Bias against research on gender bias.

Science.gov (United States)

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.

Measuring Agricultural Bias

DEFF Research Database (Denmark)

Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn

The measurement issue is the key issue in the literature on trade policy-induced agri-cultural price incentive bias. This paper introduces a general equilibrium effective rate of protection (GE-ERP) measure, which extends and generalizes earlier partial equilibrium nominal protection measures...... shares and intersectoral linkages - are crucial for determining the sign and magnitude of trade policy bias. The GE-ERP measure is therefore uniquely suited to capture the full impact of trade policies on agricultural price incentives. A Monte Carlo procedure confirms that the results are robust....... For the 15 sample countries, the results indicate that the agricultural price incentive bias, which was generally perceived to exist during the 1980s, was largely eliminated during the 1990s. The results also demonstrate that general equilibrium effects and country-specific characteristics - including trade...

Stabilization of electron beam spot size by self bias potential

International Nuclear Information System (INIS)

Kwan, T.J.T.; Moir, D.C.; Snell, C.M.; Kang, M.

1998-01-01

In high resolution flash x-ray imaging technology the electric field developed between the electron beam and the converter target is large enough to draw ions from the target surface. The ions provide fractional neutralization and cause the electron beam to focus radially inward, and the focal point subsequently moves upstream due to the expansion of the ion column. A self-bias target concept is proposed and verified via computer simulation that the electron charge deposited on the target can generate an electric potential, which can effectively limit the ion motion and thereby stabilize the growth of the spot size. A target chamber using the self bias target concept was designed and tested in the Integrated Test Stand (ITS). The authors have obtained good agreement between computer simulation and experiment

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

Science.gov (United States)

Bouzid, Assil; Pasquarello, Alfredo

2018-04-19

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

Applying GRADE-CERQual to qualitative evidence synthesis findings-paper 7: understanding the potential impacts of dissemination bias.

Science.gov (United States)

Booth, Andrew; Lewin, Simon; Glenton, Claire; Munthe-Kaas, Heather; Toews, Ingrid; Noyes, Jane; Rashidian, Arash; Berg, Rigmor C; Nyakang'o, Brenda; Meerpohl, Joerg J

2018-01-25

The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on a probable fifth component, dissemination bias. Given its exploratory nature, we are not yet able to provide guidance on applying this potential component of the CERQual approach. Instead, we focus on how dissemination bias might be conceptualised in the context of qualitative research and the potential impact dissemination bias might have on an overall assessment of confidence in a review finding. We also set out a proposed research agenda in this area. We developed this paper by gathering feedback from relevant research communities, searching MEDLINE and Web of Science to identify and characterise the existing literature discussing or assessing dissemination bias in qualitative research and its wider implications, developing consensus through project group meetings, and conducting an online survey of the extent, awareness and perceptions of dissemination bias in qualitative research. We have defined dissemination bias in qualitative research as a systematic distortion of the phenomenon of interest due to selective dissemination of studies or individual study findings. Dissemination bias is important for qualitative evidence syntheses as the selective dissemination of qualitative studies and/or study findings may distort our understanding of

Tax Evasion, Information Reporting, and the Regressive Bias Hypothesis

DEFF Research Database (Denmark)

Boserup, Simon Halphen; Pinje, Jori Veng

A robust prediction from the tax evasion literature is that optimal auditing induces a regressive bias in effective tax rates compared to statutory rates. If correct, this will have important distributional consequences. Nevertheless, the regressive bias hypothesis has never been tested empirically...

Are Managed Futures Indices Telling Truth? Biases in CTA Databases and Proposals of Potential Enhancements

Directory of Open Access Journals (Sweden)

Adam Zaremba

2011-07-01

Full Text Available Managed futures are an alternative asset class which has recently became considerably popular among investment industry. However, due to its characteristics, access to managed futures historical performance statistics is relatively confined. All available information originates from commercial and academic databases, reporting to which is entirely voluntary. This situation results in series of biases which distort the managed futures performance in the eyes of investors. The paper consists of two parts. First, the author reviews and describes various biases that influence the reliability of the managed futures indices and databases. The second section encompasses author’s proposals of potential enhancements, which aim to reduce the impact of the biases in order to derive a benchmark that could better reflect characteristics of managed futures investment from the point of view of a potential investor.

Robust mislabel logistic regression without modeling mislabel probabilities.

Science.gov (United States)

Hung, Hung; Jou, Zhi-Yu; Huang, Su-Yun

2018-03-01

Logistic regression is among the most widely used statistical methods for linear discriminant analysis. In many applications, we only observe possibly mislabeled responses. Fitting a conventional logistic regression can then lead to biased estimation. One common resolution is to fit a mislabel logistic regression model, which takes into consideration of mislabeled responses. Another common method is to adopt a robust M-estimation by down-weighting suspected instances. In this work, we propose a new robust mislabel logistic regression based on γ-divergence. Our proposal possesses two advantageous features: (1) It does not need to model the mislabel probabilities. (2) The minimum γ-divergence estimation leads to a weighted estimating equation without the need to include any bias correction term, that is, it is automatically bias-corrected. These features make the proposed γ-logistic regression more robust in model fitting and more intuitive for model interpretation through a simple weighting scheme. Our method is also easy to implement, and two types of algorithms are included. Simulation studies and the Pima data application are presented to demonstrate the performance of γ-logistic regression. © 2017, The International Biometric Society.

Cognitive Bias in the Verification and Validation of Space Flight Systems

Science.gov (United States)

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 Classroom Demonstration of Potential Biases in the Subjective Interpretation of Projective Tests.

Science.gov (United States)

Wiederman, Michael W.

1999-01-01

Suggests that instructors teaching psychological assessment can use a demonstration to illustrate potential biases when subjectively interpreting response to projective stimuli. Outlines the classroom procedure, notes styles of learning involved, and presents a summary of student evaluations. (DSK)

A robust background regression based score estimation algorithm for hyperspectral anomaly detection

Science.gov (United States)

Zhao, Rui; Du, Bo; Zhang, Liangpei; Zhang, Lefei

2016-12-01

Anomaly detection has become a hot topic in the hyperspectral image analysis and processing fields in recent years. The most important issue for hyperspectral anomaly detection is the background estimation and suppression. Unreasonable or non-robust background estimation usually leads to unsatisfactory anomaly detection results. Furthermore, the inherent nonlinearity of hyperspectral images may cover up the intrinsic data structure in the anomaly detection. In order to implement robust background estimation, as well as to explore the intrinsic data structure of the hyperspectral image, we propose a robust background regression based score estimation algorithm (RBRSE) for hyperspectral anomaly detection. The Robust Background Regression (RBR) is actually a label assignment procedure which segments the hyperspectral data into a robust background dataset and a potential anomaly dataset with an intersection boundary. In the RBR, a kernel expansion technique, which explores the nonlinear structure of the hyperspectral data in a reproducing kernel Hilbert space, is utilized to formulate the data as a density feature representation. A minimum squared loss relationship is constructed between the data density feature and the corresponding assigned labels of the hyperspectral data, to formulate the foundation of the regression. Furthermore, a manifold regularization term which explores the manifold smoothness of the hyperspectral data, and a maximization term of the robust background average density, which suppresses the bias caused by the potential anomalies, are jointly appended in the RBR procedure. After this, a paired-dataset based k-nn score estimation method is undertaken on the robust background and potential anomaly datasets, to implement the detection output. The experimental results show that RBRSE achieves superior ROC curves, AUC values, and background-anomaly separation than some of the other state-of-the-art anomaly detection methods, and is easy to implement

Links among available integral benchmarks and differential date evaluations, computational biases and uncertainties, and nuclear criticality safety biases on potential MOX production throughput

International Nuclear Information System (INIS)

Goluoglu, S.; Hopper, C.M.

