Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

PubMed Central

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

PubMed

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

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

Discerning bias in forensic psychological reports in insanity cases.

PubMed

Neal, Tess M S

2018-04-19

This project began as an attempt to develop systematic, measurable indicators of bias in written forensic mental health evaluations focused on the issue of insanity. Although forensic clinicians observed in this study did vary systematically in their report-writing behaviors on several of the indicators of interest, the data are most useful in demonstrating how and why bias is hard to ferret out. Naturalistic data were used in this project (i.e., 122 real forensic insanity reports), which in some ways is a strength. However, given the nature of bias and the problem of inferring whether a particular judgment is biased, naturalistic data also made arriving at conclusions about bias difficult. This paper describes the nature of bias - including why it is a special problem in insanity evaluations - and why it is hard to study and document. It details the efforts made in an attempt to find systematic indicators of potential bias, and how this effort was successful in part, but also how and why it failed. The lessons these efforts yield for future research are described. We close with a discussion of the limitations of this study and future directions for work in this area. Copyright © 2018 John Wiley & Sons, Ltd.

Field-Tuned Superconductor-Insulator Transition with and without Current Bias.

PubMed

Bielejec, E; Wu, Wenhao

2002-05-20

The magnetic-field-tuned superconductor-insulator transition has been studied in ultrathin beryllium films quench condensed near 20 K. In the zero-current limit, a finite-size scaling analysis yields the scaling exponent product nuz = 1.35+/-0.10 and a critical sheet resistance, R(c), of about 1.2R(Q), with R(Q) = h/4e(2). However, in the presence of dc bias currents that are smaller than the zero-field critical currents, nuz becomes 0.75+/-0.10. This new set of exponents suggests that the field-tuned transitions with and without a dc bias current belong to different universality classes.

Greenhouse tomato limited cluster production systems: crop management practices affect yield

NASA Technical Reports Server (NTRS)

Logendra, L. S.; Gianfagna, T. J.; Specca, D. R.; Janes, H. W.

2001-01-01

Limited-cluster production systems may be a useful strategy to increase crop production and profitability for the greenhouse tomato (Lycopersicon esculentum Mill). In this study, using an ebb-and-flood hydroponics system, we modified plant architecture and spacing and determined the effects on fruit yield and harvest index at two light levels. Single-cluster plants pruned to allow two leaves above the cluster had 25% higher fruit yields than did plants pruned directly above the cluster; this was due to an increase in fruit weight, not fruit number. Both fruit yield and harvest index were greater for all single-cluster plants at the higher light level because of increases in both fruit weight and fruit number. Fruit yield for two-cluster plants was 30% to 40% higher than for single-cluster plants, and there was little difference in the dates or length of the harvest period. Fruit yield for three-cluster plants was not significantly different from that of two-cluster plants; moreover, the harvest period was delayed by 5 days. Plant density (5.5, 7.4, 9.2 plants/m2) affected fruit yield/plant, but not fruit yield/unit area. Given the higher costs for materials and labor associated with higher plant densities, a two-cluster crop at 5.5 plants/m2 with two leaves above the cluster was the best of the production system strategies tested.

Water limits to closing yield gaps

NASA Astrophysics Data System (ADS)

Davis, Kyle Frankel; Rulli, Maria Cristina; Garrassino, Francesco; Chiarelli, Davide; Seveso, Antonio; D'Odorico, Paolo

2017-01-01

Agricultural intensification is often seen as a suitable approach to meet the growing demand for agricultural products and improve food security. It typically entails the use of fertilizers, new cultivars, irrigation, and other modern technology. In regions of the world affected by seasonal or chronic water scarcity, yield gap closure is strongly dependent on irrigation (blue water). Global yield gap assessments have often ignored whether the water required to close the yield gap is locally available. Here we perform a gridded global analysis (10 km resolution) of the blue water consumption that is needed annually to close the yield gap worldwide and evaluate the associated pressure on renewable freshwater resources. We find that, to close the yield gap, human appropriation of freshwater resources for irrigation would have to increase at least by 146%. Most study countries would experience at least a doubling in blue water requirement, with 71% of the additional blue water being required by only four crops - maize, rice, soybeans, and wheat. Further, in some countries (e.g., Algeria, Morocco, Syria, Tunisia, and Yemen) the total volume of blue water required for yield gap closure would exceed sustainable levels of freshwater consumption (i.e., 40% of total renewable surface and groundwater resources).

Communication: Improved ab initio molecular dynamics by minimally biasing with experimental data

NASA Astrophysics Data System (ADS)

White, Andrew D.; Knight, Chris; Hocky, Glen M.; Voth, Gregory A.

2017-01-01

Accounting for electrons and nuclei simultaneously is a powerful capability of ab initio molecular dynamics (AIMD). However, AIMD is often unable to accurately reproduce properties of systems such as water due to inaccuracies in the underlying electronic density functionals. This shortcoming is often addressed by added empirical corrections and/or increasing the simulation temperature. We present here a maximum-entropy approach to directly incorporate limited experimental data via a minimal bias. Biased AIMD simulations of water and an excess proton in water are shown to give significantly improved properties both for observables which were biased to match experimental data and for unbiased observables. This approach also yields new physical insight into inaccuracies in the underlying density functional theory as utilized in the unbiased AIMD.

Communication: Improved ab initio molecular dynamics by minimally biasing with experimental data.

PubMed

White, Andrew D; Knight, Chris; Hocky, Glen M; Voth, Gregory A

2017-01-28

Accounting for electrons and nuclei simultaneously is a powerful capability of ab initio molecular dynamics (AIMD). However, AIMD is often unable to accurately reproduce properties of systems such as water due to inaccuracies in the underlying electronic density functionals. This shortcoming is often addressed by added empirical corrections and/or increasing the simulation temperature. We present here a maximum-entropy approach to directly incorporate limited experimental data via a minimal bias. Biased AIMD simulations of water and an excess proton in water are shown to give significantly improved properties both for observables which were biased to match experimental data and for unbiased observables. This approach also yields new physical insight into inaccuracies in the underlying density functional theory as utilized in the unbiased AIMD.

Effect of Anisotropic Yield Function Evolution on Estimation of Forming Limit Diagram

NASA Astrophysics Data System (ADS)

Bandyopadhyay, K.; Basak, S.; Choi, H. J.; Panda, S. K.; Lee, M. G.

2017-09-01

In case of theoretical prediction of the FLD, the variations in yield stress and R-values along different material directions, were long been implemented to enhance the accuracy. Although influences of different yield models and hardening laws on formability were well addressed, anisotropic evolution of yield loci under monotonic loading with different deformation modes is yet to be explored. In the present study, Marciniak-Kuckzinsky (M-K) model was modified to incorporate the change in the shape of the initial yield function with evolution due to anisotropic hardening. Swift’s hardening law along with two different anisotropic yield criteria, namely Hill48 and Yld2000-2d were implemented in the model. The Hill48 yield model was applied with non-associated flow rule to comprehend the effect of variations in both yield stress and R-values. The numerically estimated FLDs were validated after comparing with FLD evaluated through experiments. A low carbon steel was selected, and hemispherical punch stretching test was performed for FLD evaluation. Additionally, the numerically estimated FLDs were incorporated in FE simulations to predict limiting dome heights for validation purpose. Other formability performances like strain distributions over the deformed cup surface were validated with experimental results.

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.

Biased selection within the social health insurance market in Colombia.

PubMed

Castano, Ramon; Zambrano, Andres

2006-12-01

Reducing the impact of insurance market failures with regulations such as community-rated premiums, standardized benefit packages and open enrolment, yield limited effect because they create room for selection bias. The Colombian social health insurance system started a market approach in 1993 expecting to improve performance of preexisting monopolistic insurance funds by exposing them to competition by new entrants. This paper tests the hypothesis that market failures would lead to biased selection favoring new entrants. Two household surveys are analyzed using Self-Reported Health Status and the presence of chronic conditions as prospective indicators of individual risk. Biased selection is found to take place, leading to adverse selection among incumbents, and favorable selection among new entrants. This pattern is absent in 1997 but is evident in 2003. Given that the two incumbents analyzed are public organizations, the fiscal implications of the findings in terms of government bailouts, are analyzed.

The Model Identification Test: Perceptual Bias of Elementary School Children Using a Limited Verbal Evaluation Instrument

ERIC Educational Resources Information Center

McIntyre, Patrick J.

1974-01-01

Reported is a study to verify the pattern of bias associated with the Model Identification Test and to determine its source. This instrument is a limited verbal science test designed to determine the knowledge possessed by elementary school children of selected concepts related to "the particle nature of matter." (PEB)

Effect of Diffusion Limitations on Multianalyte Determination from Biased Biosensor Response

PubMed Central

Baronas, Romas; Kulys, Juozas; Lančinskas, Algirdas; Žilinskas, Antanas

2014-01-01

The optimization-based quantitative determination of multianalyte concentrations from biased biosensor responses is investigated under internal and external diffusion-limited conditions. A computational model of a biocatalytic amperometric biosensor utilizing a mono-enzyme-catalyzed (nonspecific) competitive conversion of two substrates was used to generate pseudo-experimental responses to mixtures of compounds. The influence of possible perturbations of the biosensor signal, due to a white noise- and temperature-induced trend, on the precision of the concentration determination has been investigated for different configurations of the biosensor operation. The optimization method was found to be suitable and accurate enough for the quantitative determination of the concentrations of the compounds from a given biosensor transient response. The computational experiments showed a complex dependence of the precision of the concentration estimation on the relative thickness of the outer diffusion layer, as well as on whether the biosensor operates under diffusion- or kinetics-limited conditions. When the biosensor response is affected by the induced exponential trend, the duration of the biosensor action can be optimized for increasing the accuracy of the quantitative analysis. PMID:24608006

Photosynthetic limitation as a factor influencing yield in highbush blueberries (Vaccinium corymbosum) grown in a northern European environment.

PubMed

Petridis, Antonios; van der Kaay, Jeroen; Chrysanthou, Elina; McCallum, Susan; Graham, Julie; Hancock, Robert D

2018-05-25

Published evidence indicates that nearly 60% of blueberry-producing countries experience yield instability. Yield is a complex trait determined by genetic and environmental factors. Here, using physiological and biochemical approaches, we tested the hypothesis that yield instability results from year-to-year environmental variation that limits carbon assimilation, storage and partitioning. The data indicate that fruit development depends primarily on the daily production of non-structural carbohydrates by leaves, and there is no accumulation of a starch buffer to allow continuous ripening under conditions limiting for photosynthesis. Photosynthesis was saturated at moderate light irradiance and this was mainly due to stomatal and biochemical limitations. In a dynamic light environment, photosynthesis was further limited by slow stomatal response to increasing light. Finally, labelling with 13CO2 at specific stages of fruit development revealed a relatively even distribution of newly assimilated carbon between stems, roots and fruits, suggesting that the fruit is not a strong sink. We conclude that a significant component of yield variability results from limitations in photosynthetic efficiency that are compounded by an inability to accumulate starch reserves in blueberry storage tissues in a typical northern European environment. This work informs techniques for improving agronomic management and indicates key traits required for yield stability in such environments.

Photosynthetic limitation as a factor influencing yield in highbush blueberries (Vaccinium corymbosum) grown in a northern European environment

PubMed Central

van der Kaay, Jeroen; Chrysanthou, Elina; McCallum, Susan

2018-01-01

Abstract Published evidence indicates that nearly 60% of blueberry-producing countries experience yield instability. Yield is a complex trait determined by genetic and environmental factors. Here, using physiological and biochemical approaches, we tested the hypothesis that yield instability results from year-to-year environmental variation that limits carbon assimilation, storage and partitioning. The data indicate that fruit development depends primarily on the daily production of non-structural carbohydrates by leaves, and there is no accumulation of a starch buffer to allow continuous ripening under conditions limiting for photosynthesis. Photosynthesis was saturated at moderate light irradiance and this was mainly due to stomatal and biochemical limitations. In a dynamic light environment, photosynthesis was further limited by slow stomatal response to increasing light. Finally, labelling with 13CO2 at specific stages of fruit development revealed a relatively even distribution of newly assimilated carbon between stems, roots and fruits, suggesting that the fruit is not a strong sink. We conclude that a significant component of yield variability results from limitations in photosynthetic efficiency that are compounded by an inability to accumulate starch reserves in blueberry storage tissues in a typical northern European environment. This work informs techniques for improving agronomic management and indicates key traits required for yield stability in such environments. PMID:29590429

Queries for Bias Testing

NASA Technical Reports Server (NTRS)

Gordon, Diana F.

1992-01-01

Selecting a good bias prior to concept learning can be difficult. Therefore, dynamic bias adjustment is becoming increasingly popular. Current dynamic bias adjustment systems, however, are limited in their ability to identify erroneous assumptions about the relationship between the bias and the target concept. Without proper diagnosis, it is difficult to identify and then remedy faulty assumptions. We have developed an approach that makes these assumptions explicit, actively tests them with queries to an oracle, and adjusts the bias based on the test results.

On cyclic yield strength in definition of limits for characterisation of fatigue and creep behaviour

NASA Astrophysics Data System (ADS)

Gorash, Yevgen; MacKenzie, Donald

2017-06-01

This study proposes cyclic yield strength as a potential characteristic of safe design for structures operating under fatigue and creep conditions. Cyclic yield strength is defined on a cyclic stress-strain curve, while monotonic yield strength is defined on a monotonic curve. Both values of strengths are identified using a two-step procedure of the experimental stress-strain curves fitting with application of Ramberg-Osgood and Chaboche material models. A typical S-N curve in stress-life approach for fatigue analysis has a distinctive minimum stress lower bound, the fatigue endurance limit. Comparison of cyclic strength and fatigue limit reveals that they are approximately equal. Thus, safe fatigue design is guaranteed in the purely elastic domain defined by the cyclic yielding. A typical long-term strength curve in time-to-failure approach for creep analysis has two inflections corresponding to the cyclic and monotonic strengths. These inflections separate three domains on the long-term strength curve, which are characterised by different creep fracture modes and creep deformation mechanisms. Therefore, safe creep design is guaranteed in the linear creep domain with brittle failure mode defined by the cyclic yielding. These assumptions are confirmed using three structural steels for normal and high-temperature applications. The advantage of using cyclic yield strength for characterisation of fatigue and creep strength is a relatively quick experimental identification. The total duration of cyclic tests for a cyclic stress-strain curve identification is much less than the typical durations of fatigue and creep rupture tests at the stress levels around the cyclic yield strength.

A systematic review and meta-analysis of cognitive bias to food stimuli in people with disordered eating behaviour.

PubMed

Brooks, Samantha; Prince, Alexis; Stahl, Daniel; Campbell, Iain C; Treasure, Janet

2011-02-01

Maladaptive cognitions about food, weight and shape bias attention, memory and judgment and may be linked to disordered eating behaviour. This paper reviews information processing of food stimuli (words, pictures) in people with eating disorders (ED). PubMed, Ovid, ScienceDirect, PsychInfo, Web of Science, Cochrane Library and Google Scholar were searched to December 2009. 63 studies measured attention, memory and judgment bias towards food stimuli in women with ED. Stroop tasks had sufficient sample size for a meta-analyses and effects ranged from small to medium. Other studies of attention bias had variable effects (e.g. the Dot-Probe task, distracter tasks and Startle Eyeblink Modulation). A meta-analysis of memory bias studies in ED and RE yielded insignificant effect. Effect sizes for judgment bias ranged from negligible to large. People with ED have greater attentional bias to food stimuli than healthy controls (HC). Evidence for a memory and judgment bias in ED is limited. Copyright © 2010 Elsevier Ltd. All rights reserved.

Exploring the common molecular basis for the universal DNA mutation bias: Revival of Loewdin mutation model

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

Fu, Liang-Yu; Center for Bioinformatics, Huazhong Agricultural University, Wuhan 430070; Wang, Guang-Zhong

2011-06-10

Highlights: {yields} There exists a universal G:C {yields} A:T mutation bias in three domains of life. {yields} This universal mutation bias has not been sufficiently explained. {yields} A DNA mutation model proposed by Loewdin 40 years ago offers a common explanation. -- Abstract: Recently, numerous genome analyses revealed the existence of a universal G:C {yields} A:T mutation bias in bacteria, fungi, plants and animals. To explore the molecular basis for this mutation bias, we examined the three well-known DNA mutation models, i.e., oxidative damage model, UV-radiation damage model and CpG hypermutation model. It was revealed that these models cannot providemore » a sufficient explanation to the universal mutation bias. Therefore, we resorted to a DNA mutation model proposed by Loewdin 40 years ago, which was based on inter-base double proton transfers (DPT). Since DPT is a fundamental and spontaneous chemical process and occurs much more frequently within GC pairs than AT pairs, Loewdin model offers a common explanation for the observed universal mutation bias and thus has broad biological implications.« less

[Biases in the study of prognostic factors].

PubMed

Delgado-Rodríguez, M

1999-01-01

The main objective is to detail the main biases in the study of prognostic factors. Confounding bias is illustrated with social class, a prognostic factor still discussed. Within selection bias several cases are commented: response bias, specially frequent when the patients of a clinical trial are used; the shortcomings in the formation of an inception cohort; the fallacy of Neyman (bias due to the duration of disease) when the study begins with a cross-sectional study; the selection bias in the treatment of survivors for the different treatment opportunity of those living longer; the bias due to the inclusion of heterogeneous diagnostic groups; and the selection bias due to differential information losses and the use of statistical multivariate procedures. Within the biases during follow-up, an empiric rule to value the impact of the number of losses is given. In information bias the Will Rogers' phenomenon and the usefulness of clinical databases are discussed. Lastly, a recommendation against the use of cutoff points yielded by bivariate analyses to select the variable to be included in multivariate analysis is given.

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.

Toward a synthesis of cognitive biases: how noisy information processing can bias human decision making.

PubMed

Hilbert, Martin

2012-03-01

A single coherent framework is proposed to synthesize long-standing research on 8 seemingly unrelated cognitive decision-making biases. During the past 6 decades, hundreds of empirical studies have resulted in a variety of rules of thumb that specify how humans systematically deviate from what is normatively expected from their decisions. Several complementary generative mechanisms have been proposed to explain those cognitive biases. Here it is suggested that (at least) 8 of these empirically detected decision-making biases can be produced by simply assuming noisy deviations in the memory-based information processes that convert objective evidence (observations) into subjective estimates (decisions). An integrative framework is presented to show how similar noise-based mechanisms can lead to conservatism, the Bayesian likelihood bias, illusory correlations, biased self-other placement, subadditivity, exaggerated expectation, the confidence bias, and the hard-easy effect. Analytical tools from information theory are used to explore the nature and limitations that characterize such information processes for binary and multiary decision-making exercises. The ensuing synthesis offers formal mathematical definitions of the biases and their underlying generative mechanism, which permits a consolidated analysis of how they are related. This synthesis contributes to the larger goal of creating a coherent picture that explains the relations among the myriad of seemingly unrelated biases and their potential psychological generative mechanisms. Limitations and research questions are discussed.

Upper Limits for Power Yield in Thermal, Chemical, and Electrochemical Systems

NASA Astrophysics Data System (ADS)

Sieniutycz, Stanislaw

2010-03-01

We consider modeling and power optimization of energy converters, such as thermal, solar and chemical engines and fuel cells. Thermodynamic principles lead to expressions for converter's efficiency and generated power. Efficiency equations serve to solve the problems of upgrading or downgrading a resource. Power yield is a cumulative effect in a system consisting of a resource, engines, and an infinite bath. While optimization of steady state systems requires using the differential calculus and Lagrange multipliers, dynamic optimization involves variational calculus and dynamic programming. The primary result of static optimization is the upper limit of power, whereas that of dynamic optimization is a finite-rate counterpart of classical reversible work (exergy). The latter quantity depends on the end state coordinates and a dissipation index, h, which is the Hamiltonian of the problem of minimum entropy production. In reacting systems, an active part of chemical affinity constitutes a major component of the overall efficiency. The theory is also applied to fuel cells regarded as electrochemical flow engines. Enhanced bounds on power yield follow, which are stronger than those predicted by the reversible work potential.

Limitations in cooling electrons using normal-metal-superconductor tunnel junctions.

PubMed

Pekola, J P; Heikkilä, T T; Savin, A M; Flyktman, J T; Giazotto, F; Hekking, F W J

2004-02-06

We demonstrate both theoretically and experimentally two limiting factors in cooling electrons using biased tunnel junctions to extract heat from a normal metal into a superconductor. First, when the injection rate of electrons exceeds the internal relaxation rate in the metal to be cooled, the electrons do not obey the Fermi-Dirac distribution, and the concept of temperature cannot be applied as such. Second, at low bath temperatures, states within the gap induce anomalous heating and yield a theoretical limit of the achievable minimum temperature.

Ecohydrology of agroecosystems: probabilistic description of yield reduction risk under limited water availability

NASA Astrophysics Data System (ADS)

Vico, Giulia; Porporato, Amilcare

2013-04-01

Supplemental irrigation represents one of the main strategies to mitigate the effects of climate variability and stabilize yields. Irrigated agriculture currently provides 40% of food production and its relevance is expected to further increase in the near future, in face of the projected alterations of rainfall patterns and increase in food, fiber, and biofuel demand. Because of the significant investments and water requirements involved in irrigation, strategic choices are needed to preserve productivity and profitability, while maintaining a sustainable water management - a nontrivial task given the unpredictability of the rainfall forcing. To facilitate decision making under uncertainty, a widely applicable probabilistic framework is proposed. The occurrence of rainfall events and irrigation applications are linked probabilistically to crop development during the growing season and yields at harvest. Based on these linkages, the probability density function of yields and corresponding probability density function of required irrigation volumes, as well as the probability density function of yields under the most common case of limited water availability are obtained analytically, as a function of irrigation strategy, climate, soil and crop parameters. The full probabilistic description of the frequency of occurrence of yields and water requirements is a crucial tool for decision making under uncertainty, e.g., via expected utility analysis. Furthermore, the knowledge of the probability density function of yield allows us to quantify the yield reduction hydrologic risk. Two risk indices are defined and quantified: the long-term risk index, suitable for long-term irrigation strategy assessment and investment planning, and the real-time risk index, providing a rigorous probabilistic quantification of the emergence of drought conditions during a single growing season in an agricultural setting. Our approach employs relatively few parameters and is thus easily and

Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5

NASA Astrophysics Data System (ADS)

Ogura, Tomoo; Shiogama, Hideo; Watanabe, Masahiro; Yoshimori, Masakazu; Yokohata, Tokuta; Annan, James D.; Hargreaves, Julia C.; Ushigami, Naoto; Hirota, Kazuya; Someya, Yu; Kamae, Youichi; Tatebe, Hiroaki; Kimoto, Masahide

2017-12-01

This study discusses how much of the biases in top-of-atmosphere (TOA) radiation and clouds can be removed by parameter tuning in the present-day simulation of a climate model in the Coupled Model Inter-comparison Project phase 5 (CMIP5) generation. We used output of a perturbed parameter ensemble (PPE) experiment conducted with an atmosphere-ocean general circulation model (AOGCM) without flux adjustment. The Model for Interdisciplinary Research on Climate version 5 (MIROC5) was used for the PPE experiment. Output of the PPE was compared with satellite observation data to evaluate the model biases and the parametric uncertainty of the biases with respect to TOA radiation and clouds. The results indicate that removing or changing the sign of the biases by parameter tuning alone is difficult. In particular, the cooling bias of the shortwave cloud radiative effect at low latitudes could not be removed, neither in the zonal mean nor at each latitude-longitude grid point. The bias was related to the overestimation of both cloud amount and cloud optical thickness, which could not be removed by the parameter tuning either. However, they could be alleviated by tuning parameters such as the maximum cumulus updraft velocity at the cloud base. On the other hand, the bias of the shortwave cloud radiative effect in the Arctic was sensitive to parameter tuning. It could be removed by tuning such parameters as albedo of ice and snow both in the zonal mean and at each grid point. The obtained results illustrate the benefit of PPE experiments which provide useful information regarding effectiveness and limitations of parameter tuning. Implementing a shallow convection parameterization is suggested as a potential measure to alleviate the biases in radiation and clouds.

Ranking Bias in Association Studies

PubMed Central

Jeffries, Neal O.

2009-01-01

Background It is widely appreciated that genomewide association studies often yield overestimates of the association of a marker with disease when attention focuses upon the marker showing the strongest relationship. For example, in a case-control setting the largest (in absolute value) estimated odds ratio has been found to typically overstate the association as measured in a second, independent set of data. The most common reason given for this observation is that the choice of the most extreme test statistic is often conditional upon first observing a significant p value associated with the marker. A second, less appreciated reason is described here. Under common circumstances it is the multiple testing of many markers and subsequent focus upon those with most extreme test statistics (i.e. highly ranked results) that leads to bias in the estimated effect sizes. Conclusions This bias, termed ranking bias, is separate from that arising from conditioning on a significant p value and may often be a more important factor in generating bias. An analytic description of this bias, simulations demonstrating its extent, and identification of some factors leading to its exacerbation are presented. PMID:19172085

Bias analysis applied to Agricultural Health Study publications to estimate non-random sources of uncertainty.

PubMed

Lash, Timothy L

2007-11-26

The associations of pesticide exposure with disease outcomes are estimated without the benefit of a randomized design. For this reason and others, these studies are susceptible to systematic errors. I analyzed studies of the associations between alachlor and glyphosate exposure and cancer incidence, both derived from the Agricultural Health Study cohort, to quantify the bias and uncertainty potentially attributable to systematic error. For each study, I identified the prominent result and important sources of systematic error that might affect it. I assigned probability distributions to the bias parameters that allow quantification of the bias, drew a value at random from each assigned distribution, and calculated the estimate of effect adjusted for the biases. By repeating the draw and adjustment process over multiple iterations, I generated a frequency distribution of adjusted results, from which I obtained a point estimate and simulation interval. These methods were applied without access to the primary record-level dataset. The conventional estimates of effect associating alachlor and glyphosate exposure with cancer incidence were likely biased away from the null and understated the uncertainty by quantifying only random error. For example, the conventional p-value for a test of trend in the alachlor study equaled 0.02, whereas fewer than 20% of the bias analysis iterations yielded a p-value of 0.02 or lower. Similarly, the conventional fully-adjusted result associating glyphosate exposure with multiple myleoma equaled 2.6 with 95% confidence interval of 0.7 to 9.4. The frequency distribution generated by the bias analysis yielded a median hazard ratio equal to 1.5 with 95% simulation interval of 0.4 to 8.9, which was 66% wider than the conventional interval. Bias analysis provides a more complete picture of true uncertainty than conventional frequentist statistical analysis accompanied by a qualitative description of study limitations. The latter approach is

Influence of analytical bias and imprecision on the number of false positive results using Guideline-Driven Medical Decision Limits.

PubMed

Hyltoft Petersen, Per; Klee, George G

2014-03-20

Diagnostic decisions based on decision limits according to medical guidelines are different from the majority of clinical decisions due to the strict dichotomization of patients into diseased and non-diseased. Consequently, the influence of analytical performance is more critical than for other diagnostic decisions where much other information is included. The aim of this opinion paper is to investigate consequences of analytical quality and other circumstances for the outcome of "Guideline-Driven Medical Decision Limits". Effects of analytical bias and imprecision should be investigated separately and analytical quality specifications should be estimated accordingly. Use of sharp decision limits doesn't consider biological variation and effects of this variation are closely connected with the effects of analytical performance. Such relationships are investigated for the guidelines for HbA1c in diagnosis of diabetes and in risk of coronary heart disease based on serum cholesterol. The effects of a second sampling in diagnosis give dramatic reduction in the effects of analytical quality showing minimal influence of imprecision up to 3 to 5% for two independent samplings, whereas the reduction in bias is more moderate and a 2% increase in concentration doubles the percentage of false positive diagnoses, both for HbA1c and cholesterol. An alternative approach comes from the current application of guidelines for follow-up laboratory tests according to clinical procedure orders, e.g. frequency of parathyroid hormone requests as a function of serum calcium concentrations. Here, the specifications for bias can be evaluated from the functional increase in requests for increasing serum calcium concentrations. In consequence of the difficulties with biological variation and the practical utilization of concentration dependence of frequency of follow-up laboratory tests already in use, a kind of probability function for diagnosis as function of the key-analyte is proposed

Cognitive biases can affect moral intuitions about cognitive enhancement

PubMed Central

Caviola, Lucius; Mannino, Adriano; Savulescu, Julian; Faulmüller, Nadira

2014-01-01

Research into cognitive biases that impair human judgment has mostly been applied to the area of economic decision-making. Ethical decision-making has been comparatively neglected. Since ethical decisions often involve very high individual as well as collective stakes, analyzing how cognitive biases affect them can be expected to yield important results. In this theoretical article, we consider the ethical debate about cognitive enhancement (CE) and suggest a number of cognitive biases that are likely to affect moral intuitions and judgments about CE: status quo bias, loss aversion, risk aversion, omission bias, scope insensitivity, nature bias, and optimistic bias. We find that there are more well-documented biases that are likely to cause irrational aversion to CE than biases in the opposite direction. This suggests that common attitudes about CE are predominantly negatively biased. Within this new perspective, we hope that subsequent research will be able to elaborate this hypothesis and develop effective de-biasing techniques that can help increase the rationality of the public CE debate and thus improve our ethical decision-making. PMID:25360088

Sample-averaged biexciton quantum yield measured by solution-phase photon correlation.

PubMed

Beyler, Andrew P; Bischof, Thomas S; Cui, Jian; Coropceanu, Igor; Harris, Daniel K; Bawendi, Moungi G

2014-12-10

The brightness of nanoscale optical materials such as semiconductor nanocrystals is currently limited in high excitation flux applications by inefficient multiexciton fluorescence. We have devised a solution-phase photon correlation measurement that can conveniently and reliably measure the average biexciton-to-exciton quantum yield ratio of an entire sample without user selection bias. This technique can be used to investigate the multiexciton recombination dynamics of a broad scope of synthetically underdeveloped materials, including those with low exciton quantum yields and poor fluorescence stability. Here, we have applied this method to measure weak biexciton fluorescence in samples of visible-emitting InP/ZnS and InAs/ZnS core/shell nanocrystals, and to demonstrate that a rapid CdS shell growth procedure can markedly increase the biexciton fluorescence of CdSe nanocrystals.

Sample-Averaged Biexciton Quantum Yield Measured by Solution-Phase Photon Correlation

PubMed Central

Beyler, Andrew P.; Bischof, Thomas S.; Cui, Jian; Coropceanu, Igor; Harris, Daniel K.; Bawendi, Moungi G.

2015-01-01

The brightness of nanoscale optical materials such as semiconductor nanocrystals is currently limited in high excitation flux applications by inefficient multiexciton fluorescence. We have devised a solution-phase photon correlation measurement that can conveniently and reliably measure the average biexciton-to-exciton quantum yield ratio of an entire sample without user selection bias. This technique can be used to investigate the multiexciton recombination dynamics of a broad scope of synthetically underdeveloped materials, including those with low exciton quantum yields and poor fluorescence stability. Here, we have applied this method to measure weak biexciton fluorescence in samples of visible-emitting InP/ZnS and InAs/ZnS core/shell nanocrystals, and to demonstrate that a rapid CdS shell growth procedure can markedly increase the biexciton fluorescence of CdSe nanocrystals. PMID:25409496

Is racial bias malleable? Whites' lay theories of racial bias predict divergent strategies for interracial interactions.

PubMed

Neel, Rebecca; Shapiro, Jenessa R

2012-07-01

How do Whites approach interracial interactions? We argue that a previously unexamined factor-beliefs about the malleability of racial bias-guides Whites' strategies for difficult interracial interactions. We predicted and found that those who believe racial bias is malleable favor learning-oriented strategies such as taking the other person's perspective and trying to learn why an interaction is challenging, whereas those who believe racial bias is fixed favor performance-oriented strategies such as overcompensating in the interaction and trying to end the interaction as quickly as possible. Four studies support these predictions. Whether measured (Studies 1, 3, and 4) or manipulated (Study 2), beliefs that racial bias is fixed versus malleable yielded these divergent strategies for difficult interracial interactions. Furthermore, beliefs about the malleability of racial bias are distinct from related constructs (e.g., prejudice and motivations to respond without prejudice; Studies 1, 3, and 4) and influence self-reported (Studies 1-3) and actual (Study 4) strategies in imagined (Studies 1-2) and real (Studies 3-4) interracial interactions. Together, these findings demonstrate that beliefs about the malleability of racial bias influence Whites' approaches to and strategies within interracial interactions. PsycINFO Database Record (c) 2012 APA, all rights reserved

Limited mobility of target pests crucially lowers controllability when sterile insect releases are spatiotemporally biased.

PubMed

Ikegawa, Yusuke; Himuro, Chihiro

2017-05-21

The sterile insect technique (SIT) is a genetic pest control method wherein mass-reared sterile insects are periodically released into the wild, thereby impeding the successful reproduction of fertile pests. In Okinawa Prefecture, Japan, the SIT has been implemented to eradicate the West Indian sweet potato weevil Euscepes postfasciatus (Fairmaire), which is a flightless agricultural pest of sweet potatoes. It is known that E. postfasciatus is much less mobile than other insects to which the SIT has been applied. However, previous theoretical studies have rarely examined effects of low mobility of target pests and variation in the spatiotemporal evenness of sterile insect releases. To theoretically examine the effects of spatiotemporal evenness on the regional eradication of less mobile pests, we constructed a simple two-patch population model comprised of a pest and sterile insect moving between two habitats, and numerically simulated different release strategies (varying the number of released sterile insects and release intervals). We found that spatially biased releases allowed the pest to spatially escape from the sterile insect, and thus intensively lowered its controllability. However, we showed that the temporally counterbalancing spatially biased releases by swapping the number of released insects in the two habitats at every release (called temporal balancing) could greatly mitigate this negative effect and promote the controllability. We also showed that the negative effect of spatiotemporally biased releases was a result of the limited mobility of the target insect. Although directed dispersal of the insects in response to habitats of differing quality could lower the controllability in the more productive habitat, the temporal balancing could promote and eventually maximize the controllability as released insects increased. Copyright © 2017 Elsevier Ltd. All rights reserved.

Impact of derived global weather data on simulated crop yields

PubMed Central

van Wart, Justin; Grassini, Patricio; Cassman, Kenneth G

2013-01-01

Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26–72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12–19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method. PMID:23801639

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…

Sample-Averaged Biexciton Quantum Yield Measured by Solution-Phase Photon Correlation

DOE PAGES

Beyler, Andrew P.; Bischof, Thomas S.; Cui, Jian; ...

2014-11-19

The brightness of nanoscale optical materials such as semiconductor nanocrystals is currently limited in high excitation flux applications by inefficient multiexciton fluorescence. We have devised a solution-phase photon correlation measurement that can conveniently and reliably measure the average biexciton-to-exciton quantum yield ratio of an entire sample without user selection bias. This technique can be used to investigate the multiexciton recombination dynamics of a broad scope of synthetically underdeveloped materials, including those with low exciton quantum yields and poor fluorescence stability. Here in this study, we have applied this method to measure weak biexciton fluorescence in samples of visible-emitting InP/ZnS andmore » InAs/ZnS core/shell nanocrystals, and to demonstrate that a rapid CdS shell growth procedure can markedly increase the biexciton fluorescence of CdSe nanocrystals.« less

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.

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.

Surprisingly rational: probability theory plus noise explains biases in judgment.

PubMed

Costello, Fintan; Watts, Paul

2014-07-01

The systematic biases seen in people's probability judgments are typically taken as evidence that people do not use the rules of probability theory when reasoning about probability but instead use heuristics, which sometimes yield reasonable judgments and sometimes yield systematic biases. This view has had a major impact in economics, law, medicine, and other fields; indeed, the idea that people cannot reason with probabilities has become a truism. We present a simple alternative to this view, where people reason about probability according to probability theory but are subject to random variation or noise in the reasoning process. In this account the effect of noise is canceled for some probabilistic expressions. Analyzing data from 2 experiments, we find that, for these expressions, people's probability judgments are strikingly close to those required by probability theory. For other expressions, this account produces systematic deviations in probability estimates. These deviations explain 4 reliable biases in human probabilistic reasoning (conservatism, subadditivity, conjunction, and disjunction fallacies). These results suggest that people's probability judgments embody the rules of probability theory and that biases in those judgments are due to the effects of random noise. (c) 2014 APA, all rights reserved.

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

Why all randomised controlled trials produce biased results.

PubMed

Krauss, Alexander

2018-06-01

Randomised controlled trials (RCTs) are commonly viewed as the best research method to inform public health and social policy. Usually they are thought of as providing the most rigorous evidence of a treatment's effectiveness without strong assumptions, biases and limitations. This is the first study to examine that hypothesis by assessing the 10 most cited RCT studies worldwide. These 10 RCT studies with the highest number of citations in any journal (up to June 2016) were identified by searching Scopus (the largest database of peer-reviewed journals). This study shows that these world-leading RCTs that have influenced policy produce biased results by illustrating that participants' background traits that affect outcomes are often poorly distributed between trial groups, that the trials often neglect alternative factors contributing to their main reported outcome and, among many other issues, that the trials are often only partially blinded or unblinded. The study here also identifies a number of novel and important assumptions, biases and limitations not yet thoroughly discussed in existing studies that arise when designing, implementing and analysing trials. Researchers and policymakers need to become better aware of the broader set of assumptions, biases and limitations in trials. Journals need to also begin requiring researchers to outline them in their studies. We need to furthermore better use RCTs together with other research methods. Key messages RCTs face a range of strong assumptions, biases and limitations that have not yet all been thoroughly discussed in the literature. This study assesses the 10 most cited RCTs worldwide and shows that trials inevitably produce bias. Trials involve complex processes - from randomising, blinding and controlling, to implementing treatments, monitoring participants etc. - that require many decisions and steps at different levels that bring their own assumptions and degree of bias to results.

Selection bias in rheumatic disease research.

PubMed

Choi, Hyon K; Nguyen, Uyen-Sa; Niu, Jingbo; Danaei, Goodarz; Zhang, Yuqing

2014-07-01

The identification of modifiable risk factors for the development of rheumatic conditions and their sequelae is crucial for reducing the substantial worldwide burden of these diseases. However, the validity of such research can be threatened by sources of bias, including confounding, measurement and selection biases. In this Review, we discuss potentially major issues of selection bias--a type of bias frequently overshadowed by other bias and feasibility issues, despite being equally or more problematic--in key areas of rheumatic disease research. We present index event bias (a type of selection bias) as one of the potentially unifying reasons behind some unexpected findings, such as the 'risk factor paradox'--a phenomenon exemplified by the discrepant effects of certain risk factors on the development versus the progression of osteoarthritis (OA) or rheumatoid arthritis (RA). We also discuss potential selection biases owing to differential loss to follow-up in RA and OA research, as well as those due to the depletion of susceptibles (prevalent user bias) and immortal time bias. The lesson remains that selection bias can be ubiquitous and, therefore, has the potential to lead the field astray. Thus, we conclude with suggestions to help investigators avoid such issues and limit the impact on future rheumatology research.

Describing Perceived Racial Bias Among Youth With Sickle Cell Disease.

PubMed

Wakefield, Emily O; Pantaleao, Ashley; Popp, Jill M; Dale, Lourdes P; Santanelli, James P; Litt, Mark D; Zempsky, William T

2018-03-17

Sickle cell disease (SCD) predominately affects Black Americans. This is the first study of its kind to describe the racial bias experiences of youth with SCD and their reactions to these experiences. Participants were 20 youth with SCD (ages 13-21 years) who were asked to describe any racial bias events they experienced, as recorded on the Perception of Racism in Children and Youth measure (PRaCY). Interviews were recorded, transcribed, and analyzed by two independent raters using a conventional content analysis approach. All participants reported at least one incident of racial bias. Content analysis of racial bias events (n = 104) yielded 4 categories and 12 subcategories as follows: Perpetrator (Peers, Authority Figures, and General Public), Type of Racial Bias (Explicit, Implicit), Behavioral Reaction (Approach, Avoidant), and Emotional Response (Dysphoria, Anger, Unconcerned, Inferior, Anxious). This study provides a description of racial bias experiences within community and medical settings and highlights the need for further evaluation of the impact of racial bias among youth with SCD.

Yields of Soviet underground nuclear explosions from seismic surface waves: Compliance with the Threshold Test Ban Treaty

PubMed Central

Sykes, Lynn R.; Cifuentes, Inés L.

1984-01-01

Magnitudes of the larger Soviet underground nuclear weapons tests from the start of the Threshold Test Ban Treaty in 1976 through 1982 are determined for short- and long-period seismic waves. Yields are calculated from the surface wave magnitude for those explosions at the eastern Kazakh test site that triggered a small-to-negligible component of tectonic stress and are used to calibrate body wave magnitude-yield relationship that can be used to determine the sizes of other explosions at that test site. The results confirm that a large bias, related to differential attenuation of P waves, exists between Nevada and Central Asia. The yields of the seven largest Soviet explosions are nearly identical and are close to 150 kilotons, the limit set by the Threshold Treaty. PMID:16593440

Reprint of "Influence of analytical bias and imprecision on the number of false positive results using Guideline-Driven Medical Decision Limits".

PubMed

Hyltoft Petersen, Per; Klee, George G

2014-05-15

Diagnostic decisions based on decision limits according to medical guidelines are different from the majority of clinical decisions due to the strict dichotomization of patients into diseased and non-diseased. Consequently, the influence of analytical performance is more critical than for other diagnostic decisions where much other information is included. The aim of this opinion paper is to investigate consequences of analytical quality and other circumstances for the outcome of "Guideline-Driven Medical Decision Limits". Effects of analytical bias and imprecision should be investigated separately and analytical quality specifications should be estimated accordingly. Use of sharp decision limits doesn't consider biological variation and effects of this variation are closely connected with the effects of analytical performance. Such relationships are investigated for the guidelines for HbA1c in diagnosis of diabetes and in risk of coronary heart disease based on serum cholesterol. The effects of a second sampling in diagnosis give dramatic reduction in the effects of analytical quality showing minimal influence of imprecision up to 3 to 5% for two independent samplings, whereas the reduction in bias is more moderate and a 2% increase in concentration doubles the percentage of false positive diagnoses, both for HbA1c and cholesterol. An alternative approach comes from the current application of guidelines for follow-up laboratory tests according to clinical procedure orders, e.g. frequency of parathyroid hormone requests as a function of serum calcium concentrations. Here, the specifications for bias can be evaluated from the functional increase in requests for increasing serum calcium concentrations. In consequence of the difficulties with biological variation and the practical utilization of concentration dependence of frequency of follow-up laboratory tests already in use, a kind of probability function for diagnosis as function of the key-analyte is proposed

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.

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

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

Selection bias in rheumatic disease research

PubMed Central

Choi, Hyon K.; Nguyen, Uyen-Sa; Niu, Jingbo; Danaei, Goodarz; Zhang, Yuqing

2014-01-01

The identification of modifiable risk factors for the development of rheumatic conditions and their sequelae is crucial for reducing the substantial worldwide burden of these diseases. However, the validity of such research can be threatened by sources of bias, including confounding, measurement and selection biases. In this Review, we discuss potentially major issues of selection bias—a type of bias frequently overshadowed by other bias and feasibility issues, despite being equally or more problematic—in key areas of rheumatic disease research. We present index event bias (a type of selection bias) as one of the potentially unifying reasons behind some unexpected findings, such as the ‘risk factor paradox’—a phenomenon exemplified by the discrepant effects of certain risk factors on the development versus the progression of osteoarthritis (OA) or rheumatoid arthritis (RA). We also discuss potential selection biases owing to differential loss to follow-up in RA and OA research, as well as those due to the depletion of susceptibles (prevalent user bias) and immortal time bias. The lesson remains that selection bias can be ubiquitous and, therefore, has the potential to lead the field astray. Thus, we conclude with suggestions to help investigators avoid such issues and limit the impact on future rheumatology research. PMID:24686510

Electric-Field Instrument With Ac-Biased Corona Point

NASA Technical Reports Server (NTRS)

Markson, R.; Anderson, B.; Govaert, J.

1993-01-01

Measurements indicative of incipient lightning yield additional information. New instrument gives reliable readings. High-voltage ac bias applied to needle point through high-resistance capacitance network provides corona discharge at all times, enabling more-slowly-varying component of electrostatic potential of needle to come to equilibrium with surrounding air. High resistance of high-voltage coupling makes instrument insensitive to wind. Improved corona-point instrument expected to yield additional information assisting in safety-oriented forecasting of lighting.

Symmetry as Bias: Rediscovering Special Relativity

NASA Technical Reports Server (NTRS)

Lowry, Michael R.

1992-01-01

This paper describes a rational reconstruction of Einstein's discovery of special relativity, validated through an implementation: the Erlanger program. Einstein's discovery of special relativity revolutionized both the content of physics and the research strategy used by theoretical physicists. This research strategy entails a mutual bootstrapping process between a hypothesis space for biases, defined through different postulated symmetries of the universe, and a hypothesis space for physical theories. The invariance principle mutually constrains these two spaces. The invariance principle enables detecting when an evolving physical theory becomes inconsistent with its bias, and also when the biases for theories describing different phenomena are inconsistent. Structural properties of the invariance principle facilitate generating a new bias when an inconsistency is detected. After a new bias is generated. this principle facilitates reformulating the old, inconsistent theory by treating the latter as a limiting approximation. The structural properties of the invariance principle can be suitably generalized to other types of biases to enable primal-dual learning.

Biased ligand quantification in drug discovery: from theory to high throughput screening to identify new biased μ opioid receptor agonists

PubMed Central

Winpenny, David; Clark, Mellissa

2016-01-01

Background and Purpose Biased GPCR ligands are able to engage with their target receptor in a manner that preferentially activates distinct downstream signalling and offers potential for next generation therapeutics. However, accurate quantification of ligand bias in vitro is complex, and current best practice is not amenable for testing large numbers of compound. We have therefore sought to apply ligand bias theory to an industrial scale screening campaign for the identification of new biased μ receptor agonists. Experimental Approach μ receptor assays with appropriate dynamic range were developed for both Gαi‐dependent signalling and β‐arrestin2 recruitment. Δlog(Emax/EC50) analysis was validated as an alternative for the operational model of agonism in calculating pathway bias towards Gαi‐dependent signalling. The analysis was applied to a high throughput screen to characterize the prevalence and nature of pathway bias among a diverse set of compounds with μ receptor agonist activity. Key Results A high throughput screening campaign yielded 440 hits with greater than 10‐fold bias relative to DAMGO. To validate these results, we quantified pathway bias of a subset of hits using the operational model of agonism. The high degree of correlation across these biased hits confirmed that Δlog(Emax/EC50) was a suitable method for identifying genuine biased ligands within a large collection of diverse compounds. Conclusions and Implications This work demonstrates that using Δlog(Emax/EC50), drug discovery can apply the concept of biased ligand quantification on a large scale and accelerate the deliberate discovery of novel therapeutics acting via this complex pharmacology. PMID:26791140

Bias atlases for segmentation-based PET attenuation correction using PET-CT and MR.

PubMed

Ouyang, Jinsong; Chun, Se Young; Petibon, Yoann; Bonab, Ali A; Alpert, Nathaniel; Fakhri, Georges El

2013-10-01

This study was to obtain voxel-wise PET accuracy and precision using tissue-segmentation for attenuation correction. We applied multiple thresholds to the CTs of 23 patients to classify tissues. For six of the 23 patients, MR images were also acquired. The MR fat/in-phase ratio images were used for fat segmentation. Segmented tissue classes were used to create attenuation maps, which were used for attenuation correction in PET reconstruction. PET bias images were then computed using the PET reconstructed with the original CT as the reference. We registered the CTs for all the patients and transformed the corresponding bias images accordingly. We then obtained the mean and standard deviation bias atlas using all the registered bias images. Our CT-based study shows that four-class segmentation (air, lungs, fat, other tissues), which is available on most PET-MR scanners, yields 15.1%, 4.1%, 6.6%, and 12.9% RMSE bias in lungs, fat, non-fat soft-tissues, and bones, respectively. An accurate fat identification is achievable using fat/in-phase MR images. Furthermore, we have found that three-class segmentation (air, lungs, other tissues) yields less than 5% standard deviation of bias within the heart, liver, and kidneys. This implies that three-class segmentation can be sufficient to achieve small variation of bias for imaging these three organs. Finally, we have found that inter- and intra-patient lung density variations contribute almost equally to the overall standard deviation of bias within the lungs.

Impact of derived global weather data on simulated crop yields.

PubMed

van Wart, Justin; Grassini, Patricio; Cassman, Kenneth G

2013-12-01

Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26-72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12-19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method. © 2013 John Wiley & Sons Ltd.

What drives social in-group biases in face recognition memory? ERP evidence from the own-gender bias

PubMed Central

Kemter, Kathleen; Schweinberger, Stefan R.; Wiese, Holger

2014-01-01

It is well established that memory is more accurate for own-relative to other-race faces (own-race bias), which has been suggested to result from larger perceptual expertise for own-race faces. Previous studies also demonstrated better memory for own-relative to other-gender faces, which is less likely to result from differences in perceptual expertise, and rather may be related to social in-group vs out-group categorization. We examined neural correlates of the own-gender bias using event-related potentials (ERP). In a recognition memory experiment, both female and male participants remembered faces of their respective own gender more accurately compared with other-gender faces. ERPs during learning yielded significant differences between the subsequent memory effects (subsequently remembered – subsequently forgotten) for own-gender compared with other-gender faces in the occipito-temporal P2 and the central N200, whereas neither later subsequent memory effects nor ERP old/new effects at test reflected a neural correlate of the own-gender bias. We conclude that the own-gender bias is mainly related to study phase processes, which is in line with sociocognitive accounts. PMID:23474824

Interactions of soil conditioner with other limiting factors to achieve high crop yields. [Lycopersicon esculentum

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

Wallace, A.; Abouzamzam, A.M.

Tomato (Lycopersicon esculentum Mill. cv. Tropic) was used as a test plant in evaluating the interactions for simultaneously correcting deficiencies of N and P and improving physical properties of soil with a soil conditioner. The three limiting factors were improved singly and in all possible combinations. There was response to each input. The least response to the soil conditioner was with N and P, and the most response was when N and P were also used. The combined effect appeared to be synergistic. The results emphasize that the best crop management system involves overcoming as many limiting factors as possible.more » This is the key to high-yield agriculture.« less

Analysis of factors which limited the spatial variation of barley yield on the forest-steppe chernozems of Kursk region

NASA Astrophysics Data System (ADS)

Belik, Anton; Vasenev, Ivan; Jablonskikh, Lidia; Bozhko, Svetlana

2017-04-01

The crop yield is the most important indicator of the efficiency of agricultural production. It is the function that depends on a large number of groups of independent variables, such as the weather, soil fertility and overall culture agriculture. A huge number of combinations of these factors contribute to the formation of high spatial variety of crop yields within small areas, includes the slope agrolandscapes in Kursk region. Spatial variety of yield leads to a significant reduction in the efficiency of agriculture. In this connection, evaluation and analysis of the factors, which limits the yield of field crops is a very urgent proble in agroecology. The research was conducted in the period of 2003-2004 on a representative field. The typical and leached chernozems with the varying thickness and of erosion degree are dominated in soil cover. At the time of field research studied areas were busy by barley. The reseached soils have an average and increased fertility level. Chernozem typical full-face, and the leached contain an average of 4.5-6% humus, close to neutral pH, favorable values of physico-chemical parameters, medium and high content of nutrients. The eroded chernozems differs agrogenic marked declining in fertility parameters. The diversity of meso- and micro-relief in the fields and soil cover influence to significant spatial variety of fertility. For example the content of nutrients in the soil variation can be up to 5-fold level. High spatial heterogeneity of soils fertility ifluence to barley yield variety. During research on the productivity of the field varied in the range of 20-43 c/ha, and 7-44 c/ha (2004). Analysis of the factors, which limited the yield of barley, showed that the first priorities occupy unregulated characterises: slope angle and the classification of soils (subtype and race of chernozem and the difference in the degree of erosion), which determines the development of erosion processes and redistribution available to plants

Towards process-informed bias correction of climate change simulations

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Shepherd, Theodore G.; Widmann, Martin; Zappa, Giuseppe; Walton, Daniel; Gutiérrez, José M.; Hagemann, Stefan; Richter, Ingo; Soares, Pedro M. M.; Hall, Alex; Mearns, Linda O.

