findings support investigations of unstable mutations and other mechanisms that may contribute to true anticipation in schizophrenia. 37 refs., 2 tabs.« less

Validation sampling can reduce bias in healthcare database studies: an illustration using influenza vaccination effectiveness

PubMed Central

Nelson, Jennifer C.; Marsh, Tracey; Lumley, Thomas; Larson, Eric B.; Jackson, Lisa A.; Jackson, Michael

2014-01-01

Objective Estimates of treatment effectiveness in epidemiologic studies using large observational health care databases may be biased due to inaccurate or incomplete information on important confounders. Study methods that collect and incorporate more comprehensive confounder data on a validation cohort may reduce confounding bias. Study Design and Setting We applied two such methods, imputation and reweighting, to Group Health administrative data (full sample) supplemented by more detailed confounder data from the Adult Changes in Thought study (validation sample). We used influenza vaccination effectiveness (with an unexposed comparator group) as an example and evaluated each method’s ability to reduce bias using the control time period prior to influenza circulation. Results Both methods reduced, but did not completely eliminate, the bias compared with traditional effectiveness estimates that do not utilize the validation sample confounders. Conclusion Although these results support the use of validation sampling methods to improve the accuracy of comparative effectiveness findings from healthcare database studies, they also illustrate that the success of such methods depends on many factors, including the ability to measure important confounders in a representative and large enough validation sample, the comparability of the full sample and validation sample, and the accuracy with which data can be imputed or reweighted using the additional validation sample information. PMID:23849144

Empirical Validation of a Procedure to Correct Position and Stimulus Biases in Matching-to-Sample

ERIC Educational Resources Information Center

Kangas, Brian D.; Branch, Marc N.

2008-01-01

The development of position and stimulus biases often occurs during initial training on matching-to-sample tasks. Furthermore, without intervention, these biases can be maintained via intermittent reinforcement provided by matching-to-sample contingencies. The present study evaluated the effectiveness of a correction procedure designed to…

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

USGS Publications Warehouse

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

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

PubMed

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.

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

PubMed

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.

Quantitative imaging biomarkers: Effect of sample size and bias on confidence interval coverage.

PubMed

Obuchowski, Nancy A; Bullen, Jennifer

2017-01-01

Introduction Quantitative imaging biomarkers (QIBs) are being increasingly used in medical practice and clinical trials. An essential first step in the adoption of a quantitative imaging biomarker is the characterization of its technical performance, i.e. precision and bias, through one or more performance studies. Then, given the technical performance, a confidence interval for a new patient's true biomarker value can be constructed. Estimating bias and precision can be problematic because rarely are both estimated in the same study, precision studies are usually quite small, and bias cannot be measured when there is no reference standard. Methods A Monte Carlo simulation study was conducted to assess factors affecting nominal coverage of confidence intervals for a new patient's quantitative imaging biomarker measurement and for change in the quantitative imaging biomarker over time. Factors considered include sample size for estimating bias and precision, effect of fixed and non-proportional bias, clustered data, and absence of a reference standard. Results Technical performance studies of a quantitative imaging biomarker should include at least 35 test-retest subjects to estimate precision and 65 cases to estimate bias. Confidence intervals for a new patient's quantitative imaging biomarker measurement constructed under the no-bias assumption provide nominal coverage as long as the fixed bias is <12%. For confidence intervals of the true change over time, linearity must hold and the slope of the regression of the measurements vs. true values should be between 0.95 and 1.05. The regression slope can be assessed adequately as long as fixed multiples of the measurand can be generated. Even small non-proportional bias greatly reduces confidence interval coverage. Multiple lesions in the same subject can be treated as independent when estimating precision. Conclusion Technical performance studies of quantitative imaging biomarkers require moderate sample sizes in

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

PubMed

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.

State-dependent biasing method for importance sampling in the weighted stochastic simulation algorithm.

PubMed

Roh, Min K; Gillespie, Dan T; Petzold, Linda R

2010-11-07

The weighted stochastic simulation algorithm (wSSA) was developed by Kuwahara and Mura [J. Chem. Phys. 129, 165101 (2008)] to efficiently estimate the probabilities of rare events in discrete stochastic systems. The wSSA uses importance sampling to enhance the statistical accuracy in the estimation of the probability of the rare event. The original algorithm biases the reaction selection step with a fixed importance sampling parameter. In this paper, we introduce a novel method where the biasing parameter is state-dependent. The new method features improved accuracy, efficiency, and robustness.

Health indicators: eliminating bias from convenience sampling estimators.

PubMed

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.

A maximum pseudo-profile likelihood estimator for the Cox model under length-biased sampling

PubMed Central

Huang, Chiung-Yu; Qin, Jing; Follmann, Dean A.

2012-01-01

This paper considers semiparametric estimation of the Cox proportional hazards model for right-censored and length-biased data arising from prevalent sampling. To exploit the special structure of length-biased sampling, we propose a maximum pseudo-profile likelihood estimator, which can handle time-dependent covariates and is consistent under covariate-dependent censoring. Simulation studies show that the proposed estimator is more efficient than its competitors. A data analysis illustrates the methods and theory. PMID:23843659

Validation sampling can reduce bias in health care database studies: an illustration using influenza vaccination effectiveness.

PubMed

Nelson, Jennifer Clark; Marsh, Tracey; Lumley, Thomas; Larson, Eric B; Jackson, Lisa A; Jackson, Michael L

2013-08-01

Estimates of treatment effectiveness in epidemiologic studies using large observational health care databases may be biased owing to inaccurate or incomplete information on important confounders. Study methods that collect and incorporate more comprehensive confounder data on a validation cohort may reduce confounding bias. We applied two such methods, namely imputation and reweighting, to Group Health administrative data (full sample) supplemented by more detailed confounder data from the Adult Changes in Thought study (validation sample). We used influenza vaccination effectiveness (with an unexposed comparator group) as an example and evaluated each method's ability to reduce bias using the control time period before influenza circulation. Both methods reduced, but did not completely eliminate, the bias compared with traditional effectiveness estimates that do not use the validation sample confounders. Although these results support the use of validation sampling methods to improve the accuracy of comparative effectiveness findings from health care database studies, they also illustrate that the success of such methods depends on many factors, including the ability to measure important confounders in a representative and large enough validation sample, the comparability of the full sample and validation sample, and the accuracy with which the data can be imputed or reweighted using the additional validation sample information. Copyright © 2013 Elsevier Inc. All rights reserved.

Sampling bias in an international internet survey of diversion programs in the criminal justice system.

PubMed

Hartford, Kathleen; Carey, Robert; Mendonca, James

2007-03-01

Despite advances in the storage and retrieval of information within health care systems, health researchers conducting surveys for evaluations still face technical barriers that may lead to sampling bias. The authors describe their experience in administering a Web-based, international survey to English-speaking countries. Identifying the sample was a multistage effort involving (a) searching for published e-mail addresses, (b) conducting Web searches for publicly funded agencies, and (c) performing literature searches, personal contacts, and extensive Internet searches for individuals. After pretesting, the survey was converted into an electronic format accessible by multiple Web browsers. Sampling bias arose from (a) system incompatibility, which did not allow potential respondents to open the survey, (b) varying institutional gate-keeping policies that "recognized" the unsolicited survey as spam, (c) culturally unique program terminology, which confused some respondents, and (d) incomplete sampling frames. Solutions are offered to the first three problems, and the authors note that sampling bias remains a crucial problem.

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

PubMed

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.

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

PubMed Central

Starrfelt, Jostein; Liow, Lee Hsiang

2016-01-01

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. PMID:26977060

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

PubMed

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.

Bias field tunable magnetic configuration and magnetization dynamics in Ni80Fe20 nano-cross structures with varying arm length

NASA Astrophysics Data System (ADS)

Adhikari, K.; Choudhury, S.; Mandal, R.; Barman, S.; Otani, Y.; Barman, A.

2017-01-01

Ferromagnetic nano-cross structures promise exotic static magnetic configurations and very rich and tunable magnetization dynamics leading towards potential applications in magnetic logic and communication devices. Here, we report an experimental study of external magnetic field tunable static magnetic configurations and magnetization dynamics in Ni80Fe20 nano-cross structures with varying arm lengths (L). Broadband ferromagnetic resonance measurements showed a strong variation in the number of spin-wave (SW) modes and mode frequencies (f) with bias field magnitude (H). Simulated static magnetic configurations and SW mode profiles explain the rich variation of the SW spectra, including mode softening, mode crossover, mode splitting, and mode merging. Such variation of SW spectra is further modified by the size of the nano-cross. Remarkably, with decreasing arm length of nano-cross structures, the onion magnetization ground state becomes more stable. Calculated magnetostatic field distributions support the above observations and revealed the non-collective nature of the dynamics in closely packed nano-cross structures. The latter is useful for their possible applications in magnetic storage and memory devices.

New Trends in Magnetic Exchange Bias

NASA Astrophysics Data System (ADS)

Mougin, Alexandra; Mangin, Stéphane; Bobo, Jean-Francois; Loidl, Alois

2005-05-01

of the constituant layers. The spirit of this topical issue is, for the first time, to gather and survey recent and original developments, both experimental and theoretical, which bring new insights into the physics of exchange bias. It has been planned in relation with an international workshop exclusively devoted to exchange bias, namely IWEBMN’04 (International Workshop on Exchange Bias in Magnetic Nanostructures) that took place in Anglet, in the south west of France, from 16th to 18th September 2004. The conference gathered worldwide researchers in the area, both experimentalists and theoreticians. Several research paths are particularly active in the field of magnetic exchange coupling. The conference, as well as this topical issue, which was also open to contributions from scientists not participating in the conference, has been organized according to the following principles: 1. Epitaxial systems: Since the essential behavior of exchange bias critically depends on the atomic-level chemical and spin structure at the interface between the ferromagnetic and antiferromagnetic components, epitaxial AF/F systems in which the quality of the interface and the crystalline coherence are optimized and well known are ideal candidates for a better understanding of the underlying physics of exchange bias. The dependence of exchange bias on the spin configurations at the interfaces can be accomplished by selecting different crystallographic orientations. The role of interface roughness can also be understood from thin-film systems by changing the growth parameters, and correlations between the interface structure and exchange bias can be made, as reported in this issue. 2. Out-of-plane magnetized systems: While much important work has been devoted to the study of structures with in-plane magnetization, little has been done on the study of exchange bias and exchange coupling in samples with out-of-plane magnetization. Some systems can exhibit either in-plane or out

The performance of sample selection estimators to control for attrition bias.

PubMed

Grasdal, A

2001-07-01

Sample attrition is a potential source of selection bias in experimental, as well as non-experimental programme evaluation. For labour market outcomes, such as employment status and earnings, missing data problems caused by attrition can be circumvented by the collection of follow-up data from administrative registers. For most non-labour market outcomes, however, investigators must rely on participants' willingness to co-operate in keeping detailed follow-up records and statistical correction procedures to identify and adjust for attrition bias. This paper combines survey and register data from a Norwegian randomized field trial to evaluate the performance of parametric and semi-parametric sample selection estimators commonly used to correct for attrition bias. The considered estimators work well in terms of producing point estimates of treatment effects close to the experimental benchmark estimates. Results are sensitive to exclusion restrictions. The analysis also demonstrates an inherent paradox in the 'common support' approach, which prescribes exclusion from the analysis of observations outside of common support for the selection probability. The more important treatment status is as a determinant of attrition, the larger is the proportion of treated with support for the selection probability outside the range, for which comparison with untreated counterparts is possible. Copyright 2001 John Wiley & Sons, Ltd.

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

PubMed

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

A Configurational-Bias-Monte-Carlo Back-Mapping Algorithm for Efficient and Rapid Conversion of Coarse-Grained Water Structures Into Atomistic Models.

PubMed

Loeffler, Troy David; Chan, Henry; Narayanan, Badri; Cherukara, Mathew J; Gray, Stephen K; Sankaranarayanan, Subramanian K R S

2018-06-20

Coarse-grained molecular dynamics (MD) simulations represent a powerful approach to simulate longer time scale and larger length scale phenomena than those accessible to all-atom models. The gain in efficiency, however, comes at the cost of atomistic details. The reverse transformation, also known as back-mapping, of coarse grained beads into their atomistic constituents represents a major challenge. Most existing approaches are limited to specific molecules or specific force-fields and often rely on running a long time atomistic MD of the back-mapped configuration to arrive at an optimal solution. Such approaches are problematic when dealing with systems with high diffusion barriers. Here, we introduce a new extension of the configurational-bias-Monte-Carlo (CBMC) algorithm, which we term the crystalline-configurational-bias-Monte-Carlo (C-CBMC) algortihm, that allows rapid and efficient conversion of a coarse-grained model back into its atomistic representation. Although the method is generic, we use a coarse-grained water model as a representative example and demonstrate the back-mapping or reverse transformation for model systems ranging from the ice-liquid water interface to amorphous and crystalline ice configurations. A series of simulations using the TIP4P/Ice model are performed to compare the new CBMC method to several other standard Monte Carlo and Molecular Dynamics based back-mapping techniques. In all the cases, the C-CBMC algorithm is able to find optimal hydrogen bonded configuration many thousand evaluations/steps sooner than the other methods compared within this paper. For crystalline ice structures such as a hexagonal, cubic, and cubic-hexagonal stacking disorder structures, the C-CBMC was able to find structures that were between 0.05 and 0.1 eV/water molecule lower in energy than the ground state energies predicted by the other methods. Detailed analysis of the atomistic structures show a significantly better global hydrogen positioning when

A sampling bias in identifying children in foster care using Medicaid data.

PubMed

Rubin, David M; Pati, Susmita; Luan, Xianqun; Alessandrini, Evaline A

2005-01-01

Prior research identified foster care children using Medicaid eligibility codes specific to foster care, but it is unknown whether these codes capture all foster care children. To describe the sampling bias in relying on Medicaid eligibility codes to identify foster care children. Using foster care administrative files linked to Medicaid data, we describe the proportion of children whose Medicaid eligibility was correctly encoded as foster child during a 1-year follow-up period following a new episode of foster care. Sampling bias is described by comparing claims in mental health, emergency department (ED), and other ambulatory settings among correctly and incorrectly classified foster care children. Twenty-eight percent of the 5683 sampled children were incorrectly classified in Medicaid eligibility files. In a multivariate logistic regression model, correct classification was associated with duration of foster care (>9 vs <2 months, odds ratio [OR] 7.67, 95% confidence interval [CI] 7.17-7.97), number of placements (>3 vs 1 placement, OR 4.20, 95% CI 3.14-5.64), and placement in a group home among adjudicated dependent children (OR 1.87, 95% CI 1.33-2.63). Compared with incorrectly classified children, correctly classified foster care children were 3 times more likely to use any services, 2 times more likely to visit the ED, 3 times more likely to make ambulatory visits, and 4 times more likely to use mental health care services (P < .001 for all comparisons). Identifying children in foster care using Medicaid eligibility files is prone to sampling bias that over-represents children in foster care who use more services.

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

PubMed

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

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

PubMed Central

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

Publication bias in psychology: a diagnosis based on the correlation between effect size and sample size.

PubMed

Kühberger, Anton; Fritz, Astrid; Scherndl, Thomas

2014-01-01

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. 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. 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. 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.

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

PubMed

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

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

PubMed

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.

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

PubMed

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.

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

PubMed Central

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

A “Scientific Diversity” Intervention to Reduce Gender Bias in a Sample of Life Scientists

PubMed Central

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. PMID:27496360

Big Data and Large Sample Size: A Cautionary Note on the Potential for Bias

PubMed Central

Chambers, David A.; Glasgow, Russell E.

2014-01-01

Abstract A number of commentaries have suggested that large studies are more reliable than smaller studies and there is a growing interest in the analysis of “big data” that integrates information from many thousands of persons and/or different data sources. We consider a variety of biases that are likely in the era of big data, including sampling error, measurement error, multiple comparisons errors, aggregation error, and errors associated with the systematic exclusion of information. Using examples from epidemiology, health services research, studies on determinants of health, and clinical trials, we conclude that it is necessary to exercise greater caution to be sure that big sample size does not lead to big inferential errors. Despite the advantages of big studies, large sample size can magnify the bias associated with error resulting from sampling or study design. Clin Trans Sci 2014; Volume #: 1–5 PMID:25043853

Controllable exchange bias in Fe/metamagnetic FeRh bilayers

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

Suzuki, Ippei; Hamasaki, Yosuke; Itoh, Mitsuru

2014-10-27

We report the studies of tuning the exchange bias at ferromagnetic Fe/metamagnetic FeRh bilayer interfaces. Fe/FeRh(111) bilayers show exchange bias in the antiferromagnetic state of FeRh while no exchange bias occurs at Fe/FeRh(001) interface. The contrasting results are attributed to the spin configurations of FeRh at the interface, i.e., the uncompensated ferromagnetic spin configuration of FeRh appears exclusively for (111) orientation. The exchange bias disappears as the bilayers are warmed above the antiferromagnetic-ferromagnetic transition temperature. The direction of the exchange bias for Fe/FeRh(111) is also found to be perpendicular to the cooling-field direction, in contrast to the commonly observed directionmore » of exchange bias for ferromagnetic/antiferromagnetic interfaces. In view of these results, the exchange bias in Fe/FeRh bilayers with the (111) crystallographic orientation should be useful for the design of rapid writing technology for magnetic information devices.« less

New sample cell configuration for wide-frequency dielectric spectroscopy: DC to radio frequencies.

PubMed

Nakanishi, Masahiro; Sasaki, Yasutaka; Nozaki, Ryusuke

2010-12-01

A new configuration for the sample cell to be used in broadband dielectric spectroscopy is presented. A coaxial structure with a parallel plate capacitor (outward parallel plate cell: OPPC) has made it possible to extend the frequency range significantly in comparison with the frequency range of the conventional configuration. In the proposed configuration, stray inductance is significantly decreased; consequently, the upper bound of the frequency range is improved by two orders of magnitude from the upper limit of conventional parallel plate capacitor (1 MHz). Furthermore, the value of capacitance is kept high by using a parallel plate configuration. Therefore, the precision of the capacitance measurement in the lower frequency range remains sufficiently high. Finally, OPPC can cover a wide frequency range (100 Hz-1 GHz) with an appropriate admittance measuring apparatus such as an impedance or network analyzer. The OPPC and the conventional dielectric cell are compared by examining the frequency dependence of the complex permittivity for several polar liquids and polymeric films.

Estimating the occupancy of spotted owl habitat areas by sampling and adjusting for bias

Treesearch

David L. Azuma; James A. Baldwin; Barry R. Noon

1990-01-01

A basic sampling scheme is proposed to estimate the proportion of sampled units (Spotted Owl Habitat Areas (SOHAs) or randomly sampled 1000-acre polygon areas (RSAs)) occupied by spotted owl pairs. A bias adjustment for the possibility of missing a pair given its presence on a SOHA or RSA is suggested. The sampling scheme is based on a fixed number of visits to a...

Introducing etch kernels for efficient pattern sampling and etch bias prediction

NASA Astrophysics Data System (ADS)

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.

Electrically biased GaAs/AlGaAs heterostructures for enhanced detection of bacteria

NASA Astrophysics Data System (ADS)

Aziziyan, Mohammad R.; Hassen, Walid M.; Dubowski, Jan J.

2016-03-01

We have examined the influence of electrical bias on immobilization of bacteria on the surface of GaAs/AlGaAs heterostructures, functionalized with an alkanethiol based architecture. A mixture of biotinylated polyethylene glycol (PEG) thiol and hexadecanethiol was applied to attach neutravidin and antibodies targeting specific immobilization of Legionella pneumophila. An electrochemical setup was designed to bias biofunctionalized samples with the potential measured versus silver/silver chloride reference electrode in a three electrode configuration system. The immobilization efficiency has been examined with fluorescence microscopy after tagging captured bacteria with fluorescein labeled antibodies. We demonstrate more than 2 times enhanced capture of Legionella pneumophila, suggesting the potential of electrically biased biochips to deliver enhanced sensitivity in detecting these bacteria.

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

PubMed

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.

Impact of Gulf Stream SST biases on the global atmospheric circulation

NASA Astrophysics Data System (ADS)

Lee, Robert W.; Woollings, Tim J.; Hoskins, Brian J.; Williams, Keith D.; O'Reilly, Christopher H.; Masato, Giacomo

2018-02-01

The UK Met Office Unified Model in the Global Coupled 2 (GC2) configuration has a warm bias of up to almost 7 K in the Gulf Stream SSTs in the winter season, which is associated with surface heat flux biases and potentially related to biases in the atmospheric circulation. The role of this SST bias is examined with a focus on the tropospheric response by performing three sensitivity experiments. The SST biases are imposed on the atmosphere-only configuration of the model over a small and medium section of the Gulf Stream, and also the wider North Atlantic. Here we show that the dynamical response to this anomalous Gulf Stream heating (and associated shifting and changing SST gradients) is to enhance vertical motion in the transient eddies over the Gulf Stream, rather than balance the heating with a linear dynamical meridional wind or meridional eddy heat transport. Together with the imposed Gulf Stream heating bias, the response affects the troposphere not only locally but also in remote regions of the Northern Hemisphere via a planetary Rossby wave response. The sensitivity experiments partially reproduce some of the differences in the coupled configuration of the model relative to the atmosphere-only configuration and to the ERA-Interim reanalysis. These biases may have implications for the ability of the model to respond correctly to variability or changes in the Gulf Stream. Better global prediction therefore requires particular focus on reducing any large western boundary current SST biases in these regions of high ocean-atmosphere interaction.

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

PubMed

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.

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

PubMed Central

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

Objective 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. Method 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. Results 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. Discussion 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. PMID:26046352

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

PubMed

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.

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

PubMed

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.

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

PubMed

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).

Enhanced conformational sampling using replica exchange with concurrent solute scaling and hamiltonian biasing realized in one dimension.

PubMed

Yang, Mingjun; Huang, Jing; MacKerell, Alexander D

2015-06-09

Replica exchange (REX) is a powerful computational tool for overcoming the quasi-ergodic sampling problem of complex molecular systems. Recently, several multidimensional extensions of this method have been developed to realize exchanges in both temperature and biasing potential space or the use of multiple biasing potentials to improve sampling efficiency. However, increased computational cost due to the multidimensionality of exchanges becomes challenging for use on complex systems under explicit solvent conditions. In this study, we develop a one-dimensional (1D) REX algorithm to concurrently combine the advantages of overall enhanced sampling from Hamiltonian solute scaling and the specific enhancement of collective variables using Hamiltonian biasing potentials. In the present Hamiltonian replica exchange method, termed HREST-BP, Hamiltonian solute scaling is applied to the solute subsystem, and its interactions with the environment to enhance overall conformational transitions and biasing potentials are added along selected collective variables associated with specific conformational transitions, thereby balancing the sampling of different hierarchical degrees of freedom. The two enhanced sampling approaches are implemented concurrently allowing for the use of a small number of replicas (e.g., 6 to 8) in 1D, thus greatly reducing the computational cost in complex system simulations. The present method is applied to conformational sampling of two nitrogen-linked glycans (N-glycans) found on the HIV gp120 envelope protein. Considering the general importance of the conformational sampling problem, HREST-BP represents an efficient procedure for the study of complex saccharides, and, more generally, the method is anticipated to be of general utility for the conformational sampling in a wide range of macromolecular systems.

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

NASA Astrophysics Data System (ADS)

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

Technical note: Alternatives to reduce adipose tissue sampling bias.

PubMed

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.

Stability and bias of classification rates in biological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.; Hines, J.E.

1990-01-01

We assessed the sampling stability of classification rates in discriminant analysis by using a factorial design with factors for multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. Simulation results indicated strong bias in correct classification rates when group sample sizes were small and when overlap among groups was high. We also found that stability of the correct classification rates was influenced by these factors, indicating that the number of samples required for a given level of precision increases with the amount of overlap among groups. In a review of 60 published studies, we found that 57% of the articles presented results on classification rates, though few of them mentioned potential biases in their results. Wildlife researchers should choose the total number of samples per group to be at least 2 times the number of variables to be measured when overlap among groups is low. Substantially more samples are required as the overlap among groups increases

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

PubMed

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.

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Study of the Dependence on Magnetic Field and Bias Voltage of an AC-Biased TES Microcalorimeter

NASA Technical Reports Server (NTRS)

Bandler, Simon

2011-01-01

At SRON we are studying the performance of a Goddard Space Flight Center single pixel TES microcalorimeter operated in the AC bias configuration. For x-ray photons at 6keV the AC biased pixel shows a best energy resolution of 3.7eV, which is about a factor of 2 worse than the energy resolution observed in identical DC-biased pixels. To better understand the reasons of this discrepancy, we investigated the detector performance as a function of temperature, bias working point and applied magnetic field. A strong periodic dependence of the detector noise on the TES AC bias voltage is measured. We discuss the results in the framework of the recent weak-link behaviour observed inTES microcalorimeters.

Biased insert for installing data transmission components in downhole drilling pipe

DOEpatents

Hall, David R [Provo, UT; Briscoe, Michael A [Lehi, UT; Garner, Kory K [Payson, UT; Wilde, Tyson J [Spanish Fork, UT

2007-04-10

An apparatus for installing data transmission hardware in downhole tools includes an insert insertable into the box end or pin end of drill tool, such as a section of drill pipe. The insert typically includes a mount portion and a slide portion. A data transmission element is mounted in the slide portion of the insert. A biasing element is installed between the mount portion and the slide portion and is configured to create a bias between the slide portion and the mount portion. This biasing element is configured to compensate for varying tolerances encountered in different types of downhole tools. In selected embodiments, the biasing element is an elastomeric material, a spring, compressed gas, or a combination thereof.

Search strategy using LHC pileup interactions as a zero bias sample

NASA Astrophysics Data System (ADS)

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.

Perceptual Biases in Processing Facial Identity and Emotion

ERIC Educational Resources Information Center

Coolican, Jamesie; Eskes, Gail A.; McMullen, Patricia A.; Lecky, Erin

2008-01-01

Normal observers demonstrate a bias to process the left sides of faces during perceptual judgments about identity or emotion. This effect suggests a right cerebral hemisphere processing bias. To test the role of the right hemisphere and the involvement of configural processing underlying this effect, young and older control observers and patients…

Small Sample Sizes Yield Biased Allometric Equations in Temperate Forests

PubMed Central

Duncanson, L.; Rourke, O.; Dubayah, R.

2015-01-01

Accurate quantification of forest carbon stocks is required for constraining the global carbon cycle and its impacts on climate. The accuracies of forest biomass maps are inherently dependent on the accuracy of the field biomass estimates used to calibrate models, which are generated with allometric equations. Here, we provide a quantitative assessment of the sensitivity of allometric parameters to sample size in temperate forests, focusing on the allometric relationship between tree height and crown radius. We use LiDAR remote sensing to isolate between 10,000 to more than 1,000,000 tree height and crown radius measurements per site in six U.S. forests. We find that fitted allometric parameters are highly sensitive to sample size, producing systematic overestimates of height. We extend our analysis to biomass through the application of empirical relationships from the literature, and show that given the small sample sizes used in common allometric equations for biomass, the average site-level biomass bias is ~+70% with a standard deviation of 71%, ranging from −4% to +193%. These findings underscore the importance of increasing the sample sizes used for allometric equation generation. PMID:26598233

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

PubMed

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.

Study of the Dependency on Magnetic Field and Bias Voltage of an AC-Biased TES Microcalorimeter

NASA Technical Reports Server (NTRS)

Gottardi, L.; Bruijn, M.; denHartog, R.; Hoevers, H.; deKorte, P.; vanderKuur, J.; Linderman, M.; Adams, J.; Bailey, C.; Bandler, S.;

How Confocal Is Confocal Raman Microspectroscopy on the Skin? Impact of Microscope Configuration and Sample Preparation on Penetration Depth Profiles.

PubMed

Lunter, Dominique Jasmin

2016-01-01

The aim of the study was to elucidate the effect of sample preparation and microscope configuration on the results of confocal Raman microspectroscopic evaluation of the penetration of a pharmaceutical active into the skin (depth profiling). Pig ear skin and a hydrophilic formulation containing procaine HCl were used as a model system. The formulation was either left on the skin during the measurement, or was wiped off or washed off prior to the analysis. The microscope configuration was varied with respect to objectives and pinholes used. Sample preparation and microscope configuration had a tremendous effect on the results of depth profiling. Regarding sample preparation, the best results could be observed when the formulation was washed off the skin prior to the analysis. Concerning microscope configuration, the use of a 40 × 0.6 numerical aperture (NA) objective in combination with a 25-µm pinhole or a 100 × 1.25 NA objective in combination with a 50-µm pinhole was found to be advantageous. Complete removal of the sample from the skin before the analysis was found to be crucial. A thorough analysis of the suitability of the chosen microscope configuration should be performed before acquiring concentration depth profiles. © 2016 S. Karger AG, Basel.

FIP bias in a sigmoidal active region

NASA Astrophysics Data System (ADS)

Baker, D.; Brooks, D. H.; Démoulin, P.; van Driel-Gesztelyi, Lidia; Green, L. M.; Steed, K.; Carlyle, J.

2014-01-01

We investigate first ionization potential (FIP) bias levels in an anemone active region (AR) - coronal hole (CH) complex using an abundance map derived from Hinode/EIS spectra. The detailed, spatially resolved abundance map has a large field of view covering 359'' × 485''. Plasma with high FIP bias, or coronal abundances, is concentrated at the footpoints of the AR loops whereas the surrounding CH has a low FIP bias, ~1, i.e. photospheric abundances. A channel of low FIP bias is located along the AR's main polarity inversion line containing a filament where ongoing flux cancellation is observed, indicating a bald patch magnetic topology characteristic of a sigmoid/flux rope configuration.

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

PubMed

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

Study of the Dependency on Magnetic Field and Bias Voltage of an AC-Biased TES Microcalorimeter.

PubMed

Gottardi, L; Adams, J; Bailey, C; Bandler, S; Bruijn, M; Chervenak, J; Eckart, M; Finkbeiner, F; den Hartog, R; Hoevers, H; Kelley, R; Kilbourne, C; de Korte, P; van der Kuur, J; Lindeman, M; Porter, F; Sadlier, J; Smith, S

At SRON we are studying the performance of a Goddard Space Flight Center single pixel TES microcalorimeter operated in an AC bias configuration. For x-ray photons at 6 keV the pixel shows an x-ray energy resolution Δ E FWHM =3.7 eV, which is about a factor 2 worse than the energy resolution observed in an identical DC-biased pixel. In order to better understand the reasons for this discrepancy we characterised the detector as a function of temperature, bias working point and applied perpendicular magnetic field. A strong periodic dependency of the detector noise on the TES AC bias voltage is measured. We discuss the results in the framework of the recently observed weak-link behaviour of a TES microcalorimeter.

Jackknife Estimation of Sampling Variance of Ratio Estimators in Complex Samples: Bias and the Coefficient of Variation. Research Report. ETS RR-06-19

ERIC Educational Resources Information Center

Oranje, Andreas

2006-01-01

A multitude of methods has been proposed to estimate the sampling variance of ratio estimates in complex samples (Wolter, 1985). Hansen and Tepping (1985) studied some of those variance estimators and found that a high coefficient of variation (CV) of the denominator of a ratio estimate is indicative of a biased estimate of the standard error of a…

Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method

PubMed Central

Cao, Youfang; Liang, Jie

2013-01-01

Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively

Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method

NASA Astrophysics Data System (ADS)

Cao, Youfang; Liang, Jie

2013-07-01

Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively

Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method.

PubMed

Cao, Youfang; Liang, Jie

2013-07-14

Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively

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

PubMed

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.

Implicit and explicit weight bias in a national sample of 4,732 medical students: the medical student CHANGES study.

PubMed

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

2014-04-01

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. A web-based survey was completed by 4,732 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 bias: a feeling thermometer and the anti-fat attitudes test. A majority of students exhibited implicit (74%) and explicit (67%) weight bias. Implicit weight bias scores were comparable to reported bias against racial minorities. Explicit attitudes were more negative toward obese people than toward racial minorities, gays, lesbians, and poor people. In multivariate regression models, implicit and explicit weight bias was predicted by lower BMI, male sex, and non-Black race. Either implicit or explicit bias was also predicted by age, SES, country of birth, and specialty choice. Implicit and explicit weight bias is common among 1st year medical students, and varies across student factors. Future research should assess implications of biases and test interventions to reduce their impact. Copyright © 2013 The Obesity Society.

The small-x gluon distribution in centrality biased pA and pp collisions

DOE PAGES

Dumitru, Adrian; Kapilevich, Gary; Skokov, Vladimir

2018-04-04

Here, the nuclear modification factor R pA(p T) provides information on the small- x gluon distribution of a nucleus at hadron colliders. Several experiments have recently measured the nuclear modification factor not only in minimum bias but also for central pA collisions. In this paper we analyze the bias on the configurations of soft gluon fields introduced by a centrality selection via the number of hard particles. Such bias can be viewed as reweighting of configurations of small- x gluons. We find that the biased nuclear modification factor Q pA(p T) for central collisions is above R pA(p T) formore » minimum bias events, and that it may redevelop a “Cronin peak” even at small x . The magnitude of the peak is predicted to increase approximately like 1/A ⊥ ν, ν~0.6±0.1 , if one is able to select more compact configurations of the projectile proton where its gluons occupy a smaller transverse area A ⊥. We predict an enhanced Q pp(p T)–1~1/(p T 2) ν and a Cronin peak even for central pp collisions.« less

The small-x gluon distribution in centrality biased pA and pp collisions

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

Dumitru, Adrian; Kapilevich, Gary; Skokov, Vladimir

Here, the nuclear modification factor R pA(p T) provides information on the small- x gluon distribution of a nucleus at hadron colliders. Several experiments have recently measured the nuclear modification factor not only in minimum bias but also for central pA collisions. In this paper we analyze the bias on the configurations of soft gluon fields introduced by a centrality selection via the number of hard particles. Such bias can be viewed as reweighting of configurations of small- x gluons. We find that the biased nuclear modification factor Q pA(p T) for central collisions is above R pA(p T) formore » minimum bias events, and that it may redevelop a “Cronin peak” even at small x . The magnitude of the peak is predicted to increase approximately like 1/A ⊥ ν, ν~0.6±0.1 , if one is able to select more compact configurations of the projectile proton where its gluons occupy a smaller transverse area A ⊥. We predict an enhanced Q pp(p T)–1~1/(p T 2) ν and a Cronin peak even for central pp collisions.« less

The small-x gluon distribution in centrality biased pA and pp collisions

NASA Astrophysics Data System (ADS)

Dumitru, Adrian; Kapilevich, Gary; Skokov, Vladimir

2018-06-01

The nuclear modification factor RpA (pT) provides information on the small-x gluon distribution of a nucleus at hadron colliders. Several experiments have recently measured the nuclear modification factor not only in minimum bias but also for central pA collisions. In this paper we analyze the bias on the configurations of soft gluon fields introduced by a centrality selection via the number of hard particles. Such bias can be viewed as reweighting of configurations of small-x gluons. We find that the biased nuclear modification factor QpA (pT) for central collisions is above RpA (pT) for minimum bias events, and that it may redevelop a "Cronin peak" even at small x. The magnitude of the peak is predicted to increase approximately like 1 /A⊥ ν, ν ∼ 0.6 ± 0.1, if one is able to select more compact configurations of the projectile proton where its gluons occupy a smaller transverse area A⊥. We predict an enhanced Qpp (pT) - 1 ∼ 1 /(pT2) ν and a Cronin peak even for central pp collisions.

Turning intractable counting into sampling: Computing the configurational entropy of three-dimensional jammed packings.

PubMed

Martiniani, Stefano; Schrenk, K Julian; Stevenson, Jacob D; Wales, David J; Frenkel, Daan

2016-01-01

We present a numerical calculation of the total number of disordered jammed configurations Ω of N repulsive, three-dimensional spheres in a fixed volume V. To make these calculations tractable, we increase the computational efficiency of the approach of Xu et al. [Phys. Rev. Lett. 106, 245502 (2011)10.1103/PhysRevLett.106.245502] and Asenjo et al. [Phys. Rev. Lett. 112, 098002 (2014)10.1103/PhysRevLett.112.098002] and we extend the method to allow computation of the configurational entropy as a function of pressure. The approach that we use computes the configurational entropy by sampling the absolute volume of basins of attraction of the stable packings in the potential energy landscape. We find a surprisingly strong correlation between the pressure of a configuration and the volume of its basin of attraction in the potential energy landscape. This relation is well described by a power law. Our methodology to compute the number of minima in the potential energy landscape should be applicable to a wide range of other enumeration problems in statistical physics, string theory, cosmology, and machine learning that aim to find the distribution of the extrema of a scalar cost function that depends on many degrees of freedom.

Collective opinion formation model under Bayesian updating and confirmation bias

NASA Astrophysics Data System (ADS)

Nishi, Ryosuke; Masuda, Naoki

2013-06-01

We propose a collective opinion formation model with a so-called confirmation bias. The confirmation bias is a psychological effect with which, in the context of opinion formation, an individual in favor of an opinion is prone to misperceive new incoming information as supporting the current belief of the individual. Our model modifies a Bayesian decision-making model for single individuals [M. Rabin and J. L. Schrag, Q. J. Econ.0033-553310.1162/003355399555945 114, 37 (1999)] for the case of a well-mixed population of interacting individuals in the absence of the external input. We numerically simulate the model to show that all the agents eventually agree on one of the two opinions only when the confirmation bias is weak. Otherwise, the stochastic population dynamics ends up creating a disagreement configuration (also called polarization), particularly for large system sizes. A strong confirmation bias allows various final disagreement configurations with different fractions of the individuals in favor of the opposite opinions.

Biased Brownian dynamics for rate constant calculation.

PubMed

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

2000-08-01

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 sampling of trajectories is then biased, but the sampling is unbiased when the trajectory outcomes are multiplied by their weights. With a suitable choice of the biasing force, more reacted trajectories are sampled. As a consequence, the variance of the estimate is reduced. In our test case, biased Brownian dynamics gives a sevenfold improvement in central processing unit (CPU) time with the choice of a simple centripetal biasing force.