2004-01-01

Through the use of Oak Ridge National Laboratory's recently developed and applied sensitivity and uncertainty computational analysis techniques, this paper presents the relevance and importance of available and needed integral benchmarks and differential data evaluations impacting potential MOX production throughput determinations relative to low-moderated MOX fuel blending operations. The relevance and importance in the availability of or need for critical experiment benchmarks and data evaluations are presented in terms of computational biases as influenced by computational and experimental sensitivities and uncertainties relative to selected MOX production powder blending processes. Recent developments for estimating the safe margins of subcriticality for assuring nuclear criticality safety for process approval are presented. In addition, the impact of the safe margins (due to computational biases and uncertainties) on potential MOX production throughput will also be presented. (author)

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

Science.gov (United States)

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 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.

Robust model-based analysis of single-particle tracking experiments with Spot-On

Science.gov (United States)

Grimm, Jonathan B; Lavis, Luke D

2018-01-01

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce ‘Spot-On’, an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants. PMID:29300163

Electrically tunable robust edge states in graphene-based topological photonic crystal slabs

Science.gov (United States)

Song, Zidong; Liu, HongJun; Huang, Nan; Wang, ZhaoLu

2018-03-01

Topological photonic crystals are optical structures supporting topologically protected unidirectional edge states that exhibit robustness against defects. Here, we propose a graphene-based all-dielectric photonic crystal slab structure that supports two-dimensionally confined topological edge states. These topological edge states can be confined in the out-of-plane direction by two parallel graphene sheets. In the structure, the excitation frequency range of topological edge states can be dynamically and continuously tuned by varying bias voltage across the two parallel graphene sheets. Utilizing this kind of architecture, we construct Z-shaped channels to realize topological edge transmission with diffrerent frequencies. The proposal provides a new degree of freedom to dynamically control topological edge states and potential applications for robust integrated photonic devices and optical communication systems.

Prevalence of Potential and Clinically Relevant Statin-Drug Interactions in Frail and Robust Older Inpatients.

Science.gov (United States)

Thai, Michele; Hilmer, Sarah; Pearson, Sallie-Anne; Reeve, Emily; Gnjidic, Danijela

2015-10-01

A significant proportion of older people are prescribed statins and are also exposed to polypharmacy, placing them at increased risk of statin-drug interactions. To describe the prevalence rates of potential and clinically relevant statin-drug interactions in older inpatients according to frailty status. A cross-sectional study of patients aged ≥65 years who were prescribed a statin and were admitted to a teaching hospital between 30 July and 10 October 2014 in Sydney, Australia, was conducted. Data on socio-demographics, comorbidities and medications were collected using a standardized questionnaire. Potential statin-drug interactions were defined if listed in the Australian Medicines Handbook and three international drug information sources: the British National Formulary, Drug Interaction Facts and Drug-Reax(®). Clinically relevant statin-drug interactions were defined as interactions with the highest severity rating in at least two of the three international drug information sources. Frailty was assessed using the Reported Edmonton Frail Scale. A total of 180 participants were recruited (median age 78 years, interquartile range 14), 35.0% frail and 65.0% robust. Potential statin-drug interactions were identified in 10% of participants, 12.7% of frail participants and 8.5% of robust participants. Clinically relevant statin-drug interactions were identified in 7.8% of participants, 9.5% of frail participants and 6.8% of robust participants. Depending on the drug information source used, the prevalence rates of potential and clinically relevant statin-drug interactions ranged between 14.4 and 35.6% and between 14.4 and 20.6%, respectively. In our study of frail and robust older inpatients taking statins, the overall prevalence of potential statin-drug interactions was low and varied significantly according to the drug information source used.

Competition improves robustness against loss of information

Directory of Open Access Journals (Sweden)

Arash eKermani Kolankeh

2015-03-01

Full Text Available A substantial number of works aimed at modeling the receptive field properties of the primary visual cortex (V1. Their evaluation criterion is usually the similarity of the model response properties to the recorded responses from biological organisms. However, as several algorithms were able to demonstrate some degree of similarity to biological data based on the existing criteria, we focus on the robustness against loss of information in the form of occlusions as an additional constraint for better understanding the algorithmic level of early vision in the brain. We try to investigate the influence of competition mechanisms on the robustness. Therefore, we compared four methods employing different competition mechanisms, namely, independent component analysis, non-negative matrix factorization with sparseness constraint, predictive coding/biased competition, and a Hebbian neural network with lateral inhibitory connections. Each of those methods is known to be capable of developing receptive fields comparable to those of V1 simple-cells. Since measuring the robustness of methods having simple-cell like receptive fields against occlusion is difficult, we measure the robustness using the classification accuracy on the MNIST hand written digit dataset. For this we trained all methods on the training set of the MNIST hand written digits dataset and tested them on a MNIST test set with different levels of occlusions. We observe that methods which employ competitive mechanisms have higher robustness against loss of information. Also the kind of the competition mechanisms plays an important role in robustness. Global feedback inhibition as employed in predictive coding/biased competition has an advantage compared to local lateral inhibition learned by an anti-Hebb rule.

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

Directory of Open Access Journals (Sweden)

Manan Gupta

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

Potential energy landscape and robustness of a gene regulatory network: toggle switch.

Directory of Open Access Journals (Sweden)

Keun-Young Kim

2007-03-01

Full Text Available Finding a multidimensional potential landscape is the key for addressing important global issues, such as the robustness of cellular networks. We have uncovered the underlying potential energy landscape of a simple gene regulatory network: a toggle switch. This was realized by explicitly constructing the steady state probability of the gene switch in the protein concentration space in the presence of the intrinsic statistical fluctuations due to the small number of proteins in the cell. We explored the global phase space for the system. We found that the protein synthesis rate and the unbinding rate of proteins to the gene were small relative to the protein degradation rate; the gene switch is monostable with only one stable basin of attraction. When both the protein synthesis rate and the unbinding rate of proteins to the gene are large compared with the protein degradation rate, two global basins of attraction emerge for a toggle switch. These basins correspond to the biologically stable functional states. The potential energy barrier between the two basins determines the time scale of conversion from one to the other. We found as the protein synthesis rate and protein unbinding rate to the gene relative to the protein degradation rate became larger, the potential energy barrier became larger. This also corresponded to systems with less noise or the fluctuations on the protein numbers. It leads to the robustness of the biological basins of the gene switches. The technique used here is general and can be applied to explore the potential energy landscape of the gene networks.