2017-11-01

Biases in climate model simulations introduce biases in subsequent impact simulations. Therefore, bias correction methods are operationally used to post-process regional climate projections. However, many problems have been identified, and some researchers question the very basis of the approach. Here we demonstrate that a typical cross-validation is unable to identify improper use of bias correction. Several examples show the limited ability of bias correction to correct and to downscale variability, and demonstrate that bias correction can cause implausible climate change signals. Bias correction cannot overcome major model errors, and naive application might result in ill-informed adaptation decisions. We conclude with a list of recommendations and suggestions for future research to reduce, post-process, and cope with climate model biases.

Attention, interpretation, and memory biases in subclinical depression: a proof-of-principle test of the combined cognitive biases hypothesis.

PubMed

Everaert, Jonas; Duyck, Wouter; Koster, Ernst H W

2014-04-01

Emotional biases in attention, interpretation, and memory are viewed as important cognitive processes underlying symptoms of depression. To date, there is a limited understanding of the interplay among these processing biases. This study tested the dependence of memory on depression-related biases in attention and interpretation. Subclinically depressed and nondepressed participants completed a computerized version of the scrambled sentences test (measuring interpretation bias) while their eye movements were recorded (measuring attention bias). This task was followed by an incidental free recall test of previously constructed interpretations (measuring memory bias). Path analysis revealed a good fit for the model in which selective orienting of attention was associated with interpretation bias, which in turn was associated with a congruent bias in memory. Also, a good fit was observed for a path model in which biases in the maintenance of attention and interpretation were associated with memory bias. Both path models attained a superior fit compared with path models without the theorized functional relations among processing biases. These findings enhance understanding of how mechanisms of attention and interpretation regulate what is remembered. As such, they offer support for the combined cognitive biases hypothesis or the notion that emotionally biased cognitive processes are not isolated mechanisms but instead influence each other. Implications for theoretical models and emotion regulation across the spectrum of depressive symptoms are discussed.

Testing the Efficacy of Attention Bias Modification for Suicidal Thoughts: Findings From Two Experiments.

PubMed

Cha, Christine B; Najmi, Sadia; Amir, Nader; Matthews, John D; Deming, Charlene A; Glenn, Jeffrey J; Calixte, Rachelle M; Harris, Julia A; Nock, Matthew K

2017-01-02

This study explores whether four sessions of attention bias modification (ABM) decreases suicide-specific attentional bias. We conducted two experiments where suicide ideators completed either a Training or Control version of ABM, a computer-based intervention intended to target attentional bias. Suicide-specific attentional bias was measured using adapted Stroop and probe discrimination tasks. The first experiment with community-based suicide ideators did not show that ABM impacts attentional bias or suicidal ideation. The second experiment with clinically severe suicidal inpatients yielded similar results. Post-hoc findings suggest that the type of attentional bias targeted by the current intervention may differ from the type that marks suicide risk. There remains little to no evidence that the ABM intervention changes suicide-specific attentional bias or suicidal ideation.

Evaluation of limited irrigation strategies to improve water use efficiency and wheat yield in the North China Plain.

PubMed

Zhang, Di; Li, Ruiqi; Batchelor, William D; Ju, Hui; Li, Yanming

2018-01-01

The North China Plain is one of the most important grain production regions in China, but is facing serious water shortages. To achieve a balance between water use and the need for food self-sufficiency, new water efficient irrigation strategies need to be developed that balance water use with farmer net return. The Crop Environment Resource Synthesis Wheat (CERES-Wheat model) was calibrated and evaluated with two years of data which consisted of 3-4 irrigation treatments, and the model was used to investigate long-term winter wheat productivity and water use from irrigation management in the North China Plain. The calibrated model simulated accurately above-ground biomass, grain yield and evapotranspiration of winter wheat in response to irrigation management. The calibrated model was then run using weather data from 1994-2016 in order to evaluate different irrigation strategies. The simulated results using historical weather data showed that grain yield and water use was sensitive to different irrigation strategies including amounts and dates of irrigation applications. The model simulated the highest yield when irrigation was applied at jointing (T9) in normal and dry rainfall years, and gave the highest simulated yields for irrigation at double ridge (T8) in wet years. A single simulated irrigation at jointing (T9) produced yields that were 88% compared to using a double irrigation treatment at T1 and T9 in wet years, 86% of that in normal years, and 91% of that in dry years. A single irrigation at jointing or double ridge produced higher water use efficiency because it obtained higher evapotranspiration. The simulated farmer irrigation practices produced the highest yield and net income. When the cost of water was taken into account, limited irrigation was found to be more profitable based on assumptions about future water costs. In order to increase farmer income, a subsidy will likely be needed to compensate farmers for yield reductions due to water savings

Evaluation of limited irrigation strategies to improve water use efficiency and wheat yield in the North China Plain

PubMed Central

Zhang, Di; Li, Ruiqi; Batchelor, William D.; Ju, Hui

2018-01-01

The North China Plain is one of the most important grain production regions in China, but is facing serious water shortages. To achieve a balance between water use and the need for food self-sufficiency, new water efficient irrigation strategies need to be developed that balance water use with farmer net return. The Crop Environment Resource Synthesis Wheat (CERES-Wheat model) was calibrated and evaluated with two years of data which consisted of 3–4 irrigation treatments, and the model was used to investigate long-term winter wheat productivity and water use from irrigation management in the North China Plain. The calibrated model simulated accurately above-ground biomass, grain yield and evapotranspiration of winter wheat in response to irrigation management. The calibrated model was then run using weather data from 1994–2016 in order to evaluate different irrigation strategies. The simulated results using historical weather data showed that grain yield and water use was sensitive to different irrigation strategies including amounts and dates of irrigation applications. The model simulated the highest yield when irrigation was applied at jointing (T9) in normal and dry rainfall years, and gave the highest simulated yields for irrigation at double ridge (T8) in wet years. A single simulated irrigation at jointing (T9) produced yields that were 88% compared to using a double irrigation treatment at T1 and T9 in wet years, 86% of that in normal years, and 91% of that in dry years. A single irrigation at jointing or double ridge produced higher water use efficiency because it obtained higher evapotranspiration. The simulated farmer irrigation practices produced the highest yield and net income. When the cost of water was taken into account, limited irrigation was found to be more profitable based on assumptions about future water costs. In order to increase farmer income, a subsidy will likely be needed to compensate farmers for yield reductions due to water

The buffer value of groundwater when well yield is limited

NASA Astrophysics Data System (ADS)

Foster, T.; Brozović, N.; Speir, C.

2017-04-01

A large proportion of the total value of groundwater in conjunctive use systems is associated with the ability to smooth out shortfalls in surface water supply during droughts. Previous research has argued that aquifer depletion in these regions will impact farmers negatively by reducing the available stock of groundwater to buffer production in future periods, and also by increasing the costs of groundwater extraction. However, existing studies have not considered how depletion may impact the productivity of groundwater stocks in conjunctive use systems through reductions in well yields. In this work, we develop a hydro-economic modeling framework to quantify the effects of changes in well yields on the buffer value of groundwater, and apply this model to an illustrative case study of tomato production in California's Central Valley. Our findings demonstrate that farmers with low well yields are forced to forgo significant production and profits because instantaneous groundwater supply is insufficient to buffer surface water shortfalls in drought years. Negative economic impacts of low well yields are an increasing function of surface water variability, and are also greatest for farmers operating less efficient irrigation systems. These results indicate that impacts of well yield reductions on the productivity of groundwater are an important economic impact of aquifer depletion, and that failure to consider this feedback may lead to significant errors in estimates of the value of groundwater management in conjunctive use systems.

Publication bias and the limited strength model of self-control: has the evidence for ego depletion been overestimated?

PubMed

Carter, Evan C; McCullough, Michael E

2014-01-01

Few models of self-control have generated as much scientific interest as has the limited strength model. One of the entailments of this model, the depletion effect, is the expectation that acts of self-control will be less effective when they follow prior acts of self-control. Results from a previous meta-analysis concluded that the depletion effect is robust and medium in magnitude (d = 0.62). However, when we applied methods for estimating and correcting for small-study effects (such as publication bias) to the data from this previous meta-analysis effort, we found very strong signals of publication bias, along with an indication that the depletion effect is actually no different from zero. We conclude that until greater certainty about the size of the depletion effect can be established, circumspection about the existence of this phenomenon is warranted, and that rather than elaborating on the model, research efforts should focus on establishing whether the basic effect exists. We argue that the evidence for the depletion effect is a useful case study for illustrating the dangers of small-study effects as well as some of the possible tools for mitigating their influence in psychological science.

What are the bias, imprecision, and limits of agreement for finding the flexion-extension plane of the knee with five tibial reference lines?

PubMed

Brar, Abheetinder S; Howell, Stephen M; Hull, Maury L

2016-06-01

Internal-external (I-E) malrotation of the tibial component is associated with poor function after total knee arthroplasty (TKA). Kinematically aligned (KA) TKA uses a functionally defined flexion-extension (F-E) tibial reference line, which is parallel to the F-E plane of the extended knee, to set I-E rotation of the tibial component. Sixty-two, three-dimensional bone models of normal knees were analyzed. We computed the bias (mean), imprecision (±standard deviation), and limits of agreement (mean±2 standard deviations) of the angle between five anatomically defined tibial reference lines used in mechanically aligned (MA) TKA and the F-E tibial reference line (+external). The following are the bias, imprecision, and limits of agreement of the angle between the F-E tibial reference line and 1) the tibial reference lines connecting the medial border (-2°±6°, -14° to 10°), medial 1/3 (6°±6°, -6° to 18°), and the most anterior point of the tibial tubercle (9°±4°, -1° to 17°) with the center of the posterior cruciate ligament, and 2) the tibial reference lines perpendicular to the posterior condylar axis of the tibia (-3°±4°, -11° to 5°), and a line connecting the centers of the tibial condyles (1°±4°, -7° to 9°). Based on these in vitro findings, it might be prudent to reconsider setting the I-E rotation of the tibial component to tibial reference lines that have bias, imprecision, and limits of agreement that fall outside the -7° to 10° range associated with high function after KA TKA. Copyright © 2016 Elsevier B.V. All rights reserved.

Impact of variety on cotton yield monitor calibration

USDA-ARS?s Scientific Manuscript database

Public and private research and demonstration efforts are essential to keeping US producers competitive with those in the rest of the world. While modern yield monitors for grain are able to harvest variety and hybrid trials without imposing variety/hybrid-related bias, many reports have indicated t...

Local bias-induced phase transitions

DOE PAGES

Seal, Katyayani; Baddorf, Arthur P.; Jesse, Stephen; ...

2008-11-27

Electrical bias-induced phase transitions underpin a wide range of applications from data storage to energy generation and conversion. The mechanisms behind these transitions are often quite complex and in many cases are extremely sensitive to local defects that act as centers for local transformations or pinning. Furthermore, using ferroelectrics as an example, we review methods for probing bias-induced phase transitions and discuss the current limitations and challenges for extending the methods to field-induced phase transitions and electrochemical reactions in energy storage, biological and molecular systems.

The Adaptive Biasing Force Method: Everything You Always Wanted To Know but Were Afraid To Ask

PubMed Central

2014-01-01

In the host of numerical schemes devised to calculate free energy differences by way of geometric transformations, the adaptive biasing force algorithm has emerged as a promising route to map complex free-energy landscapes. It relies upon the simple concept that as a simulation progresses, a continuously updated biasing force is added to the equations of motion, such that in the long-time limit it yields a Hamiltonian devoid of an average force acting along the transition coordinate of interest. This means that sampling proceeds uniformly on a flat free-energy surface, thus providing reliable free-energy estimates. Much of the appeal of the algorithm to the practitioner is in its physically intuitive underlying ideas and the absence of any requirements for prior knowledge about free-energy landscapes. Since its inception in 2001, the adaptive biasing force scheme has been the subject of considerable attention, from in-depth mathematical analysis of convergence properties to novel developments and extensions. The method has also been successfully applied to many challenging problems in chemistry and biology. In this contribution, the method is presented in a comprehensive, self-contained fashion, discussing with a critical eye its properties, applicability, and inherent limitations, as well as introducing novel extensions. Through free-energy calculations of prototypical molecular systems, many methodological aspects are examined, from stratification strategies to overcoming the so-called hidden barriers in orthogonal space, relevant not only to the adaptive biasing force algorithm but also to other importance-sampling schemes. On the basis of the discussions in this paper, a number of good practices for improving the efficiency and reliability of the computed free-energy differences are proposed. PMID:25247823

Cosmology of biased discrete symmetry breaking

NASA Technical Reports Server (NTRS)

Gelmini, Graciela B.; Gleiser, Marcelo; Kolb, Edward W.

1988-01-01

The cosmological consequences of spontaneous breaking of an approximate discrete symmetry are studied. The breaking leads to formation of proto-domains of false and true vacuum separated by domain walls of thickness determined by the mass scale of the model. The cosmological evolution of the walls is extremely sensitive to the magnitude of the biasing; several scenarios are possible, depending on the interplay between the surface tension on the walls and the volume pressure from the biasing. Walls may disappear almost immediately after they form, or may live long enough to dominate the energy density of the Universe and cause power-law inflation. Limits are obtained on the biasing that characterizes each possible scenario.

Arousal-biased competition in perception and memory

PubMed Central

Mather, Mara; Sutherland, Matthew R.

2010-01-01

Our everyday surroundings besiege us with information. The battle is for a share of our limited attention and memory, with the brain selecting the winners and discarding the losers. Previous research shows that both bottom-up and top-down factors bias competition in favor of high priority stimuli. We propose that arousal during an event increases this bias both in perception and in long-term memory of the event. Arousal-biased competition theory provides specific predictions about when arousal will enhance and when it will impair memory for events, accounting for some puzzling contradictions in the emotional memory literature. PMID:21660127

Bevel Gear Driver and Method Having Torque Limit Selection

NASA Technical Reports Server (NTRS)

Cook, Joseph S., Jr. (Inventor)

1997-01-01

Methods and apparatus are provided for a torque driver including an axially displaceable gear with a biasing assembly to bias the displaceable gear into an engagement position. A rotatable cap is provided with a micrometer dial to select a desired output torque. An intermediate bevel gear assembly is disposed between an input gear and an output gear. A gear tooth profile provides a separation force that overcomes the bias to limit torque at a desired torque limit. The torque limit is adjustable and may be adjusted manually or automatically depending on the type of biasing assembly provided. A clutch assembly automatically limits axial force applied to a fastener by the operator to avoid alteration of the desired torque limit.

Detection biases yield misleading patterns of species persistence and colonization in fragmented landscapes

USGS Publications Warehouse

Ruiz-Gutierrez, Viviana; Zipkin, Elise F.

2011-01-01

Species occurrence patterns, and related processes of persistence, colonization and turnover, are increasingly being used to infer habitat suitability, predict species distributions, and measure biodiversity potential. The majority of these studies do not account for observational error in their analyses despite growing evidence suggesting that the sampling process can significantly influence species detection and subsequently, estimates of occurrence. We examined the potential biases of species occurrence patterns that can result from differences in detectability across species and habitat types using hierarchical multispecies occupancy models applied to a tropical bird community in an agricultural fragmented landscape. Our results suggest that detection varies widely among species and habitat types. Not incorporating detectability severely biased occupancy dynamics for many species by overestimating turnover rates, producing misleading patterns of persistence and colonization of agricultural habitats, and misclassifying species into ecological categories (i.e., forest specialists and generalists). This is of serious concern, given that most research on the ability of agricultural lands to maintain current levels of biodiversity by and large does not correct for differences in detectability. We strongly urge researchers to apply an inferential framework which explicitly account for differences in detectability to fully characterize species-habitat relationships, correctly guide biodiversity conservation in human-modified landscapes, and generate more accurate predictions of species responses to future changes in environmental conditions.

Implicit Physician Biases in Periviability Counseling.

PubMed

Shapiro, Natasha; Wachtel, Elena V; Bailey, Sean M; Espiritu, Michael M

2018-06-01

To assess whether neonatologists show implicit racial and/or socioeconomic biases and whether these are predictive of recommendations at extreme periviability. A nationwide survey using a clinical vignette of a woman in labor at 23 2/7 weeks of gestation asked physicians how likely they were to recommend intensive vs comfort care. Participants were randomized to 1 of 4 versions of the vignette in which racial and socioeconomic stimuli were varied, followed by 2 implicit association tests (IATs). IATs revealed implicit preferences favoring white (mean IAT score = 0.48, P < .001) and greater socioeconomic status (mean IAT score = 0.73, P < .001). Multivariable linear regression analysis showed that physicians with implicit bias toward greater socioeconomic status were more likely than those without bias to recommend comfort care when presented with a patient of high socioeconomic status (P = .037). No significant effect was seen for implicit racial bias. Building on previous demonstrations of unconscious racial and socioeconomic biases among physicians and their predictive validity, our results suggest that unconscious socioeconomic bias influences recommendations when counseling at the limits of viability. Physicians who display a negative socioeconomic bias are less likely to recommend resuscitation when counseling women of high socioeconomic status. The influence of implicit socioeconomic bias on recommendations at periviability may influence neonatal healthcare disparities and should be explored in future studies. Copyright © 2018 Elsevier Inc. All rights reserved.

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

Applications of DC-Self Bias in CCP Deposition Systems

NASA Astrophysics Data System (ADS)

Keil, D. L.; Augustyniak, E.; Sakiyama, Y.

2013-09-01

In many commercial CCP plasma process systems the DC-self bias is available as a reported process parameter. Since commercial systems typically limit the number of onboard diagnostics, there is great incentive to understand how DC-self bias can be expected to respond to various system perturbations. This work reviews and examines DC self bias changes in response to tool aging, chamber film accumulation and wafer processing. The diagnostic value of the DC self bias response to transient and various steady state current draw schemes are examined. Theoretical models and measured experimental results are compared and contrasted.

Examining racial bias as a potential factor in pedestrian crashes.

PubMed

Coughenour, Courtney; Clark, Sheila; Singh, Ashok; Claw, Eudora; Abelar, James; Huebner, Joshua

2017-01-01

In the US people of color are disproportionately affected by pedestrian crashes. The purpose of this study was to examine the potential for racial bias in driver yielding behaviors at midblock crosswalks in low and high income neighborhoods located in the sprawling metropolitan area of Las Vegas, NV. Participants (1 white, 1 black female) crossed at a midblock crosswalk on a multilane road in a low income and a high income neighborhood. Trained observers recorded (1) number of cars that passed in the nearest lane before yielding while the pedestrian waited near the crosswalk at the curb (2) number of cars that passed through the crosswalk with the pedestrian in the same half of the roadway. The first car in the nearest lane yielded to the pedestrian while they waited at the curb 51.5% of the time at the high income and 70.7% of the time at the low income crosswalk. Two way ANOVAs found an interaction effect between income and race on yielding behaviors. Simple effects for income revealed that at the high income crosswalk, drivers were less likely to yield to the white pedestrian while she waited at the curb (F(1,122)=11.18;p=0.001), and were less likely to yield to the black pedestrian while she was in the same half of the roadway at the high income crosswalk (F(1,124)=4.40;p=0.04). Simple effects for race showed significantly more cars passed through the crosswalk while the black pedestrian was in the roadway compared to the white pedestrian at the high income crosswalk (F(1,124)=6.62;p=0.01). Bias in driver yielding behavior may be one influencing factor in higher rates of pedestrian crashes for people of color. Copyright © 2016 Elsevier Ltd. All rights reserved.

Large-scale assembly bias of dark matter halos

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

Lazeyras, Titouan; Musso, Marcello; Schmidt, Fabian, E-mail: titouan@mpa-garching.mpg.de, E-mail: mmusso@sas.upenn.edu, E-mail: fabians@mpa-garching.mpg.de

We present precise measurements of the assembly bias of dark matter halos, i.e. the dependence of halo bias on other properties than the mass, using curved 'separate universe' N-body simulations which effectively incorporate an infinite-wavelength matter overdensity into the background density. This method measures the LIMD (local-in-matter-density) bias parameters b {sub n} in the large-scale limit. We focus on the dependence of the first two Eulerian biases b {sup E} {sup {sub 1}} and b {sup E} {sup {sub 2}} on four halo properties: the concentration, spin, mass accretion rate, and ellipticity. We quantitatively compare our results with previous worksmore » in which assembly bias was measured on fairly small scales. Despite this difference, our findings are in good agreement with previous results. We also look at the joint dependence of bias on two halo properties in addition to the mass. Finally, using the excursion set peaks model, we attempt to shed new insights on how assembly bias arises in this analytical model.« less

Information bias in health research: definition, pitfalls, and adjustment methods

PubMed Central

Althubaiti, Alaa

2016-01-01

As with other fields, medical sciences are subject to different sources of bias. While understanding sources of bias is a key element for drawing valid conclusions, bias in health research continues to be a very sensitive issue that can affect the focus and outcome of investigations. Information bias, otherwise known as misclassification, is one of the most common sources of bias that affects the validity of health research. It originates from the approach that is utilized to obtain or confirm study measurements. This paper seeks to raise awareness of information bias in observational and experimental research study designs as well as to enrich discussions concerning bias problems. Specifying the types of bias can be essential to limit its effects and, the use of adjustment methods might serve to improve clinical evaluation and health care practice. PMID:27217764

Investigating the efficacy of attention bias modification in reducing high spider fear: The role of individual differences in initial bias

PubMed Central

Fox, Elaine; Zougkou, Konstantina; Ashwin, Chris; Cahill, Shanna

2015-01-01

Background and objectives Attention Bias Modification (ABM) targets attention bias (AB) towards threat and is a potential therapeutic intervention for anxiety. The current study investigated whether initial AB (towards or away from spider images) influenced the effectiveness of ABM in spider fear. Methods AB was assessed with an attentional probe task consisting of spider and neutral images presented simultaneously followed by a probe in spider congruent or spider incongruent locations. Response time (RT) differences between spider and neutral trials > 25 ms was considered ‘Bias Toward’ threat. RT difference < - 25 ms was considered ‘Bias Away’ from threat, and a difference between −25 ms and +25 ms was considered ‘No Bias’. Participants were categorized into Initial Bias groups using pre-ABM AB scores calculated at the end of the study. 66 participants' (Bias Toward n = 27, Bias Away n = 18, No Bias n = 21) were randomly assigned to ABM-active training designed to reduce or eliminate a bias toward threat and 61 (Bias Toward n = 17, Bias Away n = 18, No Bias n = 26) to ABM-control. Results ABM-active had the largest impact on those demonstrating an initial Bias Towards spider images in terms of changing AB and reducing Spider Fear Vulnerability, with the Bias Away group experiencing least benefit from ABM. However, all Initial Bias groups benefited equally from active ABM in a Stress Task. Limitations Participants were high spider fearful but not formally diagnosed with a specific phobia. Therefore, results should be confirmed within a clinical population. Conclusions Individual differences in Initial Bias may be an important determinant of ABM efficacy. PMID:26060177

Mean size estimation yields left-side bias: Role of attention on perceptual averaging.

PubMed

Li, Kuei-An; Yeh, Su-Ling

2017-11-01

The human visual system can estimate mean size of a set of items effectively; however, little is known about whether information on each visual field contributes equally to the mean size estimation. In this study, we examined whether a left-side bias (LSB)-perceptual judgment tends to depend more heavily on left visual field's inputs-affects mean size estimation. Participants were instructed to estimate the mean size of 16 spots. In half of the trials, the mean size of the spots on the left side was larger than that on the right side (the left-larger condition) and vice versa (the right-larger condition). Our results illustrated an LSB: A larger estimated mean size was found in the left-larger condition than in the right-larger condition (Experiment 1), and the LSB vanished when participants' attention was effectively cued to the right side (Experiment 2b). Furthermore, the magnitude of LSB increased with stimulus-onset asynchrony (SOA), when spots on the left side were presented earlier than the right side. In contrast, the LSB vanished and then induced a reversed effect with SOA when spots on the right side were presented earlier (Experiment 3). This study offers the first piece of evidence suggesting that LSB does have a significant influence on mean size estimation of a group of items, which is induced by a leftward attentional bias that enhances the prior entry effect on the left side.

Crystal plasticity assisted prediction on the yield locus evolution and forming limit curves

NASA Astrophysics Data System (ADS)

Lian, Junhe; Liu, Wenqi; Shen, Fuhui; Münstermann, Sebastian

2017-10-01

The aim of this study is to predict the plastic anisotropy evolution and its associated forming limit curves of bcc steels purely based on their microstructural features by establishing an integrated multiscale modelling approach. Crystal plasticity models are employed to describe the micro deformation mechanism and correlate the microstructure with mechanical behaviour on micro and mesoscale. Virtual laboratory is performed considering the statistical information of the microstructure, which serves as the input for the phenomenological plasticity model on the macroscale. For both scales, the microstructure evolution induced evolving features, such as the anisotropic hardening, r-value and yield locus evolution are seamlessly integrated. The predicted plasticity behaviour by the numerical simulations are compared with experiments. These evolutionary features of the material deformation behaviour are eventually considered for the prediction of formability.

Squeezing the halo bispectrum: a test of bias models

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

Dizgah, Azadeh Moradinezhad; Chan, Kwan Chuen; Noreña, Jorge

We study the halo-matter cross bispectrum in the presence of primordial non-Gaussianity of the local type. We restrict ourselves to the squeezed limit, for which the calculation are straightforward, and perform the measurements in the initial conditions of N-body simulations, to mitigate the contamination induced by nonlinear gravitational evolution. Interestingly, the halo-matter cross bispectrum is not trivial even in this simple limit as it is strongly sensitive to the scale-dependence of the quadratic and third-order halo bias. Therefore, it can be used to test biasing prescriptions. We consider three different prescription for halo clustering: excursion set peaks (ESP), local biasmore » and a model in which the halo bias parameters are explicitly derived from a peak-background split. In all cases, the model parameters are fully constrained with statistics other than the cross bispectrum. We measure the cross bispectrum involving one halo fluctuation field and two mass overdensity fields for various halo masses and collapse redshifts. We find that the ESP is in reasonably good agreement with the numerical data, while the other alternatives we consider fail in various cases. This suggests that the scale-dependence of halo bias also is a crucial ingredient to the squeezed limit of the halo bispectrum.« less

Sources of bias in clinical ethics case deliberation.

PubMed

Magelssen, Morten; Pedersen, Reidar; Førde, Reidun

2014-10-01

A central task for clinical ethics consultants and committees (CEC) is providing analysis of, and advice on, prospective or retrospective clinical cases. However, several kinds of biases may threaten the integrity, relevance or quality of the CEC's deliberation. Bias should be identified and, if possible, reduced or counteracted. This paper provides a systematic classification of kinds of bias that may be present in a CEC's case deliberation. Six kinds of bias are discussed, with examples, as to their significance and risk factors. Possible remedies are suggested. The potential for bias is greater when the case deliberation is performed by an individual ethics consultant than when an entire clinical ethics committee is involved. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Predicting paddlefish roe yields using an extension of the Beverton–Holt equilibrium yield-per-recruit model

USGS Publications Warehouse

Colvin, M.E.; Bettoli, Phillip William; Scholten, G.D.

2013-01-01

Equilibrium yield models predict the total biomass removed from an exploited stock; however, traditional yield models must be modified to simulate roe yields because a linear relationship between age (or length) and mature ovary weight does not typically exist. We extended the traditional Beverton-Holt equilibrium yield model to predict roe yields of Paddlefish Polyodon spathula in Kentucky Lake, Tennessee-Kentucky, as a function of varying conditional fishing mortality rates (10-70%), conditional natural mortality rates (cm; 9% and 18%), and four minimum size limits ranging from 864 to 1,016mm eye-to-fork length. These results were then compared to a biomass-based yield assessment. Analysis of roe yields indicated the potential for growth overfishing at lower exploitation rates and smaller minimum length limits than were suggested by the biomass-based assessment. Patterns of biomass and roe yields in relation to exploitation rates were similar regardless of the simulated value of cm, thus indicating that the results were insensitive to changes in cm. Our results also suggested that higher minimum length limits would increase roe yield and reduce the potential for growth overfishing and recruitment overfishing at the simulated cm values. Biomass-based equilibrium yield assessments are commonly used to assess the effects of harvest on other caviar-based fisheries; however, our analysis demonstrates that such assessments likely underestimate the probability and severity of growth overfishing when roe is targeted. Therefore, equilibrium roe yield-per-recruit models should also be considered to guide the management process for caviar-producing fish species.

Biased Feedback in Spatial Recall Yields a Violation of Delta Rule Learning

PubMed Central

Lipinski, John; Spencer, John P.; Samuelson, Larissa K.

2010-01-01

This study investigates whether inductive processes influencing spatial memory performance generalize to supervised learning scenarios with differential feedback. After providing a location memory response in a spatial recall task, participants received visual feedback showing the target location. In critical blocks, feedback was systematically biased either 4° towards the vertical axis (Towards condition) or 4° further away from the vertical axis (Away condition). Results showed that the weaker teaching signal (i.e., a smaller difference between the remembered location and the feedback location) in the Away condition produced a stronger experience-dependent change over blocks than in the Towards condition. This violates delta rule learning. Subsequent simulations of the Dynamic Field Theory of spatial cognition provide a theoretically unified account of these results. PMID:20702881

Biased feedback in spatial recall yields a violation of delta rule learning.

PubMed

Lipinski, John; Spencer, John P; Samuelson, Larissa K

2010-08-01

This study investigates whether inductive processes influencing spatial memory performance generalize to supervised learning scenarios with differential feedback. After providing a location memory response in a spatial recall task, participants received visual feedback showing the target location. In critical blocks, feedback was systematically biased either 4 degrees toward the vertical axis (toward condition) or 4 degrees farther away from the vertical axis (away condition). Results showed that the weaker teaching signal (i.e., a smaller difference between the remembered location and the feedback location) produced a stronger experience-dependent change over blocks in the away condition than in the toward condition. This violates delta rule learning. Subsequent simulations of the dynamic field theory of spatial cognition provide a theoretically unified account of these results.

Specific yield: compilation of specific yields for various materials

USGS Publications Warehouse

Johnson, A.I.

1967-01-01

Specific yield is defined as the ratio of (1) the volume of water that a saturated rock or soil will yield by gravity to (2) the total volume of the rock or soft. Specific yield is usually expressed as a percentage. The value is not definitive, because the quantity of water that will drain by gravity depends on variables such as duration of drainage, temperature, mineral composition of the water, and various physical characteristics of the rock or soil under consideration. Values of specific yields nevertheless offer a convenient means by which hydrologists can estimate the water-yielding capacities of earth materials and, as such, are very useful in hydrologic studies. The present report consists mostly of direct or modified quotations from many selected reports that present and evaluate methods for determining specific yield, limitations of those methods, and results of the determinations made on a wide variety of rock and soil materials. Although no particular values are recommended in this report, a table summarizes values of specific yield, and their averages, determined for 10 rock textures. The following is an abstract of the table. [Table

The evolution of social learning rules: payoff-biased and frequency-dependent biased transmission.

PubMed

Kendal, Jeremy; Giraldeau, Luc-Alain; Laland, Kevin

2009-09-21

Humans and other animals do not use social learning indiscriminately, rather, natural selection has favoured the evolution of social learning rules that make selective use of social learning to acquire relevant information in a changing environment. We present a gene-culture coevolutionary analysis of a small selection of such rules (unbiased social learning, payoff-biased social learning and frequency-dependent biased social learning, including conformism and anti-conformism) in a population of asocial learners where the environment is subject to a constant probability of change to a novel state. We define conditions under which each rule evolves to a genetically polymorphic equilibrium. We find that payoff-biased social learning may evolve under high levels of environmental variation if the fitness benefit associated with the acquired behaviour is either high or low but not of intermediate value. In contrast, both conformist and anti-conformist biases can become fixed when environment variation is low, whereupon the mean fitness in the population is higher than for a population of asocial learners. Our examination of the population dynamics reveals stable limit cycles under conformist and anti-conformist biases and some highly complex dynamics including chaos. Anti-conformists can out-compete conformists when conditions favour a low equilibrium frequency of the learned behaviour. We conclude that evolution, punctuated by the repeated successful invasion of different social learning rules, should continuously favour a reduction in the equilibrium frequency of asocial learning, and propose that, among competing social learning rules, the dominant rule will be the one that can persist with the lowest frequency of asocial learning.

The nature of assembly bias - III. Observational properties

NASA Astrophysics Data System (ADS)

Lacerna, Ivan; Padilla, Nelson; Stasyszyn, Federico

2014-10-01

We analyse galaxies in groups in the Sloan Digital Sky Survey (SDSS) and find a weak but significant assembly-type bias, where old central galaxies have a higher clustering amplitude (61 ± 9 per cent) at scales >1 h-1 Mpc than young central galaxies of equal host halo mass (Mh ˜ 1011.8 h- 1 M⊙). The observational sample is volume limited out to z = 0.1 with Mr - 5 log (h) ≤ -19.6. We construct a mock catalogue of galaxies that shows a similar signal of assembly bias (46 ± 9 per cent) at the same halo mass. We then adapt the model presented by Lacerna & Padilla (Paper I) to redefine the overdensity peak height, which traces the assembly bias such that galaxies in equal density peaks show the same clustering regardless of their stellar age, but this time using observational features such as a flux limit. The proxy for peak height, which is proposed as a better alternative than the virial mass, consists in the total mass given by the mass of neighbour host haloes in cylinders centred at each central galaxy. The radius of the cylinder is parameterized as a function of stellar age and virial mass. The best-fitting sets of parameters that make the assembly bias signal lower than 5-15 per cent for both SDSS and mock central galaxies are similar. The idea behind the parameterization is not to minimize the bias, but it is to use this method to understand the physical features that produce the assembly bias effect. Even though the tracers of the density field used here differ significantly from those used in Paper I, our analysis of the simulated catalogue indicates that the different tracers produce correlated proxies, and therefore the reason behind assembly bias is the crowding of peaks in both simulations and the SDSS.

Evaluation of trends in wheat yield models

NASA Technical Reports Server (NTRS)

Ferguson, M. C.

1982-01-01

Trend terms in models for wheat yield in the U.S. Great Plains for the years 1932 to 1976 are evaluated. The subset of meteorological variables yielding the largest adjusted R(2) is selected using the method of leaps and bounds. Latent root regression is used to eliminate multicollinearities, and generalized ridge regression is used to introduce bias to provide stability in the data matrix. The regression model used provides for two trends in each of two models: a dependent model in which the trend line is piece-wise continuous, and an independent model in which the trend line is discontinuous at the year of the slope change. It was found that the trend lines best describing the wheat yields consisted of combinations of increasing, decreasing, and constant trend: four combinations for the dependent model and seven for the independent model.

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-06-15

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

Short communication: economics of sex-biased milk production.

PubMed

Ettema, J F; Østergaard, S

2015-02-01

In a recent data study using 2.4 million lactations of 1.5 million cows, it was reported that gestation of a female calf in the first parity increases cumulative milk production by approximately 445kg over the first 2 lactations. The reported effect in this study is large and remarkable because it has not been found before. To our knowledge, the economic implications of this or any other sex bias have not been studied. The objective of the current study was to quantify the reported influence of fetal sex across lactations by using a simulation model of a dairy herd including youngstock. Two scenarios were evaluated and compared with a scenario in which cows and heifers were exclusively bred with conventional (nonsexed) semen. In the first scenario, sexed semen was used moderately-on 30% of all heifers and 30% of the first parity cows. A second scenario was studied in which sexed semen was used intensively-on all heifers and 50% of the first-parity cows. The simulated proportion of cows giving birth to 2 consecutive heifers increased from 23% when using exclusively conventional semen up to 31 and 48% when using sexed semen moderately and intensively, respectively. The proportion of cows having 2 consecutive bulls decreased from 27% (conventional semen only) to 20 and 8% when using sexed semen moderately and intensively, respectively. When incorporating the sex bias in the simulation model, the simulated milk yield in the scenario in which sexed semen was used moderately increased by 48kg of energy-corrected milk (ECM) per cow/yr, compared with only 36kg of ECM when not incorporating the sex bias in the model. For the scenario in which sexed semen was used intensively, milk yield increased by 66 and 99kg of ECM when excluding and including the sex bias, respectively. The economic implications of the assumed sex bias were €4.0 and €9.9 per cow/yr, in the scenarios in which sexed semen was used moderately and intensively, respectively. Copyright © 2015 American

An associative account of how the obesogenic environment biases adolescents' food choices.

PubMed

Watson, P; Wiers, R W; Hommel, B; Ridderinkhof, K R; de Wit, S

2016-01-01

Adolescents and children are the targets of much food advertising, the majority of which is for unhealthy snacks. Although the effects of advertising on food preferences and consummatory behavior are well documented, our understanding of the underlying mechanisms is still limited. The present study investigates an associative (ideomotor) mechanism by which exposure to rewarding (snack) outcomes may activate behavior that previously resulted in these rewards. Specifically, we used a computerized task to investigate whether exposing adolescents to food pictures directly, or to Pavlovian cues predictive of those food pictures, would bias their subsequent responses towards the presented/signaled food. Furthermore, we assessed whether this effect was particularly pronounced with palatable, high-calorie snacks (crisps and chocolate) relative to low-calorie snacks (tomatoes and cucumber). In two experiments, adolescents learnt that certain key presses would yield particular food pictures - some high calorie and others low calorie - before learning Pavlovian associations between cues (cartoon monsters) and these same food pictures. Subsequently, in a response-priming test, we examined the extent to which the food pictures and Pavlovian cues spontaneously primed the previously associated response. The results show that we replicated, in adolescents, previous demonstrations of ideomotor response priming in adults: food pictures biased responding towards the response that previously yielded them, and this effect transferred to the Pavlovian cues. Furthermore, the priming effect was significantly stronger for high-calorie rewards than for low-calorie. These findings indicate that the ideomotor mechanism plays an important role in the detrimental effect of our obesogenic environment, with its plethora of unhealthy food reminders, on adolescents' food-related choices. Copyright © 2015 Elsevier Ltd. All rights reserved.

Intergroup perception as a compromise between in-group bias and fair-mindedness.

PubMed

Singh, Ramadhar; Sharmini; Choo, Ivy

2004-08-01

Previously, perceived competence of and attraction toward targets categorized by race showed in-group bias and no bias, respectively. Consequently, previous investigators regarded intergroup perception as a compromise between the norms of in-group bias and fair-mindedness. An alternative hypothesis for such findings is that attraction is not as relevant a dimension for intergroup discrimination as is competence. To test contrasting predictions of these hypotheses, the present authors asked participants from the majority and minority groups in Singapore (ns = 320) to evaluate either competence of or attraction toward one of the five targets. Consistent with the hypothesis that intergroup perception is a compromise, both dimensions yielded a uniform but weak in-group bias. The participants' equating of the in-group with one out-group further illustrated fair-mindedness. The authors discussed implications of the findings.

Single-Receiver GPS Phase Bias Resolution

NASA Technical Reports Server (NTRS)

Bertiger, William I.; Haines, Bruce J.; Weiss, Jan P.; Harvey, Nathaniel E.

2010-01-01

Existing software has been modified to yield the benefits of integer fixed double-differenced GPS-phased ambiguities when processing data from a single GPS receiver with no access to any other GPS receiver data. When the double-differenced combination of phase biases can be fixed reliably, a significant improvement in solution accuracy is obtained. This innovation uses a large global set of GPS receivers (40 to 80 receivers) to solve for the GPS satellite orbits and clocks (along with any other parameters). In this process, integer ambiguities are fixed and information on the ambiguity constraints is saved. For each GPS transmitter/receiver pair, the process saves the arc start and stop times, the wide-lane average value for the arc, the standard deviation of the wide lane, and the dual-frequency phase bias after bias fixing for the arc. The second step of the process uses the orbit and clock information, the bias information from the global solution, and only data from the single receiver to resolve double-differenced phase combinations. It is called "resolved" instead of "fixed" because constraints are introduced into the problem with a finite data weight to better account for possible errors. A receiver in orbit has much shorter continuous passes of data than a receiver fixed to the Earth. The method has parameters to account for this. In particular, differences in drifting wide-lane values must be handled differently. The first step of the process is automated, using two JPL software sets, Longarc and Gipsy-Oasis. The resulting orbit/clock and bias information files are posted on anonymous ftp for use by any licensed Gipsy-Oasis user. The second step is implemented in the Gipsy-Oasis executable, gd2p.pl, which automates the entire process, including fetching the information from anonymous ftp

Specificity and overlap of attention and memory biases in depression.

PubMed

Marchetti, Igor; Everaert, Jonas; Dainer-Best, Justin; Loeys, Tom; Beevers, Christopher G; Koster, Ernst H W

2018-01-01

Attentional and memory biases are viewed as crucial cognitive processes underlying symptoms of depression. However, it is still unclear whether these two biases are uniquely related to depression or whether they show substantial overlap. We investigated the degree of specificity and overlap of attentional and memory biases for depressotypic stimuli in relation to depression and anxiety by means of meta-analytic commonality analysis. By including four published studies, we considered a pool of 463 healthy and subclinically depressed individuals, different experimental paradigms, and different psychological measures. Memory bias is reliably and strongly related to depression and, specifically, to symptoms of negative mood, worthlessness, feelings of failure, and pessimism. Memory bias for negative information was minimally related to anxiety. Moreover, neither attentional bias nor the overlap between attentional and memory biases were significantly related to depression. Limitations include cross-sectional nature of the study. Our study showed that, across different paradigms and psychological measures, memory bias (and not attentional bias) represents a primary mechanism in depression. Copyright © 2017 Elsevier B.V. All rights reserved.

Calibrating genomic and allelic coverage bias in single-cell sequencing.

PubMed

Zhang, Cheng-Zhong; Adalsteinsson, Viktor A; Francis, Joshua; Cornils, Hauke; Jung, Joonil; Maire, Cecile; Ligon, Keith L; Meyerson, Matthew; Love, J Christopher

2015-04-16

Artifacts introduced in whole-genome amplification (WGA) make it difficult to derive accurate genomic information from single-cell genomes and require different analytical strategies from bulk genome analysis. Here, we describe statistical methods to quantitatively assess the amplification bias resulting from whole-genome amplification of single-cell genomic DNA. Analysis of single-cell DNA libraries generated by different technologies revealed universal features of the genome coverage bias predominantly generated at the amplicon level (1-10 kb). The magnitude of coverage bias can be accurately calibrated from low-pass sequencing (∼0.1 × ) to predict the depth-of-coverage yield of single-cell DNA libraries sequenced at arbitrary depths. We further provide a benchmark comparison of single-cell libraries generated by multi-strand displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC). Finally, we develop statistical models to calibrate allelic bias in single-cell whole-genome amplification and demonstrate a census-based strategy for efficient and accurate variant detection from low-input biopsy samples.

Calibrating genomic and allelic coverage bias in single-cell sequencing

PubMed Central

Francis, Joshua; Cornils, Hauke; Jung, Joonil; Maire, Cecile; Ligon, Keith L.; Meyerson, Matthew; Love, J. Christopher

2016-01-01

Artifacts introduced in whole-genome amplification (WGA) make it difficult to derive accurate genomic information from single-cell genomes and require different analytical strategies from bulk genome analysis. Here, we describe statistical methods to quantitatively assess the amplification bias resulting from whole-genome amplification of single-cell genomic DNA. Analysis of single-cell DNA libraries generated by different technologies revealed universal features of the genome coverage bias predominantly generated at the amplicon level (1–10 kb). The magnitude of coverage bias can be accurately calibrated from low-pass sequencing (~0.1 ×) to predict the depth-of-coverage yield of single-cell DNA libraries sequenced at arbitrary depths. We further provide a benchmark comparison of single-cell libraries generated by multi-strand displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC). Finally, we develop statistical models to calibrate allelic bias in single-cell whole-genome amplification and demonstrate a census-based strategy for efficient and accurate variant detection from low-input biopsy samples. PMID:25879913

SU-F-I-80: Correction for Bias in a Channelized Hotelling Model Observer Caused by Temporally Variable Non-Stationary Noise

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

Favazza, C; Fetterly, K

2016-06-15

Purpose: Application of a channelized Hotelling model observer (CHO) over a wide range of x-ray angiography detector target dose (DTD) levels demonstrated substantial bias for conditions yielding low detectability indices (d’), including low DTD and small test objects. The purpose of this work was to develop theory and methods to correct this bias. Methods: A hypothesis was developed wherein the measured detectability index (d’b) for a known test object is positively biased by temporally variable non-stationary noise in the images. Hotelling’s T2 test statistic provided the foundation for a mathematical theory which accounts for independent contributions to the measured d’bmore » value from both the test object (d’o) and non-stationary noise (d’ns). Experimental methods were developed to directly estimate d’o by determining d’ns and subtracting it from d’b, in accordance with the theory. Specifically, d’ns was determined from two sets of images from which the traditional test object was withheld. This method was applied to angiography images with DTD levels in the range 0 to 240 nGy and for disk-shaped iodine-based contrast targets with diameters 0.5 to 4.0 mm. Results: Bias in d’ was evidenced by d’b values which exceeded values expected from a quantum limited imaging system and decreasing object size and DTD. d’ns increased with decreasing DTD, reaching a maximum of 2.6 for DTD = 0. Bias-corrected d’o estimates demonstrated sub-quantum limited performance of the x-ray angiography for low DTD. Findings demonstrated that the source of non-stationary noise was detector electronic readout noise. Conclusion: Theory and methods to estimate and correct bias in CHO measurements from temporally variable non-stationary noise were presented. The temporal non-stationary noise was shown to be due to electronic readout noise. This method facilitates accurate estimates of d’ values over a large range of object size and detector target dose.« less

The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

NASA Astrophysics Data System (ADS)

Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2018-01-01

Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

Statistical bias correction method applied on CMIP5 datasets over the Indian region during the summer monsoon season for climate change applications

NASA Astrophysics Data System (ADS)

Prasanna, V.

2018-01-01

This study makes use of temperature and precipitation from CMIP5 climate model output for climate change application studies over the Indian region during the summer monsoon season (JJAS). Bias correction of temperature and precipitation from CMIP5 GCM simulation results with respect to observation is discussed in detail. The non-linear statistical bias correction is a suitable bias correction method for climate change data because it is simple and does not add up artificial uncertainties to the impact assessment of climate change scenarios for climate change application studies (agricultural production changes) in the future. The simple statistical bias correction uses observational constraints on the GCM baseline, and the projected results are scaled with respect to the changing magnitude in future scenarios, varying from one model to the other. Two types of bias correction techniques are shown here: (1) a simple bias correction using a percentile-based quantile-mapping algorithm and (2) a simple but improved bias correction method, a cumulative distribution function (CDF; Weibull distribution function)-based quantile-mapping algorithm. This study shows that the percentile-based quantile mapping method gives results similar to the CDF (Weibull)-based quantile mapping method, and both the methods are comparable. The bias correction is applied on temperature and precipitation variables for present climate and future projected data to make use of it in a simple statistical model to understand the future changes in crop production over the Indian region during the summer monsoon season. In total, 12 CMIP5 models are used for Historical (1901-2005), RCP4.5 (2005-2100), and RCP8.5 (2005-2100) scenarios. The climate index from each CMIP5 model and the observed agricultural yield index over the Indian region are used in a regression model to project the changes in the agricultural yield over India from RCP4.5 and RCP8.5 scenarios. The results revealed a better

Bias-correction of PERSIANN-CDR Extreme Precipitation Estimates Over the United States

NASA Astrophysics Data System (ADS)

Faridzad, M.; Yang, T.; Hsu, K. L.; Sorooshian, S.

2017-12-01

Ground-based precipitation measurements can be sparse or even nonexistent over remote regions which make it difficult for extreme event analysis. PERSIANN-CDR (CDR), with 30+ years of daily rainfall information, provides an opportunity to study precipitation for regions where ground measurements are limited. In this study, the use of CDR annual extreme precipitation for frequency analysis of extreme events over limited/ungauged basins is explored. The adjustment of CDR is implemented in two steps: (1) Calculated CDR bias correction factor at limited gauge locations based on the linear regression analysis of gauge and CDR annual maxima precipitation; and (2) Extend the bias correction factor to the locations where gauges are not available. The correction factors are estimated at gauge sites over various catchments, elevation zones, and climate regions and the results were generalized to ungauged sites based on regional and climatic similarity. Case studies were conducted on 20 basins with diverse climate and altitudes in the Eastern and Western US. Cross-validation reveals that the bias correction factors estimated on limited calibration data can be extended to regions with similar characteristics. The adjusted CDR estimates also outperform gauge interpolation on validation sites consistently. It is suggested that the CDR with bias adjustment has a potential for study frequency analysis of extreme events, especially for regions with limited gauge observations.

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…

Determinants of hospital tax-exempt debt yields: corrections for selection and simultaneous equation bias.

PubMed Central

Carpenter, C E

1992-01-01

The cost of capital for hospitals is a topic of continuing interest as Medicare's new capital payment policy is implemented. This study examines the determinants of tax-exempt revenue bond yields, the primary source of long-term capital for hospitals. Two important methodological issues are addressed. A probit analysis estimates the probability that a hospital or system will be observed in the tax-exempt market. A selection-corrected two-stage least squares analysis allows for the simultaneous determination of bond yield and bond size. The study is based on a sample of hospitals that issued tax-exempt revenue bonds in 1982-1984, the years immediately surrounding implementation of Medicare's new payment system based on diagnosis-related groups, and an equal number of hospitals not in the market during the study period. Results suggest that hospital systems and hospitals with high occupancy rates are most likely to enter the tax-exempt revenue bond market. The yield equation suggests that hospital-specific variables may not be good predictors of the cost of capital once estimates are corrected for selection. PMID:1464540

Determinants of hospital tax-exempt debt yields: corrections for selection and simultaneous equation bias.

PubMed

Carpenter, C E

1992-12-01

The cost of capital for hospitals is a topic of continuing interest as Medicare's new capital payment policy is implemented. This study examines the determinants of tax-exempt revenue bond yields, the primary source of long-term capital for hospitals. Two important methodological issues are addressed. A probit analysis estimates the probability that a hospital or system will be observed in the tax-exempt market. A selection-corrected two-stage least squares analysis allows for the simultaneous determination of bond yield and bond size. The study is based on a sample of hospitals that issued tax-exempt revenue bonds in 1982-1984, the years immediately surrounding implementation of Medicare's new payment system based on diagnosis-related groups, and an equal number of hospitals not in the market during the study period. Results suggest that hospital systems and hospitals with high occupancy rates are most likely to enter the tax-exempt revenue bond market. The yield equation suggests that hospital-specific variables may not be good predictors of the cost of capital once estimates are corrected for selection.

The effect of biomass densification on structural sugar release and yield in biofuel feedstock and feedstock blends

DOE PAGES

Wolfrum, Edward J.; Nagle, Nicholas J.; Ness, Ryan M.; ...

2017-01-13

In this work, we examined the behavior of feedstock blends and the effect of a specific feedstock densification strategy (pelleting) on the release and yield of structural carbohydrates in a laboratory-scale dilute acid pretreatment (PT) and enzymatic hydrolysis (EH) assay. We report overall carbohydrate release and yield from the two-stage PT-EH assay for five single feedstocks (two corn stovers, miscanthus, switchgrass, and hybrid poplar) and three feedstock blends (corn stover-switchgrass, corn stover-switchgrass-miscanthus, and corn stover-switchgrass-hybrid poplar). We first examined the experimental results over time to establish the robustness of the PT-EH assay, which limits the precision of the experimental results.more » The use of two different control samples in the assay enabled us to identify (and correct for) a small bias in the EH portion of the combined assay for some runs. We then examined the effect of variable pretreatment reaction conditions (residence time, acid loading, and reactor temperature) on the conversion of a single feedstock (single-pass corn stover, CS-SP) in order to establish the range of pretreatment reaction conditions likely to provide optimal conversion data. Finally, we applied the assay to the 16 materials (8 feedstocks in 2 formats, loose and pelleted) over a more limited range of pretreatment experimental conditions. The four herbaceous feedstocks behaved similarly, while the hybrid poplar feedstock required higher pretreatment temperatures for optimal results. As expected, the yield data for three blended feedstocks were the average of the yield data for the individual feedstocks. As a result, the pelleting process appears to provide a slightly positive effect on overall total sugar yield.« less

The effect of biomass densification on structural sugar release and yield in biofuel feedstock and feedstock blends

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

Wolfrum, Edward J.; Nagle, Nicholas J.; Ness, Ryan M.