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

PubMed Central

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

Sampling designs matching species biology produce accurate and affordable abundance indices

PubMed Central

Farley, Sean; Russell, Gareth J.; Butler, Matthew J.; Selinger, Jeff

2013-01-01

Wildlife biologists often use grid-based designs to sample animals and generate abundance estimates. Although sampling in grids is theoretically sound, in application, the method can be logistically difficult and expensive when sampling elusive species inhabiting extensive areas. These factors make it challenging to sample animals and meet the statistical assumption of all individuals having an equal probability of capture. Violating this assumption biases results. Does an alternative exist? Perhaps by sampling only where resources attract animals (i.e., targeted sampling), it would provide accurate abundance estimates more efficiently and affordably. However, biases from this approach would also arise if individuals have an unequal probability of capture, especially if some failed to visit the sampling area. Since most biological programs are resource limited, and acquiring abundance data drives many conservation and management applications, it becomes imperative to identify economical and informative sampling designs. Therefore, we evaluated abundance estimates generated from grid and targeted sampling designs using simulations based on geographic positioning system (GPS) data from 42 Alaskan brown bears (Ursus arctos). Migratory salmon drew brown bears from the wider landscape, concentrating them at anadromous streams. This provided a scenario for testing the targeted approach. Grid and targeted sampling varied by trap amount, location (traps placed randomly, systematically or by expert opinion), and traps stationary or moved between capture sessions. We began by identifying when to sample, and if bears had equal probability of capture. We compared abundance estimates against seven criteria: bias, precision, accuracy, effort, plus encounter rates, and probabilities of capture and recapture. One grid (49 km2 cells) and one targeted configuration provided the most accurate results. Both placed traps by expert opinion and moved traps between capture sessions, which

Adaptively biased molecular dynamics: An umbrella sampling method with a time-dependent potential

NASA Astrophysics Data System (ADS)

Babin, Volodymyr; Karpusenka, Vadzim; Moradi, Mahmoud; Roland, Christopher; Sagui, Celeste

We discuss an adaptively biased molecular dynamics (ABMD) method for the computation of a free energy surface for a set of reaction coordinates. The ABMD method belongs to the general category of umbrella sampling methods with an evolving biasing potential. It is characterized by a small number of control parameters and an O(t) numerical cost with simulation time t. The method naturally allows for extensions based on multiple walkers and replica exchange mechanism. The workings of the method are illustrated with a number of examples, including sugar puckering, and free energy landscapes for polymethionine and polyproline peptides, and for a short β-turn peptide. ABMD has been implemented into the latest version (Case et al., AMBER 10; University of California: San Francisco, 2008) of the AMBER software package and is freely available to the simulation community.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

An integrate-over-temperature approach for enhanced sampling.

PubMed

Gao, Yi Qin

2008-02-14

A simple method is introduced to achieve efficient random walking in the energy space in molecular dynamics simulations which thus enhances the sampling over a large energy range. The approach is closely related to multicanonical and replica exchange simulation methods in that it allows configurations of the system to be sampled in a wide energy range by making use of Boltzmann distribution functions at multiple temperatures. A biased potential is quickly generated using this method and is then used in accelerated molecular dynamics simulations.

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

PubMed

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

Unconstrained Enhanced Sampling for Free Energy Calculations of Biomolecules: A Review

PubMed Central

Miao, Yinglong; McCammon, J. Andrew

2016-01-01

Free energy calculations are central to understanding the structure, dynamics and function of biomolecules. Yet insufficient sampling of biomolecular configurations is often regarded as one of the main sources of error. Many enhanced sampling techniques have been developed to address this issue. Notably, enhanced sampling methods based on biasing collective variables (CVs), including the widely used umbrella sampling, adaptive biasing force and metadynamics, have been discussed in a recent excellent review (Abrams and Bussi, Entropy, 2014). Here, we aim to review enhanced sampling methods that do not require predefined system-dependent CVs for biomolecular simulations and as such do not suffer from the hidden energy barrier problem as encountered in the CV-biasing methods. These methods include, but are not limited to, replica exchange/parallel tempering, self-guided molecular/Langevin dynamics, essential energy space random walk and accelerated molecular dynamics. While it is overwhelming to describe all details of each method, we provide a summary of the methods along with the applications and offer our perspectives. We conclude with challenges and prospects of the unconstrained enhanced sampling methods for accurate biomolecular free energy calculations. PMID:27453631

Unconstrained Enhanced Sampling for Free Energy Calculations of Biomolecules: A Review.

PubMed

Miao, Yinglong; McCammon, J Andrew

Free energy calculations are central to understanding the structure, dynamics and function of biomolecules. Yet insufficient sampling of biomolecular configurations is often regarded as one of the main sources of error. Many enhanced sampling techniques have been developed to address this issue. Notably, enhanced sampling methods based on biasing collective variables (CVs), including the widely used umbrella sampling, adaptive biasing force and metadynamics, have been discussed in a recent excellent review (Abrams and Bussi, Entropy, 2014). Here, we aim to review enhanced sampling methods that do not require predefined system-dependent CVs for biomolecular simulations and as such do not suffer from the hidden energy barrier problem as encountered in the CV-biasing methods. These methods include, but are not limited to, replica exchange/parallel tempering, self-guided molecular/Langevin dynamics, essential energy space random walk and accelerated molecular dynamics. While it is overwhelming to describe all details of each method, we provide a summary of the methods along with the applications and offer our perspectives. We conclude with challenges and prospects of the unconstrained enhanced sampling methods for accurate biomolecular free energy calculations.

Asymmetric Differential Resistance of Current Biased Mesoscopic AuFe Wires

NASA Astrophysics Data System (ADS)

Eom, J.; Chandrasekhar, V.; Neuttiens, G.; Strunk, C.; van Haesendonck, C.; Bruynseraede, Y.

1996-03-01

An anomalous asymmetry is found in the differential resistance dV/dI of mesoscopic AuFe wires as a function of dc bias current at low temperatures. The samples are fabricated by ion implanting Au wires of length 1.0 - 35.0 μ m and of width 0.1 - 1.0 μ m with Fe at two different concentrations, 0.2 at.% and 0.4 at.%. The asymmetry is more pronounced in narrow and short samples. The asymmetric component of dV/dI increases with decreasing temperature, and saturates below the maximum in the spin glass resistance. It is found that the lead configuration for the four-terminal measurement also affects the asymmetric component of dV/dI.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

Bieler, Noah S.; Hünenberger, Philippe H.

2014-11-01

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.

High-resolution room-temperature sample scanning superconducting quantum interference device microscope configurable for geological and biomagnetic applications

NASA Astrophysics Data System (ADS)

Fong, L. E.; Holzer, J. R.; McBride, K. K.; Lima, E. A.; Baudenbacher, F.; Radparvar, M.

2005-05-01

We have developed a scanning superconducting quantum interference device (SQUID) microscope system with interchangeable sensor configurations for imaging magnetic fields of room-temperature (RT) samples with submillimeter resolution. The low-critical-temperature (Tc) niobium-based monolithic SQUID sensors are mounted on the tip of a sapphire and thermally anchored to the helium reservoir. A 25μm sapphire window separates the vacuum space from the RT sample. A positioning mechanism allows us to adjust the sample-to-sensor spacing from the top of the Dewar. We achieved a sensor-to-sample spacing of 100μm, which could be maintained for periods of up to four weeks. Different SQUID sensor designs are necessary to achieve the best combination of spatial resolution and field sensitivity for a given source configuration. For imaging thin sections of geological samples, we used a custom-designed monolithic low-Tc niobium bare SQUID sensor, with an effective diameter of 80μm, and achieved a field sensitivity of 1.5pT/Hz1/2 and a magnetic moment sensitivity of 5.4×10-18Am2/Hz1/2 at a sensor-to-sample spacing of 100μm in the white noise region for frequencies above 100Hz. Imaging action currents in cardiac tissue requires a higher field sensitivity, which can only be achieved by compromising spatial resolution. We developed a monolithic low-Tc niobium multiloop SQUID sensor, with sensor sizes ranging from 250μm to 1mm, and achieved sensitivities of 480-180fT /Hz1/2 in the white noise region for frequencies above 100Hz, respectively. For all sensor configurations, the spatial resolution was comparable to the effective diameter and limited by the sensor-to-sample spacing. Spatial registration allowed us to compare high-resolution images of magnetic fields associated with action currents and optical recordings of transmembrane potentials to study the bidomain nature of cardiac tissue or to match petrography to magnetic field maps in thin sections of geological samples.

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

NASA Astrophysics Data System (ADS)

Fort, G.; Jourdain, B.; Lelièvre, T.; Stoltz, G.

2018-04-01

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang-Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

[Evaluation of visual attentional biases in a sample of university smokers].

PubMed

Morales Domínguez, Zaira; Pascual Orts, Luis Miguel; Garrido Muñoz de Arenillas, Rocío

2013-01-01

The tobacco consumption continues being a worrying problem due to the negative consequences in the health. At presents, strategies of prevention based on the persuasion across clue pictures are used, which need to attract the attention of the smoker in order that they are effective. Nevertheless, the number of experimental studies in Spain on attentional biases in smokers is very limited. For it, in this study the aim was to verify the presence of visual attentional biases using the dot probe task in university smokers, stage where the smoking habit is consolidated. The sample was constituted by 337 students of the University of Huelva, with ages between 17 and 30 years. The participation was voluntary and the participants signed an informed assent. 135 subjects presented consumption history, which were distributed, according to classification of the WHO, in daily smokers, occasional smokers and former smokers. A experimental Ex post facto prospective design was used. The results showed that the smokers group was significantly later time to respond to the clue located in the same place that the tobacco picture than the group of not smokers. This shows that the smokers presented more difficulty to disconnect the attention towards smoking cues than not smokers.

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

PubMed

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.

Hydration of Atmospheric Molecular Clusters: Systematic Configurational Sampling.

PubMed

Kildgaard, Jens; Mikkelsen, Kurt V; Bilde, Merete; Elm, Jonas

2018-05-09

We present a new systematic configurational sampling algorithm for investigating the potential energy surface of hydrated atmospheric molecular clusters. The algo- rithm is based on creating a Fibonacci sphere around each atom in the cluster and adding water molecules to each point in 9 different orientations. To allow the sam- pling of water molecules to existing hydrogen bonds, the cluster is displaced along the hydrogen bond and a water molecule is placed in between in three different ori- entations. Generated redundant structures are eliminated based on minimizing the root mean square distance (RMSD) of different conformers. Initially, the clusters are sampled using the semiempirical PM6 method and subsequently using density func- tional theory (M06-2X and ωB97X-D) with the 6-31++G(d,p) basis set. Applying the developed algorithm we study the hydration of sulfuric acid with up to 15 water molecules. We find that the additions of the first four water molecules "saturate" the sulfuric acid molecule and are more thermodynamically favourable than the addition of water molecule 5-15. Using the large generated set of conformers, we assess the performance of approximate methods (ωB97X-D, M06-2X, PW91 and PW6B95-D3) in calculating the binding energies and assigning the global minimum conformation compared to high level CCSD(T)-F12a/VDZ-F12 reference calculations. The tested DFT functionals systematically overestimates the binding energies compared to cou- pled cluster calculations, and we find that this deficiency can be corrected by a simple scaling factor.

Associations of hallucination proneness with free-recall intrusions and response bias in a nonclinical sample.

PubMed

Brébion, Gildas; Larøi, Frank; Van der Linden, Martial

2010-10-01

Hallucinations in patients with schizophrenia have been associated with a liberal response bias in signal detection and recognition tasks and with various types of source-memory error. We investigated the associations of hallucination proneness with free-recall intrusions and false recognitions of words in a nonclinical sample. A total of 81 healthy individuals were administered a verbal memory task involving free recall and recognition of one nonorganizable and one semantically organizable list of words. Hallucination proneness was assessed by means of a self-rating scale. Global hallucination proneness was associated with free-recall intrusions in the nonorganizable list and with a response bias reflecting tendency to make false recognitions of nontarget words in both types of list. The verbal hallucination score was associated with more intrusions and with a reduced tendency to make false recognitions of words. The associations between global hallucination proneness and two types of verbal memory error in a nonclinical sample corroborate those observed in patients with schizophrenia and suggest that common cognitive mechanisms underlie hallucinations in psychiatric and nonclinical individuals.

Comparison of non-landslide sampling strategies to counteract inventory-based biases within national-scale statistical landslide susceptibility models

NASA Astrophysics Data System (ADS)

Lima, Pedro; Steger, Stefan; Glade, Thomas

2017-04-01

Landslides can represent a significant threat for people and infrastructure in hilly and mountainous landscapes worldwide. The understanding and prediction of those geomorphic processes is crucial to avoid economic loses or even casualties to people and their properties. Statistical based landslide susceptibility models are well known for being highly reliant on the quality, representativeness and availability of input data. In this context, several studies indicate that the landslide inventory represents the most important input data. However each landslide mapping technique or data collection has its drawbacks. Consequently, biased landslide inventories may be commonly introduced into statistical models, especially at regional or even national scale. It remains to the researcher to be aware of potential limitations and design strategies to avoid or reduce the potential propagation of input data errors and biases influences on the modelling outcomes. Previous studies have proven that such erroneous landslide inventories may lead to unrealistic landslide susceptibility maps. We assume that one possibility to tackle systematic landslide inventory-based biases might be a concentration on sampling strategies that focus on the distribution of non-landslide locations. For this purpose, we test an approach for the Austrian territory that concentrates on a modified non-landslide sampling strategy, instead the traditional applied random sampling. It is expected that the way non-landslide locations are represented (e.g. equally over the area or within those areas where mapping campaigns have been conducted) is important to reduce a potential over- or underestimation of landslide susceptibility within specific areas caused by bias. As presumably each landslide inventory is known to be systematically incomplete, especially in those areas where no mapping campaign was previously conducted. This is also applicable to the one currently available for the Austrian territory

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

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

Bieler, Noah S.; Hünenberger, Philippe H., E-mail: phil@igc.phys.chem.ethz.ch

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”more » 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.« less

Learning Strategies in Matching to Sample: If-then and Configural Learning by Pigeons

PubMed Central

Katz, Jeffrey S.; Bodily, Kent D.; Wright, Anthony A.

2008-01-01

Pigeons learned a matching-to-sample task with a split training-set design in which half of the stimulus displays were untrained and tested following acquisition. Transfer to the untrained displays along with no novel-stimulus transfer indicated that these pigeons learned the task (partially) via if-then rules. Comparisons to other performance measures indicated that they also partially learned the task via configural learning (learning the gestalt of the whole stimulus display). Differences in the FR-sample requirement (1 vs. 20) had no systematic effect on the type of learning or level of learning obtained. Differences from a previous study (Wright, 1997) are discussed, including the effect of displaying the stimuli vertically (traditional display orientation) or horizontally from the floor. PMID:18079071

Method and apparatus configured for identification of a material

DOEpatents

Slater, John M.; Crawford, Thomas M.

2000-01-01

The present invention includes an apparatus configured for identification of a material, and methods of identifying a material. One embodiment of the invention provides an apparatus including a first region configured to receive a first sample, the first region being configured to output a first spectrum corresponding to the first sample and responsive to exposure of the first sample to radiation; a modulator configured to modulate the first spectrum according to a first frequency; a second region configured to receive a second sample, the second region being configured to output a second spectrum corresponding to the second sample and responsive to exposure of the second sample to the modulated first spectrum; and a detector configured to detect the second spectrum having a second frequency greater than the first frequency.

Periodontal Research: Basics and beyond – Part II (Ethical issues, sampling, outcome measures and bias)

PubMed Central

Avula, Haritha

2013-01-01

A good research beginning refers to formulating a well-defined research question, developing a hypothesis and choosing an appropriate study design. The first part of the review series has discussed these issues in depth and this paper intends to throw light on other issues pertaining to the implementation of research. These include the various ethical norms and standards in human experimentation, the eligibility criteria for the participants, sampling methods and sample size calculation, various outcome measures that need to be defined and the biases that can be introduced in research. PMID:24174747

Bias modification training can alter approach bias and chocolate consumption.

PubMed

Schumacher, Sophie E; Kemps, Eva; Tiggemann, Marika

2016-01-01

Recent evidence has demonstrated that bias modification training has potential to reduce cognitive biases for attractive targets and affect health behaviours. The present study investigated whether cognitive bias modification training could be applied to reduce approach bias for chocolate and affect subsequent chocolate consumption. A sample of 120 women (18-27 years) were randomly assigned to an approach-chocolate condition or avoid-chocolate condition, in which they were trained to approach or avoid pictorial chocolate stimuli, respectively. Training had the predicted effect on approach bias, such that participants trained to approach chocolate demonstrated an increased approach bias to chocolate stimuli whereas participants trained to avoid such stimuli showed a reduced bias. Further, participants trained to avoid chocolate ate significantly less of a chocolate muffin in a subsequent taste test than participants trained to approach chocolate. Theoretically, results provide support for the dual process model's conceptualisation of consumption as being driven by implicit processes such as approach bias. In practice, approach bias modification may be a useful component of interventions designed to curb the consumption of unhealthy foods. Copyright © 2015 Elsevier Ltd. All rights reserved.

Forms of attrition in a longitudinal study of religion and health in older adults and implications for sample bias

PubMed Central

Hayward, R. David; Krause, Neal

2014-01-01

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 towards 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. PMID:25257794

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

PubMed

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.

Some comments on Anderson and Pospahala's correction of bias in line transect sampling

USGS Publications Warehouse

Anderson, D.R.; Burnham, K.P.; Chain, B.R.

1980-01-01

ANDERSON and POSPAHALA (1970) investigated the estimation of wildlife population size using the belt or line transect sampling method and devised a correction for bias, thus leading to an estimator with interesting characteristics. This work was given a uniform mathematical framework in BURNHAM and ANDERSON (1976). In this paper we show that the ANDERSON-POSPAHALA estimator is optimal in the sense of being the (unique) best linear unbiased estimator within the class of estimators which are linear combinations of cell frequencies, provided certain assumptions are met.

A Critical Assessment of Bias in Survey Studies Using Location-Based Sampling to Recruit Patrons in Bars

PubMed Central

Morrison, Christopher; Lee, Juliet P.; Gruenewald, Paul J.; Marzell, Miesha

2015-01-01

Location-based sampling is a method to obtain samples of people within ecological contexts relevant to specific public health outcomes. Random selection increases generalizability, however in some circumstances (such as surveying bar patrons) recruitment conditions increase risks of sample bias. We attempted to recruit representative samples of bars and patrons in six California cities, but low response rates precluded meaningful analysis. A systematic review of 24 similar studies revealed that none addressed the key shortcomings of our study. We recommend steps to improve studies that use location-based sampling: (i) purposively sample places of interest, (ii) utilize recruitment strategies appropriate to the environment, and (iii) provide full information on response rates at all levels of sampling. PMID:26574657

Using sketch-map coordinates to analyze and bias molecular dynamics simulations

PubMed Central

Tribello, Gareth A.; Ceriotti, Michele; Parrinello, Michele

2012-01-01

When examining complex problems, such as the folding of proteins, coarse grained descriptions of the system drive our investigation and help us to rationalize the results. Oftentimes collective variables (CVs), derived through some chemical intuition about the process of interest, serve this purpose. Because finding these CVs is the most difficult part of any investigation, we recently developed a dimensionality reduction algorithm, sketch-map, that can be used to build a low-dimensional map of a phase space of high-dimensionality. In this paper we discuss how these machine-generated CVs can be used to accelerate the exploration of phase space and to reconstruct free-energy landscapes. To do so, we develop a formalism in which high-dimensional configurations are no longer represented by low-dimensional position vectors. Instead, for each configuration we calculate a probability distribution, which has a domain that encompasses the entirety of the low-dimensional space. To construct a biasing potential, we exploit an analogy with metadynamics and use the trajectory to adaptively construct a repulsive, history-dependent bias from the distributions that correspond to the previously visited configurations. This potential forces the system to explore more of phase space by making it desirable to adopt configurations whose distributions do not overlap with the bias. We apply this algorithm to a small model protein and succeed in reproducing the free-energy surface that we obtain from a parallel tempering calculation. PMID:22427357

Spin valves with spin-engineered domain-biasing scheme

NASA Astrophysics Data System (ADS)

Lu, Z. Q.; Pan, G.

2003-06-01

Synthetic spin-filter spin valves with spin-engineered biasing scheme "sub/Ta/NiFe/IrMn/NiFe/NOL/Cu1/CoFe/Cu2/CoFe/Ru/CoFe/IrMn/Ta" were developed. In the structure, the orthogonal magnetic configuration for biasing and pinning field was obtained by one-step magnetic annealing process by means of spin flop, which eliminated the need for two antiferromagnetic materials with distinctively different blocking temperatures and two-step magnetic annealing as in conventional exchange biasing scheme. The longitudinal domain biasing of spin valves was achieved by using interlayer coupling field through Cu1 spacer. By adjusting the thickness of the Cu1 layer, the interlayer coupling biasing field can provide domain stabilization and was sufficiently strong to constrain the magnetization in coherent rotation. This can prevent Barkhausen noises associated with magnetization reversal. We report here a proof of concept study of such a domain-biasing scheme, which has its important technological applications in nanoscale spin valve and magnetic tunneling junction read heads and other spintronic devices.

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

ERIC Educational Resources Information Center

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…

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

PubMed

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.

Assessing Intellectual Ability with a Minimum of Cultural Bias for Two Samples of Metis and Indian Children.

ERIC Educational Resources Information Center

West, Lloyd Wilbert

An investigation was designed to ascertain the effects of cultural background on selected intelligence tests and to identify instruments which validly measure intellectual ability with a minimum of cultural bias. A battery of tests, selected for factor analytic study, was administered and replicated at four grade levels to a sample of Metis and…

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

PubMed

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.

Small Sample Performance of Bias-corrected Sandwich Estimators for Cluster-Randomized Trials with Binary Outcomes

PubMed Central

Li, Peng; Redden, David T.

2014-01-01

SUMMARY The sandwich estimator in generalized estimating equations (GEE) approach underestimates the true variance in small samples and consequently results in inflated type I error rates in hypothesis testing. This fact limits the application of the GEE in cluster-randomized trials (CRTs) with few clusters. Under various CRT scenarios with correlated binary outcomes, we evaluate the small sample properties of the GEE Wald tests using bias-corrected sandwich estimators. Our results suggest that the GEE Wald z test should be avoided in the analyses of CRTs with few clusters even when bias-corrected sandwich estimators are used. With t-distribution approximation, the Kauermann and Carroll (KC)-correction can keep the test size to nominal levels even when the number of clusters is as low as 10, and is robust to the moderate variation of the cluster sizes. However, in cases with large variations in cluster sizes, the Fay and Graubard (FG)-correction should be used instead. Furthermore, we derive a formula to calculate the power and minimum total number of clusters one needs using the t test and KC-correction for the CRTs with binary outcomes. The power levels as predicted by the proposed formula agree well with the empirical powers from the simulations. The proposed methods are illustrated using real CRT data. We conclude that with appropriate control of type I error rates under small sample sizes, we recommend the use of GEE approach in CRTs with binary outcomes due to fewer assumptions and robustness to the misspecification of the covariance structure. PMID:25345738

A Lack of Left Visual Field Bias when Individuals with Autism Process Faces

ERIC Educational Resources Information Center

Dundas, Eva M.; Best, Catherine A.; Minshew, Nancy J.; Strauss, Mark S.

2012-01-01

It has been established that typically developing individuals have a bias to attend to facial information in the left visual field (LVF) more than in the right visual field. This bias is thought to arise from the right hemisphere's advantage for processing facial information, with evidence suggesting it to be driven by the configural demands of…

Enhanced spin wave propagation in magnonic rings by bias field modulation

NASA Astrophysics Data System (ADS)

Venkat, G.; Venkateswarlu, D.; Joshi, R. S.; Franchin, M.; Fangohr, H.; Anil Kumar, P. S.; Prabhakar, A.

2018-05-01

We simulate the spin wave (SW) dynamics in ring structures and obtain the ω - k dispersion relations corresponding to the output waveguide. Different bias field configurations affect the transfer of SW power from one arm of the structure to the other arm. To this end, we show that circular or radial bias fields are more suitable for energy transfer across the ring than the conventional horizontal bias field Hx. The SW dispersion shows that modes excited, when the bias field is along the ring radius, are almost 10 dB higher in power when compared to the modal power in the case of Hx. This is also corroborated by the SW energy density in the receiving stub.

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

PubMed

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.

Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach. [Kansas

NASA Technical Reports Server (NTRS)

Hixson, M. M.; Bauer, M. E.; Davis, B. J.

1979-01-01

The effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of LANDSAT MSS data was investigated. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plants. Four sampling schemes involving different numbers of samples and different size sampling units were evaluated. The precision of the wheat area estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling unit size.

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

PubMed

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.

Reactivity-worth estimates of the OSMOSE samples in the MINERVE reactor R1-MOX, R2-UO2 and MORGANE/R configurations.

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

Zhong, Z.; Klann, R. T.; Nuclear Engineering Division

2007-08-03

An initial series of calculations of the reactivity-worth of the OSMOSE samples in the MINERVE reactor with the R2-UO2 and MORGANE/R core configuration were completed. The calculation model was generated using the lattice physics code DRAGON. In addition, an initial comparison of calculated values to experimental measurements was performed based on preliminary results for the R1-MOX configuration.

Simulation of the global ocean thermohaline circulation with an eddy-resolving INMIO model configuration

NASA Astrophysics Data System (ADS)

Ushakov, K. V.; Ibrayev, R. A.

2017-11-01

In this paper, the first results of a simulation of the mean World Ocean thermohaline characteristics obtained by the INMIO ocean general circulation model configured with 0.1 degree resolution in a 5-year long numerical experiment following the CORE-II protocol are presented. The horizontal and zonal mean distributions of the solution bias against the WOA09 data are analyzed. The seasonal cycle of heat content at a specified site of the North Atlantic is also discussed. The simulation results demonstrate a clear improvement in the quality of representation of the upper ocean compared to the results of experiments with 0.5 and 0.25 degree model configurations. Some remaining biases of the model solution and possible ways of their overcoming are highlighted.

Bias voltage induced resistance switching effect in single-molecule magnets' tunneling junction.

PubMed

Zhang, Zhengzhong; Jiang, Liang

2014-09-12

An electric-pulse-induced reversible resistance change effect in a molecular magnetic tunneling junction, consisting of a single-molecule magnet (SMM) sandwiched in one nonmagnetic and one ferromagnetic electrode, is theoretically investigated. By applying a time-varying bias voltage, the SMM's spin orientation can be manipulated with large bias voltage pulses. Moreover, the different magnetic configuration at high-resistance/low-resistance states can be 'read out' by utilizing relative low bias voltage. This device scheme can be implemented with current technologies (Khajetoorians et al 2013 Science 339 55) and has potential application in molecular spintronics and high-density nonvolatile memory devices.

Junctionless Diode Enabled by Self-Bias Effect of Ion Gel in Single-Layer MoS2 Device.

PubMed

Khan, Muhammad Atif; Rathi, Servin; Park, Jinwoo; Lim, Dongsuk; Lee, Yoontae; Yun, Sun Jin; Youn, Doo-Hyeb; Kim, Gil-Ho

2017-08-16

The self-biasing effects of ion gel from source and drain electrodes on electrical characteristics of single layer and few layer molybdenum disulfide (MoS 2 ) field-effect transistor (FET) have been studied. The self-biasing effect of ion gel is tested for two different configurations, covered and open, where ion gel is in contact with either one or both, source and drain electrodes, respectively. In open configuration, the linear output characteristics of the pristine device becomes nonlinear and on-off ratio drops by 3 orders of magnitude due to the increase in "off" current for both single and few layer MoS 2 FETs. However, the covered configuration results in a highly asymmetric output characteristics with a rectification of around 10 3 and an ideality factor of 1.9. This diode like behavior has been attributed to the reduction of Schottky barrier width by the electric field of self-biased ion gel, which enables an efficient injection of electrons by tunneling at metal-MoS 2 interface. Finally, finite element method based simulations are carried out and the simulated results matches well in principle with the experimental analysis. These self-biased diodes can perform a crucial role in the development of high-frequency optoelectronic and valleytronic devices.

Improving the efficiency of configurational-bias Monte Carlo: A density-guided method for generating bending angle trials for linear and branched molecules

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

Sepehri, Aliasghar; Loeffler, Troy D.; Chen, Bin, E-mail: binchen@lsu.edu

2014-08-21

A new method has been developed to generate bending angle trials to improve the acceptance rate and the speed of configurational-bias Monte Carlo. Whereas traditionally the trial geometries are generated from a uniform distribution, in this method we attempt to use the exact probability density function so that each geometry generated is likely to be accepted. In actual practice, due to the complexity of this probability density function, a numerical representation of this distribution function would be required. This numerical table can be generated a priori from the distribution function. This method has been tested on a united-atom model ofmore » alkanes including propane, 2-methylpropane, and 2,2-dimethylpropane, that are good representatives of both linear and branched molecules. It has been shown from these test cases that reasonable approximations can be made especially for the highly branched molecules to reduce drastically the dimensionality and correspondingly the amount of the tabulated data that is needed to be stored. Despite these approximations, the dependencies between the various geometrical variables can be still well considered, as evident from a nearly perfect acceptance rate achieved. For all cases, the bending angles were shown to be sampled correctly by this method with an acceptance rate of at least 96% for 2,2-dimethylpropane to more than 99% for propane. Since only one trial is required to be generated for each bending angle (instead of thousands of trials required by the conventional algorithm), this method can dramatically reduce the simulation time. The profiling results of our Monte Carlo simulation code show that trial generation, which used to be the most time consuming process, is no longer the time dominating component of the simulation.« less

Network Configurations in the Human Brain Reflect Choice Bias during Rapid Face Processing

PubMed Central

Schneck, Noam

2017-01-01

Network interactions are likely to be instrumental in processes underlying rapid perception and cognition. Specifically, high-level and perceptual regions must interact to balance pre-existing models of the environment with new incoming stimuli. Simultaneous electroencephalography (EEG) and fMRI (EEG/fMRI) enables temporal characterization of brain–network interactions combined with improved anatomical localization of regional activity. In this paper, we use simultaneous EEG/fMRI and multivariate dynamical systems (MDS) analysis to characterize network relationships between constitute brain areas that reflect a subject's choice for a face versus nonface categorization task. Our simultaneous EEG and fMRI analysis on 21 human subjects (12 males, 9 females) identifies early perceptual and late frontal subsystems that are selective to the categorical choice of faces versus nonfaces. We analyze the interactions between these subsystems using an MDS in the space of the BOLD signal. Our main findings show that differences between face-choice and house-choice networks are seen in the network interactions between the early and late subsystems, and that the magnitude of the difference in network interaction positively correlates with the behavioral false-positive rate of face choices. We interpret this to reflect the role of saliency and expectations likely encoded in frontal “late” regions on perceptual processes occurring in “early” perceptual regions. SIGNIFICANCE STATEMENT Our choices are affected by our biases. In visual perception and cognition such biases can be commonplace and quite curious—e.g., we see a human face when staring up at a cloud formation or down at a piece of toast at the breakfast table. Here we use multimodal neuroimaging and dynamical systems analysis to measure whole-brain spatiotemporal dynamics while subjects make decisions regarding the type of object they see in rapidly flashed images. We find that the degree of interaction in these

Assessing Compliance-Effect Bias in the Two Stage Least Squares Estimator

ERIC Educational Resources Information Center

Reardon, Sean; Unlu, Fatih; Zhu, Pei; Bloom, Howard

2011-01-01

The proposed paper studies the bias in the two-stage least squares, or 2SLS, estimator that is caused by the compliance-effect covariance (hereafter, the compliance-effect bias). It starts by deriving the formula for the bias in an infinite sample (i.e., in the absence of finite sample bias) under different circumstances. Specifically, it…

Double propensity-score adjustment: A solution to design bias or bias due to incomplete matching.

PubMed

Austin, Peter C

2017-02-01

Propensity-score matching is frequently used to reduce the effects of confounding when using observational data to estimate the effects of treatments. Matching allows one to estimate the average effect of treatment in the treated. Rosenbaum and Rubin coined the term "bias due to incomplete matching" to describe the bias that can occur when some treated subjects are excluded from the matched sample because no appropriate control subject was available. The presence of incomplete matching raises important questions around the generalizability of estimated treatment effects to the entire population of treated subjects. We describe an analytic solution to address the bias due to incomplete matching. Our method is based on using optimal or nearest neighbor matching, rather than caliper matching (which frequently results in the exclusion of some treated subjects). Within the sample matched on the propensity score, covariate adjustment using the propensity score is then employed to impute missing potential outcomes under lack of treatment for each treated subject. Using Monte Carlo simulations, we found that the proposed method resulted in estimates of treatment effect that were essentially unbiased. This method resulted in decreased bias compared to caliper matching alone and compared to either optimal matching or nearest neighbor matching alone. Caliper matching alone resulted in design bias or bias due to incomplete matching, while optimal matching or nearest neighbor matching alone resulted in bias due to residual confounding. The proposed method also tended to result in estimates with decreased mean squared error compared to when caliper matching was used.

Double propensity-score adjustment: A solution to design bias or bias due to incomplete matching

PubMed Central

2016-01-01

Propensity-score matching is frequently used to reduce the effects of confounding when using observational data to estimate the effects of treatments. Matching allows one to estimate the average effect of treatment in the treated. Rosenbaum and Rubin coined the term “bias due to incomplete matching” to describe the bias that can occur when some treated subjects are excluded from the matched sample because no appropriate control subject was available. The presence of incomplete matching raises important questions around the generalizability of estimated treatment effects to the entire population of treated subjects. We describe an analytic solution to address the bias due to incomplete matching. Our method is based on using optimal or nearest neighbor matching, rather than caliper matching (which frequently results in the exclusion of some treated subjects). Within the sample matched on the propensity score, covariate adjustment using the propensity score is then employed to impute missing potential outcomes under lack of treatment for each treated subject. Using Monte Carlo simulations, we found that the proposed method resulted in estimates of treatment effect that were essentially unbiased. This method resulted in decreased bias compared to caliper matching alone and compared to either optimal matching or nearest neighbor matching alone. Caliper matching alone resulted in design bias or bias due to incomplete matching, while optimal matching or nearest neighbor matching alone resulted in bias due to residual confounding. The proposed method also tended to result in estimates with decreased mean squared error compared to when caliper matching was used. PMID:25038071

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.

PubMed

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

Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach

NASA Technical Reports Server (NTRS)

Hixson, M.; Bauer, M. E.; Davis, B. J. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plans. Evaluation of four sampling schemes involving different numbers of samples and different size sampling units shows that the precision of the wheat estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling size unit.

The CO5 configuration of the 7 km Atlantic Margin Model: large-scale biases and sensitivity to forcing, physics options and vertical resolution

NASA Astrophysics Data System (ADS)

O'Dea, Enda; Furner, Rachel; Wakelin, Sarah; Siddorn, John; While, James; Sykes, Peter; King, Robert; Holt, Jason; Hewitt, Helene

2017-08-01

We describe the physical model component of the standard Coastal Ocean version 5 configuration (CO5) of the European north-west shelf (NWS). CO5 was developed jointly between the Met Office and the National Oceanography Centre. CO5 is designed with the seamless approach in mind, which allows for modelling of multiple timescales for a variety of applications from short-range ocean forecasting to climate projections. The configuration constitutes the basis of the latest update to the ocean and data assimilation components of the Met Office's operational Forecast Ocean Assimilation Model (FOAM) for the NWS. A 30.5-year non-assimilating control hindcast of CO5 was integrated from January 1981 to June 2012. Sensitivity simulations were conducted with reference to the control run. The control run is compared against a previous non-assimilating Proudman Oceanographic Laboratory Coastal Ocean Modelling System (POLCOMS) hindcast of the NWS. The CO5 control hindcast is shown to have much reduced biases compared to POLCOMS. Emphasis in the system description is weighted to updates in CO5 over previous versions. Updates include an increase in vertical resolution, a new vertical coordinate stretching function, the replacement of climatological riverine sources with the pan-European hydrological model E-HYPE, a new Baltic boundary condition and switching from directly imposed atmospheric model boundary fluxes to calculating the fluxes within the model using a bulk formula. Sensitivity tests of the updates are detailed with a view toward attributing observed changes in the new system from the previous system and suggesting future directions of research to further improve the system.

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

NASA Technical Reports Server (NTRS)

Mandra, Salvatore

2017-01-01

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 to 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)]. 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.

Comparing State SAT Scores: Problems, Biases, and Corrections.

ERIC Educational Resources Information Center

Gohmann, Stephen F.

1988-01-01

One method to correct for selection bias in comparing Scholastic Aptitude Test (SAT) scores among states is presented, which is a modification of J. J. Heckman's Selection Bias Correction (1976, 1979). Empirical results suggest that sample selection bias is present in SAT score regressions. (SLD)

Development of global sea ice 6.0 CICE configuration for the Met Office global coupled model

DOE PAGES

Rae, J. . G. L; Hewitt, H. T.; Keen, A. B.; ...

2015-03-05

The new sea ice configuration GSI6.0, used in the Met Office global coupled configuration GC2.0, is described and the sea ice extent, thickness and volume are compared with the previous configuration and with observationally-based datasets. In the Arctic, the sea ice is thicker in all seasons than in the previous configuration, and there is now better agreement of the modelled concentration and extent with the HadISST dataset. In the Antarctic, a warm bias in the ocean model has been exacerbated at the higher resolution of GC2.0, leading to a large reduction in ice extent and volume; further work is requiredmore » to rectify this in future configurations.« less

Flux-trapping during the formation of field-reversed configurations

NASA Astrophysics Data System (ADS)

Armstrong, W. T.; Harding, D. G.; Crawford, E. A.; Hoffman, A. L.

1981-10-01

Optimized trapping of bias flux during the early formation phases of a Field Reversed Configuration was studied experimentally on the field reversed theta pinch TRX-1. An annular z-pinch preionizer was employed to permit ionization at high values of initial reverse bias flux. Octopole barrier fields are pulsed during field reversal to minimize plasma/wall contact and associated loss of reverse flux. Also, second half cycle operation was examined in obtaining very high values of reverse flux. Flux loss is generally observed to be governed by resistive diffusion through a current sheath at the plasma boundary, rather than flux convection to the plasma boundary. Trapped reverse flux at the time of field reversal, as well as after the radial implosion, is observed to increase with the applied bias field. This increase is greatest, and in fact nearly linear with bias field, when barrier fields are employed. Barrier fields also appear to broaden the current sheath, which results in some flux loss and a less dynamic radial implosion. A general model and one dimensional simulation of flux loss is described and correlated with experimental results.