White and Black American Children’s Implicit Intergroup Bias

Science.gov (United States)

Newheiser, Anna-Kaisa; Olson, Kristina R.

2011-01-01

Despite a decline in explicit prejudice, adults and children from majority groups (e.g., White Americans) often express bias implicitly, as assessed by the Implicit Association Test. In contrast, minority-group (e.g., Black American) adults on average show no bias on the IAT. In the present research, representing the first empirical investigation of whether Black children’s IAT responses parallel those of Black adults, we examined implicit bias in 7–11-year-old White and Black American children. Replicating previous findings with adults, whereas White children showed a robust ingroup bias, Black children showed no bias. Additionally, we investigated the role of valuing status in the development of implicit bias. For Black children, explicit preference for high status predicted implicit outgroup bias: Black children who explicitly expressed high preference for rich (vs. poor) people showed an implicit preference for Whites comparable in magnitude to White children’s ingroup bias. Implications for research on intergroup bias are discussed. PMID:22184478

Robust and accurate detection algorithm for multimode polymer optical FBG sensor system

DEFF Research Database (Denmark)

Ganziy, Denis; Jespersen, O.; Rose, B.

2015-01-01

We propose a novel dynamic gate algorithm (DGA) for robust and fast peak detection. The algorithm uses a threshold determined detection window and center of gravity algorithm with bias compensation. Our experiment demonstrates that the DGA method is fast and robust with better stability and accur...

Exponential dependence of potential barrier height on biased voltages of inorganic/organic static induction transistor

International Nuclear Information System (INIS)

Zhang Yong; Yang Jianhong; Cai Xueyuan; Wang Zaixing

2010-01-01

The exponential dependence of the potential barrier height φ c on the biased voltages of the inorganic/organic static induction transistor (SIT/OSIT) through a normalized approach in the low-current regime is presented. It shows a more accurate description than the linear expression of the potential barrier height. Through the verification of the numerical calculated and experimental results, the exponential dependence of φ c on the applied biases can be used to derive the I-V characteristics. For both SIT and OSIT, the calculated results, using the presented relationship, are agreeable with the experimental results. Compared to the previous linear relationship, the exponential description of φ c can contribute effectively to reduce the error between the theoretical and experimental results of the I-V characteristics. (semiconductor devices)

A robust classic.

Science.gov (United States)

Kutzner, Florian; Vogel, Tobias; Freytag, Peter; Fiedler, Klaus

2011-01-01

In the present research, we argue for the robustness of illusory correlations (ICs, Hamilton & Gifford, 1976) regarding two boundary conditions suggested in previous research. First, we argue that ICs are maintained under extended experience. Using simulations, we derive conflicting predictions. Whereas noise-based accounts predict ICs to be maintained (Fielder, 2000; Smith, 1991), a prominent account based on discrepancy-reducing feedback learning predicts ICs to disappear (Van Rooy et al., 2003). An experiment involving 320 observations with majority and minority members supports the claim that ICs are maintained. Second, we show that actively using the stereotype to make predictions that are met with reward and punishment does not eliminate the bias. In addition, participants' operant reactions afford a novel online measure of ICs. In sum, our findings highlight the robustness of ICs that can be explained as a result of unbiased but noisy learning.

The robustness of truncated Airy beam in PT Gaussian potentials media

Science.gov (United States)

Wang, Xianni; Fu, Xiquan; Huang, Xianwei; Yang, Yijun; Bai, Yanfeng

2018-03-01

The robustness of truncated Airy beam in parity-time (PT) symmetric Gaussian potentials media is numerically investigated. A high-peak power beam sheds from the Airy beam due to the media modulation while the Airy wavefront still retain its self-bending and non-diffraction characteristics under the influence of modulation parameters. Increasing the modulation factor results in the smaller value of maximum power of the center beam, and the opposite trend occurs with the increment of the modulation depth. However, the parabolic trajectory of the Airy wavefront does not be influenced. By utilizing the unique features, the Airy beam can be used as a long distance transmission source under the PT symmetric Gaussian potentials medium.

Attentional and affective biases for attractive females emerge early in development.

Science.gov (United States)

Rennels, Jennifer Lynn; Verba, Stephanie Ann

2017-01-01

Predominant experience with females early in development results in infants developing an attractive, female-like facial representation that guides children's attention toward and affective preferences for attractive females. When combined with increased interest in the other sex at puberty, these early emerging biases might help explain the robust prosocial and financial biases men exhibit toward attractive women during adulthood.

Graphical evaluation of the ridge-type robust regression estimators in mixture experiments.

Science.gov (United States)

Erkoc, Ali; Emiroglu, Esra; Akay, Kadri Ulas

2014-01-01

In mixture experiments, estimation of the parameters is generally based on ordinary least squares (OLS). However, in the presence of multicollinearity and outliers, OLS can result in very poor estimates. In this case, effects due to the combined outlier-multicollinearity problem can be reduced to certain extent by using alternative approaches. One of these approaches is to use biased-robust regression techniques for the estimation of parameters. In this paper, we evaluate various ridge-type robust estimators in the cases where there are multicollinearity and outliers during the analysis of mixture experiments. Also, for selection of biasing parameter, we use fraction of design space plots for evaluating the effect of the ridge-type robust estimators with respect to the scaled mean squared error of prediction. The suggested graphical approach is illustrated on Hald cement data set.

Negativity bias for sad faces in depression: An event-related potential study.

Science.gov (United States)

Dai, Qin; Wei, Juanjuan; Shu, Xiaorui; Feng, Zhengzhi

2016-12-01

Negativity bias in depression has been previously confirmed. However, mainly during a valence category task, it remains unclear how happy or unhappy individuals perceive emotional materials. Moreover, cerebral alteration measurements during a valence judgment task is lacking. The present study aimed to explore a valence judgment of a valence rating task, combined with event-related potential (ERP) recording. Healthy controls, individuals with sub-clinical depression, and patients diagnosed with major depressive disorder (MDD) were recruited. Twenty-four subjects in each group completed a valence rating task, during which the ERP amplitudes were recorded. The MDD group had lower valence scores, faster responses, and greater N1 amplitudes for sad faces, whereas individuals with sub-clinical depression had faster responses and greater P1 amplitudes for all faces but lower valence scores and greater P2 amplitudes for happy faces. The findings suggest the tendency toward a negativity bias in valence ratings in patients with depression supported by behavioral and cerebral evidence, which is a latent trait of depression, possibly associated with the vulnerability of depression. The current study offers the first experimental evidence of cognitive and cerebral biomarkers of negativity bias in valence ratings in depression, which confirms Beck's cognitive theory and gives important direction for clinical therapy. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Bias modification training can alter approach bias and chocolate consumption.