In this work, we examined the behavior of feedstock blends and the effect of a specific feedstock densification strategy (pelleting) on the release and yield of structural carbohydrates in a laboratory-scale dilute acid pretreatment (PT) and enzymatic hydrolysis (EH) assay. We report overall carbohydrate release and yield from the two-stage PT-EH assay for five single feedstocks (two corn stovers, miscanthus, switchgrass, and hybrid poplar) and three feedstock blends (corn stover-switchgrass, corn stover-switchgrass-miscanthus, and corn stover-switchgrass-hybrid poplar). We first examined the experimental results over time to establish the robustness of the PT-EH assay, which limits the precision of the experimental results.more » The use of two different control samples in the assay enabled us to identify (and correct for) a small bias in the EH portion of the combined assay for some runs. We then examined the effect of variable pretreatment reaction conditions (residence time, acid loading, and reactor temperature) on the conversion of a single feedstock (single-pass corn stover, CS-SP) in order to establish the range of pretreatment reaction conditions likely to provide optimal conversion data. Finally, we applied the assay to the 16 materials (8 feedstocks in 2 formats, loose and pelleted) over a more limited range of pretreatment experimental conditions. The four herbaceous feedstocks behaved similarly, while the hybrid poplar feedstock required higher pretreatment temperatures for optimal results. As expected, the yield data for three blended feedstocks were the average of the yield data for the individual feedstocks. As a result, the pelleting process appears to provide a slightly positive effect on overall total sugar yield.« less

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.

Increased latencies to respond in a judgment bias test are not associated with pessimistic biases in rats.

PubMed

Barker, Timothy Hugh; Howarth, Gordon Stanley; Whittaker, Alexandra Louise

2018-01-01

Extinction of learning is a common, yet under-reported limitation of judgment bias testing methods Repeated exposure to the ambiguous probe of a judgment bias paradigm encourages the animal to cease display of the required behaviours. However, there remains a need to repeatedly test animals to achieve statistical power. A delicate balance therefore needs to be struck between over- and under-exposure of the animals to the test conditions. This study presents the data of rats, a common animal subject of judgment bias testing. Rats were exposed to the ambiguous probe of a common, active-choice judgment bias test for 11 consecutive days. There was a significant increase in the latency to respond to the ambiguous probe following day 8, with no significant increase experienced for either the positive or less-positive probes. Following day 8 there was a significant increase in both optimistic and pessimistic latencies in response to the ambiguous probe. Therefore, repeated exposure to the ambiguous probe caused an increased latency in response even though optimistic interpretations were recorded. This implies that the use of response latency alone as a measure in judgment bias testing can falsely identify pessimism. Researchers should modify experimental design to include both choice and latency measures. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Continual training of attentional bias in social anxiety.

PubMed

Li, Songwei; Tan, Jieqing; Qian, Mingyi; Liu, Xinghua

2008-08-01

Using the dot-probe paradigm, it has been shown that high social anxiety is associated with an attentional bias toward negative information. In the present study, individuals with high social anxiety were divided into two groups randomly. One group was the attentional bias training group (Group T), and the other was the control group (Group C). For Group T, 7 days' continuous training of attentional bias was conducted using the dot-probe paradigm to make socially anxious individuals focus more on positive face pictures. The results showed that the training was effective in changing attentional bias in Group T. Scores of the Social Interaction Anxiety Scale (SIAS) in Group T were reduced compared to Group C, while the scores of Social Phobia Scale (SPS) and scores of Negative Evaluation Scale (FNE) showed no difference between the two groups, which suggested a limited reduction of social anxiety.

Plant nuclear factor Y (NF-Y) B subunits confer drought tolerance and lead to improved corn yields on water-limited acres.

PubMed

Nelson, Donald E; Repetti, Peter P; Adams, Tom R; Creelman, Robert A; Wu, Jingrui; Warner, David C; Anstrom, Don C; Bensen, Robert J; Castiglioni, Paolo P; Donnarummo, Meghan G; Hinchey, Brendan S; Kumimoto, Roderick W; Maszle, Don R; Canales, Roger D; Krolikowski, Katherine A; Dotson, Stanton B; Gutterson, Neal; Ratcliffe, Oliver J; Heard, Jacqueline E

2007-10-16

Commercially improved crop performance under drought conditions has been challenging because of the complexity of the trait and the multitude of factors that influence yield. Here we report the results of a functional genomics approach that identified a transcription factor from the nuclear factor Y (NF-Y) family, AtNF-YB1, which acts through a previously undescribed mechanism to confer improved performance in Arabidopsis under drought conditions. An orthologous maize transcription factor, ZmNF-YB2, is shown to have an equivalent activity. Under water-limited conditions, transgenic maize plants with increased ZmNF-YB2 expression show tolerance to drought based on the responses of a number of stress-related parameters, including chlorophyll content, stomatal conductance, leaf temperature, reduced wilting, and maintenance of photosynthesis. These stress adaptations contribute to a grain yield advantage to maize under water-limited environments. The application of this technology has the potential to significantly impact maize production systems that experience drought.

Plant nuclear factor Y (NF-Y) B subunits confer drought tolerance and lead to improved corn yields on water-limited acres

PubMed Central

Nelson, Donald E.; Repetti, Peter P.; Adams, Tom R.; Creelman, Robert A.; Wu, Jingrui; Warner, David C.; Anstrom, Don C.; Bensen, Robert J.; Castiglioni, Paolo P.; Donnarummo, Meghan G.; Hinchey, Brendan S.; Kumimoto, Roderick W.; Maszle, Don R.; Canales, Roger D.; Krolikowski, Katherine A.; Dotson, Stanton B.; Gutterson, Neal; Ratcliffe, Oliver J.; Heard, Jacqueline E.

2007-01-01

Commercially improved crop performance under drought conditions has been challenging because of the complexity of the trait and the multitude of factors that influence yield. Here we report the results of a functional genomics approach that identified a transcription factor from the nuclear factor Y (NF-Y) family, AtNF-YB1, which acts through a previously undescribed mechanism to confer improved performance in Arabidopsis under drought conditions. An orthologous maize transcription factor, ZmNF-YB2, is shown to have an equivalent activity. Under water-limited conditions, transgenic maize plants with increased ZmNF-YB2 expression show tolerance to drought based on the responses of a number of stress-related parameters, including chlorophyll content, stomatal conductance, leaf temperature, reduced wilting, and maintenance of photosynthesis. These stress adaptations contribute to a grain yield advantage to maize under water-limited environments. The application of this technology has the potential to significantly impact maize production systems that experience drought. PMID:17923671

Efficient multidimensional free energy calculations for ab initio molecular dynamics using classical bias potentials

NASA Astrophysics Data System (ADS)

VandeVondele, Joost; Rothlisberger, Ursula

2000-09-01

We present a method for calculating multidimensional free energy surfaces within the limited time scale of a first-principles molecular dynamics scheme. The sampling efficiency is enhanced using selected terms of a classical force field as a bias potential. This simple procedure yields a very substantial increase in sampling accuracy while retaining the high quality of the underlying ab initio potential surface and can thus be used for a parameter free calculation of free energy surfaces. The success of the method is demonstrated by the applications to two gas phase molecules, ethane and peroxynitrous acid, as test case systems. A statistical analysis of the results shows that the entire free energy landscape is well converged within a 40 ps simulation at 500 K, even for a system with barriers as high as 15 kcal/mol.

Association of HMO penetration and other credit quality factors with tax-exempt bond yields.

PubMed

McCue, M J

1997-01-01

This paper evaluates the relationship of HMO penetration, as well as other credit quality measures of market, institutional, operational, and financial traits, to tax-exempt bond yields. The study analyzed more than 1,500 bond issues from 1990 through 1993 and corrected for simultaneous relationships between bond size and yield and selection bias. The study found lower bond yields for hospitals located in markets with no HMO penetration. Lower yields for bond issues also were found for facilities generating higher numbers of days cash on hand and greater debt service coverage. Finally, results show that hospitals with higher occupancy rates achieve a lower yield.

Mutational Biases and GC-Biased Gene Conversion Affect GC Content in the Plastomes of Dendrobium Genus

PubMed Central

Niu, Zhitao; Xue, Qingyun; Wang, Hui; Xie, Xuezhu; Zhu, Shuying; Liu, Wei; Ding, Xiaoyu

2017-01-01

The variation of GC content is a key genome feature because it is associated with fundamental elements of genome organization. However, the reason for this variation is still an open question. Different kinds of hypotheses have been proposed to explain the variation of GC content during genome evolution. However, these hypotheses have not been explicitly investigated in whole plastome sequences. Dendrobium is one of the largest genera in the orchid species. Evolutionary studies of the plastomic organization and base composition are limited in this genus. In this study, we obtained the high-quality plastome sequences of D. loddigesii and D. devonianum. The comparison results showed a nearly identical organization in Dendrobium plastomes, indicating that the plastomic organization is highly conserved in Dendrobium genus. Furthermore, the impact of three evolutionary forces—selection, mutational biases, and GC-biased gene conversion (gBGC)—on the variation of GC content in Dendrobium plastomes was evaluated. Our results revealed: (1) consistent GC content evolution trends and mutational biases in single-copy (SC) and inverted repeats (IRs) regions; and (2) that gBGC has influenced the plastome-wide GC content evolution. These results suggest that both mutational biases and gBGC affect GC content in the plastomes of Dendrobium genus. PMID:29099062

A Systematic Review of Attention Biases in Opioid, Cannabis, Stimulant Use Disorders.

PubMed

Zhang, Melvyn; Ying, Jiangbo; Wing, Tracey; Song, Guo; Fung, Daniel S S; Smith, Helen

2018-06-01

Background : Opiates, cannabis, and amphetamines are highly abused, and use of these substances are prevalent disorders. Psychological interventions are crucial given that they help individuals maintain abstinence following a lapse or relapse into substance use. Advances in experimental psychology have suggested that automatic attention biases might be responsible for relapse. Prior reviews have provided evidence for the presence of these biases in addictive disorders and the effectiveness of bias modification. However, the prior studies are limited, as they failed to include trials involving participants with these prevalent addictive disorders or have failed to adopt a systematic approach in evidence synthesis. Objectives : The primary aim of this current systematic review is to synthesise the current evidence for attention biases amongst opioid use, cannabis use, and stimulant use disorders. The secondary aim is to determine the efficacy of attention bias modification interventions and other addictions related outcomes. Methods : A search was conducted from November 2017 to January 2018 on PubMed, MEDLINE, Embase, PsycINFO, Science Direct, Cochrane Central, and Scopus. The selection process of the articles was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. A qualitative synthesis was undertaken. Risk of bias was assessed using the Cochrane Risk of Bias tool. Results : Six randomised trials were identified. The evidence synthesized from these trials have provided strong evidence that attentional biases are present in opioid and stimulant use disorders. Evidence synthesis for other secondary outcome measures could not be performed given the heterogeneity in the measures reported and the limited number of trials. The risk of bias assessment for the included trials revealed a high risk of selection and attrition bias. Conclusions : This review demonstrates the potential need for interventions targeting attention

Biased interpretation and memory in children with varying levels of spider fear.

PubMed

Klein, Anke M; Titulaer, Geraldine; Simons, Carlijn; Allart, Esther; de Gier, Erwin; Bögels, Susan M; Becker, Eni S; Rinck, Mike

2014-01-01

This study investigated multiple cognitive biases in children simultaneously, to investigate whether spider-fearful children display an interpretation bias, a recall bias, and source monitoring errors, and whether these biases are specific for spider-related materials. Furthermore, the independent ability of these biases to predict spider fear was investigated. A total of 121 children filled out the Spider Anxiety and Disgust Screening for Children (SADS-C), and they performed an interpretation task, a memory task, and a Behavioural Assessment Test (BAT). As expected, a specific interpretation bias was found: Spider-fearful children showed more negative interpretations of ambiguous spider-related scenarios, but not of other scenarios. We also found specific source monitoring errors: Spider-fearful children made more fear-related source monitoring errors for the spider-related scenarios, but not for the other scenarios. Only limited support was found for a recall bias. Finally, interpretation bias, recall bias, and source monitoring errors predicted unique variance components of spider fear.

Optimizing rice yields while minimizing yield-scaled global warming potential.

PubMed

Pittelkow, Cameron M; Adviento-Borbe, Maria A; van Kessel, Chris; Hill, James E; Linquist, Bruce A

2014-05-01

To meet growing global food demand with limited land and reduced environmental impact, agricultural greenhouse gas (GHG) emissions are increasingly evaluated with respect to crop productivity, i.e., on a yield-scaled as opposed to area basis. Here, we compiled available field data on CH4 and N2 O emissions from rice production systems to test the hypothesis that in response to fertilizer nitrogen (N) addition, yield-scaled global warming potential (GWP) will be minimized at N rates that maximize yields. Within each study, yield N surplus was calculated to estimate deficit or excess N application rates with respect to the optimal N rate (defined as the N rate at which maximum yield was achieved). Relationships between yield N surplus and GHG emissions were assessed using linear and nonlinear mixed-effects models. Results indicate that yields increased in response to increasing N surplus when moving from deficit to optimal N rates. At N rates contributing to a yield N surplus, N2 O and yield-scaled N2 O emissions increased exponentially. In contrast, CH4 emissions were not impacted by N inputs. Accordingly, yield-scaled CH4 emissions decreased with N addition. Overall, yield-scaled GWP was minimized at optimal N rates, decreasing by 21% compared to treatments without N addition. These results are unique compared to aerobic cropping systems in which N2 O emissions are the primary contributor to GWP, meaning yield-scaled GWP may not necessarily decrease for aerobic crops when yields are optimized by N fertilizer addition. Balancing gains in agricultural productivity with climate change concerns, this work supports the concept that high rice yields can be achieved with minimal yield-scaled GWP through optimal N application rates. Moreover, additional improvements in N use efficiency may further reduce yield-scaled GWP, thereby strengthening the economic and environmental sustainability of rice systems. © 2013 John Wiley & Sons Ltd.

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.

Cultural and biological factors modulate spatial biases over development.

PubMed

Girelli, Luisa; Marinelli, Chiara Valeria; Grossi, Giuseppe; Arduino, Lisa S

2017-11-01

Increasing evidence supports the contribution of both biological and cultural factors to visuospatial processing. The present study adds to the literature by exploring the interplay of perceptual and linguistic mechanisms in determining visuospatial asymmetries in adults (Experiment 1) and children (Experiment 2). In particular, pre-schoolers (3 and 5 year-olds), school-aged children (8 year-old), and adult participants were required to bisect different types of stimuli, that is, lines, words, and figure strings. In accordance with the literature, results yielded a leftward bias for lines and words and a rightward bias for figure strings, in adult participants. More critically, different biases were found for lines, words, and figure strings in children as a function of age, reflecting the impact of both cultural and biological factors on the processing of different visuospatial materials. Specifically, an adult-like pattern of results emerged only in the older group of children (8 year-old), but not in pre-schoolers. Results are discussed in terms of literacy, reading habits exposure, and biological maturation.

Assessing Response Bias in a Web Survey at a University Faculty

ERIC Educational Resources Information Center

Menachemi, Nir

2011-01-01

Online surveys are increasingly common due to the myriad of benefits they offer over traditional survey methods. However, research has shown that response rates to web-based surveys are typically lower than to traditional surveys and can possibly yield biased results. University-based faculty members are a unique cohort that may be ideally suited…

How Accurately Do Maize Crop Models Simulate the Interactions of Atmospheric CO2 Concentration Levels With Limited Water Supply on Water Use and Yield?

NASA Technical Reports Server (NTRS)

Durand, Jean-Louis; Delusca, Kenel; Boote, Ken; Lizaso, Jon; Manderscheid, Remy; Weigel, Hans Johachim; Ruane, Alexander Clark; Rosenzweig, Cynthia E.; Jones, Jim; Ahuja, Laj;

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Whither cognitive bias modification research? Commentary on the special section articles.

PubMed

MacLeod, Colin; Koster, Ernst H W; Fox, Elaine

2009-02-01

This commentary reviews key theoretical, methodological, and clinical issues raised by recent research on cognitive bias modification (CBM). The authors identify the major ways in which the new work reported within this special section extends earlier CBM research. In particular, they note that it considers a wider range of participants, includes a greater diversity of symptoms measures, and targets for change a broader array of processing biases than previously has been the case. Furthermore, they point out that the present work develops and employs a more diverse arsenal of bias modification procedures, in some cases delivered across extended periods of time within naturalistic settings. They also draw attention to methodological limitations associated with the current studies, offering recommendations concerning how future CBM research might profitably build upon these exciting new directions while overcoming such limitations. Finally, they evaluate the theoretical and applied implications of the reported findings, discussing their capacity to illuminate the causal contributions made by cognitive bias to emotional vulnerability and their promise concerning the potential therapeutic value of CBM as a clinical tool.

A bias-corrected CMIP5 dataset for Africa using the CDF-t method - a contribution to agricultural impact studies

NASA Astrophysics Data System (ADS)

Moise Famien, Adjoua; Janicot, Serge; Delfin Ochou, Abe; Vrac, Mathieu; Defrance, Dimitri; Sultan, Benjamin; Noël, Thomas

2018-03-01

The objective of this paper is to present a new dataset of bias-corrected CMIP5 global climate model (GCM) daily data over Africa. This dataset was obtained using the cumulative distribution function transform (CDF-t) method, a method that has been applied to several regions and contexts but never to Africa. Here CDF-t has been applied over the period 1950-2099 combining Historical runs and climate change scenarios for six variables: precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. WFDEI has been used as the reference dataset to correct the GCMs. Evaluation of the results over West Africa has been carried out on a list of priority user-based metrics that were discussed and selected with stakeholders. It includes simulated yield using a crop model simulating maize growth. These bias-corrected GCM data have been compared with another available dataset of bias-corrected GCMs using WATCH Forcing Data as the reference dataset. The impact of WFD, WFDEI, and also EWEMBI reference datasets has been also examined in detail. It is shown that CDF-t is very effective at removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets. This is particularly true for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields. Projections of future yields over West Africa are quite different, depending on the bias-correction method used. However all these projections show a similar relative decreasing trend over the 21st century.

Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

2013-12-01

Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

Current limiting cathodes for non transit-time limited operation of InP TED's in the 100 GHz window

NASA Astrophysics Data System (ADS)

Friscouri, Marie-Renée; Rolland, Paul-Alain

1985-03-01

Reverse-biased low-barrier Schottky contact and reverse-biased isotype GaInAsP/InP heterojunction, used as current limiting cathodes for InP TED's, are investigated on the basis of output power and efficiency improvement as compared to N +NN + devices.

Publication Bias ( The "File-Drawer Problem") in Scientific Inference

NASA Technical Reports Server (NTRS)

Scargle, Jeffrey D.; DeVincenzi, Donald (Technical Monitor)

1999-01-01

Publication bias arises whenever the probability that a study is published depends on the statistical significance of its results. This bias, often called the file-drawer effect since the unpublished results are imagined to be tucked away in researchers' file cabinets, is potentially a severe impediment to combining the statistical results of studies collected from the literature. With almost any reasonable quantitative model for publication bias, only a small number of studies lost in the file-drawer will produce a significant bias. This result contradicts the well known Fail Safe File Drawer (FSFD) method for setting limits on the potential harm of publication bias, widely used in social, medical and psychic research. This method incorrectly treats the file drawer as unbiased, and almost always miss-estimates the seriousness of publication bias. A large body of not only psychic research, but medical and social science studies, has mistakenly relied on this method to validate claimed discoveries. Statistical combination can be trusted only if it is known with certainty that all studies that have been carried out are included. Such certainty is virtually impossible to achieve in literature surveys.

Comparison of bias analysis strategies applied to a large data set.

PubMed

Lash, Timothy L; Abrams, Barbara; Bodnar, Lisa M

2014-07-01

Epidemiologic data sets continue to grow larger. Probabilistic-bias analyses, which simulate hundreds of thousands of replications of the original data set, may challenge desktop computational resources. We implemented a probabilistic-bias analysis to evaluate the direction, magnitude, and uncertainty of the bias arising from misclassification of prepregnancy body mass index when studying its association with early preterm birth in a cohort of 773,625 singleton births. We compared 3 bias analysis strategies: (1) using the full cohort, (2) using a case-cohort design, and (3) weighting records by their frequency in the full cohort. Underweight and overweight mothers were more likely to deliver early preterm. A validation substudy demonstrated misclassification of prepregnancy body mass index derived from birth certificates. Probabilistic-bias analyses suggested that the association between underweight and early preterm birth was overestimated by the conventional approach, whereas the associations between overweight categories and early preterm birth were underestimated. The 3 bias analyses yielded equivalent results and challenged our typical desktop computing environment. Analyses applied to the full cohort, case cohort, and weighted full cohort required 7.75 days and 4 terabytes, 15.8 hours and 287 gigabytes, and 8.5 hours and 202 gigabytes, respectively. Large epidemiologic data sets often include variables that are imperfectly measured, often because data were collected for other purposes. Probabilistic-bias analysis allows quantification of errors but may be difficult in a desktop computing environment. Solutions that allow these analyses in this environment can be achieved without new hardware and within reasonable computational time frames.

Foreground Bias from Parametric Models of Far-IR Dust Emission

NASA Technical Reports Server (NTRS)

Kogut, A.; Fixsen, D. J.

2016-01-01

We use simple toy models of far-IR dust emission to estimate the accuracy to which the polarization of the cosmic microwave background can be recovered using multi-frequency fits, if the parametric form chosen for the fitted dust model differs from the actual dust emission. Commonly used approximations to the far-IR dust spectrum yield CMB residuals comparable to or larger than the sensitivities expected for the next generation of CMB missions, despite fitting the combined CMB plus foreground emission to precision 0.1 percent or better. The Rayleigh-Jeans approximation to the dust spectrum biases the fitted dust spectral index by (Delta)(Beta)(sub d) = 0.2 and the inflationary B-mode amplitude by (Delta)(r) = 0.03. Fitting the dust to a modified blackbody at a single temperature biases the best-fit CMB by (Delta)(r) greater than 0.003 if the true dust spectrum contains multiple temperature components. A 13-parameter model fitting two temperature components reduces this bias by an order of magnitude if the true dust spectrum is in fact a simple superposition of emission at different temperatures, but fails at the level (Delta)(r) = 0.006 for dust whose spectral index varies with frequency. Restricting the observing frequencies to a narrow region near the foreground minimum reduces these biases for some dust spectra but can increase the bias for others. Data at THz frequencies surrounding the peak of the dust emission can mitigate these biases while providing a direct determination of the dust temperature profile.

Human-display interactions: Context-specific biases

NASA Technical Reports Server (NTRS)

Kaiser, Mary Kister; Proffitt, Dennis R.

1987-01-01

Recent developments in computer engineering have greatly enhanced the capabilities of display technology. As displays are no longer limited to simple alphanumeric output, they can present a wide variety of graphic information, using either static or dynamic presentation modes. At the same time that interface designers exploit the increased capabilities of these displays, they must be aware of the inherent limitation of these displays. Generally, these limitations can be divided into those that reflect limitations of the medium (e.g., reducing three-dimensional representations onto a two-dimensional projection) and those reflecting the perceptual and conceptual biases of the operator. The advantages and limitations of static and dynamic graphic displays are considered. Rather than enter into the discussion of whether dynamic or static displays are superior, general advantages and limitations are explored which are contextually specific to each type of display.

Simulation of relationship between river discharge and sediment yield in the semi-arid river watersheds

NASA Astrophysics Data System (ADS)

Khaleghi, Mohammad Reza; Varvani, Javad

2018-02-01

Complex and variable nature of the river sediment yield caused many problems in estimating the long-term sediment yield and problems input into the reservoirs. Sediment Rating Curves (SRCs) are generally used to estimate the suspended sediment load of the rivers and drainage watersheds. Since the regression equations of the SRCs are obtained by logarithmic retransformation and have a little independent variable in this equation, they also overestimate or underestimate the true sediment load of the rivers. To evaluate the bias correction factors in Kalshor and Kashafroud watersheds, seven hydrometric stations of this region with suitable upstream watershed and spatial distribution were selected. Investigation of the accuracy index (ratio of estimated sediment yield to observed sediment yield) and the precision index of different bias correction factors of FAO, Quasi-Maximum Likelihood Estimator (QMLE), Smearing, and Minimum-Variance Unbiased Estimator (MVUE) with LSD test showed that FAO coefficient increases the estimated error in all of the stations. Application of MVUE in linear and mean load rating curves has not statistically meaningful effects. QMLE and smearing factors increased the estimated error in mean load rating curve, but that does not have any effect on linear rating curve estimation.

Limitation of Inverse Probability-of-Censoring Weights in Estimating Survival in the Presence of Strong Selection Bias

PubMed Central

Howe, Chanelle J.; Cole, Stephen R.; Chmiel, Joan S.; Muñoz, Alvaro

2011-01-01

In time-to-event analyses, artificial censoring with correction for induced selection bias using inverse probability-of-censoring weights can be used to 1) examine the natural history of a disease after effective interventions are widely available, 2) correct bias due to noncompliance with fixed or dynamic treatment regimens, and 3) estimate survival in the presence of competing risks. Artificial censoring entails censoring participants when they meet a predefined study criterion, such as exposure to an intervention, failure to comply, or the occurrence of a competing outcome. Inverse probability-of-censoring weights use measured common predictors of the artificial censoring mechanism and the outcome of interest to determine what the survival experience of the artificially censored participants would be had they never been exposed to the intervention, complied with their treatment regimen, or not developed the competing outcome. Even if all common predictors are appropriately measured and taken into account, in the context of small sample size and strong selection bias, inverse probability-of-censoring weights could fail because of violations in assumptions necessary to correct selection bias. The authors used an example from the Multicenter AIDS Cohort Study, 1984–2008, regarding estimation of long-term acquired immunodeficiency syndrome-free survival to demonstrate the impact of violations in necessary assumptions. Approaches to improve correction methods are discussed. PMID:21289029

A query theory account of the effect of memory retrieval on the sunk cost bias.

PubMed

Ting, Hsuchi; Wallsten, Thomas S

2011-08-01

The sunk cost bias occurs when individuals continue to invest in the same option when better alternatives are available. Many researchers believe that this bias is due to overemphasizing the past investment over the (missed) opportunities offered by alternatives. As an alternative or complement to this view, we show that memory retrieval and attention play important roles in the sunk cost bias. In two experiments, individuals generated more reasons for pursuing the invested option than for an alternative; they generated those reasons earlier in a sequence of reasons; and these effects increased as the individuals made progress toward attaining the reward yielded by the invested option. Associated with these effects, individuals perceived an increasingly wide gap in value between the invested and alternative options as they progressed toward the goal, thereby creating the sunk cost bias. Forcing individuals to reverse the order in which they generated reasons for the invested and alternative options reduced the bias. [corrected

The Extracellular Surface of the GLP-1 Receptor Is a Molecular Trigger for Biased Agonism.

PubMed

Wootten, Denise; Reynolds, Christopher A; Smith, Kevin J; Mobarec, Juan C; Koole, Cassandra; Savage, Emilia E; Pabreja, Kavita; Simms, John; Sridhar, Rohan; Furness, Sebastian G B; Liu, Mengjie; Thompson, Philip E; Miller, Laurence J; Christopoulos, Arthur; Sexton, Patrick M

2016-06-16

Ligand-directed signal bias offers opportunities for sculpting molecular events, with the promise of better, safer therapeutics. Critical to the exploitation of signal bias is an understanding of the molecular events coupling ligand binding to intracellular signaling. Activation of class B G protein-coupled receptors is driven by interaction of the peptide N terminus with the receptor core. To understand how this drives signaling, we have used advanced analytical methods that enable separation of effects on pathway-specific signaling from those that modify agonist affinity and mapped the functional consequence of receptor modification onto three-dimensional models of a receptor-ligand complex. This yields molecular insights into the initiation of receptor activation and the mechanistic basis for biased agonism. Our data reveal that peptide agonists can engage different elements of the receptor extracellular face to achieve effector coupling and biased signaling providing a foundation for rational design of biased agonists. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Impacts of forest restoration on water yield: A systematic review

PubMed Central

Filoso, Solange; Bezerra, Maíra Ometto; Weiss, Katherine C. B.; Palmer, Margaret A.

2017-01-01

Background Enhancing water provision services is a common target in forest restoration projects worldwide due to growing concerns over freshwater scarcity. However, whether or not forest cover expansion or restoration can improve water provision services is still unclear and highly disputed. Purpose The goal of this review is to provide a balanced and impartial assessment of the impacts of forest restoration and forest cover expansion on water yields as informed by the scientific literature. Potential sources of bias on the results of papers published are also examined. Data sources English, Spanish and Portuguese peer-review articles in Agricola, CAB Abstracts, ISI Web of Science, JSTOR, Google Scholar, and SciELO. Databases were searched through 2015. Search terms Intervention terms included forest restoration, regeneration/regrowth, forest second-growth, forestation/afforestation, and forestry. Target terms included water yield/quantity, streamflow, discharge, channel runoff, and annual flow. Study selection and eligibility criteria Articles were pre-selected based on key words in the title, abstract or text. Eligible articles addressed relevant interventions and targets and included quantitative information. Results Most studies reported decreases in water yields following the intervention, while other hydrological benefits have been observed. However, relatively few studies focused specifically on forest restoration, especially with native species, and/or on projects done at large spatial or temporal scales. Information is especially limited for the humid tropics and subtropics. Conclusions and implications of key findings While most studies reported a decrease in water yields, meta-analyses from a sub-set of studies suggest the potential influence of temporal and/or spatial scales on the outcomes of forest cover expansion or restoration projects. Given the many other benefits of forest restoration, improving our understanding of when and why forest

Slope Controls Grain Yield and Climatic Yield in Mountainous Yunnan province, China

NASA Astrophysics Data System (ADS)

Duan, X.; Rong, L.; Gu, Z.; Feng, D.

2017-12-01

Mountainous regions are increasingly vulnerable to food insecurity because of limited arable land, growing population pressure, and climate change. Development of sustainable mountain agriculture will require an increased understanding of the effects of environmental factors on grain and climatic yields. The objective of this study was to explore the relationships between actual grain yield, climatic yield, and environmental factors in a mountainous region in China. We collected data on the average grain yield per unit area in 119 counties in Yunnan province from 1985 to 2012, and chose 17 environmental factors for the same period. Our results showed that actual grain yield ranged from 1.43 to 6.92 t·ha-1, and the climatic yield ranged from -0.15 to -0.01 t·ha-1. Lower climatic yield but higher grain yield was generally found in central areas and at lower slopes and elevations in the western and southwestern counties of Yunnan province. Higher climatic yield but lower grain yield were found in northwestern parts of Yunnan province on steep slopes. Annual precipation and temperature had a weak influence on the climatic yield. Slope explained 44.62 and 26.29% of the variation in grain yield and climatic yield. The effects of topography on grain and climatic yields were greater than climatic factors. Slope was the most important environmental variable for the variability in climatic and grain yields in the mountainous Yunnan province due to the highly heterogeneous topographic conditions. Conversion of slopes to terraces in areas with higher climatic yields is an effective way to maintain grain production in response to climate variability. Additionally, soil amendments and soil and water conservation measures should be considered to maintain soil fertility and aid in sustainable development in central areas, and in counties at lower slopes and elevations in western and southwestern Yunnan province.

Bias, belief, and consensus: Collective opinion formation on fluctuating networks

NASA Astrophysics Data System (ADS)

Ngampruetikorn, Vudtiwat; Stephens, Greg J.

2016-11-01

With the advent of online networks, societies have become substantially more interconnected with individual members able to easily both maintain and modify their own social links. Here, we show that active network maintenance exposes agents to confirmation bias, the tendency to confirm one's beliefs, and we explore how this bias affects collective opinion formation. We introduce a model of binary opinion dynamics on a complex, fluctuating network with stochastic rewiring and we analyze these dynamics in the mean-field limit of large networks and fast link rewiring. We show that confirmation bias induces a segregation of individuals with different opinions and stabilizes the consensus state. We further show that bias can have an unusual, nonmonotonic effect on the time to consensus and this suggests a novel avenue for large-scale opinion manipulation.

Bias, belief, and consensus: Collective opinion formation on fluctuating networks.

PubMed

Ngampruetikorn, Vudtiwat; Stephens, Greg J

2016-11-01

With the advent of online networks, societies have become substantially more interconnected with individual members able to easily both maintain and modify their own social links. Here, we show that active network maintenance exposes agents to confirmation bias, the tendency to confirm one's beliefs, and we explore how this bias affects collective opinion formation. We introduce a model of binary opinion dynamics on a complex, fluctuating network with stochastic rewiring and we analyze these dynamics in the mean-field limit of large networks and fast link rewiring. We show that confirmation bias induces a segregation of individuals with different opinions and stabilizes the consensus state. We further show that bias can have an unusual, nonmonotonic effect on the time to consensus and this suggests a novel avenue for large-scale opinion manipulation.

Spatial Working Memory Capacity Predicts Bias in Estimates of Location

PubMed Central

Crawford, L. Elizabeth; Landy, David H.; Salthouse, Timothy A.

2016-01-01

Spatial memory research has attributed systematic bias in location estimates to a combination of a noisy memory trace with a prior structure that people impose on the space. Little is known about intra-individual stability and inter-individual variation in these patterns of bias. In the current work we align recent empirical and theoretical work on working memory capacity limits and spatial memory bias to generate the prediction that those with lower working memory capacity will show greater bias in memory of the location of a single item. Reanalyzing data from a large study of cognitive aging, we find support for this prediction. Fitting separate models to individuals’ data revealed a surprising variety of strategies. Some were consistent with Bayesian models of spatial category use, however roughly half of participants biased estimates outward in a way not predicted by current models and others seemed to combine these strategies. These analyses highlight the importance of studying individuals when developing general models of cognition. PMID:26900708

Reasoning, biases and dual processes: The lasting impact of Wason (1960).

PubMed

Evans, Jonathan St B T

2016-10-01

Wason (1960) published a relatively short experimental paper, in which he introduced the 2-4-6 problem as a test of inductive reasoning. This paper became one of the most highly cited to be published in the Quarterly Journal of Experimental Psychology and is significant for a number of reasons. First, the 2-4-6 task itself was ingenious and yielded evidence of error and bias in the intelligent participants who attempted it. Research on the 2-4-6 problem continues to the present day. More importantly, it was Wason's first paper on reasoning and one which made strong claims for bias and irrationality in a period dominated by rationalist writers like Piaget. It set in motion the study of cognitive biases in thinking and reasoning, well before the start of Tversky and Kahneman's famous heuristics and biases research programme. I also show here something for which Wason has received insufficient credit. It was Wason's work on this task and his later studies of his four card selection task that led to the first development of the dual process theory of reasoning which is so dominant in the current literature on the topic more than half a century later.

Simulating evapotranspiration (ET) yield response of selected corn varieties under full and limited irrigation in the Texas High Plains using DSSAT-CERES-Maize

USDA-ARS?s Scientific Manuscript database

Water scarcity due to drought and groundwater depletion has led to increased interest in deficit irrigation strategies that reduce irrigation requirements while maintaining profitable yields. This has resulted in an increase in the number modeling studies aimed at evaluating crop response to limite...

Work probability distribution and tossing a biased coin

NASA Astrophysics Data System (ADS)

Saha, Arnab; Bhattacharjee, Jayanta K.; Chakraborty, Sagar

2011-01-01

We show that the rare events present in dissipated work that enters Jarzynski equality, when mapped appropriately to the phenomenon of large deviations found in a biased coin toss, are enough to yield a quantitative work probability distribution for the Jarzynski equality. This allows us to propose a recipe for constructing work probability distribution independent of the details of any relevant system. The underlying framework, developed herein, is expected to be of use in modeling other physical phenomena where rare events play an important role.

A review of bias flow liners for acoustic damping in gas turbine combustors

NASA Astrophysics Data System (ADS)

Lahiri, C.; Bake, F.

2017-07-01

The optimized design of bias flow liner is a key element for the development of low emission combustion systems in modern gas turbines and aero-engines. The research of bias flow liners has a fairly long history concerning both the parameter dependencies as well as the methods to model the acoustic behaviour of bias flow liners under the variety of different bias and grazing flow conditions. In order to establish an overview over the state of the art, this paper provides a comprehensive review about the published research on bias flow liners and modelling approaches with an extensive study of the most relevant parameters determining the acoustic behaviour of these liners. The paper starts with a historical description of available investigations aiming on the characterization of the bias flow absorption principle. This chronological compendium is extended by the recent and ongoing developments in this field. In a next step the fundamental acoustic property of bias flow liner in terms of the wall impedance is introduced and the different derivations and formulations of this impedance yielding the different published model descriptions are explained and compared. Finally, a parametric study reveals the most relevant parameters for the acoustic damping behaviour of bias flow liners and how this is reflected by the various model representations. Although the general trend of the investigated acoustic behaviour is captured by the different models fairly well for a certain range of parameters, in the transition region between the resonance dominated and the purely bias flow related regime all models lack the correct damping prediction. This seems to be connected to the proper implementation of the reactance as a function of bias flow Mach number.

Optimization and validation of moving average quality control procedures using bias detection curves and moving average validation charts.

PubMed

van Rossum, Huub H; Kemperman, Hans

2017-02-01

To date, no practical tools are available to obtain optimal settings for moving average (MA) as a continuous analytical quality control instrument. Also, there is no knowledge of the true bias detection properties of applied MA. We describe the use of bias detection curves for MA optimization and MA validation charts for validation of MA. MA optimization was performed on a data set of previously obtained consecutive assay results. Bias introduction and MA bias detection were simulated for multiple MA procedures (combination of truncation limits, calculation algorithms and control limits) and performed for various biases. Bias detection curves were generated by plotting the median number of test results needed for bias detection against the simulated introduced bias. In MA validation charts the minimum, median, and maximum numbers of assay results required for MA bias detection are shown for various bias. Their use was demonstrated for sodium, potassium, and albumin. Bias detection curves allowed optimization of MA settings by graphical comparison of bias detection properties of multiple MA. The optimal MA was selected based on the bias detection characteristics obtained. MA validation charts were generated for selected optimal MA and provided insight into the range of results required for MA bias detection. Bias detection curves and MA validation charts are useful tools for optimization and validation of MA procedures.

Assessing Omitted Confounder Bias in Multilevel Mediation Models.

PubMed

Tofighi, Davood; Kelley, Ken

2016-01-01

To draw valid inference about an indirect effect in a mediation model, there must be no omitted confounders. No omitted confounders means that there are no common causes of hypothesized causal relationships. When the no-omitted-confounder assumption is violated, inference about indirect effects can be severely biased and the results potentially misleading. Despite the increasing attention to address confounder bias in single-level mediation, this topic has received little attention in the growing area of multilevel mediation analysis. A formidable challenge is that the no-omitted-confounder assumption is untestable. To address this challenge, we first analytically examined the biasing effects of potential violations of this critical assumption in a two-level mediation model with random intercepts and slopes, in which all the variables are measured at Level 1. Our analytic results show that omitting a Level 1 confounder can yield misleading results about key quantities of interest, such as Level 1 and Level 2 indirect effects. Second, we proposed a sensitivity analysis technique to assess the extent to which potential violation of the no-omitted-confounder assumption might invalidate or alter the conclusions about the indirect effects observed. We illustrated the methods using an empirical study and provided computer code so that researchers can implement the methods discussed.

Structural bias in the sentencing of felony defendants.

PubMed

Sutton, John R

2013-09-01

As incarceration rates have risen in the US, so has the overrepresentation of African Americans and Latinos among prison inmates. Whether and to what degree these disparities are due to bias in the criminal courts remains a contentious issue. This article pursues two lines of argument toward a structural account of bias in the criminal law, focusing on (1) cumulative disadvantages that may accrue over successive stages of the criminal justice process, and (2) the contexts of racial disadvantage in which courts are embedded. These arguments are tested using case-level data on male defendants charged with felony crimes in urban US counties in 2000. Multilevel binary and ordinal logit models are used to estimate contextual effects on pretrial detention, guilty pleas, and sentence severity, and cumulative effects are estimated as conditional probabilities that are allowed to vary by race across all three outcomes. Results yield strong, but qualified, evidence of cumulative disadvantage accruing to black and Latino defendants, but do not support the contextual hypotheses. When the cumulative effects of bias are taken into account, the estimated probability of the average African American or Latino felon going to prison is 26% higher than that of the average Anglo. Copyright © 2013 Elsevier Inc. All rights reserved.

Maximized exoEarth candidate yields for starshades

NASA Astrophysics Data System (ADS)

Stark, Christopher C.; Shaklan, Stuart; Lisman, Doug; Cady, Eric; Savransky, Dmitry; Roberge, Aki; Mandell, Avi M.

2016-10-01

The design and scale of a future mission to directly image and characterize potentially Earth-like planets will be impacted, to some degree, by the expected yield of such planets. Recent efforts to increase the estimated yields, by creating observation plans optimized for the detection and characterization of Earth-twins, have focused solely on coronagraphic instruments; starshade-based missions could benefit from a similar analysis. Here we explore how to prioritize observations for a starshade given the limiting resources of both fuel and time, present analytic expressions to estimate fuel use, and provide efficient numerical techniques for maximizing the yield of starshades. We implemented these techniques to create an approximate design reference mission code for starshades and used this code to investigate how exoEarth candidate yield responds to changes in mission, instrument, and astrophysical parameters for missions with a single starshade. We find that a starshade mission operates most efficiently somewhere between the fuel- and exposuretime-limited regimes and, as a result, is less sensitive to photometric noise sources as well as parameters controlling the photon collection rate in comparison to a coronagraph. We produced optimistic yield curves for starshades, assuming our optimized observation plans are schedulable and future starshades are not thrust-limited. Given these yield curves, detecting and characterizing several dozen exoEarth candidates requires either multiple starshades or an η≳0.3.

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.

Perceptual expertise: can sensorimotor experience change holistic processing and left-side bias?

PubMed

Tso, Ricky Van-yip; Au, Terry Kit-fong; Hsiao, Janet Hui-wen

2014-09-01

Holistic processing and left-side bias are both behavioral markers of expert face recognition. By contrast, expert recognition of characters in Chinese orthography involves left-side bias but reduced holistic processing, although faces and Chinese characters share many visual properties. Here, we examined whether this reduction in holistic processing of Chinese characters can be better explained by writing experience than by reading experience. Compared with Chinese nonreaders, Chinese readers who had limited writing experience showed increased holistic processing, whereas Chinese readers who could write characters fluently showed reduced holistic processing. This result suggests that writing and sensorimotor experience can modulate holistic-processing effects and that the reduced holistic processing observed in expert Chinese readers may depend mostly on writing experience. However, both expert writers and writers with limited experience showed similarly stronger left-side bias than novices did in processing mirror-symmetric Chinese characters; left-side bias may therefore be a robust expertise marker for object recognition that is uninfluenced by sensorimotor experience. © The Author(s) 2014.

Measurement Directiveness as a Cause of Response Bias: Evidence From Two Survey Experiments

ERIC Educational Resources Information Center

Brenner, Philip S.; DeLamater, John

2016-01-01

Extant research comparing survey self-reports of normative behavior to direct observations and time diary data have yielded evidence of extensive measurement bias. However, most of this research program has relied on observational data, comparing independent samples from the same target population, rather than comparing survey self-reports to a…

Emergent biological properties of arrestin pathway-selective biased agonism.

PubMed

Appleton, Kathryn M; Luttrell, Louis M

2013-06-01

Our growing appreciation of the pluridimensionality of G protein-coupled receptor (GPCR) signaling, combined with the phenomenon of orthosteric ligand "bias", has created the possibility of drugs that selectively modulate different aspects of GPCR function for therapeutic benefit. When viewed from the short-term perspective, e.g. changes in receptor conformation, effector coupling or second messenger generation, biased ligands appear to activate a subset of the response profile produced by a conventional agonist. Yet when examined in vivo, the limited data available suggest that biased ligand effects can diverge from their conventional counterparts in ways that cannot be predicted from their in vitro efficacy profile. What is currently missing, at least with respect to G protein and arrestin pathway-selective ligands, is a rational framework for relating the in vitro efficacy of a "biased" agonist to its in vivo actions that will enable drug screening programs to identify ligands with the desired biological effects.

The anchoring bias reflects rational use of cognitive resources.

PubMed

Lieder, Falk; Griffiths, Thomas L; M Huys, Quentin J; Goodman, Noah D

2018-02-01

Cognitive biases, such as the anchoring bias, pose a serious challenge to rational accounts of human cognition. We investigate whether rational theories can meet this challenge by taking into account the mind's bounded cognitive resources. We asked what reasoning under uncertainty would look like if people made rational use of their finite time and limited cognitive resources. To answer this question, we applied a mathematical theory of bounded rationality to the problem of numerical estimation. Our analysis led to a rational process model that can be interpreted in terms of anchoring-and-adjustment. This model provided a unifying explanation for ten anchoring phenomena including the differential effect of accuracy motivation on the bias towards provided versus self-generated anchors. Our results illustrate the potential of resource-rational analysis to provide formal theories that can unify a wide range of empirical results and reconcile the impressive capacities of the human mind with its apparently irrational cognitive biases.

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.

Affective bias in visual working memory is associated with capacity.

PubMed

Xie, Weizhen; Li, Huanhuan; Ying, Xiangyu; Zhu, Shiyou; Fu, Rong; Zou, Yingmin; Cui, Yanyan

2017-11-01

How does the affective nature of task stimuli modulate working memory (WM)? This study investigates whether WM maintains emotional information in a biased manner to meet the motivational principle of approaching positivity and avoiding negativity by retaining more approach-related positive content over avoidance-related negative content. This bias may exist regardless of individual differences in WM functionality, as indexed by WM capacity (overall bias hypothesis). Alternatively, this bias may be contingent on WM capacity (capacity-based hypothesis), in which a better WM system may be more likely to reveal an adaptive bias. In two experiments, participants performed change localisation tasks with emotional and non-emotional stimuli to estimate the number of items that they could retain for each of those stimuli. Although participants did not seem to remember one type of emotional content (e.g. happy faces) better than the other type of emotional content (e.g. sad faces), there was a significant correlation between WM capacity and affective bias. Specifically, participants with higher WM capacity for non-emotional stimuli (colours or line-drawing symbols) tended to maintain more happy faces over sad faces. These findings demonstrated the presence of a "built-in" affective bias in WM as a function of its systematic limitations, favouring the capacity-based hypothesis.

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

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.

An exploration of Intolerance of Uncertainty and memory bias.

PubMed

Francis, Kylie; Dugas, Michel J; Ricard, Nathalie C

2016-09-01

Research suggests that individuals high in Intolerance of Uncertainty (IU) have information processing biases, which may explain the close relationship between IU and worry. Specifically, high IU individuals show an attentional bias for uncertainty, and negatively interpret uncertain information. However, evidence of a memory bias for uncertainty among high IU individuals is limited. This study therefore explored the relationship between IU and memory for uncertainty. In two separate studies, explicit and implicit memory for uncertain compared to other types of words was assessed. Cognitive avoidance and other factors that could influence information processing were also examined. IUS Factor 1 was a significant positive predictor of explicit memory for positive words, and IUS Factor 2 a significant negative predictor of implicit memory for positive words. Stimulus relevance and vocabulary were significant predictors of implicit memory for uncertain words. Cognitive avoidance was a significant predictor of both explicit and implicit memory for threat words. Female gender was a significant predictor of implicit memory for uncertain and neutral words. Word stimuli such as those used in these studies may not be the optimal way of assessing information processing biases related to IU. In addition, the predominantly female, largely student sample may limit the generalizability of the findings. Future research focusing on IU factors, stimulus relevance, and both explicit and implicit memory, was recommended. The potential role of cognitive avoidance on memory, information processing, and worry was explored. Copyright © 2016 Elsevier Ltd. All rights reserved.

Testing the accuracy of growth and yield models for southern hardwood forests

Treesearch

H. Michael Rauscher; Michael J. Young; Charles D. Webb; Daniel J. Robison

2000-01-01

The accuracy of ten growth and yield models for Southern Appalachian upland hardwood forests and southern bottomland forests was evaluated. In technical applications, accuracy is the composite of both bias (average error) and precision. Results indicate that GHAT, NATPIS, and a locally calibrated version of NETWIGS may be regarded as being operationally valid...

Genotypic Variation in Yield, Yield Components, Root Morphology and Architecture, in Soybean in Relation to Water and Phosphorus Supply

PubMed Central

He, Jin; Jin, Yi; Du, Yan-Lei; Wang, Tao; Turner, Neil C.; Yang, Ru-Ping; Siddique, Kadambot H. M.; Li, Feng-Min

2017-01-01

Water shortage and low phosphorus (P) availability limit yields in soybean. Roots play important roles in water-limited and P-deficient environment, but the underlying mechanisms are largely unknown. In this study we determined the responses of four soybean [Glycine max (L.) Merr.] genotypes [Huandsedadou (HD), Bailudou (BLD), Jindou 21 (J21), and Zhonghuang 30 (ZH)] to three P levels [applied 0 (P0), 60 (P60), and 120 (P120) mg P kg-1 dry soil to the upper 0.4 m of the soil profile] and two water treatment [well-watered (WW) and water-stressed (WS)] with special reference to root morphology and architecture, we compared yield and its components, root morphology and root architecture to find out which variety and/or what kind of root architecture had high grain yield under P and drought stress. The results showed that water stress and low P, respectively, significantly reduced grain yield by 60 and 40%, daily water use by 66 and 31%, P accumulation by 40 and 80%, and N accumulation by 39 and 65%. The cultivar ZH with the lowest daily water use had the highest grain yield at P60 and P120 under drought. Increased root length was positively associated with N and P accumulation in both the WW and WS treatments, but not with grain yield under water and P deficits. However, in the WS treatment, high adventitious and lateral root densities were associated with high N and P uptake per unit root length which in turn was significantly and positively associated with grain yield. Our results suggest that (1) genetic variation of grain yield, daily water use, P and N accumulation, and root morphology and architecture were observed among the soybean cultivars and ZH had the best yield performance under P and water limited conditions; (2) water has a major influence on nutrient uptake and grain yield, while additional P supply can modestly increase yields under drought in some soybean genotypes; (3) while conserved water use plays an important role in grain yield under drought

Genotypic Variation in Yield, Yield Components, Root Morphology and Architecture, in Soybean in Relation to Water and Phosphorus Supply.

PubMed

He, Jin; Jin, Yi; Du, Yan-Lei; Wang, Tao; Turner, Neil C; Yang, Ru-Ping; Siddique, Kadambot H M; Li, Feng-Min

2017-01-01

Water shortage and low phosphorus (P) availability limit yields in soybean. Roots play important roles in water-limited and P-deficient environment, but the underlying mechanisms are largely unknown. In this study we determined the responses of four soybean [ Glycine max (L.) Merr.] genotypes [Huandsedadou (HD), Bailudou (BLD), Jindou 21 (J21), and Zhonghuang 30 (ZH)] to three P levels [applied 0 (P0), 60 (P60), and 120 (P120) mg P kg -1 dry soil to the upper 0.4 m of the soil profile] and two water treatment [well-watered (WW) and water-stressed (WS)] with special reference to root morphology and architecture, we compared yield and its components, root morphology and root architecture to find out which variety and/or what kind of root architecture had high grain yield under P and drought stress. The results showed that water stress and low P, respectively, significantly reduced grain yield by 60 and 40%, daily water use by 66 and 31%, P accumulation by 40 and 80%, and N accumulation by 39 and 65%. The cultivar ZH with the lowest daily water use had the highest grain yield at P60 and P120 under drought. Increased root length was positively associated with N and P accumulation in both the WW and WS treatments, but not with grain yield under water and P deficits. However, in the WS treatment, high adventitious and lateral root densities were associated with high N and P uptake per unit root length which in turn was significantly and positively associated with grain yield. Our results suggest that (1) genetic variation of grain yield, daily water use, P and N accumulation, and root morphology and architecture were observed among the soybean cultivars and ZH had the best yield performance under P and water limited conditions; (2) water has a major influence on nutrient uptake and grain yield, while additional P supply can modestly increase yields under drought in some soybean genotypes; (3) while conserved water use plays an important role in grain yield under drought

Two biased estimation techniques in linear regression: Application to aircraft

NASA Technical Reports Server (NTRS)

Klein, Vladislav

1988-01-01

Several ways for detection and assessment of collinearity in measured data are discussed. Because data collinearity usually results in poor least squares estimates, two estimation techniques which can limit a damaging effect of collinearity are presented. These two techniques, the principal components regression and mixed estimation, belong to a class of biased estimation techniques. Detection and assessment of data collinearity and the two biased estimation techniques are demonstrated in two examples using flight test data from longitudinal maneuvers of an experimental aircraft. The eigensystem analysis and parameter variance decomposition appeared to be a promising tool for collinearity evaluation. The biased estimators had far better accuracy than the results from the ordinary least squares technique.

Experimental and theoretical determination of sea-state bias in radar altimetry

NASA Technical Reports Server (NTRS)

Stewart, Robert H.