The gas chromatographic determination of volatile fatty acids in wastewater samples: evaluation of experimental biases in direct injection method against thermal desorption method.

PubMed

Ullah, Md Ahsan; Kim, Ki-Hyun; Szulejko, Jan E; Cho, Jinwoo

2014-04-11

The production of short-chained volatile fatty acids (VFAs) by the anaerobic bacterial digestion of sewage (wastewater) affords an excellent opportunity to alternative greener viable bio-energy fuels (i.e., microbial fuel cell). VFAs in wastewater (sewage) samples are commonly quantified through direct injection (DI) into a gas chromatograph with a flame ionization detector (GC-FID). In this study, the reliability of VFA analysis by the DI-GC method has been examined against a thermal desorption (TD-GC) method. The results indicate that the VFA concentrations determined from an aliquot from each wastewater sample by the DI-GC method were generally underestimated, e.g., reductions of 7% (acetic acid) to 93.4% (hexanoic acid) relative to the TD-GC method. The observed differences between the two methods suggest the possibly important role of the matrix effect to give rise to the negative biases in DI-GC analysis. To further explore this possibility, an ancillary experiment was performed to examine bias patterns of three DI-GC approaches. For instance, the results of the standard addition (SA) method confirm the definite role of matrix effect when analyzing wastewater samples by DI-GC. More importantly, their biases tend to increase systematically with increasing molecular weight and decreasing VFA concentrations. As such, the use of DI-GC method, if applied for the analysis of samples with a complicated matrix, needs a thorough validation to improve the reliability in data acquisition. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed

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.

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

PubMed Central

2015-01-01

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. PMID:26574437

Bias against research on gender bias.

PubMed

Cislak, Aleksandra; Formanowicz, Magdalena; Saguy, Tamar

2018-01-01

The bias against women in academia is a documented phenomenon that has had detrimental consequences, not only for women, but also for the quality of science. First, gender bias in academia affects female scientists, resulting in their underrepresentation in academic institutions, particularly in higher ranks. The second type of gender bias in science relates to some findings applying only to male participants, which produces biased knowledge. Here, we identify a third potentially powerful source of gender bias in academia: the bias against research on gender bias. In a bibliometric investigation covering a broad range of social sciences, we analyzed published articles on gender bias and race bias and established that articles on gender bias are funded less often and published in journals with a lower Impact Factor than articles on comparable instances of social discrimination. This result suggests the possibility of an underappreciation of the phenomenon of gender bias and related research within the academic community. Addressing this meta-bias is crucial for the further examination of gender inequality, which severely affects many women across the world.

Network Configurations in the Human Brain Reflect Choice Bias during Rapid Face Processing.

PubMed

Tu, Tao; Schneck, Noam; Muraskin, Jordan; Sajda, Paul

2017-12-13

Network interactions are likely to be instrumental in processes underlying rapid perception and cognition. Specifically, high-level and perceptual regions must interact to balance pre-existing models of the environment with new incoming stimuli. Simultaneous electroencephalography (EEG) and fMRI (EEG/fMRI) enables temporal characterization of brain-network interactions combined with improved anatomical localization of regional activity. In this paper, we use simultaneous EEG/fMRI and multivariate dynamical systems (MDS) analysis to characterize network relationships between constitute brain areas that reflect a subject's choice for a face versus nonface categorization task. Our simultaneous EEG and fMRI analysis on 21 human subjects (12 males, 9 females) identifies early perceptual and late frontal subsystems that are selective to the categorical choice of faces versus nonfaces. We analyze the interactions between these subsystems using an MDS in the space of the BOLD signal. Our main findings show that differences between face-choice and house-choice networks are seen in the network interactions between the early and late subsystems, and that the magnitude of the difference in network interaction positively correlates with the behavioral false-positive rate of face choices. We interpret this to reflect the role of saliency and expectations likely encoded in frontal "late" regions on perceptual processes occurring in "early" perceptual regions. SIGNIFICANCE STATEMENT Our choices are affected by our biases. In visual perception and cognition such biases can be commonplace and quite curious-e.g., we see a human face when staring up at a cloud formation or down at a piece of toast at the breakfast table. Here we use multimodal neuroimaging and dynamical systems analysis to measure whole-brain spatiotemporal dynamics while subjects make decisions regarding the type of object they see in rapidly flashed images. We find that the degree of interaction in these networks

Nonlinear vs. linear biasing in Trp-cage folding simulations

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

Spiwok, Vojtěch, E-mail: spiwokv@vscht.cz; Oborský, Pavel; Králová, Blanka

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 energymore » 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.« less

Nonlinear vs. linear biasing in Trp-cage folding simulations

NASA Astrophysics Data System (ADS)

Spiwok, Vojtěch; Oborský, Pavel; Pazúriková, Jana; Křenek, Aleš; Králová, Blanka

2015-03-01

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.

Nonlinear vs. linear biasing in Trp-cage folding simulations.

PubMed

Spiwok, Vojtěch; Oborský, Pavel; Pazúriková, Jana; Křenek, Aleš; Králová, Blanka

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.

More Than the Sum of Its Parts: A Role for the Hippocampus in Configural Reinforcement Learning.

PubMed

Duncan, Katherine; Doll, Bradley B; Daw, Nathaniel D; Shohamy, Daphna

2018-05-02

People often perceive configurations rather than the elements they comprise, a bias that may emerge because configurations often predict outcomes. But how does the brain learn to associate configurations with outcomes and how does this learning differ from learning about individual elements? We combined behavior, reinforcement learning models, and functional imaging to understand how people learn to associate configurations of cues with outcomes. We found that configural learning depended on the relative predictive strength of elements versus configurations and was related to both the strength of BOLD activity and patterns of BOLD activity in the hippocampus. Configural learning was further related to functional connectivity between the hippocampus and nucleus accumbens. Moreover, configural learning was associated with flexible knowledge about associations and differential eye movements during choice. Together, this suggests that configural learning is associated with a distinct computational, cognitive, and neural profile that is well suited to support flexible and adaptive behavior. Copyright © 2018 Elsevier Inc. All rights reserved.

The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 and GC3.1) Configurations

NASA Astrophysics Data System (ADS)

Williams, K. D.; Copsey, D.; Blockley, E. W.; Bodas-Salcedo, A.; Calvert, D.; Comer, R.; Davis, P.; Graham, T.; Hewitt, H. T.; Hill, R.; Hyder, P.; Ineson, S.; Johns, T. C.; Keen, A. B.; Lee, R. W.; Megann, A.; Milton, S. F.; Rae, J. G. L.; Roberts, M. J.; Scaife, A. A.; Schiemann, R.; Storkey, D.; Thorpe, L.; Watterson, I. G.; Walters, D. N.; West, A.; Wood, R. A.; Woollings, T.; Xavier, P. K.

2018-02-01

The Global Coupled 3 (GC3) configuration of the Met Office Unified Model is presented. Among other applications, GC3 is the basis of the United Kingdom's submission to the Coupled Model Intercomparison Project 6 (CMIP6). This paper documents the model components that make up the configuration (although the scientific descriptions of these components are in companion papers) and details the coupling between them. The performance of GC3 is assessed in terms of mean biases and variability in long climate simulations using present-day forcing. The suitability of the configuration for predictability on shorter time scales (weather and seasonal forecasting) is also briefly discussed. The performance of GC3 is compared against GC2, the previous Met Office coupled model configuration, and against an older configuration (HadGEM2-AO) which was the submission to CMIP5. In many respects, the performance of GC3 is comparable with GC2, however, there is a notable improvement in the Southern Ocean warm sea surface temperature bias which has been reduced by 75%, and there are improvements in cloud amount and some aspects of tropical variability. Relative to HadGEM2-AO, many aspects of the present-day climate are improved in GC3 including tropospheric and stratospheric temperature structure, most aspects of tropical and extratropical variability and top-of-atmosphere and surface fluxes. A number of outstanding errors are identified including a residual asymmetric sea surface temperature bias (cool northern hemisphere, warm Southern Ocean), an overly strong global hydrological cycle and insufficient European blocking.

A universal sample manipulator with 50 kV negative bias

NASA Astrophysics Data System (ADS)

Kenny, M. J.; Wielunski, L. S.; Scott, M. D.; Clissold, R. A.; Stevenson, D.; Baxter, G.

1991-04-01

A manipulator incorporating a number of novel features has been built for a research ion implanter. The system is designed to enable uniform dose implantation of both planar and nonplanar surfaces by incorporating one translational and two rotational degrees of freedom. Negative target bias of up to 50 kV may be applied to the target, thus increasing the ion energy by this amount. The target chamber and all external manipulator controls are grounded. With the exception of the high voltage power supply, cable and feedthrough, all high voltage components are within the vacuum system. A secondary electron suppression cage which can be held at a negative bias of up to 60 kV relative to the chamber (i.e. 10 kV relative to the manipulator) surrounds the manipulator. Performance has been evaluated using 15N ions and nuclear reaction analysis through 15N(p,α) 12C to profile ion concentrations for dose uniformity and for ion depth at elevated target potentials.

Apparatus configured for identification of a material and method of identifying a material

DOEpatents

Slater, John M.; Crawford, Thomas M.; Frickey, Dean A.

2001-01-01

The present invention relates to an apparatus configured for identification of a material and method of identifying a material. One embodiment of the present invention provides an apparatus configured for identification of a material including a first region configured to receive a first sample and output a first spectrum responsive to exposure of the first sample to radiation; a signal generator configured to provide a reference signal having a reference frequency and a modulation signal having a modulation frequency; a modulator configured to selectively modulate the first spectrum using the modulation signal according to the reference frequency; a second region configured to receive a second sample and output a second spectrum responsive to exposure of the second sample to the first spectrum; and a detector configured to detect the second spectrum.

Threat-Related Attention Bias Variability and Posttraumatic Stress.

PubMed

Naim, Reut; Abend, Rany; Wald, Ilan; Eldar, Sharon; Levi, Ofir; Fruchter, Eyal; Ginat, Karen; Halpern, Pinchas; Sipos, Maurice L; Adler, Amy B; Bliese, Paul D; Quartana, Phillip J; Pine, Daniel S; Bar-Haim, Yair

2015-12-01

Threat monitoring facilitates survival by allowing one to efficiently and accurately detect potential threats. Traumatic events can disrupt healthy threat monitoring, inducing biased and unstable threat-related attention deployment. Recent research suggests that greater attention bias variability, that is, attention fluctuations alternating toward and away from threat, occurs in participants with PTSD relative to healthy comparison subjects who were either exposed or not exposed to traumatic events. The current study extends findings on attention bias variability in PTSD. Previous measurement of attention bias variability was refined by employing a moving average technique. Analyses were conducted across seven independent data sets; in each, data on attention bias variability were collected by using variants of the dot-probe task. Trauma-related and anxiety symptoms were evaluated across samples by using structured psychiatric interviews and widely used self-report questionnaires, as specified for each sample. Analyses revealed consistent evidence of greater attention bias variability in patients with PTSD following various types of traumatic events than in healthy participants, participants with social anxiety disorder, and participants with acute stress disorder. Moreover, threat-related, and not positive, attention bias variability was correlated with PTSD severity. These findings carry possibilities for using attention bias variability as a specific cognitive marker of PTSD and for tailoring protocols for attention bias modification for this disorder.

Interface spins in polycrystalline FeMn/Fe bilayers with small exchange bias

NASA Astrophysics Data System (ADS)

Pires, M. J. M.

2018-04-01

The magnetic moments at the interface between ferromagnetic and antiferromagnetic layers play a central role in exchange biased systems, but their behavior is still not completely understood. In this work, the FeMn/Fe interface in polycrystalline thin films has been studied using conversion electron Mössbauer spectroscopy (CEMS), magneto-optic Kerr effect (MOKE) and micromagnetic simulations. Samples were prepared with 57Fe layers at two distinct depths in order to probe the interface and bulk behaviors. At the equilibrium, the interface moments are randomly oriented while the bulk of the Fe layer has an in-plane magnetic anisotropy. Several models for the interface and anisotropies of the layers were used in the simulations of spin configurations and hysteresis loops. From the whole set of simulations, one can conclude the direct analysis of hysteresis curves is not enough to infer whether the interface has a configuration with spins tilted out of the film plane at equilibrium since different choices of parameters provide similar curves. The simulations have also shown the occurrence of spin clusters at the interface is compatible with CEMS and MOKE measurements.

Adaptive-numerical-bias metadynamics.

PubMed

Khanjari, Neda; Eslami, Hossein; Müller-Plathe, Florian

2017-12-05

A metadynamics scheme is presented in which the free energy surface is filled with progressively adding adaptive biasing potentials, obtained from the accumulated probability distribution of the collective variables. Instead of adding Gaussians with assigned height and width in conventional metadynamics method, here we add a more realistic adaptive biasing potential to the Hamiltonian of the system. The shape of the adaptive biasing potential is adjusted on the fly by sampling over the visited states. As the top of the barrier is approached, the biasing potentials become wider. This decreases the problem of trapping the system in the niches, introduced by the addition of Gaussians of fixed height in metadynamics. Our results for the free energy profiles of three test systems show that this method is more accurate and converges more quickly than the conventional metadynamics, and is quite comparable (in accuracy and convergence rate) with the well-tempered metadynamics method. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

BIAS: Bioinformatics Integrated Application Software.

PubMed

Finak, G; Godin, N; Hallett, M; Pepin, F; Rajabi, Z; Srivastava, V; Tang, Z

2005-04-15

We introduce a development platform especially tailored to Bioinformatics research and software development. BIAS (Bioinformatics Integrated Application Software) provides the tools necessary for carrying out integrative Bioinformatics research requiring multiple datasets and analysis tools. It follows an object-relational strategy for providing persistent objects, allows third-party tools to be easily incorporated within the system and supports standards and data-exchange protocols common to Bioinformatics. BIAS is an OpenSource project and is freely available to all interested users at http://www.mcb.mcgill.ca/~bias/. This website also contains a paper containing a more detailed description of BIAS and a sample implementation of a Bayesian network approach for the simultaneous prediction of gene regulation events and of mRNA expression from combinations of gene regulation events. hallett@mcb.mcgill.ca.

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

PubMed

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.

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

PubMed Central

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

2010-01-01

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. PMID:18725208

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

PubMed

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.

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

ERIC Educational Resources Information Center

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…

Unconscious biases in task choices depend on conscious expectations.

PubMed

González-García, Carlos; Tudela, Pío; Ruz, María

2015-12-01

Recent studies highlight the influence of non-conscious information on task-set selection. However, it has not yet been tested whether this influence depends on conscious settings, as some theoretical models propose. In a series of three experiments, we explored whether non-conscious abstract cues could bias choices between a semantic and a perceptual task. In Experiment 1, we observed a non-conscious influence on task-set selection even when perceptual priming and cue-target compound confounds did not apply. Experiments 2 and 3 showed that, under restrictive conditions of visibility, cues only biased task selection when the conscious task-setting mindset led participants to search for information during the time period of the cue. However, this conscious strategy did not modulate the effect found when a subjective measure of consciousness was used. Altogether, our results show that the configuration of the conscious mindset determines the potential bias of non-conscious information on task-set selection. Copyright © 2015 Elsevier Inc. All rights reserved.

A machine learning model with human cognitive biases capable of learning from small and biased datasets.

PubMed

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.

Sequential biases in accumulating evidence

PubMed Central

Huggins, Richard; Dogo, Samson Henry

2015-01-01

Whilst it is common in clinical trials to use the results of tests at one phase to decide whether to continue to the next phase and to subsequently design the next phase, we show that this can lead to biased results in evidence synthesis. Two new kinds of bias associated with accumulating evidence, termed ‘sequential decision bias’ and ‘sequential design bias’, are identified. Both kinds of bias are the result of making decisions on the usefulness of a new study, or its design, based on the previous studies. Sequential decision bias is determined by the correlation between the value of the current estimated effect and the probability of conducting an additional study. Sequential design bias arises from using the estimated value instead of the clinically relevant value of an effect in sample size calculations. We considered both the fixed‐effect and the random‐effects models of meta‐analysis and demonstrated analytically and by simulations that in both settings the problems due to sequential biases are apparent. According to our simulations, the sequential biases increase with increased heterogeneity. Minimisation of sequential biases arises as a new and important research area necessary for successful evidence‐based approaches to the development of science. © 2015 The Authors. Research Synthesis Methods Published by John Wiley & Sons Ltd. PMID:26626562

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

PubMed Central

Albers, D. J.; Hripcsak, George

2012-01-01

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. PMID:22536009

Development of the global sea ice 6.0 CICE configuration for the Met Office global coupled model

DOE PAGES

Rae, J. G. L.; Hewitt, H. T.; Keen, A. B.; ...

2015-07-24

The new sea ice configuration GSI6.0, used in the Met Office global coupled configuration GC2.0, is described and the sea ice extent, thickness and volume are compared with the previous configuration and with observationally based data sets. In the Arctic, the sea ice is thicker in all seasons than in the previous configuration, and there is now better agreement of the modelled concentration and extent with the HadISST data set. As a result, in the Antarctic, a warm bias in the ocean model has been exacerbated at the higher resolution of GC2.0, leading to a large reduction in ice extentmore » and volume; further work is required to rectify this in future configurations.« less

Development of the global sea ice 6.0 CICE configuration for the Met Office global coupled model

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

Rae, J. G. L.; Hewitt, H. T.; Keen, A. B.

The new sea ice configuration GSI6.0, used in the Met Office global coupled configuration GC2.0, is described and the sea ice extent, thickness and volume are compared with the previous configuration and with observationally based data sets. In the Arctic, the sea ice is thicker in all seasons than in the previous configuration, and there is now better agreement of the modelled concentration and extent with the HadISST data set. As a result, in the Antarctic, a warm bias in the ocean model has been exacerbated at the higher resolution of GC2.0, leading to a large reduction in ice extentmore » and volume; further work is required to rectify this in future configurations.« less

Is probabilistic bias analysis approximately Bayesian?

PubMed Central

MacLehose, Richard F.; Gustafson, Paul

2011-01-01

Case-control studies are particularly susceptible to differential exposure misclassification when exposure status is determined following incident case status. Probabilistic bias analysis methods have been developed as ways to adjust standard effect estimates based on the sensitivity and specificity of exposure misclassification. The iterative sampling method advocated in probabilistic bias analysis bears a distinct resemblance to a Bayesian adjustment; however, it is not identical. Furthermore, without a formal theoretical framework (Bayesian or frequentist), the results of a probabilistic bias analysis remain somewhat difficult to interpret. We describe, both theoretically and empirically, the extent to which probabilistic bias analysis can be viewed as approximately Bayesian. While the differences between probabilistic bias analysis and Bayesian approaches to misclassification can be substantial, these situations often involve unrealistic prior specifications and are relatively easy to detect. Outside of these special cases, probabilistic bias analysis and Bayesian approaches to exposure misclassification in case-control studies appear to perform equally well. PMID:22157311

Implicit Social Biases in People with Autism

PubMed Central

Birmingham, Elina; Stanley, Damian; Nair, Remya; Adolphs, Ralph

2015-01-01

Implicit social biases are ubiquitous and are known to influence social behavior. A core diagnostic criterion of Autism Spectrum Disorder (ASD) is abnormal social behavior. Here we investigated the extent to which individuals with ASD might show a specific attenuation of implicit social biases, using the Implicit Association Test (IAT) across Social (gender, race) and Nonsocial (flowers/insect, shoes) categories. High-functioning adults with ASD showed intact but reduced IAT effects relative to healthy controls. Importantly, we observed no selective attenuation of implicit social (vs. nonsocial) biases in our ASD population. To extend these results, we collected data from a large online sample of the general population, and explored correlations between autistic traits and IAT effects. No associations were found between autistic traits and IAT effects for any of the categories tested in our online sample. Taken together, these results suggest that implicit social biases, as measured by the IAT, are largely intact in ASD. PMID:26386014

Mapping High Dimensional Sparse Customer Requirements into Product Configurations

NASA Astrophysics Data System (ADS)

Jiao, Yao; Yang, Yu; Zhang, Hongshan

2017-10-01

Mapping customer requirements into product configurations is a crucial step for product design, while, customers express their needs ambiguously and locally due to the lack of domain knowledge. Thus the data mining process of customer requirements might result in fragmental information with high dimensional sparsity, leading the mapping procedure risk uncertainty and complexity. The Expert Judgment is widely applied against that background since there is no formal requirements for systematic or structural data. However, there are concerns on the repeatability and bias for Expert Judgment. In this study, an integrated method by adjusted Local Linear Embedding (LLE) and Naïve Bayes (NB) classifier is proposed to map high dimensional sparse customer requirements to product configurations. The integrated method adjusts classical LLE to preprocess high dimensional sparse dataset to satisfy the prerequisite of NB for classifying different customer requirements to corresponding product configurations. Compared with Expert Judgment, the adjusted LLE with NB performs much better in a real-world Tablet PC design case both in accuracy and robustness.

Bias in fallout data from nuclear surface shot SMALL BOY: an evaluation of sample perturbation by sieve sizing. Technical report

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

Pascual, J.N.

1967-06-26

Evaluation of sample bias introduced by the mechanical sieving of Small Boy fallout samples for 10 minutes revealed the following: Up to 20% of the mass and 30% of the gamma-ray activity can be lost from the large-particle (greater than 1400 microns) fraction. The pan fraction (less than 44 microns) can gain in weight by as much as 79%, and in activity by as much as 44%. The gamma-ray spectra of the fractions were not noticeably altered by the process. Examination of unbiased pan fractions (before mechanical sieving) indicated bimodality of the mass-size distribution in a sample collected 9,200 feetmore » from ground zero, but not in a sample collected at 13,300 feet.« less

Exploratory Studies of Bias in Achievement Tests.

ERIC Educational Resources Information Center

Green, Donald Ross; Draper, John F.

This paper considers the question of bias in group administered academic achievement tests, bias which is inherent in the instruments themselves. A body of data on the test of performance of three disadvantaged minority groups--northern, urban black; southern, rural black; and, southwestern, Mexican-Americans--as tryout samples in contrast to…

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.

PubMed

Gupta, Manan; Joshi, Amitabh; Vidya, T N C

2017-01-01

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. Therefore, the

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

PubMed Central

Joshi, Amitabh; Vidya, T. N. C.

2017-01-01

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. Therefore, the

Attention Bias toward Threat in Pediatric Anxiety Disorders

ERIC Educational Resources Information Center

Roy, Amy Krain; Vasa, Roma A.; Bruck, Maggie; Mogg, Karin; Bradley, Brendan P.; Sweeney, Michael; Bergman, R. Lindsey; McClure-Tone, Erin B.; Pine, Daniel S.

2008-01-01

Attention bias towards threat faces is examined for a large sample of anxiety-disordered youths using visual probe task. The results showed that anxious individuals showed a selective bias towards threat due to perturbation in neural mechanisms that control vigilance.

Biased four-point probe resistance

NASA Astrophysics Data System (ADS)

Garcia-Vazquez, Valentin

2017-11-01

The implications of switching the current polarity in a four-point probe resistance measurement are presented. We demonstrate that, during the inversion of the applied current, any change in the voltage V produced by a continuous drop of the sample temperature T will induce a bias in the temperature-dependent DC resistance. The analytical expression for the bias is deduced and written in terms of the variations of the measured voltages with respect to T and by the variations of T with respect to time t. Experimental data measured on a superconducting Nb thin film confirm that the bias of the normal-state resistance monotonically increases with the cooling rate dT/dt while keeping fixed dV/dT; on the other hand, the bias increases with dV/dT, reaching values up to 13% with respect to the unbiased resistance obtained at room temperature.

Atomic-Scale Simulation of Electrochemical Processes at Electrode/Water Interfaces under Referenced Bias Potential.

PubMed

Bouzid, Assil; Pasquarello, Alfredo

2018-04-19

Based on constant Fermi-level molecular dynamics and a proper alignment scheme, we perform simulations of the Pt(111)/water interface under variable bias potential referenced to the standard hydrogen electrode (SHE). Our scheme yields a potential of zero charge μ pzc of ∼0.22 eV relative to the SHE and a double layer capacitance C dl of ≃19 μF cm -2 , in excellent agreement with experimental measurements. In addition, we study the structural reorganization of the electrical double layer for bias potentials ranging from -0.92 eV to +0.44 eV and find that O down configurations, which are dominant at potentials above the pzc, reorient to favor H down configurations as the measured potential becomes negative. Our modeling scheme allows one to not only access atomic-scale processes at metal/water interfaces, but also to quantitatively estimate macroscopic electrochemical quantities.

Implicit Bias in Pediatric Academic Medicine.

PubMed

Johnson, Tiffani J; Ellison, Angela M; Dalembert, George; Fowler, Jessica; Dhingra, Menaka; Shaw, Kathy; Ibrahim, Said

2017-01-01

Despite known benefits of diversity, certain racial/ethnic groups remain underrepresented in academic pediatrics. Little research exists regarding unconscious racial attitudes among pediatric faculty responsible for decisions on workforce recruitment and retention in academia. This study sought to describe levels of unconscious racial bias and perceived barriers to minority recruitment and retention among academic pediatric faculty leaders. Authors measured unconscious racial bias in a sample of pediatric faculty attending diversity workshops conducted at local and national meetings in 2015. A paper version of the validated Implicit Association Test (IAT) measured unconscious racial bias. Subjects also reported perceptions about minority recruitment and retention. Of 68 eligible subjects approached, 58 (85%) consented and completed the survey with IAT. Of participants, 83% had leadership roles and 93% were involved in recruitment. Participants had slight pro-white/anti-black bias on the IAT (M = 0.28, SD = 0.49). There were similar IAT scores among participants in leadership roles (M = 0.33, SD = 0.47) and involved in recruitment (M = 0.28, SD = 0.43). Results did not differ when comparing participants in local workshops to the national workshop (n = 36, M = 0.29, SD = 0.40 and n = 22, M = 0.27, SD = 0.49 respectively; p = 0.88). Perceived barriers to minority recruitment and retention included lack of minority mentors, poor recruitment efforts, and lack of qualified candidates. Unconscious pro-white/anti-black racial bias was identified in this sample of academic pediatric faculty and leaders. Further research is needed to examine how unconscious bias impacts decisions in academic pediatric workforce recruitment. Addressing unconscious bias and perceived barriers to minority recruitment and retention represent opportunities to improve diversity efforts. Copyright © 2017 National Medical Association. All rights reserved.

Substrate-biasing during plasma-assisted atomic layer deposition to tailor metal-oxide thin film growth

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

Profijt, H. B.; Sanden, M. C. M. van de; Kessels, W. M. M.

2013-01-15

Two substrate-biasing techniques, i.e., substrate-tuned biasing and RF biasing, have been implemented in a remote plasma configuration, enabling control of the ion energy during plasma-assisted atomic layer deposition (ALD). With both techniques, substrate bias voltages up to -200 V have been reached, which allowed for ion energies up to 272 eV. Besides the bias voltage, the ion energy and the ion flux, also the electron temperature, the electron density, and the optical emission of the plasma have been measured. The effects of substrate biasing during plasma-assisted ALD have been investigated for Al{sub 2}O{sub 3}, Co{sub 3}O{sub 4}, and TiO{sub 2}more » thin films. The growth per cycle, the mass density, and the crystallinity have been investigated, and it was found that these process and material properties can be tailored using substrate biasing. Additionally, the residual stress in substrates coated with Al{sub 2}O{sub 3} films varied with the substrate bias voltage. The results reported in this article demonstrate that substrate biasing is a promising technique to tailor the material properties of thin films synthesized by plasma-assisted ALD.« less

Mixed Model Association with Family-Biased Case-Control Ascertainment.

PubMed

Hayeck, Tristan J; Loh, Po-Ru; Pollack, Samuela; Gusev, Alexander; Patterson, Nick; Zaitlen, Noah A; Price, Alkes L

2017-01-05

Mixed models have become the tool of choice for genetic association studies; however, standard mixed model methods may be poorly calibrated or underpowered under family sampling bias and/or case-control ascertainment. Previously, we introduced a liability threshold-based mixed model association statistic (LTMLM) to address case-control ascertainment in unrelated samples. Here, we consider family-biased case-control ascertainment, where case and control subjects are ascertained non-randomly with respect to family relatedness. Previous work has shown that this type of ascertainment can severely bias heritability estimates; we show here that it also impacts mixed model association statistics. We introduce a family-based association statistic (LT-Fam) that is robust to this problem. Similar to LTMLM, LT-Fam is computed from posterior mean liabilities (PML) under a liability threshold model; however, LT-Fam uses published narrow-sense heritability estimates to avoid the problem of biased heritability estimation, enabling correct calibration. In simulations with family-biased case-control ascertainment, LT-Fam was correctly calibrated (average χ 2 = 1.00-1.02 for null SNPs), whereas the Armitage trend test (ATT), standard mixed model association (MLM), and case-control retrospective association test (CARAT) were mis-calibrated (e.g., average χ 2 = 0.50-1.22 for MLM, 0.89-2.65 for CARAT). LT-Fam also attained higher power than other methods in some settings. In 1,259 type 2 diabetes-affected case subjects and 5,765 control subjects from the CARe cohort, downsampled to induce family-biased ascertainment, LT-Fam was correctly calibrated whereas ATT, MLM, and CARAT were again mis-calibrated. Our results highlight the importance of modeling family sampling bias in case-control datasets with related samples. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Spatial variability of "Did You Feel It?" intensity data: insights into sampling biases in historical earthquake intensity distributions

USGS Publications Warehouse

Hough, Susan E.

2013-01-01

Recent parallel development of improved quantitative methods to analyze intensity distributions for historical earthquakes and of web‐based systems for collecting intensity data for modern earthquakes provides an opportunity to reconsider not only important individual historical earthquakes but also the overall characterization of intensity distributions for historical events. The focus of this study is a comparison between intensity distributions of historical earthquakes with those from modern earthquakes for which intensities have been determined by the U.S. Geological Survey “Did You Feel It?” (DYFI) website (see Data and Resources). As an example of a historical earthquake, I focus initially on the 1843 Marked Tree, Arkansas, event. Its magnitude has been previously estimated as 6.0–6.2. I first reevaluate the macroseismic effects of this earthquake, assigning intensities using a traditional approach, and estimate a preferred magnitude of 5.4. Modified Mercalli intensity (MMI) values for the Marked Tree earthquake are higher, on average, than those from the 2011 >Mw 5.8 Mineral, Virginia, earthquake for distances ≤500  km but comparable or lower on average at larger distances, with a smaller overall felt extent. Intensity distributions for other moderate historical earthquakes reveal similar discrepancies; the discrepancy is also even more pronounced using earlier published intensities for the 1843 earthquake. I discuss several hypotheses to explain the discrepancies, including the possibility that intensity values associated with historical earthquakes are commonly inflated due to reporting/sampling biases. A detailed consideration of the DYFI intensity distribution for the Mineral earthquake illustrates how reporting and sampling biases can account for historical earthquake intensity biases as high as two intensity units and for the qualitative difference in intensity distance decays for modern versus historical events. Thus, intensity maps for

A New Source Biasing Approach in ADVANTG

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

Bevill, Aaron M; Mosher, Scott W

2012-01-01

The ADVANTG code has been developed at Oak Ridge National Laboratory to generate biased sources and weight window maps for MCNP using the CADIS and FW-CADIS methods. In preparation for an upcoming RSICC release, a new approach for generating a biased source has been developed. This improvement streamlines user input and improves reliability. Previous versions of ADVANTG generated the biased source from ADVANTG input, writing an entirely new general fixed-source definition (SDEF). Because volumetric sources were translated into SDEF-format as a finite set of points, the user had to perform a convergence study to determine whether the number of sourcemore » points used accurately represented the source region. Further, the large number of points that must be written in SDEF-format made the MCNP input and output files excessively long and difficult to debug. ADVANTG now reads SDEF-format distributions and generates corresponding source biasing cards, eliminating the need for a convergence study. Many problems of interest use complicated source regions that are defined using cell rejection. In cell rejection, the source distribution in space is defined using an arbitrarily complex cell and a simple bounding region. Source positions are sampled within the bounding region but accepted only if they fall within the cell; otherwise, the position is resampled entirely. When biasing in space is applied to sources that use rejection sampling, current versions of MCNP do not account for the rejection in setting the source weight of histories, resulting in an 'unfair game'. This problem was circumvented in previous versions of ADVANTG by translating volumetric sources into a finite set of points, which does not alter the mean history weight ({bar w}). To use biasing parameters without otherwise modifying the original cell-rejection SDEF-format source, ADVANTG users now apply a correction factor for {bar w} in post-processing. A stratified-random sampling approach in ADVANTG is

Prediction of Protein Configurational Entropy (Popcoen).

PubMed

Goethe, Martin; Gleixner, Jan; Fita, Ignacio; Rubi, J Miguel

2018-03-13

A knowledge-based method for configurational entropy prediction of proteins is presented; this methodology is extremely fast, compared to previous approaches, because it does not involve any type of configurational sampling. Instead, the configurational entropy of a query fold is estimated by evaluating an artificial neural network, which was trained on molecular-dynamics simulations of ∼1000 proteins. The predicted entropy can be incorporated into a large class of protein software based on cost-function minimization/evaluation, in which configurational entropy is currently neglected for performance reasons. Software of this type is used for all major protein tasks such as structure predictions, proteins design, NMR and X-ray refinement, docking, and mutation effect predictions. Integrating the predicted entropy can yield a significant accuracy increase as we show exemplarily for native-state identification with the prominent protein software FoldX. The method has been termed Popcoen for Prediction of Protein Configurational Entropy. An implementation is freely available at http://fmc.ub.edu/popcoen/ .

What Were They Thinking? Reducing Sunk-Cost Bias in a Life-Span Sample

PubMed Central

Strough, JoNell; Bruine de Bruin, Wändi; Parker, Andrew M.; Karns, Tara; Lemaster, Philip; Pichayayothin, Nipat; Delaney, Rebecca; Stoiko, Rachel

2016-01-01

We tested interventions to reduce “sunk-cost bias,” the tendency to continue investing in failing plans even when those plans have soured and are no longer rewarding. We showed members of a national U.S. life-span panel a hypothetical scenario about a failing plan that was halfway complete. Participants were randomly assigned to an intervention to focus on how to improve the situation, an intervention to focus on thoughts and feelings, or a no-intervention control group. First, we found that the thoughts and feelings intervention reduced sunk-cost bias in decisions about project completion, as compared to the improvement intervention and the no-intervention control. Second, older age was associated with greater willingness to cancel the failing plan across all three groups. Third, we found that introspection processes helped to explain the effectiveness of the interventions. Specifically, the larger reduction in sunk-cost bias as observed in the thoughts and feelings intervention (vs. the improvement intervention) was associated with suppression of future-oriented thoughts of eventual success, and with suppression of augmentations of the scenario that could make it seem reasonable to continue the plan. Fourth, we found that introspection processes were related to age differences in decisions. Older people were less likely to mention future-oriented thoughts of eventual success associated with greater willingness to continue the failing plan. We discuss factors to consider when designing interventions for reducing sunk-cost bias. PMID:27831712

The role of features and configural processing in face-race classification

PubMed Central

Zhao, Lun; Bentin, Shlomo

2011-01-01

We explored perceptual factors that might account for the other-race classification advantage (ORCA) in classifying faces by race. Testing Chinese participants in China and Israeli participants in Israel we show that: (a) The distinction between Chinese and Israeli faces is highly accurate even on the basis of isolated eyes or faces with eyes concealed, but full faces are categorized faster. (b) The ORCA is similarly robust for full faces and for face parts. (c) The ORCA was larger when the configuration of the inner-face components was distorted, reflecting delayed categorization of own-race distorted faces relative to own-race normally configured faces but no conspicuous distortion effect on other-race faces. These data demonstrate that perceptual factors can account for the ORCA independently of social bias. We suggest that one source of the ORCA in race categorization is the configural analysis applied by default while processing own-race but not other-race faces. PMID:22008980

Selection bias in dynamically measured supermassive black hole samples: its consequences and the quest for the most fundamental relation

NASA Astrophysics Data System (ADS)

Shankar, Francesco; Bernardi, Mariangela; Sheth, Ravi K.; Ferrarese, Laura; Graham, Alister W.; Savorgnan, Giulia; Allevato, Viola; Marconi, Alessandro; Läsker, Ronald; Lapi, Andrea

2016-08-01

We compare the set of local galaxies having dynamically measured black holes with a large, unbiased sample of galaxies extracted from the Sloan Digital Sky Survey. We confirm earlier work showing that the majority of black hole hosts have significantly higher velocity dispersions σ than local galaxies of similar stellar mass. We use Monte Carlo simulations to illustrate the effect on black hole scaling relations if this bias arises from the requirement that the black hole sphere of influence must be resolved to measure black hole masses with spatially resolved kinematics. We find that this selection effect artificially increases the normalization of the Mbh-σ relation by a factor of at least ˜3; the bias for the Mbh-Mstar relation is even larger. Our Monte Carlo simulations and analysis of the residuals from scaling relations both indicate that σ is more fundamental than Mstar or effective radius. In particular, the Mbh-Mstar relation is mostly a consequence of the Mbh-σ and σ-Mstar relations, and is heavily biased by up to a factor of 50 at small masses. This helps resolve the discrepancy between dynamically based black hole-galaxy scaling relations versus those of active galaxies. Our simulations also disfavour broad distributions of black hole masses at fixed σ. Correcting for this bias suggests that the calibration factor used to estimate black hole masses in active galaxies should be reduced to values of fvir ˜ 1. Black hole mass densities should also be proportionally smaller, perhaps implying significantly higher radiative efficiencies/black hole spins. Reducing black hole masses also reduces the gravitational wave signal expected from black hole mergers.

Ethnic Group Bias in Intelligence Test Items.

ERIC Educational Resources Information Center

Scheuneman, Janice

In previous studies of ethnic group bias in intelligence test items, the question of bias has been confounded with ability differences between the ethnic group samples compared. The present study is based on a conditional probability model in which an unbiased item is defined as one where the probability of a correct response to an item is the…

Flux-trapping during the formation of field-reversed configurations

NASA Astrophysics Data System (ADS)

Armstrong, W. T.; Harding, D. G.; Crawford, E. A.; Hoffman, A. L.