Science.gov (United States)

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.

Robust and bias-corrected estimation of the coefficient of tail dependence

DEFF Research Database (Denmark)

Dutang, C.; Goegebeur, Y.; Guillou, A.

2014-01-01

We introduce a robust and asymptotically unbiased estimator for the coefficient of tail dependence in multivariate extreme value statistics. The estimator is obtained by fitting a second order model to the data by means of the minimum density power divergence criterion. The asymptotic properties ...

Bias correction of daily satellite precipitation data using genetic algorithm

Science.gov (United States)

Pratama, A. W.; Buono, A.; Hidayat, R.; Harsa, H.

2018-05-01

Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) was producted by blending Satellite-only Climate Hazards Group InfraRed Precipitation (CHIRP) with Stasion observations data. The blending process was aimed to reduce bias of CHIRP. However, Biases of CHIRPS on statistical moment and quantil values were high during wet season over Java Island. This paper presented a bias correction scheme to adjust statistical moment of CHIRP using observation precipitation data. The scheme combined Genetic Algorithm and Nonlinear Power Transformation, the results was evaluated based on different season and different elevation level. The experiment results revealed that the scheme robustly reduced bias on variance around 100% reduction and leaded to reduction of first, and second quantile biases. However, bias on third quantile only reduced during dry months. Based on different level of elevation, the performance of bias correction process is only significantly different on skewness indicators.

Asymmetric forecasting and commitment policy in a robust control problem

OpenAIRE

Taro Ikeda

2013-01-01

This paper provides a piece of results regarding asymmetric forecasting and commitment monetary policy with a robust control algorithm. Previous studies provide no clarification of the connection between asymmetric preference and robust commitment policy. Three results emerge from general equilibrium modeling with asymmetric preference: (i) the condition for system stability implies an average inflation bias with respect to asymmetry (ii) the effect of asymmetry can be mitigated if policy mak...

Cognitive bias in clinical practice - nurturing healthy skepticism among medical students.

Science.gov (United States)

Bhatti, Alysha

2018-01-01

Errors in clinical reasoning, known as cognitive biases, are implicated in a significant proportion of diagnostic errors. Despite this knowledge, little emphasis is currently placed on teaching cognitive psychology in the undergraduate medical curriculum. Understanding the origin of these biases and their impact on clinical decision making helps stimulate reflective practice. This article outlines some of the common types of cognitive biases encountered in the clinical setting as well as cognitive debiasing strategies. Medical educators should nurture healthy skepticism among medical students by raising awareness of cognitive biases and equipping them with robust tools to circumvent such biases. This will enable tomorrow's doctors to improve the quality of care delivered, thus optimizing patient outcomes.

Junction Potentials Bias Measurements of Ion Exchange Membrane Permselectivity.

Science.gov (United States)

Kingsbury, Ryan S; Flotron, Sophie; Zhu, Shan; Call, Douglas F; Coronell, Orlando

2018-04-17

Ion exchange membranes (IEMs) are versatile materials relevant to a variety of water and waste treatment, energy production, and industrial separation processes. The defining characteristic of IEMs is their ability to selectively allow positive or negative ions to permeate, which is referred to as permselectivity. Measured values of permselectivity that equal unity (corresponding to a perfectly selective membrane) or exceed unity (theoretically impossible) have been reported for cation exchange membranes (CEMs). Such nonphysical results call into question our ability to correctly measure this crucial membrane property. Because weighing errors, temperature, and measurement uncertainty have been shown to not explain these anomalous permselectivity results, we hypothesized that a possible explanation are junction potentials that occur at the tips of reference electrodes. In this work, we tested this hypothesis by comparing permselectivity values obtained from bare Ag/AgCl wire electrodes (which have no junction) to values obtained from single-junction reference electrodes containing two different electrolytes. We show that permselectivity values obtained using reference electrodes with junctions were greater than unity for CEMs. In contrast, electrodes without junctions always produced permselectivities lower than unity. Electrodes with junctions also resulted in artificially low permselectivity values for AEMs compared to electrodes without junctions. Thus, we conclude that junctions in reference electrodes introduce two biases into results in the IEM literature: (i) permselectivity values larger than unity for CEMs and (ii) lower permselectivity values for AEMs compared to those for CEMs. These biases can be avoided by using electrodes without a junction.

Application of Probabilistic Multiple-Bias Analyses to a Cohort- and a Case-Control Study on the Association between Pandemrix™ and Narcolepsy.

Directory of Open Access Journals (Sweden)

Kaatje Bollaerts

Full Text Available An increase in narcolepsy cases was observed in Finland and Sweden towards the end of the 2009 H1N1 influenza pandemic. Preliminary observational studies suggested a temporal link with the pandemic influenza vaccine Pandemrix™, leading to a number of additional studies across Europe. Given the public health urgency, these studies used readily available retrospective data from various sources. The potential for bias in such settings was generally acknowledged. Although generally advocated by key opinion leaders and international health authorities, no systematic quantitative assessment of the potential joint impact of biases was undertaken in any of these studies.We applied bias-level multiple-bias analyses to two of the published narcolepsy studies: a pediatric cohort study from Finland and a case-control study from France. In particular, we developed Monte Carlo simulation models to evaluate a potential cascade of biases, including confounding by age, by indication and by natural H1N1 infection, selection bias, disease- and exposure misclassification. All bias parameters were evidence-based to the extent possible.Given the assumptions used for confounding, selection bias and misclassification, the Finnish rate ratio of 13.78 (95% CI: 5.72-28.11 reduced to a median value of 6.06 (2.5th- 97.5th percentile: 2.49-15.1 and the French odds ratio of 5.43 (95% CI: 2.6-10.08 to 1.85 (2.5th-97.5th percentile: 0.85-4.08.We illustrate multiple-bias analyses using two studies on the Pandemrix™-narcolepsy association and advocate their use to better understand the robustness of study findings. Based on our multiple-bias models, the observed Pandemrix™-narcolepsy association consistently persists in the Finnish study. For the French study, the results of our multiple-bias models were inconclusive.

Robust inference in sample selection models

KAUST Repository

Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio

2015-01-01

The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman's two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

Robust inference in sample selection models

KAUST Repository

Zhelonkin, Mikhail

2015-11-20

The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman\\'s two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

Recognition bias and the physical attractiveness stereotype.

Science.gov (United States)

Rohner, Jean-Christophe; Rasmussen, Anders

2012-06-01

Previous studies have found a recognition bias for information consistent with the physical attractiveness stereotype (PAS), in which participants believe that they remember that attractive individuals have positive qualities and that unattractive individuals have negative qualities, regardless of what information actually occurred. The purpose of this research was to examine whether recognition bias for PAS congruent information is replicable and invariant across a variety of conditions (i.e. generalizable). The effects of nine different moderator variables were examined in two experiments. With a few exceptions, the effect of PAS congruence on recognition bias was independent of the moderator variables. The results suggest that the tendency to believe that one remembers information consistent with the physical attractiveness stereotype is a robust phenomenon. © 2012 The Authors. Scandinavian Journal of Psychology © 2012 The Scandinavian Psychological Associations.