1991-01-01

The major unknown error in radar altimetry is due to waves on the sea surface which cause the mean radar-reflecting surface to be displaced from mean sea level. This is the electromagnetic bias. The primary motivation for the project was to understand the causes of the bias so that the error it produces in radar altimetry could be calculated and removed from altimeter measurements made from space by the Topex/Poseidon altimetric satellite. The goals of the project were: (1) observe radar scatter at vertical incidence using a simple radar on a platform for a wide variety of environmental conditions at the same time wind and wave conditions were measured; (2) calculate electromagnetic bias from the radar observations; (3) investigate the limitations of the present theory describing radar scatter at vertical incidence; (4) compare measured electromagnetic bias with bias calculated from theory using measurements of wind and waves made at the time of the radar measurements; and (5) if possible, extend the theory so bias can be calculated for a wider range of environmental conditions.

Variation of inulin content, inulin yield and water use efficiency for inulin yield in Jerusalem artichoke genotypes under different water regimes

USDA-ARS?s Scientific Manuscript database

The information on genotypic variation for inulin content, inulin yield and water use efficiency of inulin yield (WUEi) in response to drought is limited. This study was to investigate the genetic variability in inulin content, inulin yield and WUEi of Jerusalem artichoke (Helianthus tuberosus L.) ...

Spatial working memory capacity predicts bias in estimates of location.

PubMed

Crawford, L Elizabeth; Landy, David; Salthouse, Timothy A

2016-09-01

Spatial memory research has attributed systematic bias in location estimates to a combination of a noisy memory trace with a prior structure that people impose on the space. Little is known about intraindividual stability and interindividual variation in these patterns of bias. In the current work, we align recent empirical and theoretical work on working memory capacity limits and spatial memory bias to generate the prediction that those with lower working memory capacity will show greater bias in memory of the location of a single item. Reanalyzing data from a large study of cognitive aging, we find support for this prediction. Fitting separate models to individuals' data revealed a surprising variety of strategies. Some were consistent with Bayesian models of spatial category use, however roughly half of participants biased estimates outward in a way not predicted by current models and others seemed to combine these strategies. These analyses highlight the importance of studying individuals when developing general models of cognition. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Electrocortical measures of information processing biases in social anxiety disorder: A review.

PubMed

Harrewijn, Anita; Schmidt, Louis A; Westenberg, P Michiel; Tang, Alva; van der Molen, Melle J W

2017-10-01

Social anxiety disorder (SAD) is characterized by information processing biases, however, their underlying neural mechanisms remain poorly understood. The goal of this review was to give a comprehensive overview of the most frequently studied EEG spectral and event-related potential (ERP) measures in social anxiety during rest, anticipation, stimulus processing, and recovery. A Web of Science search yielded 35 studies reporting on electrocortical measures in individuals with social anxiety or related constructs. Social anxiety was related to increased delta-beta cross-frequency correlation during anticipation and recovery, and information processing biases during early processing of faces (P1) and errors (error-related negativity). These electrocortical measures are discussed in relation to the persistent cycle of information processing biases maintaining SAD. Future research should further investigate the mechanisms of this persistent cycle and study the utility of electrocortical measures in early detection, prevention, treatment and endophenotype research. Copyright © 2017 Elsevier B.V. All rights reserved.

Brighter galaxy bias: underestimating the velocity dispersions of galaxy clusters

NASA Astrophysics Data System (ADS)

Old, L.; Gray, M. E.; Pearce, F. R.

2013-09-01

We study the systematic bias introduced when selecting the spectroscopic redshifts of brighter cluster galaxies to estimate the velocity dispersion of galaxy clusters from both simulated and observational galaxy catalogues. We select clusters with Ngal ≥ 50 at five low-redshift snapshots from the publicly available De Lucia & Blaziot semi-analytic model galaxy catalogue. Clusters are also selected from the Tempel Sloan Digital Sky Survey Data Release 8 groups and clusters catalogue across the redshift range 0.021 ≤ z ≤ 0.098. We employ various selection techniques to explore whether the velocity dispersion bias is simply due to a lack of dynamical information or is the result of an underlying physical process occurring in the cluster, for example, dynamical friction experienced by the brighter cluster members. The velocity dispersions of the parent dark matter (DM) haloes are compared to the galaxy cluster dispersions and the stacked distribution of DM particle velocities is examined alongside the corresponding galaxy velocity distribution. We find a clear bias between the halo and the semi-analytic galaxy cluster velocity dispersion on the order of σgal/σDM ˜ 0.87-0.95 and a distinct difference in the stacked galaxy and DM particle velocities distribution. We identify a systematic underestimation of the velocity dispersions when imposing increasing absolute I-band magnitude limits. This underestimation is enhanced when using only the brighter cluster members for dynamical analysis on the order of 5-35 per cent, indicating that dynamical friction is a serious source of bias when using galaxy velocities as tracers of the underlying gravitational potential. In contrast to the literature we find that the resulting bias is not only halo mass dependent but also that the nature of the dependence changes according to the galaxy selection strategy. We make a recommendation that, in the realistic case of limited availability of spectral observations, a strictly

Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications.

PubMed

Silvestro, Paolo Cosmo; Pignatti, Stefano; Yang, Hao; Yang, Guijun; Pascucci, Simone; Castaldi, Fabio; Casa, Raffaele

2017-01-01

Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations.

Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications

PubMed Central

Pignatti, Stefano; Yang, Hao; Yang, Guijun; Pascucci, Simone; Castaldi, Fabio

2017-01-01

Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations. PMID:29107963

Effects of dc bias on the kinetics and electrical properties of silicon dioxide grown in an electron cyclotron resonance plasma

NASA Astrophysics Data System (ADS)

Carl, D. A.; Hess, D. W.; Lieberman, M. A.; Nguyen, T. D.; Gronsky, R.

1991-09-01

Thin (3-300-nm) oxides were grown on single-crystal silicon substrates at temperatures from 523 to 673 K in a low-pressure electron cyclotron resonance (ECR) oxygen plasma. Oxides were grown under floating, anodic or cathodic bias conditions, although only the oxides grown under floating or anodic bias conditions are acceptable for use as gate dielectrics in metal-oxide-semiconductor technology. Oxide thickness uniformity as measured by ellipsometry decreased with increasing oxidation time for all bias conditions. Oxidation kinetics under anodic conditions can be explained by negatively charged atomic oxygen, O-, transport limited growth. Constant current anodizations yielded three regions of growth: (1) a concentration gradient dominated regime for oxides thinner than 10 nm, (2) a field dominated regime with ohmic charged oxidant transport for oxide thickness in the range of 10 nm to approximately 100 nm, and (3) a space-charge limited regime for films thicker than approximately 100 nm. The relationship between oxide thickness (xox), overall potential drop (Vox) and ion current (ji) in the space-charge limited transport region was of the form: ji ∝ V2ox/x3ox. Transmission electron microscopy analysis of 5-60-nm-thick anodized films indicated that the silicon-silicon dioxide interface was indistinguishable from that of thermal oxides grown at 1123 K. High-frequency capacitance-voltage (C-V) and ramped bias current-voltage (I-V) studies performed on 5.4-30-nm gate thickness capacitors indicated that the as-grown ECR films had high levels of fixed oxide charge (≳1011 cm-2) and interface traps (≳1012 cm-2 eV-1). The fixed charge level could be reduced to ≊4×1010 cm-2 by a 20 min polysilicon gate activation anneal at 1123 K in nitrogen; the interface trap density at mid-band gap decreased to ≊(1-2)×1011 cm-2 eV-1 after this process. The mean breakdown strength for anodic oxides grown under optimum conditions was 10.87±0.83 MV cm-1. Electrical properties of

Seed-Specific Expression of OsDWF4, a Rate-Limiting Gene Involved in Brassinosteroids Biosynthesis, Improves Both Grain Yield and Quality in Rice.

PubMed

Li, Qian-Feng; Yu, Jia-Wen; Lu, Jun; Fei, Hong-Yuan; Luo, Ming; Cao, Bu-Wei; Huang, Li-Chun; Zhang, Chang-Quan; Liu, Qiao-Quan

2018-04-18

Brassinosteroids (BRs) are essential plant-specific steroidal hormones that regulate diverse growth and developmental processes in plants. We evaluated the effects of OsDWF4, a gene that encodes a rate-limiting enzyme in BR biosynthesis, on both rice yield and quality when driven by the Gt1 or Ubi promoter, which correspond to seed-specific or constitutive expression, respectively. Generally, transgenic plants expressing OsDWF4 showed increased grain yield with more tillers and longer and heavier seeds. Moreover, the starch physicochemical properties of the transgenic rice were also improved. Interestingly, OsDWF4 was found to exert different effects on either rice yield or quality when driven by the different promoters. The overall performance of the pGt1::OsDWF4 lines was better than that of the pUbi::OsDWF4 lines. Our data not only demonstrate the effects of OsDWF4 overexpression on both rice yield and quality but also suggest that a seed-specific promoter is a good choice in BR-mediated rice breeding programs.

Obesity, the Endocannabinoid System, and Bias Arising from Pharmaceutical Sponsorship

PubMed Central

McPartland, John M.

2009-01-01

Background Previous research has shown that academic physicians conflicted by funding from the pharmaceutical industry have corrupted evidence based medicine and helped enlarge the market for drugs. Physicians made pharmaceutical-friendly statements, engaged in disease mongering, and signed biased review articles ghost-authored by corporate employees. This paper tested the hypothesis that bias affects review articles regarding rimonabant, an anti-obesity drug that blocks the central cannabinoid receptor. Methods/Principal Findings A MEDLINE search was performed for rimonabant review articles, limited to articles authored by USA physicians who served as consultants for the company that manufactures rimonabant. Extracted articles were examined for industry-friendly bias, identified by three methods: analysis with a validated instrument for monitoring bias in continuing medical education (CME); analysis for bias defined as statements that ran contrary to external evidence; and a tally of misrepresentations about the endocannabinoid system. Eight review articles were identified, but only three disclosed authors' financial conflicts of interest, despite easily accessible information to the contrary. The Takhar CME bias instrument demonstrated statistically significant bias in all the review articles. Biased statements that were nearly identical reappeared in the articles, including disease mongering, exaggerating rimonabant's efficacy and safety, lack of criticisms regarding rimonabant clinical trials, and speculations about surrogate markers stated as facts. Distinctive and identical misrepresentations regarding the endocannabinoid system also reappeared in articles by different authors. Conclusions The findings are characteristic of bias that arises from financial conflicts of interest, and suggestive of ghostwriting by a common author. Resolutions for this scenario are proposed. PMID:19333392

A Summary of Biases in the BATSE Burst Trigger

NASA Technical Reports Server (NTRS)

Meegan, Charles A; Pendleton, Geoffrey N.; Mallozzi, Robert S.

1999-01-01

The BATSE threshold for triggering on a gamma-ray burst is generally expressed in units of peak flux between 50 and 300 keV averaged over 1024 milliseconds. The completeness of the sample is affected by several systematic and statistical affects. A study is currently underway to characterize two of these that have not yet been Included Abstract: in the BATSE trigger efficiency calculation. They are: 1) the effects of statistical fluctuations on the measurement of peak flux and, 2) the effect on the trigger threshold of "slow risers", In which some of the burst flux is Identified as background. Some other biases that have been identified are in fact Malmquist-type biases which relate to a volume limited, rather than peak flux limited, burst source distribution and which cannot be determined without knowledge of the burst luminosity distribution.

Numerical bias in bounded and unbounded number line tasks.

PubMed

Cohen, Dale J; Blanc-Goldhammer, Daryn

2011-04-01

The number line task is often used to assess children's and adults' underlying representations of integers. Traditional bounded number line tasks, however, have limitations that can lead to misinterpretation. Here we present a new task, an unbounded number line task, that overcomes these limitations. In Experiment 1, we show that adults use a biased proportion estimation strategy to complete the traditional bounded number line task. In Experiment 2, we show that adults use a dead-reckoning integer estimation strategy in our unbounded number line task. Participants revealed a positively accelerating numerical bias in both tasks, but showed scalar variance only in the unbounded number line task. We conclude that the unbounded number line task is a more pure measure of integer representation than the bounded number line task, and using these results, we present a preliminary description of adults' underlying representation of integers.

Discrimination, Racial Bias, and Telomere Length in African-American Men

PubMed Central

Chae, David H.; Nuru-Jeter, Amani M.; Adler, Nancy E.; Brody, Gene H.; Lin, Jue; Blackburn, Elizabeth H.; Epel, Elissa S.

2013-01-01

Background Leukocyte telomere length (LTL) is an indicator of general systemic aging, with shorter LTL being associated with several chronic diseases of aging and earlier mortality. Identifying factors related to LTL among African Americans may yield insights into mechanisms underlying racial disparities in health. Purpose To test whether the combination of more frequent reports of racial discrimination and holding a greater implicit anti-black racial bias is associated with shorter LTL among African-American men. Methods Cross-sectional study of a community sample of 92 African-American men aged between 30 and 50 years. Participants were recruited from February to May 2010. Ordinary least squares regressions were used to examine LTL in kilobase pairs in relation to racial discrimination and implicit racial bias. Data analysis was completed in July 2013. Results After controlling for chronologic age, socioeconomic, and health-related characteristics, the interaction between racial discrimination and implicit racial bias was significantly associated with LTL (b= −0.10, SE=0.04, p=0.02). Those demonstrating a stronger implicit anti-black bias and reporting higher levels of racial discrimination had the shortest LTL. Household income-to-poverty threshold ratio was also associated with LTL (b=0.05, SE=0.02, p<0.01). Conclusions Results suggest that multiple levels of racism, including interpersonal experiences of racial discrimination and the internalization of negative racial bias, operate jointly to accelerate biological aging among African-American men. Societal efforts to address racial discrimination in concert with efforts to promote positive in-group racial attitudes may protect against premature biological aging in this population. PMID:24439343

How does bias correction of RCM precipitation affect modelled runoff?

NASA Astrophysics Data System (ADS)

Teng, J.; Potter, N. J.; Chiew, F. H. S.; Zhang, L.; Vaze, J.; Evans, J. P.

2014-09-01

Many studies bias correct daily precipitation from climate models to match the observed precipitation statistics, and the bias corrected data are then used for various modelling applications. This paper presents a review of recent methods used to bias correct precipitation from regional climate models (RCMs). The paper then assesses four bias correction methods applied to the weather research and forecasting (WRF) model simulated precipitation, and the follow-on impact on modelled runoff for eight catchments in southeast Australia. Overall, the best results are produced by either quantile mapping or a newly proposed two-state gamma distribution mapping method. However, the difference between the tested methods is small in the modelling experiments here (and as reported in the literature), mainly because of the substantial corrections required and inconsistent errors over time (non-stationarity). The errors remaining in bias corrected precipitation are typically amplified in modelled runoff. The tested methods cannot overcome limitation of RCM in simulating precipitation sequence, which affects runoff generation. Results further show that whereas bias correction does not seem to alter change signals in precipitation means, it can introduce additional uncertainty to change signals in high precipitation amounts and, consequently, in runoff. Future climate change impact studies need to take this into account when deciding whether to use raw or bias corrected RCM results. Nevertheless, RCMs will continue to improve and will become increasingly useful for hydrological applications as the bias in RCM simulations reduces.

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

Yield responses of wild C3 and C4 crop progenitors to subambient CO2 : a test for the role of CO2 limitation in the origin of agriculture.

PubMed

Cunniff, Jennifer; Jones, Glynis; Charles, Michael; Osborne, Colin P

2017-01-01

Limitation of plant productivity by the low partial pressure of atmospheric CO 2 (C a ) experienced during the last glacial period is hypothesized to have been an important constraint on the origins of agriculture. In support of this hypothesis, previous work has shown that glacial C a limits vegetative growth in the wild progenitors of both C 3 and C 4 founder crops. Here, we present data showing that glacial C a also reduces grain yield in both crop types. We grew four wild progenitors of C 3 (einkorn wheat and barley) and C 4 crops (foxtail and broomcorn millets) at glacial and postglacial C a , measuring grain yield and the morphological and physiological components contributing to these yield changes. The C 3 species showed a significant increase in unthreshed grain yield of ~50% with the glacial to postglacial increase in C a , which matched the stimulation of photosynthesis, suggesting that increases in photosynthesis are directly translated into yield at subambient levels of C a . Increased yield was controlled by a higher rate of tillering, leading to a larger number of tillers bearing fertile spikes, and increases in seed number and size. The C 4 species showed smaller, but significant, increases in grain yield of 10-15%, arising from larger seed numbers and sizes. Photosynthesis was enhanced by C a in only one C 4 species and the effect diminished during development, suggesting that an indirect mechanism mediated by plant water relations could also be playing a role in the yield increase. Interestingly, the C 4 species at glacial C a showed some evidence that photosynthetic capacity was upregulated to enhance carbon capture. Development under glacial C a also impacted negatively on the subsequent germination and viability of seeds. These results suggest that the grain production of both C 3 and C 4 crop progenitors was limited by the atmospheric conditions of the last glacial period, with important implications for the origins of agriculture. © 2016

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.

Anti-pointing is mediated by a perceptual bias of target location in left and right visual space.

PubMed

Heath, Matthew; Maraj, Anika; Gradkowski, Ashlee; Binsted, Gordon

2009-01-01

We sought to determine whether mirror-symmetrical limb movements (so-called anti-pointing) elicit a pattern of endpoint bias commensurate with perceptual judgments. In particular, we examined whether asymmetries related to the perceptual over- and under-estimation of target extent in respective left and right visual space impacts the trajectories of anti-pointing. In Experiment 1, participants completed direct (i.e. pro-pointing) and mirror-symmetrical (i.e. anti-pointing) responses to targets in left and right visual space with their right hand. In line with the anti-saccade literature, anti-pointing yielded longer reaction times than pro-pointing: a result suggesting increased top-down processing for the sensorimotor transformations underlying a mirror-symmetrical response. Most interestingly, pro-pointing yielded comparable endpoint accuracy in left and right visual space; however, anti-pointing produced an under- and overshooting bias in respective left and right visual space. In Experiment 2, we replicated the findings from Experiment 1 and further demonstrate that the endpoint bias of anti-pointing is independent of the reaching limb (i.e. left vs. right hand) and between-task differences in saccadic drive. We thus propose that the visual field-specific endpoint bias observed here is related to the cognitive (i.e. top-down) nature of anti-pointing and the corollary use of visuo-perceptual networks to support the sensorimotor transformations underlying such actions.

Evaluation of the CEAS model for barley yields in North Dakota and Minnesota

NASA Technical Reports Server (NTRS)

Barnett, T. L. (Principal Investigator)

1981-01-01

The CEAS yield model is based upon multiple regression analysis at the CRD and state levels. For the historical time series, yield is regressed on a set of variables derived from monthly mean temperature and monthly precipitation. Technological trend is represented by piecewise linear and/or quadriatic functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test (1970-79) demonstrated that biases are small and performance as indicated by the root mean square errors are acceptable for intended application, however, model response for individual years particularly unusual years, is not very reliable and shows some large errors. The model is objective, adequate, timely, simple and not costly. It considers scientific knowledge on a broad scale but not in detail, and does not provide a good current measure of modeled yield reliability.

Upper limits for the rate constant for the reaction Br + H2O2 yields HB2 + HO2

NASA Technical Reports Server (NTRS)

Leu, M.-T.

1980-01-01

Upper limits for the rate constant for the reaction Br + H2O2 yields HBr + HO2 have been measured over the temperature range 298 to 417 K in a discharge flow system using a mass spectrometer as a detector. Results are k sub 1 less than 1.5 x 10 to the -15th power cu cm/s at 298 K and k sub 1 less than 3.0 x 10 to the -15th power cu cm/s at 417 K, respectively. The implication to stratospheric chemistry is discussed.

Lost in translation: Review of identification bias, translation bias and research waste in dentistry.

PubMed

Layton, Danielle M; Clarke, Michael

2016-01-01

To review how articles are retrieved from bibliographic databases, what article identification and translation problems have affected research, and how these problems can contribute to research waste and affect clinical practice. This literature review sought and appraised articles regarding identification- and translation-bias in the medical and dental literature, which limit the ability of users to find research articles and to use these in practice. Articles can be retrieved from bibliographic databases by performing a word or index-term (for example, MeSH for MEDLINE) search. Identification of articles is challenging when it is not clear which words are most relevant, and which terms have been allocated to indexing fields. Poor reporting quality of abstracts and articles has been reported across the medical literature at large. Specifically in dentistry, research regarding time-to-event survival analyses found the allocation of MeSH terms to be inconsistent and inaccurate, important words were omitted from abstracts by authors, and the quality of reporting in the body of articles was generally poor. These shortcomings mean that articles will be difficult to identify, and difficult to understand if found. Use of specialized electronic search strategies can decrease identification bias, and use of tailored reporting guidelines can decrease translation bias. Research that cannot be found, or cannot be used results in research waste, and undermines clinical practice. Identification- and translation-bias have been shown to affect time-to-event dental articles, are likely affect other fields of research, and are largely unrecognized by authors and evidence seekers alike. By understanding that the problems exist, solutions can be sought to improve identification and translation of our research. Copyright © 2015 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Hyperdynamics boost factor achievable with an ideal bias potential

DOE PAGES

Huang, Chen; Perez, Danny; Voter, Arthur F.

2015-08-20

Hyperdynamics is a powerful method to significantly extend the time scales amenable to molecular dynamics simulation of infrequent events. One outstanding challenge, however, is the development of the so-called bias potential required by the method. In this work, we design a bias potential using information about all minimum energy pathways (MEPs) out of the current state. While this approach is not suitable for use in an actual hyperdynamics simulation, because the pathways are generally not known in advance, it allows us to show that it is possible to come very close to the theoretical boost limit of hyperdynamics while maintainingmore » high accuracy. We demonstrate this by applying this MEP-based hyperdynamics (MEP-HD) to metallic surface diffusion systems. In most cases, MEP-HD gives boost factors that are orders of magnitude larger than the best existing bias potential, indicating that further development of hyperdynamics bias potentials could have a significant payoff. Lastly, we discuss potential practical uses of MEP-HD, including the possibility of developing MEP-HD into a true hyperdynamics.« less

Toward a Comprehensive Understanding of Executive Cognitive Function in Implicit Racial Bias

PubMed Central

Ito, Tiffany A.; Friedman, Naomi P.; Bartholow, Bruce D.; Correll, Joshua; Loersch, Chris; Altamirano, Lee J.; Miyake, Akira

2014-01-01

Although performance on laboratory-based implicit bias tasks often is interpreted strictly in terms of the strength of automatic associations, recent evidence suggests that such tasks are influenced by higher-order cognitive control processes, so-called executive functions (EFs). However, extant work in this area has been limited by failure to account for the unity and diversity of EFs, focus on only a single measure of bias and/or EF, and relatively small sample sizes. The current study sought to comprehensively model the relation between individual differences in EFs and the expression of racial bias in three commonly used laboratory measures. Participants (N=485) completed a battery of EF tasks (session 1) and three racial bias tasks (session 2), along with numerous individual difference questionnaires. The main findings were as follows: (1) measures of implicit bias were only weakly intercorrelated; (2) EF and estimates of automatic processes both predicted implicit bias and also interacted, such that the relation between automatic processes and bias expression was reduced at higher levels of EF; (3) specific facets of EF were differentially associated with overall task performance and controlled processing estimates across different bias tasks; (4) EF did not moderate associations between implicit and explicit measures of bias; and (5) external, but not internal, motivation to control prejudice depended on EF to reduce bias expression. Findings are discussed in terms of the importance of global and specific EF abilities in determining expression of implicit racial bias. PMID:25603372

Redefining yield gaps at various spatial scales

NASA Astrophysics Data System (ADS)

Meng, K.; Fishman, R.; Norstrom, A. V.; Diekert, F. K.; Engstrom, G.; Gars, J.; McCarney, G. R.; Sjostedt, M.

2013-12-01

Recent research has highlighted the prevalence of 'yield gaps' around the world and the importance of closing them for global food security. However, the traditional concept of yield gap -defined as the difference between observed and optimal yield under biophysical conditions - omit relevant socio-economic and ecological constraints and thus offer limited guidance on potential policy interventions. This paper proposes alternative definitions of yield gaps by incorporating rich, high resolution, national and sub-national agricultural datasets. We examine feasible efforts to 'close yield gaps' at various spatial scales and across different socio-economic and ecological domains.

Interactions between plant nutrients, water and carbon dioxide as factors limiting crop yields

PubMed Central

Gregory, P. J.; Simmonds, L. P.; Warren, G. P.

1997-01-01

Biomass production of annual crops is often directly proportional to the amounts of radiation intercepted, water transpired and nutrients taken up. In many places the amount of rainfall during the period of rapid crop growth is less than the potential rate of evaporation, so that depletion of stored soil water is commonplace. The rate of mineralization of nitrogen (N) from organic matter and the processes of nutrient loss are closely related to the availability of soil water. Results from Kenya indicate the rapid changes in nitrate availability following rain.
Nutrient supply has a large effect on the quantity of radiation intercepted and hence, biomass production. There is considerable scope for encouraging canopy expansion to conserve water by reducing evaporation from the soil surface in environments where it is frequently rewetted, and where the unsaturated hydraulic conductivity of the soil is sufficient to supply water at the energy limited rate (e.g. northern Syria). In regions with high evaporative demand and coarse-textured soils (e.g. Niger), transpiration may be increased by management techniques that reduce drainage.
Increases in atmospheric [CO2] are likely to have only a small impact on crop yields when allowance is made for the interacting effects of temperature, and water and nutrient supply.

Positional bias in variant calls against draft reference assemblies.

PubMed

Briskine, Roman V; Shimizu, Kentaro K

2017-03-28

Whole genome resequencing projects may implement variant calling using draft reference genomes assembled de novo from short-read libraries. Despite lower quality of such assemblies, they allowed researchers to extend a wide range of population genetic and genome-wide association analyses to non-model species. As the variant calling pipelines are complex and involve many software packages, it is important to understand inherent biases and limitations at each step of the analysis. In this article, we report a positional bias present in variant calling performed against draft reference assemblies constructed from de Bruijn or string overlap graphs. We assessed how frequently variants appeared at each position counted from ends of a contig or scaffold sequence, and discovered unexpectedly high number of variants at the positions related to the length of either k-mers or reads used for the assembly. We detected the bias in both publicly available draft assemblies from Assemblathon 2 competition as well as in the assemblies we generated from our simulated short-read data. Simulations confirmed that the bias causing variants are predominantly false positives induced by reads from spatially distant repeated sequences. The bias is particularly strong in contig assemblies. Scaffolding does not eliminate the bias but tends to mitigate it because of the changes in variants' relative positions and alterations in read alignments. The bias can be effectively reduced by filtering out the variants that reside in repetitive elements. Draft genome sequences generated by several popular assemblers appear to be susceptible to the positional bias potentially affecting many resequencing projects in non-model species. The bias is inherent to the assembly algorithms and arises from their particular handling of repeated sequences. It is recommended to reduce the bias by filtering especially if higher-quality genome assembly cannot be achieved. Our findings can help other researchers to

Effects of standard and explicit cognitive bias modification and computer-administered cognitive-behaviour therapy on cognitive biases and social anxiety☆

PubMed Central

Mobini, Sirous; Mackintosh, Bundy; Illingworth, Jo; Gega, Lina; Langdon, Peter; Hoppitt, Laura

2014-01-01

Background and objectives This study examines the effects of a single session of Cognitive Bias Modification to induce positive Interpretative bias (CBM-I) using standard or explicit instructions and an analogue of computer-administered CBT (c-CBT) program on modifying cognitive biases and social anxiety. Methods A sample of 76 volunteers with social anxiety attended a research site. At both pre- and post-test, participants completed two computer-administered tests of interpretative and attentional biases and a self-report measure of social anxiety. Participants in the training conditions completed a single session of either standard or explicit CBM-I positive training and a c-CBT program. Participants in the Control (no training) condition completed a CBM-I neutral task matched the active CBM-I intervention in format and duration but did not encourage positive disambiguation of socially ambiguous or threatening scenarios. Results Participants in both CBM-I programs (either standard or explicit instructions) and the c-CBT condition exhibited more positive interpretations of ambiguous social scenarios at post-test and one-week follow-up as compared to the Control condition. Moreover, the results showed that CBM-I and c-CBT, to some extent, changed negative attention biases in a positive direction. Furthermore, the results showed that both CBM-I training conditions and c-CBT reduced social anxiety symptoms at one-week follow-up. Limitations This study used a single session of CBM-I training, however multi-sessions intervention might result in more endurable positive CBM-I changes. Conclusions A computerised single session of CBM-I and an analogue of c-CBT program reduced negative interpretative biases and social anxiety. PMID:24412966

Potential fitting biases resulting from grouping data into variable width bins

NASA Astrophysics Data System (ADS)

Towers, S.

2014-07-01

When reading peer-reviewed scientific literature describing any analysis of empirical data, it is natural and correct to proceed with the underlying assumption that experiments have made good faith efforts to ensure that their analyses yield unbiased results. However, particle physics experiments are expensive and time consuming to carry out, thus if an analysis has inherent bias (even if unintentional), much money and effort can be wasted trying to replicate or understand the results, particularly if the analysis is fundamental to our understanding of the universe. In this note we discuss the significant biases that can result from data binning schemes. As we will show, if data are binned such that they provide the best comparison to a particular (but incorrect) model, the resulting model parameter estimates when fitting to the binned data can be significantly biased, leading us to too often accept the model hypothesis when it is not in fact true. When using binned likelihood or least squares methods there is of course no a priori requirement that data bin sizes need to be constant, but we show that fitting to data grouped into variable width bins is particularly prone to produce biased results if the bin boundaries are chosen to optimize the comparison of the binned data to a wrong model. The degree of bias that can be achieved simply with variable binning can be surprisingly large. Fitting the data with an unbinned likelihood method, when possible to do so, is the best way for researchers to show that their analyses are not biased by binning effects. Failing that, equal bin widths should be employed as a cross-check of the fitting analysis whenever possible.

The relationship between attentional bias toward safety and driving behavior.

PubMed

Zheng, Tingting; Qu, Weina; Zhang, Kan; Ge, Yan

2016-11-01

As implicit cognitive processes garner more and more importance, studies in the fields of healthy psychology and organizational safety research have focused on attentional bias, a kind of selective allocation of attentional resources in the early stage of cognitive processing. However, few studies have explored the role of attentional bias on driving behavior. This study assessed drivers' attentional bias towards safety-related words (ABS) using the dot-probe paradigm and self-reported daily driving behaviors. The results revealed significant negative correlations between attentional bias scores and several indicators of dangerous driving. Drivers with fewer dangerous driving behaviors showed greater ABS. We also built a significant linear regression model between ABS and the total DDDI score, as well as ABS and the number of accidents. Finally, we discussed the possible mechanism underlying these associations and several limitations of our study. This study opens up a new topic for the exploration of implicit processes in driving safety research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Digital droplet multiple displacement amplification (ddMDA) for whole genome sequencing of limited DNA samples

DOE PAGES

Rhee, Minsoung; Light, Yooli K.; Meagher, Robert J.; ...

2016-05-04

Here, multiple displacement amplification (MDA) is a widely used technique for amplification of DNA from samples containing limited amounts of DNA (e.g., uncultivable microbes or clinical samples) before whole genome sequencing. Despite its advantages of high yield and fidelity, it suffers from high amplification bias and non-specific amplification when amplifying sub-nanogram of template DNA. Here, we present a microfluidic digital droplet MDA (ddMDA) technique where partitioning of the template DNA into thousands of sub-nanoliter droplets, each containing a small number of DNA fragments, greatly reduces the competition among DNA fragments for primers and polymerase thereby greatly reducing amplification bias. Consequently,more » the ddMDA approach enabled a more uniform coverage of amplification over the entire length of the genome, with significantly lower bias and non-specific amplification than conventional MDA. For a sample containing 0.1 pg/μL of E. coli DNA (equivalent of ~3/1000 of an E. coli genome per droplet), ddMDA achieves a 65-fold increase in coverage in de novo assembly, and more than 20-fold increase in specificity (percentage of reads mapping to E. coli) compared to the conventional tube MDA. ddMDA offers a powerful method useful for many applications including medical diagnostics, forensics, and environmental microbiology.« less

Digital droplet multiple displacement amplification (ddMDA) for whole genome sequencing of limited DNA samples

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

Rhee, Minsoung; Light, Yooli K.; Meagher, Robert J.

Here, multiple displacement amplification (MDA) is a widely used technique for amplification of DNA from samples containing limited amounts of DNA (e.g., uncultivable microbes or clinical samples) before whole genome sequencing. Despite its advantages of high yield and fidelity, it suffers from high amplification bias and non-specific amplification when amplifying sub-nanogram of template DNA. Here, we present a microfluidic digital droplet MDA (ddMDA) technique where partitioning of the template DNA into thousands of sub-nanoliter droplets, each containing a small number of DNA fragments, greatly reduces the competition among DNA fragments for primers and polymerase thereby greatly reducing amplification bias. Consequently,more » the ddMDA approach enabled a more uniform coverage of amplification over the entire length of the genome, with significantly lower bias and non-specific amplification than conventional MDA. For a sample containing 0.1 pg/μL of E. coli DNA (equivalent of ~3/1000 of an E. coli genome per droplet), ddMDA achieves a 65-fold increase in coverage in de novo assembly, and more than 20-fold increase in specificity (percentage of reads mapping to E. coli) compared to the conventional tube MDA. ddMDA offers a powerful method useful for many applications including medical diagnostics, forensics, and environmental microbiology.« less

Do horses with poor welfare show 'pessimistic' cognitive biases?

PubMed

Henry, S; Fureix, C; Rowberry, R; Bateson, M; Hausberger, M

2017-02-01

This field study tested the hypothesis that domestic horses living under putatively challenging-to-welfare conditions (for example involving social, spatial, feeding constraints) would present signs of poor welfare and co-occurring pessimistic judgement biases. Our subjects were 34 horses who had been housed for over 3 years in either restricted riding school situations (e.g. kept in single boxes, with limited roughage, ridden by inexperienced riders; N = 25) or under more naturalistic conditions (e.g. access to free-range, kept in stable social groups, leisure riding; N = 9). The horses' welfare was assessed by recording health-related, behavioural and postural indicators. Additionally, after learning a location task to discriminate a bucket containing either edible food ('positive' location) or unpalatable food ('negative' location), the horses were presented with a bucket located near the positive position, near the negative position and halfway between the positive and negative positions to assess their judgement biases. The riding school horses displayed the highest levels of behavioural and health-related problems and a pessimistic judgment bias, whereas the horses living under more naturalistic conditions displayed indications of good welfare and an optimistic bias. Moreover, pessimistic bias data strongly correlated with poor welfare data. This suggests that a lowered mood impacts a non-human species' perception of its environment and highlights cognitive biases as an appropriate tool to assess the impact of chronic living conditions on horse welfare.

Do horses with poor welfare show `pessimistic' cognitive biases?

NASA Astrophysics Data System (ADS)

Henry, S.; Fureix, C.; Rowberry, R.; Bateson, M.; Hausberger, M.

2017-02-01

This field study tested the hypothesis that domestic horses living under putatively challenging-to-welfare conditions (for example involving social, spatial, feeding constraints) would present signs of poor welfare and co-occurring pessimistic judgement biases. Our subjects were 34 horses who had been housed for over 3 years in either restricted riding school situations ( e.g. kept in single boxes, with limited roughage, ridden by inexperienced riders; N = 25) or under more naturalistic conditions ( e.g. access to free-range, kept in stable social groups, leisure riding; N = 9). The horses' welfare was assessed by recording health-related, behavioural and postural indicators. Additionally, after learning a location task to discriminate a bucket containing either edible food (`positive' location) or unpalatable food (`negative' location), the horses were presented with a bucket located near the positive position, near the negative position and halfway between the positive and negative positions to assess their judgement biases. The riding school horses displayed the highest levels of behavioural and health-related problems and a pessimistic judgment bias, whereas the horses living under more naturalistic conditions displayed indications of good welfare and an optimistic bias. Moreover, pessimistic bias data strongly correlated with poor welfare data. This suggests that a lowered mood impacts a non-human species' perception of its environment and highlights cognitive biases as an appropriate tool to assess the impact of chronic living conditions on horse welfare.

A question of separation: disentangling tracer bias and gravitational non-linearity with counts-in-cells statistics

NASA Astrophysics Data System (ADS)

Uhlemann, C.; Feix, M.; Codis, S.; Pichon, C.; Bernardeau, F.; L'Huillier, B.; Kim, J.; Hong, S. E.; Laigle, C.; Park, C.; Shin, J.; Pogosyan, D.

2018-02-01

Starting from a very accurate model for density-in-cells statistics of dark matter based on large deviation theory, a bias model for the tracer density in spheres is formulated. It adopts a mean bias relation based on a quadratic bias model to relate the log-densities of dark matter to those of mass-weighted dark haloes in real and redshift space. The validity of the parametrized bias model is established using a parametrization-independent extraction of the bias function. This average bias model is then combined with the dark matter PDF, neglecting any scatter around it: it nevertheless yields an excellent model for densities-in-cells statistics of mass tracers that is parametrized in terms of the underlying dark matter variance and three bias parameters. The procedure is validated on measurements of both the one- and two-point statistics of subhalo densities in the state-of-the-art Horizon Run 4 simulation showing excellent agreement for measured dark matter variance and bias parameters. Finally, it is demonstrated that this formalism allows for a joint estimation of the non-linear dark matter variance and the bias parameters using solely the statistics of subhaloes. Having verified that galaxy counts in hydrodynamical simulations sampled on a scale of 10 Mpc h-1 closely resemble those of subhaloes, this work provides important steps towards making theoretical predictions for density-in-cells statistics applicable to upcoming galaxy surveys like Euclid or WFIRST.

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

DOE PAGES

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

2017-12-01

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 subhalomore » 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. Lastly, 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.« less

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

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

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

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 subhalomore » 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. Lastly, 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.« less

Discrimination, racial bias, and telomere length in African-American men.

PubMed

Chae, David H; Nuru-Jeter, Amani M; Adler, Nancy E; Brody, Gene H; Lin, Jue; Blackburn, Elizabeth H; Epel, Elissa S

2014-02-01

Leukocyte telomere length (LTL) is an indicator of general systemic aging, with shorter LTL being associated with several chronic diseases of aging and earlier mortality. Identifying factors related to LTL among African Americans may yield insights into mechanisms underlying racial disparities in health. To test whether the combination of more frequent reports of racial discrimination and holding a greater implicit anti-black racial bias is associated with shorter LTL among African-American men. Cross-sectional study of a community sample of 92 African-American men aged between 30 and 50 years. Participants were recruited from February to May 2010. Ordinary least squares regressions were used to examine LTL in kilobase pairs in relation to racial discrimination and implicit racial bias. Data analysis was completed in July 2013. After controlling for chronologic age and socioeconomic and health-related characteristics, the interaction between racial discrimination and implicit racial bias was significantly associated with LTL (b=-0.10, SE=0.04, p=0.02). Those demonstrating a stronger implicit anti-black bias and reporting higher levels of racial discrimination had the shortest LTL. Household income-to-poverty threshold ratio was also associated with LTL (b=0.05, SE=0.02, p<0.01). Results suggest that multiple levels of racism, including interpersonal experiences of racial discrimination and the internalization of negative racial bias, operate jointly to accelerate biological aging among African-American men. Societal efforts to address racial discrimination in concert with efforts to promote positive in-group racial attitudes may protect against premature biological aging in this population. © 2013 American Journal of Preventive Medicine Published by American Journal of Preventive Medicine All rights reserved.

Toward a comprehensive understanding of executive cognitive function in implicit racial bias.

PubMed

Ito, Tiffany A; Friedman, Naomi P; Bartholow, Bruce D; Correll, Joshua; Loersch, Chris; Altamirano, Lee J; Miyake, Akira

2015-02-01

Although performance on laboratory-based implicit bias tasks often is interpreted strictly in terms of the strength of automatic associations, recent evidence suggests that such tasks are influenced by higher-order cognitive control processes, so-called executive functions (EFs). However, extant work in this area has been limited by failure to account for the unity and diversity of EFs, focus on only a single measure of bias and/or EF, and relatively small sample sizes. The current study sought to comprehensively model the relation between individual differences in EFs and the expression of racial bias in 3 commonly used laboratory measures. Participants (N = 485) completed a battery of EF tasks (Session 1) and 3 racial bias tasks (Session 2), along with numerous individual difference questionnaires. The main findings were as follows: (a) measures of implicit bias were only weakly intercorrelated; (b) EF and estimates of automatic processes both predicted implicit bias and also interacted, such that the relation between automatic processes and bias expression was reduced at higher levels of EF; (c) specific facets of EF were differentially associated with overall task performance and controlled processing estimates across different bias tasks; (d) EF did not moderate associations between implicit and explicit measures of bias; and (e) external, but not internal, motivation to control prejudice depended on EF to reduce bias expression. Findings are discussed in terms of the importance of global and specific EF abilities in determining expression of implicit racial bias. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Adjustable direct current and pulsed circuit fault current limiter

DOEpatents

Boenig, Heinrich J.; Schillig, Josef B.

2003-09-23

A fault current limiting system for direct current circuits and for pulsed power circuit. In the circuits, a current source biases a diode that is in series with the circuits' transmission line. If fault current in a circuit exceeds current from the current source biasing the diode open, the diode will cease conducting and route the fault current through the current source and an inductor. This limits the rate of rise and the peak value of the fault current.

An analytical expression for ion velocities at the wall including the sheath electric field and surface biasing for erosion modeling at JET ILW

DOE PAGES

Borodkina, I.; Borodin, D.; Brezinsek, S.; ...

2017-04-12

For simulation of plasma-facing component erosion in fusion experiments, an analytical expression for the ion velocity just before the surface impact including the local electric field and an optional surface biasing effect is suggested. Energy and angular impact distributions and the resulting effective sputtering yields were produced for several experimental scenarios at JET ILW mostly involving PFCs exposed to an oblique magnetic field. The analytic solution has been applied as an improvement to earlier ERO modelling of localized, Be outer limiter, RF-enhanced erosion, modulated by toggling of a remote, however magnetically connected ICRH antenna. The effective W sputtering yields duemore » to D and Be ion impact in Type-I and Type-III ELMs and inter-ELM conditions were also estimated using the analytical approach and benchmarked by spectroscopy. The intra-ELM W sputtering flux increases almost 10 times in comparison to the inter-ELM flux.« less

Health benefits offer rates: is there a nonresponse bias?

PubMed

Pickreign, Jeremy D; Gabel, Jon R

2005-04-01

To determine whether a nonresponse bias exists in the offer rate for health benefits in firms with fewer than 50 workers and to present a simple adjustment to correct for observed bias. The 2003 Employer Health Benefits Survey (EHBS) conducted by the Kaiser Family Foundation and Health Research and Educational Trust, and a follow-up survey of nonrespondents to the 2003 EHBS. We conducted a follow-up survey to the 2003 EHBS to collect health benefits offering data from firms with fewer than 50 workers. We used McNemar's test to verify that the follow-up survey provided results comparable to the EHBS, and t-tests were used to determine nonresponse bias. We applied a simple weighting adjustment to the EHBS. The data for both the EHBS and the follow-up survey were collected by the same survey research firm. The EHBS interviews the person most knowledgeable about the firm's health benefits, while the follow-up survey interviews the first person who answers the telephone whether they are the most knowledgeable or not. Principal Findings. Firms with 3-9 workers were more likely to exhibit a bias than were firms with 10-24 workers and 25-49 workers. Although the calculated bias for each size category was not significant, there is sufficient evidence to warrant caution when reporting offer rates. Survey nonresponse in the EHBS produces an upward bias on estimates for the offer rates of small firms. Although not significant, this upward bias is because of nonresponse by small firms that do not offer health benefits. Our research is limited in that we only control for differences in the size of the firm.

Free energy calculations: an efficient adaptive biasing potential method.

PubMed

Dickson, Bradley M; Legoll, Frédéric; Lelièvre, Tony; Stoltz, Gabriel; Fleurat-Lessard, Paul

2010-05-06

We develop an efficient sampling and free energy calculation technique within the adaptive biasing potential (ABP) framework. By mollifying the density of states we obtain an approximate free energy and an adaptive bias potential that is computed directly from the population along the coordinates of the free energy. Because of the mollifier, the bias potential is "nonlocal", and its gradient admits a simple analytic expression. A single observation of the reaction coordinate can thus be used to update the approximate free energy at every point within a neighborhood of the observation. This greatly reduces the equilibration time of the adaptive bias potential. This approximation introduces two parameters: strength of mollification and the zero of energy of the bias potential. While we observe that the approximate free energy is a very good estimate of the actual free energy for a large range of mollification strength, we demonstrate that the errors associated with the mollification may be removed via deconvolution. The zero of energy of the bias potential, which is easy to choose, influences the speed of convergence but not the limiting accuracy. This method is simple to apply to free energy or mean force computation in multiple dimensions and does not involve second derivatives of the reaction coordinates, matrix manipulations nor on-the-fly adaptation of parameters. For the alanine dipeptide test case, the new method is found to gain as much as a factor of 10 in efficiency as compared to two basic implementations of the adaptive biasing force methods, and it is shown to be as efficient as well-tempered metadynamics with the postprocess deconvolution giving a clear advantage to the mollified density of states method.

Weight bias in work settings - a qualitative review.

PubMed

Giel, Katrin Elisabeth; Thiel, Ansgar; Teufel, Martin; Mayer, Jochen; Zipfel, Stephan

2010-02-01

Studies have repeatedly demonstrated the influence of physical appearance on behavior and treatment of individuals in work settings. A high proportion of obese individuals in the USA have reported perceived discrimination in the work place due to their body weight. The present review examines the specific kind, context and extent of a weight bias in work settings. We performed a literature search in the scientific databases PubMed and PsychINFO to identify studies which have investigated aspects of a potential weight bias in the occupational context. There is evidence from self-report data, surveys, and laboratory research for a weight bias in five aspects of work life. Evidence shows that obesity is a general barrier to employment, certain professions and professional success. Obese individuals are at higher risk of encountering stereotypes concerning their work-related qualities and for general unequal treatment in the work place. Current evidence reveals a weight bias in several areas in the work place. The ecological validity of results is limited due to the predominant reliance on laboratory studies with student samples. Field studies are needed to examine weight-based discrimination in actual work environments as well as to uncover underlying mechanisms. Copyright 2010 S. Karger AG, Basel.

Evaluation of the Williams-type model for barley yields in North Dakota and Minnesota

NASA Technical Reports Server (NTRS)

Barnett, T. L. (Principal Investigator)

1981-01-01

The Williams-type yield model is based on multiple regression analysis of historial time series data at CRD level pooled to regional level (groups of similar CRDs). Basic variables considered in the analysis include USDA yield, monthly mean temperature, monthly precipitation, soil texture and topographic information, and variables derived from these. Technologic trend is represented by piecewise linear and/or quadratic functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test (1970-1979) demonstrate that biases are small and performance based on root mean square appears to be acceptable for the intended AgRISTARS large area applications. The model is objective, adequate, timely, simple, and not costly. It consideres scientific knowledge on a broad scale but not in detail, and does not provide a good current measure of modeled yield reliability.

Interpretation biases in paranoia.

PubMed

Savulich, George; Freeman, Daniel; Shergill, Sukhi; Yiend, Jenny

2015-01-01

Information in the environment is frequently ambiguous in meaning. Emotional ambiguity, such as the stare of a stranger, or the scream of a child, encompasses possible good or bad emotional consequences. Those with elevated vulnerability to affective disorders tend to interpret such material more negatively than those without, a phenomenon known as "negative interpretation bias." In this study we examined the relationship between vulnerability to psychosis, measured by trait paranoia, and interpretation bias. One set of material permitted broadly positive/negative (valenced) interpretations, while another allowed more or less paranoid interpretations, allowing us to also investigate the content specificity of interpretation biases associated with paranoia. Regression analyses (n=70) revealed that trait paranoia, trait anxiety, and cognitive inflexibility predicted paranoid interpretation bias, whereas trait anxiety and cognitive inflexibility predicted negative interpretation bias. In a group comparison those with high levels of trait paranoia were negatively biased in their interpretations of ambiguous information relative to those with low trait paranoia, and this effect was most pronounced for material directly related to paranoid concerns. Together these data suggest that a negative interpretation bias occurs in those with elevated vulnerability to paranoia, and that this bias may be strongest for material matching paranoid beliefs. We conclude that content-specific biases may be important in the cause and maintenance of paranoid symptoms. Copyright © 2014. Published by Elsevier Ltd.

Perceptual and Gaze Biases during Face Processing: Related or Not?

PubMed Central

Samson, Hélène; Fiori-Duharcourt, Nicole; Doré-Mazars, Karine; Lemoine, Christelle; Vergilino-Perez, Dorine

2014-01-01

Previous studies have demonstrated a left perceptual bias while looking at faces, due to the fact that observers mainly use information from the left side of a face (from the observer's point of view) to perform a judgment task. Such a bias is consistent with the right hemisphere dominance for face processing and has sometimes been linked to a left gaze bias, i.e. more and/or longer fixations on the left side of the face. Here, we recorded eye-movements, in two different experiments during a gender judgment task, using normal and chimeric faces which were presented above, below, right or left to the central fixation point or on it (central position). Participants performed the judgment task by remaining fixated on the fixation point or after executing several saccades (up to three). A left perceptual bias was not systematically found as it depended on the number of allowed saccades and face position. Moreover, the gaze bias clearly depended on the face position as the initial fixation was guided by face position and landed on the closest half-face, toward the center of gravity of the face. The analysis of the subsequent fixations revealed that observers move their eyes from one side to the other. More importantly, no apparent link between gaze and perceptual biases was found here. This implies that we do not look necessarily toward the side of the face that we use to make a gender judgment task. Despite the fact that these results may be limited by the absence of perceptual and gaze biases in some conditions, we emphasized the inter-individual differences observed in terms of perceptual bias, hinting at the importance of performing individual analysis and drawing attention to the influence of the method used to study this bias. PMID:24454927

PEAK LIMITING AMPLIFIER

DOEpatents

Goldsworthy, W.W.; Robinson, J.B.

1959-03-31

A peak voltage amplitude limiting system adapted for use with a cascade type amplifier is described. In its detailed aspects, the invention includes an amplifier having at least a first triode tube and a second triode tube, the cathode of the second tube being connected to the anode of the first tube. A peak limiter triode tube has its control grid coupled to thc anode of the second tube and its anode connected to the cathode of the second tube. The operation of the limiter is controlled by a bias voltage source connected to the control grid of the limiter tube and the output of the system is taken from the anode of the second tube.

Beyond attentional bias: a perceptual bias in a dot-probe task.

PubMed

Bocanegra, Bruno R; Huijding, Jorg; Zeelenberg, René

2012-12-01

Previous dot-probe studies indicate that threat-related face cues induce a bias in spatial attention. Independently of spatial attention, a recent psychophysical study suggests that a bilateral fearful face cue improves low spatial-frequency perception (LSF) and impairs high spatial-frequency perception (HSF). Here, we combine these separate lines of research within a single dot-probe paradigm. We found that a bilateral fearful face cue, compared with a bilateral neutral face cue, speeded up responses to LSF targets and slowed down responses to HSF targets. This finding is important, as it shows that emotional cues in dot-probe tasks not only bias where information is preferentially processed (i.e., an attentional bias in spatial location), but also bias what type of information is preferentially processed (i.e., a perceptual bias in spatial frequency). PsycINFO Database Record (c) 2012 APA, all rights reserved.

Avoiding Unintended Bias

PubMed Central

VAN RYN, MICHELLE

2017-01-01

Research shows that unintentional bias on the part of physicians can influence the way they treat patients from certain racial and ethnic groups. Most physicians are unaware that they hold such biases, which can unknowingly contribute to inequalities in health care delivery. This article explains why a person’s thoughts and behaviors may not align, and provides strategies for preventing implicit biases from interfering with patient care. PMID:27089675

Challenges of Guarantee-Time Bias

PubMed Central

Giobbie-Hurder, Anita; Gelber, Richard D.; Regan, Meredith M.