1982-11-01

Flux-trapping during the early formation phases of a field-reversed configuration has been studied experimentally on the field-reversed theta-pinch TRX-1. An annular z-pinch preionizer was employed to permit ionization at high values of reverse-bias flux. Contrary to previous analysis, the rate of flux loss was not governed exclusively by inertially limited plasma convection to the tube walls. At high reverse flux levels, a pressure bearing sheath was observed to form at the tube walls and the flux loss was restricted by resistive diffusion across this sheath. The characteristic time for flux loss was 0.08rt (cm) μsec, independent of the bias field and independent of the fill pressure for fill pressures above 15 mTorr D2. Octopole barrier fields were found to be effective in limiting the inertially governed flux loss at very early times before the wall sheath formed.

Bi-directional flow induced by an AC electroosmotic micropump with DC voltage bias.

PubMed

Islam, Nazmul; Reyna, Jairo

2012-04-01

This paper discusses the principle of biased alternating current electroosmosis (ACEO) and its application to move the bulk fluid in a microchannel, as an alternative to mechanical pumping methods. Previous EO-driven flow research has looked at the effect of electrode asymmetry and transverse traveling wave forms on the performance of electroosmotic pumps. This paper presents an analysis that was conducted to assess the effect of combining an AC signal with a DC (direct current) bias when generating the electric field needed to impart electroosmosis (EO) within a microchannel. The results presented here are numerical and experimental. The numerical results were generated through simulations performed using COMSOL 3.5a. Currently available theoretical models for EO flows were embedded in the software and solved numerically to evaluate the effects of channel geometry, frequency of excitation, electrode array geometry, and AC signal with a DC bias on the flow imparted on an electrically conducting fluid. Simulations of the ACEO flow driven by a constant magnitude of AC voltage over symmetric electrodes did not indicate relevant net flows. However, superimposing a DC signal over the AC signal on the same symmetric electrode array leads to a noticeable net forward flow. Moreover, changing the polarity of electrical signal creates a bi-directional flow on symmetrical electrode array. Experimental flow measurements were performed on several electrode array configurations. The mismatch between the numerical and experimental results revealed the limitations of the currently available models for the biased EO. However, they confirm that using a symmetric electrode array excited by an AC signal with a DC bias leads to a significant improvement in flow rates in comparison to the flow rates obtained in an asymmetric electrode array configuration excited just with an AC signal. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Deeper than Shallow: Evidence for Structure-Based Parsing Biases in Second-Language Sentence Processing

ERIC Educational Resources Information Center

Witzel, Jeffrey; Witzel, Naoko; Nicol, Janet

2012-01-01

This study examines the reading patterns of native speakers (NSs) and high-level (Chinese) nonnative speakers (NNSs) on three English sentence types involving temporarily ambiguous structural configurations. The reading patterns on each sentence type indicate that both NSs and NNSs were biased toward specific structural interpretations. These…

Spatial clustering of dark matter haloes: secondary bias, neighbour bias, and the influence of massive neighbours on halo properties

NASA Astrophysics Data System (ADS)

Salcedo, Andrés N.; Maller, Ariyeh H.; Berlind, Andreas A.; Sinha, Manodeep; McBride, Cameron K.; Behroozi, Peter S.; Wechsler, Risa H.; Weinberg, David H.

2018-04-01

We explore the phenomenon commonly known as halo assembly bias, whereby dark matter haloes of the same mass are found to be more or less clustered when a second halo property is considered, for haloes in the mass range 3.7 × 1011-5.0 × 1013 h-1 M⊙. Using the Large Suite of Dark Matter Simulations (LasDamas) we consider nine commonly used halo properties and find that a clustering bias exists if haloes are binned by mass or by any other halo property. This secondary bias implies that no single halo property encompasses all the spatial clustering information of the halo population. The mean values of some halo properties depend on their halo's distance to a more massive neighbour. Halo samples selected by having high values of one of these properties therefore inherit a neighbour bias such that they are much more likely to be close to a much more massive neighbour. This neighbour bias largely accounts for the secondary bias seen in haloes binned by mass and split by concentration or age. However, haloes binned by other mass-like properties still show a secondary bias even when the neighbour bias is removed. The secondary bias of haloes selected by their spin behaves differently than that for other halo properties, suggesting that the origin of the spin bias is different than of other secondary biases.

Conservative Tests under Satisficing Models of Publication Bias.

PubMed

McCrary, Justin; Christensen, Garret; Fanelli, Daniele

2016-01-01

Publication bias leads consumers of research to observe a selected sample of statistical estimates calculated by producers of research. We calculate critical values for statistical significance that could help to adjust after the fact for the distortions created by this selection effect, assuming that the only source of publication bias is file drawer bias. These adjusted critical values are easy to calculate and differ from unadjusted critical values by approximately 50%-rather than rejecting a null hypothesis when the t-ratio exceeds 2, the analysis suggests rejecting a null hypothesis when the t-ratio exceeds 3. Samples of published social science research indicate that on average, across research fields, approximately 30% of published t-statistics fall between the standard and adjusted cutoffs.

Conservative Tests under Satisficing Models of Publication Bias

PubMed Central

McCrary, Justin; Christensen, Garret; Fanelli, Daniele

2016-01-01

Publication bias leads consumers of research to observe a selected sample of statistical estimates calculated by producers of research. We calculate critical values for statistical significance that could help to adjust after the fact for the distortions created by this selection effect, assuming that the only source of publication bias is file drawer bias. These adjusted critical values are easy to calculate and differ from unadjusted critical values by approximately 50%—rather than rejecting a null hypothesis when the t-ratio exceeds 2, the analysis suggests rejecting a null hypothesis when the t-ratio exceeds 3. Samples of published social science research indicate that on average, across research fields, approximately 30% of published t-statistics fall between the standard and adjusted cutoffs. PMID:26901834

Some insights into analytical bias involved in the application of grab sampling for volatile organic compounds: a case study against used Tedlar bags.

PubMed

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.

Effect of Malmquist bias on correlation studies with IRAS data base

NASA Technical Reports Server (NTRS)

Verter, Frances

1993-01-01

The relationships between galaxy properties in the sample of Trinchieri et al. (1989) are reexamined with corrections for Malmquist bias. The linear correlations are tested and linear regressions are fit for log-log plots of L(FIR), L(H-alpha), and L(B) as well as ratios of these quantities. The linear correlations for Malmquist bias are corrected using the method of Verter (1988), in which each galaxy observation is weighted by the inverse of its sampling volume. The linear regressions are corrected for Malmquist bias by a new method invented here in which each galaxy observation is weighted by its sampling volume. The results of correlation and regressions among the sample are significantly changed in the anticipated sense that the corrected correlation confidences are lower and the corrected slopes of the linear regressions are lower. The elimination of Malmquist bias eliminates the nonlinear rise in luminosity that has caused some authors to hypothesize additional components of FIR emission.

Attention bias modification training under working memory load increases the magnitude of change in attentional bias.

PubMed

Clarke, Patrick J F; Branson, Sonya; Chen, Nigel T M; Van Bockstaele, Bram; Salemink, Elske; MacLeod, Colin; Notebaert, Lies

2017-12-01

Attention bias modification (ABM) procedures have shown promise as a therapeutic intervention, however current ABM procedures have proven inconsistent in their ability to reliably achieve the requisite change in attentional bias needed to produce emotional benefits. This highlights the need to better understand the precise task conditions that facilitate the intended change in attention bias in order to realise the therapeutic potential of ABM procedures. Based on the observation that change in attentional bias occurs largely outside conscious awareness, the aim of the current study was to determine if an ABM procedure delivered under conditions likely to preclude explicit awareness of the experimental contingency, via the addition of a working memory load, would contribute to greater change in attentional bias. Bias change was assessed among 122 participants in response to one of four ABM tasks given by the two experimental factors of ABM training procedure delivered either with or without working memory load, and training direction of either attend-negative or avoid-negative. Findings revealed that avoid-negative ABM procedure under working memory load resulted in significantly greater reductions in attentional bias compared to the equivalent no-load condition. The current findings will require replication with clinical samples to determine the utility of the current task for achieving emotional benefits. These present findings are consistent with the position that the addition of a working memory load may facilitate change in attentional bias in response to an ABM training procedure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Is there gender bias in nursing research?

PubMed

Polit, Denise F; Beck, Cheryl Tatano

2008-10-01

Using data from a consecutive sample of 259 studies published in four leading nursing research journals in 2005-2006, we examined whether nurse researchers favor females as study participants. On average, 75.3% of study participants were female, and 38% of studies had all-female samples. The bias favoring female participants was statistically significant and persistent. The bias was observed regardless of funding source, methodological features, and other participant and researcher characteristics, with one exception: studies that had male investigators had more sex-balanced samples. When designing studies, nurse researchers need to pay close attention to who will benefit from their research and to whether they are leaving out a specific group about which there is a gap in knowledge. (c) 2008 Wiley Periodicals, Inc.

Asymmetric Cultural Effects on Perceptual Expertise Underlie an Own-Race Bias for Voices

ERIC Educational Resources Information Center

Perrachione, Tyler K.; Chiao, Joan Y.; Wong, Patrick C. M.

2010-01-01

The own-race bias in memory for faces has been a rich source of empirical work on the mechanisms of person perception. This effect is thought to arise because the face-perception system differentially encodes the relevant structural dimensions of features and their configuration based on experiences with different groups of faces. However, the…

Spatial clustering of dark matter haloes: secondary bias, neighbour bias, and the influence of massive neighbours on halo properties

DOE PAGES

Salcedo, Andres N.; Maller, Ariyeh H.; Berlind, Andreas A.; ...

2018-01-15

Here, we explore the phenomenon commonly known as halo assembly bias, whereby dark matter haloes of the same mass are found to be more or less clustered when a second halo property is considered, for haloes in the mass range 3.7 × 10 11–5.0 × 10 13 h –1 M ⊙. Using the Large Suite of Dark Matter Simulations (LasDamas) we consider nine commonly used halo properties and find that a clustering bias exists if haloes are binned by mass or by any other halo property. This secondary bias implies that no single halo property encompasses all the spatial clusteringmore » information of the halo population. The mean values of some halo properties depend on their halo's distance to a more massive neighbour. Halo samples selected by having high values of one of these properties therefore inherit a neighbour bias such that they are much more likely to be close to a much more massive neighbour. This neighbour bias largely accounts for the secondary bias seen in haloes binned by mass and split by concentration or age. However, haloes binned by other mass-like properties still show a secondary bias even when the neighbour bias is removed. The secondary bias of haloes selected by their spin behaves differently than that for other halo properties, suggesting that the origin of the spin bias is different than of other secondary biases.« less

Spatial clustering of dark matter haloes: secondary bias, neighbour bias, and the influence of massive neighbours on halo properties

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

Salcedo, Andres N.; Maller, Ariyeh H.; Berlind, Andreas A.

Here, we explore the phenomenon commonly known as halo assembly bias, whereby dark matter haloes of the same mass are found to be more or less clustered when a second halo property is considered, for haloes in the mass range 3.7 × 10 11–5.0 × 10 13 h –1 M ⊙. Using the Large Suite of Dark Matter Simulations (LasDamas) we consider nine commonly used halo properties and find that a clustering bias exists if haloes are binned by mass or by any other halo property. This secondary bias implies that no single halo property encompasses all the spatial clusteringmore » information of the halo population. The mean values of some halo properties depend on their halo's distance to a more massive neighbour. Halo samples selected by having high values of one of these properties therefore inherit a neighbour bias such that they are much more likely to be close to a much more massive neighbour. This neighbour bias largely accounts for the secondary bias seen in haloes binned by mass and split by concentration or age. However, haloes binned by other mass-like properties still show a secondary bias even when the neighbour bias is removed. The secondary bias of haloes selected by their spin behaves differently than that for other halo properties, suggesting that the origin of the spin bias is different than of other secondary biases.« less

Response Rates and Response Bias for 50 Surveys of Pediatricians

PubMed Central

Cull, William L; O'Connor, Karen G; Sharp, Sanford; Tang, Suk-fong S

2005-01-01

Research Objective To track response rates across time for surveys of pediatricians, to explore whether response bias is present for these surveys, and to examine whether response bias increases with lower response rates. Data Source/Study Setting A total of 63,473 cases were gathered from 50 different surveys of pediatricians conducted by the American Academy of Pediatrics (AAP) since 1994. Thirty-one surveys targeted active U.S. members of the AAP, six targeted pediatric residents, and the remaining 13 targeted AAP-member and nonmember pediatric subspecialists. Information for the full target samples, including nonrespondents, was collected using administrative databases of the AAP and the American Board of Pediatrics. Study Design To assess bias for each survey, age, gender, location, and AAP membership type were compared for respondents and the full target sample. Correlational analyses were conducted to examine whether surveys with lower response rates had increasing levels of response bias. Principal Findings Response rates to the 50 surveys examined declined significantly across survey years (1994–2002). Response rates ranged from 52 to 81 percent with an average of 68 percent. Comparisons between respondents and the full target samples showed the respondent group to be younger, to have more females, and to have less specialty-fellow members. Response bias was not apparent for pediatricians' geographical location. The average response bias, however, was fairly small for all factors: age (0.45 years younger), gender (1.4 percentage points more females), and membership type (1.1 percentage points fewer specialty-fellow members). Gender response bias was found to be inversely associated with survey response rates (r=−0.38). Even for the surveys with the lowest response rates, amount of response bias never exceeded 5 percentage points for gender, 3 years for age, or 3 percent for membership type. Conclusions While response biases favoring women, young

Uses and biases of volunteer water quality data

USGS Publications Warehouse

Loperfido, J.V.; Beyer, P.; Just, C.L.; Schnoor, J.L.

2010-01-01

State water quality monitoring has been augmented by volunteer monitoring programs throughout the United States. Although a significant effort has been put forth by volunteers, questions remain as to whether volunteer data are accurate and can be used by regulators. In this study, typical volunteer water quality measurements from laboratory and environmental samples in Iowa were analyzed for error and bias. Volunteer measurements of nitrate+nitrite were significantly lower (about 2-fold) than concentrations determined via standard methods in both laboratory-prepared and environmental samples. Total reactive phosphorus concentrations analyzed by volunteers were similar to measurements determined via standard methods in laboratory-prepared samples and environmental samples, but were statistically lower than the actual concentration in four of the five laboratory-prepared samples. Volunteer water quality measurements were successful in identifying and classifying most of the waters which violate United States Environmental Protection Agency recommended water quality criteria for total nitrogen (66%) and for total phosphorus (52%) with the accuracy improving when accounting for error and biases in the volunteer data. An understanding of the error and bias in volunteer water quality measurements can allow regulators to incorporate volunteer water quality data into total maximum daily load planning or state water quality reporting. ?? 2010 American Chemical Society.

Estimation and correction of visibility bias in aerial surveys of wintering ducks

USGS Publications Warehouse

Pearse, A.T.; Gerard, P.D.; Dinsmore, S.J.; Kaminski, R.M.; Reinecke, K.J.

2008-01-01

Incomplete detection of all individuals leading to negative bias in abundance estimates is a pervasive source of error in aerial surveys of wildlife, and correcting that bias is a critical step in improving surveys. We conducted experiments using duck decoys as surrogates for live ducks to estimate bias associated with surveys of wintering ducks in Mississippi, USA. We found detection of decoy groups was related to wetland cover type (open vs. forested), group size (1?100 decoys), and interaction of these variables. Observers who detected decoy groups reported counts that averaged 78% of the decoys actually present, and this counting bias was not influenced by either covariate cited above. We integrated this sightability model into estimation procedures for our sample surveys with weight adjustments derived from probabilities of group detection (estimated by logistic regression) and count bias. To estimate variances of abundance estimates, we used bootstrap resampling of transects included in aerial surveys and data from the bias-correction experiment. When we implemented bias correction procedures on data from a field survey conducted in January 2004, we found bias-corrected estimates of abundance increased 36?42%, and associated standard errors increased 38?55%, depending on species or group estimated. We deemed our method successful for integrating correction of visibility bias in an existing sample survey design for wintering ducks in Mississippi, and we believe this procedure could be implemented in a variety of sampling problems for other locations and species.

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

PubMed Central

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

Performance of an X-ray single pixel TES microcalorimeter under DC and AC biasing

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

Gottardi, L.; Kuur, J. van der; Korte, P. A. J. de

2009-12-16

We are developing Frequency Domain Multiplexing (FDM) for the read-out of TES imaging microcalorimeter arrays for future X-ray missions like IXO. In the FDM configuration the TES is AC voltage biased at a well defined frequencies (between 0.3 to 10 MHz) and acts as an AM modulating element. In this paper we will present a full comparison of the performance of a TES microcalorimeter under DC bias and AC bias at a frequency of 370 kHz. In both cases we measured the current-to-voltage characteristics, the complex impedance, the noise, the X-ray responsivity, and energy resolution. The behaviour is very similarmore » in both cases, but deviations in performances are observed for detector working points low in the superconducting transition (R/R{sub N}<0.5). The measured energy resolution at 5.89 keV is 2.7 eV for DC bias and 3.7 eV for AC bias, while the baseline resolution is 2.8 eV and 3.3 eV, respectively.« less

Investigating bias in squared regression structure coefficients

PubMed Central

Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce

2015-01-01

The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients. PMID:26217273

A review of cognitive biases in youth depression: attention, interpretation and memory.

PubMed

Platt, Belinda; Waters, Allison M; Schulte-Koerne, Gerd; Engelmann, Lina; Salemink, Elske

2017-04-01

Depression is one of the most common mental health problems in childhood and adolescence. Although data consistently show it is associated with self-reported negative cognitive styles, less is known about the mechanisms underlying this relationship. Cognitive biases in attention, interpretation and memory represent plausible mechanisms and are known to characterise adult depression. We provide the first structured review of studies investigating the nature and causal role of cognitive biases in youth depression. Key questions are (i) do cognitive biases characterise youth depression? (ii) are cognitive biases a vulnerability factor for youth depression? and (iii) do cognitive biases play a causal role in youth depression? We find consistent evidence for positive associations between attention and interpretation biases and youth depression. Stronger biases in youth with an elevated risk of depression support cognitive-vulnerability models. Preliminary evidence from cognitive bias modification paradigms supports a causal role of attention and interpretation biases in youth depression but these paradigms require testing in clinical samples before they can be considered treatment tools. Studies of memory biases in youth samples have produced mixed findings and none have investigated the causal role of memory bias. We identify numerous areas for future research in this emerging field.

Configurations and calibration methods for passive sampling techniques.

PubMed

Ouyang, Gangfeng; Pawliszyn, Janusz

2007-10-19

Passive sampling technology has developed very quickly in the past 15 years, and is widely used for the monitoring of pollutants in different environments. The design and quantification of passive sampling devices require an appropriate calibration method. Current calibration methods that exist for passive sampling, including equilibrium extraction, linear uptake, and kinetic calibration, are presented in this review. A number of state-of-the-art passive sampling devices that can be used for aqueous and air monitoring are introduced according to their calibration methods.

Autocalibration method for non-stationary CT bias correction.

PubMed

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.

Selection bias in dynamically-measured super-massive black hole samples: its consequences and the quest for the most fundamental relation

NASA Astrophysics Data System (ADS)

Shankar, Francesco; Bernardi, M.; Sheth, R. K.; Weinberg, D. H.; Miralda-Escudé, J.; Ferrarese, L.; Graham, A.; Sesana, A.; Lapi, A.; Marconi, A.; Allevato, V.; Savorgnan, G.; Laesker, R.

2016-08-01

We compare the set of local galaxies having dynamically measured black holes with a large, unbiased sample of galaxies extracted from the Sloan Digital Sky Survey. We confirm earlier work showing that the majority of black hole hosts have significantly higher velocity dispersions sigma than local galaxies of similar stellar mass. We use Monte-Carlo simulations to illustrate the effect on black hole scaling relations if this bias arises from the requirement that the black hole sphere of influence must be resolved to measure black hole masses with spatially resolved kinematics. We find that this selection effect artificially increases the normalization of the Mbh-sigma relation by a factor of at least ~3; the bias for the Mbh-Mstar relation is even larger. Our Monte Carlo simulations and analysis of the residuals from scaling relations both indicate that sigma is more fundamental than Mstar or effective radius. In particular, the Mbh-Mstar relation is mostly a consequence of the Mbh-sigma and sigma-Mstar relations, and is heavily biased by up to a factor of 50 at small masses. This helps resolve the discrepancy between dynamically-based black hole-galaxy scaling relations versus those of active galaxies. Our simulations also disfavour broad distributions of black hole masses at fixed sigma. Correcting for this bias suggests that the calibration factor used to estimate black hole masses in active galaxies should be reduced to values of fvir~1. Black hole mass densities should also be proportionally smaller, perhaps implying significantly higher radiative efficiencies/black hole spins. Reducing black hole masses also reduces the gravitational wave signal expected from black hole mergers.

The role of observer bias in the North American Breeding Bird Survey

USGS Publications Warehouse

Faanes, C.A.; Bystrak, D.

1981-01-01

Ornithologists sampling breeding bird populations are subject to a number of biases in bird recognition and identification. Using Breeding Bird Survey data, these biases are examined qualitatively and quantitatively, and their effects on counts are evaluated. Differences in hearing ability and degree of expertise are the major observer biases considered. Other, more subtle influences are also discussed, including unfamiliar species, resolution, imagination, similar songs and attitude and condition of observers. In most cases, welltrained observers are comparable in ability and their differences contribute little beyond sampling error. However, just as hearing loss can affect results, so can an unprepared observer. These biases are important because they can reduce the credibility of any bird population sampling effort. Care is advised in choosing observers and in interpreting and using results when observers of variable competence are involved.

Enhanced Wang Landau sampling of adsorbed protein conformations.

PubMed

Radhakrishna, Mithun; Sharma, Sumit; Kumar, Sanat K

2012-03-21

Using computer simulations to model the folding of proteins into their native states is computationally expensive due to the extraordinarily low degeneracy of the ground state. In this paper, we develop an efficient way to sample these folded conformations using Wang Landau sampling coupled with the configurational bias method (which uses an unphysical "temperature" that lies between the collapse and folding transition temperatures of the protein). This method speeds up the folding process by roughly an order of magnitude over existing algorithms for the sequences studied. We apply this method to study the adsorption of intrinsically disordered hydrophobic polar protein fragments on a hydrophobic surface. We find that these fragments, which are unstructured in the bulk, acquire secondary structure upon adsorption onto a strong hydrophobic surface. Apparently, the presence of a hydrophobic surface allows these random coil fragments to fold by providing hydrophobic contacts that were lost in protein fragmentation. © 2012 American Institute of Physics

Attentional Bias towards Positive Emotion Predicts Stress Resilience.

PubMed

Thoern, Hanna A; Grueschow, Marcus; Ehlert, Ulrike; Ruff, Christian C; Kleim, Birgit

2016-01-01

There is extensive evidence for an association between an attentional bias towards emotionally negative stimuli and vulnerability to stress-related psychopathology. Less is known about whether selective attention towards emotionally positive stimuli relates to mental health and stress resilience. The current study used a modified Dot Probe task to investigate if individual differences in attentional biases towards either happy or angry emotional stimuli, or an interaction between these biases, are related to self-reported trait stress resilience. In a nonclinical sample (N = 43), we indexed attentional biases as individual differences in reaction time for stimuli preceded by either happy or angry (compared to neutral) face stimuli. Participants with greater attentional bias towards happy faces (but not angry faces) reported higher trait resilience. However, an attentional bias towards angry stimuli moderated this effect: The attentional bias towards happy faces was only predictive for resilience in those individuals who also endorsed an attentional bias towards angry stimuli. An attentional bias towards positive emotional stimuli may thus be a protective factor contributing to stress resilience, specifically in those individuals who also endorse an attentional bias towards negative emotional stimuli. Our findings therefore suggest a novel target for prevention and treatment interventions addressing stress-related psychopathology.

Differential shift in spatial bias over time depends on observers׳ initial bias: Observer subtypes, or regression to the mean?

PubMed

Newman, Daniel P; Loughnane, Gerard M; Abe, Rafael; Zoratti, Marco T R; Martins, Ana C P; van den Bogert, Petra C; Kelly, Simon P; O'Connell, Redmond G; Bellgrove, Mark A

2014-11-01

Healthy subjects typically exhibit a subtle bias of visuospatial attention favouring left space that is commonly termed 'pseudoneglect'. This bias is attenuated, or shifted rightwards, with decreasing alertness over time, consistent with theoretical models proposing that pseudoneglect is a result of the right hemisphere׳s dominance in regulating attention. Although this 'time-on-task effect' for spatial bias is observed when averaging across whole samples of healthy participants, Benwell, C. S. Y., Thut, G., Learmonth, G., & Harvey, M. (2013b). Spatial attention: differential shifts in pseudoneglect direction with time-on-task and initial bias support the idea of observer subtypes. Neuropsychologia, 51(13), 2747-2756 recently presented evidence that the direction and magnitude of bias exhibited by the participant early in the task (left biased, no bias, or right biased) were stable traits that predicted the direction of the subsequent time-on-task shift in spatial bias. That is, the spatial bias of participants who were initially left biased shifted in a rightward direction with time, whereas that of participants who were initially right biased shifted in a leftward direction. If valid, the data of Benwell et al. are potentially important and may demand a re-evaluation of current models of the neural networks governing spatial attention. Here we use two novel spatial attention tasks in an attempt to confirm the results of Benwell et al. We show that rather than being indicative of true participant subtypes, these data patterns are likely driven, at least in part, by 'regression towards the mean' arising from the analysis method employed. Although evidence supports the contention that trait-like individual differences in spatial bias exist within the healthy population, no clear evidence is yet available for participant/observer subtypes in the direction of time-on-task shift in spatial biases. Copyright © 2014 Elsevier Ltd. All rights reserved.

Why is "S" a Biased Estimate of [sigma]?

ERIC Educational Resources Information Center

Sanqui, Jose Almer T.; Arnholt, Alan T.

2011-01-01

This article describes a simulation activity that can be used to help students see that the estimator "S" is a biased estimator of [sigma]. The activity can be implemented using either a statistical package such as R, Minitab, or a Web applet. In the activity, the students investigate and compare the bias of "S" when sampling from different…

Personality Factors and Depressive Configurations. An Exploratory Study in an Italian Clinical Sample

PubMed Central

Straccamore, Francesca; Ruggi, Simona; Lingiardi, Vittorio; Zanardi, Raffaella; Vecchi, Sara; Oasi, Osmano

2017-01-01

Introduction: This study focuses on the relationship between personality configurations and depressive experiences. More specifically, the aim of this study is to investigate the relationship between self-criticism and dependency and personality styles or disorders, exploring the association between personality features and depressive symptoms. The two-configurations model of personality developed by Blatt (2004, 2008) is adopted as a reference point in sharing a valid framework and in understanding the results. Methods: Five instruments are administered to 51 participants with a diagnosis of depressive disorder, in accordance with DSM-IV-TR (American Psychiatric Association, 2000): Self-criticism and dependency dimensions of depression are measured with the Depressive Experiences Questionnaire (DEQ); self-reported depression is assessed with the Beck Depression Inventory-II (BDI-II); observer-rated depression is assessed with the Hamilton Depression Rating Scale (HDRS); personality is assessed with the Clinical Diagnostic Interview (CDI) and the Shedler Westen Assessment Procedure-200 (SWAP-200). Results: Only self-criticism, and not dependency, is associated with depressive symptoms. In addition, the SWAP Borderline PD Scale and the Dysphoric: Emotionally dysregulated Q-factor emerge as significant in predicting depression. Conclusions: Findings support the assumption that depressive personality configurations can enhance the vulnerability to developing depression. Theoretical and clinical implications of these results are discussed. PMID:28316575

Potential Reporting Bias in Neuroimaging Studies of Sex Differences.

PubMed

David, Sean P; Naudet, Florian; Laude, Jennifer; Radua, Joaquim; Fusar-Poli, Paolo; Chu, Isabella; Stefanick, Marcia L; Ioannidis, John P A

2018-04-17

Numerous functional magnetic resonance imaging (fMRI) studies have reported sex differences. To empirically evaluate for evidence of excessive significance bias in this literature, we searched for published fMRI studies of human brain to evaluate sex differences, regardless of the topic investigated, in Medline and Scopus over 10 years. We analyzed the prevalence of conclusions in favor of sex differences and the correlation between study sample sizes and number of significant foci identified. In the absence of bias, larger studies (better powered) should identify a larger number of significant foci. Across 179 papers, median sample size was n = 32 (interquartile range 23-47.5). A median of 5 foci related to sex differences were reported (interquartile range, 2-9.5). Few articles (n = 2) had titles focused on no differences or on similarities (n = 3) between sexes. Overall, 158 papers (88%) reached "positive" conclusions in their abstract and presented some foci related to sex differences. There was no statistically significant relationship between sample size and the number of foci (-0.048% increase for every 10 participants, p = 0.63). The extremely high prevalence of "positive" results and the lack of the expected relationship between sample size and the number of discovered foci reflect probable reporting bias and excess significance bias in this literature.

Reducing bias in survival under non-random temporary emigration

USGS Publications Warehouse

Peñaloza, Claudia L.; Kendall, William L.; Langtimm, Catherine Ann

2014-01-01

Despite intensive monitoring, temporary emigration from the sampling area can induce bias severe enough for managers to discard life-history parameter estimates toward the terminus of the times series (terminal bias). Under random temporary emigration unbiased parameters can be estimated with CJS models. However, unmodeled Markovian temporary emigration causes bias in parameter estimates and an unobservable state is required to model this type of emigration. The robust design is most flexible when modeling temporary emigration, and partial solutions to mitigate bias have been identified, nonetheless there are conditions were terminal bias prevails. Long-lived species with high adult survival and highly variable non-random temporary emigration present terminal bias in survival estimates, despite being modeled with the robust design and suggested constraints. Because this bias is due to uncertainty about the fate of individuals that are undetected toward the end of the time series, solutions should involve using additional information on survival status or location of these individuals at that time. Using simulation, we evaluated the performance of models that jointly analyze robust design data and an additional source of ancillary data (predictive covariate on temporary emigration, telemetry, dead recovery, or auxiliary resightings) in reducing terminal bias in survival estimates. The auxiliary resighting and predictive covariate models reduced terminal bias the most. Additional telemetry data was effective at reducing terminal bias only when individuals were tracked for a minimum of two years. High adult survival of long-lived species made the joint model with recovery data ineffective at reducing terminal bias because of small-sample bias. The naïve constraint model (last and penultimate temporary emigration parameters made equal), was the least efficient, though still able to reduce terminal bias when compared to an unconstrained model. Joint analysis of several

A pilot study of attention bias subtypes: examining their relation to cognitive bias and their change following cognitive behavioral therapy.

PubMed

Calamaras, Martha R; Tone, Erin B; Anderson, Page L

2012-07-01

The present investigation examined (a) whether a clinical sample of individuals with social anxiety disorder (SAD) comprises two distinct groups based on attention bias for social threat (vigilant, avoidant), (b) the relation between attention bias and cognitive bias, specifically estimates of the probability that negative social events will occur (probability bias), and (c) specific changes in attention bias following cognitive behavioral therapy for social anxiety. Participants were 24 individuals (nfemale = 7, nmale = 17; mage = 41) who met diagnostic criteria for SAD and sought treatment for fear of public speaking. Hypotheses were tested using t tests, linear regression analyses, and a mixed design analysis of variance. Results yielded evidence of 2 pretreatment groups (vigilant and avoidant). There was a significant positive correlation between vigilance for (but not avoidance of) threat and probability bias (R = .561, p < .05). After 8 weeks of treatment, the direction of change in attention bias differed between groups, such that the vigilant group became less vigilant and the avoidant group became less avoidant, with the avoidant group showing a significant change in attention bias from pretreatment to posttreatment. These findings provide very preliminary support for the idea that individuals with SAD may differ according to type attention bias, avoidant or vigilant, as these biases changed in different ways following cognitive-behavioral therapy for SAD. Further research is needed to replicate and extend these findings in order to evaluate whether SAD comprises subgroups of attentional biases. © 2012 Wiley Periodicals, Inc.

Affective forecasting bias in preschool children.

PubMed

Gautam, Shalini; Bulley, Adam; von Hippel, William; Suddendorf, Thomas

2017-07-01

Adults are capable of predicting their emotional reactions to possible future events. Nevertheless, they systematically overestimate the intensity of their future emotional reactions relative to how they feel when these events actually occur. The developmental origin of this "intensity bias" has not yet been examined. Two studies were conducted to test the intensity bias in preschool children. In the first study, 5-year-olds (N=30) predicted how they would feel if they won or lost various games. Comparisons with subsequent self-reported feelings indicated that participants overestimated how sad they would feel to lose the games but did not overestimate their happiness from winning. The second study replicated this effect in another sample of 5-year-olds (n=34) and also found evidence of an intensity bias in 4-year-olds (n=30). These findings provide the first evidence of a negative intensity bias in affective forecasting among young children. Copyright © 2017 Elsevier Inc. All rights reserved.

Switching terahertz wave with grating-coupled Kretschmann configuration.

PubMed

Jiu-Sheng, Li

2017-08-07

We present a terahertz wave switch utilizing Kretschmann configuration which consists of high-refractive-index prism-liquid crystal-periodically grooved metal grating. The switching mechanism of the terahertz switch is based on spoof surface plasmon polariton (SSPP) excitation in the attenuated total reflection regime by changing the liquid crystal refractive index. The results highlighted the fact that the feasibility to "tune" the attenuated total reflection terahertz wave intensity by using the external applied bias voltage. The extinction ratio of the terahertz switch reaches 31.48dB. The terahertz switch has good control ability and flexibility, and can be used in potential terahertz free space device systems.

Approach bias for food cues in obese individuals.

PubMed

Kemps, Eva; Tiggemann, Marika

2015-01-01

This study aimed to investigate the existence of an approach bias for food cues in obese individuals. A community sample of 56 obese women and 56 normal weight controls completed an approach-avoidance variant of the implicit association task. The obese participants were faster to respond to trials that paired food words with approach words, and trials that paired non-food words with avoid words, than the converse pairings, thus, demonstrating an approach bias for food. This bias was evident for both high caloric and low caloric food words, and was not attributable to a state of deprivation or feelings of hunger. By contrast, the normal weight controls did not show any such bias. The results are consistent with recent neurocognitive perspectives of obesity. At a practical level, approach biases for food may present a potential target for modifying (excessive) food intake.

DC currents collected by a RF biased electrode quasi-parallel to the magnetic field

NASA Astrophysics Data System (ADS)

Faudot, E.; Devaux, S.; Moritz, J.; Bobkov, V.; Heuraux, S.

2017-10-01

Local plasma biasings due to RF sheaths close to ICRF antennas result mainly in a negative DC current collection on the antenna structure. In some specific cases, we may observe positive currents when the ion mobility (seen from the collecting surface) overcomes the electron one or/and when the collecting surface on the antenna side becomes larger than the other end of the flux tube connected to the wall. The typical configuration is when the antenna surface is almost parallel to the magnetic field lines and the other side perpendicular. To test the optimal case where the magnetic field is quasi-parallel to the electrode surface, one needs a linear magnetic configuration as our magnetized RF discharge experiment called Aline. The magnetic field angle is in our case lower than 1 relative to the RF biased surface. The DC current flowing through the discharge has been measured as a function of the magnetic field strength, neutral gas (He) pressure and RF power. The main result is the reversal of the DC current depending on the magnetic field, collision frequency and RF power level.

Bias Corrections for Regional Estimates of the Time-averaged Geomagnetic Field

NASA Astrophysics Data System (ADS)

Constable, C.; Johnson, C. L.

2009-05-01

We assess two sources of bias in the time-averaged geomagnetic field (TAF) and paleosecular variation (PSV): inadequate temporal sampling, and the use of unit vectors in deriving temporal averages of the regional geomagnetic field. For the first temporal sampling question we use statistical resampling of existing data sets to minimize and correct for bias arising from uneven temporal sampling in studies of the time- averaged geomagnetic field (TAF) and its paleosecular variation (PSV). The techniques are illustrated using data derived from Hawaiian lava flows for 0-5~Ma: directional observations are an updated version of a previously published compilation of paleomagnetic directional data centered on ± 20° latitude by Lawrence et al./(2006); intensity data are drawn from Tauxe & Yamazaki, (2007). We conclude that poor temporal sampling can produce biased estimates of TAF and PSV, and resampling to appropriate statistical distribution of ages reduces this bias. We suggest that similar resampling should be attempted as a bias correction for all regional paleomagnetic data to be used in TAF and PSV modeling. The second potential source of bias is the use of directional data in place of full vector data to estimate the average field. This is investigated for the full vector subset of the updated Hawaiian data set. Lawrence, K.P., C.G. Constable, and C.L. Johnson, 2006, Geochem. Geophys. Geosyst., 7, Q07007, DOI 10.1029/2005GC001181. Tauxe, L., & Yamazkai, 2007, Treatise on Geophysics,5, Geomagnetism, Elsevier, Amsterdam, Chapter 13,p509

Chemosensory Communication of Gender Information: Masculinity Bias in Body Odor Perception and Femininity Bias Introduced by Chemosignals During Social Perception.

PubMed

Mutic, Smiljana; Moellers, Eileen M; Wiesmann, Martin; Freiherr, Jessica

2015-01-01

Human body odor is a source of important social information. In this study, we explore whether the sex of an individual can be established based on smelling axillary odor and whether exposure to male and female odors biases chemosensory and social perception. In a double-blind, pseudo-randomized application, 31 healthy normosmic heterosexual male and female raters were exposed to male and female chemosignals (odor samples of 27 heterosexual donors collected during a cardio workout) and a no odor sample. Recipients rated chemosensory samples on a masculinity-femininity scale and provided intensity, familiarity and pleasantness ratings. Additionally, the modulation of social perception (gender-neutral faces and personality attributes) and affective introspection (mood) by male and female chemosignals was assessed. Male and female axillary odors were rated as rather masculine, regardless of the sex of the donor. As opposed to the masculinity bias in the odor perception, a femininity bias modulating social perception appeared. A facilitated femininity detection in gender-neutral faces and personality attributes in male and female chemosignals appeared. No chemosensory effect on mood of the rater was observed. The results are discussed with regards to the use of male and female chemosignals in affective and social communication.