Spatial uncertainty in bias corrected climate change projections and hydrogeological impacts

DEFF Research Database (Denmark)

Seaby, Lauren Paige; Refsgaard, Jens Christian; Sonnenborg, Torben

2015-01-01

Model pairing, this paper analyses the relationship between complexity and robustness of three distribution-based scaling (DBS) bias correction methods applied to daily precipitation at various spatial scales. Hydrological simulations are forced by CM inputs to assess the spatial uncertainty......The question of which climate model bias correction methods and spatial scales for correction are optimal for both projecting future hydrological changes as well as removing initial model bias has so far received little attention. For 11 climate models (CMs), or GCM/RCM – Global/Regional Climate...... signals. The magnitude of spatial bias seen in precipitation inputs does not necessarily correspond to the magnitude of biases seen in hydrological outputs. Variables that integrate basin responses over time and space are more sensitive to mean spatial biases and less so on extremes. Hydrological...

Efficacy of attention bias modification using threat and appetitive stimuli: a meta-analytic review.

Science.gov (United States)

Beard, Courtney; Sawyer, Alice T; Hofmann, Stefan G

2012-12-01

Attention bias modification (ABM) protocols aim to modify attentional biases underlying many forms of pathology. Our objective was to conduct an effect size analysis of ABM across a wide range of samples and psychological problems. We conducted a literature search using PubMed, PsycInfo, and author searches to identify randomized studies that examined the effects of ABM on attention and subjective experiences. We identified 37 studies (41 experiments) totaling 2,135 participants who were randomized to training toward neutral, positive, threat, or appetitive stimuli or to a control condition. The effect size estimate for changes in attentional bias was large for the neutral versus threat comparisons (g=1.06), neutral versus appetitive (g=1.41), and neutral versus control comparisons (g=0.80), and small for positive versus control (g=0.24). The effects of ABM on attention bias were moderated by stimulus type (words vs. pictures) and sample characteristics (healthy vs. high symptomatology). Effect sizes of ABM on subjective experiences ranged from 0.03 to 0.60 for postchallenge outcomes, -0.31 to 0.51 for posttreatment, and were moderated by number of training sessions, stimulus type, and stimulus orientation (top/bottom vs. left/right). Fail-safe N calculations suggested that the effect size estimates were robust for the training effects on attentional biases, but not for the effect on subjective experiences. ABM studies using threat stimuli produced significant effects on attention bias across comparison conditions, whereas appetitive stimuli produced changes in attention only when comparing appetitive versus neutral conditions. ABM has a moderate and robust effect on attention bias when using threat stimuli. Further studies are needed to determine whether these effects are also robust when using appetitive stimuli and for affecting subjective experiences. Copyright © 2012. Published by Elsevier Ltd.

Potential Reporting Bias in Neuroimaging Studies of Sex Differences.

Science.gov (United States)

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

2018-04-17

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

Sex differences in event-related potentials and attentional biases to emotional facial stimuli.

Science.gov (United States)

Pfabigan, Daniela M; Lamplmayr-Kragl, Elisabeth; Pintzinger, Nina M; Sailer, Uta; Tran, Ulrich S

2014-01-01

Attentional processes play an important role in the processing of emotional information. Previous research reported attentional biases during stimulus processing in anxiety and depression. However, sex differences in the processing of emotional stimuli and higher prevalence rates of anxiety disorders among women, compared to men, suggest that attentional biases may also differ between the two sexes. The present study used a modified version of the dot probe task with happy, angry, and neutral facial stimuli to investigate the time course of attentional biases in healthy volunteers. Moreover, associations of attentional biases with alexithymia were examined on the behavioral and physiological level. Event-related potentials were measured while 21 participants (11 women) performed the task, utilizing also for the first time a difference wave approach in the analysis to highlight emotion-specific aspects. Women showed overall enhanced probe P1 amplitudes compared to men, in particular after rewarding facial stimuli. Using the difference wave approach, probe P1 amplitudes appeared specifically enhanced with regard to congruently presented happy facial stimuli among women, compared to men. Both methods yielded enhanced probe P1 amplitudes after presentation of the emotional stimulus in the left compared to the right visual hemifield. Probe P1 amplitudes correlated negatively with self-reported alexithymia, most of these correlations were only observable in women. Our results suggest that women orient their attention to a greater extent to facial stimuli than men and corroborate that alexithymia is a correlate of reduced emotional reactivity on a neuronal level. We recommend using a difference wave approach when addressing attentional processes of orientation and disengagement also in future studies.

Sex differences in event-related potentials and attentional biases to emotional facial stimuli

Directory of Open Access Journals (Sweden)

Daniela M. Pfabigan

2014-12-01

Full Text Available Attentional processes play an important role in the processing of emotional information. Previous research reported attentional biases during stimulus processing in anxiety and depression. However, sex differences in the processing of emotional stimuli and higher prevalence rates of anxiety disorders among women, compared to men, suggest that attentional biases may also differ between the two sexes. The present study used a modified version of the dot probe task with happy, angry, and neutral facial stimuli to investigate the time course of attentional biases in healthy volunteers. Moreover, associations of attentional biases with alexithymia were examined on the behavioral and physiological level. Event-related potentials were measured while 21 participants (11 women performed the task, utilizing also for the first time a difference wave approach in the analysis to highlight emotion-specific aspects. Women showed overall enhanced probe P1 amplitudes compared to men, in particular after rewarding facial stimuli. Under the difference wave approach, probe P1 amplitudes appeared specifically enhanced with regard to congruently presented happy facial stimuli among women, compared to men. Both methods yielded enhanced probe P1 amplitudes after presentation of the emotional stimulus in the left compared to the right visual hemifield. Probe P1 amplitudes correlated negatively with self-reported alexithymia, most of these correlations were only observable in women. Our results suggest that women orient their attention to a greater extent to facial stimuli than men and corroborate that alexithymia is a correlate of reduced emotional reactivity on a neuronal level. We recommend using a difference wave approach when addressing attentional processes of orientation and disengagement also in future studies.

Significant biases affecting abundance determinations

Science.gov (United States)

Wesson, Roger

2015-08-01

I have developed two highly efficient codes to automate analyses of emission line nebulae. The tools place particular emphasis on the propagation of uncertainties. The first tool, ALFA, uses a genetic algorithm to rapidly optimise the parameters of gaussian fits to line profiles. It can fit emission line spectra of arbitrary resolution, wavelength range and depth, with no user input at all. It is well suited to highly multiplexed spectroscopy such as that now being carried out with instruments such as MUSE at the VLT. The second tool, NEAT, carries out a full analysis of emission line fluxes, robustly propagating uncertainties using a Monte Carlo technique.Using these tools, I have found that considerable biases can be introduced into abundance determinations if the uncertainty distribution of emission lines is not well characterised. For weak lines, normally distributed uncertainties are generally assumed, though it is incorrect to do so, and significant biases can result. I discuss observational evidence of these biases. The two new codes contain routines to correctly characterise the probability distributions, giving more reliable results in analyses of emission line nebulae.