2013-01-01

The potential for guarantee-time bias (GTB), also known as immortal time bias, exists whenever an analysis that is timed from enrollment or random assignment, such as disease-free or overall survival, is compared across groups defined by a classifying event occurring sometime during follow-up. The types of events associated with GTB are varied and may include the occurrence of objective disease response, onset of toxicity, or seroconversion. However, comparative analyses using these types of events as predictors are different from analyses using baseline characteristics that are specified completely before the occurrence of any outcome event. Recognizing the potential for GTB is not always straightforward, and it can be challenging to know when GTB is influencing the results of an analysis. This article defines GTB, provides examples of GTB from several published articles, and discusses three analytic techniques that can be used to remove the bias: conditional landmark analysis, extended Cox model, and inverse probability weighting. The strengths and limitations of each technique are presented. As an example, we explore the effect of bisphosphonate use on disease-free survival (DFS) using data from the BIG (Breast International Group) 1-98 randomized clinical trial. An analysis using a naive approach showed substantial benefit for patients who received bisphosphonate therapy. In contrast, analyses using the three methods known to remove GTB showed no statistical evidence of a reduction in risk of a DFS event with bisphosphonate therapy. PMID:23835712

Investigating the 'jumping to conclusions' bias in people with anorexia nervosa.

PubMed

McKenna, Gráinne; Fox, John R E; Haddock, Gillian

2014-09-01

'Jumping to conclusions' (JTC) is an established reasoning bias in people with psychosis and delusion proneness. Research investigating the JTC bias in other clinical populations remains in its infancy. This study investigated whether individuals with anorexia (AN) displayed the JTC bias compared with healthy controls and, if so, whether the bias was greater in relation to emotionally salient information. The study also investigated whether delusionality was correlated with the JTC bias. JTC was measured using the 'beads task'. Three versions were employed: the standard version and two emotionally salient tasks. Results indicated that a majority (55.6%) of people with AN (n=26) displayed poor insight into their eating disorder beliefs but did not display an elevated JTC compared with healthy controls (n=33) on any task. The level of delusionality in the AN group was not correlated with JTC bias. Findings suggest that although a majority of people with AN demonstrated limited insight, they did not display the JTC bias. This may suggest that poor insight in eating disorders has different characteristics to that found in psychotic disorders, which may suggest that differences are needed in relation to how they are treated using psychological means. However, this was a small study, and study replication is required. Copyright © 2014 John Wiley & Sons, Ltd and Eating Disorders Association.

Tools for assessing risk of reporting biases in studies and syntheses of studies: a systematic review

PubMed Central

Page, Matthew J; McKenzie, Joanne E; Higgins, Julian P T

2018-01-01

Background Several scales, checklists and domain-based tools for assessing risk of reporting biases exist, but it is unclear how much they vary in content and guidance. We conducted a systematic review of the content and measurement properties of such tools. Methods We searched for potentially relevant articles in Ovid MEDLINE, Ovid Embase, Ovid PsycINFO and Google Scholar from inception to February 2017. One author screened all titles, abstracts and full text articles, and collected data on tool characteristics. Results We identified 18 tools that include an assessment of the risk of reporting bias. Tools varied in regard to the type of reporting bias assessed (eg, bias due to selective publication, bias due to selective non-reporting), and the level of assessment (eg, for the study as a whole, a particular result within a study or a particular synthesis of studies). Various criteria are used across tools to designate a synthesis as being at ‘high’ risk of bias due to selective publication (eg, evidence of funnel plot asymmetry, use of non-comprehensive searches). However, the relative weight assigned to each criterion in the overall judgement is unclear for most of these tools. Tools for assessing risk of bias due to selective non-reporting guide users to assess a study, or an outcome within a study, as ‘high’ risk of bias if no results are reported for an outcome. However, assessing the corresponding risk of bias in a synthesis that is missing the non-reported outcomes is outside the scope of most of these tools. Inter-rater agreement estimates were available for five tools. Conclusion There are several limitations of existing tools for assessing risk of reporting biases, in terms of their scope, guidance for reaching risk of bias judgements and measurement properties. Development and evaluation of a new, comprehensive tool could help overcome present limitations. PMID:29540417

Charge Yield at Low Electric Fields: Considerations for Bipolar Integrated Circuits

NASA Technical Reports Server (NTRS)

Johnston, A. H.; Swimm, R. T.; Thorbourn, D. O.

2013-01-01

A significant reduction in total dose damage is observed when bipolar integrated circuits are irradiated at low temperature. This can be partially explained by the Onsager theory of recombination, which predicts a strong temperature dependence for charge yield under low-field conditions. Reduced damage occurs for biased as well as unbiased devices because the weak fringing field in thick bipolar oxides only affects charge yield near the Si/SiO2 interface, a relatively small fraction of the total oxide thickness. Lowering the temperature of bipolar ICs - either continuously, or for time periods when they are exposed to high radiation levels - provides an additional degree of freedom to improve total dose performance of bipolar circuits, particularly in space applications.

Expectancy biases in fear and anxiety and their link to biases in attention.

PubMed

Aue, Tatjana; Okon-Singer, Hadas

2015-12-01

Healthy individuals often exhibit prioritized processing of aversive information, as manifested in enhanced orientation of attention to threatening stimuli compared with neutral items. In contrast to this adaptive behavior, anxious, fearful, and phobic individuals show exaggerated attention biases to threat. In addition, they overestimate the likelihood of encountering their feared stimulus and the severity of the consequences; both are examples of expectancy biases. The co-occurrence of attention and expectancy biases in fear and anxiety raises the question about causal influences. Herein, we summarize findings related to expectancy biases in fear and anxiety, and their association with attention biases. We suggest that evidence calls for more comprehensive research strategies in the investigation of mutual influences between expectancy and attention biases, as well as their combined effects on fear and anxiety. Moreover, both types of bias need to be related to other types of distorted information processing commonly observed in fear and anxiety (e.g., memory and interpretation biases). Finally, we propose new research directions that may be worth considering in developing more effective treatments for anxiety disorders. Copyright © 2015 Elsevier Ltd. All rights reserved.

Importance of understanding landscape biases in USGS gage locations: Implications and solutions for managers

USGS Publications Warehouse

Wagner, Tyler; DeWeber, Jefferson Tyrell; Tsang, Yin-Phan; Krueger, Damon; Whittier, Joanna B.; Infante, Dana M.; Whelan, Gary

2014-01-01

Flow and water temperature are fundamental properties of stream ecosystems upon which many freshwater resource management decisions are based. U.S. Geological Survey (USGS) gages are the most important source of streamflow and water temperature data available nationwide, but the degree to which gages represent landscape attributes of the larger population of streams has not been thoroughly evaluated. We identified substantial biases for seven landscape attributes in one or more regions across the conterminous United States. Streams with small watersheds (<10 km2) and at high elevations were often underrepresented, and biases were greater for water temperature gages and in arid regions. Biases can fundamentally alter management decisions and at a minimum this potential for error must be acknowledged accurately and transparently. We highlight three strategies that seek to reduce bias or limit errors arising from bias and illustrate how one strategy, supplementing USGS data, can greatly reduce bias.

Attention and interpretation bias modification treatment for social anxiety disorder: A randomized clinical trial of efficacy and synergy.

PubMed

Naim, Reut; Kivity, Yogev; Bar-Haim, Yair; Huppert, Jonathan D

2018-06-01

Attention bias modification treatment (ABMT) and cognitive bias modification of interpretation (CBM-I) both have demonstrated efficacy in alleviating social anxiety, but how they compare with each other, their combination, and with a combined control condition has not been studied. We examined their relative and combined efficacy compared to control conditions in a randomized controlled trial (RCT). Ninety-five adults diagnosed with social anxiety disorder (SAD), were randomly allocated to 4 groups: ABMT + CBM-I control (hereafter ABMT; n = 23), CBM-I + ABMT control (hereafter CBM-I; n = 24), combined ABMT + CBM-I (n = 23), and combined control (n = 25). Treatment included eight sessions over four weeks. Clinician-rated and self-reported measures of social anxiety symptoms, functional impairment, and threat-related attention and interpretive biases were evaluated at baseline, post-treatment, and 3-month follow-up. ABMT yielded greater symptom reduction as measured by both clinician-ratings (Cohen's ds = 0.57-0.70) and self-reports (ds = 0.70-0.85) compared with the CBM-I, the combined ABMT + CBM-I, and the combined control conditions. Neither of the other conditions demonstrated superior symptom change compared to the control condition. No group differences were found for functioning or cognitive biases measures. Limitations mainly include the mix of active and control treatments applied across the different groups. Therefore, the net effect of each of the treatments by itself could not be clearly tested. Results suggest superiority of ABMT compared to CBM-I and their combination in terms of symptom reduction. Possible interpretations and methodological issues underlying the observed findings are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Too good to be true: publication bias in two prominent studies from experimental psychology.

PubMed

Francis, Gregory

2012-04-01

Empirical replication has long been considered the final arbiter of phenomena in science, but replication is undermined when there is evidence for publication bias. Evidence for publication bias in a set of experiments can be found when the observed number of rejections of the null hypothesis exceeds the expected number of rejections. Application of this test reveals evidence of publication bias in two prominent investigations from experimental psychology that have purported to reveal evidence of extrasensory perception and to indicate severe limitations of the scientific method. The presence of publication bias suggests that those investigations cannot be taken as proper scientific studies of such phenomena, because critical data are not available to the field. Publication bias could partly be avoided if experimental psychologists started using Bayesian data analysis techniques.

Ultrahigh Error Threshold for Surface Codes with Biased Noise

NASA Astrophysics Data System (ADS)

Tuckett, David K.; Bartlett, Stephen D.; Flammia, Steven T.

2018-02-01

We show that a simple modification of the surface code can exhibit an enormous gain in the error correction threshold for a noise model in which Pauli Z errors occur more frequently than X or Y errors. Such biased noise, where dephasing dominates, is ubiquitous in many quantum architectures. In the limit of pure dephasing noise we find a threshold of 43.7(1)% using a tensor network decoder proposed by Bravyi, Suchara, and Vargo. The threshold remains surprisingly large in the regime of realistic noise bias ratios, for example 28.2(2)% at a bias of 10. The performance is, in fact, at or near the hashing bound for all values of the bias. The modified surface code still uses only weight-4 stabilizers on a square lattice, but merely requires measuring products of Y instead of Z around the faces, as this doubles the number of useful syndrome bits associated with the dominant Z errors. Our results demonstrate that large efficiency gains can be found by appropriately tailoring codes and decoders to realistic noise models, even under the locality constraints of topological codes.

Weighing Galaxy Clusters with Gas. II. On the Origin of Hydrostatic Mass Bias in ΛCDM Galaxy Clusters

NASA Astrophysics Data System (ADS)

Nelson, Kaylea; Lau, Erwin T.; Nagai, Daisuke; Rudd, Douglas H.; Yu, Liang

2014-02-01

The use of galaxy clusters as cosmological probes hinges on our ability to measure their masses accurately and with high precision. Hydrostatic mass is one of the most common methods for estimating the masses of individual galaxy clusters, which suffer from biases due to departures from hydrostatic equilibrium. Using a large, mass-limited sample of massive galaxy clusters from a high-resolution hydrodynamical cosmological simulation, in this work we show that in addition to turbulent and bulk gas velocities, acceleration of gas introduces biases in the hydrostatic mass estimate of galaxy clusters. In unrelaxed clusters, the acceleration bias is comparable to the bias due to non-thermal pressure associated with merger-induced turbulent and bulk gas motions. In relaxed clusters, the mean mass bias due to acceleration is small (lsim 3%), but the scatter in the mass bias can be reduced by accounting for gas acceleration. Additionally, this acceleration bias is greater in the outskirts of higher redshift clusters where mergers are more frequent and clusters are accreting more rapidly. Since gas acceleration cannot be observed directly, it introduces an irreducible bias for hydrostatic mass estimates. This acceleration bias places limits on how well we can recover cluster masses from future X-ray and microwave observations. We discuss implications for cluster mass estimates based on X-ray, Sunyaev-Zel'dovich effect, and gravitational lensing observations and their impact on cluster cosmology.

Unconscious memory bias in depression: perceptual and conceptual processes.

PubMed

Watkins, P C; Martin, C K; Stern, L D

2000-05-01

Mood-congruent memory (MCM) bias in depression was investigated using 4 different implicit memory tests. Two of the implicit tests were perceptually driven, and 2 were conceptually driven. Depressed participants and nondepressed controls were assigned to 1 of 4 implicit memory tests after studying positive and negative adjectives. Results showed no MCM bias in the perceptually driven tests. MCM was demonstrated in 1 of the conceptually driven tests, but only for adjectives that were conceptually encoded. Results support the theory that mood-congruent processes in depression are limited to conceptual processing. However, activation of conceptual processes may not be sufficient for demonstrating mood congruency.

Large-scale galaxy bias

NASA Astrophysics Data System (ADS)

Desjacques, Vincent; Jeong, Donghui; Schmidt, Fabian

2018-02-01

This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy statistics. We then review the excursion-set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

Mixture models reveal multiple positional bias types in RNA-Seq data and lead to accurate transcript concentration estimates.

PubMed

Tuerk, Andreas; Wiktorin, Gregor; Güler, Serhat

2017-05-01

Accuracy of transcript quantification with RNA-Seq is negatively affected by positional fragment bias. This article introduces Mix2 (rd. "mixquare"), a transcript quantification method which uses a mixture of probability distributions to model and thereby neutralize the effects of positional fragment bias. The parameters of Mix2 are trained by Expectation Maximization resulting in simultaneous transcript abundance and bias estimates. We compare Mix2 to Cufflinks, RSEM, eXpress and PennSeq; state-of-the-art quantification methods implementing some form of bias correction. On four synthetic biases we show that the accuracy of Mix2 overall exceeds the accuracy of the other methods and that its bias estimates converge to the correct solution. We further evaluate Mix2 on real RNA-Seq data from the Microarray and Sequencing Quality Control (MAQC, SEQC) Consortia. On MAQC data, Mix2 achieves improved correlation to qPCR measurements with a relative increase in R2 between 4% and 50%. Mix2 also yields repeatable concentration estimates across technical replicates with a relative increase in R2 between 8% and 47% and reduced standard deviation across the full concentration range. We further observe more accurate detection of differential expression with a relative increase in true positives between 74% and 378% for 5% false positives. In addition, Mix2 reveals 5 dominant biases in MAQC data deviating from the common assumption of a uniform fragment distribution. On SEQC data, Mix2 yields higher consistency between measured and predicted concentration ratios. A relative error of 20% or less is obtained for 51% of transcripts by Mix2, 40% of transcripts by Cufflinks and RSEM and 30% by eXpress. Titration order consistency is correct for 47% of transcripts for Mix2, 41% for Cufflinks and RSEM and 34% for eXpress. We, further, observe improved repeatability across laboratory sites with a relative increase in R2 between 8% and 44% and reduced standard deviation.

Dye bias correction in dual-labeled cDNA microarray gene expression measurements.

PubMed Central

Rosenzweig, Barry A; Pine, P Scott; Domon, Olen E; Morris, Suzanne M; Chen, James J; Sistare, Frank D

2004-01-01

A significant limitation to the analytical accuracy and precision of dual-labeled spotted cDNA microarrays is the signal error due to dye bias. Transcript-dependent dye bias may be due to gene-specific differences of incorporation of two distinctly different chemical dyes and the resultant differential hybridization efficiencies of these two chemically different targets for the same probe. Several approaches were used to assess and minimize the effects of dye bias on fluorescent hybridization signals and maximize the experimental design efficiency of a cell culture experiment. Dye bias was measured at the individual transcript level within each batch of simultaneously processed arrays by replicate dual-labeled split-control sample hybridizations and accounted for a significant component of fluorescent signal differences. This transcript-dependent dye bias alone could introduce unacceptably high numbers of both false-positive and false-negative signals. We found that within a given set of concurrently processed hybridizations, the bias is remarkably consistent and therefore measurable and correctable. The additional microarrays and reagents required for paired technical replicate dye-swap corrections commonly performed to control for dye bias could be costly to end users. Incorporating split-control microarrays within a set of concurrently processed hybridizations to specifically measure dye bias can eliminate the need for technical dye swap replicates and reduce microarray and reagent costs while maintaining experimental accuracy and technical precision. These data support a practical and more efficient experimental design to measure and mathematically correct for dye bias. PMID:15033598

The Effect of Selection Bias in Studies of Fads and Fashions

PubMed Central

Denrell, Jerker; Kovács, Balázs

2015-01-01

Most studies of fashion and fads focus on objects and practices that once were popular. We argue that limiting the sample to such trajectories generates a selection bias that obscures the underlying process and generates biased estimates. Through simulations and the analysis of a data set that has previously not been used to analyze the rise and fall of cultural practices, the New York Times text archive, we show that studying a whole range of cultural objects, both popular and less popular, is essential for understanding the drivers of popularity. In particular, we show that estimates of statistical models of the drivers of popularity will be biased if researchers use only trajectories of those practices that once were popular. PMID:25886158

Low-template methods yield limited extra information for PowerPlex® Fusion 6C profiling.

PubMed

Duijs, Francisca; van de Merwe, Linda; Sijen, Titia; Benschop, Corina C G

2018-06-01

Advances in autosomal DNA profiling systems enable analyzing increased numbers of short tandem repeat (STR) loci in one reaction. Increasing the number of STR loci increases the amount of information that may be obtained from a (crime scene) sample. In this study, we examined whether even more allelic information can be obtained by applying low-template methods. To this aim, the performance of the PowerPlex® Fusion 6C STR typing system was assessed when increasing the number of PCR cycles or enhancing the capillary electrophoresis (CE) injection settings. Results show that applying these low-template methods yields limited extra information and comes at cost of more background noise. In addition, the gain in detection of alleles was much smaller when compared to the gain when applying low-template methods to the 15-loci AmpFLSTR® NGM™ system. Consequently, the PowerPlex® Fusion 6C STR typing system was implemented using standard settings only; low-template methods were not implemented for our routine forensic casework. Copyright © 2018 Elsevier B.V. All rights reserved.

Model selection bias and Freedman's paradox

USGS Publications Warehouse

Lukacs, P.M.; Burnham, K.P.; Anderson, D.R.

2010-01-01

In situations where limited knowledge of a system exists and the ratio of data points to variables is small, variable selection methods can often be misleading. Freedman (Am Stat 37:152-155, 1983) demonstrated how common it is to select completely unrelated variables as highly "significant" when the number of data points is similar in magnitude to the number of variables. A new type of model averaging estimator based on model selection with Akaike's AIC is used with linear regression to investigate the problems of likely inclusion of spurious effects and model selection bias, the bias introduced while using the data to select a single seemingly "best" model from a (often large) set of models employing many predictor variables. The new model averaging estimator helps reduce these problems and provides confidence interval coverage at the nominal level while traditional stepwise selection has poor inferential properties. ?? The Institute of Statistical Mathematics, Tokyo 2009.

Climate change impacts on crop yield in the Euro-Mediterranean region

NASA Astrophysics Data System (ADS)

Toreti, Andrea; Ceglar, Andrej; Dentener, Frank; Niemeyer, Stefan; Dosio, Alessandro; Fumagalli, Davide

2017-04-01

Agriculture is strongly influenced by climate variability, climate extremes and climate changes. Recent studies on past decades have identified and analysed the effects of climate variability and extremes on crop yields in the Euro-Mediterranean region. As these effects could be amplified in a changing climate context, it is essential to analyse available climate projections and investigate the possible impacts on European agriculture in terms of crop yield. In this study, five model runs from the Euro-CORDEX initiative under two scenarios (RCP4.5 and RCP8.5) have been used. Climate model data have been bias corrected and then used to feed a mechanistic crop growth model. The crop model has been run under different settings to better sample the intrinsic uncertainties. Among the main results, it is worth to report a weak but significant and spatially homogeneous increase in potential wheat yield at mid-century (under a CO2 fertilisation effect scenario). While more complex changes seem to characterise potential maize yield, with large areas in the region showing a weak-to-moderate decrease.

Large-scale galaxy bias

NASA Astrophysics Data System (ADS)

Jeong, Donghui; Desjacques, Vincent; Schmidt, Fabian

2018-01-01

Here, we briefly introduce the key results of the recent review (arXiv:1611.09787), whose abstract is as following. This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy (or halo) statistics. We then review the excursion set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

Local and sex-specific biases in crossover vs. noncrossover outcomes at meiotic recombination hot spots in mice

PubMed Central

de Boer, Esther; Jasin, Maria; Keeney, Scott

2015-01-01

Meiotic recombination initiated by programmed double-strand breaks (DSBs) yields two types of interhomolog recombination products, crossovers and noncrossovers, but what determines whether a DSB will yield a crossover or noncrossover is not understood. In this study, we analyzed the influence of sex and chromosomal location on mammalian recombination outcomes by constructing fine-scale recombination maps in both males and females at two mouse hot spots located in different regions of the same chromosome. These include the most comprehensive maps of recombination hot spots in oocytes to date. One hot spot, located centrally on chromosome 1, behaved similarly in male and female meiosis: Crossovers and noncrossovers formed at comparable levels and ratios in both sexes. In contrast, at a distal hot spot, crossovers were recovered only in males even though noncrossovers were obtained at similar frequencies in both sexes. These findings reveal an example of extreme sex-specific bias in recombination outcome. We further found that estimates of relative DSB levels are surprisingly poor predictors of relative crossover frequencies between hot spots in males. Our results demonstrate that the outcome of mammalian meiotic recombination can be biased, that this bias can vary depending on location and cellular context, and that DSB frequency is not the only determinant of crossover frequency. PMID:26251527

The problem of bias when nursing facility staff administer customer satisfaction surveys.

PubMed

Hodlewsky, R Tamara; Decker, Frederic H

2002-10-01

Customer satisfaction instruments are being used with increasing frequency to assess and monitor residents' assessments of quality of care in nursing facilities. There is no standard protocol, however, for how or by whom the instruments should be administered when anonymous, written responses are not feasible. Researchers often use outside interviewers to assess satisfaction, but cost considerations may limit the extent to which facilities are able to hire outside interviewers on a regular basis. This study was designed to investigate the existence and extent of any bias caused by staff administering customer satisfaction surveys. Customer satisfaction data were collected in 1998 from 265 residents in 21 nursing facilities in North Dakota. Half the residents in each facility were interviewed by staff members and the other half by outside consultants; scores were compared by interviewer type. In addition to a tabulation of raw scores, ordinary least-squares analysis with facility fixed effects was used to control for resident characteristics and unmeasured facility-level factors that could influence scores. Significant positive bias was found when staff members interviewed residents. The bias was not limited to questions directly affecting staff responsibilities but applied across all types of issues. The bias was robust under varying constructions of satisfaction and dissatisfaction. A uniform method of survey administration appears to be important if satisfaction data are to be used to compare facilities. Bias is an important factor that should be considered and weighed against the costs of obtaining outside interviewers when assessing customer satisfaction among long term care residents.

Censoring: a new approach for detection limits in total-reflection X-ray fluorescence

NASA Astrophysics Data System (ADS)

Pajek, M.; Kubala-Kukuś, A.; Braziewicz, J.

2004-08-01

It is shown that the detection limits in the total-reflection X-ray fluorescence (TXRF), which restrict quantification of very low concentrations of trace elements in the samples, can be accounted for using the statistical concept of censoring. We demonstrate that the incomplete TXRF measurements containing the so-called "nondetects", i.e. the non-measured concentrations falling below the detection limits and represented by the estimated detection limit values, can be viewed as the left random-censored data, which can be further analyzed using the Kaplan-Meier (KM) method correcting for nondetects. Within this approach, which uses the Kaplan-Meier product-limit estimator to obtain the cumulative distribution function corrected for the nondetects, the mean value and median of the detection limit censored concentrations can be estimated in a non-parametric way. The Monte Carlo simulations performed show that the Kaplan-Meier approach yields highly accurate estimates for the mean and median concentrations, being within a few percent with respect to the simulated, uncensored data. This means that the uncertainties of KM estimated mean value and median are limited in fact only by the number of studied samples and not by the applied correction procedure for nondetects itself. On the other hand, it is observed that, in case when the concentration of a given element is not measured in all the samples, simple approaches to estimate a mean concentration value from the data yield erroneous, systematically biased results. The discussed random-left censoring approach was applied to analyze the TXRF detection-limit-censored concentration measurements of trace elements in biomedical samples. We emphasize that the Kaplan-Meier approach allows one to estimate the mean concentrations being substantially below the mean level of detection limits. Consequently, this approach gives a new access to lower the effective detection limits for TXRF method, which is of prime interest for

The Z {yields} cc-bar {yields} {gamma}{gamma}*, Z {yields} bb-bar {yields} {gamma}{gamma}* triangle diagrams and the Z {yields} {gamma}{psi}, Z {yields} {gamma}Y decays

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

Achasov, N. N., E-mail: achasov@math.nsc.ru

2011-03-15

The approach to the Z {yields} {gamma}{psi} and Z {yields} {gamma}Y decay study is presented in detail, based on the sum rules for the Z {yields} cc-bar {yields} {gamma}{gamma}* and Z {yields} bb-bar {yields} {gamma}{gamma}* amplitudes and their derivatives. The branching ratios of the Z {yields} {gamma}{psi} and Z {yields} {gamma}Y decays are calculated for different hypotheses on saturation of the sum rules. The lower bounds of {Sigma}{sub {psi}} BR(Z {yields} {gamma}{psi}) = 1.95 Multiplication-Sign 10{sup -7} and {Sigma}{sub {upsilon}} BR(Z {yields} {gamma}Y) = 7.23 Multiplication-Sign 10{sup -7} are found. Deviations from the lower bounds are discussed, including the possibilitymore » of BR(Z {yields} {gamma}J/{psi}(1S)) {approx} BR(Z {yields} {gamma}Y(1S)) {approx} 10{sup -6}, that could be probably measured in LHC. The angular distributions in the Z {yields} {gamma}{psi} and Z {yields} {gamma}Y decays are also calculated.« less

Explication of Interspousal Criticality Bias

PubMed Central

Peterson, Kristina M.; Smith, David A.; Windle, Chaunce R.

2009-01-01

Although bias towards perceiving spousal criticism is related to dysphoria and marital discord (Smith & Peterson, 2008), the bias construct has received insufficient elaboration. We explicated the criticality bias construct by exploring its correlates and incremental validity relative to perceived criticism, marital attributions, and negative affect. 118 couples completed self-report measures and undertook a videotaped discussion task. Signal detection analyses of both spouses’ and outside observers’ ratings of discussions produced bias indices. Criticality bias evidenced a pattern of convergent and discriminant validity mirroring perceived criticism’s (Renshaw, 2008). Bias also provided incremental validity beyond perceived criticism, marital attributions, and negative affect to the prediction of behavior. Bias may be a dysfunctional way to view marital events and a stress generation process. PMID:19286167

The limits of crop productivity

NASA Technical Reports Server (NTRS)

Bugbee, Bruce; Monje, Oscar

1992-01-01

The component processes that govern yield limits in food crops are reviewed and how each process can be individually measured is described. The processes considered include absorption of photosynthetic radiation by green tissue, carbon-fixation efficiency in photosynthesis, carbon use efficiency in respiration, biomass allocation to edible products, and efficiency of photosynthesis and respiration. The factors limiting yields in optimal environments are considered.

Time-course of attention biases in social phobia.

PubMed

Schofield, Casey A; Inhoff, Albrecht W; Coles, Meredith E

2013-10-01

Theoretical models of social phobia implicate preferential attention to social threat in the maintenance of anxiety symptoms, though there has been limited work characterizing the nature of these biases over time. The current study utilized eye-movement data to examine the time-course of visual attention over 1500ms trials of a probe detection task. Nineteen participants with a primary diagnosis of social phobia based on DSM-IV criteria and 20 non-clinical controls completed this task with angry, fearful, and happy face trials. Overt visual attention to the emotional and neutral faces was measured in 50ms segments across the trial. Over time, participants with social phobia attend less to emotional faces and specifically less to happy faces compared to controls. Further, attention to emotional relative to neutral expressions did not vary notably by emotion for participants with social phobia, but control participants showed a pattern after 1000ms in which over time they preferentially attended to happy expressions and avoided negative expressions. Findings highlight the importance of considering attention biases to positive stimuli as well as the pattern of attention between groups. These results suggest that attention "bias" in social phobia may be driven by a relative lack of the biases seen in non-anxious participants. Copyright © 2013 Elsevier Ltd. All rights reserved.

Bias and design in software specifications

NASA Technical Reports Server (NTRS)

Straub, Pablo A.; Zelkowitz, Marvin V.

1990-01-01

Implementation bias in a specification is an arbitrary constraint in the solution space. Presented here is a model of bias in software specifications. Bias is defined in terms of the specification process and a classification of the attributes of the software product. Our definition of bias provides insight into both the origin and the consequences of bias. It also shows that bias is relative and essentially unavoidable. Finally, we describe current work on defining a measure of bias, formalizing our model, and relating bias to software defects.

New age- and sex-specific criteria for QT prolongation based on rate correction formulas that minimize bias at the upper normal limits.

PubMed

Rautaharju, Pentti M; Mason, Jay W; Akiyama, Toshio

2014-07-01

Existing formulas for rate-corrected QT (QTc) commonly fail to properly adjust the upper normal limits which are more critical than the mean QTc for evaluation of prolonged QT. Age- and sex-related differences in QTc are also often overlooked. Our goal was to establish criteria for prolonged QTc using formulas that minimize QTc bias at the upper normal limits. Strict criteria were used in selecting a study group of 57,595 persons aged 5 to 89 years (54% women) and to exclude electrocardiograms (ECG) with possible disease-associated changes. Two QT rate adjustment formulas were identified which both minimized rate-dependency in the 98 th percentile limits: QTcmod, based on an electrophysiological model (QTcMod = QTx(120 + HR)/180)), and QTcLogLin, a power function of the RR interval with exponents 0.37 for men and 0.38 for women. QTc shortened in men during adolescence and QTcMod became 13 ms shorter than in women at age 20-29 years. The sex difference was maintained through adulthood although decreasing with age. The criteria established for prolonged QTc were: Age < 40 years, men 430 ms, women 440 ms; Age 40 to 69, men 440 ms, women 450 ms; Age ≥ 70 years, men 455 ms, and women 460 ms. Sex difference in QTc originates from shortened QT in adolescent males. Upper normal limits for QTc vary substantially by age and sex, and it is essential to use age- and sex-specific criteria for evaluation of QT prolongation. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

FROM BIAS TO BISEXUAL HEALTH DISPARITIES: ATTITUDES TOWARD BISEXUAL MEN AND WOMEN IN THE UNITED STATES.

PubMed

Friedman, M Reuel; Dodge, Brian; Schick, Vanessa; Herbenick, Debby; Hubach, Randolph; Bowling, Jessamyn; Goncalves, Gabriel; Krier, Sarah; Reece, Michael

2014-12-01

A newly emergent literature suggest that bisexual men and women face profound health disparities in comparison to both heterosexual and homosexual individuals. Additionally, bisexual individuals often experience prejudice, stigma, and discrimination from both gay/lesbian and straight communities, termed "biphobia." However, only limited research exists that empirically tests the extent and predictors of this double discrimination. The Bisexualities: Indiana Attitudes Survey (BIAS) was developed to test associations between biphobia and sexual identity. Using standard techniques, we developed and administered a scale to a purposive online sample of adults from a wide range of social networking websites. We conducted exploratory factor analysis to refine scales assessing attitudes toward bisexual men and bisexual women, respectively. Using generalized linear modeling, we assessed relationships between BIAS scores and sexual identity, adjusting for covariates. Two separately gendered scales were developed, administered, and refined: BIAS-m (n=645), focusing on attitudes toward bisexual men; and BIAS-f (n=631), focusing on attitudes toward bisexual women. Across scales, sexual identity significantly predicted response variance. Lesbian/gay respondents had lower levels of bi-negative attitudes than their heterosexual counterparts (all p-values <.05); bisexual respondents had lower levels of bi-negative attitudes than their straight counterparts (all p-values <.001); and bisexual respondents had lower levels of bi-negative attitudes than their lesbian/gay counterparts (all p-values <.05). Within racial/ethnic minority respondents, biracial/multiracial status was associated with lower bi-negativity scores (all p-values <.05). This study provides important quantitative support for theories related to biphobia and double discrimination. Our findings provide strong evidence for understanding how stereotypes and stigma may lead to dramatic disparities in depression, anxiety

Weighing galaxy clusters with gas. II. On the origin of hydrostatic mass bias in ΛCDM galaxy clusters

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

Nelson, Kaylea; Nagai, Daisuke; Yu, Liang

2014-02-20

The use of galaxy clusters as cosmological probes hinges on our ability to measure their masses accurately and with high precision. Hydrostatic mass is one of the most common methods for estimating the masses of individual galaxy clusters, which suffer from biases due to departures from hydrostatic equilibrium. Using a large, mass-limited sample of massive galaxy clusters from a high-resolution hydrodynamical cosmological simulation, in this work we show that in addition to turbulent and bulk gas velocities, acceleration of gas introduces biases in the hydrostatic mass estimate of galaxy clusters. In unrelaxed clusters, the acceleration bias is comparable to themore » bias due to non-thermal pressure associated with merger-induced turbulent and bulk gas motions. In relaxed clusters, the mean mass bias due to acceleration is small (≲ 3%), but the scatter in the mass bias can be reduced by accounting for gas acceleration. Additionally, this acceleration bias is greater in the outskirts of higher redshift clusters where mergers are more frequent and clusters are accreting more rapidly. Since gas acceleration cannot be observed directly, it introduces an irreducible bias for hydrostatic mass estimates. This acceleration bias places limits on how well we can recover cluster masses from future X-ray and microwave observations. We discuss implications for cluster mass estimates based on X-ray, Sunyaev-Zel'dovich effect, and gravitational lensing observations and their impact on cluster cosmology.« less

Bias to CMB lensing reconstruction from temperature anisotropies due to large-scale galaxy motions

NASA Astrophysics Data System (ADS)

Ferraro, Simone; Hill, J. Colin

2018-01-01

Gravitational lensing of the cosmic microwave background (CMB) is expected to be amongst the most powerful cosmological tools for ongoing and upcoming CMB experiments. In this work, we investigate a bias to CMB lensing reconstruction from temperature anisotropies due to the kinematic Sunyaev-Zel'dovich (kSZ) effect, that is, the Doppler shift of CMB photons induced by Compton scattering off moving electrons. The kSZ signal yields biases due to both its own intrinsic non-Gaussianity and its nonzero cross-correlation with the CMB lensing field (and other fields that trace the large-scale structure). This kSZ-induced bias affects both the CMB lensing autopower spectrum and its cross-correlation with low-redshift tracers. Furthermore, it cannot be removed by multifrequency foreground separation techniques because the kSZ effect preserves the blackbody spectrum of the CMB. While statistically negligible for current data sets, we show that it will be important for upcoming surveys, and failure to account for it can lead to large biases in constraints on neutrino masses or the properties of dark energy. For a stage 4 CMB experiment, the bias can be as large as ≈15 % or 12% in cross-correlation with LSST galaxy lensing convergence or galaxy overdensity maps, respectively, when the maximum temperature multipole used in the reconstruction is ℓmax=4000 , and about half of that when ℓmax=3000 . Similarly, we find that the CMB lensing autopower spectrum can be biased by up to several percent. These biases are many times larger than the expected statistical errors. We validate our analytical predictions with cosmological simulations and present the first complete estimate of secondary-induced CMB lensing biases. The predicted bias is sensitive to the small-scale gas distribution, which is affected by pressure and feedback mechanisms, thus making removal via "bias-hardened" estimators challenging. Reducing ℓmax can significantly mitigate the bias at the cost of a decrease

Wind models for the NSTS ascent trajectory biasing for wind load alleviation

NASA Technical Reports Server (NTRS)

Smith, O. E.; Adelfang, S. I.; Batts, G. W.; Hill, C. K.

1989-01-01

New concepts are presented for aerospace vehicle ascent wind profile biasing. The purpose for wind biasing the ascent trajectory is to provide ascent wind loads relief and thus decrease the probability for launch delays due to wind loads exceeding critical limits. Wind biasing trajectories to the profile of monthly mean winds have been widely used for this purpose. The wind profile models presented give additional alternatives for wind biased trajectories. They are derived from the properties of the bivariate normal probability function using the available wind statistical parameters for the launch site. The analytical expressions are presented to permit generalizations. Specific examples are given to illustrate the procedures. The wind profile models can be used to establish the ascent trajectory steering commands to guide the vehicle through the first stage. For the National Space Transportation System (NSTS) program these steering commands are called I-loads.

Opinion Dynamics with Confirmation Bias

PubMed Central

Allahverdyan, Armen E.; Galstyan, Aram

2014-01-01

Background Confirmation bias is the tendency to acquire or evaluate new information in a way that is consistent with one's preexisting beliefs. It is omnipresent in psychology, economics, and even scientific practices. Prior theoretical research of this phenomenon has mainly focused on its economic implications possibly missing its potential connections with broader notions of cognitive science. Methodology/Principal Findings We formulate a (non-Bayesian) model for revising subjective probabilistic opinion of a confirmationally-biased agent in the light of a persuasive opinion. The revision rule ensures that the agent does not react to persuasion that is either far from his current opinion or coincides with it. We demonstrate that the model accounts for the basic phenomenology of the social judgment theory, and allows to study various phenomena such as cognitive dissonance and boomerang effect. The model also displays the order of presentation effect–when consecutively exposed to two opinions, the preference is given to the last opinion (recency) or the first opinion (primacy) –and relates recency to confirmation bias. Finally, we study the model in the case of repeated persuasion and analyze its convergence properties. Conclusions The standard Bayesian approach to probabilistic opinion revision is inadequate for describing the observed phenomenology of persuasion process. The simple non-Bayesian model proposed here does agree with this phenomenology and is capable of reproducing a spectrum of effects observed in psychology: primacy-recency phenomenon, boomerang effect and cognitive dissonance. We point out several limitations of the model that should motivate its future development. PMID:25007078

Fat fraction bias correction using T1 estimates and flip angle mapping.

PubMed

Yang, Issac Y; Cui, Yifan; Wiens, Curtis N; Wade, Trevor P; Friesen-Waldner, Lanette J; McKenzie, Charles A

2014-01-01

To develop a new method of reducing T1 bias in proton density fat fraction (PDFF) measured with iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL). PDFF maps reconstructed from high flip angle IDEAL measurements were simulated and acquired from phantoms and volunteer L4 vertebrae. T1 bias was corrected using a priori T1 values for water and fat, both with and without flip angle correction. Signal-to-noise ratio (SNR) maps were used to measure precision of the reconstructed PDFF maps. PDFF measurements acquired using small flip angles were then compared to both sets of corrected large flip angle measurements for accuracy and precision. Simulations show similar results in PDFF error between small flip angle measurements and corrected large flip angle measurements as long as T1 estimates were within one standard deviation from the true value. Compared to low flip angle measurements, phantom and in vivo measurements demonstrate better precision and accuracy in PDFF measurements if images were acquired at a high flip angle, with T1 bias corrected using T1 estimates and flip angle mapping. T1 bias correction of large flip angle acquisitions using estimated T1 values with flip angle mapping yields fat fraction measurements of similar accuracy and superior precision compared to low flip angle acquisitions. Copyright © 2013 Wiley Periodicals, Inc.

How does bias correction of regional climate model precipitation affect modelled runoff?

NASA Astrophysics Data System (ADS)

Teng, J.; Potter, N. J.; Chiew, F. H. S.; Zhang, L.; Wang, B.; Vaze, J.; Evans, J. P.

2015-02-01

Many studies bias correct daily precipitation from climate models to match the observed precipitation statistics, and the bias corrected data are then used for various modelling applications. This paper presents a review of recent methods used to bias correct precipitation from regional climate models (RCMs). The paper then assesses four bias correction methods applied to the weather research and forecasting (WRF) model simulated precipitation, and the follow-on impact on modelled runoff for eight catchments in southeast Australia. Overall, the best results are produced by either quantile mapping or a newly proposed two-state gamma distribution mapping method. However, the differences between the methods are small in the modelling experiments here (and as reported in the literature), mainly due to the substantial corrections required and inconsistent errors over time (non-stationarity). The errors in bias corrected precipitation are typically amplified in modelled runoff. The tested methods cannot overcome limitations of the RCM in simulating precipitation sequence, which affects runoff generation. Results further show that whereas bias correction does not seem to alter change signals in precipitation means, it can introduce additional uncertainty to change signals in high precipitation amounts and, consequently, in runoff. Future climate change impact studies need to take this into account when deciding whether to use raw or bias corrected RCM results. Nevertheless, RCMs will continue to improve and will become increasingly useful for hydrological applications as the bias in RCM simulations reduces.

The Likelihood of Injury Among Bias Crimes: An Analysis of General and Specific Bias Types.

PubMed

Pezzella, Frank S; Fetzer, Matthew D

2015-06-18

In 2009, President Barack Obama signed the Mathew Sheppard and James Byrd Jr. Hate Crimes Protection act and thereby extended the list of previously protected classes of victims from actual or perceived race, color, religion, national origin, disability and sex orientation to gender and gender identity. Over 45 states, the District of Columbia and the federal government now include hate crime statutes that increase penalties when offenders perpetrate hate crimes against protected classes of victims. Penalty enhancement statutes sanction unlawful bias conduct arguably because they result in more severe injuries relative to non-bias conduct. We contend that physical injuries vary by bias type and are not equally injurious. Data on bias crimes was analyzed from the National Incident Based Reporting System. Descriptive patterns of bias crimes were identified by offense type, bias motivation and major and minor injuries. Using Multivariate analyses, we found an escalating trend of violence against racial minorities. Moreover, relative to non-bias crimes, only anti-White and anti-lesbian bias crimes experienced our two prong "animus" criteria of disproportionate prevalence and severity of injury. However, when compared to anti-White bias, anti-Black bias crimes were more prevalent and likely to suffer serious injuries. Implications for hate crime jurisprudence are discussed. © The Author(s) 2015.

Bias in estimating accuracy of a binary screening test with differential disease verification

PubMed Central

Brinton, John T.; Ringham, Brandy M.; Glueck, Deborah H.

2011-01-01

SUMMARY Sensitivity, specificity, positive and negative predictive value are typically used to quantify the accuracy of a binary screening test. In some studies it may not be ethical or feasible to obtain definitive disease ascertainment for all subjects using a gold standard test. When a gold standard test cannot be used an imperfect reference test that is less than 100% sensitive and specific may be used instead. In breast cancer screening, for example, follow-up for cancer diagnosis is used as an imperfect reference test for women where it is not possible to obtain gold standard results. This incomplete ascertainment of true disease, or differential disease verification, can result in biased estimates of accuracy. In this paper, we derive the apparent accuracy values for studies subject to differential verification. We determine how the bias is affected by the accuracy of the imperfect reference test, the percent who receive the imperfect reference standard test not receiving the gold standard, the prevalence of the disease, and the correlation between the results for the screening test and the imperfect reference test. It is shown that designs with differential disease verification can yield biased estimates of accuracy. Estimates of sensitivity in cancer screening trials may be substantially biased. However, careful design decisions, including selection of the imperfect reference test, can help to minimize bias. A hypothetical breast cancer screening study is used to illustrate the problem. PMID:21495059

Calibration of colour gradient bias in shear measurement using HST/CANDELS data

NASA Astrophysics Data System (ADS)

Er, X.; Hoekstra, H.; Schrabback, T.; Cardone, V. F.; Scaramella, R.; Maoli, R.; Vicinanza, M.; Gillis, B.; Rhodes, J.

2018-06-01

Accurate shape measurements are essential to infer cosmological parameters from large area weak gravitational lensing studies. The compact diffraction-limited point spread function (PSF) in space-based observations is greatly beneficial, but its chromaticity for a broad-band observation can lead to new subtle effects that could hitherto be ignored: the PSF of a galaxy is no longer uniquely defined and spatial variations in the colours of galaxies result in biases in the inferred lensing signal. Taking Euclid as a reference, we show that this colour gradient bias (CG bias) can be quantified with high accuracy using available multicolour Hubble Space Telescope (HST) data. In particular we study how noise in the HST observations might impact such measurements and find this to be negligible. We determine the CG bias using HST observations in the F606W and F814W filters and observe a correlation with the colour, in line with expectations, whereas the dependence with redshift is weak. The biases for individual galaxies are generally well below 1 per cent, which may be reduced further using morphological information from the Euclid data. Our results demonstrate that CG bias should not be ignored, but it is possible to determine its amplitude with sufficient precision, so that it will not significantly bias the weak lensing measurements using Euclid data.

Cognitive Bias in the Verification and Validation of Space Flight Systems

NASA Technical Reports Server (NTRS)

Larson, Steve

2012-01-01

Cognitive bias is generally recognized as playing a significant role in virtually all domains of human decision making. Insight into this role is informally built into many of the system engineering practices employed in the aerospace industry. The review process, for example, typically has features that help to counteract the effect of bias. This paper presents a discussion of how commonly recognized biases may affect the verification and validation process. Verifying and validating a system is arguably more challenging than development, both technically and cognitively. Whereas there may be a relatively limited number of options available for the design of a particular aspect of a system, there is a virtually unlimited number of potential verification scenarios that may be explored. The probability of any particular scenario occurring in operations is typically very difficult to estimate, which increases reliance on judgment that may be affected by bias. Implementing a verification activity often presents technical challenges that, if they can be overcome at all, often result in a departure from actual flight conditions (e.g., 1-g testing, simulation, time compression, artificial fault injection) that may raise additional questions about the meaningfulness of the results, and create opportunities for the introduction of additional biases. In addition to mitigating the biases it can introduce directly, the verification and validation process must also overcome the cumulative effect of biases introduced during all previous stages of development. A variety of cognitive biases will be described, with research results for illustration. A handful of case studies will be presented that show how cognitive bias may have affected the verification and validation process on recent JPL flight projects, identify areas of strength and weakness, and identify potential changes or additions to commonly used techniques that could provide a more robust verification and validation of

A Systematic Review of Experimental Paradigms for Exploring Biased Interpretation of Ambiguous Information with Emotional and Neutral Associations

PubMed Central

Schoth, Daniel E.; Liossi, Christina

2017-01-01

Interpretation biases have been extensively explored in a range of populations, including patients with anxiety and depressive disorders where they have been argued to influence the onset and maintenance of such conditions. Other populations in which interpretation biases have been explored include patients with chronic pain, anorexia nervosa, and alcohol dependency among others, although this literature is more limited. In this research, stimuli with threatening/emotional and neutral meanings are presented, with participant responses indicative of ambiguity resolution. A large number of paradigms have been designed and implemented in the exploration of interpretation biases, some varying in minor features only. This article provides a review of experimental paradigms available for exploring interpretation biases, with the aim to stimulate and inform the design of future research exploring cognitive biases across a range of populations. A systematic search of the experimental literature was conducted in Medline, PsychINFO, Web of Science, CINAHL, and Cochrane Library databases. Search terms were information, stimuli, and ambiguous intersected with the terms interpretation and bias*. Forty-five paradigms were found, categorized into those using ambiguous words, ambiguous images, and ambiguous scenarios. The key features, strengths and limitations of the paradigms identified are discussed. PMID:28232813

A Systematic Review of Experimental Paradigms for Exploring Biased Interpretation of Ambiguous Information with Emotional and Neutral Associations.

PubMed

Schoth, Daniel E; Liossi, Christina

2017-01-01

Interpretation biases have been extensively explored in a range of populations, including patients with anxiety and depressive disorders where they have been argued to influence the onset and maintenance of such conditions. Other populations in which interpretation biases have been explored include patients with chronic pain, anorexia nervosa, and alcohol dependency among others, although this literature is more limited. In this research, stimuli with threatening/emotional and neutral meanings are presented, with participant responses indicative of ambiguity resolution. A large number of paradigms have been designed and implemented in the exploration of interpretation biases, some varying in minor features only. This article provides a review of experimental paradigms available for exploring interpretation biases, with the aim to stimulate and inform the design of future research exploring cognitive biases across a range of populations. A systematic search of the experimental literature was conducted in Medline, PsychINFO, Web of Science, CINAHL, and Cochrane Library databases. Search terms were information, stimuli , and ambiguous intersected with the terms interpretation and bias * . Forty-five paradigms were found, categorized into those using ambiguous words, ambiguous images, and ambiguous scenarios. The key features, strengths and limitations of the paradigms identified are discussed.

Comparison of whole-genome bisulfite sequencing library preparation strategies identifies sources of biases affecting DNA methylation data.

PubMed

Olova, Nelly; Krueger, Felix; Andrews, Simon; Oxley, David; Berrens, Rebecca V; Branco, Miguel R; Reik, Wolf

2018-03-15

Whole-genome bisulfite sequencing (WGBS) is becoming an increasingly accessible technique, used widely for both fundamental and disease-oriented research. Library preparation methods benefit from a variety of available kits, polymerases and bisulfite conversion protocols. Although some steps in the procedure, such as PCR amplification, are known to introduce biases, a systematic evaluation of biases in WGBS strategies is missing. We perform a comparative analysis of several commonly used pre- and post-bisulfite WGBS library preparation protocols for their performance and quality of sequencing outputs. Our results show that bisulfite conversion per se is the main trigger of pronounced sequencing biases, and PCR amplification builds on these underlying artefacts. The majority of standard library preparation methods yield a significantly biased sequence output and overestimate global methylation. Importantly, both absolute and relative methylation levels at specific genomic regions vary substantially between methods, with clear implications for DNA methylation studies. We show that amplification-free library preparation is the least biased approach for WGBS. In protocols with amplification, the choice of bisulfite conversion protocol or polymerase can significantly minimize artefacts. To aid with the quality assessment of existing WGBS datasets, we have integrated a bias diagnostic tool in the Bismark package and offer several approaches for consideration during the preparation and analysis of WGBS datasets.

Biases in the production and reception of collective knowledge: the case of hindsight bias in Wikipedia.

PubMed

Oeberst, Aileen; von der Beck, Ina; D Back, Mitja; Cress, Ulrike; Nestler, Steffen

2017-04-17

The Web 2.0 enabled collaboration at an unprecedented level. In one of the flagships of mass collaboration-Wikipedia-a large number of authors socially negotiate the world's largest compendium of knowledge. Several guidelines in Wikipedia restrict contributions to verifiable information from reliable sources to ensure recognized knowledge. Much psychological research demonstrates, however, that individual information processing is biased. This poses the question whether individual biases translate to Wikipedia articles or whether they are prevented by its guidelines. The present research makes use of hindsight bias to examine this question. To this end, we analyzed foresight and hindsight versions of Wikipedia articles regarding a broad variety of events (Study 1). We found the majority of articles not to contain traces of hindsight bias-contrary to prior individual research. However, for a particular category of events-disasters-we found robust evidence for hindsight bias. In a lab experiment (Study 2), we then examined whether individuals' hindsight bias is translated into articles under controlled conditions and tested whether collaborative writing-as present in Wikipedia-affects the resultant bias (vs. individual writing). Finally, we investigated the impact of biased Wikipedia articles on readers (Study 3). As predicted, biased articles elicited a hindsight bias in readers, who had not known of the event previously. Moreover, biased articles also affected individuals who knew about the event already, and who had already developed a hindsight bias: biased articles further increased their hindsight.

Sampling of temporal networks: Methods and biases

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Tools for assessing risk of reporting biases in studies and syntheses of studies: a systematic review.

PubMed

Page, Matthew J; McKenzie, Joanne E; Higgins, Julian P T

2018-03-14

Several scales, checklists and domain-based tools for assessing risk of reporting biases exist, but it is unclear how much they vary in content and guidance. We conducted a systematic review of the content and measurement properties of such tools. We searched for potentially relevant articles in Ovid MEDLINE, Ovid Embase, Ovid PsycINFO and Google Scholar from inception to February 2017. One author screened all titles, abstracts and full text articles, and collected data on tool characteristics. We identified 18 tools that include an assessment of the risk of reporting bias. Tools varied in regard to the type of reporting bias assessed (eg, bias due to selective publication, bias due to selective non-reporting), and the level of assessment (eg, for the study as a whole, a particular result within a study or a particular synthesis of studies). Various criteria are used across tools to designate a synthesis as being at 'high' risk of bias due to selective publication (eg, evidence of funnel plot asymmetry, use of non-comprehensive searches). However, the relative weight assigned to each criterion in the overall judgement is unclear for most of these tools. Tools for assessing risk of bias due to selective non-reporting guide users to assess a study, or an outcome within a study, as 'high' risk of bias if no results are reported for an outcome. However, assessing the corresponding risk of bias in a synthesis that is missing the non-reported outcomes is outside the scope of most of these tools. Inter-rater agreement estimates were available for five tools. There are several limitations of existing tools for assessing risk of reporting biases, in terms of their scope, guidance for reaching risk of bias judgements and measurement properties. Development and evaluation of a new, comprehensive tool could help overcome present limitations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial

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.

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.