Low bias negative differential conductance and reversal of current in coupled quantum dots in different topological configurations

NASA Astrophysics Data System (ADS)

Devi, Sushila; Brogi, B. B.; Ahluwalia, P. K.; Chand, S.

2018-06-01

Electronic transport through asymmetric parallel coupled quantum dot system hybridized between normal leads has been investigated theoretically in the Coulomb blockade regime by using Non-Equilibrium Green Function formalism. A new decoupling scheme proposed by Rabani and his co-workers has been adopted to close the chain of higher order Green's functions appearing in the equations of motion. For resonant tunneling case; the calculations of current and differential conductance have been presented during transition of coupled quantum dot system from series to symmetric parallel configuration. It has been found that during this transition, increase in current and differential conductance of the system occurs. Furthermore, clear signatures of negative differential conductance and negative current appear in series case, both of which disappear when topology of system is tuned to asymmetric parallel configuration.

Sampling biases in datasets of historical mean air temperature over land.

PubMed

Wang, Kaicun

2014-04-10

Global mean surface air temperature (Ta) has been reported to have risen by 0.74°C over the last 100 years. However, the definition of mean Ta is still a subject of debate. The most defensible definition might be the integral of the continuous temperature measurements over a day (Td0). However, for technological and historical reasons, mean Ta over land have been taken to be the average of the daily maximum and minimum temperature measurements (Td1). All existing principal global temperature analyses over land rely heavily on Td1. Here, I make a first quantitative assessment of the bias in the use of Td1 to estimate trends of mean Ta using hourly Ta observations at 5600 globally distributed weather stations from the 1970s to 2013. I find that the use of Td1 has a negligible impact on the global mean warming rate. However, the trend of Td1 has a substantial bias at regional and local scales, with a root mean square error of over 25% at 5° × 5° grids. Therefore, caution should be taken when using mean Ta datasets based on Td1 to examine high resolution details of warming trends.

Parametric study of statistical bias in laser Doppler velocimetry

NASA Technical Reports Server (NTRS)

Gould, Richard D.; Stevenson, Warren H.; Thompson, H. Doyle

1989-01-01

Analytical studies have often assumed that LDV velocity bias depends on turbulence intensity in conjunction with one or more characteristic time scales, such as the time between validated signals, the time between data samples, and the integral turbulence time-scale. These parameters are presently varied independently, in an effort to quantify the biasing effect. Neither of the post facto correction methods employed is entirely accurate. The mean velocity bias error is found to be nearly independent of data validation rate.

A new dynamical downscaling approach with GCM bias corrections and spectral nudging

NASA Astrophysics Data System (ADS)

Xu, Zhongfeng; Yang, Zong-Liang

2015-04-01

To improve confidence in regional projections of future climate, a new dynamical downscaling (NDD) approach with both general circulation model (GCM) bias corrections and spectral nudging is developed and assessed over North America. GCM biases are corrected by adjusting GCM climatological means and variances based on reanalysis data before the GCM output is used to drive a regional climate model (RCM). Spectral nudging is also applied to constrain RCM-based biases. Three sets of RCM experiments are integrated over a 31 year period. In the first set of experiments, the model configurations are identical except that the initial and lateral boundary conditions are derived from either the original GCM output, the bias-corrected GCM output, or the reanalysis data. The second set of experiments is the same as the first set except spectral nudging is applied. The third set of experiments includes two sensitivity runs with both GCM bias corrections and nudging where the nudging strength is progressively reduced. All RCM simulations are assessed against North American Regional Reanalysis. The results show that NDD significantly improves the downscaled mean climate and climate variability relative to other GCM-driven RCM downscaling approach in terms of climatological mean air temperature, geopotential height, wind vectors, and surface air temperature variability. In the NDD approach, spectral nudging introduces the effects of GCM bias corrections throughout the RCM domain rather than just limiting them to the initial and lateral boundary conditions, thereby minimizing climate drifts resulting from both the GCM and RCM biases.

What is abnormal about addiction-related attentional biases?

PubMed

Anderson, Brian A

2016-10-01

The phenotype of addiction includes prominent attentional biases for drug cues, which play a role in motivating drug-seeking behavior and contribute to relapse. In a separate line of research, arbitrary stimuli have been shown to automatically capture attention when previously associated with reward in non-clinical samples. Here, I argue that these two attentional biases reflect the same cognitive process. I outline five characteristics that exemplify attentional biases for drug cues: resistant to conflicting goals, robust to extinction, linked to dorsal striatal dopamine and to biases in approach behavior, and can distinguish between individuals with and without a history of drug dependence. I then go on to describe how attentional biases for arbitrary reward-associated stimuli share all of these features, and conclude by arguing that the attentional components of addiction reflect a normal cognitive process that promotes reward-seeking behavior. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Racial and Ethnic Bias in Test Construction.

ERIC Educational Resources Information Center

Green, Donald Ross

To determine if tryout samples typically used for item selection contribute to test bias against minority groups, item analyses were made of the California Achievement Tests using seven sub-groups of the standardization sample: Northern White Suburban, Northern Black Urban, Southern White Suburban, Southern Black Rural, Southern White Rural,…

Modulated exchange bias in NiFe/CoO/α-Fe2O3 trilayers and NiFe/CoO bilayers

NASA Astrophysics Data System (ADS)

Li, X.; Lin, K.-W.; Yeh, W.-C.; Desautels, R. D.; van Lierop, J.; Pong, Philip W. T.

2017-02-01

While the exchange bias in ferromagnetic/antiferromagnetic (FM/AF) bilayer and FM1/AF/FM2 trilayer configurations has been widely investigated, the role of an AF2 layer in FM/AF1/AF2 trilayer configurations is still not well understood. In this work, the magnetic properties of NiFe/CoO, NiFe/α-Fe2O3 bilayers, and NiFe/CoO/α-Fe2O3 trilayer were studied comparatively. The microstructure and chemical composition were characterized. Temperature dependent magnetometry reveals increased irreversibility temperature in NiFe/CoO/α-Fe2O3 trilayer compared with NiFe/CoO bilayer. The magnetic hysteresis loops show that the exchange bias (Hex) and coercivity (Hc) depend strongly on the anisotropy of AF layer (CoO, α-Fe2O3 and CoO/α-Fe2O3). Our work shows that the AF1/AF2 interfacial interactions can be used effectively for tuning the exchange bias in FM/AF1/AF2 trilayers.

Bias-Corrected Estimation of Noncentrality Parameters of Covariance Structure Models

ERIC Educational Resources Information Center

Raykov, Tenko

2005-01-01

A bias-corrected estimator of noncentrality parameters of covariance structure models is discussed. The approach represents an application of the bootstrap methodology for purposes of bias correction, and utilizes the relation between average of resample conventional noncentrality parameter estimates and their sample counterpart. The…

Bias-dependent local structure of water molecules at an electrochemical interface

NASA Astrophysics Data System (ADS)

Pedroza, Luana; Brandimarte, Pedro; Rocha, Alexandre R.; Fernandez-Serra, Marivi

2015-03-01

Following the need for new - and renewable - sources of energy worldwide, fuel cells using electrocatalysts can be thought of as a viable option. Understanding the local structure of water molecules at the interfaces of the metallic electrodes is a key problem. Notably the system is under an external potential bias, which makes the task of simulating this setup difficult. A first principle description of all components of the system is the most appropriate methodology in order to advance understanding of electrochemical processes. There, the metal is usually charged. To correctly compute the effect of an external bias potential applied to electrodes, we combine density functional theory (DFT) and non-equilibrium Green's functions methods (NEGF), with and without van der Waals interactions. In this work, we apply this methodology to study the electronic properties and forces of one water molecule and water monolayer at the interface of gold electrodes. We find that the water molecule has a different torque direction depending on the sign of the bias applied. We also show that it changes the position of the most stable configuration indicating that the external bias plays an important role in the structural properties of the interface. We acknowledge financial support from FAPESP.

Goniochromatic and sparkle properties of effect pigmented samples in multidimensional configuration

NASA Astrophysics Data System (ADS)

Höpe, Andreas; Hauer, Kai-Olaf; Teichert, Sven; Hünerhoff, Dirk; Strothkämper, Christian

2015-03-01

The effects of goniochromatism and sparkle are gaining more and more interest for surface refinement applications driven by demanding requirements from such different branches as automotive, cosmetics, printing and packaging industry. The common background and intention in all of these implementations is improvement of the visual appearance of the related commercial products. Goniochromatic materials show strong angular-dependent reflection characteristics and hence a color impression depending on the effective spatial arrangement of illumination and observation relative to the surface of the artifact. Sparkle is a texture related effect giving a surface which is irradiated directionally, like direct sun light, a bright glittering effect, similar to twinkling stars at the night sky. The prototype for this new effect is the Xirallic® pigment of MERCK KGaA, Germany. The same pigment shows in diffuse irradiation, like on a cloudy day, a different visual effect called graininess (coarseness) which appears as a granular structure of the surface. Both effects were studied on especially manufactured samples of a dilution series in pigment concentration and a tonality series with carbon black. The experiments were carried out with the robot-based gonioreflectometer and integrating sphere facilities at Physikalisch-Technische Bundesanstalt (PTB) in multidimensional configurations of directional and diffuse irradiation. The research is part of the European Metrology Research Program (EMRP), which is a metrology-focused program of coordinated Research & Development (R&D) funded by the European Commission and participating countries within the European Association of National Metrology Institutes (EURAMET). More information and updated news concerning the project can be found on the xD-Reflect website http://www.xdreflect.eu/.

Sample selection may bias the outcome of an adolescent mental health survey: results from a five-year follow-up of 4171 adolescents.

PubMed

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.

Spin effects in transport through triangular quantum dot molecule in different geometrical configurations

NASA Astrophysics Data System (ADS)

Wrześniewski, Kacper; Weymann, Ireneusz

2015-07-01

We analyze the spin-resolved transport properties of a triangular quantum dot molecule weakly coupled to external ferromagnetic leads. The calculations are performed by using the real-time diagrammatic technique up to the second-order of perturbation theory, which enables a description of both the sequential and cotunneling processes. We study the behavior of the current and differential conductance in the parallel and antiparallel magnetic configurations, as well as the tunnel magnetoresistance (TMR) and the Fano factor in both the linear and nonlinear response regimes. It is shown that the transport characteristics depend greatly on how the system is connected to external leads. Two specific geometrical configurations of the device are considered—the mirror one, which possesses the reflection symmetry with respect to the current flow direction and the fork one, in which this symmetry is broken. In the case of first configuration we show that, depending on the bias and gate voltages, the system exhibits both enhanced TMR and super-Poissonian shot noise. On the other hand, when the system is in the second configuration, we predict a negative TMR and a negative differential conductance in certain transport regimes. The mechanisms leading to those effects are thoroughly discussed.

Analysis of Nonresponse Bias in Research for Business Education

ERIC Educational Resources Information Center

Bartlett, James E., II; Bartlett, Michelle E.; Reio, Thomas G., Jr.

2008-01-01

This research examined the issue of nonresponse bias and how it was reported in nonexperimental quantitative research published in the "Delta Pi Epsilon Journal" between 1995 and 2004. Through content analysis, 85 articles consisting of 91 separate samples were examined. In 72.5% of the cases, possible nonresponse bias was not examined in the…

Meta-assessment of bias in science

PubMed Central

Fanelli, Daniele; Costas, Rodrigo; Ioannidis, John P. A.

2017-01-01

Numerous biases are believed to affect the scientific literature, but their actual prevalence across disciplines is unknown. To gain a comprehensive picture of the potential imprint of bias in science, we probed for the most commonly postulated bias-related patterns and risk factors, in a large random sample of meta-analyses taken from all disciplines. The magnitude of these biases varied widely across fields and was overall relatively small. However, we consistently observed a significant risk of small, early, and highly cited studies to overestimate effects and of studies not published in peer-reviewed journals to underestimate them. We also found at least partial confirmation of previous evidence suggesting that US studies and early studies might report more extreme effects, although these effects were smaller and more heterogeneously distributed across meta-analyses and disciplines. Authors publishing at high rates and receiving many citations were, overall, not at greater risk of bias. However, effect sizes were likely to be overestimated by early-career researchers, those working in small or long-distance collaborations, and those responsible for scientific misconduct, supporting hypotheses that connect bias to situational factors, lack of mutual control, and individual integrity. Some of these patterns and risk factors might have modestly increased in intensity over time, particularly in the social sciences. Our findings suggest that, besides one being routinely cautious that published small, highly-cited, and earlier studies may yield inflated results, the feasibility and costs of interventions to attenuate biases in the literature might need to be discussed on a discipline-specific and topic-specific basis. PMID:28320937

Test-to-Test Repeatability of Results From a Subsonic Wing-Body Configuration in the National Transonic Facility

NASA Technical Reports Server (NTRS)

Mineck, Raymond E.; Pendergraft, Odis C., Jr.

2000-01-01

Results from three wind tunnel tests in the National Transonic Facility of a model of an advanced-technology, subsonic-transport wing-body configuration have been analyzed to assess the test-to-test repeatability of several aerodynamic parameters. The scatter, as measured by the prediction interval, in the longitudinal force and moment coefficients increases as the Mach number increases. Residual errors with and without the ESP tubes installed suggest a bias leading to lower drag with the tubes installed. Residual errors as well as average values of the longitudinal force and moment coefficients show that there are small bias errors between the different tests.

Weight Bias in University Health Professions Students.

PubMed

Blanton, Cynthia; Brooks, Jennifer K; McKnight, Laura

2016-01-01

Negative attitudes toward people with high body weight have been documented in pre-professional health students, prompting concern that such feelings may manifest as poor patient care in professional practice. This study assessed weight bias in university students in the non-physician health professions. A convenience sample of 206 students completed an online survey composed of a validated 14-item scale (1-5 lowest to highest weight bias) and questions regarding personal experiences of weight bias. Respondents were grouped by discipline within graduate and undergraduate levels. Weight bias was present in a majority of respondents. Overall, the percentage of responses indicative of weight bias was 92.7%. The mean total score was 3.65. ± 0.52, and the rating exceeded 3 for all 14 scale descriptors of high-weight people. In graduate students, discipline had a significant main effect on total score (p=0.01), with lower scores in dietetics (3.17 ± 0.46) vs audiology/sign language/speech language pathology (3.84 ± 0.41) and physician assistant students (3.78 ± 0.51; p<0.05). These findings show that weight bias is prevalent in health professions students at a mountain west university. Well-controlled studies that track students into professional practice would help determine whether bias-reduction interventions in college improve provider behaviors and clinical outcomes.

Visual search attentional bias modification reduced social phobia in adolescents.

PubMed

De Voogd, E L; Wiers, R W; Prins, P J M; Salemink, E

2014-06-01

An attentional bias for negative information plays an important role in the development and maintenance of (social) anxiety and depression, which are highly prevalent in adolescence. Attention Bias Modification (ABM) might be an interesting tool in the prevention of emotional disorders. The current study investigated whether visual search ABM might affect attentional bias and emotional functioning in adolescents. A visual search task was used as a training paradigm; participants (n = 16 adolescents, aged 13-16) had to repeatedly identify the only smiling face in a 4 × 4 matrix of negative emotional faces, while participants in the control condition (n = 16) were randomly allocated to one of three placebo training versions. An assessment version of the task was developed to directly test whether attentional bias changed due to the training. Self-reported anxiety and depressive symptoms and self-esteem were measured pre- and post-training. After two sessions of training, the ABM group showed a significant decrease in attentional bias for negative information and self-reported social phobia, while the control group did not. There were no effects of training on depressive mood or self-esteem. No correlation between attentional bias and social phobia was found, which raises questions about the validity of the attentional bias assessment task. Also, the small sample size precludes strong conclusions. Visual search ABM might be beneficial in changing attentional bias and social phobia in adolescents, but further research with larger sample sizes and longer follow-up is needed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Narrow-band microwave radiation from a biased single-Cooper-pair transistor.

PubMed

Naaman, O; Aumentado, J

2007-06-01

We show that a single-Cooper-pair transistor (SCPT) electrometer emits narrow-band microwave radiation when biased in its subgap region. Photoexcitation of quasiparticle tunneling in a nearby SCPT is used to spectroscopically detect this radiation in a configuration that closely mimics a qubit-electrometer integrated circuit. We identify emission lines due to Josephson radiation and radiative transport processes in the electrometer and argue that a dissipative superconducting electrometer can severely disrupt the system it attempts to measure.

Biased Tests.

ERIC Educational Resources Information Center

Green, Donald Ross

This paper is concerned with the accusations made by such groups as the Association of Black Psychologists in their call for a moratorium on testing, that standardized tests are biased. A biased test measures one trait in one group of people but a different trait in a second group. Evidence about the amount of bias in tests is thin. Bias must be…

Implications of weight-based stigma and self-bias on quality of life among individuals with Schizophrenia

PubMed Central

Barber, Jessica; Palmese, Laura; Reutenauer, Erin L.; Grilo, Carlos; Tek, Cenk

2011-01-01

Obesity has been associated with significant stigma and weight-related self-bias in community and clinical studies, but these issues have not been studied among individuals with schizophrenia. A consecutive series of 70 obese individuals with schizophrenia or schizoaffective disorder underwent assessment for perceptions of weight-based stigmatization, self-directed weight-bias, negative affect, medication compliance, and quality of life. Levels of weight-based stigmatization and self-bias were compared to levels reported for non-psychiatric overweight/obese samples. Weight measures were unrelated to stigma, self-bias, affect, and quality of life. Weight-based stigmatization was lower than published levels for non-psychiatric samples, whereas levels of weight-based self-bias did not differ. After controlling for negative affect, weight-based self-bias predicted an additional 11% of the variance in the quality of life measure. Individuals with schizophrenia and schizoaffective disorder reported weight-based self-bias to the same extent as non-psychiatric samples despite reporting less weight stigma. Weight-based self-bias was associated with poorer quality of life after controlling for negative affect. PMID:21716053

Bias of damped Lyman-α systems from their cross-correlation with CMB lensing

DOE PAGES

Alonso, D.; Colosimo, J.; Font-Ribera, A.; ...

2018-04-20

We cross-correlate the positions of damped Lyman-α systems (DLAs) and their parent quasar catalog with a convergence map derived from the Planck cosmic microwave background (CMB) temperature data. We then make consistent measurements of the lensing signal of both samples in both Fourier and configuration space. By interpreting the excess signal present in the DLA catalog with respect to the parent quasar catalog as caused by the large scale structure traced by DLAs, we are able to infer the bias of these objects: b DLA=2.6±0.9. These results are consistent with previous measurements made in cross-correlation with the Lyman-α forest, althoughmore » the current noise in the lensing data and the low number density of DLAs limits the constraining power of this measurement. We discuss the robustness of the analysis with respect to a number different systematic effects and forecast prospects of carrying out this measurement with data from future experiments.« less

Bias of damped Lyman-α systems from their cross-correlation with CMB lensing

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

Alonso, D.; Colosimo, J.; Font-Ribera, A.

We cross-correlate the positions of damped Lyman-α systems (DLAs) and their parent quasar catalog with a convergence map derived from the Planck cosmic microwave background (CMB) temperature data. We then make consistent measurements of the lensing signal of both samples in both Fourier and configuration space. By interpreting the excess signal present in the DLA catalog with respect to the parent quasar catalog as caused by the large scale structure traced by DLAs, we are able to infer the bias of these objects: b DLA=2.6±0.9. These results are consistent with previous measurements made in cross-correlation with the Lyman-α forest, althoughmore » the current noise in the lensing data and the low number density of DLAs limits the constraining power of this measurement. We discuss the robustness of the analysis with respect to a number different systematic effects and forecast prospects of carrying out this measurement with data from future experiments.« less

Bias of damped Lyman-α systems from their cross-correlation with CMB lensing

NASA Astrophysics Data System (ADS)

Alonso, D.; Colosimo, J.; Font-Ribera, A.; Slosar, A.

2018-04-01

We cross-correlate the positions of damped Lyman-α systems (DLAs) and their parent quasar catalog with a convergence map derived from the Planck cosmic microwave background (CMB) temperature data. We make consistent measurements of the lensing signal of both samples in both Fourier and configuration space. By interpreting the excess signal present in the DLA catalog with respect to the parent quasar catalog as caused by the large scale structure traced by DLAs, we are able to infer the bias of these objects: bDLA=2.6±0.9. These results are consistent with previous measurements made in cross-correlation with the Lyman-α forest, although the current noise in the lensing data and the low number density of DLAs limits the constraining power of this measurement. We discuss the robustness of the analysis with respect to a number different systematic effects and forecast prospects of carrying out this measurement with data from future experiments.

Memory Device and Nanofabrication Techniques Using Electrically Configurable Materials

NASA Astrophysics Data System (ADS)

Ascenso Simões, Bruno

Development of novel nanofabrication techniques and single-walled carbon nanotubes field configurable transistor (SWCNT-FCT) memory devices using electrically configurable materials is presented. A novel lithographic technique, electric lithography (EL), that uses electric field for pattern generation has been demonstrated. It can be used for patterning of biomolecules on a polymer surface and patterning of resist as well. Using electrical resist composed of a polymer having Boc protected amine group and iodonium salt, Boc group on the surface of polymer was modified to free amine by applying an electric field. On the modified surface of the polymer, Streptavidin pattern was fabricated with a sub-micron scale. Also patterning of polymer resin composed of epoxy monomers and diaryl iodonium salt by EL has been demonstrated. Reaction mechanism for electric resist configuration is believed to be induced by an acid generation via electrochemical reduction in the resist. We show a novel field configurable transistor (FCT) based on single-walled carbon nanotube network field-effect transistors in which poly (ethylene glycol) crosslinked by electron-beam is incorporated into the gate. The device conductance can be configured to arbitrary states reversibly and repeatedly by applying external gate voltages. Raman spectroscopy revealed that evolution of the ratio of D- to G-band intensity in the SWCNTs of the FCT progressively increases as the device is configured to lower conductance states. Electron transport studies at low temperatures showed a strong temperature dependence of the resistance. Band gap widening of CNTs up to ˜ 4 eV has been observed by examining the differential conductance-gate voltage-bias voltage relationship. The switching mechanism of the FCT is attributed a structural transformation of CNTs via reversible hydrogenation and dehydrogenations induced by gate voltages, which tunes the CNT bandgap continuously and reversibly to non-volatile analog values

Spin-torque driven magnetization switching in ferromagnetic nanopillar with pinned layer biasing configuration

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

Bhoomeeswaran, H.; Sabareesan, P., E-mail: sendtosabari@gmail.com; Bharathi, B. Divya

2016-05-06

Magnetization switching driven by spin transfer torque in a ferromagnetic nanopillar by biasing the angular polarizer with different orientation has been studied. The free layer dynamics includes the spin torque from the oscillating free layer with magneto crystalline anisotropy and shape anisotropy, which is governed by the Landau-Lifshitsz-Gilbert-Slonczweski (LLGS) equation and solving it numerically by using embedded Runge Kutta fourth order method. Results of numerical simulation shows that there is a drastic reduction of switching time in the free layer by the orientation of angular polarizer of the nano pillar device. We fixed the angular polarizer as 0°, 30°, 60°,more » 90° and the corresponding switching time is 6.53 ns, 4.36 ns, 2.25 ns and 1.21 ns respectively for an applied current density of 5 × 10{sup 11} Am{sup −2}.« less

Dynamic positioning configuration and its first-order optimization

NASA Astrophysics Data System (ADS)

Xue, Shuqiang; Yang, Yuanxi; Dang, Yamin; Chen, Wu

2014-02-01

symmetrical cone configuration and helical curve configuration are still D-optimal. It shows that the given total observation time determines the optimal frequency (repeatability) of moving known points and vice versa, and one way to improve the repeatability is to increase the rotational speed. Under the Newton's law of motion, the frequency of satellite motion determines the orbital altitude. Furthermore, we study three kinds of complex dynamic configurations, one of which is the combination of D-optimal cone configurations and a so-called Walker constellation composed of D-optimal helical configuration, the other is the nested cone configuration composed of n cones, and the last is the nested helical configuration composed of n orbital planes. It shows that an effective way to achieve high coverage is to employ the configuration composed of a certain number of moving known points instead of the simplex configuration (such as D-optimal helical configuration), and one can use the D-optimal simplex solutions or D-optimal complex configurations in any combination to achieve powerful configurations with flexile coverage and flexile repeatability. Alternately, how to optimally generate and assess the discrete configurations sampled from the continuous one is discussed. The proposed configuration optimization framework has taken the well-known regular polygons (such as equilateral triangle and quadrangular) in two-dimensional space and regular polyhedrons (regular tetrahedron, cube, regular octahedron, regular icosahedron, or regular dodecahedron) into account. It shows that the conclusions made by the proposed technique are more general and no longer limited by different sampling schemes. By the conditional equation of D-optimal nested helical configuration, the relevance issues of GNSS constellation optimization are solved and some examples are performed by GPS constellation to verify the validation of the newly proposed optimization technique. The proposed technique is

Influence of growth conditions on exchange bias of NiMn-based spin valves

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

Wienecke, Anja; Kruppe, Rahel; Rissing, Lutz

2015-05-07

As shown in previous investigations, a correlation between a NiMn-based spin valve's thermal stability and its inherent exchange bias exists, even if the blocking temperature of the antiferromagnet is clearly above the heating temperature and the reason for thermal degradation is mainly diffusion and not the loss of exchange bias. Samples with high exchange bias are thermally more stable than samples with low exchange bias. Those structures promoting a high exchange bias are seemingly the same suppressing thermally induced diffusion processes (A. Wienecke and L. Rissing, “Relationship between thermal stability and layer-stack/structure of NiMn-based GMR systems,” in IEEE Transaction onmore » Magnetic Conference (EMSA 2014)). Many investigations were carried out on the influence of the sputtering parameters as well as the layer thickness on the magnetoresistive effect. The influence of these parameters on the exchange bias and the sample's thermal stability, respectively, was hardly taken into account. The investigation described here concentrates on the last named issue. The focus lies on the influence of the sputtering parameters and layer thickness of the “starting layers” in the stack and the layers forming the (synthetic) antiferromagnet. This paper includes a guideline for the evaluated sputtering conditions and layer thicknesses to realize a high exchange bias and presumably good thermal stability for NiMn-based spin valves with a synthetic antiferromagnet.« less

Bias, Confounding, and Interaction: Lions and Tigers, and Bears, Oh My!

PubMed

Vetter, Thomas R; Mascha, Edward J

2017-09-01

Epidemiologists seek to make a valid inference about the causal effect between an exposure and a disease in a specific population, using representative sample data from a specific population. Clinical researchers likewise seek to make a valid inference about the association between an intervention and outcome(s) in a specific population, based upon their randomly collected, representative sample data. Both do so by using the available data about the sample variable to make a valid estimate about its corresponding or underlying, but unknown population parameter. Random error in an experiment can be due to the natural, periodic fluctuation or variation in the accuracy or precision of virtually any data sampling technique or health measurement tool or scale. In a clinical research study, random error can be due to not only innate human variability but also purely chance. Systematic error in an experiment arises from an innate flaw in the data sampling technique or measurement instrument. In the clinical research setting, systematic error is more commonly referred to as systematic bias. The most commonly encountered types of bias in anesthesia, perioperative, critical care, and pain medicine research include recall bias, observational bias (Hawthorne effect), attrition bias, misclassification or informational bias, and selection bias. A confounding variable is a factor associated with both the exposure of interest and the outcome of interest. A confounding variable (confounding factor or confounder) is a variable that correlates (positively or negatively) with both the exposure and outcome. Confounding is typically not an issue in a randomized trial because the randomized groups are sufficiently balanced on all potential confounding variables, both observed and nonobserved. However, confounding can be a major problem with any observational (nonrandomized) study. Ignoring confounding in an observational study will often result in a "distorted" or incorrect estimate of

Chemosensory Communication of Gender Information: Masculinity Bias in Body Odor Perception and Femininity Bias Introduced by Chemosignals During Social Perception

PubMed Central

Mutic, Smiljana; Moellers, Eileen M.; Wiesmann, Martin; Freiherr, Jessica

2016-01-01

Human body odor is a source of important social information. In this study, we explore whether the sex of an individual can be established based on smelling axillary odor and whether exposure to male and female odors biases chemosensory and social perception. In a double-blind, pseudo-randomized application, 31 healthy normosmic heterosexual male and female raters were exposed to male and female chemosignals (odor samples of 27 heterosexual donors collected during a cardio workout) and a no odor sample. Recipients rated chemosensory samples on a masculinity-femininity scale and provided intensity, familiarity and pleasantness ratings. Additionally, the modulation of social perception (gender-neutral faces and personality attributes) and affective introspection (mood) by male and female chemosignals was assessed. Male and female axillary odors were rated as rather masculine, regardless of the sex of the donor. As opposed to the masculinity bias in the odor perception, a femininity bias modulating social perception appeared. A facilitated femininity detection in gender-neutral faces and personality attributes in male and female chemosignals appeared. No chemosensory effect on mood of the rater was observed. The results are discussed with regards to the use of male and female chemosignals in affective and social communication. PMID:26834656

Efficiently estimating salmon escapement uncertainty using systematically sampled data

USGS Publications Warehouse

Reynolds, Joel H.; Woody, Carol Ann; Gove, Nancy E.; Fair, Lowell F.

2007-01-01

Fish escapement is generally monitored using nonreplicated systematic sampling designs (e.g., via visual counts from towers or hydroacoustic counts). These sampling designs support a variety of methods for estimating the variance of the total escapement. Unfortunately, all the methods give biased results, with the magnitude of the bias being determined by the underlying process patterns. Fish escapement commonly exhibits positive autocorrelation and nonlinear patterns, such as diurnal and seasonal patterns. For these patterns, poor choice of variance estimator can needlessly increase the uncertainty managers have to deal with in sustaining fish populations. We illustrate the effect of sampling design and variance estimator choice on variance estimates of total escapement for anadromous salmonids from systematic samples of fish passage. Using simulated tower counts of sockeye salmon Oncorhynchus nerka escapement on the Kvichak River, Alaska, five variance estimators for nonreplicated systematic samples were compared to determine the least biased. Using the least biased variance estimator, four confidence interval estimators were compared for expected coverage and mean interval width. Finally, five systematic sampling designs were compared to determine the design giving the smallest average variance estimate for total annual escapement. For nonreplicated systematic samples of fish escapement, all variance estimators were positively biased. Compared to the other estimators, the least biased estimator reduced bias by, on average, from 12% to 98%. All confidence intervals gave effectively identical results. Replicated systematic sampling designs consistently provided the smallest average estimated variance among those compared.

Uncovering racial bias in nursing fundamentals textbooks.

PubMed

Byrne, M M

2001-01-01

This article describes research that sought to identify and critique selected content areas from three nursing fundamentals textbooks for the presence or absence of racial bias embedded in the portrayal of African Americans. The analyzed content areas were the history of nursing, cultural content, and physical assessment/hygiene parameters. A researcher-developed guide was used for data collection and analysis of textual language, illustrations, linguistics, and references. A thematic analysis resulted in I I themes reflecting the portrayal of African Americans in these sampled textbooks. An interpretive analysis with a lens of Sadker and Sadker's categories of bias, along with other literary and theoretical contexts, were used to explore for the presence or absence of racial bias. Recommendations for nursing education are provided.

Photon detector configured to employ the Gunn effect and method of use

DOEpatents

Cich, Michael J

2015-03-17

Embodiments disclosed herein relate to photon detectors configured to employ the Gunn effect for detecting high-energy photons (e.g., x-rays and gamma rays) and methods of use. In an embodiment, a photon detector for detecting high-energy photons is disclosed. The photon detector includes a p-i-n semiconductor diode having a p-type semiconductor region, an n-type semiconductor region, and a compensated i-region disposed between the p-type semiconductor region and the n-type semiconductor region. The compensated i-region and has a width of about 100 .mu.m to about 400 .mu.m and is configured to exhibit the Gunn effect when the p-i-n semiconductor diode is forward biased a sufficient amount. The compensated i-region is doped to include a free carrier concentration of less than about 10.sup.10 cm.sup.-3.

Composite Partial Likelihood Estimation Under Length-Biased Sampling, With Application to a Prevalent Cohort Study of Dementia

PubMed Central

Huang, Chiung-Yu; Qin, Jing

2013-01-01

The Canadian Study of Health and Aging (CSHA) employed a prevalent cohort design to study survival after onset of dementia, where patients with dementia were sampled and the onset time of dementia was determined retrospectively. The prevalent cohort sampling scheme favors individuals who survive longer. Thus, the observed survival times are subject to length bias. In recent years, there has been a rising interest in developing estimation procedures for prevalent cohort survival data that not only account for length bias but also actually exploit the incidence distribution of the disease to improve efficiency. This article considers semiparametric estimation of the Cox model for the time from dementia onset to death under a stationarity assumption with respect to the disease incidence. Under the stationarity condition, the semiparametric maximum likelihood estimation is expected to be fully efficient yet difficult to perform for statistical practitioners, as the likelihood depends on the baseline hazard function in a complicated way. Moreover, the asymptotic properties of the semiparametric maximum likelihood estimator are not well-studied. Motivated by the composite likelihood method (Besag 1974), we develop a composite partial likelihood method that retains the simplicity of the popular partial likelihood estimator and can be easily performed using standard statistical software. When applied to the CSHA data, the proposed method estimates a significant difference in survival between the vascular dementia group and the possible Alzheimer’s disease group, while the partial likelihood method for left-truncated and right-censored data yields a greater standard error and a 95% confidence interval covering 0, thus highlighting the practical value of employing a more efficient methodology. To check the assumption of stable disease for the CSHA data, we also present new graphical and numerical tests in the article. The R code used to obtain the maximum composite partial

Bias correction in species distribution models: pooling survey and collection data for multiple species.

PubMed

Fithian, William; Elith, Jane; Hastie, Trevor; Keith, David A

2015-04-01

Presence-only records may provide data on the distributions of rare species, but commonly suffer from large, unknown biases due to their typically haphazard collection schemes. Presence-absence or count data collected in systematic, planned surveys are more reliable but typically less abundant.We proposed a probabilistic model to allow for joint analysis of presence-only and survey data to exploit their complementary strengths. Our method pools presence-only and presence-absence data for many species and maximizes a joint likelihood, simultaneously estimating and adjusting for the sampling bias affecting the presence-only data. By assuming that the sampling bias is the same for all species, we can borrow strength across species to efficiently estimate the bias and improve our inference from presence-only data.We evaluate our model's performance on data for 36 eucalypt species in south-eastern Australia. We find that presence-only records exhibit a strong sampling bias towards the coast and towards Sydney, the largest city. Our data-pooling technique substantially improves the out-of-sample predictive performance of our model when the amount of available presence-absence data for a given species is scarceIf we have only presence-only data and no presence-absence data for a given species, but both types of data for several other species that suffer from the same spatial sampling bias, then our method can obtain an unbiased estimate of the first species' geographic range.

Bias correction in species distribution models: pooling survey and collection data for multiple species

PubMed Central

Fithian, William; Elith, Jane; Hastie, Trevor; Keith, David A.

2016-01-01

Summary Presence-only records may provide data on the distributions of rare species, but commonly suffer from large, unknown biases due to their typically haphazard collection schemes. Presence–absence or count data collected in systematic, planned surveys are more reliable but typically less abundant.We proposed a probabilistic model to allow for joint analysis of presence-only and survey data to exploit their complementary strengths. Our method pools presence-only and presence–absence data for many species and maximizes a joint likelihood, simultaneously estimating and adjusting for the sampling bias affecting the presence-only data. By assuming that the sampling bias is the same for all species, we can borrow strength across species to efficiently estimate the bias and improve our inference from presence-only data.We evaluate our model’s performance on data for 36 eucalypt species in south-eastern Australia. We find that presence-only records exhibit a strong sampling bias towards the coast and towards Sydney, the largest city. Our data-pooling technique substantially improves the out-of-sample predictive performance of our model when the amount of available presence–absence data for a given species is scarceIf we have only presence-only data and no presence–absence data for a given species, but both types of data for several other species that suffer from the same spatial sampling bias, then our method can obtain an unbiased estimate of the first species’ geographic range. PMID:27840673

Scalable free energy calculation of proteins via multiscale essential sampling

NASA Astrophysics Data System (ADS)

Moritsugu, Kei; Terada, Tohru; Kidera, Akinori

2010-12-01

A multiscale simulation method, "multiscale essential sampling (MSES)," is proposed for calculating free energy surface of proteins in a sizable dimensional space with good scalability. In MSES, the configurational sampling of a full-dimensional model is enhanced by coupling with the accelerated dynamics of the essential degrees of freedom. Applying the Hamiltonian exchange method to MSES can remove the biasing potential from the coupling term, deriving the free energy surface of the essential degrees of freedom. The form of the coupling term ensures good scalability in the Hamiltonian exchange. As a test application, the free energy surface of the folding process of a miniprotein, chignolin, was calculated in the continuum solvent model. Results agreed with the free energy surface derived from the multicanonical simulation. Significantly improved scalability with the MSES method was clearly shown in the free energy calculation of chignolin in explicit solvent, which was achieved without increasing the number of replicas in the Hamiltonian exchange.

Configuration aerodynamics

NASA Technical Reports Server (NTRS)

Polhamus, E. C.; Gloss, B. B.

1981-01-01

Static aerodynamic research related to aircraft configurations in their cruise or combat modes is discussed. Subsonic transport aircraft, transonic tactical aircraft, and slender wing aircraft are considered. The status and plans of Langley's NTF configuration research program are reviewed. Recommendations for near term configuration research are made.

Rater Perceptions of Bias Using the Multiple Mini-Interview Format: A Qualitative Study

ERIC Educational Resources Information Center

Alweis, Richard L.; Fitzpatrick, Caroline; Donato, Anthony A.

2015-01-01

Introduction: The Multiple Mini-Interview (MMI) format appears to mitigate individual rater biases. However, the format itself may introduce structural systematic bias, favoring extroverted personality types. This study aimed to gain a better understanding of these biases from the perspective of the interviewer. Methods: A sample of MMI…

Sensitivity of Coupled Tropical Pacific Model Biases to Convective Parameterization in CESM1

NASA Astrophysics Data System (ADS)

Woelfle, M. D.; Yu, S.; Bretherton, C. S.; Pritchard, M. S.