Robust global identifiability theory using potentials--Application to compartmental models.

Science.gov (United States)

Wongvanich, N; Hann, C E; Sirisena, H R

2015-04-01

This paper presents a global practical identifiability theory for analyzing and identifying linear and nonlinear compartmental models. The compartmental system is prolonged onto the potential jet space to formulate a set of input-output equations that are integrals in terms of the measured data, which allows for robust identification of parameters without requiring any simulation of the model differential equations. Two classes of linear and non-linear compartmental models are considered. The theory is first applied to analyze the linear nitrous oxide (N2O) uptake model. The fitting accuracy of the identified models from differential jet space and potential jet space identifiability theories is compared with a realistic noise level of 3% which is derived from sensor noise data in the literature. The potential jet space approach gave a match that was well within the coefficient of variation. The differential jet space formulation was unstable and not suitable for parameter identification. The proposed theory is then applied to a nonlinear immunological model for mastitis in cows. In addition, the model formulation is extended to include an iterative method which allows initial conditions to be accurately identified. With up to 10% noise, the potential jet space theory predicts the normalized population concentration infected with pathogens, to within 9% of the true curve. Copyright © 2015 Elsevier Inc. All rights reserved.

The bias of weighted dark matter halos from peak theory

CERN Document Server

Verde, Licia; Simpson, Fergus; Alvarez-Gaume, Luis; Heavens, Alan; Matarrese, Sabino

2014-01-01

We give an analytical form for the weighted correlation function of peaks in a Gaussian random field. In a cosmological context, this approach strictly describes the formation bias and is the main result here. Nevertheless, we show its validity and applicability to the evolved cosmological density field and halo field, using Gaussian random field realisations and dark matter N-body numerical simulations. Using this result from peak theory we compute the bias of peaks (and dark matter halos) and show that it reproduces results from the simulations at the ${\\mathcal O}(10\\%)$ level. Our analytical formula for the bias predicts a scale-dependent bias with two characteristics: a broad band shape which, however, is most affected by the choice of weighting scheme and evolution bias, and a more robust, narrow feature localised at the BAO scale, an effect that is confirmed in simulations. This scale-dependent bias smooths the BAO feature but, conveniently, does not move it. We provide a simple analytic formula to des...

Bias-corrected estimation in potentially mildly explosive autoregressive models

DEFF Research Database (Denmark)

Haufmann, Hendrik; Kruse, Robinson

This paper provides a comprehensive Monte Carlo comparison of different finite-sample bias-correction methods for autoregressive processes. We consider classic situations where the process is either stationary or exhibits a unit root. Importantly, the case of mildly explosive behaviour is studied...... that the indirect inference approach oers a valuable alternative to other existing techniques. Its performance (measured by its bias and root mean squared error) is balanced and highly competitive across many different settings. A clear advantage is its applicability for mildly explosive processes. In an empirical...

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-11-28

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

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

International Nuclear Information System (INIS)

Bieler, Noah S.; Hünenberger, Philippe H.

2014-01-01

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

Postactivation potentiation biases maximal isometric strength assessment.

Science.gov (United States)

Lima, Leonardo Coelho Rabello; Oliveira, Felipe Bruno Dias; Oliveira, Thiago Pires; Assumpção, Claudio de Oliveira; Greco, Camila Coelho; Cardozo, Adalgiso Croscato; Denadai, Benedito Sérgio

2014-01-01

Postactivation potentiation (PAP) is known to enhance force production. Maximal isometric strength assessment protocols usually consist of two or more maximal voluntary isometric contractions (MVCs). The objective of this study was to determine if PAP would influence isometric strength assessment. Healthy male volunteers (n = 23) performed two five-second MVCs separated by a 180-seconds interval. Changes in isometric peak torque (IPT), time to achieve it (tPTI), contractile impulse (CI), root mean square of the electromyographic signal during PTI (RMS), and rate of torque development (RTD), in different intervals, were measured. Significant increases in IPT (240.6 ± 55.7 N·m versus 248.9 ± 55.1 N·m), RTD (746 ± 152 N·m·s(-1) versus 727 ± 158 N·m·s(-1)), and RMS (59.1 ± 12.2% RMSMAX  versus 54.8 ± 9.4% RMSMAX) were found on the second MVC. tPTI decreased significantly on the second MVC (2373 ± 1200 ms versus 2784 ± 1226 ms). We conclude that a first MVC leads to PAP that elicits significant enhancements in strength-related variables of a second MVC performed 180 seconds later. If disconsidered, this phenomenon might bias maximal isometric strength assessment, overestimating some of these variables.

On writing legibly: Processing fluency systematically biases evaluations of handwritten material

OpenAIRE

Greifeneder, Rainer; Alt, Alexander; Bottenberg, Konstantin; Seele, Tim; Zelt, Sarah; Wagener, Dietrich

2010-01-01

Evaluations of handwritten essays or exams are often suspected of being biased, such as by mood states or individual predilections. Although most of these influences are unsystematic, at least one bias is problematic because it systematically affects evaluations of handwritten materials. Three experiments revealed that essays in legible as compared to less legible handwriting were evaluated more positively. This robust finding was related to a basic judgmental mechanism that builds on the flu...

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

Science.gov (United States)

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

2016-12-01

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

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

Science.gov (United States)

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

2016-01-01

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

Robustness of Structural Systems

DEFF Research Database (Denmark)

Canisius, T.D.G.; Sørensen, John Dalsgaard; Baker, J.W.

2007-01-01

The importance of robustness as a property of structural systems has been recognised following several structural failures, such as that at Ronan Point in 1968,where the consequenceswere deemed unacceptable relative to the initiating damage. A variety of research efforts in the past decades have...... attempted to quantify aspects of robustness such as redundancy and identify design principles that can improve robustness. This paper outlines the progress of recent work by the Joint Committee on Structural Safety (JCSS) to develop comprehensive guidance on assessing and providing robustness in structural...... systems. Guidance is provided regarding the assessment of robustness in a framework that considers potential hazards to the system, vulnerability of system components, and failure consequences. Several proposed methods for quantifying robustness are reviewed, and guidelines for robust design...

Eliminating Gender-Based Bias in Academic Medicine: More Than Naming the "Elephant in the Room".