Radial Bias Is Not Necessary For Orientation Decoding

PubMed Central

Pratte, Michael S.; Sy, Jocelyn L.; Swisher, Jascha D.; Tong, Frank

2015-01-01

Multivariate pattern analysis can be used to decode the orientation of a viewed grating from fMRI signals in early visual areas. Although some studies have reported identifying multiple sources of the orientation information that make decoding possible, a recent study argued that orientation decoding is only possible because of a single source: a coarse-scale retinotopically organized preference for radial orientations. Here we aim to resolve these discrepant findings. We show that there were subtle, but critical, experimental design choices that led to the erroneous conclusion that a radial bias is the only source of orientation information in fMRI signals. In particular, we show that the reliance on a fast temporal-encoding paradigm for spatial mapping can be problematic, as effects of space and time become conflated and lead to distorted estimates of a voxel’s orientation or retinotopic preference. When we implement minor changes to the temporal paradigm or to the visual stimulus itself, by slowing the periodic rotation of the stimulus or by smoothing its contrast-energy profile, we find significant evidence of orientation information that does not originate from radial bias. In an additional block-paradigm experiment where space and time were not conflated, we apply a formal model comparison approach and find that many voxels exhibit more complex tuning properties than predicted by radial bias alone or in combination with other known coarse-scale biases. Our findings support the conclusion that radial bias is not necessary for orientation decoding. In addition, our study highlights potential limitations of using temporal phase-encoded fMRI designs for characterizing voxel tuning properties. PMID:26666900

On CD-AFM bias related to probe bending

NASA Astrophysics Data System (ADS)

Ukraintsev, V. A.; Orji, N. G.; Vorburger, T. V.; Dixson, R. G.; Fu, J.; Silver, R. M.

2012-03-01

Critical Dimension AFM (CD-AFM) is a widely used reference metrology. To characterize modern semiconductor devices, very small and flexible probes, often 15 nm to 20 nm in diameter, are now frequently used. Several recent publications have reported on uncontrolled and significant probe-to-probe bias variation during linewidth and sidewall angle measurements [1,2]. Results obtained in this work suggest that probe bending can be on the order of several nanometers and thus potentially can explain much of the observed CD-AFM probe-to-probe bias variation. We have developed and experimentally tested one-dimensional (1D) and two-dimensional (2D) models to describe the bending of cylindrical probes. An earlier 1D bending model reported by Watanabe et al. [3] was refined. Contributions from several new phenomena were considered, including: probe misalignment, diameter variation near the carbon nanotube tip (CNT) apex, probe bending before snapping, distributed van der Waals-London force, etc. The methodology for extraction of the Hamaker probe-surface interaction energy from experimental probe bending data was developed. To overcome limitations of the 1D model, a new 2D distributed force (DF) model was developed. Comparison of the new model with the 1D single point force (SPF) model revealed about 27 % difference in probe bending bias between the two. A simple linear relation between biases predicted by the 1D SPF and 2D DF models was found. This finding simplifies use of the advanced 2D DF model of probe bending in various CD-AFM applications. New 2D and three-dimensional (3D) CDAFM data analysis software is needed to take full advantage of the new bias correction modeling capabilities.

A Novel Method for Analyzing Extremely Biased Agonism at G Protein–Coupled Receptors

PubMed Central

Zhou, Lei; Ehlert, Frederick J.; Bohn, Laura M.

2015-01-01

Seven transmembrane receptors were originally named and characterized based on their ability to couple to heterotrimeric G proteins. The assortment of coupling partners for G protein–coupled receptors has subsequently expanded to include other effectors (most notably the βarrestins). This diversity of partners available to the receptor has prompted the pursuit of ligands that selectively activate only a subset of the available partners. A biased or functionally selective ligand may be able to distinguish between different active states of the receptor, and this would result in the preferential activation of one signaling cascade more than another. Although application of the “standard” operational model for analyzing ligand bias is useful and suitable in most cases, there are limitations that arise when the biased agonist fails to induce a significant response in one of the assays being compared. In this article, we describe a quantitative method for measuring ligand bias that is particularly useful for such cases of extreme bias. Using simulations and experimental evidence from several κ opioid receptor agonists, we illustrate a “competitive” model for quantitating the degree and direction of bias. By comparing the results obtained from the competitive model with the standard model, we demonstrate that the competitive model expands the potential for evaluating the bias of very partial agonists. We conclude the competitive model provides a useful mechanism for analyzing the bias of partial agonists that exhibit extreme bias. PMID:25680753

Quantifying Heuristic Bias: Anchoring, Availability, and Representativeness.

PubMed

Richie, Megan; Josephson, S Andrew

2018-01-01

Construct: Authors examined whether a new vignette-based instrument could isolate and quantify heuristic bias. Heuristics are cognitive shortcuts that may introduce bias and contribute to error. There is no standardized instrument available to quantify heuristic bias in clinical decision making, limiting future study of educational interventions designed to improve calibration of medical decisions. This study presents validity data to support a vignette-based instrument quantifying bias due to the anchoring, availability, and representativeness heuristics. Participants completed questionnaires requiring assignment of probabilities to potential outcomes of medical and nonmedical scenarios. The instrument randomly presented scenarios in one of two versions: Version A, encouraging heuristic bias, and Version B, worded neutrally. The primary outcome was the difference in probability judgments for Version A versus Version B scenario options. Of 167 participants recruited, 139 enrolled. Participants assigned significantly higher mean probability values to Version A scenario options (M = 9.56, SD = 3.75) than Version B (M = 8.98, SD = 3.76), t(1801) = 3.27, p = .001. This result remained significant analyzing medical scenarios alone (Version A, M = 9.41, SD = 3.92; Version B, M = 8.86, SD = 4.09), t(1204) = 2.36, p = .02. Analyzing medical scenarios by heuristic revealed a significant difference between Version A and B for availability (Version A, M = 6.52, SD = 3.32; Version B, M = 5.52, SD = 3.05), t(404) = 3.04, p = .003, and representativeness (Version A, M = 11.45, SD = 3.12; Version B, M = 10.67, SD = 3.71), t(396) = 2.28, p = .02, but not anchoring. Stratifying by training level, students maintained a significant difference between Version A and B medical scenarios (Version A, M = 9.83, SD = 3.75; Version B, M = 9.00, SD = 3.98), t(465) = 2.29, p = .02, but not residents or attendings. Stratifying by heuristic and training level, availability maintained

Dipole-induced exchange bias.

PubMed

Torres, Felipe; Morales, Rafael; Schuller, Ivan K; Kiwi, Miguel

2017-11-09

The discovery of dipole-induced exchange bias (EB), switching from negative to positive sign, is reported in systems where the antiferromagnet and the ferromagnet are separated by a paramagnetic spacer (AFM-PM-FM). The magnitude and sign of the EB is determined by the cooling field strength and the PM thickness. The same cooling field yields negative EB for thin spacers, and positive EB for thicker ones. The EB decay profile as a function of the spacer thickness, and the change of sign, are attributed to long-ranged dipole coupling. Our model, which accounts quantitatively for the experimental results, ignores the short range interfacial exchange interactions of the usual EB theories. Instead, it retains solely the long range dipole field that allows for the coupling of the FM and AFM across the PM spacer. The experiments allow for novel switching capabilities of long range EB systems, while the theory allows description of the structures where the FM and AFM are not in atomic contact. The results provide a new approach to design novel interacting heterostructures.

Mitochondrial DNA as a non-invasive biomarker: Accurate quantification using real time quantitative PCR without co-amplification of pseudogenes and dilution bias

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

Malik, Afshan N., E-mail: afshan.malik@kcl.ac.uk; Shahni, Rojeen; Rodriguez-de-Ledesma, Ana

2011-08-19

Highlights: {yields} Mitochondrial dysfunction is central to many diseases of oxidative stress. {yields} 95% of the mitochondrial genome is duplicated in the nuclear genome. {yields} Dilution of untreated genomic DNA leads to dilution bias. {yields} Unique primers and template pretreatment are needed to accurately measure mitochondrial DNA content. -- Abstract: Circulating mitochondrial DNA (MtDNA) is a potential non-invasive biomarker of cellular mitochondrial dysfunction, the latter known to be central to a wide range of human diseases. Changes in MtDNA are usually determined by quantification of MtDNA relative to nuclear DNA (Mt/N) using real time quantitative PCR. We propose that themore » methodology for measuring Mt/N needs to be improved and we have identified that current methods have at least one of the following three problems: (1) As much of the mitochondrial genome is duplicated in the nuclear genome, many commonly used MtDNA primers co-amplify homologous pseudogenes found in the nuclear genome; (2) use of regions from genes such as {beta}-actin and 18S rRNA which are repetitive and/or highly variable for qPCR of the nuclear genome leads to errors; and (3) the size difference of mitochondrial and nuclear genomes cause a 'dilution bias' when template DNA is diluted. We describe a PCR-based method using unique regions in the human mitochondrial genome not duplicated in the nuclear genome; unique single copy region in the nuclear genome and template treatment to remove dilution bias, to accurately quantify MtDNA from human samples.« less

Useful ion yields for Cameca IMS 3f and 6f SIMS: Limits on quantitative analysis

USGS Publications Warehouse

Hervig, R.L.; Mazdab, F.K.; Williams, Pat; Guan, Y.; Huss, G.R.; Leshin, L.A.

2006-01-01

The useful yields (ions detected/atom sputtered) of major and trace elements in NIST 610 glass were measured by secondary ion mass spectrometry (SIMS) using Cameca IMS 3f and 6f instruments. Useful yields of positive ions at maximum transmission range from 10-4 to 0.2 and are negatively correlated with ionization potential. We quantified the decrease in useful yields when applying energy filtering or high mass resolution techniques to remove molecular interferences. The useful yields of selected negative ions (O, S, Au) in magnetite and pyrite were also determined. These data allow the analyst to determine if a particular analysis (trace element contents or isotopic ratio) can be achieved, given the amount of sample available and the conditions of the analysis. ?? 2005 Elsevier B.V. All rights reserved.

GOTHiC, a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data.

PubMed

Mifsud, Borbala; Martincorena, Inigo; Darbo, Elodie; Sugar, Robert; Schoenfelder, Stefan; Fraser, Peter; Luscombe, Nicholas M

2017-01-01

Hi-C is one of the main methods for investigating spatial co-localisation of DNA in the nucleus. However, the raw sequencing data obtained from Hi-C experiments suffer from large biases and spurious contacts, making it difficult to identify true interactions. Existing methods use complex models to account for biases and do not provide a significance threshold for detecting interactions. Here we introduce a simple binomial probabilistic model that resolves complex biases and distinguishes between true and false interactions. The model corrects biases of known and unknown origin and yields a p-value for each interaction, providing a reliable threshold based on significance. We demonstrate this experimentally by testing the method against a random ligation dataset. Our method outperforms previous methods and provides a statistical framework for further data analysis, such as comparisons of Hi-C interactions between different conditions. GOTHiC is available as a BioConductor package (http://www.bioconductor.org/packages/release/bioc/html/GOTHiC.html).

Helping medical learners recognise and manage unconscious bias toward certain patient groups.

PubMed

Teal, Cayla R; Gill, Anne C; Green, Alexander R; Crandall, Sonia

2012-01-01

For the last 30 years, developments in cognitive sciences have demonstrated that human behaviour, beliefs and attitudes are shaped by automatic and unconscious cognitive processes. Only recently has much attention been paid to how unconscious biases based on certain patient characteristics may: (i) result in behaviour that is preferential toward or against specific patients; (ii) influence treatment decisions, and (iii) adversely influence the patient-doctor relationship. Partly in response to accreditation requirements, medical educators are now exploring how they might help students and residents to develop awareness of their own potential biases and strategies to mitigate them. In this paper, we briefly review key cognition concepts and describe the limited published literature about educational strategies for addressing unconscious bias. We propose a developmental model to illustrate how individuals might move from absolute denial of unconscious bias to the integration of strategies to mitigate its influence on their interactions with patients and offer recommendations to educators and education researchers. © Blackwell Publishing Ltd 2012.

Rapid Evolution of Ovarian-Biased Genes in the Yellow Fever Mosquito (Aedes aegypti).

PubMed

Whittle, Carrie A; Extavour, Cassandra G

2017-08-01

Males and females exhibit highly dimorphic phenotypes, particularly in their gonads, which is believed to be driven largely by differential gene expression. Typically, the protein sequences of genes upregulated in males, or male-biased genes, evolve rapidly as compared to female-biased and unbiased genes. To date, the specific study of gonad-biased genes remains uncommon in metazoans. Here, we identified and studied a total of 2927, 2013, and 4449 coding sequences (CDS) with ovary-biased, testis-biased, and unbiased expression, respectively, in the yellow fever mosquito Aedes aegypti The results showed that ovary-biased and unbiased CDS had higher nonsynonymous to synonymous substitution rates (dN/dS) and lower optimal codon usage (those codons that promote efficient translation) than testis-biased genes. Further, we observed higher dN/dS in ovary-biased genes than in testis-biased genes, even for genes coexpressed in nonsexual (embryo) tissues. Ovary-specific genes evolved exceptionally fast, as compared to testis- or embryo-specific genes, and exhibited higher frequency of positive selection. Genes with ovary expression were preferentially involved in olfactory binding and reception. We hypothesize that at least two potential mechanisms could explain rapid evolution of ovary-biased genes in this mosquito: (1) the evolutionary rate of ovary-biased genes may be accelerated by sexual selection (including female-female competition or male-mate choice) affecting olfactory genes during female swarming by males, and/or by adaptive evolution of olfactory signaling within the female reproductive system ( e.g. , sperm-ovary signaling); and/or (2) testis-biased genes may exhibit decelerated evolutionary rates due to the formation of mating plugs in the female after copulation, which limits male-male sperm competition. Copyright © 2017 by the Genetics Society of America.

Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset

NASA Astrophysics Data System (ADS)

Lange, Stefan

2018-05-01

Many meteorological forcing datasets include bias-corrected surface downwelling longwave and shortwave radiation (rlds and rsds). Methods used for such bias corrections range from multi-year monthly mean value scaling to quantile mapping at the daily timescale. An additional downscaling is necessary if the data to be corrected have a higher spatial resolution than the observational data used to determine the biases. This was the case when EartH2Observe (E2OBS; Calton et al., 2016) rlds and rsds were bias-corrected using more coarsely resolved Surface Radiation Budget (SRB; Stackhouse Jr. et al., 2011) data for the production of the meteorological forcing dataset EWEMBI (Lange, 2016). This article systematically compares various parametric quantile mapping methods designed specifically for this purpose, including those used for the production of EWEMBI rlds and rsds. The methods vary in the timescale at which they operate, in their way of accounting for physical upper radiation limits, and in their approach to bridging the spatial resolution gap between E2OBS and SRB. It is shown how temporal and spatial variability deflation related to bilinear interpolation and other deterministic downscaling approaches can be overcome by downscaling the target statistics of quantile mapping from the SRB to the E2OBS grid such that the sub-SRB-grid-scale spatial variability present in the original E2OBS data is retained. Cross validations at the daily and monthly timescales reveal that it is worthwhile to take empirical estimates of physical upper limits into account when adjusting either radiation component and that, overall, bias correction at the daily timescale is more effective than bias correction at the monthly timescale if sampling errors are taken into account.

Cognitive Bias in Systems Verification

NASA Technical Reports Server (NTRS)

Larson, Steve

2012-01-01

Working definition of cognitive bias: Patterns by which information is sought and interpreted that can lead to systematic errors in decisions. Cognitive bias is used in diverse fields: Economics, Politics, Intelligence, Marketing, to name a few. Attempts to ground cognitive science in physical characteristics of the cognitive apparatus exceed our knowledge. Studies based on correlations; strict cause and effect is difficult to pinpoint. Effects cited in the paper and discussed here have been replicated many times over, and appear sound. Many biases have been described, but it is still unclear whether they are all distinct. There may only be a handful of fundamental biases, which manifest in various ways. Bias can effect system verification in many ways . Overconfidence -> Questionable decisions to deploy. Availability -> Inability to conceive critical tests. Representativeness -> Overinterpretation of results. Positive Test Strategies -> Confirmation bias. Debiasing at individual level very difficult. The potential effect of bias on the verification process can be managed, but not eliminated. Worth considering at key points in the process.

Yield: it's now an entitlement

NASA Astrophysics Data System (ADS)

George, Bill

1994-09-01

Only a few years ago, the primary method of cost reduction and productivity improvement in the semiconductor industry was increasing manufacturing yields throughout the process. Many of the remarkable reliability improvements realized over the past decade have come about as a result of actions that were originally taken primarily to improve device yields. Obviously, the practice of productivity improvement through yield enhancement is limited to the attainment of 100% yield, at which point some other mechanism must be employed. Traditionally, new products have been introduced to manufacturing at a point of relative immaturity, and semiconductor producers have relied on the traditional `learning curve' method of yield improvement to attain profitable levels of manufacturing yield. Recently, results of a survey of several fabs by a group of University of California at Berkeley researchers in the Competitive Semiconductor Manufacturing Program indicate that most factories learn at about the same rate after startup, in terms of both line yield and defectivity. If this is indeed generally true, then the most competitive factor is the one that starts with the highest yield, and it is difficult to displace a leader once his lead has been established. The two observations made above carry enormous implications for the semiconductor development or manufacturing professional. First, one must achieve very high yields in order to even play the game. Second, the achievement of competitive yields over time in the life of a factory is determined even before the factory is opened, in the planning and development phase. Third, and perhaps most uncomfortable for those of us who have relied on yield improvement as a cost driver, the winners of the nineties will find new levers to drive costs down, having already gotten the benefit of very high yield. This paper looks at the question of how the winners will achieve the critical measures of success, high initial yield and utilization

Limitations to photosynthesis under light and heat stress in three high-yielding wheat genotypes.

PubMed

Monneveux, Philippe; Pastenes, Claudio; Reynolds, Matthew P

2003-06-01

Three high-yielding wheat genotypes (T. aestivum L., c.v. Siete Cerros, Seri and Bacanora, released in 1966, 1982 and 1988, respectively) were grown under irrigation in two high radiation, low relative humidity environments (Tlaltizapan and Ciudad Obregon CIMMYT experimental stations, Mexico). Gas exchange and fluorescence parameters were assessed on the flag leaf during the day. Carbon isotope discrimination (delta) was analysed in flag leaf at anthesis and in grain at maturity. In both environments, gas exchange and fluorescence parameters varied markedly with irradiance and temperature. Analysis of their respective variation indicated the occurrence of photo-respiration and photo-inhibition, particularly in Tlaltizapan, the warmest environment, and in Siete Cerros. In Ciudad Obregon (high-yielding environment) lower Ci (internal CO2 concentration) and delta La (carbon isotope discrimination of the leaf) suggested a higher intrinsic photosynthetic capacity in the variety Bacanora. Higher yield of this genotype was also associated with higher Fv'/Fo' (ratio of photochemical and non photochemical rate constants in the light) and Fm'/Fm (ratio of the non photochemical rate constants in the dark and light adapted state).

Publication bias in situ

PubMed Central

Phillips, Carl V

2004-01-01

Background Publication bias, as typically defined, refers to the decreased likelihood of studies' results being published when they are near the null, not statistically significant, or otherwise "less interesting." But choices about how to analyze the data and which results to report create a publication bias within the published results, a bias I label "publication bias in situ" (PBIS). Discussion PBIS may create much greater bias in the literature than traditionally defined publication bias (the failure to publish any result from a study). The causes of PBIS are well known, consisting of various decisions about reporting that are influenced by the data. But its impact is not generally appreciated, and very little attention is devoted to it. What attention there is consists largely of rules for statistical analysis that are impractical and do not actually reduce the bias in reported estimates. PBIS cannot be reduced by statistical tools because it is not fundamentally a problem of statistics, but rather of non-statistical choices and plain language interpretations. PBIS should be recognized as a phenomenon worthy of study – it is extremely common and probably has a huge impact on results reported in the literature – and there should be greater systematic efforts to identify and reduce it. The paper presents examples, including results of a recent HIV vaccine trial, that show how easily PBIS can have a large impact on reported results, as well as how there can be no simple answer to it. Summary PBIS is a major problem, worthy of substantially more attention than it receives. There are ways to reduce the bias, but they are very seldom employed because they are largely unrecognized. PMID:15296515

Publication bias in situ.

PubMed

Phillips, Carl V

2004-08-05

Publication bias, as typically defined, refers to the decreased likelihood of studies' results being published when they are near the null, not statistically significant, or otherwise "less interesting." But choices about how to analyze the data and which results to report create a publication bias within the published results, a bias I label "publication bias in situ" (PBIS). PBIS may create much greater bias in the literature than traditionally defined publication bias (the failure to publish any result from a study). The causes of PBIS are well known, consisting of various decisions about reporting that are influenced by the data. But its impact is not generally appreciated, and very little attention is devoted to it. What attention there is consists largely of rules for statistical analysis that are impractical and do not actually reduce the bias in reported estimates. PBIS cannot be reduced by statistical tools because it is not fundamentally a problem of statistics, but rather of non-statistical choices and plain language interpretations. PBIS should be recognized as a phenomenon worthy of study - it is extremely common and probably has a huge impact on results reported in the literature - and there should be greater systematic efforts to identify and reduce it. The paper presents examples, including results of a recent HIV vaccine trial, that show how easily PBIS can have a large impact on reported results, as well as how there can be no simple answer to it. PBIS is a major problem, worthy of substantially more attention than it receives. There are ways to reduce the bias, but they are very seldom employed because they are largely unrecognized.

Towards physics responsible for large-scale Lyman-α forest bias parameters

DOE PAGES

Agnieszka M. Cieplak; Slosar, Anze

2016-03-08

Using a series of carefully constructed numerical experiments based on hydrodynamic cosmological SPH simulations, we attempt to build an intuition for the relevant physics behind the large scale density (b δ) and velocity gradient (b η) biases of the Lyman-α forest. Starting with the fluctuating Gunn-Peterson approximation applied to the smoothed total density field in real-space, and progressing through redshift-space with no thermal broadening, redshift-space with thermal broadening and hydrodynamically simulated baryon fields, we investigate how approximations found in the literature fare. We find that Seljak's 2012 analytical formulae for these bias parameters work surprisingly well in the limit ofmore » no thermal broadening and linear redshift-space distortions. We also show that his b η formula is exact in the limit of no thermal broadening. Since introduction of thermal broadening significantly affects its value, we speculate that a combination of large-scale measurements of b η and the small scale flux PDF might be a sensitive probe of the thermal state of the IGM. Lastly, we find that large-scale biases derived from the smoothed total matter field are within 10–20% to those based on hydrodynamical quantities, in line with other measurements in the literature.« less

Towards physics responsible for large-scale Lyman-α forest bias parameters

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

Agnieszka M. Cieplak; Slosar, Anze

Using a series of carefully constructed numerical experiments based on hydrodynamic cosmological SPH simulations, we attempt to build an intuition for the relevant physics behind the large scale density (b δ) and velocity gradient (b η) biases of the Lyman-α forest. Starting with the fluctuating Gunn-Peterson approximation applied to the smoothed total density field in real-space, and progressing through redshift-space with no thermal broadening, redshift-space with thermal broadening and hydrodynamically simulated baryon fields, we investigate how approximations found in the literature fare. We find that Seljak's 2012 analytical formulae for these bias parameters work surprisingly well in the limit ofmore » no thermal broadening and linear redshift-space distortions. We also show that his b η formula is exact in the limit of no thermal broadening. Since introduction of thermal broadening significantly affects its value, we speculate that a combination of large-scale measurements of b η and the small scale flux PDF might be a sensitive probe of the thermal state of the IGM. Lastly, we find that large-scale biases derived from the smoothed total matter field are within 10–20% to those based on hydrodynamical quantities, in line with other measurements in the literature.« less

Quantifying the Usefulness of Ensemble-Based Precipitation Forecasts with Respect to Water Use and Yield during a Field Trial

NASA Astrophysics Data System (ADS)

Christ, E.; Webster, P. J.; Collins, G.; Byrd, S.

2014-12-01

Recent droughts and the continuing water wars between the states of Georgia, Alabama and Florida have made agricultural producers more aware of the importance of managing their irrigation systems more efficiently. Many southeastern states are beginning to consider laws that will require monitoring and regulation of water used for irrigation. Recently, Georgia suspended issuing irrigation permits in some areas of the southwestern portion of the state to try and limit the amount of water being used in irrigation. However, even in southern Georgia, which receives on average between 23 and 33 inches of rain during the growing season, irrigation can significantly impact crop yields. In fact, studies have shown that when fields do not receive rainfall at the most critical stages in the life of cotton, yield for irrigated fields can be up to twice as much as fields for non-irrigated cotton. This leads to the motivation for this study, which is to produce a forecast tool that will enable producers to make more efficient irrigation management decisions. We will use the ECMWF (European Centre for Medium-Range Weather Forecasts) vars EPS (Ensemble Prediction System) model precipitation forecasts for the grid points included in the 1◦ x 1◦ lat/lon square surrounding the point of interest. We will then apply q-to-q bias corrections to the forecasts. Once we have applied the bias corrections, we will use the check-book method of irrigation scheduling to determine the probability of receiving the required amount of rainfall for each week of the growing season. These forecasts will be used during a field trial conducted at the CM Stripling Irrigation Research Park in Camilla, Georgia. This research will compare differences in yield and water use among the standard checkbook method of irrigation, which uses no precipitation forecast knowledge, the weather.com forecast, a dry land plot, and the ensemble-based forecasts mentioned above.

Influential Cognitive Processes on Framing Biases in Aging

PubMed Central

Perez, Alison M.; Spence, Jeffrey Scott; Kiel, L. D.; Venza, Erin E.; Chapman, Sandra B.

2018-01-01

Factors that contribute to overcoming decision-making biases in later life pose an important investigational question given the increasing older adult population. Limited empirical evidence exists and the literature remains equivocal of whether increasing age is associated with elevated susceptibility to decision-making biases such as framing effects. Research into the individual differences contributing to decision-making ability may offer better understanding of the influence of age in decision-making ability. Changes in cognition underlying decision-making have been shown with increased age and may contribute to individual variability in decision-making abilities. This study had three aims; (1) to understand the influence of age on susceptibility to decision-making biases as measured by framing effects across a large, continuous age range; (2) to examine influence of cognitive abilities that change with age; and (3) to understand the influence of individual factors such as gender and education on susceptibility to framing effects. 200 individuals (28–79 years of age) were tested on a large battery of cognitive measures in the domains of executive function, memory and complex attention. Findings from this study demonstrated that cognitive abilities such as strategic control and delayed memory better predicted susceptibility to framing biases than age. The current findings demonstrate that age may not be as influential a factor in decision-making as cognitive ability and cognitive reserve. These findings motivate future studies to better characterize cognitive ability to determine decision-making susceptibilities in aging populations. PMID:29867641

Influential Cognitive Processes on Framing Biases in Aging.

PubMed

Perez, Alison M; Spence, Jeffrey Scott; Kiel, L D; Venza, Erin E; Chapman, Sandra B

2018-01-01

Factors that contribute to overcoming decision-making biases in later life pose an important investigational question given the increasing older adult population. Limited empirical evidence exists and the literature remains equivocal of whether increasing age is associated with elevated susceptibility to decision-making biases such as framing effects. Research into the individual differences contributing to decision-making ability may offer better understanding of the influence of age in decision-making ability. Changes in cognition underlying decision-making have been shown with increased age and may contribute to individual variability in decision-making abilities. This study had three aims; (1) to understand the influence of age on susceptibility to decision-making biases as measured by framing effects across a large, continuous age range; (2) to examine influence of cognitive abilities that change with age; and (3) to understand the influence of individual factors such as gender and education on susceptibility to framing effects. 200 individuals (28-79 years of age) were tested on a large battery of cognitive measures in the domains of executive function, memory and complex attention. Findings from this study demonstrated that cognitive abilities such as strategic control and delayed memory better predicted susceptibility to framing biases than age. The current findings demonstrate that age may not be as influential a factor in decision-making as cognitive ability and cognitive reserve. These findings motivate future studies to better characterize cognitive ability to determine decision-making susceptibilities in aging populations.

Local and sex-specific biases in crossover vs. noncrossover outcomes at meiotic recombination hot spots in mice.

PubMed

de Boer, Esther; Jasin, Maria; Keeney, Scott

2015-08-15

Meiotic recombination initiated by programmed double-strand breaks (DSBs) yields two types of interhomolog recombination products, crossovers and noncrossovers, but what determines whether a DSB will yield a crossover or noncrossover is not understood. In this study, we analyzed the influence of sex and chromosomal location on mammalian recombination outcomes by constructing fine-scale recombination maps in both males and females at two mouse hot spots located in different regions of the same chromosome. These include the most comprehensive maps of recombination hot spots in oocytes to date. One hot spot, located centrally on chromosome 1, behaved similarly in male and female meiosis: Crossovers and noncrossovers formed at comparable levels and ratios in both sexes. In contrast, at a distal hot spot, crossovers were recovered only in males even though noncrossovers were obtained at similar frequencies in both sexes. These findings reveal an example of extreme sex-specific bias in recombination outcome. We further found that estimates of relative DSB levels are surprisingly poor predictors of relative crossover frequencies between hot spots in males. Our results demonstrate that the outcome of mammalian meiotic recombination can be biased, that this bias can vary depending on location and cellular context, and that DSB frequency is not the only determinant of crossover frequency. © 2015 de Boer et al.; Published by Cold Spring Harbor Laboratory Press.

Soybean grown under elevated CO2 benefits more under low temperature than high temperature stress: Varying response of photosynthetic limitations, leaf metabolites, growth, and seed yield.

PubMed

Xu, Guangli; Singh, Shardendu K; Reddy, Vangimalla R; Barnaby, Jinyoung Y; Sicher, Richard C; Li, Tian

2016-10-20

To evaluate the combined effect of temperature and CO 2 on photosynthetic processes, leaf metabolites and growth, soybean was grown under a controlled environment at low (22/18°C, LT), optimum (28/24°C, OT) and high (36/32°C HT) temperatures under ambient (400μmolmol -1 ; aCO 2 ) or elevated (800μmolmol -1 ; eCO 2 ) CO 2 concentrations during the reproductive stage. In general, the rate of photosynthesis (A), stomatal (g s ) and mesophyll (g m ) conductance, quantum yield of photosystem II, rates of maximum carboxylation (V Cmax ), and electron transport (J) increased with temperature across CO 2 levels. However, compared with OT, the percentage increases in these parameters at HT were lower than the observed decline at LT. The photosynthetic limitation at LT and OT was primarily caused by photo-biochemical processes (49-58%, L b ) followed by stomatal (27-32%, L s ) and mesophyll (15-19%, L m ) limitations. However, at HT, it was primarily caused by L s (41%) followed by L b (33%) and L m (26%). The dominance of L b at LT and OT was associated with the accumulation of non-structural carbohydrates (e.g., starch) and several organic acids, whereas this accumulation did not occur at HT, indicating increased metabolic activities. Compared with OT, biomass and seed yield declined more at HT than at LT. The eCO 2 treatment compensated for the temperature-stress effects on biomass but only partially compensated for the effects on seed yield, especially at HT. Photosynthetic downregulation at eCO 2 was possibly due to the accumulation of non-structural carbohydrates and the decrease in g s and A std (standard A measured at 400μmolmol -1 sub-stomatal CO 2 concentration), as well as the lack of CO 2 effect on g m , V Cmax , and J, and photosynthetic limitation. Thus, the photosynthetic limitation was temperature-dependent and was primarily influenced by the alteration in photo-biochemical processes and metabolic activities. Despite the inconsistent response of

Measurement of the $B^-$ lifetime using a simulation free approach for trigger bias correction

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

Aaltonen, T.; /Helsinki Inst. of Phys.; Adelman, J.

2010-04-01

The collection of a large number of B hadron decays to hadronic final states at the CDF II detector is possible due to the presence of a trigger that selects events based on track impact parameters. However, the nature of the selection requirements of the trigger introduces a large bias in the observed proper decay time distribution. A lifetime measurement must correct for this bias and the conventional approach has been to use a Monte Carlo simulation. The leading sources of systematic uncertainty in the conventional approach are due to differences between the data and the Monte Carlo simulation. Inmore » this paper they present an analytic method for bias correction without using simulation, thereby removing any uncertainty between data and simulation. This method is presented in the form of a measurement of the lifetime of the B{sup -} using the mode B{sup -} {yields} D{sup 0}{pi}{sup -}. The B{sup -} lifetime is measured as {tau}{sub B{sup -}} = 1.663 {+-} 0.023 {+-} 0.015 ps, where the first uncertainty is statistical and the second systematic. This new method results in a smaller systematic uncertainty in comparison to methods that use simulation to correct for the trigger bias.« less

Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias.

PubMed

Clarke, Laurence J; Soubrier, Julien; Weyrich, Laura S; Cooper, Alan

2014-11-01

Studies of insect assemblages are suited to the simultaneous DNA-based identification of multiple taxa known as metabarcoding. To obtain accurate estimates of diversity, metabarcoding markers ideally possess appropriate taxonomic coverage to avoid PCR-amplification bias, as well as sufficient sequence divergence to resolve species. We used in silico PCR to compare the taxonomic coverage and resolution of newly designed insect metabarcodes (targeting 16S) with that of existing markers [16S and cytochrome oxidase c subunit I (COI)] and then compared their efficiency in vitro. Existing metabarcoding primers amplified in silico <75% of insect species with complete mitochondrial genomes available, whereas new primers targeting 16S provided >90% coverage. Furthermore, metabarcodes targeting COI appeared to introduce taxonomic PCR-amplification bias, typically amplifying a greater percentage of Lepidoptera and Diptera species, while failing to amplify certain orders in silico. To test whether bias predicted in silico was observed in vitro, we created an artificial DNA blend containing equal amounts of DNA from 14 species, representing 11 insect orders and one arachnid. We PCR-amplified the blend using five primer sets, targeting either COI or 16S, with high-throughput amplicon sequencing yielding more than 6 million reads. In vitro results typically corresponded to in silico PCR predictions, with newly designed 16S primers detecting 11 insect taxa present, thus providing equivalent or better taxonomic coverage than COI metabarcodes. Our results demonstrate that in silico PCR is a useful tool for predicting taxonomic bias in mixed template PCR and that researchers should be wary of potential bias when selecting metabarcoding markers. © 2014 John Wiley & Sons Ltd.

Threat bias, not negativity bias, underpins differences in political ideology.

PubMed

Lilienfeld, Scott O; Latzman, Robert D

2014-06-01

Although disparities in political ideology are rooted partly in dispositional differences, Hibbing et al.'s analysis paints with an overly broad brush. Research on the personality correlates of liberal-conservative differences points not to global differences in negativity bias, but to differences in threat bias, probably emanating from differences in fearfulness. This distinction bears implications for etiological research and persuasion efforts.

Evaluation of Fission Product Critical Experiments and Associated Biases for Burnup Credit Validation

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

Mueller, Don; Rearden, Bradley T; Reed, Davis Allan

2010-01-01

One of the challenges associated with implementation of burnup credit is the validation of criticality calculations used in the safety evaluation; in particular the availability and use of applicable critical experiment data. The purpose of the validation is to quantify the relationship between reality and calculated results. Validation and determination of bias and bias uncertainty require the identification of sets of critical experiments that are similar to the criticality safety models. A principal challenge for crediting fission products (FP) in a burnup credit safety evaluation is the limited availability of relevant FP critical experiments for bias and bias uncertainty determination.more » This paper provides an evaluation of the available critical experiments that include FPs, along with bounding, burnup-dependent estimates of FP biases generated by combining energy dependent sensitivity data for a typical burnup credit application with the nuclear data uncertainty information distributed with SCALE 6. A method for determining separate bias and bias uncertainty values for individual FPs and illustrative results is presented. Finally, a FP bias calculation method based on data adjustment techniques and reactivity sensitivity coefficients calculated with the SCALE sensitivity/uncertainty tools and some typical results is presented. Using the methods described in this paper, the cross-section bias for a representative high-capacity spent fuel cask associated with the ENDF/B-VII nuclear data for 16 most important stable or near stable FPs is predicted to be no greater than 2% of the total worth of the 16 FPs, or less than 0.13 % k/k.« less

Asthma among World Trade Center First Responders: A Qualitative Synthesis and Bias Assessment.

PubMed

Kim, Hyun; Baidwan, Navneet Kaur; Kriebel, David; Cifuentes, Manuel; Baron, Sherry

2018-05-23

The World Trade Center (WTC) disaster exposed the responders to several hazards. Three cohorts i.e., the Fire Department of New York (FDNY), the General Responder Cohort (GRC), and the WTC Health Registry (WTCHR) surveyed the exposed responder population. We searched Pubmed and Web of Science for literature on a well-published association between the WTC exposures and asthma, focusing on new-onset self-reported physician-diagnosed asthma. The resulting five articles were qualitatively assessed for potential biases. These papers were independently reviewed by the co-authors, and conclusions were derived after discussions. While, the cohorts had well-defined eligibility criteria, they lacked information about the entire exposed population. We conclude that selection and surveillance biases may have occurred in the GRC and WTCHR cohorts, but were likely to have been minimal in the FDNY cohort. Health care benefits available to responders may have increased the reporting of both exposure and outcome in the former, and decreased outcome reporting in the FDNY cohort. Irrespective of the biases, the studies showed similar findings, confirming the association between WTC exposure and self-reported physician-diagnosed asthma among responders. This suggests that health data gathered under great duress and for purposes other than epidemiology can yield sound conclusions. Potential biases can, however, be minimized by having validated survey instruments and worker registries in place before events occur.

Good practices for quantitative bias analysis.

PubMed

Lash, Timothy L; Fox, Matthew P; MacLehose, Richard F; Maldonado, George; McCandless, Lawrence C; Greenland, Sander

2014-12-01

Quantitative bias analysis serves several objectives in epidemiological research. First, it provides a quantitative estimate of the direction, magnitude and uncertainty arising from systematic errors. Second, the acts of identifying sources of systematic error, writing down models to quantify them, assigning values to the bias parameters and interpreting the results combat the human tendency towards overconfidence in research results, syntheses and critiques and the inferences that rest upon them. Finally, by suggesting aspects that dominate uncertainty in a particular research result or topic area, bias analysis can guide efficient allocation of sparse research resources. The fundamental methods of bias analyses have been known for decades, and there have been calls for more widespread use for nearly as long. There was a time when some believed that bias analyses were rarely undertaken because the methods were not widely known and because automated computing tools were not readily available to implement the methods. These shortcomings have been largely resolved. We must, therefore, contemplate other barriers to implementation. One possibility is that practitioners avoid the analyses because they lack confidence in the practice of bias analysis. The purpose of this paper is therefore to describe what we view as good practices for applying quantitative bias analysis to epidemiological data, directed towards those familiar with the methods. We focus on answering questions often posed to those of us who advocate incorporation of bias analysis methods into teaching and research. These include the following. When is bias analysis practical and productive? How does one select the biases that ought to be addressed? How does one select a method to model biases? How does one assign values to the parameters of a bias model? How does one present and interpret a bias analysis?. We hope that our guide to good practices for conducting and presenting bias analyses will encourage

Bias Properties of Extragalactic Distance Indicators. VIII. H0 from Distance-limited Luminosity Class and Morphological Type-Specific Luminosity Functions for SB, SBC, and SC Galaxies Calibrated Using Cepheids

NASA Astrophysics Data System (ADS)

Sandage, Allan

1999-12-01

Relative, reduced to absolute, magnitude distributions are obtained for Sb, Sbc, and Sc galaxies in the flux-limited Revised Shapley-Ames Catalog (RSA2) for each van den Bergh luminosity class (L), within each Hubble type (T). The method to isolate bias-free subsets of the total sample is via Spaenhauer diagrams, as in previous papers of this series. The distance-limited type and class-specific luminosity functions are normalized to numbers of galaxies per unit volume (105 Mpc3), rather than being left as relative functions, as in Paper V. The functions are calculated using kinematic absolute magnitudes, based on an arbitrary trial value of H0=50. Gaussian fits to the individual normalized functions are listed for each T and L subclass. As in Paper V, the data can be freed from the T and L dependencies by applying a correction of 0.23T+0.5L to the individual absolute magnitudes. Here, T=3 for Sb, 4 for Sbc, and 5 for Sc galaxies, and the L values range from 1 to 6 as the luminosity class changes from I to III-IV. The total luminosity function, obtained by combining the volume-normalized Sb, Sbc, and Sc individual luminosity functions, each corrected for the T and L dependencies, has an rms dispersion of 0.67 mag, similar to much of the Tully-Fisher parameter space. Absolute calibration of the trial kinematic absolute magnitudes is made using 27 galaxies with known T and L that also have Cepheid distances. This permits the systematic correction to the H0=50 kinematic absolute magnitudes of 0.22+/-0.12 mag, givingH0=55+/-3(internal) km s-1 Mpc-1 . The Cepheid distances are based on the Madore/Freedman Cepheid period-luminosity (PL) zero point that requires (m-M)0=18.50 for the LMC. Using the modern LMC modulus of (m-M)0=18.58 requires a 4% decrease in H0, giving a final value of H0=53+/-7 (external) by this method. These values of H0, based here on the method of luminosity functions, are in good agreement with (1) H0=55+/-5 by Theureau and coworkers from their bias

Hindsight bias and outcome bias in the social construction of medical negligence: a review.

PubMed

Hugh, Thomas B; Dekker, Sidney W A

2009-05-01

Medical negligence has been the subject of much public debate in recent decades. Although the steep increase in the frequency and size of claims against doctors at the end of the last century appears to have plateaued, in Australia at least, medical indemnity costs and consequences are still a matter of concern for doctors, medical defence organisations and governments in most developed countries. Imprecision in the legal definition of negligence opens the possibility that judgments of this issue at several levels may be subject to hindsight and outcome bias. Hindsight bias relates to the probability of an adverse event perceived by a retrospective observer ("I would have known it was going to happen"), while outcome bias is a largely subconscious cognitive distortion produced by the observer's knowledge of the adverse outcome. This review examines the relevant legal, medical, psychological and sociological literature on the operation of these pervasive and universal biases in the retrospective evaluation of adverse events. A finding of medical negligence is essentially an after-the-event social construction and is invariably affected by hindsight bias and knowledge of the adverse outcome. Such biases obviously pose a threat to the fairness of judgments. A number of debiasing strategies have been suggested but are relatively ineffective because of the universality and strength of these biases and the inherent difficulty of concealing from expert witnesses knowledge of the outcome. Education about the effect of the biases is therefore important for lawyers, medical expert witnesses and the judiciary.

Biasogram: Visualization of Confounding Technical Bias in Gene Expression Data

PubMed Central

Krzystanek, Marcin; Szallasi, Zoltan; Eklund, Aron C.

2013-01-01

Gene expression profiles of clinical cohorts can be used to identify genes that are correlated with a clinical variable of interest such as patient outcome or response to a particular drug. However, expression measurements are susceptible to technical bias caused by variation in extraneous factors such as RNA quality and array hybridization conditions. If such technical bias is correlated with the clinical variable of interest, the likelihood of identifying false positive genes is increased. Here we describe a method to visualize an expression matrix as a projection of all genes onto a plane defined by a clinical variable and a technical nuisance variable. The resulting plot indicates the extent to which each gene is correlated with the clinical variable or the technical variable. We demonstrate this method by applying it to three clinical trial microarray data sets, one of which identified genes that may have been driven by a confounding technical variable. This approach can be used as a quality control step to identify data sets that are likely to yield false positive results. PMID:23613961

Modelling cognitive affective biases in major depressive disorder using rodents

PubMed Central

Hales, Claire A; Stuart, Sarah A; Anderson, Michael H; Robinson, Emma S J

2014-01-01

Major depressive disorder (MDD) affects more than 10% of the population, although our understanding of the underlying aetiology of the disease and how antidepressant drugs act to remediate symptoms is limited. Major obstacles include the lack of availability of good animal models that replicate aspects of the phenotype and tests to assay depression-like behaviour in non-human species. To date, research in rodents has been dominated by two types of assays designed to test for depression-like behaviour: behavioural despair tests, such as the forced swim test, and measures of anhedonia, such as the sucrose preference test. These tests have shown relatively good predictive validity in terms of antidepressant efficacy, but have limited translational validity. Recent developments in clinical research have revealed that cognitive affective biases (CABs) are a key feature of MDD. Through the development of neuropsychological tests to provide objective measures of CAB in humans, we have the opportunity to use ‘reverse translation’ to develop and evaluate whether similar methods are suitable for research into MDD using animals. The first example of this approach was reported in 2004 where rodents in a putative negative affective state were shown to exhibit pessimistic choices in a judgement bias task. Subsequent work in both judgement bias tests and a novel affective bias task suggest that these types of assay may provide translational methods for studying MDD using animals. This review considers recent work in this area and the pharmacological and translational validity of these new animal models of CABs. Linked Articles This article is part of a themed section on Animal Models in Psychiatry Research. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2014.171.issue-20 PMID:24467454

Complementary frame reconstruction: a low-biased dynamic PET technique for low count density data in projection space

NASA Astrophysics Data System (ADS)

Hong, Inki; Cho, Sanghee; Michel, Christian J.; Casey, Michael E.; Schaefferkoetter, Joshua D.

2014-09-01

A new data handling method is presented for improving the image noise distribution and reducing bias when reconstructing very short frames from low count dynamic PET acquisition. The new method termed ‘Complementary Frame Reconstruction’ (CFR) involves the indirect formation of a count-limited emission image in a short frame through subtraction of two frames with longer acquisition time, where the short time frame data is excluded from the second long frame data before the reconstruction. This approach can be regarded as an alternative to the AML algorithm recently proposed by Nuyts et al, as a method to reduce the bias for the maximum likelihood expectation maximization (MLEM) reconstruction of count limited data. CFR uses long scan emission data to stabilize the reconstruction and avoids modification of algorithms such as MLEM. The subtraction between two long frame images, naturally allows negative voxel values and significantly reduces bias introduced in the final image. Simulations based on phantom and clinical data were used to evaluate the accuracy of the reconstructed images to represent the true activity distribution. Applicability to determine the arterial input function in human and small animal studies is also explored. In situations with limited count rate, e.g. pediatric applications, gated abdominal, cardiac studies, etc., or when using limited doses of short-lived isotopes such as 15O-water, the proposed method will likely be preferred over independent frame reconstruction to address bias and noise issues.

HMO marketing and selection bias: are TEFRA HMOs skimming?

PubMed

Lichtenstein, R; Thomas, J W; Watkins, B; Puto, C; Lepkowski, J; Adams-Watson, J; Simone, B; Vest, D

1992-04-01

The research evidence indicates that health maintenance organizations (HMOs) participating in the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) At-Risk Program tend to experience favorable selection. Although favorable selection might result from patient decisions, a common conjecture is that it can be induced by HMOs through their marketing activities. The purpose of this study is to examine the relationship between HMO marketing strategies and selection bias in TEFRA At-Risk HMOs. A purposive sample of 22 HMOs that were actively marketing their TEFRA programs was selected and data on organizational characteristics, market area characteristics, and HMO marketing decisions were collected. To measure selection bias in these HMOs, the functional health status of approximately 300 enrollees in each HMO was compared to that of 300 non-enrolling beneficiaries in the same area. Three dependent variables, reflecting selection bias at the mean, the low health tail, and the high health tail of the health status distribution were created. Weighted least squares regressions were then used to identify relationships between marketing elements and selection bias. Subject to the statistical limitations of the study, our conclusion is that it is doubtful that HMO marketing decisions are responsible for the prevalence of favorable selection in HMO enrollment. It also appears unlikely that HMOs were differentially targeting healthy and unhealthy segments of the Medicare market.

Bias versus bias: harnessing hindsight to reveal paranormal belief change beyond demand characteristics.

PubMed

Kane, Michael J; Core, Tammy J; Hunt, R Reed

2010-04-01

Psychological change is difficult to assess, in part because self-reported beliefs and attitudes may be biased or distorted. The present study probed belief change, in an educational context, by using the hindsight bias to counter another bias that generally plagues assessment of subjective change. Although research has indicated that skepticism courses reduce paranormal beliefs, those findings may reflect demand characteristics (biases toward desired, skeptical responses). Our hindsight-bias procedure circumvented demand by asking students, following semester-long skepticism (and control) courses, to recall their precourse levels of paranormal belief. People typically remember themselves as previously thinking, believing, and acting as they do now, so current skepticism should provoke false recollections of previous skepticism. Given true belief change, therefore, skepticism students should have remembered themselves as having been more skeptical than they were. They did, at least about paranormal topics that were covered most extensively in the course. Our findings thus show hindsight to be useful in evaluating cognitive change beyond demand characteristics.

Biases in simulation of the rice phenology models when applied in warmer climates

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, T.; Yang, X.; Simelton, E.

2015-12-01

The current model inter-comparison studies highlight the difference in projections between crop models when they are applied to warmer climates, but these studies do not provide results on how the accuracy of the models would change in these projections because the adequate observations under largely diverse growing season temperature (GST) are often unavailable. Here, we investigate the potential changes in the accuracy of rice phenology models when these models were applied to a significantly warmer climate. We collected phenology data from 775 trials with 19 cultivars in 5 Asian countries (China, India, Philippines, Bangladesh and Thailand). Each cultivar encompasses the phenology observations under diverse GST regimes. For a given rice cultivar in different trials, the GST difference reaches 2.2 to 8.2°C, which allows us to calibrate the models under lower GST and validate under higher GST (i.e., warmer climates). Four common phenology models representing major algorithms on simulations of rice phenology, and three model calibration experiments were conducted. The results suggest that the bilinear and beta models resulted in gradually increasing phenology bias (Figure) and double yield bias per percent increase in phenology bias, whereas the growing-degree-day (GDD) and exponential models maintained a comparatively constant bias when applied in warmer climates (Figure). Moreover, the bias of phenology estimated by the bilinear and beta models did not reduce with increase in GST when all data were used to calibrate models. These suggest that variations in phenology bias are primarily attributed to intrinsic properties of the respective phenology model rather than on the calibration dataset. Therefore we conclude that using the GDD and exponential models has more chances of predicting rice phenology correctly and thus, production under warmer climates, and result in effective agricultural strategic adaptation to and mitigation of climate change.

Spin relaxation measurements of electrostatic bias in intermolecular exploration

NASA Astrophysics Data System (ADS)

Teng, Ching-Ling; Bryant, Robert G.

2006-04-01

We utilize the paramagnetic contribution to proton spin-lattice relaxation rate constants induced by freely diffusing charged paramagnetic centers to investigate the effect of charge on the intermolecular exploration of a protein by the small molecule. The proton NMR spectrum provided 255 resolved resonances that report how the explorer molecule local concentration varies with position on the surface. The measurements integrate over local dielectric constant variations, and, in principle, provide an experimental characterization of the surface free energy sampling biases introduced by the charge distribution on the protein. The experimental results for ribonuclease A obtained using positive, neutral, and negatively charged small nitroxide radicals are qualitatively similar to those expected from electrostatic calculations. However, while systematic electrostatic trends are apparent, the three different combinations of the data sets do not yield internally consistent values for the electrostatic contribution to the intermolecular free energy. We attribute this failure to the weakness of the electrostatic sampling bias for charged nitroxides in water and local variations in effective translational diffusion constant at the water-protein interface, which enters the nuclear spin relaxation equations for the nitroxide-proton dipolar coupling.

Three-input majority function as the unique optimal function for the bias amplification using nonlocal boxes

NASA Astrophysics Data System (ADS)

Mori, Ryuhei

2016-11-01

Brassard et al. [Phys. Rev. Lett. 96, 250401 (2006), 10.1103/PhysRevLett.96.250401] showed that shared nonlocal boxes with a CHSH (Clauser, Horne, Shimony, and Holt) probability greater than 3/+√{6 } 6 yield trivial communication complexity. There still exists a gap with the maximum CHSH probability 2/+√{2 } 4 achievable by quantum mechanics. It is an interesting open question to determine the exact threshold for the trivial communication complexity. Brassard et al.'s idea is based on recursive bias amplification by the three-input majority function. It was not obvious if another choice of function exhibits stronger bias amplification. We show that the three-input majority function is the unique optimal function, so that one cannot improve the threshold 3/+√{6 } 6 by Brassard et al.'s bias amplification. In this work, protocols for computing the function used for the bias amplification are restricted to be nonadaptive protocols or a particular adaptive protocol inspired by Pawłowski et al.'s protocol for information causality [Nature (London) 461, 1101 (2009), 10.1038/nature08400]. We first show an adaptive protocol inspired by Pawłowski et al.'s protocol, and then show that the adaptive protocol improves upon nonadaptive protocols. Finally, we show that the three-input majority function is the unique optimal function for the bias amplification if we apply the adaptive protocol to each step of the bias amplification.