2018-01-01

Six month coupled hindcasts show the central equatorial Pacific cold tongue bias development in a GCM to be sensitive to the atmospheric convective parameterization employed. Simulations using the standard configuration of the Community Earth System Model version 1 (CESM1) develop a cold bias in equatorial Pacific sea surface temperatures (SSTs) within the first two months of integration due to anomalous ocean advection driven by overly strong easterly surface wind stress along the equator. Disabling the deep convection parameterization enhances the zonal pressure gradient leading to stronger zonal wind stress and a stronger equatorial SST bias, highlighting the role of pressure gradients in determining the strength of the cold bias. Superparameterized hindcasts show reduced SST bias in the cold tongue region due to a reduction in surface easterlies despite simulating an excessively strong low-level jet at 1-1.5 km elevation. This reflects inadequate vertical mixing of zonal momentum from the absence of convective momentum transport in the superparameterized model. Standard CESM1simulations modified to omit shallow convective momentum transport reproduce the superparameterized low-level wind bias and associated equatorial SST pattern. Further superparameterized simulations using a three-dimensional cloud resolving model capable of producing realistic momentum transport simulate a cold tongue similar to the default CESM1. These findings imply convective momentum fluxes may be an underappreciated mechanism for controlling the strength of the equatorial cold tongue. Despite the sensitivity of equatorial SST to these changes in convective parameterization, the east Pacific double-Intertropical Convergence Zone rainfall bias persists in all simulations presented in this study.

Association between attention bias to threat and anxiety symptoms in children and adolescents.

PubMed

Abend, Rany; de Voogd, Leone; Salemink, Elske; Wiers, Reinout W; Pérez-Edgar, Koraly; Fitzgerald, Amanda; White, Lauren K; Salum, Giovanni A; He, Jie; Silverman, Wendy K; Pettit, Jeremy W; Pine, Daniel S; Bar-Haim, Yair

2018-03-01

Considerable research links threat-related attention biases to anxiety symptoms in adults, whereas extant findings on threat biases in youth are limited and mixed. Inconsistent findings may arise due to substantial methodological variability and limited sample sizes, emphasizing the need for systematic research on large samples. The aim of this report is to examine the association between threat bias and pediatric anxiety symptoms using standardized measures in a large, international, multi-site youth sample. A total of 1,291 children and adolescents from seven research sites worldwide completed standardized attention bias assessment task (dot-probe task) and child anxiety symptoms measure (Screen for Child Anxiety Related Emotional Disorders). Using a dimensional approach to symptomatology, we conducted regression analyses predicting overall, and disorder-specific, anxiety symptoms severity, based on threat bias scores. Threat bias correlated positively with overall anxiety symptoms severity (ß = 0.078, P = .004). Furthermore, threat bias was positively associated specifically with social anxiety (ß = 0.072, P = .008) and school phobia (ß = 0.076, P = .006) symptoms severity, but not with panic, generalized anxiety, or separation anxiety symptoms. These associations were not moderated by age or gender. These findings indicate associations between threat bias and pediatric anxiety symptoms, and suggest that vigilance to external threats manifests more prominently in symptoms of social anxiety and school phobia, regardless of age and gender. These findings point to the role of attention bias to threat in anxiety, with implications for translational clinical research. The significance of applying standardized methods in multi-site collaborations for overcoming challenges inherent to clinical research is discussed. © 2017 Wiley Periodicals, Inc.

Investigating the Stability of Four Methods for Estimating Item Bias.

ERIC Educational Resources Information Center

Perlman, Carole L.; And Others

The reliability of item bias estimates was studied for four methods: (1) the transformed delta method; (2) Shepard's modified delta method; (3) Rasch's one-parameter residual analysis; and (4) the Mantel-Haenszel procedure. Bias statistics were computed for each sample using all methods. Data were from administration of multiple-choice items from…

Evaluation of Bias-Variance Trade-Off for Commonly Used Post-Summarizing Normalization Procedures in Large-Scale Gene Expression Studies

PubMed Central

Qiu, Xing; Hu, Rui; Wu, Zhixin

2014-01-01

Normalization procedures are widely used in high-throughput genomic data analyses to remove various technological noise and variations. They are known to have profound impact to the subsequent gene differential expression analysis. Although there has been some research in evaluating different normalization procedures, few attempts have been made to systematically evaluate the gene detection performances of normalization procedures from the bias-variance trade-off point of view, especially with strong gene differentiation effects and large sample size. In this paper, we conduct a thorough study to evaluate the effects of normalization procedures combined with several commonly used statistical tests and MTPs under different configurations of effect size and sample size. We conduct theoretical evaluation based on a random effect model, as well as simulation and biological data analyses to verify the results. Based on our findings, we provide some practical guidance for selecting a suitable normalization procedure under different scenarios. PMID:24941114

Randomly biased investments and the evolution of public goods on interdependent networks

NASA Astrophysics Data System (ADS)

Chen, Wei; Wu, Te; Li, Zhiwu; Wang, Long

2017-08-01

Deciding how to allocate resources between interdependent systems is significant to optimize efficiency. We study the effects of heterogeneous contribution, induced by such interdependency, on the evolution of cooperation, through implementing the public goods games on two-layer networks. The corresponding players on different layers try to share a fixed amount of resources as the initial investment properly. The symmetry breaking of investments between players located on different layers is able to either prevent investments from, or extract them out of the deadlock. Results show that a moderate investment heterogeneity is best favorable for the evolution of cooperation, and random allocation of investment bias suppresses the cooperators at a wide range of the investment bias and the enhancement effect. Further studies on time evolution with different initial strategy configurations show that the non-interdependent cooperators along the interface of interdependent cooperators also are an indispensable factor in facilitating cooperative behavior. Our main results are qualitatively unchanged even diversifying investment bias that is subject to uniform distribution. Our study may shed light on the understanding of the origin of cooperative behavior on interdependent networks.

Large biases in regression-based constituent flux estimates: causes and diagnostic tools

USGS Publications Warehouse

Hirsch, Robert M.

2014-01-01

It has been documented in the literature that, in some cases, widely used regression-based models can produce severely biased estimates of long-term mean river fluxes of various constituents. These models, estimated using sample values of concentration, discharge, and date, are used to compute estimated fluxes for a multiyear period at a daily time step. This study compares results of the LOADEST seven-parameter model, LOADEST five-parameter model, and the Weighted Regressions on Time, Discharge, and Season (WRTDS) model using subsampling of six very large datasets to better understand this bias problem. This analysis considers sample datasets for dissolved nitrate and total phosphorus. The results show that LOADEST-7 and LOADEST-5, although they often produce very nearly unbiased results, can produce highly biased results. This study identifies three conditions that can give rise to these severe biases: (1) lack of fit of the log of concentration vs. log discharge relationship, (2) substantial differences in the shape of this relationship across seasons, and (3) severely heteroscedastic residuals. The WRTDS model is more resistant to the bias problem than the LOADEST models but is not immune to them. Understanding the causes of the bias problem is crucial to selecting an appropriate method for flux computations. Diagnostic tools for identifying the potential for bias problems are introduced, and strategies for resolving bias problems are described.

Sympathetic bias.

PubMed

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.

Are ecstasy users biased toward endorsing somatic mental health symptoms? Results from a general community sample.

PubMed

George, Amanda M; Windsor, Tim D; Rodgers, Bryan

2011-04-01

Whether the reported poorer mental health of ecstasy users is due to a bias in endorsement of somatic symptoms has been postulated, but rarely examined. The purpose of this study is to investigate whether levels of ecstasy use were associated with differential probabilities of endorsing somatic mental health symptoms. Current ecstasy users aged 24-30 years (n = 316) were identified from a population-based Australian study. Measures included frequency of ecstasy, meth/amphetamine, and cannabis use and the Goldberg anxiety/depression symptom scales. Multiple indicator, multiple cause models demonstrated no bias towards endorsing somatic symptoms with higher ecstasy use, both with and without adjustment for gender, cannabis, and meth/amphetamine use. Other studies using alternate measures of mental health should adopt this approach to determine if there is a bias in the endorsement of somatic symptoms among ecstasy users.

Modification of cognitive biases related to posttraumatic stress: A systematic review and research agenda.

PubMed

Woud, Marcella L; Verwoerd, Johan; Krans, Julie

2017-06-01

Cognitive models of Posttraumatic Stress Disorder (PTSD) postulate that cognitive biases in attention, interpretation, and memory represent key factors involved in the onset and maintenance of PTSD. Developments in experimental research demonstrate that it may be possible to manipulate such biases by means of Cognitive Bias Modification (CBM). In the present paper, we summarize studies assessing cognitive biases in posttraumatic stress to serve as a theoretical and methodological background. However, our main aim was to provide an overview of the scientific literature on CBM in (analogue) posttraumatic stress. Results of our systematic literature review showed that most CBM studies targeted attentional and interpretation biases (attention: five studies; interpretation: three studies), and one study modified memory biases. Overall, results showed that CBM can indeed modify cognitive biases and affect (analog) trauma symptoms in a training congruent manner. Interpretation bias procedures seemed effective in analog samples, and memory bias training proved preliminary success in a clinical PTSD sample. Studies of attention bias modification provided more mixed results. This heterogeneous picture may be explained by differences in the type of population or variations in the CBM procedure. Therefore, we sketched a detailed research agenda targeting the challenges for CBM in posttraumatic stress. Copyright © 2017 Elsevier Ltd. All rights reserved.

The lighter side of advertising: investigating posing and lighting biases.

PubMed

Thomas, Nicole A; Burkitt, Jennifer A; Patrick, Regan E; Elias, Lorin J

2008-11-01

People tend to display the left cheek when posing for a portrait; however, this effect does not appear to generalise to advertising. The amount of body visible in the image and the sex of the poser might also contribute to the posing bias. Portraits also exhibit lateral lighting biases, with most images being lit from the left. This effect might also be present in advertisements. A total of 2801 full-page advertisements were sampled and coded for posing direction, lighting direction, sex of model, and amount of body showing. Images of females showed an overall leftward posing bias, but the biases in males depended on the amount of body visible. Males demonstrated rightward posing biases for head-only images. Overall, images tended to be lit from the top left corner. The two factors of posing and lighting biases appear to influence one another. Leftward-lit images had more leftward poses than rightward, while the opposite occurred for rightward-lit images. Collectively, these results demonstrate that the posing biases in advertisements are dependent on the amount of body showing in the image, and that biases in lighting direction interact with these posing biases.

Assessing the potential for racial bias in hair analysis for cocaine: examining the relative risk of positive outcomes when comparing urine samples to hair samples.

PubMed

Mieczkowski, Tom

2011-03-20

This article examines the conjecture that hair analysis, performed to detect cocaine use or exposure, is biased against African Americans. It does so by comparing the outcomes of 33,928 hair and 105,792 urine samples collected from both African American and white subjects. In making this comparison the analysis seeks to determine if there is a departure in rates of positive and negative outcomes when comparing the results of hair analysis for cocaine to the results from urinalysis for cocaine by racial group. It treats urine as an unbiased test. It compares both the relative ratios of positive outcomes when comparing the two groups and it calculates the relative risk of outcomes for each group for having positive or negative outcomes. The findings show that the ratios of each racial group are effectively same for hair and urine assays, and they also show that the relative risk and risk estimates for positive and negative outcomes are the same for both racial groups. Considering all samples, the cocaine positive risk estimate for the hair samples comparing the two racial groups is 3.28 and for urinalysis the risk estimate is 3.10 (Breslow-Day χ(2) .250, 1 df, p = 0.617) a non-significant difference in risk. For pre-employment samples, the cocaine positive risk estimate for the hair samples comparing the two racial groups is 3.10 and for urinalysis the risk estimate is 2.90 (Breslow-Day χ(2) .281, df = 1, p = 0.595), also a non-significant difference in risk. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Cross-cultural measurement invariance of the General Health Questionnaire-12 in a German and a Colombian population sample.

PubMed

Romppel, Matthias; Hinz, Andreas; Finck, Carolyn; Young, Jeremy; Brähler, Elmar; Glaesmer, Heide

2017-12-01

While the General Health Questionnaire, 12-item version (GHQ-12) has been widely used in cross-cultural comparisons, rigorous tests of the measurement equivalence of different language versions are still lacking. Thus, our study aims at investigating configural, metric and scalar invariance across the German and the Spanish version of the GHQ-12 in two population samples. The GHQ-12 was applied in two large-scale population-based samples in Germany (N = 1,977) and Colombia (N = 1,500). To investigate measurement equivalence, confirmatory factor analyses were conducted in both samples. In the German sample mean GHQ-12 total scores were higher than in the Colombian sample. A one-factor model including response bias on the negatively worded items showed superior fit in the German and the Colombian sample; thus both versions of the GHQ-12 showed configural invariance. Factor loadings and intercepts were not equal across both samples; thus GHQ-12 showed no metric and scalar invariance. As both versions of the GHQ-12 did not show measurement equivalence, it is not recommendable to compare both measures and to conclude that mental distress is higher in the German sample, although we do not know if the differences are attributable to measurement problems or represent a real difference in mental distress. The study underlines the importance of measurement equivalence in cross-cultural comparisons. Copyright © 2017 John Wiley & Sons, Ltd.

GRADE guidelines: 5. Rating the quality of evidence--publication bias.

PubMed

Guyatt, Gordon H; Oxman, Andrew D; Montori, Victor; Vist, Gunn; Kunz, Regina; Brozek, Jan; Alonso-Coello, Pablo; Djulbegovic, Ben; Atkins, David; Falck-Ytter, Yngve; Williams, John W; Meerpohl, Joerg; Norris, Susan L; Akl, Elie A; Schünemann, Holger J

2011-12-01

In the GRADE approach, randomized trials start as high-quality evidence and observational studies as low-quality evidence, but both can be rated down if a body of evidence is associated with a high risk of publication bias. Even when individual studies included in best-evidence summaries have a low risk of bias, publication bias can result in substantial overestimates of effect. Authors should suspect publication bias when available evidence comes from a number of small studies, most of which have been commercially funded. A number of approaches based on examination of the pattern of data are available to help assess publication bias. The most popular of these is the funnel plot; all, however, have substantial limitations. Publication bias is likely frequent, and caution in the face of early results, particularly with small sample size and number of events, is warranted. Copyright © 2011 Elsevier Inc. All rights reserved.

Quantitative Characterization of Configurational Space Sampled by HIV-1 Nucleocapsid Using Solution NMR, X-ray Scattering and Protein Engineering.

PubMed

Deshmukh, Lalit; Schwieters, Charles D; Grishaev, Alexander; Clore, G Marius

2016-06-03

Nucleic-acid-related events in the HIV-1 replication cycle are mediated by nucleocapsid, a small protein comprising two zinc knuckles connected by a short flexible linker and flanked by disordered termini. Combining experimental NMR residual dipolar couplings, solution X-ray scattering and protein engineering with ensemble simulated annealing, we obtain a quantitative description of the configurational space sampled by the two zinc knuckles, the linker and disordered termini in the absence of nucleic acids. We first compute the conformational ensemble (with an optimal size of three members) of an engineered nucleocapsid construct lacking the N- and C-termini that satisfies the experimental restraints, and then validate this ensemble, as well as characterize the disordered termini, using the experimental data from the full-length nucleocapsid construct. The experimental and computational strategy is generally applicable to multidomain proteins. Differential flexibility within the linker results in asymmetric motion of the zinc knuckles which may explain their functionally distinct roles despite high sequence identity. One of the configurations (populated at a level of ≈40 %) closely resembles that observed in various ligand-bound forms, providing evidence for conformational selection and a mechanistic link between protein dynamics and function. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Trap configuration and spacing influences parameter estimates in spatial capture-recapture models

USGS Publications Warehouse

Sun, Catherine C.; Fuller, Angela K.; Royle, J. Andrew

2014-01-01

An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus) populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation). We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.

Stereotypical images and implicit weight bias in overweight/obese people

PubMed Central

Hinman, Nova G.; Burmeister, Jacob M.; Hoffmann, Debra A.; Ashrafioun, Lisham; Koball, Afton M.

2013-01-01

Purpose In this brief report, an unanswered question in implicit weight bias research is addressed: Is weight bias stronger when obese and thin people are pictured engaging in stereotype consistent behaviors (e.g., obese—watching TV/eating junk food; thin—exercising/eating healthy) as opposed to the converse? Methods Implicit Associations Test (IAT) data were collected from two samples of overweight/obese adults participating in weight loss treatment. Both samples completed two IATs. In one IAT, obese and thin people were pictured engaging in stereotype consistent behaviors (e.g., obese—watching TV/eating junk food; thin—exercising/eating healthy). In the second IAT, obese and thin people were pictured engaging in stereotype inconsistent behaviors (e.g., obese—exercising/eating healthy; thin—watching TV/eating junk food). Results Implicit weight bias was evident regardless of whether participants viewed stereotype consistent or inconsistent pictures. However, implicit bias was significantly stronger for stereotype consistent compared to stereotype inconsistent images. Conclusion Implicit anti-fat attitudes may be connected to the way in which people with obesity are portrayed. PMID:24057679

Enhancement of exchange bias in ferromagnetic/antiferromagnetic core-shell nanoparticles through ferromagnetic domain wall formation

NASA Astrophysics Data System (ADS)

Wu, Rui; Ding, Shilei; Lai, Youfang; Tian, Guang; Yang, Jinbo

2018-01-01

The spin configuration in the ferromagnetic part during the magnetization reversal plays a crucial role in the exchange bias effect. Through Monte Carlo simulation, the exchange bias effect in ferromagnetic-antiferromagnetic core-shell nanoparticles is investigated. Magnetization reversals in the ferromagnetic core were controlled between the coherent rotation and the domain wall motion by modulating the ferromagnetic domain wall width with parameters of uniaxial anisotropy constant and exchange coupling strength. An anomalous monotonic dependence of exchange bias on the uniaxial anisotropy constant is found in systems with small exchange coupling, showing an obvious violation of classic Meiklejohn-Bean model, while domain walls are found to form close to the interface and propagate in the ferromagnetic core with larger uniaxial anisotropy in both branches of the hysteresis. The asymmetric magnetization reversal with the formation of a spherical domain wall dramatically reduces the coercive field in the ascending branch, leading to the enhancement of the exchange bias. The results provide another degree of freedom to optimize the magnetic properties of magnetic nanoparticles for applications.

Directional bias of illusory stream caused by relative motion adaptation.

PubMed

Tomimatsu, Erika; Ito, Hiroyuki

2016-07-01

Enigma is an op-art painting that elicits an illusion of rotational streaming motion. In the present study, we tested whether adaptation to various motion configurations that included relative motion components could be reflected in the directional bias of the illusory stream. First, participants viewed the center of a rotating Enigma stimulus for adaptation. There was no physical motion on the ring area. During the adaptation period, the illusory stream on the ring was mainly seen in the direction opposite to that of the physical rotation. After the physical rotation stopped, the illusory stream on the ring was mainly seen in the same direction as that of the preceding physical rotation. Moreover, adapting to strong relative motion induced a strong bias in the illusory motion direction in the subsequently presented static Enigma stimulus. The results suggest that relative motion detectors corresponding to the ring area may produce the illusory stream of Enigma. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Correction of bias in belt transect studies of immotile objects

USGS Publications Warehouse

Anderson, D.R.; Pospahala, R.S.

1970-01-01

Unless a correction is made, population estimates derived from a sample of belt transects will be biased if a fraction of, the individuals on the sample transects are not counted. An approach, useful for correcting this bias when sampling immotile populations using transects of a fixed width, is presented. The method assumes that a searcher's ability to find objects near the center of the transect is nearly perfect. The method utilizes a mathematical equation, estimated from the data, to represent the searcher's inability to find all objects at increasing distances from the center of the transect. An example of the analysis of data, formation of the equation, and application is presented using waterfowl nesting data collected in Colorado.

The guidance of visual search by shape features and shape configurations.

PubMed

McCants, Cody W; Berggren, Nick; Eimer, Martin

2018-03-01

Representations of target features (attentional templates) guide attentional object selection during visual search. In many search tasks, targets objects are defined not by a single feature but by the spatial configuration of their component shapes. We used electrophysiological markers of attentional selection processes to determine whether the guidance of shape configuration search is entirely part-based or sensitive to the spatial relationship between shape features. Participants searched for targets defined by the spatial arrangement of two shape components (e.g., hourglass above circle). N2pc components were triggered not only by targets but also by partially matching distractors with one target shape (e.g., hourglass above hexagon) and by distractors that contained both target shapes in the reverse arrangement (e.g., circle above hourglass), in line with part-based attentional control. Target N2pc components were delayed when a reverse distractor was present on the opposite side of the same display, suggesting that early shape-specific attentional guidance processes could not distinguish between targets and reverse distractors. The control of attention then became sensitive to spatial configuration, which resulted in a stronger attentional bias for target objects relative to reverse and partially matching distractors. Results demonstrate that search for target objects defined by the spatial arrangement of their component shapes is initially controlled in a feature-based fashion but can later be guided by templates for spatial configurations. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Bias-induced conformational switching of supramolecular networks of trimesic acid at the solid-liquid interface

NASA Astrophysics Data System (ADS)

Ubink, J.; Enache, M.; Stöhr, M.

2018-05-01

Using the tip of a scanning tunneling microscope, an electric field-induced reversible phase transition between two planar porous structures ("chickenwire" and "flower") of trimesic acid was accomplished at the nonanoic acid/highly oriented pyrolytic graphite interface. The chickenwire structure was exclusively observed for negative sample bias, while for positive sample bias only the more densely packed flower structure was found. We suggest that the slightly negatively charged carboxyl groups of the trimesic acid molecule are the determining factor for this observation: their adsorption behavior varies with the sample bias and is thus responsible for the switching behavior.

Sampling free energy surfaces as slices by combining umbrella sampling and metadynamics.

PubMed

Awasthi, Shalini; Kapil, Venkat; Nair, Nisanth N

2016-06-15

Metadynamics (MTD) is a very powerful technique to sample high-dimensional free energy landscapes, and due to its self-guiding property, the method has been successful in studying complex reactions and conformational changes. MTD sampling is based on filling the free energy basins by biasing potentials and thus for cases with flat, broad, and unbound free energy wells, the computational time to sample them becomes very large. To alleviate this problem, we combine the standard Umbrella Sampling (US) technique with MTD to sample orthogonal collective variables (CVs) in a simultaneous way. Within this scheme, we construct the equilibrium distribution of CVs from biased distributions obtained from independent MTD simulations with umbrella potentials. Reweighting is carried out by a procedure that combines US reweighting and Tiwary-Parrinello MTD reweighting within the Weighted Histogram Analysis Method (WHAM). The approach is ideal for a controlled sampling of a CV in a MTD simulation, making it computationally efficient in sampling flat, broad, and unbound free energy surfaces. This technique also allows for a distributed sampling of a high-dimensional free energy surface, further increasing the computational efficiency in sampling. We demonstrate the application of this technique in sampling high-dimensional surface for various chemical reactions using ab initio and QM/MM hybrid molecular dynamics simulations. Further, to carry out MTD bias reweighting for computing forward reaction barriers in ab initio or QM/MM simulations, we propose a computationally affordable approach that does not require recrossing trajectories. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Estimates of External Validity Bias When Impact Evaluations Select Sites Nonrandomly

ERIC Educational Resources Information Center

Bell, Stephen H.; Olsen, Robert B.; Orr, Larry L.; Stuart, Elizabeth A.

2016-01-01

Evaluations of educational programs or interventions are typically conducted in nonrandomly selected samples of schools or districts. Recent research has shown that nonrandom site selection can yield biased impact estimates. To estimate the external validity bias from nonrandom site selection, we combine lists of school districts that were…

AMM15: a new high-resolution NEMO configuration for operational simulation of the European north-west shelf

NASA Astrophysics Data System (ADS)

Graham, Jennifer A.; O'Dea, Enda; Holt, Jason; Polton, Jeff; Hewitt, Helene T.; Furner, Rachel; Guihou, Karen; Brereton, Ashley; Arnold, Alex; Wakelin, Sarah; Castillo Sanchez, Juan Manuel; Mayorga Adame, C. Gabriela

2018-02-01

This paper describes the next-generation ocean forecast model for the European north-west shelf, which will become the basis of operational forecasts in 2018. This new system will provide a step change in resolution and therefore our ability to represent small-scale processes. The new model has a resolution of 1.5 km compared with a grid spacing of 7 km in the current operational system. AMM15 (Atlantic Margin Model, 1.5 km) is introduced as a new regional configuration of NEMO v3.6. Here we describe the technical details behind this configuration, with modifications appropriate for the new high-resolution domain. Results from a 30-year non-assimilative run using the AMM15 domain demonstrate the ability of this model to represent the mean state and variability of the region.

Overall, there is an improvement in the representation of the mean state across the region, suggesting similar improvements may be seen in the future operational system. However, the reduction in seasonal bias is greater off-shelf than on-shelf. In the North Sea, biases are largely unchanged. Since there has been no change to the vertical resolution or parameterization schemes, performance improvements are not expected in regions where stratification is dominated by vertical processes rather than advection. This highlights the fact that increased horizontal resolution will not lead to domain-wide improvements. Further work is needed to target bias reduction across the north-west shelf region.

Redundant Array Configurations for 21 cm Cosmology

NASA Astrophysics Data System (ADS)

Dillon, Joshua S.; Parsons, Aaron R.

2016-08-01

Realizing the potential of 21 cm tomography to statistically probe the intergalactic medium before and during the Epoch of Reionization requires large telescopes and precise control of systematics. Next-generation telescopes are now being designed and built to meet these challenges, drawing lessons from first-generation experiments that showed the benefits of densely packed, highly redundant arrays—in which the same mode on the sky is sampled by many antenna pairs—for achieving high sensitivity, precise calibration, and robust foreground mitigation. In this work, we focus on the Hydrogen Epoch of Reionization Array (HERA) as an interferometer with a dense, redundant core designed following these lessons to be optimized for 21 cm cosmology. We show how modestly supplementing or modifying a compact design like HERA’s can still deliver high sensitivity while enhancing strategies for calibration and foreground mitigation. In particular, we compare the imaging capability of several array configurations, both instantaneously (to address instrumental and ionospheric effects) and with rotation synthesis (for foreground removal). We also examine the effects that configuration has on calibratability using instantaneous redundancy. We find that improved imaging with sub-aperture sampling via “off-grid” antennas and increased angular resolution via far-flung “outrigger” antennas is possible with a redundantly calibratable array configuration.

REDUNDANT ARRAY CONFIGURATIONS FOR 21 cm COSMOLOGY

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

Dillon, Joshua S.; Parsons, Aaron R., E-mail: jsdillon@berkeley.edu

Realizing the potential of 21 cm tomography to statistically probe the intergalactic medium before and during the Epoch of Reionization requires large telescopes and precise control of systematics. Next-generation telescopes are now being designed and built to meet these challenges, drawing lessons from first-generation experiments that showed the benefits of densely packed, highly redundant arrays—in which the same mode on the sky is sampled by many antenna pairs—for achieving high sensitivity, precise calibration, and robust foreground mitigation. In this work, we focus on the Hydrogen Epoch of Reionization Array (HERA) as an interferometer with a dense, redundant core designed followingmore » these lessons to be optimized for 21 cm cosmology. We show how modestly supplementing or modifying a compact design like HERA’s can still deliver high sensitivity while enhancing strategies for calibration and foreground mitigation. In particular, we compare the imaging capability of several array configurations, both instantaneously (to address instrumental and ionospheric effects) and with rotation synthesis (for foreground removal). We also examine the effects that configuration has on calibratability using instantaneous redundancy. We find that improved imaging with sub-aperture sampling via “off-grid” antennas and increased angular resolution via far-flung “outrigger” antennas is possible with a redundantly calibratable array configuration.« less

Standardized mean differences cause funnel plot distortion in publication bias assessments.

PubMed

Zwetsloot, Peter-Paul; Van Der Naald, Mira; Sena, Emily S; Howells, David W; IntHout, Joanna; De Groot, Joris Ah; Chamuleau, Steven Aj; MacLeod, Malcolm R; Wever, Kimberley E

2017-09-08

Meta-analyses are increasingly used for synthesis of evidence from biomedical research, and often include an assessment of publication bias based on visual or analytical detection of asymmetry in funnel plots. We studied the influence of different normalisation approaches, sample size and intervention effects on funnel plot asymmetry, using empirical datasets and illustrative simulations. We found that funnel plots of the Standardized Mean Difference (SMD) plotted against the standard error (SE) are susceptible to distortion, leading to overestimation of the existence and extent of publication bias. Distortion was more severe when the primary studies had a small sample size and when an intervention effect was present. We show that using the Normalised Mean Difference measure as effect size (when possible), or plotting the SMD against a sample size-based precision estimate, are more reliable alternatives. We conclude that funnel plots using the SMD in combination with the SE are unsuitable for publication bias assessments and can lead to false-positive results.

Standardized mean differences cause funnel plot distortion in publication bias assessments

PubMed Central

Van Der Naald, Mira; Sena, Emily S; Howells, David W; IntHout, Joanna; De Groot, Joris AH; Chamuleau, Steven AJ; MacLeod, Malcolm R

2017-01-01

Meta-analyses are increasingly used for synthesis of evidence from biomedical research, and often include an assessment of publication bias based on visual or analytical detection of asymmetry in funnel plots. We studied the influence of different normalisation approaches, sample size and intervention effects on funnel plot asymmetry, using empirical datasets and illustrative simulations. We found that funnel plots of the Standardized Mean Difference (SMD) plotted against the standard error (SE) are susceptible to distortion, leading to overestimation of the existence and extent of publication bias. Distortion was more severe when the primary studies had a small sample size and when an intervention effect was present. We show that using the Normalised Mean Difference measure as effect size (when possible), or plotting the SMD against a sample size-based precision estimate, are more reliable alternatives. We conclude that funnel plots using the SMD in combination with the SE are unsuitable for publication bias assessments and can lead to false-positive results. PMID:28884685

Dynamically re-configurable CMOS imagers for an active vision system

NASA Technical Reports Server (NTRS)

Yang, Guang (Inventor); Pain, Bedabrata (Inventor)

2005-01-01

A vision system is disclosed. The system includes a pixel array, at least one multi-resolution window operation circuit, and a pixel averaging circuit. The pixel array has an array of pixels configured to receive light signals from an image having at least one tracking target. The multi-resolution window operation circuits are configured to process the image. Each of the multi-resolution window operation circuits processes each tracking target within a particular multi-resolution window. The pixel averaging circuit is configured to sample and average pixels within the particular multi-resolution window.

Estimation after classification using lot quality assurance sampling: corrections for curtailed sampling with application to evaluating polio vaccination campaigns.

PubMed

Olives, Casey; Valadez, Joseph J; Pagano, Marcello

2014-03-01

To assess the bias incurred when curtailment of Lot Quality Assurance Sampling (LQAS) is ignored, to present unbiased estimators, to consider the impact of cluster sampling by simulation and to apply our method to published polio immunization data from Nigeria. We present estimators of coverage when using two kinds of curtailed LQAS strategies: semicurtailed and curtailed. We study the proposed estimators with independent and clustered data using three field-tested LQAS designs for assessing polio vaccination coverage, with samples of size 60 and decision rules of 9, 21 and 33, and compare them to biased maximum likelihood estimators. Lastly, we present estimates of polio vaccination coverage from previously published data in 20 local government authorities (LGAs) from five Nigerian states. Simulations illustrate substantial bias if one ignores the curtailed sampling design. Proposed estimators show no bias. Clustering does not affect the bias of these estimators. Across simulations, standard errors show signs of inflation as clustering increases. Neither sampling strategy nor LQAS design influences estimates of polio vaccination coverage in 20 Nigerian LGAs. When coverage is low, semicurtailed LQAS strategies considerably reduces the sample size required to make a decision. Curtailed LQAS designs further reduce the sample size when coverage is high. Results presented dispel the misconception that curtailed LQAS data are unsuitable for estimation. These findings augment the utility of LQAS as a tool for monitoring vaccination efforts by demonstrating that unbiased estimation using curtailed designs is not only possible but these designs also reduce the sample size. © 2014 John Wiley & Sons Ltd.

Optimize of shrink process with X-Y CD bias on hole pattern

NASA Astrophysics Data System (ADS)

Koike, Kyohei; Hara, Arisa; Natori, Sakurako; Yamauchi, Shohei; Yamato, Masatoshi; Oyama, Kenichi; Yaegashi, Hidetami

2017-03-01

Gridded design rules[1] is major process in configuring logic circuit used 193-immersion lithography. In the scaling of grid patterning, we can make 10nm order line and space pattern by using multiple patterning techniques such as self-aligned multiple patterning (SAMP) and litho-etch- litho-etch (LELE)[2][3][4] . On the other hand, Line cut process has some error parameters such as pattern defect, placement error, roughness and X-Y CD bias with the decreasing scale. We tried to cure hole pattern roughness to use additional process such as Line smoothing[5] . Each smoothing process showed different effect. As the result, CDx shrink amount is smaller than CDy without one additional process. In this paper, we will report the pattern controllability comparison of EUV and 193-immersion. And we will discuss optimum method about CD bias on hole pattern.

Cognitive Deficits and Positively Biased Self-Perceptions in Children with ADHD

ERIC Educational Resources Information Center

McQuade, Julia D.; Tomb, Meghan; Hoza, Betsy; Waschbusch, Daniel A.; Hurt, Elizabeth A.; Vaughn, Aaron J.

2011-01-01

This study examined the relation between cognitive deficits and positive bias in a sample of 272 children with and without Attention Deficit Hyperactivity Disorder (ADHD; 7-12 years old). Results indicated that children with ADHD with and without biased self-perceptions exhibit differences in specific cognitive deficits (executive processes,…

The Effects of Sample Selection Bias on Racial Differences in Child Abuse Reporting.

ERIC Educational Resources Information Center

Ards, Sheila; Chung, Chanjin; Myers, Samuel L., Jr.

1998-01-01

Data from the National Incidence Study (NIS) of Child Abuse and Neglect suggest no racial difference in child maltreatment, although there are more black children within the child welfare population. This study found selection bias in the NIS design caused by the exclusion of family, friends, and neighbors that resulted in differences in NIS cases…

Respondent-Driven Sampling: An Assessment of Current Methodology.

PubMed

Gile, Krista J; Handcock, Mark S

2010-08-01

Respondent-Driven Sampling (RDS) employs a variant of a link-tracing network sampling strategy to collect data from hard-to-reach populations. By tracing the links in the underlying social network, the process exploits the social structure to expand the sample and reduce its dependence on the initial (convenience) sample.The current estimators of population averages make strong assumptions in order to treat the data as a probability sample. We evaluate three critical sensitivities of the estimators: to bias induced by the initial sample, to uncontrollable features of respondent behavior, and to the without-replacement structure of sampling.Our analysis indicates: (1) that the convenience sample of seeds can induce bias, and the number of sample waves typically used in RDS is likely insufficient for the type of nodal mixing required to obtain the reputed asymptotic unbiasedness; (2) that preferential referral behavior by respondents leads to bias; (3) that when a substantial fraction of the target population is sampled the current estimators can have substantial bias.This paper sounds a cautionary note for the users of RDS. While current RDS methodology is powerful and clever, the favorable statistical properties claimed for the current estimates are shown to be heavily dependent on often unrealistic assumptions. We recommend ways to improve the methodology.

Risk of bias reporting in the recent animal focal cerebral ischaemia literature.

PubMed

Bahor, Zsanett; Liao, Jing; Macleod, Malcolm R; Bannach-Brown, Alexandra; McCann, Sarah K; Wever, Kimberley E; Thomas, James; Ottavi, Thomas; Howells, David W; Rice, Andrew; Ananiadou, Sophia; Sena, Emily

2017-10-15

Findings from in vivo research may be less reliable where studies do not report measures to reduce risks of bias. The experimental stroke community has been at the forefront of implementing changes to improve reporting, but it is not known whether these efforts are associated with continuous improvements. Our aims here were firstly to validate an automated tool to assess risks of bias in published works, and secondly to assess the reporting of measures taken to reduce the risk of bias within recent literature for two experimental models of stroke. We developed and used text analytic approaches to automatically ascertain reporting of measures to reduce risk of bias from full-text articles describing animal experiments inducing middle cerebral artery occlusion (MCAO) or modelling lacunar stroke. Compared with previous assessments, there were improvements in the reporting of measures taken to reduce risks of bias in the MCAO literature but not in the lacunar stroke literature. Accuracy of automated annotation of risk of bias in the MCAO literature was 86% (randomization), 94% (blinding) and 100% (sample size calculation); and in the lacunar stroke literature accuracy was 67% (randomization), 91% (blinding) and 96% (sample size calculation). There remains substantial opportunity for improvement in the reporting of animal research modelling stroke, particularly in the lacunar stroke literature. Further, automated tools perform sufficiently well to identify whether studies report blinded assessment of outcome, but improvements are required in the tools to ascertain whether randomization and a sample size calculation were reported. © 2017 The Author(s).

Module Configuration

DOEpatents

Oweis, Salah; D'Ussel, Louis; Chagnon, Guy; Zuhowski, Michael; Sack, Tim; Laucournet, Gaullume; Jackson, Edward J.

2002-06-04

A stand alone battery module including: (a) a mechanical configuration; (b) a thermal management configuration; (c) an electrical connection configuration; and (d) an electronics configuration. Such a module is fully interchangeable in a battery pack assembly, mechanically, from the thermal management point of view, and electrically. With the same hardware, the module can accommodate different cell sizes and, therefore, can easily have different capacities. The module structure is designed to accommodate the electronics monitoring, protection, and printed wiring assembly boards (PWAs), as well as to allow airflow through the module. A plurality of modules may easily be connected together to form a battery pack. The parts of the module are designed to facilitate their manufacture and assembly.

Effects of interpretation training on hostile attribution bias and reactivity to interpersonal insult.