Science.gov (United States)

Morgan, Anna U; Chaiyachati, Krisda H; Weissman, Gary E; Liao, Joshua M

2018-06-01

Gender-based discrimination and bias are widespread in professional settings, including academic medicine. Overt manifestations such as sexual harassment have long been identified but attention is only more recently turning towards subtler forms of bias, including inequity in promotion and compensation. Barriers to progress vary across institutions and include lack of awareness, inadequate training, poor informational transparency, and challenging power dynamics. We propose five solutions that the academic medical community can adopt to not only name, but also address, gender-based bias as the proverbial elephant in the room: definitively identify the systemic nature of the problem, prompt those with influence and power to advance a culture of equity, broadly incorporate evidence-based explicit anti-sexist training, increase transparency of information related to professional development and compensation, and use robust research methods to study the drivers and potential solutions of gender inequity within academic medicine. While implementing these proposals is no small task, doing so is an important step in helping the academic medical community become more just.

Cognitive bias in clinical practice – nurturing healthy skepticism among medical students

Directory of Open Access Journals (Sweden)

Bhatti A

2018-04-01

Full Text Available Alysha Bhatti Faculty of Medicine, Imperial College London, London, UK Abstract: Errors in clinical reasoning, known as cognitive biases, are implicated in a significant proportion of diagnostic errors. Despite this knowledge, little emphasis is currently placed on teaching cognitive psychology in the undergraduate medical curriculum. Understanding the origin of these biases and their impact on clinical decision making helps stimulate reflective practice. This article outlines some of the common types of cognitive biases encountered in the clinical setting as well as cognitive debiasing strategies. Medical educators should nurture healthy skepticism among medical students by raising awareness of cognitive biases and equipping them with robust tools to circumvent such biases. This will enable tomorrow’s doctors to improve the quality of care delivered, thus optimizing patient outcomes. Keywords: cognitive bias, diagnostic error, clinical decision making

Voluntary vs. compulsory student evaluation of clerkships: effect on validity and potential bias.

Science.gov (United States)

Aoun Bahous, Sola; Salameh, Pascale; Salloum, Angelique; Salameh, Wael; Park, Yoon Soo; Tekian, Ara

2018-01-05

Students evaluations of their learning experiences can provide a useful source of information about clerkship effectiveness in undergraduate medical education. However, low response rates in clerkship evaluation surveys remain an important limitation. This study examined the impact of increasing response rates using a compulsory approach on validity evidence. Data included 192 responses obtained voluntarily from 49 third-year students in 2014-2015, and 171 responses obtained compulsorily from 49 students in the first six months of the consecutive year at one medical school in Lebanon. Evidence supporting internal structure and response process validity was compared between the two administration modalities. The authors also tested for potential bias introduced by the use of the compulsory approach by examining students' responses to a sham item that was added to the last survey administration. Response rates increased from 56% in the voluntary group to 100% in the compulsory group (P two consecutive years. Testing for non-response bias in the voluntary group showed that females were more frequent responders in two clerkships. Testing for authority-induced bias revealed that students might complete the evaluation randomly without attention to content. While increasing response rates is often a policy requirement aimed to improve the credibility of ratings, using authority to enforce responses may not increase reliability and can raise concerns over the meaningfulness of the evaluation. Administrators are urged to consider not only response rates, but also representativeness and quality of responses in administering evaluation surveys.

A simple technique investigating baseline heterogeneity helped to eliminate potential bias in meta-analyses.

Science.gov (United States)

Hicks, Amy; Fairhurst, Caroline; Torgerson, David J

2018-03-01

To perform a worked example of an approach that can be used to identify and remove potentially biased trials from meta-analyses via the analysis of baseline variables. True randomisation produces treatment groups that differ only by chance; therefore, a meta-analysis of a baseline measurement should produce no overall difference and zero heterogeneity. A meta-analysis from the British Medical Journal, known to contain significant heterogeneity and imbalance in baseline age, was chosen. Meta-analyses of baseline variables were performed and trials systematically removed, starting with those with the largest t-statistic, until the I 2 measure of heterogeneity became 0%, then the outcome meta-analysis repeated with only the remaining trials as a sensitivity check. We argue that heterogeneity in a meta-analysis of baseline variables should not exist, and therefore removing trials which contribute to heterogeneity from a meta-analysis will produce a more valid result. In our example none of the overall outcomes changed when studies contributing to heterogeneity were removed. We recommend routine use of this technique, using age and a second baseline variable predictive of outcome for the particular study chosen, to help eliminate potential bias in meta-analyses. Copyright © 2017 Elsevier Inc. All rights reserved.

Placebo effect studies are susceptible to response bias and to other types of biases

DEFF Research Database (Denmark)

Hróbjartsson, Asbjørn; Kaptchuk, Ted J; Miller, Franklin G

2011-01-01

Investigations of the effect of placebo are often challenging to conduct and interpret. The history of placebo shows that assessment of its clinical significance has a real potential to be biased. We analyze and discuss typical types of bias in studies on placebo....

On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach

Science.gov (United States)

Chen, Bor-Sen; Lin, Ying-Po

2011-01-01

In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563

A comparative study of some robust ridge and liu estimators ...

African Journals Online (AJOL)

In multiple linear regression analysis, multicollinearity and outliers are two main problems. When multicollinearity exists, biased estimation techniques such as Ridge and Liu Estimators are preferable to Ordinary Least Square. On the other hand, when outliers exist in the data, robust estimators like M, MM, LTS and S ...

Potential fitting biases resulting from grouping data into variable width bins

International Nuclear Information System (INIS)

Towers, S.

2014-01-01

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

Potential fitting biases resulting from grouping data into variable width bins

Energy Technology Data Exchange (ETDEWEB)

Towers, S., E-mail: smtowers@asu.edu

2014-07-30

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.

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

DEFF Research Database (Denmark)

Hovy, Dirk; Plank, Barbara; Søgaard, Anders

2014-01-01

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

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

Science.gov (United States)

Burgoon, Judee K.; Blair, J. Pete; Strom, Renee E.

2008-01-01

In potentially deceptive situations, people rely on mental shortcuts to help process information. These heuristic judgments are often biased and result in inaccurate assessments of sender veracity. Four such biases--truth bias, visual bias, demeanor bias, and expectancy violation bias--were examined in a judgment experiment that varied nonverbal…

Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

Science.gov (United States)

Cid, Jaime A; von Davier, Alina A

2015-05-01

Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

Speed Biases With Real-Life Video Clips

Directory of Open Access Journals (Sweden)

Federica Rossi

2018-03-01

Full Text Available We live almost literally immersed in an artificial visual world, especially motion pictures. In this exploratory study, we asked whether the best speed for reproducing a video is its original, shooting speed. By using adjustment and double staircase methods, we examined speed biases in viewing real-life video clips in three experiments, and assessed their robustness by manipulating visual and auditory factors. With the tested stimuli (short clips of human motion, mixed human-physical motion, physical motion and ego-motion, speed underestimation was the rule rather than the exception, although it depended largely on clip content, ranging on average from 2% (ego-motion to 32% (physical motion. Manipulating display size or adding arbitrary soundtracks did not modify these speed biases. Estimated speed was not correlated with estimated duration of these same video clips. These results indicate that the sense of speed for real-life video clips can be systematically biased, independently of the impression of elapsed time. Measuring subjective visual tempo may integrate traditional methods that assess time perception: speed biases may be exploited to develop a simple, objective test of reality flow, to be used for example in clinical and developmental contexts. From the perspective of video media, measuring speed biases may help to optimize video reproduction speed and validate “natural” video compression techniques based on sub-threshold temporal squeezing.