The CHESS method of forensic opinion formulation: striving to checkmate bias.

PubMed

Wills, Cheryl D

2008-01-01

Expert witnesses use various methods to render dispassionate opinions. Some forensic psychiatrists acknowledge bias up front; other experts use principles endorsed by the American Academy of Psychiatry and the Law or other professional organizations. This article introduces CHESS, a systematic method for reducing bias in expert opinions. The CHESS method involves identifying a Claim or preliminary opinion; developing a Hierarchy of supporting evidence; examining the evidence for weaknesses or areas of Exposure; Studying and revising the claim and supporting evidence; and Synthesizing a revised opinion. Case examples illustrate how the CHESS method may help experts reduce bias while strengthening opinions. The method also helps experts prepare for court by reminding them to anticipate questions that may be asked during cross-examination. The CHESS method provides a framework for formulating, revising, and identifying limitations of opinions, which allows experts to incorporate neutrality into forensic opinions.

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

Moving Beyond Salmon Bias: Mexican Return Migration and Health Selection

PubMed Central

Diaz, Christina J.; Koning, Stephanie M.; Martinez-Donate, Ana P.

2017-01-01

Despite having lower levels of education and limited access to health care services, Mexican immigrants report better health outcomes than U.S.-born individuals. Research suggests that the Mexican health advantage may be partially attributable to selective return migration among less healthy migrants—often referred to as “salmon bias.” Our study takes advantage of a rare opportunity to observe the health status of Mexican-origin males as they cross the Mexican border. To assess whether unhealthy migrants are disproportionately represented among those who return, we use data from two California-based studies: the California Health Interview Survey; and the Migrante Study, a survey that samples Mexican migrants entering and leaving the United States through Tijuana. We pool these data sources to look for evidence of health-related return migration. Results provide mixed support for salmon bias. Although migrants who report health limitations and frequent stress are more likely to return, we find little evidence that chronic conditions and self-reported health are associated with higher probabilities of return. Results also provide some indication that limited health care access increases the likelihood of return among the least healthy. This study provides new theoretical considerations of return migration and further elucidates the relationship between health and migration decisions. PMID:27848222

Moving Beyond Salmon Bias: Mexican Return Migration and Health Selection.

PubMed

Diaz, Christina J; Koning, Stephanie M; Martinez-Donate, Ana P

2016-12-01

Despite having lower levels of education and limited access to health care services, Mexican immigrants report better health outcomes than U.S.-born individuals. Research suggests that the Mexican health advantage may be partially attributable to selective return migration among less healthy migrants-often referred to as "salmon bias." Our study takes advantage of a rare opportunity to observe the health status of Mexican-origin males as they cross the Mexican border. To assess whether unhealthy migrants are disproportionately represented among those who return, we use data from two California-based studies: the California Health Interview Survey; and the Migrante Study, a survey that samples Mexican migrants entering and leaving the United States through Tijuana. We pool these data sources to look for evidence of health-related return migration. Results provide mixed support for salmon bias. Although migrants who report health limitations and frequent stress are more likely to return, we find little evidence that chronic conditions and self-reported health are associated with higher probabilities of return. Results also provide some indication that limited health care access increases the likelihood of return among the least healthy. This study provides new theoretical considerations of return migration and further elucidates the relationship between health and migration decisions.

Positively Biased Self-Perceptions of Peer Acceptance and Subtypes of Aggression in Children

PubMed Central

Lynch, Rebecca J.; Kistner, Janet A.; Stephens, Haley F.; David-Ferdon, Corinne

2016-01-01

There is a growing body of research linking children’s positively biased self-perceptions with higher levels of aggression. This study extended this area of research by examining prospective associations of positively biased self-perceptions of peer acceptance with overt and relational aggression. In addition, moderating effects of peer rejection were examined to test the “disputed overestimation hypothesis,” which posits that the link between bias and aggression is limited to children who are rejected by their peers. Using a two-wave longitudinal design, measures of peer-rated and self-perceived peer acceptance and peer-rated overt and relational aggression were obtained for 712 children in 3rd through 5th grades (386 girls and 326 boys). Positively biased perceptions led to increases in relational, but not overt, aggression. This pattern was observed even when the effects of gender, race, peer rejection, and overt aggression on relational aggression were controlled. Contrary to the disputed overestimation hypothesis, the prospective associations between bias and aggression did not vary as a function of children’s peer rejection status, thus supporting the view that positive bias predicts future aggressive behavior, regardless of social status. The results are discussed in terms of the comparability with previous findings and practical implications. PMID:26423823

EFFECTS OF BIASES IN VIRIAL MASS ESTIMATION ON COSMIC SYNCHRONIZATION OF QUASAR ACCRETION

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

Steinhardt, Charles L.

2011-09-01

Recent work using virial mass estimates and the quasar mass-luminosity plane has yielded several new puzzles regarding quasar accretion, including a sub-Eddington boundary (SEB) on most quasar accretion, near-independence of the accretion rate from properties of the host galaxy, and a cosmic synchronization of accretion among black holes of a common mass. We consider how these puzzles might change if virial mass estimation turns out to have a systematic bias. As examples, we consider two recent claims of mass-dependent biases in Mg II masses. Under any such correction, the surprising cosmic synchronization of quasar accretion rates and independence from themore » host galaxy remain. The slope and location of the SEB are very sensitive to biases in virial mass estimation, and various mass calibrations appear to favor different possible physical explanations for feedback between the central black hole and its environment. The alternative mass estimators considered do not simply remove puzzling quasar behavior, but rather replace it with new puzzles that may be more difficult to solve than those using current virial mass estimators and the Shen et al. catalog.« less

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

Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods.

PubMed

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

2016-09-27

Cultivation-independent investigation of microbial ecology is biased by the DNA extraction methods used. We aimed to quantify those biases by comparative analysis of the metagenome mined from four diverse naturally fermented foods (bamboo shoot, milk, fish, soybean) using eight different DNA extraction methods with different cell lysis principles. Our findings revealed that the enzymatic lysis yielded higher eubacterial and yeast metagenomic DNA from the food matrices compared to the widely used chemical and mechanical lysis principles. Further analysis of the bacterial community structure by Illumina MiSeq amplicon sequencing revealed a high recovery of lactic acid bacteria by the enzymatic lysis in all food types. However, Bacillaceae, Acetobacteraceae, Clostridiaceae and Proteobacteria were more abundantly recovered when mechanical and chemical lysis principles were applied. The biases generated due to the differential recovery of operational taxonomic units (OTUs) by different DNA extraction methods including DNA and PCR amplicons mix from different methods have been quantitatively demonstrated here. The different methods shared only 29.9-52.0% of the total OTUs recovered. Although similar comparative research has been performed on other ecological niches, this is the first in-depth investigation of quantifying the biases in metagenome mining from naturally fermented foods.

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.

Detecting and correcting for publication bias in meta-analysis - A truncated normal distribution approach.

PubMed

Zhu, Qiaohao; Carriere, K C

2016-01-01

Publication bias can significantly limit the validity of meta-analysis when trying to draw conclusion about a research question from independent studies. Most research on detection and correction for publication bias in meta-analysis focus mainly on funnel plot-based methodologies or selection models. In this paper, we formulate publication bias as a truncated distribution problem, and propose new parametric solutions. We develop methodologies of estimating the underlying overall effect size and the severity of publication bias. We distinguish the two major situations, in which publication bias may be induced by: (1) small effect size or (2) large p-value. We consider both fixed and random effects models, and derive estimators for the overall mean and the truncation proportion. These estimators will be obtained using maximum likelihood estimation and method of moments under fixed- and random-effects models, respectively. We carried out extensive simulation studies to evaluate the performance of our methodology, and to compare with the non-parametric Trim and Fill method based on funnel plot. We find that our methods based on truncated normal distribution perform consistently well, both in detecting and correcting publication bias under various situations.

Phylogeography, intraspecific structure and sex-biased dispersal of Dall's porpoise, Phocoenoides dalli, revealed by mitochondrial and microsatellite DNA analyses.

PubMed

Escorza-Treviño, S; Dizon, A E

2000-08-01

Mitochondrial DNA (mtDNA) control-region sequences and microsatellite loci length polymorphisms were used to estimate phylogeographical patterns (historical patterns underlying contemporary distribution), intraspecific population structure and gender-biased dispersal of Phocoenoides dalli dalli across its entire range. One-hundred and thirteen animals from several geographical strata were sequenced over 379 bp of mtDNA, resulting in 58 mtDNA haplotypes. Analysis using F(ST) values (based on haplotype frequencies) and phi(ST) values (based on frequencies and genetic distances between haplotypes) yielded statistically significant separation (bootstrap values P < 0.05) among most of the stocks currently used for management purposes. A minimum spanning network of haplotypes showed two very distinctive clusters, differentially occupied by western and eastern populations, with some common widespread haplotypes. This suggests some degree of phyletic radiation from west to east, superimposed on gene flow. Highly male-biased migration was detected for several population comparisons. Nuclear microsatellite DNA markers (119 individuals and six loci) provided additional support for population subdivision and gender-biased dispersal detected in the mtDNA sequences. Analysis using F(ST) values (based on allelic frequencies) yielded statistically significant separation between some, but not all, populations distinguished by mtDNA analysis. R(ST) values (based on frequencies of and genetic distance between alleles) showed no statistically significant subdivision. Again, highly male-biased dispersal was detected for all population comparisons, suggesting, together with morphological and reproductive data, the existence of sexual selection. Our molecular results argue for nine distinct dalli-type populations that should be treated as separate units for management purposes.

The Threat of Common Method Variance Bias to Theory Building

ERIC Educational Resources Information Center

Reio, Thomas G., Jr.

2010-01-01

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

Simulating county-level crop yields in the Conterminous United States using the Community Land Model: The effects of optimizing irrigation and fertilization

DOE PAGES

Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi; ...

2016-11-12

fixing nitrogen to meet nitrogen demand, the reduced positive bias to 6.9 Bu/acre (or 21% of the country mean) was mainly attributed to consideration of the dynamic interactions between fertilizer demand and supply. Although large bias remains in terms of the spatial pattern (i.e. high county-level RMSE), mainly due to limited performance over the Western US, our results show that optimizing irrigation and fertilization can lead to promising improvement in crop and soybean yield simulations in terms of the mean and variability especially over the Mid-west corn belt, and subsequent evapotranspiration (ET) estimates. Finally, this study demonstrates the CLM4.5 capability for predicting crop yields and their interactions with climate, and highlights the value of continued model improvements and development to understand biogeophysical and biogeochemical impacts of land use and land cover change using an Earth system modeling framework.« less

Simulating county-level crop yields in the Conterminous United States using the Community Land Model: The effects of optimizing irrigation and fertilization

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

Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi

fixing nitrogen to meet nitrogen demand, the reduced positive bias to 6.9 Bu/acre (or 21% of the country mean) was mainly attributed to consideration of the dynamic interactions between fertilizer demand and supply. Although large bias remains in terms of the spatial pattern (i.e. high county-level RMSE), mainly due to limited performance over the Western US, our results show that optimizing irrigation and fertilization can lead to promising improvement in crop and soybean yield simulations in terms of the mean and variability especially over the Mid-west corn belt, and subsequent evapotranspiration (ET) estimates. Finally, this study demonstrates the CLM4.5 capability for predicting crop yields and their interactions with climate, and highlights the value of continued model improvements and development to understand biogeophysical and biogeochemical impacts of land use and land cover change using an Earth system modeling framework.« less

Attentional bias in high math-anxious individuals: evidence from an emotional Stroop task

PubMed Central

Suárez-Pellicioni, Macarena; Núñez-Peña, Maria Isabel; Colomé, Àngels

2015-01-01

Attentional bias toward threatening or emotional information is considered a cognitive marker of anxiety, and it has been described in various clinical and subclinical populations. This study used an emotional Stroop task to investigate whether math anxiety is characterized by an attentional bias toward math-related words. Two previous studies failed to observe such an effect in math-anxious individuals, although the authors acknowledged certain methodological limitations that the present study seeks to avoid. Twenty high math-anxious (HMA) and 20 low math-anxious (LMA) individuals were presented with an emotional Stroop task including math-related and neutral words. Participants in the two groups did not differ in trait anxiety or depression. We found that the HMA group showed slower response times to math-related words than to neutral words, as well as a greater attentional bias (math-related – neutral difference score) than the LMA one, which constitutes the first demonstration of an attentional bias toward math-related words in HMA individuals. PMID:26539137

A Dynamic Bayesian Observer Model Reveals Origins of Bias in Visual Path Integration.

PubMed

Lakshminarasimhan, Kaushik J; Petsalis, Marina; Park, Hyeshin; DeAngelis, Gregory C; Pitkow, Xaq; Angelaki, Dora E

2018-06-20

Path integration is a strategy by which animals track their position by integrating their self-motion velocity. To identify the computational origins of bias in visual path integration, we asked human subjects to navigate in a virtual environment using optic flow and found that they generally traveled beyond the goal location. Such a behavior could stem from leaky integration of unbiased self-motion velocity estimates or from a prior expectation favoring slower speeds that causes velocity underestimation. Testing both alternatives using a probabilistic framework that maximizes expected reward, we found that subjects' biases were better explained by a slow-speed prior than imperfect integration. When subjects integrate paths over long periods, this framework intriguingly predicts a distance-dependent bias reversal due to buildup of uncertainty, which we also confirmed experimentally. These results suggest that visual path integration in noisy environments is limited largely by biases in processing optic flow rather than by leaky integration. Copyright © 2018 Elsevier Inc. All rights reserved.

The Politics of Affirmation Theory: When Group-Affirmation Leads to Greater Ingroup Bias.

PubMed

Ehrlich, Gaven A; Gramzow, Richard H

2015-08-01

It has been well established in the literature that affirming the individual self reduces the tendency to exhibit group-favoring biases. The limited research examining group-affirmation and bias, however, is inconclusive. We argue that group-affirmation can exacerbate group-serving biases in certain contexts, and in the current set of studies, we document this phenomenon directly. Unlike self-affirmation, group-affirmation led to greater ingroup-favoring evaluative judgments among political partisans (Experiment 1). This increase in evaluative bias following group-affirmation was moderated by political party identification and was not found among those who affirmed a non-political ingroup (Experiment 2). In addition, the mechanism underlying these findings is explored and interpreted within the theoretical frameworks of self-categorization theory and the multiple self-aspects model (Experiments 2 and 3). The broader implications of our findings for the understanding of social identity and affirmation theory are discussed. © 2015 by the Society for Personality and Social Psychology, Inc.

Software thresholds alter the bias of actigraphy for monitoring sleep in team-sport athletes.

PubMed

Fuller, Kate L; Juliff, Laura; Gore, Christopher J; Peiffer, Jeremiah J; Halson, Shona L

2017-08-01

Actical ® actigraphy is commonly used to monitor athlete sleep. The proprietary software, called Actiware ® , processes data with three different sleep-wake thresholds (Low, Medium or High), but there is no standardisation regarding their use. The purpose of this study was to examine validity and bias of the sleep-wake thresholds for processing Actical ® sleep data in team sport athletes. Validation study comparing actigraph against accepted gold standard polysomnography (PSG). Sixty seven nights of sleep were recorded simultaneously with polysomnography and Actical ® devices. Individual night data was compared across five sleep measures for each sleep-wake threshold using Actiware ® software. Accuracy of each sleep-wake threshold compared with PSG was evaluated from mean bias with 95% confidence limits, Pearson moment-product correlation and associated standard error of estimate. The Medium threshold generated the smallest mean bias compared with polysomnography for total sleep time (8.5min), sleep efficiency (1.8%) and wake after sleep onset (-4.1min); whereas the Low threshold had the smallest bias (7.5min) for wake bouts. Bias in sleep onset latency was the same across thresholds (-9.5min). The standard error of the estimate was similar across all thresholds; total sleep time ∼25min, sleep efficiency ∼4.5%, wake after sleep onset ∼21min, and wake bouts ∼8 counts. Sleep parameters measured by the Actical ® device are greatly influenced by the sleep-wake threshold applied. In the present study the Medium threshold produced the smallest bias for most parameters compared with PSG. Given the magnitude of measurement variability, confidence limits should be employed when interpreting changes in sleep parameters. Copyright © 2017 Sports Medicine Australia. All rights reserved.

Harnessing learning biases is essential for applying social learning in conservation.

PubMed

Greggor, Alison L; Thornton, Alex; Clayton, Nicola S

2017-01-01

Social learning can influence how animals respond to anthropogenic changes in the environment, determining whether animals survive novel threats and exploit novel resources or produce maladaptive behaviour and contribute to human-wildlife conflict. Predicting where social learning will occur and manipulating its use are, therefore, important in conservation, but doing so is not straightforward. Learning is an inherently biased process that has been shaped by natural selection to prioritize important information and facilitate its efficient uptake. In this regard, social learning is no different from other learning processes because it too is shaped by perceptual filters, attentional biases and learning constraints that can differ between habitats, species, individuals and contexts. The biases that constrain social learning are not understood well enough to accurately predict whether or not social learning will occur in many situations, which limits the effective use of social learning in conservation practice. Nevertheless, we argue that by tapping into the biases that guide the social transmission of information, the conservation applications of social learning could be improved. We explore the conservation areas where social learning is highly relevant and link them to biases in the cues and contexts that shape social information use. The resulting synthesis highlights many promising areas for collaboration between the fields and stresses the importance of systematic reviews of the evidence surrounding social learning practices.

[Effects of plastic mulch on soil moisture and temperature and limiting factors to yield increase for dryland spring maize in the North China].

PubMed

Liu, Sheng-Yao; Zhang, Li-Feng; Li, Zhi-Hong; Jia, Jian-Ming; Fan, Feng-Cui; Shi, Yu-Fang

2014-11-01

Four treatments, including ridge tillage with plastic mulch (RP), ridge tillage without mulch (RB), flat tillage with plastic mulch (FP) and flat tillage without mulch (FB), were carried out to examine the tillage type and mulch on the effects of soil moisture and temperature, yield and water use efficiency (WUE) of dry land spring maize in the North China. Results showed that the average soil temperature was increased by 1-3 °C and the accumulated soil temperature was increased by 155.2-280.9 °C from sowing to tasseling by plastic mulch, and the growing duration was extended by 5.9-10.7 d. The water conservation effect of plastic mulch was significant from sowing to the seedling establishment, with WUE being increased by 81.6%-136.4% under mulch as compared with that without mulch. From the seedling to jointing stage, which coincided with the dry period in the region, soil water utilization by the maize under mulch could reach the depth of 80-100 cm, and its WUE was about 17.0%-21.6% lower than the maize without mulch, since the latter was affected by dry stress. With the coming of rainy season around the trumpeting stage, soil water in each treatment was replenished and maintained at relative high level up to harvest. Yield of maize was increased by 9.5% under RP as compared with RB. However, yield was reduced by 5.0% under FP, due to the plastic film under flat tillage prevented the infiltration of rainfall and waterlogging occurred. No significant difference in yield was found between RB and FB. Higher yield of spring maize was limited because of the mismatching in water supply and demand characterized by soil water shortage before the rainy season and abundant soil water storage after the rainy season.

Inelastic effects in molecular transport junctions: The probe technique at high bias

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

Kilgour, Michael; Segal, Dvira, E-mail: dsegal@chem.utoronto.ca

2016-03-28

We extend the Landauer-Büttiker probe formalism for conductances to the high bias regime and study the effects of environmentally induced elastic and inelastic scattering on charge current in single molecule junctions, focusing on high-bias effects. The probe technique phenomenologically incorporates incoherent elastic and inelastic effects to the fully coherent case, mimicking a rich physical environment at trivial cost. We further identify environmentally induced mechanisms which generate an asymmetry in the current, manifested as a weak diode behavior. This rectifying behavior, found in two types of molecular junction models, is absent in the coherent-elastic limit and is only active in themore » case with incoherent-inelastic scattering. Our work illustrates that in the low bias-linear response regime, the commonly used “dephasing probe” (mimicking only elastic decoherence effects) operates nearly indistinguishably from a “voltage probe” (admitting inelastic-dissipative effects). However, these probes realize fundamentally distinct I-V characteristics at high biases, reflecting the central roles of dissipation and inelastic scattering processes on molecular electronic transport far-from-equilibrium.« less

Motivational Mechanisms and Outcome Expectancies Underlying the Approach Bias toward Addictive Substances.

PubMed

Watson, P; de Wit, S; Hommel, Bernhard; Wiers, R W

2012-01-01

Human behavior can be paradoxical, in that actions can be initiated that are seemingly incongruent with an individual's explicit desires. This is most commonly observed in drug addiction, where maladaptive behavior (i.e., drug seeking) appears to be compulsive, continuing at great personal cost. Approach biases toward addictive substances have been correlated with actual drug-use in a number of studies, suggesting that this measure can, in some cases, index everyday maladaptive tendencies. At present it is unclear whether this bias to drug cues is a Pavlovian conditioned approach response, a habitual response, the result of a Pavlovian-instrumental transfer process, or a goal-directed action in the sense that expectancy of the rewarding effects of drugs controls approach. We consider this question by combining the theoretical framework of associative learning with the available evidence from approach bias research. Although research investigating the relative contributions of these mechanisms to the approach bias is to date relatively limited, we review existing studies and also outline avenues for future research.

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.

Optimization of Angular-Momentum Biases of Reaction Wheels

NASA Technical Reports Server (NTRS)

Lee, Clifford; Lee, Allan

2008-01-01

RBOT [RWA Bias Optimization Tool (wherein RWA signifies Reaction Wheel Assembly )] is a computer program designed for computing angular momentum biases for reaction wheels used for providing spacecraft pointing in various directions as required for scientific observations. RBOT is currently deployed to support the Cassini mission to prevent operation of reaction wheels at unsafely high speeds while minimizing time in undesirable low-speed range, where elasto-hydrodynamic lubrication films in bearings become ineffective, leading to premature bearing failure. The problem is formulated as a constrained optimization problem in which maximum wheel speed limit is a hard constraint and a cost functional that increases as speed decreases below a low-speed threshold. The optimization problem is solved using a parametric search routine known as the Nelder-Mead simplex algorithm. To increase computational efficiency for extended operation involving large quantity of data, the algorithm is designed to (1) use large time increments during intervals when spacecraft attitudes or rates of rotation are nearly stationary, (2) use sinusoidal-approximation sampling to model repeated long periods of Earth-point rolling maneuvers to reduce computational loads, and (3) utilize an efficient equation to obtain wheel-rate profiles as functions of initial wheel biases based on conservation of angular momentum (in an inertial frame) using pre-computed terms.

Pain and Pessimism: Dairy Calves Exhibit Negative Judgement Bias following Hot-Iron Disbudding

PubMed Central

Neave, Heather W.; Daros, Rolnei R.; Costa, João H. C.; von Keyserlingk, Marina A. G.; Weary, Daniel M.

2013-01-01

Pain is defined as an unpleasant sensory and emotional experience associated with actual or potential tissue damage, but emotional states are difficult to directly assess in animals. Researchers have assessed pain using behavioural and physiological measures, but these approaches are limited to understanding the arousal rather than valence of the emotional experience. Cognitive bias tasks show that depressed humans judge ambiguous events negatively and this technique has been applied to assess emotional states in animals. However, limited research has examined how pain states affect cognitive processes in animals. Here we present the first evidence of cognitive bias in response to pain in any non-human species. In two experiments, dairy calves (n = 17) were trained to respond differentially to red and white video screens and then tested with unreinforced ambiguous colours in two or three test sessions before and two sessions after the routine practice of hot-iron disbudding. After disbudding calves were more likely to judge ambiguous colours as negative. This ‘pessimistic’ bias indicates that post-operative pain following hot-iron disbudding results in a negative change in emotional state. PMID:24324609

Estimating Bias Error Distributions

NASA Technical Reports Server (NTRS)

Liu, Tian-Shu; Finley, Tom D.

2001-01-01

This paper formulates the general methodology for estimating the bias error distribution of a device in a measuring domain from less accurate measurements when a minimal number of standard values (typically two values) are available. A new perspective is that the bias error distribution can be found as a solution of an intrinsic functional equation in a domain. Based on this theory, the scaling- and translation-based methods for determining the bias error distribution arc developed. These methods are virtually applicable to any device as long as the bias error distribution of the device can be sufficiently described by a power series (a polynomial) or a Fourier series in a domain. These methods have been validated through computational simulations and laboratory calibration experiments for a number of different devices.

Secondary Electron Emission Yields

NASA Technical Reports Server (NTRS)

Krainsky, I.; Lundin, W.; Gordon, W. L.; Hoffman, R. W.

1981-01-01

The secondary electron emission (SEE) characteristics for a variety of spacecraft materials were determined under UHV conditions using a commercial double pass CMA which permits sequential Auger electron electron spectroscopic analysis of the surface. The transparent conductive coating indium tin oxide (ITO) was examined on Kapton and borosilicate glass and indium oxide on FED Teflon. The total SEE coefficient ranges from 2.5 to 2.6 on as-received surfaces and from 1.5 to 1.6 on Ar(+) sputtered surfaces with 5 nm removed. A cylindrical sample carousel provides normal incidence of the primary beam as well as a multiple Faraday cup measurement of the approximately nA beam currents. Total and true secondary yields are obtained from target current measurements with biasing of the carousel. A primary beam pulsed mode to reduce electron beam dosage and minimize charging of insulating coatings was applied to Mg/F2 coated solar cell covers. Electron beam effects on ITO were found quite important at the current densities necessary to do Auger studies.

Suicidal ideation and attentional biases in children: An eye-tracking study.

PubMed

Tsypes, Aliona; Owens, Max; Gibb, Brandon E

2017-11-01

Despite theoretical and empirical evidence for a heighted responsiveness to signals of social-threat in suicidal individuals, no studies to date have examined whether this responsiveness might also manifest in the form of specific biases in attention to interpersonal stimuli. The current study, therefore, examined the presence and nature of attentional biases for facial expressions of emotion in children with and without a history of suicidal ideation (SI). Participants were 88 children (44 with a history of SI and 44 demographically and clinically matched controls without such history) recruited from the community. The average age of children was 9.26 years (44.3% female; 67.0% Caucasian). Children's history of SI was assessed via structured interviews with children and their parent. Attentional biases were assessed using a dot probe task and included fearful, happy, and sad facial stimuli and focused on eye tracking and reaction time indices of attentional bias. Children with a history of SI exhibited significantly greater gaze duration toward fearful faces. The findings appeared to be at least partially independent of children's history of major depression or anxiety disorders or their current depressive or anxious symptoms. The study is limited by its cross-sectional design, which precludes any causal conclusions regarding the role of attentional biases in future suicide risk. Our results suggest that children with a history of SI exhibit biases in sustained attention toward socially-threatening facial expressions. Pending replications, these findings might represent a new avenue of suicide risk assessment and intervention. Copyright © 2017 Elsevier B.V. All rights reserved.

The Frontal View of the Nose: Lighting Effects and Photographic Bias.

PubMed

Strub, Benedikt; Mende, Konrad; Meuli-Simmen, Claudia; Bessler, Stephan

2015-07-01

Most aesthetic rhinosurgeons rely on proper photographic documentation of the nose using several different views. The frontal view is probably the most important, but it is also the most demanding. In the frontal view, delicate, 3-dimensional (3D) anatomic structures require special photographic skills. Lighting is crucial for detail rendition and 3D reproduction of the nose, and for apparent photographic bias. We compared the quality of reproduction and photographic bias with different symmetric and asymmetric lighting in common clinical practice described in the literature. The photographs were compared for anatomic reproduction, shadowing, 3-dimensionality, and apparent changes of nasal shape (bias). Symmetric lighting did not satisfy the demands of the rhinosurgeons because of marginal 3-dimensionality, reduced detail rendition, or photographic bias. Strongly asymmetric lighting altered the nasal shape adversely for bias depending on the side of illumination, but led to very good 3-dimensionality. Slightly asymmetric lighting demonstrated the best results for detail rendition and 3-dimensionality. Classic symmetric quarter light is a practicable lighting technique with limitations in the rendition of detail and 3-dimensionality. Slightly asymmetric lighting offered a perfect compromise, with substantially improved detail rendition and 3-dimensionality. Strongly asymmetric lighting may lead to photographic bias depending on the side of illumination. Frontal documentation of the nose with asymmetric lighting should, therefore, always be performed in duplicate, with asymmetric lighting from the right side and from the left side, to prevent misleading interpretations. © 2015 The American Society for Aesthetic Plastic Surgery, Inc. Reprints and permission: journals.permissions@oup.com.

Overgeneral autobiographical memory bias in clinical and non-clinical voice hearers.

PubMed

Jacobsen, Pamela; Peters, Emmanuelle; Ward, Thomas; Garety, Philippa A; Jackson, Mike; Chadwick, Paul

2018-03-14

Hearing voices can be a distressing and disabling experience for some, whilst it is a valued experience for others, so-called 'healthy voice-hearers'. Cognitive models of psychosis highlight the role of memory, appraisal and cognitive biases in determining emotional and behavioural responses to voices. A memory bias potentially associated with distressing voices is the overgeneral memory bias (OGM), namely the tendency to recall a summary of events rather than specific occasions. It may limit access to autobiographical information that could be helpful in re-appraising distressing experiences, including voices. We investigated the possible links between OGM and distressing voices in psychosis by comparing three groups: (1) clinical voice-hearers (N = 39), (2) non-clinical voice-hearers (N = 35) and (3) controls without voices (N = 77) on a standard version of the autobiographical memory test (AMT). Clinical and non-clinical voice-hearers also completed a newly adapted version of the task, designed to assess voices-related memories (vAMT). As hypothesised, the clinical group displayed an OGM bias by retrieving fewer specific autobiographical memories on the AMT compared with both the non-clinical and control groups, who did not differ from each other. The clinical group also showed an OGM bias in recall of voice-related memories on the vAMT, compared with the non-clinical group. Clinical voice-hearers display an OGM bias when compared with non-clinical voice-hearers on both general and voices-specific recall tasks. These findings have implications for the refinement and targeting of psychological interventions for psychosis.

Mood-congruent attention and memory bias in dysphoria: Exploring the coherence among information-processing biases.

PubMed

Koster, Ernst H W; De Raedt, Rudi; Leyman, Lemke; De Lissnyder, Evi

2010-03-01

Recent studies indicate that depression is characterized by mood-congruent attention bias at later stages of information-processing. Moreover, depression has been associated with enhanced recall of negative information. The present study tested the coherence between attention and memory bias in dysphoria. Stable dysphoric (n = 41) and non-dysphoric (n = 41) undergraduates first performed a spatial cueing task that included negative, positive, and neutral words. Words were presented for 250 ms under conditions that allowed or prevented elaborate processing. Memory for the words presented in the cueing task was tested using incidental free recall. Dysphoric individuals exhibited an attention bias for negative words in the condition that allowed elaborate processing, with the attention bias for negative words predicting free recall of negative words. Results demonstrate the coherence of attention and memory bias in dysphoric individuals and provide suggestions on the influence of attention bias on further processing of negative material. 2009 Elsevier Ltd. All rights reserved.

Bias field tailored plasmonic nano-electrode for high-power terahertz photonic devices.

PubMed

Moon, Kiwon; Lee, Il-Min; Shin, Jun-Hwan; Lee, Eui Su; Kim, Namje; Lee, Won-Hui; Ko, Hyunsung; Han, Sang-Pil; Park, Kyung Hyun

2015-09-08

Photoconductive antennas with nano-structured electrodes and which show significantly improved performances have been proposed to satisfy the demand for compact and efficient terahertz (THz) sources. Plasmonic field enhancement was previously considered the dominant mechanism accounting for the improvements in the underlying physics. However, we discovered that the role of plasmonic field enhancement is limited and near-field distribution of bias field should be considered as well. In this paper, we clearly show that the locally enhanced bias field due to the size effect is much more important than the plasmonic enhanced absorption in the nano-structured electrodes for the THz emitters. Consequently, an improved nano-electrode design is presented by tailoring bias field distribution and plasmonic enhancement. Our findings will pave the way for new perspectives in the design and analysis of plasmonic nano-structures for more efficient THz photonic devices.

Sequence-specific bias correction for RNA-seq data using recurrent neural networks.

PubMed

Zhang, Yao-Zhong; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2017-01-25

The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures. The sequence-specific bias of a read is then calculated based on the sequence probabilities estimated by RNNs, and used in the estimation of gene abundance. We explore the application of two popular RNN recurrent units for this task and demonstrate that RNN-based approaches provide a flexible way to model nucleotide sequences without knowledge of predetermined sequence structures. Our experiments show that training a RNN-based nucleotide sequence model is efficient and RNN-based bias correction methods compare well with the-state-of-the-art sequence-specific bias correction method on the commonly used MAQC-III data set. RNNs provides an alternative and flexible way to calculate sequence-specific bias without explicitly pre-determining sequence structures.

A review of current evidence for the causal impact of attentional bias on fear and anxiety.

PubMed

Van Bockstaele, Bram; Verschuere, Bruno; Tibboel, Helen; De Houwer, Jan; Crombez, Geert; Koster, Ernst H W

2014-05-01

Prominent cognitive theories postulate that an attentional bias toward threatening information contributes to the etiology, maintenance, or exacerbation of fear and anxiety. In this review, we investigate to what extent these causal claims are supported by sound empirical evidence. Although differences in attentional bias are associated with differences in fear and anxiety, this association does not emerge consistently. Moreover, there is only limited evidence that individual differences in attentional bias are related to individual differences in fear or anxiety. In line with a causal relation, some studies show that attentional bias precedes fear or anxiety in time. However, other studies show that fear and anxiety can precede the onset of attentional bias, suggesting circular or reciprocal causality. Importantly, a recent line of experimental research shows that changes in attentional bias can lead to changes in anxiety. Yet changes in fear and anxiety also lead to changes in attentional bias, which confirms that the relation between attentional bias and fear and anxiety is unlikely to be unidirectional. Finally, a similar causal relation between interpretation bias and anxiety has been documented. In sum, there is evidence in favor of causality, yet a strict unidirectional cause-effect model is unlikely to hold. The relation between attentional bias and fear and anxiety is best described as a bidirectional, maintaining, or mutually reinforcing relation.

Estimation of attitude sensor timetag biases

NASA Technical Reports Server (NTRS)

Sedlak, J.

1995-01-01

This paper presents an extended Kalman filter for estimating attitude sensor timing errors. Spacecraft attitude is determined by finding the mean rotation from a set of reference vectors in inertial space to the corresponding observed vectors in the body frame. Any timing errors in the observations can lead to attitude errors if either the spacecraft is rotating or the reference vectors themselves vary with time. The state vector here consists of the attitude quaternion, timetag biases, and, optionally, gyro drift rate biases. The filter models the timetags as random walk processes: their expectation values propagate as constants and white noise contributes to their covariance. Thus, this filter is applicable to cases where the true timing errors are constant or slowly varying. The observability of the state vector is studied first through an examination of the algebraic observability condition and then through several examples with simulated star tracker timing errors. The examples use both simulated and actual flight data from the Extreme Ultraviolet Explorer (EUVE). The flight data come from times when EUVE had a constant rotation rate, while the simulated data feature large angle attitude maneuvers. The tests include cases with timetag errors on one or two sensors, both constant and time-varying, and with and without gyro bias errors. Due to EUVE's sensor geometry, the observability of the state vector is severely limited when the spacecraft rotation rate is constant. In the absence of attitude maneuvers, the state elements are highly correlated, and the state estimate is unreliable. The estimates are particularly sensitive to filter mistuning in this case. The EUVE geometry, though, is a degenerate case having coplanar sensors and rotation vector. Observability is much improved and the filter performs well when the rate is either varying or noncoplanar with the sensors, as during a slew. Even with bad geometry and constant rates, if gyro biases are

Stimulus-driven attention, threat bias, and sad bias in youth with a history of an anxiety disorder or depression

PubMed Central

Sylvester, Chad M.; Hudziak, James J.; Gaffrey, Michael S.; Barch, Deanna M.; Luby, Joan L.

2015-01-01

Attention biases towards threatening and sad stimuli are associated with pediatric anxiety and depression, respectively. The basic cognitive mechanisms associated with attention biases in youth, however, remain unclear. Here, we tested the hypothesis that threat bias (selective attention for threatening versus neutral stimuli) but not sad bias relies on stimulus-driven attention. We collected measures of stimulus-driven attention, threat bias, sad bias, and current clinical symptoms in youth with a history of an anxiety disorder and/or depression (ANX/DEP; n=40) as well as healthy controls (HC; n=33). Stimulus-driven attention was measured with a non-emotional spatial orienting task, while threat bias and sad bias were measured at a short time interval (150 ms) with a spatial orienting task using emotional faces and at a longer time interval (500 ms) using a dot-probe task. In ANX/DEP but not HC, early attention bias towards threat was negatively correlated with later attention bias to threat, suggesting that early threat vigilance was associated with later threat avoidance. Across all subjects, stimulus-driven orienting was not correlated with early threat bias but was negatively correlated with later threat bias, indicating that rapid stimulus-driven orienting is linked to later threat avoidance. No parallel relationships were detected for sad bias. Current symptoms of depression but not anxiety were related to decreased stimulus-driven attention. Together, these results are consistent with the hypothesis that threat bias but not sad bias relies on stimulus-driven attention. These results inform the design of attention bias modification programs that aim to reverse threat biases and reduce symptoms associated with pediatric anxiety and depression. PMID:25702927

Stimulus-Driven Attention, Threat Bias, and Sad Bias in Youth with a History of an Anxiety Disorder or Depression.

PubMed

Sylvester, Chad M; Hudziak, James J; Gaffrey, Michael S; Barch, Deanna M; Luby, Joan L

2016-02-01

Attention biases towards threatening and sad stimuli are associated with pediatric anxiety and depression, respectively. The basic cognitive mechanisms associated with attention biases in youth, however, remain unclear. Here, we tested the hypothesis that threat bias (selective attention for threatening versus neutral stimuli) but not sad bias relies on stimulus-driven attention. We collected measures of stimulus-driven attention, threat bias, sad bias, and current clinical symptoms in youth with a history of an anxiety disorder and/or depression (ANX/DEP; n = 40) as well as healthy controls (HC; n = 33). Stimulus-driven attention was measured with a non-emotional spatial orienting task, while threat bias and sad bias were measured at a short time interval (150 ms) with a spatial orienting task using emotional faces and at a longer time interval (500 ms) using a dot-probe task. In ANX/DEP but not HC, early attention bias towards threat was negatively correlated with later attention bias to threat, suggesting that early threat vigilance was associated with later threat avoidance. Across all subjects, stimulus-driven orienting was not correlated with early threat bias but was negatively correlated with later threat bias, indicating that rapid stimulus-driven orienting is linked to later threat avoidance. No parallel relationships were detected for sad bias. Current symptoms of depression but not anxiety were related to decreased stimulus-driven attention. Together, these results are consistent with the hypothesis that threat bias but not sad bias relies on stimulus-driven attention. These results inform the design of attention bias modification programs that aim to reverse threat biases and reduce symptoms associated with pediatric anxiety and depression.

The Systematic Bias of Ingestible Core Temperature Sensors Requires a Correction by Linear Regression.

PubMed

Hunt, Andrew P; Bach, Aaron J E; Borg, David N; Costello, Joseph T; Stewart, Ian B

2017-01-01

An accurate measure of core body temperature is critical for monitoring individuals, groups and teams undertaking physical activity in situations of high heat stress or prolonged cold exposure. This study examined the range in systematic bias of ingestible temperature sensors compared to a certified and traceable reference thermometer. A total of 119 ingestible temperature sensors were immersed in a circulated water bath at five water temperatures (TEMP A: 35.12 ± 0.60°C, TEMP B: 37.33 ± 0.56°C, TEMP C: 39.48 ± 0.73°C, TEMP D: 41.58 ± 0.97°C, and TEMP E: 43.47 ± 1.07°C) along with a certified traceable reference thermometer. Thirteen sensors (10.9%) demonstrated a systematic bias > ±0.1°C, of which 4 (3.3%) were > ± 0.5°C. Limits of agreement (95%) indicated that systematic bias would likely fall in the range of -0.14 to 0.26°C, highlighting that it is possible for temperatures measured between sensors to differ by more than 0.4°C. The proportion of sensors with systematic bias > ±0.1°C (10.9%) confirms that ingestible temperature sensors require correction to ensure their accuracy. An individualized linear correction achieved a mean systematic bias of 0.00°C, and limits of agreement (95%) to 0.00-0.00°C, with 100% of sensors achieving ±0.1°C accuracy. Alternatively, a generalized linear function (Corrected Temperature (°C) = 1.00375 × Sensor Temperature (°C) - 0.205549), produced as the average slope and intercept of a sub-set of 51 sensors and excluding sensors with accuracy outside ±0.5°C, reduced the systematic bias to < ±0.1°C in 98.4% of the remaining sensors ( n = 64). In conclusion, these data show that using an uncalibrated ingestible temperature sensor may provide inaccurate data that still appears to be statistically, physiologically, and clinically meaningful. Correction of sensor temperature to a reference thermometer by linear function eliminates this systematic bias (individualized functions) or ensures systematic bias is

Detection and Attribution of Simulated Climatic Extreme Events and Impacts: High Sensitivity to Bias Correction

NASA Astrophysics Data System (ADS)

Sippel, S.; Otto, F. E. L.; Forkel, M.; Allen, M. R.; Guillod, B. P.; Heimann, M.; Reichstein, M.; Seneviratne, S. I.; Kirsten, T.; Mahecha, M. D.

2015-12-01

Understanding, quantifying and attributing the impacts of climatic extreme events and variability is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit pronounced biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. We assess how biases and their correction affect the quantification and attribution of simulated extremes and variability in i) climatological variables and ii) impacts on ecosystem functioning as simulated by a terrestrial biosphere model. Our study demonstrates that assessments of simulated climatic extreme events and impacts in the terrestrial biosphere are highly sensitive to bias correction schemes with major implications for the detection and attribution of these events. We introduce a novel ensemble-based resampling scheme based on a large regional climate model ensemble generated by the distributed weather@home setup[1], which fully preserves the physical consistency and multivariate correlation structure of the model output. We use extreme value statistics to show that this procedure considerably improves the representation of climatic extremes and variability. Subsequently, biosphere-atmosphere carbon fluxes are simulated using a terrestrial ecosystem model (LPJ-GSI) to further demonstrate the sensitivity of ecosystem impacts to the methodology of bias correcting climate model output. We find that uncertainties arising from bias correction schemes are comparable in magnitude to model structural and parameter uncertainties. The present study consists of a first attempt to alleviate climate model biases in a physically consistent way and demonstrates that this yields improved simulations of

Unconscious gender bias in fame judgments?

PubMed

Buchner, A; Wippich, W

1996-01-01

In two experiments the conditions of, and the processes leading to, gender biases in fame judgments were investigated. In Experiment 1, the gender bias was not reduced in a condition that alerted participants to the gender of the names. In Experiment 2, participants' sex-role orientation, but not their gender, was related to the gender bias. The process dissociation procedure was used in both experiments in an attempt to separate conscious and unconscious memory processes contributing to the gender bias. Using L.L. Jacoby's 1991) original measurement model there appeared to be evidence for unconscious influences on the gender bias in fame judgments. Unfortunately, this evidence disappeared when a model was used that takes guessing and, hence, response biases into account, which confirms that measurement models that ignore response biases in the process dissociation procedure may lead to erroneous conclusions.

Cognitive Bias Modification Training in Adolescents: Effects on Interpretation Biases and Mood

ERIC Educational Resources Information Center

Lothmann, Claudia; Holmes, Emily A.; Chan, Stella W. Y.; Lau, Jennifer Y. F.

2011-01-01

Background: Negative biases in the interpretation of ambiguous material have been linked to anxiety and mood problems. Accumulating data from adults show that positive and negative interpretation styles can be induced through cognitive bias modification (CBM) paradigms with accompanying changes in mood. Despite the therapeutic potential of…

Unpacking the Evidence of Gender Bias

ERIC Educational Resources Information Center

Fulmer, Connie L.

2010-01-01

The purpose of this study was to investigate gender bias in pre-service principals using the Gender-Leader Implicit Association Test. Analyses of student-learning narratives revealed how students made sense of gender bias (biased or not-biased) and how each reacted to evidence (surprised or not-surprised). Two implications were: (1) the need for…

Apoplastic infusion of sucrose into stem internodes during female flowering does not increase grain yield in maize plants grown under nitrogen-limiting conditions.

PubMed

Peng, Yunfeng; Li, Chunjian; Fritschi, Felix B

2013-08-01

Nitrogen (N) limitation reduces leaf growth and photosynthetic rates of maize (Zea mays), and constrains photosynthate translocation to developing ears. Additionally, the period from about 1 week before to 2 weeks after silking is critical for establishing the reproductive sink capacity necessary to attain maximum yield. To investigate the influence of carbohydrate availability in plants of differing N status, a greenhouse study was performed in which exogenous sucrose (Suc) was infused around the time of silking into maize stems grown under different N regimes. N deficiency significantly reduced leaf area, leaf longevity, leaf chlorophyll content and photosynthetic rate. High N-delayed leaf senescence, particularly of the six uppermost leaves, compared to the other two N treatments. While N application increased ear leaf soluble protein concentration, it did not influence glucose and suc concentrations. Interestingly, ear leaf starch concentration decreased with increasing N application. Infusion of exogenous suc tended to increase non-structural carbohydrate concentrations in the developing ears of all N treatments at silking and 6 days after silking. However, leaf photosynthetic rates were not affected by suc infusion, and suc infusion failed to increase grain yield in any N treatment. The lack of an effect of suc infusion on ear growth and the high ear leaf starch concentration of N-deficient maize, suggest that yield reduction under N deficiency may not be due to insufficient photosynthate availability to the developing ear during silking, and that yield reduction under N deficiency may be determined at an earlier growth stage. Copyright © Physiologia Plantarum 2012.

CD-SEM real time bias correction using reference metrology based modeling

NASA Astrophysics Data System (ADS)

Ukraintsev, V.; Banke, W.; Zagorodnev, G.; Archie, C.; Rana, N.; Pavlovsky, V.; Smirnov, V.; Briginas, I.; Katnani, A.; Vaid, A.

2018-03-01

Accuracy of patterning impacts yield, IC performance and technology time to market. Accuracy of patterning relies on optical proximity correction (OPC) models built using CD-SEM inputs and intra die critical dimension (CD) control based on CD-SEM. Sub-nanometer measurement uncertainty (MU) of CD-SEM is required for current technologies. Reported design and process related bias variation of CD-SEM is in the range of several nanometers. Reference metrology and numerical modeling are used to correct SEM. Both methods are slow to be used for real time bias correction. We report on real time CD-SEM bias correction using empirical models based on reference metrology (RM) data. Significant amount of currently untapped information (sidewall angle, corner rounding, etc.) is obtainable from SEM waveforms. Using additional RM information provided for specific technology (design rules, materials, processes) CD extraction algorithms can be pre-built and then used in real time for accurate CD extraction from regular CD-SEM images. The art and challenge of SEM modeling is in finding robust correlation between SEM waveform features and bias of CD-SEM as well as in minimizing RM inputs needed to create accurate (within the design and process space) model. The new approach was applied to improve CD-SEM accuracy of 45 nm GATE and 32 nm MET1 OPC 1D models. In both cases MU of the state of the art CD-SEM has been improved by 3x and reduced to a nanometer level. Similar approach can be applied to 2D (end of line, contours, etc.) and 3D (sidewall angle, corner rounding, etc.) cases.

The Heart Trumps the Head: Desirability Bias in Political Belief Revision

PubMed Central

2017-01-01

Understanding how individuals revise their political beliefs has important implications for society. In a preregistered study (N = 900), we experimentally separated the predictions of 2 leading theories of human belief revision—desirability bias and confirmation bias—in the context of the 2016 U.S. presidential election. Participants indicated who they desired to win, and who they believed would win, the election. Following confrontation with evidence that was either consistent or inconsistent with their desires or beliefs, they again indicated who they believed would win. We observed a robust desirability bias—individuals updated their beliefs more if the evidence was consistent (vs. inconsistent) with their desired outcome. This bias was independent of whether the evidence was consistent or inconsistent with their prior beliefs. In contrast, we found limited evidence of an independent confirmation bias in belief updating. These results have implications for the relevant psychological theories and for political belief revision in practice. PMID:28557511

Biases in GNSS-Data Processing

NASA Astrophysics Data System (ADS)

Schaer, S. C.; Dach, R.; Lutz, S.; Meindl, M.; Beutler, G.

2010-12-01

Within the Global Positioning System (GPS) traditionally different types of pseudo-range measurements (P-code, C/A-code) are available on the first frequency that are tracked by the receivers with different technologies. For that reason, P1-C1 and P1-P2 Differential Code Biases (DCB) need to be considered in a GPS data processing with a mix of different receiver types. Since the Block IIR-M series of GPS satellites also provide C/A-code on the second frequency, P2-C2 DCB need to be added to the list of biases for maintenance. Potential quarter-cycle biases between different phase observables (specifically L2P and L2C) are another issue. When combining GNSS (currently GPS and GLONASS), careful consideration of inter-system biases (ISB) is indispensable, in particular when an adequate combination of individual GLONASS clock correction results from different sources (using, e.g., different software packages) is intended. Facing the GPS and GLONASS modernization programs and the upcoming GNSS, like the European Galileo and the Chinese Compass, an increasing number of types of biases is expected. The Center for Orbit Determination in Europe (CODE) is monitoring these GPS and GLONASS related biases for a long time based on RINEX files of the tracking network of the International GNSS Service (IGS) and in the frame of the data processing as one of the global analysis centers of the IGS. Within the presentation we give an overview on the stability of the biases based on the monitoring. Biases derived from different sources are compared. Finally, we give an outlook on the potential handling of such biases with the big variety of signals and systems expected in the future.

Process-conditioned bias correction for seasonal forecasting: a case-study with ENSO in Peru

NASA Astrophysics Data System (ADS)

Manzanas, R.; Gutiérrez, J. M.

2018-05-01

This work assesses the suitability of a first simple attempt for process-conditioned bias correction in the context of seasonal forecasting. To do this, we focus on the northwestern part of Peru and bias correct 1- and 4-month lead seasonal predictions of boreal winter (DJF) precipitation from the ECMWF System4 forecasting system for the period 1981-2010. In order to include information about the underlying large-scale circulation which may help to discriminate between precipitation affected by different processes, we introduce here an empirical quantile-quantile mapping method which runs conditioned on the state of the Southern Oscillation Index (SOI), which is accurately predicted by System4 and is known to affect the local climate. Beyond the reduction of model biases, our results show that the SOI-conditioned method yields better ROC skill scores and reliability than the raw model output over the entire region of study, whereas the standard unconditioned implementation provides no added value for any of these metrics. This suggests that conditioning the bias correction on simple but well-simulated large-scale processes relevant to the local climate may be a suitable approach for seasonal forecasting. Yet, further research on the suitability of the application of similar approaches to the one considered here for other regions, seasons and/or variables is needed.

Expectancy bias in anxious samples

PubMed Central

Cabeleira, Cindy M.; Steinman, Shari A.; Burgess, Melissa M.; Bucks, Romola S.; MacLeod, Colin; Melo, Wilson; Teachman, Bethany A.

2014-01-01

While it is well documented that anxious individuals have negative expectations about the future, it is unclear what cognitive processes give rise to this expectancy bias. Two studies are reported that use the Expectancy Task, which is designed to assess expectancy bias and illuminate its basis. This task presents individuals with valenced scenarios (Positive Valence, Negative Valence, or Conflicting Valence), and then evaluates their tendency to expect subsequent future positive relative to negative events. The Expectancy Task was used with low and high trait anxious (Study 1: N = 32) and anxiety sensitive (Study 2: N = 138) individuals. Results suggest that in the context of physical concerns, both high anxious samples display a less positive expectancy bias. In the context of social concerns, high trait anxious individuals display a negative expectancy bias only when negatively valenced information was previously presented. Overall, this suggests that anxious individuals display a less positive expectancy bias, and that the processes that give rise to this bias may vary by type of situation (e.g., social or physical) or anxiety difficulty. PMID:24798678

Gender Bias in Early Childhood Education.

ERIC Educational Resources Information Center

Kovar, Patricia McAfee; Doty, LuEllen

Noting that both boys and girls suffer because of gender bias in society and in the classroom, this paper examines the roots and consequences of such bias. The paper first provides a historical overview of gender bias and its relation to the prevalent world view. Next, it examines the manifestations of gender bias in the classroom and their…

Robust features of future climate change impacts on sorghum yields in West Africa

NASA Astrophysics Data System (ADS)

Sultan, B.; Guan, K.; Kouressy, M.; Biasutti, M.; Piani, C.; Hammer, G. L.; McLean, G.; Lobell, D. B.