PubMed

Hawkins, Kirsten A; Cougle, Jesse R

2013-09-01

Research suggests that individuals high in anger have a bias for attributing hostile intentions to ambiguous situations. The current study tested whether this interpretation bias can be altered to influence anger reactivity to an interpersonal insult using a single-session cognitive bias modification program. One hundred thirty-five undergraduate students were randomized to receive positive training, negative training, or a control condition. Anger reactivity to insult was then assessed. Positive training led to significantly greater increases in positive interpretation bias relative to the negative group, though these increases were only marginally greater than the control group. Negative training led to increased negative interpretation bias relative to other groups. During the insult, participants in the positive condition reported less anger than those in the control condition. Observers rated participants in the positive condition as less irritated than those in the negative condition and more amused than the other two conditions. Though mediation of effects via bias modification was not demonstrated, among the positive condition posttraining interpretation bias was correlated with self-reported anger, suggesting that positive training reduced anger reactivity by influencing interpretation biases. Findings suggest that positive interpretation training may be a promising treatment for reducing anger. However, the current study was conducted with a non-treatment-seeking student sample; further research with a treatment-seeking sample with problematic anger is necessary. Copyright © 2013. Published by Elsevier Ltd.

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.

PubMed

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.

Cognitive bias in action: evidence for a reciprocal relation between confirmation bias and fear in children.

PubMed

Remmerswaal, Danielle; Huijding, Jorg; Bouwmeester, Samantha; Brouwer, Marlies; Muris, Peter

2014-03-01

Some cognitive models propose that information processing biases and fear are reciprocally related. This idea has never been formally tested. Therefore, this study investigated the existence of a vicious circle by which confirmation bias and fear exacerbate each other. One-hundred-and-seventy-one school children (8-13 years) were first provided with threatening, ambiguous, or positive information about an unknown animal. Then they completed a computerized information search task during which they could collect additional (negative, positive, or neutral) information about the novel animal. Because fear levels were repeatedly assessed during the task, it was possible to examine the reciprocal relationship between confirmation bias and fear. A reciprocal relation of mutual reinforcement was found between confirmation bias and fear over the course of the experiment: increases in fear predicted subsequent increases in the search for negative information, and increases in the search for negative information further enhanced fear on a later point-in-time. In addition, the initial information given about the animals successfully induced diverging fear levels in the children, and determined their first inclination to search for additional information. As this study employed a community sample of primary school children, future research should test whether these results can be generalized to clinically anxious youth. These findings provide first support for the notion that fearful individuals may become trapped in a vicious circle in which fear and a fear-related confirmation bias mutually strengthen each other, thereby maintaining the anxiety pathology. Copyright © 2013 Elsevier Ltd. All rights reserved.

A high performance field-reversed configuration

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

Binderbauer, M. W.; Tajima, T.; Steinhauer, L. C.

2015-05-15

Conventional field-reversed configurations (FRCs), high-beta, prolate compact toroids embedded in poloidal magnetic fields, face notable stability and confinement concerns. These can be ameliorated by various control techniques, such as introducing a significant fast ion population. Indeed, adding neutral beam injection into the FRC over the past half-decade has contributed to striking improvements in confinement and stability. Further, the addition of electrically biased plasma guns at the ends, magnetic end plugs, and advanced surface conditioning led to dramatic reductions in turbulence-driven losses and greatly improved stability. Together, these enabled the build-up of a well-confined and dominant fast-ion population. Under such conditions,more » highly reproducible, macroscopically stable hot FRCs (with total plasma temperature of ∼1 keV) with record lifetimes were achieved. These accomplishments point to the prospect of advanced, beam-driven FRCs as an intriguing path toward fusion reactors. This paper reviews key results and presents context for further interpretation.« less

How do geological sampling biases affect studies of morphological evolution in deep time? A case study of pterosaur (Reptilia: Archosauria) disparity.

PubMed

Butler, Richard J; Brusatte, Stephen L; Andres, Brian; Benson, Roger B J

2012-01-01

A fundamental contribution of paleobiology to macroevolutionary theory has been the illumination of deep time patterns of diversification. However, recent work has suggested that taxonomic diversity counts taken from the fossil record may be strongly biased by uneven spatiotemporal sampling. Although morphological diversity (disparity) is also frequently used to examine evolutionary radiations, no empirical work has yet addressed how disparity might be affected by uneven fossil record sampling. Here, we use pterosaurs (Mesozoic flying reptiles) as an exemplar group to address this problem. We calculate multiple disparity metrics based upon a comprehensive anatomical dataset including a novel phylogenetic correction for missing data, statistically compare these metrics to four geological sampling proxies, and use multiple regression modeling to assess the importance of uneven sampling and exceptional fossil deposits (Lagerstätten). We find that range-based disparity metrics are strongly affected by uneven fossil record sampling, and should therefore be interpreted cautiously. The robustness of variance-based metrics to sample size and geological sampling suggests that they can be more confidently interpreted as reflecting true biological signals. In addition, our results highlight the problem of high levels of missing data for disparity analyses, indicating a pressing need for more theoretical and empirical work. © 2011 The Author(s). Evolution © 2011 The Society for the Study of Evolution.

Maximum Likelihood Estimations and EM Algorithms with Length-biased Data

PubMed Central

Qin, Jing; Ning, Jing; Liu, Hao; Shen, Yu

2012-01-01

SUMMARY Length-biased sampling has been well recognized in economics, industrial reliability, etiology applications, epidemiological, genetic and cancer screening studies. Length-biased right-censored data have a unique data structure different from traditional survival data. The nonparametric and semiparametric estimations and inference methods for traditional survival data are not directly applicable for length-biased right-censored data. We propose new expectation-maximization algorithms for estimations based on full likelihoods involving infinite dimensional parameters under three settings for length-biased data: estimating nonparametric distribution function, estimating nonparametric hazard function under an increasing failure rate constraint, and jointly estimating baseline hazards function and the covariate coefficients under the Cox proportional hazards model. Extensive empirical simulation studies show that the maximum likelihood estimators perform well with moderate sample sizes and lead to more efficient estimators compared to the estimating equation approaches. The proposed estimates are also more robust to various right-censoring mechanisms. We prove the strong consistency properties of the estimators, and establish the asymptotic normality of the semi-parametric maximum likelihood estimators under the Cox model using modern empirical processes theory. We apply the proposed methods to a prevalent cohort medical study. Supplemental materials are available online. PMID:22323840

Associations among selective attention, memory bias, cognitive errors and symptoms of anxiety in youth.

PubMed

Watts, Sarah E; Weems, Carl F

2006-12-01

The purpose of this study was to examine the linkages among selective attention, memory bias, cognitive errors, and anxiety problems by testing a model of the interrelations among these cognitive variables and childhood anxiety disorder symptoms. A community sample of 81 youth (38 females and 43 males) aged 9-17 years and their parents completed measures of the child's anxiety disorder symptoms. Youth completed assessments measuring selective attention, memory bias, and cognitive errors. Results indicated that selective attention, memory bias, and cognitive errors were each correlated with childhood anxiety problems and provide support for a cognitive model of anxiety which posits that these three biases are associated with childhood anxiety problems. Only limited support for significant interrelations among selective attention, memory bias, and cognitive errors was found. Finally, results point towards an effective strategy for moving the assessment of selective attention to younger and community samples of youth.

Racial and Ethnic Bias in Test Construction. Final Report.

ERIC Educational Resources Information Center

Green, Donald Ross

To determine if tryout samples typically used for item selection contribute to test bias against minority groups, item analyses were made of the California Achievement Tests using seven subgroups of the standardization sample: Northern White Suburban, Northern Black Urban, Southern White Suburban, Southern Black Rural, Southern White Rural,…

An Optimized Configuration for the Brazilian Decimetric Array

NASA Astrophysics Data System (ADS)

Sawant, Hanumant; Faria, Claudio; Stephany, Stephan

The Brazilian Decimetric Array (BDA) is a radio interferometer designed to operate in the frequency range of 1.2-1.7, 2.8 and 5.6 GHz and to obtain images of radio sources with high dynamic range. A 5-antenna configuration is already operational being implemented in BDA phase I. Phase II will provide a 26-antenna configuration forming a compact T-array, whereas phase III will include further 12 antennas. However, the BDA site has topographic constraints that preclude the placement of these antennas along the lines defined by the 3 arms of the T-array. Therefore, some antennas must be displaced in a direction that is slightly transverse tothese lines. This work presents the investigation of possible optimized configurations for all 38 antennas spread over the distances of 2.5 x 1.25 km. It was required to determine the optimal position of the last 12 antennas.A new optimization strategy was then proposed in order to obtain the optimal array configuration. It is based on the entropy of the distribution of the sampled points in the Fourier plane. A stochastic model, Ant Colony Optimization, uses the entropy of the such distribution to iteratively refine the candidate solutions. The proposed strategy can be used to determine antenna locations for free-shape arrays in order to provide uniform u-v coverage with minimum redundancy of sampled points in u-v plane that are less susceptible to errors due to unmeasured Fourier components. A different distribution could be chosen for the coverage. It also allows to consider the topographical constraints of the available site. Furthermore, it provides an optimal configuration even considering the predetermined placement of the 26 antennas that compose the central T-array. In this case, the optimal location of the last 12 antennas was determined. Performance results corresponding to the Fourier plane coverage, synthesized beam and sidelobes levels are shown for this optimized BDA configuration and are compared to the results of

Bias properties of extragalactic distance indicators. 3: Analysis of Tully-Fisher distances for the Mathewson-Ford-Buchhorn sample of 1355 galaxies

NASA Technical Reports Server (NTRS)

Federspiel, Martin; Sandage, Allan; Tammann, G. A.

1994-01-01

The observational selection bias properties of the large Mathewson-Ford-Buchhorn (MFB) sample of axies are demonstrated by showing that the apparent Hubble constant incorrectly increases outward when determined using Tully-Fisher (TF) photometric distances that are uncorreted for bias. It is further shown that the value of H(sub 0) so determined is also multivlaued at a given redshift when it is calculated by the TF method using galaxies with differenct line widths. The method of removing this unphysical contradiction is developed following the model of the bias set out in Paper II. The model developed further here shows that the appropriate TF magnitude of a galaxy that is drawn from a flux-limited catalog not only is a function of line width but, even in the most idealistic cases, requires a triple-entry correction depending on line width, apparent magnitude, and catalog limit. Using the distance-limited subset of the data, it is shown that the mean intrinsic dispersion of a bias-free TF relation is high. The dispersion depends on line width, decreasing from sigma(M) = 0.7 mag for galaxies with rotational velocities less than 100 km s(exp-1) to sigma(M) = 0.4 mag for galaxies with rotational velocities greater than 250 km s(exp-1). These dispersions are so large that the random errors of the bias-free TF distances are too gross to detect any peculiar motions of individual galaxies, but taken together the data show again the offset of 500 km s(exp-1) fond both by Dressler & Faber and by MFB for galaxies in the direction of the putative Great Attractor but described now in a different way. The maximum amplitude of the bulk streaming motion at the Local Group is approximately 500 km s(exp-1) but the perturbation dies out, approaching the Machian frame defined by the CMB at a distance of approximately 80 Mpc (v is approximately 4000 km s(exp -1)). This decay to zero perturbation at v is approximately 4000 km s(exp -1) argues against existing models with a single

Bias and robustness of uncertainty components estimates in transient climate projections

NASA Astrophysics Data System (ADS)

Hingray, Benoit; Blanchet, Juliette; Jean-Philippe, Vidal

2016-04-01

A critical issue in climate change studies is the estimation of uncertainties in projections along with the contribution of the different uncertainty sources, including scenario uncertainty, the different components of model uncertainty and internal variability. Quantifying the different uncertainty sources faces actually different problems. For instance and for the sake of simplicity, an estimate of model uncertainty is classically obtained from the empirical variance of the climate responses obtained for the different modeling chains. These estimates are however biased. Another difficulty arises from the limited number of members that are classically available for most modeling chains. In this case, the climate response of one given chain and the effect of its internal variability may be actually difficult if not impossible to separate. The estimate of scenario uncertainty, model uncertainty and internal variability components are thus likely to be not really robust. We explore the importance of the bias and the robustness of the estimates for two classical Analysis of Variance (ANOVA) approaches: a Single Time approach (STANOVA), based on the only data available for the considered projection lead time and a time series based approach (QEANOVA), which assumes quasi-ergodicity of climate outputs over the whole available climate simulation period (Hingray and Saïd, 2014). We explore both issues for a simple but classical configuration where uncertainties in projections are composed of two single sources: model uncertainty and internal climate variability. The bias in model uncertainty estimates is explored from theoretical expressions of unbiased estimators developed for both ANOVA approaches. The robustness of uncertainty estimates is explored for multiple synthetic ensembles of time series projections generated with MonteCarlo simulations. For both ANOVA approaches, when the empirical variance of climate responses is used to estimate model uncertainty, the bias

Internal Standards: A Source of Analytical Bias For Volatile Organic Analyte Determinations

EPA Science Inventory

The use of internal standards in the determination of volatile organic compounds as described in SW-846 Method 8260C introduces a potential for bias in results once the internal standards (ISTDs) are added to a sample for analysis. The bias is relative to the dissimilarity betw...

Are attentional bias and memory bias for negative words causally related?

PubMed

Blaut, Agata; Paulewicz, Borysław; Szastok, Marta; Prochwicz, Katarzyna; Koster, Ernst

2013-09-01

In cognitive theories of depression, processing biases are assumed to be partly responsible for the onset and maintenance of mood disorders. Despite a wealth of studies examining the relation between depression and individual biases (at the level of attention, interpretation, and memory), little is known about relationships between different biases. The purpose of the present study was to assess if attentional bias is causally related to memory bias. 71 participants were randomly assigned to a control (n = 37) or attentional training group (n = 34). The attentional manipulation was followed by an explicit, intentional memory task during which novel neutral, negative, and positive words were presented. It was found that individuals with elevated depression score trained to orient away from negative words did not display a memory bias for negative words (adjectives) whereas similar individuals displayed this memory bias in the control condition. Generalization of the findings is limited because of the short study time frame and specific nature of the memory task. These results indicate that altering attentional bias can influence elaborative processing of emotional material and that this bias could be one of the causes of mood congruent memory in depression. Copyright © 2013 Elsevier Ltd. All rights reserved.

Smoothed Biasing Forces Yield Unbiased Free Energies with the Extended-System Adaptive Biasing Force Method

PubMed Central

2016-01-01

We report a theoretical description and numerical tests of the extended-system adaptive biasing force method (eABF), together with an unbiased estimator of the free energy surface from eABF dynamics. Whereas the original ABF approach uses its running estimate of the free energy gradient as the adaptive biasing force, eABF is built on the idea that the exact free energy gradient is not necessary for efficient exploration, and that it is still possible to recover the exact free energy separately with an appropriate estimator. eABF does not directly bias the collective coordinates of interest, but rather fictitious variables that are harmonically coupled to them; therefore is does not require second derivative estimates, making it easily applicable to a wider range of problems than ABF. Furthermore, the extended variables present a smoother, coarse-grain-like sampling problem on a mollified free energy surface, leading to faster exploration and convergence. We also introduce CZAR, a simple, unbiased free energy estimator from eABF trajectories. eABF/CZAR converges to the physical free energy surface faster than standard ABF for a wide range of parameters. PMID:27959559

Evaluation of bias and logistics in a survey of adults at increased risk for oral health decrements.

PubMed

Gilbert, G H; Duncan, R P; Kulley, A M; Coward, R T; Heft, M W

1997-01-01

Designing research to include sufficient respondents in groups at highest risk for oral health decrements can present unique challenges. Our purpose was to evaluate bias and logistics in this survey of adults at increased risk for oral health decrements. We used a telephone survey methodology that employed both listed numbers and random digit dialing to identify dentate persons 45 years old or older and to oversample blacks, poor persons, and residents of nonmetropolitan counties. At a second stage, a subsample of the respondents to the initial telephone screening was selected for further study, which consisted of a baseline in-person interview and a clinical examination. We assessed bias due to: (1) limiting the sample to households with telephones, (2) using predominantly listed numbers instead of random digit dialing, and (3) nonresponse at two stages of data collection. While this approach apparently created some biases in the sample, they were small in magnitude. Specifically, limiting the sample to households with telephones biased the sample overall toward more females, larger households, and fewer functionally impaired persons. Using predominantly listed numbers led to a modest bias toward selection of persons more likely to be younger, healthier, female, have had a recent dental visit, and reside in smaller households. Blacks who were selected randomly at a second stage were more likely to participate in baseline data gathering than their white counterparts. Comparisons of the data obtained in this survey with those from recent national surveys suggest that this methodology for sampling high-risk groups did not substantively bias the sample with respect to two important dental parameters, prevalence of edentulousness and dental care use, nor were conclusions about multivariate associations with dental care recency substantively affected. This method of sampling persons at high risk for oral health decrements resulted in only modest bias with respect to the

Use of Bayes theorem to correct size-specific sampling bias in growth data.

PubMed

Troynikov, V S

1999-03-01

The bayesian decomposition of posterior distribution was used to develop a likelihood function to correct bias in the estimates of population parameters from data collected randomly with size-specific selectivity. Positive distributions with time as a parameter were used for parametrization of growth data. Numerical illustrations are provided. The alternative applications of the likelihood to estimate selectivity parameters are discussed.

Evaluating outcome-correlated recruitment and geographic recruitment bias in a respondent-driven sample of people who inject drugs in Tijuana, Mexico.

PubMed

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.

Running Performance, VO2max, and Running Economy: The Widespread Issue of Endogenous Selection Bias.

PubMed

Borgen, Nicolai T

2018-05-01

Studies in sport and exercise medicine routinely use samples of highly trained individuals in order to understand what characterizes elite endurance performance, such as running economy and maximal oxygen uptake VO 2max . However, it is not well understood in the literature that using such samples most certainly leads to biased findings and accordingly potentially erroneous conclusions because of endogenous selection bias. In this paper, I review the current literature on running economy and VO 2max , and discuss the literature in light of endogenous selection bias. I demonstrate that the results in a large part of the literature may be misleading, and provide some practical suggestions as to how future studies may alleviate endogenous selection bias.

Hindsight Bias.

PubMed

Roese, Neal J; Vohs, Kathleen D

2012-09-01

Hindsight bias occurs when people feel that they "knew it all along," that is, when they believe that an event is more predictable after it becomes known than it was before it became known. Hindsight bias embodies any combination of three aspects: memory distortion, beliefs about events' objective likelihoods, or subjective beliefs about one's own prediction abilities. Hindsight bias stems from (a) cognitive inputs (people selectively recall information consistent with what they now know to be true and engage in sensemaking to impose meaning on their own knowledge), (b) metacognitive inputs (the ease with which a past outcome is understood may be misattributed to its assumed prior likelihood), and (c) motivational inputs (people have a need to see the world as orderly and predictable and to avoid being blamed for problems). Consequences of hindsight bias include myopic attention to a single causal understanding of the past (to the neglect of other reasonable explanations) as well as general overconfidence in the certainty of one's judgments. New technologies for visualizing and understanding data sets may have the unintended consequence of heightening hindsight bias, but an intervention that encourages people to consider alternative causal explanations for a given outcome can reduce hindsight bias. © The Author(s) 2012.

Shape measurement biases from underfitting and ellipticity gradients

DOE PAGES

Bernstein, Gary M.

2010-08-21

With this study, precision weak gravitational lensing experiments require measurements of galaxy shapes accurate to <1 part in 1000. We investigate measurement biases, noted by Voigt and Bridle (2009) and Melchior et al. (2009), that are common to shape measurement methodologies that rely upon fitting elliptical-isophote galaxy models to observed data. The first bias arises when the true galaxy shapes do not match the models being fit. We show that this "underfitting bias" is due, at root, to these methods' attempts to use information at high spatial frequencies that has been destroyed by the convolution with the point-spread function (PSF)more » and/or by sampling. We propose a new shape-measurement technique that is explicitly confined to observable regions of k-space. A second bias arises for galaxies whose ellipticity varies with radius. For most shape-measurement methods, such galaxies are subject to "ellipticity gradient bias". We show how to reduce such biases by factors of 20–100 within the new shape-measurement method. The resulting shear estimator has multiplicative errors < 1 part in 10 3 for high-S/N images, even for highly asymmetric galaxies. Without any training or recalibration, the new method obtains Q = 3000 in the GREAT08 Challenge of blind shear reconstruction on low-noise galaxies, several times better than any previous method.« less

Nature's engineering: Giant magnetic exchange bias > 1T in a natural mineral

NASA Astrophysics Data System (ADS)

McEnroe, S. A.; Carter-Stiglitz, B.; Harrison, R. J.; Robinson, P.; McCammon, C.

2006-12-01

Magnetic exchange bias is a phenomenon whereby the hysteresis loop of a "soft" magnetic phase is shifted along the applied field axis by an amount of exchange due to interaction with a "hard" magnetic phase. Exchange bias is the subject of intense experimental and theoretical investigation because of its widespread technological applications and recent advances in manipulating nanoscale materials. Understanding the physical origin of exchange bias has been hampered, by the general uncertainty in the crystal and magnetic structure of the interface between hard and soft phases. Here we discuss a natural sample that has one of the largest exchange biases ever reported, nearly 1 Tesla (T) in a 1.5 T field and is the first documented example of exchange bias of this magnitude in a natural mineral. We demonstrate that exchange bias in this system is due to the interaction between coherently intergrown magnetic phases, formed through a natural process of phase separation during slow cooling. These extreme properties are found in a sample of titanohematite (15- 19 percent Ti-substitution ) from the 1 Gyr metamorphic rocks of the Modum district, south Norway. Low temperature magnetic measurements demonstrate the nature of the giant exchange bias. Transmission electron microscopy, electron microprobe analyses combined with Mossbauer measurements, at room and low temperature, are used to identify the interacting phases. The titanohematite contain ilmenite lamellae which are mostly sub-unit cell size. Fe-rutile is also present as an intergrowth phase.

Performance Improvement of a Magnetized Coaxial Plasma Gun by adopting Iron-core Bias Coil and New Pre-Ionization System

NASA Astrophysics Data System (ADS)

Edo, Takahiro; Asai, T.; Tanaka, F.; Yamada, S.; Hosozawa, A.; Gota, H.; Roche, T.; Allfrey, I.; Matsumoto, T.

2017-10-01

A magnetized coaxial plasma gun (MCPG) is a device used to generate a compact toroid (CT), which has a spheromak-like configuration. A typical MCPG consists of a set of axisymmetric cylindrical electrodes, bias coil, and gas-puff valves. In order to expand the CT operating range, the distributions of the bias magnetic field and neutral gas have been investigated. We have developed a new means of generating stuffing flux. By inserting an iron core into the bias coil, the magnetic field increases dramatically; even a small current of a few Amps produces a sufficient bias field. According to a simulation result, it was also suggested that the radial distribution of the bias field is easily controlled. The ejected CT and the target FRC are cooled by excess neutral gas that typical MCPGs require to initiate a breakdown; therefore, we have adopted a miniature gun as a new pre-ionization (PI) system. By introducing this PI system, the breakdown occurs at lower neutral gas density so that the amount of excess neutral gas can be reduced.

Exchange bias mediated by interfacial nanoparticles (invited)

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

Berkowitz, A. E., E-mail: aberk@ucsd.edu; Center for Magnetic Recording Research, University of California, California 92093; Sinha, S. K.

2015-05-07

The objective of this study on the iconic exchange-bias bilayer Permalloy/CoO has been to identify those elements of the interfacial microstructure and accompanying magnetic properties that are responsible for the exchange-bias and hysteretic properties of this bilayer. Both epitaxial and polycrystalline samples were examined. X-ray and neutron reflectometry established that there existed an interfacial region, of width ∼1 nm, whose magnetic properties differed from those of Py or CoO. A model was developed for the interfacial microstructure that predicts all the relevant properties of this system; namely; the temperature and Permalloy thickness dependence of the exchange-bias, H{sub EX}, and coercivity, H{submore » C}; the much smaller measured values of H{sub EX} from what was nominally expected; the different behavior of H{sub EX} and H{sub C} in epitaxial and polycrystalline bilayers. A surprising result is that the exchange-bias does not involve direct exchange-coupling between Permalloy and CoO, but rather is mediated by CoFe{sub 2}O{sub 4} nanoparticles in the interfacial region.« less

Positive exchange-bias and giant vertical hysteretic shift in La0.3Sr0.7FeO3/SrRuO3 bilayers

PubMed Central

Rana, Rakesh; Pandey, Parul; Singh, R. P.; Rana, D. S.

2014-01-01

The exchange-bias effects in the mosaic epitaxial bilayers of the itinerant ferromagnet (FM) SrRuO3 and the antiferromagnetic (AFM) charge-ordered La0.3Sr0.7FeO3 were investigated. An uncharacteristic low-field positive exchange bias, a cooling-field driven reversal of positive to negative exchange-bias and a layer thickness optimised unusual vertical magnetization shift were all novel facets of exchange bias realized for the first time in magnetic oxides. The successive magnetic training induces a transition from positive to negative exchange bias regime with changes in domain configurations. These observations are well corroborated by the hysteretic loop asymmetries which display the modifications in the AFM spin correlations. These exotic features emphasize the key role of i) mosaic disorder induced subtle interplay of competing AFM-superexchange and FM double exchange at the exchange biased interface and, ii) training induced irrecoverable alterations in the AFM spin structure. PMID:24569516

Linear and non-linear bias: predictions versus measurements

NASA Astrophysics Data System (ADS)

Hoffmann, K.; Bel, J.; Gaztañaga, E.

2017-02-01

We study the linear and non-linear bias parameters which determine the mapping between the distributions of galaxies and the full matter density fields, comparing different measurements and predictions. Associating galaxies with dark matter haloes in the Marenostrum Institut de Ciències de l'Espai (MICE) Grand Challenge N-body simulation, we directly measure the bias parameters by comparing the smoothed density fluctuations of haloes and matter in the same region at different positions as a function of smoothing scale. Alternatively, we measure the bias parameters by matching the probability distributions of halo and matter density fluctuations, which can be applied to observations. These direct bias measurements are compared to corresponding measurements from two-point and different third-order correlations, as well as predictions from the peak-background model, which we presented in previous papers using the same data. We find an overall variation of the linear bias measurements and predictions of ˜5 per cent with respect to results from two-point correlations for different halo samples with masses between ˜1012and1015 h-1 M⊙ at the redshifts z = 0.0 and 0.5. Variations between the second- and third-order bias parameters from the different methods show larger variations, but with consistent trends in mass and redshift. The various bias measurements reveal a tight relation between the linear and the quadratic bias parameters, which is consistent with results from the literature based on simulations with different cosmologies. Such a universal relation might improve constraints on cosmological models, derived from second-order clustering statistics at small scales or higher order clustering statistics.

Configurations of Common Childhood Psychosocial Risk Factors

ERIC Educational Resources Information Center

Copeland, William; Shanahan, Lilly; Costello, E. Jane; Angold, Adrian

2009-01-01

Background: Co-occurrence of psychosocial risk factors is commonplace, but little is known about psychiatrically-predictive configurations of psychosocial risk factors. Methods: Latent class analysis (LCA) was applied to 17 putative psychosocial risk factors in a representative population sample of 920 children ages 9 to 17. The resultant class…

An experimental investigation of recruitment bias in eating pathology research.

PubMed

Moss, Erin L; von Ranson, Kristin M

2006-04-01

Previous, uncontrolled research has suggested a bias may exist in recruiting participants for eating disorder research. Recruitment biases may affect sample representativeness and generalizability of findings. This experiment investigated whether revealing that a study's topic was related to eating disorders created a self-selection bias. Young women at a university responded to advertisements containing contrasting information about the nature of a single study. We recruited one group by advertising the study under the title "Disordered Eating in Young Women" (n = 251) and another group using the title "Consumer Preferences" (n = 259). Results indicated similar levels of eating pathology in both groups, so the different recruitment techniques did not engender self-selection. However, the consumer preferences group scored higher in self-reported social desirability. The level of information conveyed in study advertising does not impact reporting of eating disturbances among nonclinical samples, although there is evidence social desirability might. 2006 by Wiley Periodicals, Inc.

Commercial influence and learner-perceived bias in continuing medical education.

PubMed

Steinman, Michael A; Boscardin, Christy K; Aguayo, Leslie; Baron, Robert B

2010-01-01

To directly examine the relationship between commercial support of continuing medical education (CME) and perceived bias in the content of these activities. Cross-sectional study of 213 accredited live educational programs organized by a university provider of CME from 2005 to 2007. A standard question from course evaluations was used to determine the degree to which attendees believed commercial bias was present. Binomial regression models were used to determine the association between course features that may introduce commercial bias and the extent of perceived bias at those CME activities. Mean response rate for attendee evaluations was 56% (SD 15%). Commercial support covered 20%-49% of costs for 45 (21%) educational activities, and > or = 50% of costs for 46 activities (22%). Few course participants perceived commercial bias, with a median of 97% (interquartile range 95%-99%) of respondents stating that the activity they attended was free of commercial bias. There was no association between extent of commercial support and the degree of perceived bias in CME activities. Similarly, perceived bias did not vary for 11 of 12 event characteristics evaluated as potential sources of commercial bias, or by score on a risk index designed to prospectively assess risk of commercial bias. Rates of perceived bias were low for the vast majority of CME activities in the sample and did not differ by the degree of industry support or other event characteristics. Further study is needed to determine whether commercial influence persisted in more subtle forms that were difficult for participants to detect.

Eye Movements while Reading Biased Homographs: Effects of Prior Encounter and Biasing Context on Reducing the Subordinate Bias Effect

PubMed Central

Leinenger, Mallorie; Rayner, Keith

2013-01-01

Readers experience processing difficulties when reading biased homographs preceded by subordinate-biasing contexts. Attempts to overcome this processing deficit have often failed to reduce the subordinate bias effect (SBE). In the present studies, we examined the processing of biased homographs preceded by single-sentence, subordinate-biasing contexts, and varied whether this preceding context contained a prior instance of the homograph or a control word/phrase. Having previously encountered the homograph earlier in the sentence reduced the SBE for the subsequent encounter, while simply instantiating the subordinate meaning produced processing difficulty. We compared these reductions in reading times to differences in processing time between dominant-biased repeated and non-repeated conditions in order to verify that the reductions observed in the subordinate cases did not simply reflect a general repetition benefit. Our results indicate that a strong, subordinate-biasing context can interact during lexical access to overcome the activation from meaning frequency and reduce the SBE during reading. PMID:24073328

Driven Metadynamics: Reconstructing Equilibrium Free Energies from Driven Adaptive-Bias Simulations

PubMed Central

2013-01-01

We present a novel free-energy calculation method that constructively integrates two distinct classes of nonequilibrium sampling techniques, namely, driven (e.g., steered molecular dynamics) and adaptive-bias (e.g., metadynamics) methods. By employing nonequilibrium work relations, we design a biasing protocol with an explicitly time- and history-dependent bias that uses on-the-fly work measurements to gradually flatten the free-energy surface. The asymptotic convergence of the method is discussed, and several relations are derived for free-energy reconstruction and error estimation. Isomerization reaction of an atomistic polyproline peptide model is used to numerically illustrate the superior efficiency and faster convergence of the method compared with its adaptive-bias and driven components in isolation. PMID:23795244

Eliminating Bias

EPA Pesticide Factsheets

Learn how to eliminate bias from monitoring systems by instituting appropriate installation, operation, and quality assurance procedures. Provides links to download An Operator's Guide to Eliminating Bias in CEM Systems.

Set-theoretic estimation of hybrid system configurations.

PubMed

Benazera, Emmanuel; Travé-Massuyès, Louise

2009-10-01

Hybrid systems serve as a powerful modeling paradigm for representing complex continuous controlled systems that exhibit discrete switches in their dynamics. The system and the models of the system are nondeterministic due to operation in uncertain environment. Bayesian belief update approaches to stochastic hybrid system state estimation face a blow up in the number of state estimates. Therefore, most popular techniques try to maintain an approximation of the true belief state by either sampling or maintaining a limited number of trajectories. These limitations can be avoided by using bounded intervals to represent the state uncertainty. This alternative leads to splitting the continuous state space into a finite set of possibly overlapping geometrical regions that together with the system modes form configurations of the hybrid system. As a consequence, the true system state can be captured by a finite number of hybrid configurations. A set of dedicated algorithms that can efficiently compute these configurations is detailed. Results are presented on two systems of the hybrid system literature.

Managing Bias in Palliative Care: Professional Hazards in Goals of Care Discussions at the End of Life.

PubMed

Callaghan, Katharine A; Fanning, Joseph B

2018-02-01

In the setting of end-of-life care, biases can interfere with patient articulation of goals and hinder provision of patient-centered care. No studies have addressed clinician bias or bias management specific to goals of care discussions at the end of life. To identify and determine the prevalence of palliative care clinician biases and bias management strategies in end-of-life goals of care discussions. A semistructured interview guide with relevant domains was developed to facilitate data collection. Participants were asked directly to identify biases and bias management strategies applicable to this setting. Two researchers developed a codebook to identify themes using a 25% transcript sample through an iterative process based on grounded theory. Inter-rater reliability was evaluated using Cohen κ. It was 0.83, indicating near perfect agreement between coders. The data approach saturation. A purposive sampling of 20 palliative care clinicians in Middle Tennessee participated in interviews. The 20 clinicians interviewed identified 16 biases and 11 bias management strategies. The most frequently mentioned bias was a bias against aggressive treatment (n = 9), described as a clinician's assumption that most interventions at the end of life are not beneficial. The most frequently mentioned bias management strategy was self-recognition of bias (n = 17), described as acknowledging that bias is present. This is the first study identifying palliative care clinicians' biases and bias management strategies in end-of-life goals of care discussions.

Operational Dynamic Configuration Analysis

NASA Technical Reports Server (NTRS)

Lai, Chok Fung; Zelinski, Shannon

2010-01-01

Sectors may combine or split within areas of specialization in response to changing traffic patterns. This method of managing capacity and controller workload could be made more flexible by dynamically modifying sector boundaries. Much work has been done on methods for dynamically creating new sector boundaries [1-5]. Many assessments of dynamic configuration methods assume the current day baseline configuration remains fixed [6-7]. A challenging question is how to select a dynamic configuration baseline to assess potential benefits of proposed dynamic configuration concepts. Bloem used operational sector reconfigurations as a baseline [8]. The main difficulty is that operational reconfiguration data is noisy. Reconfigurations often occur frequently to accommodate staff training or breaks, or to complete a more complicated reconfiguration through a rapid sequence of simpler reconfigurations. Gupta quantified a few aspects of airspace boundary changes from this data [9]. Most of these metrics are unique to sector combining operations and not applicable to more flexible dynamic configuration concepts. To better understand what sort of reconfigurations are acceptable or beneficial, more configuration change metrics should be developed and their distribution in current practice should be computed. This paper proposes a method to select a simple sequence of configurations among operational configurations to serve as a dynamic configuration baseline for future dynamic configuration concept assessments. New configuration change metrics are applied to the operational data to establish current day thresholds for these metrics. These thresholds are then corroborated, refined, or dismissed based on airspace practitioner feedback. The dynamic configuration baseline selection method uses a k-means clustering algorithm to select the sequence of configurations and trigger times from a given day of operational sector combination data. The clustering algorithm selects a simplified

Biases in affective forecasting and recall in individuals with depression and anxiety symptoms.

PubMed

Wenze, Susan J; Gunthert, Kathleen C; German, Ramaris E

2012-07-01

The authors used experience sampling to investigate biases in affective forecasting and recall in individuals with varying levels of depression and anxiety symptoms. Participants who were higher in depression symptoms demonstrated stronger (more pessimistic) negative mood prediction biases, marginally stronger negative mood recall biases, and weaker (less optimistic) positive mood prediction and recall biases. Participants who were higher in anxiety symptoms demonstrated stronger negative mood prediction biases, but positive mood prediction biases that were on par with those who were lower in anxiety. Anxiety symptoms were not associated with mood recall biases. Neither depression symptoms nor anxiety symptoms were associated with bias in event prediction. Their findings fit well with the tripartite model of depression and anxiety. Results are also consistent with the conceptualization of anxiety as a "forward-looking" disorder, and with theories that emphasize the importance of pessimism and general negative information processing in depressive functioning.

Bias correction of satellite-based rainfall data

NASA Astrophysics Data System (ADS)

Bhattacharya, Biswa; Solomatine, Dimitri

2015-04-01

Limitation in hydro-meteorological data availability in many catchments limits the possibility of reliable hydrological analyses especially for near-real-time predictions. However, the variety of satellite based and meteorological model products for rainfall provides new opportunities. Often times the accuracy of these rainfall products, when compared to rain gauge measurements, is not impressive. The systematic differences of these rainfall products from gauge observations can be partially compensated by adopting a bias (error) correction. Many of such methods correct the satellite based rainfall data by comparing their mean value to the mean value of rain gauge data. Refined approaches may also first find out a suitable time scale at which different data products are better comparable and then employ a bias correction at that time scale. More elegant methods use quantile-to-quantile bias correction, which however, assumes that the available (often limited) sample size can be useful in comparing probabilities of different rainfall products. Analysis of rainfall data and understanding of the process of its generation reveals that the bias in different rainfall data varies in space and time. The time aspect is sometimes taken into account by considering the seasonality. In this research we have adopted a bias correction approach that takes into account the variation of rainfall in space and time. A clustering based approach is employed in which every new data point (e.g. of Tropical Rainfall Measuring Mission (TRMM)) is first assigned to a specific cluster of that data product and then, by identifying the corresponding cluster of gauge data, the bias correction specific to that cluster is adopted. The presented approach considers the space-time variation of rainfall and as a result the corrected data is more realistic. Keywords: bias correction, rainfall, TRMM, satellite rainfall

Enhanced Conformational Sampling in Molecular Dynamics Simulations of Solvated Peptides: Fragment-Based Local Elevation Umbrella Sampling.