2014-10-01

West Africa is highly vulnerable to climate hazards and better quantification and understanding of the impact of climate change on crop yields are urgently needed. Here we provide an assessment of near-term climate change impacts on sorghum yields in West Africa and account for uncertainties both in future climate scenarios and in crop models. Towards this goal, we use simulations of nine bias-corrected CMIP5 climate models and two crop models (SARRA-H and APSIM) to evaluate the robustness of projected crop yield impacts in this area. In broad agreement with the full CMIP5 ensemble, our subset of bias-corrected climate models projects a mean warming of +2.8 °C in the decades of 2031-2060 compared to a baseline of 1961-1990 and a robust change in rainfall in West Africa with less rain in the Western part of the Sahel (Senegal, South-West Mali) and more rain in Central Sahel (Burkina Faso, South-West Niger). Projected rainfall deficits are concentrated in early monsoon season in the Western part of the Sahel while positive rainfall changes are found in late monsoon season all over the Sahel, suggesting a shift in the seasonality of the monsoon. In response to such climate change, but without accounting for direct crop responses to CO2, mean crop yield decreases by about 16-20% and year-to-year variability increases in the Western part of the Sahel, while the eastern domain sees much milder impacts. Such differences in climate and impacts projections between the Western and Eastern parts of the Sahel are highly consistent across the climate and crop models used in this study. We investigate the robustness of impacts for different choices of cultivars, nutrient treatments, and crop responses to CO2. Adverse impacts on mean yield and yield variability are lowest for modern cultivars, as their short and nearly fixed growth cycle appears to be more resilient to the seasonality shift of the monsoon, thus suggesting shorter season varieties could be considered a potential

Thinking anxious, feeling anxious, or both? Cognitive bias moderates the relationship between anxiety disorder status and sympathetic arousal in youth.

PubMed

Rozenman, Michelle; Vreeland, Allison; Piacentini, John

2017-01-01

Cognitive bias and physiological arousal are two putative markers that may underlie youth anxiety. However, data on relationships between cognitive bias and arousal are limited, and typically do not include behavioral measurement of these constructs in order to tap real-time processes. We aimed to examine the relationship between performance-based cognitive bias and sympathetic arousal during stress in clinically anxious and typically-developing youth. The sample included children and adolescents ages 9 to 17 (Mean age=13.18, SD=2.60) who either met diagnostic criteria for primary generalized anxiety, social phobia, or separation anxiety (N=24) or healthy controls who had no history of psychopathology (N=22). Youth completed performance-based measures of attention and interpretation bias. Electrodermal activity was assessed while youth participated in the Trier Social Stress Test for Children (TSST-C; Buske-Kirschbaum, Jobst, & Wustmans, 1997). A mixed models analysis indicated significant linear and non-linear changes in skin conductance, with similar slopes for both groups. Interpretation bias, but not attention bias, moderated the relationship between group status and sympathetic arousal during the TSST-C. Arousal trajectories did not differ for anxious and healthy control youth who exhibited high levels of threat interpretation bias. However, for youth who exhibited moderate and low levels of interpretation bias, the anxious group demonstrated greater arousal slopes than healthy control youth. Results provide initial evidence that the relationship between anxiety status and physiological arousal during stress may be moderated by level of interpretation bias for threat. These findings may implicate interpretation bias as a marker of sympathetic reactivity in youth. Implications for future research and limitations are discussed. Published by Elsevier Ltd.

Using the Criterion-Predictor Factor Model to Compute the Probability of Detecting Prediction Bias with Ordinary Least Squares Regression

ERIC Educational Resources Information Center

Culpepper, Steven Andrew

2012-01-01

The study of prediction bias is important and the last five decades include research studies that examined whether test scores differentially predict academic or employment performance. Previous studies used ordinary least squares (OLS) to assess whether groups differ in intercepts and slopes. This study shows that OLS yields inaccurate inferences…

Potential for Bias When Estimating Critical Windows for Air Pollution in Children's Health.

PubMed

Wilson, Ander; Chiu, Yueh-Hsiu Mathilda; Hsu, Hsiao-Hsien Leon; Wright, Robert O; Wright, Rosalind J; Coull, Brent A

2017-12-01

Evidence supports an association between maternal exposure to air pollution during pregnancy and children's health outcomes. Recent interest has focused on identifying critical windows of vulnerability. An analysis based on a distributed lag model (DLM) can yield estimates of a critical window that are different from those from an analysis that regresses the outcome on each of the 3 trimester-average exposures (TAEs). Using a simulation study, we assessed bias in estimates of critical windows obtained using 3 regression approaches: 1) 3 separate models to estimate the association with each of the 3 TAEs; 2) a single model to jointly estimate the association between the outcome and all 3 TAEs; and 3) a DLM. We used weekly fine-particulate-matter exposure data for 238 births in a birth cohort in and around Boston, Massachusetts, and a simulated outcome and time-varying exposure effect. Estimates using separate models for each TAE were biased and identified incorrect windows. This bias arose from seasonal trends in particulate matter that induced correlation between TAEs. Including all TAEs in a single model reduced bias. DLM produced unbiased estimates and added flexibility to identify windows. Analysis of body mass index z score and fat mass in the same cohort highlighted inconsistent estimates from the 3 methods. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The impact of work-limiting disability on labor force participation.

PubMed

Webber, Douglas A; Bjelland, Melissa J

2015-03-01

According to the justification hypothesis, non-employed individuals may over-report their level of work limitation, leading to biased census/survey estimates of the prevalence of severe disabilities and the associated labor force participation rate. For researchers studying policies which impact the disabled or elderly (e.g., Supplemental Security Income, Disability Insurance, and Early Retirement), this could lead to significant bias in key parameters of interest. Using the American Community Survey, we examine the potential for both inflated and deflated reported disability status and generate a general index of disability, which can be used to reduce the bias of these self-reports in other studies. We find that at least 4.8 million individuals have left the labor force because of a work-limiting disability, at least four times greater than the impact implied by our replication of previous models. Copyright © 2013 John Wiley & Sons, Ltd.

Virtual Reality-Based Attention Bias Modification Training for Social Anxiety: A Feasibility and Proof of Concept Study.

PubMed

Urech, Antoine; Krieger, Tobias; Chesham, Alvin; Mast, Fred W; Berger, Thomas

2015-01-01

Attention bias modification (ABM) programs have been considered as a promising new approach for the treatment of various disorders, including social anxiety disorder (SAD). However, previous studies yielded ambiguous results regarding the efficacy of ABM in SAD. The present proof-of-concept study investigates the feasibility of a newly developed virtual reality (VR)-based dot-probe training paradigm. It was designed to facilitate attentional disengagement from threatening stimuli in socially anxious individuals (N = 15). The following outcomes were examined: (a) self-reports of enjoyment, motivation, flow, and presence; (b) attentional bias for social stimuli; and (c) social anxiety symptoms. Results showed that ABM training is associated with high scores in enjoyment, motivation, flow, and presence. Furthermore, significant improvements in terms of attention bias and social anxiety symptoms were observed from pre- to follow-up assessment. The study suggests that VR is a feasible and presumably a promising new medium for ABM trainings. Controlled studies will need to be carried out.

Virtual Reality-Based Attention Bias Modification Training for Social Anxiety: A Feasibility and Proof of Concept Study

PubMed Central

Urech, Antoine; Krieger, Tobias; Chesham, Alvin; Mast, Fred W.; Berger, Thomas

2015-01-01

Attention bias modification (ABM) programs have been considered as a promising new approach for the treatment of various disorders, including social anxiety disorder (SAD). However, previous studies yielded ambiguous results regarding the efficacy of ABM in SAD. The present proof-of-concept study investigates the feasibility of a newly developed virtual reality (VR)-based dot-probe training paradigm. It was designed to facilitate attentional disengagement from threatening stimuli in socially anxious individuals (N = 15). The following outcomes were examined: (a) self-reports of enjoyment, motivation, flow, and presence; (b) attentional bias for social stimuli; and (c) social anxiety symptoms. Results showed that ABM training is associated with high scores in enjoyment, motivation, flow, and presence. Furthermore, significant improvements in terms of attention bias and social anxiety symptoms were observed from pre- to follow-up assessment. The study suggests that VR is a feasible and presumably a promising new medium for ABM trainings. Controlled studies will need to be carried out. PMID:26578986

The Telescoping Phenomenon: Origins in Gender Bias and Implications for Contemporary Scientific Inquiry.

PubMed

Marks, Katherine R; Clark, Claire D

2018-05-12

In an article published in International Journal of the Addictions in 1989, Nick Piazza and his coauthors described "telescoping," an accelerated progression through "landmark symptoms" of alcoholism, among a sample of recovering women. The aim of this critical analysis is to apply a feminist philosophy of science to examine the origins of the framework of telescoping research and its implications for contemporary scientific inquiry. A feminist philosophy of science framework is outlined and applied to key source publications of telescoping literature drawn from international and United States-based peer-reviewed journals published beginning in 1952. A feminist philosophy of science framework identifies gender bias in telescoping research in three ways. First, gender bias was present in the early conventions that laid the groundwork for telescoping research. Second, a "masculine" framework was present in the methodology guiding telescoping research. Third, gender bias was present in the interpretation of results as evidenced by biased comparative language. Telescoping research contributed to early evidence of critical sex and gender differences helping to usher in women's substance abuse research more broadly. However, it also utilized a "masculine" framework that perpetuated gender bias and limited generative, novel research that can arise from women-focused research and practice. A feminist philosophy of science identifies gender bias in telescoping research and provides an alternative, more productive approach for substance abuse researchers and clinicians.

Simulated building energy demand biases resulting from the use of representative weather stations

DOE PAGES

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd; ...

2017-11-06

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. Here, we quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging frommore » 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ~4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ~1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. Our approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Simulated building energy demand biases resulting from the use of representative weather stations

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

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. Here, we quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging frommore » 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ~4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ~1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. Our approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Those were the days: memory bias for the frequency of positive events, depression, and self-enhancement.

PubMed

Lotterman, Jenny H; Bonanno, George A

2014-01-01

Past research has associated depression with memory biases pertaining to the frequency, duration, and specificity of past events. Associations have been proposed between both negative and positive memory biases and depression symptoms. However, research has not examined the occurrence of actual events over time in the study of memory bias. To address these limitations and investigate whether a negative or positive memory bias is associated with symptoms of depression, we collected weekly data on specific types of life events over a 4-year period from a sample of college students, and asked students to recall event frequency at the end of that period. Exaggerated recall of frequency for positive events but not other types of events was associated with depression symptoms, using both continuous and categorical measures. Moderator analyses indicated that these effects were evidenced primarily for memories involving the self and among individuals low in trait self-enhancement. The current study indicates that positive memory-frequency bias is an important type of memory bias associated with symptoms of depression. Results support the idea that the link between memory bias for positive event frequency and depressed mood arises out of a current-self vs past-self comparison.

Publication bias in obesity treatment trials?

PubMed

Allison, D B; Faith, M S; Gorman, B S

1996-10-01

The present investigation examined the extent of publication bias (namely the tendency to publish significant findings and file away non-significant findings) within the obesity treatment literature. Quantitative literature synthesis of four published meta-analyses from the obesity treatment literature. Interventions in these studies included pharmacological, educational, child, and couples treatments. To assess publication bias, several regression procedures (for example weighted least-squares, random-effects multi-level modeling, and robust regression methods) were used to regress effect sizes onto their standard errors, or proxies thereof, within each of the four meta-analysis. A significant positive beta weight in these analyses signified publication bias. There was evidence for publication bias within two of the four published meta-analyses, such that reviews of published studies were likely to overestimate clinical efficacy. The lack of evidence for publication bias within the two other meta-analyses might have been due to insufficient statistical power rather than the absence of selection bias. As in other disciplines, publication bias appears to exist in the obesity treatment literature. Suggestions are offered for managing publication bias once identified or reducing its likelihood in the first place.

Design space exploration for early identification of yield limiting patterns

NASA Astrophysics Data System (ADS)

Li, Helen; Zou, Elain; Lee, Robben; Hong, Sid; Liu, Square; Wang, JinYan; Du, Chunshan; Zhang, Recco; Madkour, Kareem; Ali, Hussein; Hsu, Danny; Kabeel, Aliaa; ElManhawy, Wael; Kwan, Joe

2016-03-01

In order to resolve the causality dilemma of which comes first, accurate design rules or real designs, this paper presents a flow for exploration of the layout design space to early identify problematic patterns that will negatively affect the yield. A new random layout generating method called Layout Schema Generator (LSG) is reported in this paper, this method generates realistic design-like layouts without any design rule violation. Lithography simulation is then used on the generated layout to discover the potentially problematic patterns (hotspots). These hotspot patterns are further explored by randomly inducing feature and context variations to these identified hotspots through a flow called Hotspot variation Flow (HSV). Simulation is then performed on these expanded set of layout clips to further identify more problematic patterns. These patterns are then classified into design forbidden patterns that should be included in the design rule checker and legal patterns that need better handling in the RET recipes and processes.

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.

Plasma-Based Tunable High Frequency Power Limiter

NASA Astrophysics Data System (ADS)

Semnani, Abbas; Macheret, Sergey; Peroulis, Dimitrios

2016-09-01

Power limiters are often employed to protect sensitive receivers from being damaged or saturated by high-power incoming waves. Although wideband low-power limiters based on semiconductor technology are widely available, the options for high-power frequency-selective ones are very few. In this work, we study the application of a gas discharge tube (GDT) integrated in an evanescent-mode (EVA) cavity resonator as a plasma-based power limiter. Plasmas can inherently handle higher power in comparison with semiconductor diodes. Also, using a resonant structure provides the ability of having both lower threshold power and frequency-selective limiting, which are important if only a narrowband high-power signal is targeted. Higher input RF power results in stronger discharge in the GDT and consequently higher electron density which results in larger reflection. It is also possible to tune the threshold power by pre-ionizing the GDT with a DC bias voltage. As a proof of concept, a 2-GHz EVA resonator loaded by a 90-V GDT was fabricated and measured. With reasonable amount of insertion loss, the limiting threshold power was successfully tuned from 8.3 W to 590 mW when the external DC bias was varied from 0 to 80 V. The limiter performed well up to 100 W of maximum available input power.

Do People Experience Cognitive Biases while Searching for Information?

PubMed Central

Lau, Annie Y.S.; Coiera, Enrico W.

2007-01-01

their post-search answer (retrospective: P < 0.001; prospective: P < 0.001). Documents accessed at different positions in a search session (order effect [retrospective: P = 0.76; prospective: P = 0.026]), and documents processed for different lengths of time (exposure effect [retrospective: P = 0.27; prospective: P = 0.0081]) also influenced decision post-search more than expected in the prospective experiment but not in the retrospective analysis. Reinforcement through repeated exposure to a document did not yield statistical differences in decision outcome post-search (retrospective: P = 0.31; prospective: P = 0.81). Conclusion People may experience anchoring, exposure and order biases while searching for information, and these biases may influence the quality of decision making during and after the use of information retrieval systems. PMID:17600097

Unit bias. A new heuristic that helps explain the effect of portion size on food intake.

PubMed

Geier, Andrew B; Rozin, Paul; Doros, Gheorghe

2006-06-01

People seem to think that a unit of some entity (with certain constraints) is the appropriate and optimal amount. We refer to this heuristic as unit bias. We illustrate unit bias by demonstrating large effects of unit segmentation, a form of portion control, on food intake. Thus, people choose, and presumably eat, much greater weights of Tootsie Rolls and pretzels when offered a large as opposed to a small unit size (and given the option of taking as many units as they choose at no monetary cost). Additionally, they consume substantially more M&M's when the candies are offered with a large as opposed to a small spoon (again with no limits as to the number of spoonfuls to be taken). We propose that unit bias explains why small portion sizes are effective in controlling consumption; in some cases, people served small portions would simply eat additional portions if it were not for unit bias. We argue that unit bias is a general feature in human choice and discuss possible origins of this bias, including consumption norms.

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Spectral reflectance indices as a selection criterion for yield improvement in wheat

NASA Astrophysics Data System (ADS)

Babar, Md. Ali

2005-11-01

Scope and methods of study. Yield in wheat ( Triticum aestivum L.) is a complex trait and influenced by many environmental factors, and yield improvement is a daunting task for wheat breeders. Spectral reflectance indices (SRIs) have been used to study different physiological traits in wheat. SRIs have the potential to differentiate genotypes for grain yield. SRIs strongly associated with grain yield can be used to achieve effective genetic gain in wheat under different environments. Three experiments (15 adapted genotypes, 25 and 36 random sister lines derived from two different crosses) under irrigated conditions, and three experiments (each with 30 advanced genotypes) under water-limited conditions were conducted in three successive years in Northwest Mexico at the CIMMYT (International Maize and wheat Improvement Center) experimental station. SRIs and different agronomic data were collected for three years, and biomass was harvested for two years. Phenotypic and genetic correlations between SRIs and grain yield, between SRIs and biomass, realized and broad sense heritability, direct and correlated selection responses for grain yield, and SRIs were calculated. Findings and conclusion. Seven SRIs were calculated, and three near infrared based indices (WI, NWI-1 and NWI-2) showed higher level of genetic and phenotypic correlations with grain yield, yield components and biomass than other SRIs (PRI, RNDVI, GNDVI, and SR) under both irrigated and water limiting environments. Moderate to high realized and broad sense heritability, and selection response were demonstrated by the three NIR based indices. High efficiency of correlated response for yield estimation was demonstrated by the three NIR based indices. The ratio between the correlated response to grain yield based on the three NIR based indices and direct selection response for grain yield was very close to one. The NIR based indices showed very high accuracy in selecting superior genotypes for grain yield

[Winter wheat yield gap between field blocks based on comparative performance analysis].

PubMed

Chen, Jian; Wang, Zhong-Yi; Li, Liang-Tao; Zhang, Ke-Feng; Yu, Zhen-Rong

2008-09-01

Based on a two-year household survey data, the yield gap of winter wheat in Quzhou County of Hebei Province, China in 2003-2004 was studied through comparative performance analysis (CPA). The results showed that there was a greater yield gap (from 4.2 to 7.9 t x hm(-2)) between field blocks, with a variation coefficient of 0.14. Through stepwise forward linear multiple regression, it was found that the yield model with 8 selected variables could explain 63% variability of winter wheat yield. Among the variables selected, soil salinity, soil fertility, and irrigation water quality were the most important limiting factors, accounting for 52% of the total yield gap. Crop variety was another important limiting factor, accounting for 14%; while planting date, fertilizer type, disease and pest, and water press accounted for 7%, 14%, 10%, and 3%, respectively. Therefore, besides soil and climate conditions, management practices occupied the majority of yield variability in Quzhou County, suggesting that the yield gap could be reduced significantly through optimum field management.

Simulated building energy demand biases resulting from the use of representative weather stations

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

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. We quantify the potential reduction in bias from using an increasing number of weather stations over the western U.S. The approach is based on deriving temperature and load time series using incrementally more weather stations, ranging from 8 to roughly 150, tomore » capture weather across different seasons. Using 8 stations, one from each climate zone, across the western U.S. results in an average absolute summertime temperature bias of 7.2°F with respect to a spatially-resolved gridded dataset. The mean absolute bias drops to 2.8°F using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.8%, a significant error for capacity expansion planners who may use these types of simulations. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20-40% overestimation of peak building loads during both summer and winter. Using weather stations close to population centers reduces both mean and peak load biases. This approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Bias field tailored plasmonic nano-electrode for high-power terahertz photonic devices

PubMed Central

Moon, Kiwon; Lee, Il-Min; Shin, Jun-Hwan; Lee, Eui Su; Kim, Namje; Lee, Won-Hui; Ko, Hyunsung; Han, Sang-Pil; Park, Kyung Hyun

2015-01-01

Photoconductive antennas with nano-structured electrodes and which show significantly improved performances have been proposed to satisfy the demand for compact and efficient terahertz (THz) sources. Plasmonic field enhancement was previously considered the dominant mechanism accounting for the improvements in the underlying physics. However, we discovered that the role of plasmonic field enhancement is limited and near-field distribution of bias field should be considered as well. In this paper, we clearly show that the locally enhanced bias field due to the size effect is much more important than the plasmonic enhanced absorption in the nano-structured electrodes for the THz emitters. Consequently, an improved nano-electrode design is presented by tailoring bias field distribution and plasmonic enhancement. Our findings will pave the way for new perspectives in the design and analysis of plasmonic nano-structures for more efficient THz photonic devices. PMID:26347288

Thin-Film Module Reverse-Bias Breakdown Sites Identified by Thermal Imaging

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

Johnston, Steven; Sulas, Dana; Guthrey, Harvey L

Thin-film module sections are stressed under reverse bias to simulate partial shading conditions. Such stresses can cause permanent damage in the form of 'wormlike' defects due to thermal runaway. When large reverse biases with limited current are applied to the cells, dark lock-in thermography (DLIT) can detect where spatially-localized breakdown initiates before thermal runaway leads to permanent damage. Predicted breakdown defect sites have been identified in both CIGS and CdTe modules using DLIT. These defects include small pinholes, craters, or voids in the absorber layer of the film that lead to built-in areas of weakness where high current densities maymore » cause thermal damage in a partial-shading event.« less

Linearity optimizations of analog ring resonator modulators through bias voltage adjustments

NASA Astrophysics Data System (ADS)

Hosseinzadeh, Arash; Middlebrook, Christopher T.

2018-03-01

The linearity of ring resonator modulator (RRM) in microwave photonic links is studied in terms of instantaneous bandwidth, fabrication tolerances, and operational bandwidth. A proposed bias voltage adjustment method is shown to maximize spur-free dynamic range (SFDR) at instantaneous bandwidths required by microwave photonic link (MPL) applications while also mitigating RRM fabrication tolerances effects. The proposed bias voltage adjustment method shows RRM SFDR improvement of ∼5.8 dB versus common Mach-Zehnder modulators at 500 MHz instantaneous bandwidth. Analyzing operational bandwidth effects on SFDR shows RRMs can be promising electro-optic modulators for MPL applications which require high operational frequencies while in a limited bandwidth such as radio-over-fiber 60 GHz wireless network access.

A direct comparison of exoEarth yields for starshades and coronagraphs

NASA Astrophysics Data System (ADS)

Stark, Christopher C.; Cady, Eric J.; Clampin, Mark; Domagal-Goldman, Shawn; Lisman, Doug; Mandell, Avi M.; McElwain, Michael W.; Roberge, Aki; Robinson, Tyler D.; Savransky, Dmitry; Shaklan, Stuart B.; Stapelfeldt, Karl R.

2016-07-01

The scale and design of a future mission capable of directly imaging extrasolar planets will be influenced by the detectable number (yield) of potentially Earth-like planets. Currently, coronagraphs and starshades are being considered as instruments for such a mission. We will use a novel code to estimate and compare the yields for starshade- and coronagraph-based missions. We will show yield scaling relationships for each instrument and discuss the impact of astrophysical and instrumental noise on yields. Although the absolute yields are dependent on several yet-unknown parameters, we will present several limiting cases allowing us to bound the yield comparison.

High-biomass C4 grasses-Filling the yield gap.

PubMed

Mullet, John E

2017-08-01

A significant increase in agricultural productivity will be required by 2050 to meet the needs of an expanding and rapidly developing world population, without allocating more land and water resources to agriculture, and despite slowing rates of grain yield improvement. This review examines the proposition that high-biomass C 4 grasses could help fill the yield gap. High-biomass C 4 grasses exhibit high yield due to C 4 photosynthesis, long growth duration, and efficient capture and utilization of light, water, and nutrients. These C 4 grasses exhibit high levels of drought tolerance during their long vegetative growth phase ideal for crops grown in water-limited regions of agricultural production. The stems of some high-biomass C 4 grasses can accumulate high levels of non-structural carbohydrates that could be engineered to enhance biomass yield and utility as feedstocks for animals and biofuels production. The regulatory pathway that delays flowering of high-biomass C 4 grasses in long days has been elucidated enabling production and deployment of hybrids. Crop and landscape-scale modeling predict that utilization of high-biomass C 4 grass crops on land and in regions where water resources limit grain crop yield could increase agricultural productivity. Copyright © 2017 Elsevier B.V. All rights reserved.

Hauser-Feshbach fission fragment de-excitation with calculated macroscopic-microscopic mass yields

NASA Astrophysics Data System (ADS)

Jaffke, Patrick; Möller, Peter; Talou, Patrick; Sierk, Arnold J.

2018-03-01

The Hauser-Feshbach statistical model is applied to the de-excitation of primary fission fragments using input mass yields calculated with macroscopic-microscopic models of the potential energy surface. We test the sensitivity of the prompt fission observables to the input mass yields for two important reactions, 235U(nth,f ) and 239Pu(nth,f ) , for which good experimental data exist. General traits of the mass yields, such as the location of the peaks and their widths, can impact both the prompt neutron and γ -ray multiplicities, as well as their spectra. Specifically, we use several mass yields to determine a linear correlation between the calculated prompt neutron multiplicity ν ¯ and the average heavy-fragment mass 〈Ah〉 of the input mass yields ∂ ν ¯/∂ 〈Ah〉 =±0.1 (n /f ) /u . The mass peak width influences the correlation between the total kinetic energy of the fission fragments and the total number of prompt neutrons emitted, ν¯T(TKE ) . Typical biases on prompt particle observables from using calculated mass yields instead of experimental ones are δ ν ¯=4 % for the average prompt neutron multiplicity, δ M ¯γ=1 % for the average prompt γ -ray multiplicity, δ ɛ¯nLAB=1 % for the average outgoing neutron energy, δ ɛ¯γ=1 % for the average γ -ray energy, and δ 〈TKE 〉=0.4 % for the average total kinetic energy of the fission fragments.

Bias sputtered NbN and superconducting nanowire devices

NASA Astrophysics Data System (ADS)

Dane, Andrew E.; McCaughan, Adam N.; Zhu, Di; Zhao, Qingyuan; Kim, Chung-Soo; Calandri, Niccolo; Agarwal, Akshay; Bellei, Francesco; Berggren, Karl K.

2017-09-01

Superconducting nanowire single photon detectors (SNSPDs) promise to combine near-unity quantum efficiency with >100 megacounts per second rates, picosecond timing jitter, and sensitivity ranging from x-ray to mid-infrared wavelengths. However, this promise is not yet fulfilled, as superior performance in all metrics is yet to be combined into one device. The highest single-pixel detection efficiency and the widest bias windows for saturated quantum efficiency have been achieved in SNSPDs based on amorphous materials, while the lowest timing jitter and highest counting rates were demonstrated in devices made from polycrystalline materials. Broadly speaking, the amorphous superconductors that have been used to make SNSPDs have higher resistivities and lower critical temperature (Tc) values than typical polycrystalline materials. Here, we demonstrate a method of preparing niobium nitride (NbN) that has lower-than-typical superconducting transition temperature and higher-than-typical resistivity. As we will show, NbN deposited onto unheated SiO2 has a low Tc and high resistivity but is too rough for fabricating unconstricted nanowires, and Tc is too low to yield SNSPDs that can operate well at liquid helium temperatures. By adding a 50 W RF bias to the substrate holder during sputtering, the Tc of the unheated NbN films was increased by up to 73%, and the roughness was substantially reduced. After optimizing the deposition for nitrogen flow rates, we obtained 5 nm thick NbN films with a Tc of 7.8 K and a resistivity of 253 μΩ cm. We used this bias sputtered room temperature NbN to fabricate SNSPDs. Measurements were performed at 2.5 K using 1550 nm light. Photon count rates appeared to saturate at bias currents approaching the critical current, indicating that the device's quantum efficiency was approaching unity. We measured a single-ended timing jitter of 38 ps. The optical coupling to these devices was not optimized; however, integration with front-side optical

Zero-sum bias: perceived competition despite unlimited resources.

PubMed

Meegan, Daniel V

2010-01-01

Zero-sum bias describes intuitively judging a situation to be zero-sum (i.e., resources gained by one party are matched by corresponding losses to another party) when it is actually non-zero-sum. The experimental participants were students at a university where students' grades are determined by how the quality of their work compares to a predetermined standard of quality rather than to the quality of the work produced by other students. This creates a non-zero-sum situation in which high grades are an unlimited resource. In three experiments, participants were shown the grade distribution after a majority of the students in a course had completed an assigned presentation, and asked to predict the grade of the next presenter. When many high grades had already been given, there was a corresponding increase in low grade predictions. This suggests a zero-sum bias, in which people perceive a competition for a limited resource despite unlimited resource availability. Interestingly, when many low grades had already been given, there was not a corresponding increase in high grade predictions. This suggests that a zero-sum heuristic is only applied in response to the allocation of desirable resources. A plausible explanation for the findings is that a zero-sum heuristic evolved as a cognitive adaptation to enable successful intra-group competition for limited resources. Implications for understanding inter-group interaction are also discussed.

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

PubMed

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

2017-09-01

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

Bias-field equalizer for bubble memories

NASA Technical Reports Server (NTRS)

Keefe, G. E.

1977-01-01

Magnetoresistive Perm-alloy sensor monitors bias field required to maintain bubble memory. Sensor provides error signal that, in turn, corrects magnitude of bias field. Error signal from sensor can be used to control magnitude of bias field in either auxiliary set of bias-field coils around permanent magnet field, or current in small coils used to remagnetize permanent magnet by infrequent, short, high-current pulse or short sequence of pulses.

Targeting carbon for crop yield and drought resilience

PubMed Central

Griffiths, Cara A

2017-01-01

Abstract Current methods of crop improvement are not keeping pace with projected increases in population growth. Breeding, focused around key traits of stem height and disease resistance, delivered the step‐change yield improvements of the green revolution of the 1960s. However, subsequently, yield increases through conventional breeding have been below the projected requirement of 2.4% per year required by 2050. Genetic modification (GM) mainly for herbicide tolerance and insect resistance has been transformational, akin to a second green revolution, although GM has yet to make major inroads into intrinsic yield processes themselves. Drought imposes the major restriction on crop yields globally but, as yet, has not benefited substantially from genetic improvement and still presents a major challenge to agriculture. Much still has to be learnt about the complex process of how drought limits yield and what should be targeted. Mechanisms of drought adaptation from the natural environment cannot be taken into crops without significant modification for the agricultural environment because mechanisms of drought tolerance are often in contrast with mechanisms of high productivity required in agriculture. However, through convergence of fundamental and translational science, it would appear that a mechanism of sucrose allocation in crops can be modified for both productivity and resilience to drought and other stresses. Recent publications show how this mechanism can be targeted by GM, natural variation and a new chemical approach. Here, with an emphasis on drought, we highlight how understanding fundamental science about how crops grow, develop and what limits their growth and yield can be combined with targeted genetic selection and pioneering chemical intervention technology for transformational yield improvements. © 2017 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. PMID

ROBIS: A new tool to assess risk of bias in systematic reviews was developed.

PubMed

Whiting, Penny; Savović, Jelena; Higgins, Julian P T; Caldwell, Deborah M; Reeves, Barnaby C; Shea, Beverley; Davies, Philippa; Kleijnen, Jos; Churchill, Rachel

2016-01-01

To develop ROBIS, a new tool for assessing the risk of bias in systematic reviews (rather than in primary studies). We used four-stage approach to develop ROBIS: define the scope, review the evidence base, hold a face-to-face meeting, and refine the tool through piloting. ROBIS is currently aimed at four broad categories of reviews mainly within health care settings: interventions, diagnosis, prognosis, and etiology. The target audience of ROBIS is primarily guideline developers, authors of overviews of systematic reviews ("reviews of reviews"), and review authors who might want to assess or avoid risk of bias in their reviews. The tool is completed in three phases: (1) assess relevance (optional), (2) identify concerns with the review process, and (3) judge risk of bias. Phase 2 covers four domains through which bias may be introduced into a systematic review: study eligibility criteria; identification and selection of studies; data collection and study appraisal; and synthesis and findings. Phase 3 assesses the overall risk of bias in the interpretation of review findings and whether this considered limitations identified in any of the phase 2 domains. Signaling questions are included to help judge concerns with the review process (phase 2) and the overall risk of bias in the review (phase 3); these questions flag aspects of review design related to the potential for bias and aim to help assessors judge risk of bias in the review process, results, and conclusions. ROBIS is the first rigorously developed tool designed specifically to assess the risk of bias in systematic reviews. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

ROBIS: A new tool to assess risk of bias in systematic reviews was developed

PubMed Central

Whiting, Penny; Savović, Jelena; Higgins, Julian P.T.; Caldwell, Deborah M.; Reeves, Barnaby C.; Shea, Beverley; Davies, Philippa; Kleijnen, Jos; Churchill, Rachel

2016-01-01

Objective To develop ROBIS, a new tool for assessing the risk of bias in systematic reviews (rather than in primary studies). Study Design and Setting We used four-stage approach to develop ROBIS: define the scope, review the evidence base, hold a face-to-face meeting, and refine the tool through piloting. Results ROBIS is currently aimed at four broad categories of reviews mainly within health care settings: interventions, diagnosis, prognosis, and etiology. The target audience of ROBIS is primarily guideline developers, authors of overviews of systematic reviews (“reviews of reviews”), and review authors who might want to assess or avoid risk of bias in their reviews. The tool is completed in three phases: (1) assess relevance (optional), (2) identify concerns with the review process, and (3) judge risk of bias. Phase 2 covers four domains through which bias may be introduced into a systematic review: study eligibility criteria; identification and selection of studies; data collection and study appraisal; and synthesis and findings. Phase 3 assesses the overall risk of bias in the interpretation of review findings and whether this considered limitations identified in any of the phase 2 domains. Signaling questions are included to help judge concerns with the review process (phase 2) and the overall risk of bias in the review (phase 3); these questions flag aspects of review design related to the potential for bias and aim to help assessors judge risk of bias in the review process, results, and conclusions. Conclusions ROBIS is the first rigorously developed tool designed specifically to assess the risk of bias in systematic reviews. PMID:26092286

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.

Introduction to Unconscious Bias

NASA Astrophysics Data System (ADS)

Schmelz, Joan T.

2010-05-01

We all have biases, and we are (for the most part) unaware of them. In general, men and women BOTH unconsciously devalue the contributions of women. This can have a detrimental effect on grant proposals, job applications, and performance reviews. Sociology is way ahead of astronomy in these studies. When evaluating identical application packages, male and female University psychology professors preferred 2:1 to hire "Brian” over "Karen” as an assistant professor. When evaluating a more experienced record (at the point of promotion to tenure), reservations were expressed four times more often when the name was female. This unconscious bias has a repeated negative effect on Karen's career. This talk will introduce the concept of unconscious bias and also give recommendations on how to address it using an example for a faculty search committee. The process of eliminating unconscious bias begins with awareness, then moves to policy and practice, and ends with accountability.

A propensity score approach to correction for bias due to population stratification using genetic and non-genetic factors.

PubMed

Zhao, Huaqing; Rebbeck, Timothy R; Mitra, Nandita

2009-12-01

Confounding due to population stratification (PS) arises when differences in both allele and disease frequencies exist in a population of mixed racial/ethnic subpopulations. Genomic control, structured association, principal components analysis (PCA), and multidimensional scaling (MDS) approaches have been proposed to address this bias using genetic markers. However, confounding due to PS can also be due to non-genetic factors. Propensity scores are widely used to address confounding in observational studies but have not been adapted to deal with PS in genetic association studies. We propose a genomic propensity score (GPS) approach to correct for bias due to PS that considers both genetic and non-genetic factors. We compare the GPS method with PCA and MDS using simulation studies. Our results show that GPS can adequately adjust and consistently correct for bias due to PS. Under no/mild, moderate, and severe PS, GPS yielded estimated with bias close to 0 (mean=-0.0044, standard error=0.0087). Under moderate or severe PS, the GPS method consistently outperforms the PCA method in terms of bias, coverage probability (CP), and type I error. Under moderate PS, the GPS method consistently outperforms the MDS method in terms of CP. PCA maintains relatively high power compared to both MDS and GPS methods under the simulated situations. GPS and MDS are comparable in terms of statistical properties such as bias, type I error, and power. The GPS method provides a novel and robust tool for obtaining less-biased estimates of genetic associations that can consider both genetic and non-genetic factors. 2009 Wiley-Liss, Inc.

Electronegative plasma diagnostic by laser photo-detachment combined with negatively biased Langmuir probe

NASA Astrophysics Data System (ADS)

Oudini, N.; Sirse, N.; Taccogna, F.; Ellingboe, A. R.; Bendib, A.

2018-05-01

We propose a new technique for diagnosing negative ion properties using Langmuir probe assisted pulsed laser photo-detachment. While the classical technique uses a laser pulse to convert negative ions into electron-atom pairs and a positively biased Langmuir probe tracking the change of electron saturation current, the proposed method uses a negatively biased Langmuir probe to track the temporal evolution of positive ion current. The negative bias aims to avoid the parasitic electron current inherent to probe tip surface ablation. In this work, we show through analytical and numerical approaches that, by knowing electron temperature and performing photo-detachment at two different laser wavelengths, it is possible to deduce plasma electronegativity (ratio of negative ion to electron densities) α, and anisothermicity (ratio of electron to negative ion temperatures) γ-. We present an analytical model that links the change in the collected positive ion current to plasma electronegativity and anisothermicity. Particle-In-Cell simulation is used as a numerical experiment covering a wide range of α and γ- to test the new analysis technique. The new technique is sensitive to α in the range 0.5 < α < 10 and yields γ- for large α, where negative ion flux affects the probe sheath behavior, typically α > 1.

Temperature trend biases

NASA Astrophysics Data System (ADS)

Venema, Victor; Lindau, Ralf

2016-04-01

In an accompanying talk we show that well-homogenized national dataset warm more than temperatures from global collections averaged over the region of common coverage. In this poster we want to present auxiliary work about possible biases in the raw observations and on how well relative statistical homogenization can remove trend biases. There are several possible causes of cooling biases, which have not been studied much. Siting could be an important factor. Urban stations tend to move away from the centre to better locations. Many stations started inside of urban areas and are nowadays more outside. Even for villages the temperature difference between the centre and edge can be 0.5°C. When a city station moves to an airport, which often happened around WWII, this takes the station (largely) out of the urban heat island. During the 20th century the Stevenson screen was established as the dominant thermometer screen. This screen protected the thermometer much better against radiation than earlier designs. Deficits of earlier measurement methods have artificially warmed the temperatures in the 19th century. Newer studies suggest we may have underestimated the size of this bias. Currently we are in a transition to Automatic Weather Stations. The net global effect of this transition is not clear at this moment. Irrigation on average decreases the 2m-temperature by about 1 degree centigrade. At the same time, irrigation has increased significantly during the last century. People preferentially live in irrigated areas and weather stations serve agriculture. Thus it is possible that there is a higher likelihood that weather stations are erected in irrigated areas than elsewhere. In this case irrigation could lead to a spurious cooling trend. In the Parallel Observations Science Team of the International Surface Temperature Initiative (ISTI-POST) we are studying influence of the introduction of Stevenson screens and Automatic Weather Stations using parallel measurements

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.

Under the Radar: How Unexamined Biases in Decision-Making Processes in Clinical Interactions Can Contribute to Health Care Disparities

PubMed Central

Fiske, Susan T.

2012-01-01

Several aspects of social psychological science shed light on how unexamined racial/ethnic biases contribute to health care disparities. Biases are complex but systematic, differing by racial/ethnic group and not limited to love–hate polarities. Group images on the universal social cognitive dimensions of competence and warmth determine the content of each group's overall stereotype, distinct emotional prejudices (pity, envy, disgust, pride), and discriminatory tendencies. These biases are often unconscious and occur despite the best intentions. Such ambivalent and automatic biases can influence medical decisions and interactions, systematically producing discrimination in health care and ultimately disparities in health. Understanding how these processes may contribute to bias in health care can help guide interventions to address racial and ethnic disparities in health. PMID:22420809

Toroidal-Core Microinductors Biased by Permanent Magnets

NASA Technical Reports Server (NTRS)

Lieneweg, Udo; Blaes, Brent

2003-01-01

. In either case, permanent-magnet material and the slant (if any) and thickness of the gap must be chosen according to the equations to obtain the required bias flux. In modifying the design of the inductor, one must ensure that the inductance is not altered. The simplest way to preserve the original value of inductance would be to leave the gap dimensions unchanged and fill the gap with a permanent- magnet material that, fortuitously, would produce just the required bias flux. A more generally applicable alternative would be to partly fill either the original gap or a slightly enlarged gap with a suitable permanent-magnet material (thereby leaving a small residual gap) so that the reluctance of the resulting magnetic circuit would yield the desired inductance.

Bias error reduction using ratios to baseline experiments. Heat transfer case study

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

Chakroun, W.; Taylor, R.P.; Coleman, H.W.

1993-10-01

Employing a set of experiments devoted to examining the effect of surface finish (riblets) on convective heat transfer as an example, this technical note seeks to explore the notion that precision uncertainties in experiments can be reduced by repeated trials and averaging. This scheme for bias error reduction can give considerable advantage when parametric effects are investigated experimentally. When the results of an experiment are presented as a ratio with the baseline results, a large reduction in the overall uncertainty can be achieved when all the bias limits in the variables of the experimental result are fully correlated with thosemore » of the baseline case. 4 refs.« less

Ligation Bias in Illumina Next-Generation DNA Libraries: Implications for Sequencing Ancient Genomes

PubMed Central

Seguin-Orlando, Andaine; Schubert, Mikkel; Clary, Joel; Stagegaard, Julia; Alberdi, Maria T.; Prado, José Luis; Prieto, Alfredo; Willerslev, Eske; Orlando, Ludovic

2013-01-01

Ancient DNA extracts consist of a mixture of endogenous molecules and contaminant DNA templates, often originating from environmental microbes. These two populations of templates exhibit different chemical characteristics, with the former showing depurination and cytosine deamination by-products, resulting from post-mortem DNA damage. Such chemical modifications can interfere with the molecular tools used for building second-generation DNA libraries, and limit our ability to fully characterize the true complexity of ancient DNA extracts. In this study, we first use fresh DNA extracts to demonstrate that library preparation based on adapter ligation at AT-overhangs are biased against DNA templates starting with thymine residues, contrarily to blunt-end adapter ligation. We observe the same bias on fresh DNA extracts sheared on Bioruptor, Covaris and nebulizers. This contradicts previous reports suggesting that this bias could originate from the methods used for shearing DNA. This also suggests that AT-overhang adapter ligation efficiency is affected in a sequence-dependent manner and results in an uneven representation of different genomic contexts. We then show how this bias could affect the base composition of ancient DNA libraries prepared following AT-overhang ligation, mainly by limiting the ability to ligate DNA templates starting with thymines and therefore deaminated cytosines. This results in particular nucleotide misincorporation damage patterns, deviating from the signature generally expected for authenticating ancient sequence data. Consequently, we show that models adequate for estimating post-mortem DNA damage levels must be robust to the molecular tools used for building ancient DNA libraries. PMID:24205269

Mobile Phone Cognitive Bias Modification Research Platform for Substance Use Disorders: Protocol for a Feasibility Study.

PubMed

Zhang, Melvyn; Ying, JiangBo; Song, Guo; Fung, Daniel Ss; Smith, Helen

2018-06-12

Cognitive biases refer to automatic attentional and interpretational tendencies, which could be retained by cognitive bias modification interventions. Cristea et al and Jones et al have published reviews (in 2016 and 2017 respectively) on the effectiveness of such interventions. The advancement of technologies such as electronic health (eHealth) and mobile health (mHealth) has led to them being harnessed for the delivery of cognitive bias modification. To date, at least eight studies have demonstrated the feasibility of mobile technologies for the delivery of cognitive bias modification. Most of the studies are limited to a description of the conventional cognitive bias modification methodology that has been adopted. None of the studies shared the developmental process for the methodology involved, such that future studies could adopt it in the cost-effective replication of such interventions. It is important to have a common platform that could facilitate the design and customization of cognitive bias modification interventions for a variety of psychiatric and addictive disorders. It is the aim of the current research protocol to describe the design of a research platform that allows for customization of cognitive bias modification interventions for addictive disorders. A multidisciplinary team of 2 addiction psychiatrists, a psychologist with expertise in cognitive bias modification, and a computer engineer, were involved in the development of the intervention. The proposed platform would comprise of a mobile phone version of the cognitive bias task which is controlled by a server that could customize the algorithm for the tasks and collate the reaction-time data in realtime. The server would also allow the researcher to program the specific set of images that will be present in the task. The mobile phone app would synchronize with the backend server in real-time. An open-sourced cross-platform gaming software from React Native was used in the current development

Electrochemical sensors applied to pollution monitoring: Measurement error and gas ratio bias - A volcano plume case study

NASA Astrophysics Data System (ADS)

Roberts, T. J.; Saffell, J. R.; Oppenheimer, C.; Lurton, T.

2014-06-01

There is an increasing scientific interest in the use of miniature electrochemical sensors to detect and quantify atmospheric trace gases. This has led to the development of ‘Multi-Gas' systems applied to measurements of both volcanic gas emissions, and urban air pollution. However, such measurements are subject to uncertainties introduced by sensor response time, a critical issue that has received limited attention to date. Here, a detailed analysis of output from an electrochemical SO2 sensor and two H2S sensors (contrasting in their time responses and cross-sensitivities) demonstrates how instrument errors arise under the conditions of rapidly fluctuating (by dilution) gas abundances, leading to scatter and importantly bias in the reported gas ratios. In a case study at Miyakejima volcano (Japan), electrochemical sensors were deployed at both the crater-rim and downwind locations, thereby exposed to rapidly fluctuating and smoothly varying plume gas concentrations, respectively. Discrepancies in the H2S/SO2 gas mixing ratios derived from these measurements are attributed to the sensors' differing time responses to SO2 and H2S under fluctuating plume conditions, with errors magnified by the need to correct for SO2 interference in the H2S readings. Development of a sensor response model that reproduces sensor t90 behaviour (the time required to reach 90% of the final signal following a step change in gas abundance) during calibration enabled this measurement error to be simulated numerically. The sensor response times were characterised as SO2 sensor (t90 ~ 13 s), H2S sensor without interference (t90 ~ 11 s), and H2S sensor with interference (t90 ~ 20 s to H2S and ~ 32 s to SO2). We show that a method involving data integration between periods of episodic plume exposure identifiable in the sensor output yields a less biased H2S/SO2 ratio estimate than that derived from standard analysis approaches. For the Miyakejima crater-rim dataset this method yields highly

Free energy surface of an intrinsically disordered protein: comparison between temperature replica exchange molecular dynamics and bias-exchange metadynamics.

PubMed

Zerze, Gül H; Miller, Cayla M; Granata, Daniele; Mittal, Jeetain

2015-06-09

Intrinsically disordered proteins (IDPs), which are expected to be largely unstructured under physiological conditions, make up a large fraction of eukaryotic proteins. Molecular dynamics simulations have been utilized to probe structural characteristics of these proteins, which are not always easily accessible to experiments. However, exploration of the conformational space by brute force molecular dynamics simulations is often limited by short time scales. Present literature provides a number of enhanced sampling methods to explore protein conformational space in molecular simulations more efficiently. In this work, we present a comparison of two enhanced sampling methods: temperature replica exchange molecular dynamics and bias exchange metadynamics. By investigating both the free energy landscape as a function of pertinent order parameters and the per-residue secondary structures of an IDP, namely, human islet amyloid polypeptide, we found that the two methods yield similar results as expected. We also highlight the practical difference between the two methods by describing the path that we followed to obtain both sets of data.

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.

Simulation of corn yields and parameters uncertainties analysis in Hebei and Sichuang, China

NASA Astrophysics Data System (ADS)

Fu, A.; Xue, Y.; Hartman, M. D.; Chandran, A.; Qiu, B.; Liu, Y.

2016-12-01

Corn is one of most important agricultural production in China. Research on the impacts of climate change and human activities on corn yields is important in understanding and mitigating the negative effects of environmental factors on corn yields and maintaining the stable corn production. Using climatic data, including daily temperature, precipitation, and solar radiation from 1948 to 2010, soil properties, observed corn yields, and farmland management information, corn yields in Sichuang and Hebei Provinces of China in the past 63 years were simulated using the Daycent model, and the results was evaluated using Root mean square errors, bias, simulation efficiency, and standard deviation. The primary climatic factors influencing corn yields were examined, the uncertainties of climatic factors was analyzed, and the uncertainties of human activity parameters were also studied by changing fertilization levels and cultivated ways. The results showed that: (1) Daycent model is capable to simulate corn yields in Sichuang and Hebei provinces of China. Observed and simulated corn yields have the similar increasing trend with time. (2) The minimum daily temperature is the primary factor influencing corn yields in Sichuang. In Hebei Province, daily temperature, precipitation and wind speed significantly affect corn yields.(3) When the global warming trend of original data was removed, simulated corn yields were lower than before, decreased by about 687 kg/hm2 from 1992 to 2010; When the fertilization levels, cultivated ways were increased and decreased by 50% and 75%, respectively in the Schedule file in Daycent model, the simulated corn yields increased by 1206 kg/hm2 and 776 kg/hm2, respectively, with the enhancement of fertilization level and the improvement of cultivated way. This study provides a scientific base for selecting a suitable fertilization level and cultivated way in corn fields in China.

SLS Trade Study 0058: Day of Launch (DOL) Wind Biasing

NASA Technical Reports Server (NTRS)

Decker, Ryan K.; Duffin, Paul; Hill, Ashley; Beck, Roger; Dukeman, Greg

2014-01-01

SLS heritage hardware and legacy designs have shown load exceedances at several locations during Design Analysis Cycles (DAC): MPCV Z bending moments; ICPS Electro-Mechanical Actuator (EMA) loads; Core Stage loads just downstream of Booster forward interface. SLS Buffet Loads Mitigation Task Team (BLMTT) tasked to study issue. Identified low frequency buffet load responses are a function of the vehicle's total angle of attack (AlphaTotal). SLS DOL Wind Biasing Trade team to analyze DOL wind biasing methods to limit maximum AlphaTotal in the M0.8 - 2.0 altitude region for EM-1 and EM-2 missions through investigating: Trajectory design process; Wind wavelength filtering options; Launch availability; DOL process to achieve shorter processing/uplink timeline. Trade Team consisted of personnel supporting SLS, MPCV, GSDO programs.

Affective state influences perception by affecting decision parameters underlying bias and sensitivity.

PubMed

Lynn, Spencer K; Zhang, Xuan; Barrett, Lisa Feldman

2012-08-01

Studies of the effect of affect on perception often show consistent directional effects of a person's affective state on perception. Unpleasant emotions have been associated with a "locally focused" style of stimulus evaluation, and positive emotions with a "globally focused" style. Typically, however, studies of affect and perception have not been conducted under the conditions of perceptual uncertainty and behavioral risk inherent to perceptual judgments outside the laboratory. We investigated the influence of perceivers' experienced affect (valence and arousal) on the utility of social threat perception by combining signal detection theory and behavioral economics. We compared 3 perceptual decision environments that systematically differed with respect to factors that underlie uncertainty and risk: the base rate of threat, the costs of incorrect identification threat, and the perceptual similarity of threats and nonthreats. We found that no single affective state yielded the best performance on the threat perception task across the 3 environments. Unpleasant valence promoted calibration of response bias to base rate and costs, high arousal promoted calibration of perceptual sensitivity to perceptual similarity, and low arousal was associated with an optimal adjustment of bias to sensitivity. However, the strength of these associations was conditional upon the difficulty of attaining optimal bias and high sensitivity, such that the effect of the perceiver's affective state on perception differed with the cause and/or level of uncertainty and risk.

Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxies

NASA Astrophysics Data System (ADS)

Lawlor, David; Budavári, Tamás; Mahoney, Michael W.

2016-12-01

We present a novel approach to studying the diversity of galaxies. It is based on a novel spectral graph technique, that of locally-biased semi-supervised eigenvectors. Our method introduces new coordinates that summarize an entire spectrum, similar to but going well beyond the widely used Principal Component Analysis (PCA). Unlike PCA, however, this technique does not assume that the Euclidean distance between galaxy spectra is a good global measure of similarity. Instead, we relax that condition to only the most similar spectra, and we show that doing so yields more reliable results for many astronomical questions of interest. The global variant of our approach can identify very finely numerous astronomical phenomena of interest. The locally-biased variants of our basic approach enable us to explore subtle trends around a set of chosen objects. The power of the method is demonstrated in the Sloan Digital Sky Survey Main Galaxy Sample, by illustrating that the derived spectral coordinates carry an unprecedented amount of information.