PubMed

Hansen, Halvor S; Daura, Xavier; Hünenberger, Philippe H

2010-09-14

A new method, fragment-based local elevation umbrella sampling (FB-LEUS), is proposed to enhance the conformational sampling in explicit-solvent molecular dynamics (MD) simulations of solvated polymers. The method is derived from the local elevation umbrella sampling (LEUS) method [ Hansen and Hünenberger , J. Comput. Chem. 2010 , 31 , 1 - 23 ], which combines the local elevation (LE) conformational searching and the umbrella sampling (US) conformational sampling approaches into a single scheme. In LEUS, an initial (relatively short) LE build-up (searching) phase is used to construct an optimized (grid-based) biasing potential within a subspace of conformationally relevant degrees of freedom, which is then frozen and used in a (comparatively longer) US sampling phase. This combination dramatically enhances the sampling power of MD simulations but, due to computational and memory costs, is only applicable to relevant subspaces of low dimensionalities. As an attempt to expand the scope of the LEUS approach to solvated polymers with more than a few relevant degrees of freedom, the FB-LEUS scheme involves an US sampling phase that relies on a superposition of low-dimensionality biasing potentials optimized using LEUS at the fragment level. The feasibility of this approach is tested using polyalanine (poly-Ala) and polyvaline (poly-Val) oligopeptides. Two-dimensional biasing potentials are preoptimized at the monopeptide level, and subsequently applied to all dihedral-angle pairs within oligopeptides of 4,  6,  8, or 10 residues. Two types of fragment-based biasing potentials are distinguished: (i) the basin-filling (BF) potentials act so as to "fill" free-energy basins up to a prescribed free-energy level above the global minimum; (ii) the valley-digging (VD) potentials act so as to "dig" valleys between the (four) free-energy minima of the two-dimensional maps, preserving barriers (relative to linearly interpolated free-energy changes) of a prescribed magnitude

Overview of C-2W Field-Reversed Configuration Experimental Program

NASA Astrophysics Data System (ADS)

Gota, H.; Binderbauer, M. W.; Tajima, T.; Putvinski, S.; Tuszewski, M.; Dettrick, S.; Korepanov, S.; Romero, J.; Smirnov, A.; Song, Y.; Thompson, M. C.; van Drie, A.; Yang, X.; Ivanov, A. A.; TAE Team

2017-10-01

Tri Alpha Energy's research has been devoted to producing a high temperature, stable, long-lived field-reversed configuration (FRC) plasma state by neutral-beam injection (NBI) and edge biasing/control. C-2U experiments have demonstrated drastic improvements in particle and energy confinement properties of FRC's, and the plasma performance obtained via 10 MW NBI has achieved plasma sustainment of up to 5 ms and plasma (diamagnetism) lifetimes of 10 + ms. The emerging confinement scaling, whereby electron energy confinement time is proportional to a positive power of the electron temperature, is very attractive for higher energy plasma confinement; accordingly, verification of the observed Te scaling law will be a key future research objective. The new experimental device, C-2W (now also called ``Norman''), has the following key subsystem upgrades from C-2U: (i) higher injected power, optimum energies, and extended pulse duration of the NBI system; (ii) installation of inner divertors with upgraded edge-biasing systems; (iii) fast external equilibrium/mirror-coil current ramp-up capability; and (iv) installation of trim/saddle coils for active feedback control of the FRC plasma. This paper will review highlights of the C-2W program.

Fast imaging diagnostics on the C-2U advanced beam-driven field-reversed configuration device

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

Granstedt, E. M., E-mail: egranstedt@trialphaenergy.com; Petrov, P.; Knapp, K.

2016-11-15

The C-2U device employed neutral beam injection, end-biasing, and various particle fueling techniques to sustain a Field-Reversed Configuration (FRC) plasma. As part of the diagnostic suite, two fast imaging instruments with radial and nearly axial plasma views were developed using a common camera platform. To achieve the necessary viewing geometry, imaging lenses were mounted behind re-entrant viewports attached to welded bellows. During gettering, the vacuum optics were retracted and isolated behind a gate valve permitting their removal if cleaning was necessary. The axial view incorporated a stainless-steel mirror in a protective cap assembly attached to the vacuum-side of the viewport.more » For each system, a custom lens-based, high-throughput optical periscope was designed to relay the plasma image about half a meter to a high-speed camera. Each instrument also contained a remote-controlled filter wheel, set between shots to isolate a particular hydrogen or impurity emission line. The design of the camera platform, imaging performance, and sample data for each view is presented.« less

Fast imaging diagnostics on the C-2U advanced beam-driven field-reversed configuration device

NASA Astrophysics Data System (ADS)

Granstedt, E. M.; Petrov, P.; Knapp, K.; Cordero, M.; Patel, V.

2016-11-01

The C-2U device employed neutral beam injection, end-biasing, and various particle fueling techniques to sustain a Field-Reversed Configuration (FRC) plasma. As part of the diagnostic suite, two fast imaging instruments with radial and nearly axial plasma views were developed using a common camera platform. To achieve the necessary viewing geometry, imaging lenses were mounted behind re-entrant viewports attached to welded bellows. During gettering, the vacuum optics were retracted and isolated behind a gate valve permitting their removal if cleaning was necessary. The axial view incorporated a stainless-steel mirror in a protective cap assembly attached to the vacuum-side of the viewport. For each system, a custom lens-based, high-throughput optical periscope was designed to relay the plasma image about half a meter to a high-speed camera. Each instrument also contained a remote-controlled filter wheel, set between shots to isolate a particular hydrogen or impurity emission line. The design of the camera platform, imaging performance, and sample data for each view is presented.

Stack sampling apparatus

DOEpatents

Lind, Randall F; Lloyd, Peter D; Love, Lonnie J; Noakes, Mark W; Pin, Francois G; Richardson, Bradley S; Rowe, John C

2014-09-16

An apparatus for obtaining samples from a structure includes a support member, at least one stabilizing member, and at least one moveable member. The stabilizing member has a first portion coupled to the support member and a second portion configured to engage with the structure to restrict relative movement between the support member and the structure. The stabilizing member is radially expandable from a first configuration where the second portion does not engage with a surface of the structure to a second configuration where the second portion engages with the surface of the structure.

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

PubMed Central

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. PMID:27504823

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

PubMed

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.

Evaluation of respondent-driven sampling.

PubMed

McCreesh, Nicky; Frost, Simon D W; Seeley, Janet; Katongole, Joseph; Tarsh, Matilda N; Ndunguse, Richard; Jichi, Fatima; Lunel, Natasha L; Maher, Dermot; Johnston, Lisa G; Sonnenberg, Pam; Copas, Andrew J; Hayes, Richard J; White, Richard G

2012-01-01

Respondent-driven sampling is a novel variant of link-tracing sampling for estimating the characteristics of hard-to-reach groups, such as HIV prevalence in sex workers. Despite its use by leading health organizations, the performance of this method in realistic situations is still largely unknown. We evaluated respondent-driven sampling by comparing estimates from a respondent-driven sampling survey with total population data. Total population data on age, tribe, religion, socioeconomic status, sexual activity, and HIV status were available on a population of 2402 male household heads from an open cohort in rural Uganda. A respondent-driven sampling (RDS) survey was carried out in this population, using current methods of sampling (RDS sample) and statistical inference (RDS estimates). Analyses were carried out for the full RDS sample and then repeated for the first 250 recruits (small sample). We recruited 927 household heads. Full and small RDS samples were largely representative of the total population, but both samples underrepresented men who were younger, of higher socioeconomic status, and with unknown sexual activity and HIV status. Respondent-driven sampling statistical inference methods failed to reduce these biases. Only 31%-37% (depending on method and sample size) of RDS estimates were closer to the true population proportions than the RDS sample proportions. Only 50%-74% of respondent-driven sampling bootstrap 95% confidence intervals included the population proportion. Respondent-driven sampling produced a generally representative sample of this well-connected nonhidden population. However, current respondent-driven sampling inference methods failed to reduce bias when it occurred. Whether the data required to remove bias and measure precision can be collected in a respondent-driven sampling survey is unresolved. Respondent-driven sampling should be regarded as a (potentially superior) form of convenience sampling method, and caution is required

Evaluation of Respondent-Driven Sampling

PubMed Central

McCreesh, Nicky; Frost, Simon; Seeley, Janet; Katongole, Joseph; Tarsh, Matilda Ndagire; Ndunguse, Richard; Jichi, Fatima; Lunel, Natasha L; Maher, Dermot; Johnston, Lisa G; Sonnenberg, Pam; Copas, Andrew J; Hayes, Richard J; White, Richard G

2012-01-01

Background Respondent-driven sampling is a novel variant of link-tracing sampling for estimating the characteristics of hard-to-reach groups, such as HIV prevalence in sex-workers. Despite its use by leading health organizations, the performance of this method in realistic situations is still largely unknown. We evaluated respondent-driven sampling by comparing estimates from a respondent-driven sampling survey with total-population data. Methods Total-population data on age, tribe, religion, socioeconomic status, sexual activity and HIV status were available on a population of 2402 male household-heads from an open cohort in rural Uganda. A respondent-driven sampling (RDS) survey was carried out in this population, employing current methods of sampling (RDS sample) and statistical inference (RDS estimates). Analyses were carried out for the full RDS sample and then repeated for the first 250 recruits (small sample). Results We recruited 927 household-heads. Full and small RDS samples were largely representative of the total population, but both samples under-represented men who were younger, of higher socioeconomic status, and with unknown sexual activity and HIV status. Respondent-driven-sampling statistical-inference methods failed to reduce these biases. Only 31%-37% (depending on method and sample size) of RDS estimates were closer to the true population proportions than the RDS sample proportions. Only 50%-74% of respondent-driven-sampling bootstrap 95% confidence intervals included the population proportion. Conclusions Respondent-driven sampling produced a generally representative sample of this well-connected non-hidden population. However, current respondent-driven-sampling inference methods failed to reduce bias when it occurred. Whether the data required to remove bias and measure precision can be collected in a respondent-driven sampling survey is unresolved. Respondent-driven sampling should be regarded as a (potentially superior) form of convenience-sampling

Attention bias in adults with anorexia nervosa, obsessive-compulsive disorder, and social anxiety disorder

PubMed Central

Schneier, Franklin R.; Kimeldorf, Marcia B.; Choo, Tse; Steinglass, Joanna E.; Wall, Melanie; Fyer, Abby J.; Simpson, H. Blair

2016-01-01

Background Attention bias to threat (selective attention toward threatening stimuli) has been frequently found in anxiety disorder samples, but its distribution both within and beyond this category is unclear. Attention bias has been studied extensively in social anxiety disorder (SAD) but relatively little in obsessive compulsive disorder (OCD), historically considered an anxiety disorder, or anorexia nervosa (AN), which is often characterized by interpersonal as well as body image/eating fears. Methods Medication-free adults with SAD (n=43), OCD (n=50), or AN (n=30), and healthy control volunteers (HC, n=74) were evaluated for attention bias with an established dot probe task presenting images of angry and neutral faces. Additional outcomes included attention bias variability (ABV), which summarizes fluctuation in attention between vigilance and avoidance, and has been reported to have superior reliability. We hypothesized that attention bias would be elevated in SAD and associated with SAD severity. Results Attention bias in each disorder did not differ from HC, but within the SAD group attention bias correlated significantly with severity of social avoidance. ABV was significantly lower in OCD versus HC, and it correlated positively with severity of OCD symptoms within the OCD group. Conclusions Findings do not support differences from HC in attention bias to threat faces for SAD, OCD, or AN. Within the SAD sample, the association of attention bias with severity of social avoidance is consistent with evidence that attention bias moderates development of social withdrawal. The association of ABV with OCD diagnosis and severity is novel and deserves further study. PMID:27174402

Parental and Family Factors as Predictors of Threat Bias in Anxious Youth

PubMed Central

Blossom, Jennifer B.; Ginsburg, Golda S.; Birmaher, Boris; Walkup, John T.; Kendall, Philip C.; Keeton, Courtney P.; Langley, Audra K.; Piacentini, John C.; Sakolsky, Dara; Albano, Anne Marie

2014-01-01

The present study examined the relative predictive value of parental anxiety, parents' expectation of child threat bias, and family dysfunction on child's threat bias in a clinical sample of anxious youth. Participants (N = 488) were part of the Child/Adolescent Anxiety Multi-modal study (CAMS), ages 7–17 years (M = 10.69; SD = 2.80). Children met diagnostic criteria for generalized anxiety disorder, separation anxiety and/or social phobia. Children and caregivers completed questionnaires assessing child threat bias, child anxiety, parent anxiety and family functioning. Child age, child anxiety, parental anxiety, parents' expectation of child's threat bias and child-reported family dysfunction were significantly associated with child threat bias. Controlling for child's age and anxiety, regression analyses indicated that parents' expectation of child's threat bias and child-reported family dysfunction were significant positive predictors of child's self-reported threat bias. Findings build on previous literature by clarifying parent and family factors that appear to play a role in the development or maintenance of threat bias and may inform etiological models of child anxiety. PMID:25328258

Not all numbers are equal: preferences and biases among children and adults when generating random sequences.

PubMed

Towse, John N; Loetscher, Tobias; Brugger, Peter

2014-01-01

We investigate the number preferences of children and adults when generating random digit sequences. Previous research has shown convincingly that adults prefer smaller numbers when randomly choosing between responses 1-6. We analyze randomization choices made by both children and adults, considering a range of experimental studies and task configurations. Children - most of whom are between 8 and 11~years - show a preference for relatively large numbers when choosing numbers 1-10. Adults show a preference for small numbers with the same response set. We report a modest association between children's age and numerical bias. However, children also exhibit a small number bias with a smaller response set available, and they show a preference specifically for the numbers 1-3 across many datasets. We argue that number space demonstrates both continuities (numbers 1-3 have a distinct status) and change (a developmentally emerging bias toward the left side of representational space or lower numbers).

The CogBIAS longitudinal study protocol: cognitive and genetic factors influencing psychological functioning in adolescence.

PubMed

Booth, Charlotte; Songco, Annabel; Parsons, Sam; Heathcote, Lauren; Vincent, John; Keers, Robert; Fox, Elaine

2017-12-29

Optimal psychological development is dependent upon a complex interplay between individual and situational factors. Investigating the development of these factors in adolescence will help to improve understanding of emotional vulnerability and resilience. The CogBIAS longitudinal study (CogBIAS-L-S) aims to combine cognitive and genetic approaches to investigate risk and protective factors associated with the development of mood and impulsivity-related outcomes in an adolescent sample. CogBIAS-L-S is a three-wave longitudinal study of typically developing adolescents conducted over 4 years, with data collection at age 12, 14 and 16. At each wave participants will undergo multiple assessments including a range of selective cognitive processing tasks (e.g. attention bias, interpretation bias, memory bias) and psychological self-report measures (e.g. anxiety, depression, resilience). Saliva samples will also be collected at the baseline assessment for genetic analyses. Multilevel statistical analyses will be performed to investigate the developmental trajectory of cognitive biases on psychological functioning, as well as the influence of genetic moderation on these relationships. CogBIAS-L-S represents the first longitudinal study to assess multiple cognitive biases across adolescent development and the largest study of its kind to collect genetic data. It therefore provides a unique opportunity to understand how genes and the environment influence the development and maintenance of cognitive biases and provide insight into risk and protective factors that may be key targets for intervention.

Configurational Molecular Glue: One Optically Active Polymer Attracts Two Oppositely Configured Optically Active Polymers.

PubMed

Tsuji, Hideto; Noda, Soma; Kimura, Takayuki; Sobue, Tadashi; Arakawa, Yuki

2017-03-24

D-configured poly(D-lactic acid) (D-PLA) and poly(D-2-hydroxy-3-methylbutanoic acid) (D-P2H3MB) crystallized separately into their homo-crystallites when crystallized by precipitation or solvent evaporation, whereas incorporation of L-configured poly(L-2-hydroxybutanoic acid) (L-P2HB) in D-configured D-PLA and D-P2H3MB induced co-crystallization or ternary stereocomplex formation between D-configured D-PLA and D-P2H3MB and L-configured L-P2HB. However, incorporation of D-configured poly(D-2-hydroxybutanoic acid) (D-P2HB) in D-configured D-PLA and D-P2H3MB did not cause co-crystallization between D-configured D-PLA and D-P2H3MB and D-configured D-P2HB but separate crystallization of each polymer occurred. These findings strongly suggest that an optically active polymer (L-configured or D-configured polymer) like unsubstituted or substituted optically active poly(lactic acid)s can act as "a configurational or helical molecular glue" for two oppositely configured optically active polymers (two D-configured polymers or two L-configured polymers) to allow their co-crystallization. The increased degree of freedom in polymer combination is expected to assist to pave the way for designing polymeric composites having a wide variety of physical properties, biodegradation rate and behavior in the case of biodegradable polymers.

Configurational Molecular Glue: One Optically Active Polymer Attracts Two Oppositely Configured Optically Active Polymers

NASA Astrophysics Data System (ADS)

Tsuji, Hideto; Noda, Soma; Kimura, Takayuki; Sobue, Tadashi; Arakawa, Yuki

2017-03-01

D-configured poly(D-lactic acid) (D-PLA) and poly(D-2-hydroxy-3-methylbutanoic acid) (D-P2H3MB) crystallized separately into their homo-crystallites when crystallized by precipitation or solvent evaporation, whereas incorporation of L-configured poly(L-2-hydroxybutanoic acid) (L-P2HB) in D-configured D-PLA and D-P2H3MB induced co-crystallization or ternary stereocomplex formation between D-configured D-PLA and D-P2H3MB and L-configured L-P2HB. However, incorporation of D-configured poly(D-2-hydroxybutanoic acid) (D-P2HB) in D-configured D-PLA and D-P2H3MB did not cause co-crystallization between D-configured D-PLA and D-P2H3MB and D-configured D-P2HB but separate crystallization of each polymer occurred. These findings strongly suggest that an optically active polymer (L-configured or D-configured polymer) like unsubstituted or substituted optically active poly(lactic acid)s can act as “a configurational or helical molecular glue” for two oppositely configured optically active polymers (two D-configured polymers or two L-configured polymers) to allow their co-crystallization. The increased degree of freedom in polymer combination is expected to assist to pave the way for designing polymeric composites having a wide variety of physical properties, biodegradation rate and behavior in the case of biodegradable polymers.

Expectancy bias mediates the link between social anxiety and memory bias for social evaluation

PubMed Central

Caouette, Justin D.; Ruiz, Sarah K.; Lee, Clinton C.; Anbari, Zainab; Schriber, Roberta A.; Guyer, Amanda E.

2014-01-01

Social anxiety (SA) involves a multitude of cognitive symptoms related to fear of evaluation, including expectancy and memory biases. We examined whether memory biases are influenced by expectancy biases for social feedback in SA. We hypothesized that, faced with a socially evaluative event, people with higher SA would show a negative expectancy bias for future feedback. Furthermore, we predicted that memory bias for feedback in SA would be mediated by expectancy bias. Ninety-four undergraduate students (55 women, mean age = 19.76 years) underwent a two-visit task that measured expectations about (Visit 1) and memory of (Visit 2) feedback from unknown peers. Results showed that higher levels of SA were associated with negative expectancy bias. An indirect relationship was found between SA and memory bias that was mediated by expectancy bias. The results suggest that expectancy biases are in the causal path from SA to negative memory biases for social evaluation. PMID:25252925

Beyond assembly bias: exploring secondary halo biases for cluster-size haloes

NASA Astrophysics Data System (ADS)

Mao, Yao-Yuan; Zentner, Andrew R.; Wechsler, Risa H.

2018-03-01

Secondary halo bias, commonly known as `assembly bias', is the dependence of halo clustering on a halo property other than mass. This prediction of the Λ Cold Dark Matter cosmology is essential to modelling the galaxy distribution to high precision and interpreting clustering measurements. As the name suggests, different manifestations of secondary halo bias have been thought to originate from halo assembly histories. We show conclusively that this is incorrect for cluster-size haloes. We present an up-to-date summary of secondary halo biases of high-mass haloes due to various halo properties including concentration, spin, several proxies of assembly history, and subhalo properties. While concentration, spin, and the abundance and radial distribution of subhaloes exhibit significant secondary biases, properties that directly quantify halo assembly history do not. In fact, the entire assembly histories of haloes in pairs are nearly identical to those of isolated haloes. In general, a global correlation between two halo properties does not predict whether or not these two properties exhibit similar secondary biases. For example, assembly history and concentration (or subhalo abundance) are correlated for both paired and isolated haloes, but follow slightly different conditional distributions in these two cases. This results in a secondary halo bias due to concentration (or subhalo abundance), despite the lack of assembly bias in the strict sense for cluster-size haloes. Due to this complexity, caution must be exercised in using any one halo property as a proxy to study the secondary bias due to another property.

Cognitive Deficits and Positively Biased Self-Perceptions in Children with ADHD

PubMed Central

McQuade, Julia D.; Tomb, Meghan; Hoza, Betsy; Waschbusch, Daniel A.; Hurt, Elizabeth A.; Vaughn, Aaron J.

2011-01-01

This study examined the relation between cognitive deficits and positive bias in a sample of 272 children with and without Attention Deficit Hyperactivity Disorder (ADHD; 7–12 years old). Results indicated that children with ADHD with and without biased self-perceptions exhibit differences in specific cognitive deficits (executive processes, working memory, broad attention, and cognitive fluency) compared to each other and to control children. Further, specific cognitive deficits emerged as partial mediators of the relation between ADHD diagnostic status and positive bias. Interestingly, some differences in results emerged based on the domain considered (academic, social, behavioral competence). Results lend initial support to the role of cognitive deficits in the positive bias of some children with ADHD. Implications for future research and intervention are discussed. PMID:20820902

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

PubMed

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.

ION Configuration Editor

NASA Technical Reports Server (NTRS)

Borgen, Richard L.

2013-01-01

The configuration of ION (Inter - planetary Overlay Network) network nodes is a manual task that is complex, time-consuming, and error-prone. This program seeks to accelerate this job and produce reliable configurations. The ION Configuration Editor is a model-based smart editor based on Eclipse Modeling Framework technology. An ION network designer uses this Eclipse-based GUI to construct a data model of the complete target network and then generate configurations. The data model is captured in an XML file. Intrinsic editor features aid in achieving model correctness, such as field fill-in, type-checking, lists of valid values, and suitable default values. Additionally, an explicit "validation" feature executes custom rules to catch more subtle model errors. A "survey" feature provides a set of reports providing an overview of the entire network, enabling a quick assessment of the model s completeness and correctness. The "configuration" feature produces the main final result, a complete set of ION configuration files (eight distinct file types) for each ION node in the network.

Estimation and applications of size-biased distributions in forestry

Treesearch

Jeffrey H. Gove

2003-01-01

Size-biased distributions arise naturally in several contexts in forestry and ecology. Simple power relationships (e.g. basal area and diameter at breast height) between variables are one such area of interest arising from a modelling perspective. Another, probability proportional to size PPS) sampling, is found in the most widely used methods for sampling standing or...

Large exchange bias effect in NiFe2O4/CoO nanocomposites

NASA Astrophysics Data System (ADS)

Mohan, Rajendra; Prasad Ghosh, Mritunjoy; Mukherjee, Samrat

2018-03-01

In this work, we report the exchange bias effect of NiFe2O4/CoO nanocomposites, synthesized via chemical co-precipitation method. Four samples of different particle size ranging from 4 nm to 31 nm were prepared with the annealing temperature varying from 200 °C to 800 °C. X-ray diffraction analysis of all the samples confirmed the presence of cubic spinel phase of Nickel ferrite along with CoO phase without trace of any impurity. Sizes of the particles were studied from transmission electron micrographs and were found to be in agreement with those estimated from x-ray diffraction. Field cooled (FC) hysteresis loops at 5 K revealed an exchange bias (HE) of 2.2 kOe for the sample heated at 200 °C which decreased with the increase of particle size. Exchange bias expectedly vanished at 300 K due to high thermal energy (kBT) and low effective surface anisotropy. M-T curves revealed a blocking temperature of 135 K for the sample with smaller particle size.

Driving spin transition at interface: Role of adsorption configurations

NASA Astrophysics Data System (ADS)

Zhang, Yachao

2018-01-01

A clear insight into the electrical manipulation of molecular spins at interface is crucial to the design of molecule-based spintronic devices. Here we report on the electrically driven spin transition in manganocene physisorbed on a metallic surface in two different adsorption configurations predicted by ab initio techniques, including a Hubbard-U correction at the manganese site and accounting for the long-range van der Waals interactions. We show that the application of an electric field at the interface induces a high-spin to low-spin transition in the flat-lying manganocene, while it could hardly alter the high-spin ground state of the standing-up molecule. This phenomenon cannot be explained by either the molecule-metal charge transfer or the local electron correlation effects. We demonstrate a linear dependence of the intra-molecular spin-state splitting on the energy difference between crystal-field splitting and on-site Coulomb repulsion. After considering the molecule-surface binding energy shifts upon spin transition, we reproduce the obtained spin-state energetics. We find that the configuration-dependent responses of the spin-transition originate from the binding energy shifts instead of the variation of the local ligand field. Through these analyses, we obtain an intuitive understanding of the effects of molecule-surface contact on spin-crossover under electrical bias.

Promoting Institutional Change Through Bias Literacy

PubMed Central

Carnes, Molly; Devine, Patricia G.; Isaac, Carol; Manwell, Linda Baier; Ford, Cecelia E.; Byars-Winston, Angela; Fine, Eve; Sheridan, Jennifer Thurik

2012-01-01

The National Science Foundation and others conclude that institutional transformation is required to ensure equal opportunities for the participation and advancement of men and women in academic science, technology, engineering, mathematics, and medicine (STEMM). Such transformation requires changing the habitual attitudes and behaviors of faculty. Approaching implicit bias as a remediable habit, we present the theoretical basis and conceptual model underpinning an educational intervention to promote bias literacy among university faculty as a step toward institutional transformation regarding gender equity. We describe the development and implementation of a Bias Literacy Workshop in detail so others can replicate or adapt it to their setting. Of the 220 (167 faculty and 53 nonfaculty) attendees from the initial 17 departments/divisions offered this workshop, all 180 who completed a written evaluation found the workshop at least “somewhat useful” and 74% found it “very useful.” Over 68% indicated increased knowledge of the workshop material. Of the 186 participants who wrote a commitment to engage in new activities to promote gender equity, 87% incorporated specific workshop content. Twenty-four participants were interviewed 4–6 months after attending the workshop; 75% of these not only demonstrated increased bias awareness, but described plans to change—or had actually changed—behaviors because of the workshop. Based on our sample of faculty from a Midwestern university, we conclude that at least one third of STEMM faculty who are invited will attend a 2.5-hr Bias Literacy Workshop, that nearly all will find it useful, and that most will complete a written commitment to promoting gender equity. These findings suggest that this educational intervention may effectively promote institutional change regarding gender equity. PMID:22822416

Associations among Negative Parenting, Attention Bias to Anger, and Social Anxiety among Youth

PubMed Central

Gulley, Lauren; Oppenheimer, Caroline; Hankin, Benjamin

2014-01-01

Theories of affective learning suggest that early experiences contribute to emotional disorders by influencing the development of processing biases for negative emotional stimuli. Although studies show that physically abused children preferentially attend to angry faces, it is unclear whether youth exposed to more typical aspects of negative parenting would exhibit the same type of bias. The current studies extend previous research by linking observed negative parenting styles (e.g. authoritarian) and behaviors (e.g. criticism and negative affect) to attention bias for angry faces in both a psychiatrically enriched (ages 11–17 years; N = 60) and a general community (ages 9–15 years; N = 75) sample of youth. In addition, the association between observed negative parenting (e.g. authoritarian style and negative affect) and youth social anxiety was mediated by attention bias for angry faces in the general community sample. Overall, findings provide preliminary support for theories of affective learning and risk for psychopathology among youth. PMID:23815705

Associations among negative parenting, attention bias to anger, and social anxiety among youth.

PubMed

Gulley, Lauren D; Oppenheimer, Caroline W; Hankin, Benjamin L

2014-02-01

Theories of affective learning suggest that early experiences contribute to emotional disorders by influencing the development of processing biases for negative emotional stimuli. Although studies have shown that physically abused children preferentially attend to angry faces, it is unclear whether youth exposed to more typical aspects of negative parenting exhibit the same type of bias. The current studies extend previous research by linking observed negative parenting styles (e.g., authoritarian) and behaviors (e.g., criticism and negative affect) to attention bias for angry faces in both a psychiatrically enriched (ages 11-17 years; N = 60) and a general community (ages 9-15 years; N = 75) sample of youth. In addition, the association between observed negative parenting (e.g., authoritarian style and negative affect) and youth social anxiety was mediated by attention bias for angry faces in the general community sample. Overall, findings provide preliminary support for theories of affective learning and risk for psychopathology among youth.

Household chaos moderates the link between maternal attribution bias and parenting

PubMed Central

Wang, Z.; Deater-Deckard, K.; Bell, M.A.

2013-01-01

Objective Parents who attribute child misbehavior to children's intentions and dismiss situational factors tend to show more hostility and less warmth in their parenting behavior, and are at greater risk for maltreatment. We extended this literature by investigating the role of household chaos as a moderator of the link between maternal attribution biases and parenting behaviors. Design The current sample included 160 mothers of 3- to7-year-old children. Mothers provided reports on their attribution biases and household chaos levels. Maternal negativity and positivity were measured using self-reports and observers’ ratings. Results The links between attribution bias and parenting behavior were stronger in more chaotic environments, with the moderating effect of chaos being particularly strong for internal attribution bias. Conclusions The findings point to the importance of social cognitive biases in the etiology of maternal behavior in family contexts that lack order and predictability. PMID:24358017

Chirality and Magnetic Configurations of Solar Filaments

NASA Astrophysics Data System (ADS)

Ouyang, Y.; Zhou, Y. H.; Chen, P. F.; Fang, C.

2017-01-01

It has been revealed that the magnetic topology in the solar atmosphere displays hemispheric preference, I.e., helicity is mainly negative/positive in the northern/southern hemispheres, respectively. However, the strength of the hemispheric rule and its cyclic variation are controversial. In this paper, we apply a new method based on the filament drainage to 571 erupting filaments from 2010 May to 2015 December in order to determine the filament chirality and its hemispheric preference. It is found that 91.6% of our sample of erupting filaments follows the hemispheric rule of helicity sign. It is also found that the strength of the hemispheric preference of the quiescent filaments decreases slightly from ˜97% in the rising phase to ˜85% in the declining phase of solar cycle 24, whereas the strength of the intermediate filaments keeps a high value around 96 ± 4% at all times. Only the active-region filaments show significant variations. Their strength of the hemispheric rule rises from ˜63% to ˜95% in the rising phase, and keeps a high value of 82% ± 5% during the declining phase. Furthermore, during a half-year period around the solar maximum, their hemispheric preference totally vanishes. Additionally, we also diagnose the magnetic configurations of the filaments based on our indirect method and find that in our sample of erupting events, 89% are inverse-polarity filaments with a flux rope magnetic configuration, whereas 11% are normal-polarity filaments with a sheared arcade configuration.

Race-Related Cognitive Test Bias in the ACTIVE Study: A MIMIC Model Approach

PubMed Central

Aiken Morgan, Adrienne T.; Marsiske, Michael; Dzierzewski, Joseph; Jones, Richard N.; Whitfield, Keith E.; Johnson, Kathy E.; Cresci, Mary K.

2010-01-01

The present study investigated evidence for race-related test bias in cognitive measures used in the baseline assessment of the ACTIVE clinical trial. Test bias against African Americans has been documented in both cognitive aging and early lifespan studies. Despite significant mean performance differences, Multiple Indicators Multiple Causes (MIMIC) models suggested most differences were at the construct level. There was little evidence that specific measures put either group at particular advantage or disadvantage and little evidence of cognitive test bias in this sample. Small group differences in education, cognitive status, and health suggest positive selection may have attenuated possible biases. PMID:20845121

Volunteer Bias in Recruitment, Retention, and Blood Sample Donation in a Randomised Controlled Trial Involving Mothers and Their Children at Six Months and Two Years: A Longitudinal Analysis

PubMed Central

Jordan, Sue; Watkins, Alan; Storey, Mel; Allen, Steven J.; Brooks, Caroline J.; Garaiova, Iveta; Heaven, Martin L.; Jones, Ruth; Plummer, Sue F.; Russell, Ian T.; Thornton, Catherine A.; Morgan, Gareth

2013-01-01

Background The vulnerability of clinical trials to volunteer bias is under-reported. Volunteer bias is systematic error due to differences between those who choose to participate in studies and those who do not. Methods and Results This paper extends the applications of the concept of volunteer bias by using data from a trial of probiotic supplementation for childhood atopy in healthy dyads to explore 1) differences between a) trial participants and aggregated data from publicly available databases b) participants and non-participants as the trial progressed 2) impact on trial findings of weighting data according to deprivation (Townsend) fifths in the sample and target populations. 1) a) Recruits (n = 454) were less deprived than the target population, matched for area of residence and delivery dates (n = 6,893) (mean [SD] deprivation scores 0.09[4.21] and 0.79[4.08], t = 3.44, df = 511, p<0.001). b) i)As the trial progressed, representation of the most deprived decreased. These participants and smokers were less likely to be retained at 6 months (n = 430[95%]) (OR 0.29,0.13–0.67 and 0.20,0.09–0.46), and 2 years (n = 380[84%]) (aOR 0.68,0.50–0.93 and 0.55,0.28–1.09), and consent to infant blood sample donation (n = 220[48%]) (aOR 0.72,0.57–0.92 and 0.43,0.22–0.83). ii)Mothers interested in probiotics or research or reporting infants’ adverse events or rashes were more likely to attend research clinics and consent to skin-prick testing. Mothers participating to help children were more likely to consent to infant blood sample donation. 2) In one trial outcome, atopic eczema, the intervention had a positive effect only in the over-represented, least deprived group. Here, data weighting attenuated risk reduction from 6.9%(0.9–13.1%) to 4.6%(−1.4–+10.5%), and OR from 0.40(0.18–0.91) to 0.56(0.26–1.21). Other findings were unchanged. Conclusions Potential for volunteer bias intensified during the trial, due to non

Volunteer bias in recruitment, retention, and blood sample donation in a randomised controlled trial involving mothers and their children at six months and two years: a longitudinal analysis.

PubMed

Jordan, Sue; Watkins, Alan; Storey, Mel; Allen, Steven J; Brooks, Caroline J; Garaiova, Iveta; Heaven, Martin L; Jones, Ruth; Plummer, Sue F; Russell, Ian T; Thornton, Catherine A; Morgan, Gareth

2013-01-01

The vulnerability of clinical trials to volunteer bias is under-reported. Volunteer bias is systematic error due to differences between those who choose to participate in studies and those who do not. This paper extends the applications of the concept of volunteer bias by using data from a trial of probiotic supplementation for childhood atopy in healthy dyads to explore 1) differences between a) trial participants and aggregated data from publicly available databases b) participants and non-participants as the trial progressed 2) impact on trial findings of weighting data according to deprivation (Townsend) fifths in the sample and target populations. 1) a) Recruits (n = 454) were less deprived than the target population, matched for area of residence and delivery dates (n = 6,893) (mean [SD] deprivation scores 0.09[4.21] and 0.79[4.08], t = 3.44, df = 511, p<0.001). b) i) As the trial progressed, representation of the most deprived decreased. These participants and smokers were less likely to be retained at 6 months (n = 430[95%]) (OR 0.29,0.13-0.67 and 0.20,0.09-0.46), and 2 years (n = 380[84%]) (aOR 0.68,0.50-0.93 and 0.55,0.28-1.09), and consent to infant blood sample donation (n = 220[48%]) (aOR 0.72,0.57-0.92 and 0.43,0.22-0.83). ii) Mothers interested in probiotics or research or reporting infants' adverse events or rashes were more likely to attend research clinics and consent to skin-prick testing. Mothers participating to help children were more likely to consent to infant blood sample donation. 2) In one trial outcome, atopic eczema, the intervention had a positive effect only in the over-represented, least deprived group. Here, data weighting attenuated risk reduction from 6.9%(0.9-13.1%) to 4.6%(-1.4-+10.5%), and OR from 0.40(0.18-0.91) to 0.56(0.26-1.21). Other findings were unchanged. Potential for volunteer bias intensified during the trial, due to non-participation of the most deprived and smokers. However, these were

Peak-locking centroid bias in Shack-Hartmann wavefront sensing

NASA Astrophysics Data System (ADS)

Anugu, Narsireddy; Garcia, Paulo J. V.; Correia, Carlos M.

2018-05-01

Shack-Hartmann wavefront sensing relies on accurate spot centre measurement. Several algorithms were developed with this aim, mostly focused on precision, i.e. minimizing random errors. In the solar and extended scene community, the importance of the accuracy (bias error due to peak-locking, quantization, or sampling) of the centroid determination was identified and solutions proposed. But these solutions only allow partial bias corrections. To date, no systematic study of the bias error was conducted. This article bridges the gap by quantifying the bias error for different correlation peak-finding algorithms and types of sub-aperture images and by proposing a practical solution to minimize its effects. Four classes of sub-aperture images (point source, elongated laser guide star, crowded field, and solar extended scene) together with five types of peak-finding algorithms (1D parabola, the centre of gravity, Gaussian, 2D quadratic polynomial, and pyramid) are considered, in a variety of signal-to-noise conditions. The best performing peak-finding algorithm depends on the sub-aperture image type, but none is satisfactory to both bias and random errors. A practical solution is proposed that relies on the antisymmetric response of the bias to the sub-pixel position of the true centre. The solution decreases the bias by a factor of ˜7 to values of ≲ 0.02 pix. The computational cost is typically twice of current cross-correlation algorithms.

Method and apparatus for sensing a desired component of an incident magnetic field using magneto resistive elements biased in different directions

NASA Technical Reports Server (NTRS)

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.

Growing cell-phone population and noncoverage bias in traditional random digit dial telephone health surveys.

PubMed

Lee, Sunghee; Brick, J Michael; Brown, E Richard; Grant, David

2010-08-01

Examine the effect of including cell-phone numbers in a traditional landline random digit dial (RDD) telephone survey. The 2007 California Health Interview Survey (CHIS). CHIS 2007 is an RDD telephone survey supplementing a landline sample in California with a sample of cell-only (CO) adults. We examined the degree of bias due to exclusion of CO populations and compared a series of demographic and health-related characteristics by telephone usage. When adjusted for noncoverage in the landline sample through weighting, the potential noncoverage bias due to excluding CO adults in landline telephone surveys is diminished. Both CO adults and adults who have both landline and cell phones but mostly use cell phones appear different from other telephone usage groups. Controlling for demographic differences did not attenuate the significant distinctiveness of cell-mostly adults. While careful weighting can mitigate noncoverage bias in landline telephone surveys, the rapid growth of cell-phone population and their distinctive characteristics suggest it is important to include a cell-phone sample. Moreover, the threat of noncoverage bias in telephone health survey estimates could mislead policy makers with possibly serious consequences for their ability to address important health policy issues.

Neural Network and Nearest Neighbor Algorithms for Enhancing Sampling of Molecular Dynamics.

PubMed