Local linear density estimation for filtered survival data, with bias correction

DEFF Research Database (Denmark)

Nielsen, Jens Perch; Tanggaard, Carsten; Jones, M.C.

2009-01-01

it comes to exposure robustness, and a simple alternative weighting is to be preferred. Indeed, this weighting has, effectively, to be well chosen in a 'pilot' estimator of the survival function as well as in the main estimator itself. We also investigate multiplicative and additive bias-correction methods...... within our framework. The multiplicative bias-correction method proves to be the best in a simulation study comparing the performance of the considered estimators. An example concerning old-age mortality demonstrates the importance of the improvements provided....

Local Linear Density Estimation for Filtered Survival Data with Bias Correction

DEFF Research Database (Denmark)

Tanggaard, Carsten; Nielsen, Jens Perch; Jones, M.C.

it comes to exposure robustness, and a simple alternative weighting is to be preferred. Indeed, this weighting has, effectively, to be well chosen in a ‘pilot' estimator of the survival function as well as in the main estimator itself. We also investigate multiplicative and additive bias correction methods...... within our framework. The multiplicative bias correction method proves to be best in a simulation study comparing the performance of the considered estimators. An example concerning old age mortality demonstrates the importance of the improvements provided....

Debiasing egocentrism and optimism biases in repeated competitions

Directory of Open Access Journals (Sweden)

Jason P. Rose

2012-11-01

Full Text Available When judging their likelihood of success in competitive tasks, people tend to be overoptimistic for easy tasks and overpessimistic for hard tasks (the shared circumstance effect; SCE. Previous research has shown that feedback and experience from repeated-play competitions has a limited impact on SCEs. However, in this paper, we suggest that competitive situations, in which the shared difficulty or easiness of the task is more transparent, will be more amenable to debiasing via repeated play. Pairs of participants competed in, made predictions about, and received feedback on, multiple rounds of a throwing task involving both easy- and hard-to-aim objects. Participants initially showed robust SCEs, but they also showed a significant reduction in bias after only one round of feedback. These and other results support a more positive view (than suggested from past research on the potential for SCEs to be debiased through outcome feedback.

On a Robust MaxEnt Process Regression Model with Sample-Selection

Directory of Open Access Journals (Sweden)

Hea-Jung Kim

2018-04-01

Full Text Available In a regression analysis, a sample-selection bias arises when a dependent variable is partially observed as a result of the sample selection. This study introduces a Maximum Entropy (MaxEnt process regression model that assumes a MaxEnt prior distribution for its nonparametric regression function and finds that the MaxEnt process regression model includes the well-known Gaussian process regression (GPR model as a special case. Then, this special MaxEnt process regression model, i.e., the GPR model, is generalized to obtain a robust sample-selection Gaussian process regression (RSGPR model that deals with non-normal data in the sample selection. Various properties of the RSGPR model are established, including the stochastic representation, distributional hierarchy, and magnitude of the sample-selection bias. These properties are used in the paper to develop a hierarchical Bayesian methodology to estimate the model. This involves a simple and computationally feasible Markov chain Monte Carlo algorithm that avoids analytical or numerical derivatives of the log-likelihood function of the model. The performance of the RSGPR model in terms of the sample-selection bias correction, robustness to non-normality, and prediction, is demonstrated through results in simulations that attest to its good finite-sample performance.

Cognitive Bias in Systems Verification

Science.gov (United States)

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.

Biases in GNSS-Data Processing

Science.gov (United States)

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.

Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study.

Science.gov (United States)

Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P

2014-06-26

To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.

Hindsight bias: how knowledge and heuristics affect our reconstruction of the past.

Science.gov (United States)

Hertwig, Ralph; Fanselow, Carola; Hoffrage, Ulrich

2003-01-01

Once people know the outcome of an event, they tend to overestimate what could have been anticipated in foresight. Although typically considered to be a robust phenomenon, this hindsight bias is subject to moderating circumstances. In their meta-analysis, Christensen-Szalanski and Willham (1991) observed that the more experience people have with the task under consideration, the smaller is the resulting hindsight bias. This observation is one benchmark against which the explanatory power of process models of hindsight bias can be measured. Therefore, we used it to put the recently proposed RAFT model (Hoffrage, Hertwig, & Gigerenzer, 2000) to another test. Our findings were consistent with the "expertise effect." Specifically, we observed-using computer simulations of the RAFT model-that the more comprehensive people's knowledge is in foresight, the smaller is their hindsight bias. In addition, we made two counterintuitive observations: First, the relation between foresight knowledge and hindsight bias appears to be independent of how knowledge is processed. Second, even if foresight knowledge is false, it can reduce hindsight bias. We conclude with a discussion of the functional value of hindsight bias.

Anisotropic magnetoresistance and anomalous Nernst effect in exchange biased permalloy/(1 0 0) NiO single-crystal

Energy Technology Data Exchange (ETDEWEB)

Holanda, J., E-mail: joseholanda@df.ufpe.br; Maior, D.S.; Azevedo, A.; Rezende, S.M.

2017-06-15

Highlights: • We have investigated the anisotropic magnetoresistance (AMR) and the anomalous Nernst effect (ANE) in an exchange-biased bilayer Py/(100) NiO single-Crystal. • The shift of the hysteresis loop, measured with the different techniques, yield approximately the same value of H{sub EB}. • In spite of the measurement techniques be based in different physical phenomena, our results confirm the robustness of the exchange anisotropy at the Py/NiO interface. • The strength of the anomalous Nernst effect for the exchange-biased permalloy film is compared to values measured in non biased films. - Abstract: We have investigated the anisotropic magnetoresistance (AMR) and the anomalous Nernst effect (ANE) in an exchange-biased bilayer consisting of a thin film of permalloy deposited on a single crystal antiferromagnetic NiO (1 0 0). The exchange bias field (H{sub EB}) value was obtained by means of AMR, ANE and magnetization hysteresis measurements. The shift of the hysteresis loop, measured with the three different techniques, yield approximately the same value of H{sub EB.} In spite of the measurement techniques be based in different physical phenomena, our results confirm the robustness of the exchange anisotropy at the Py/NiO interface. The strength of the anomalous Nernst effect for the exchange-biased permalloy film is compared to values measured in non biased films.

Good practices for quantitative bias analysis.

Science.gov (United States)

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

2014-12-01

more widespread use of bias analysis to estimate the potential magnitude and direction of biases, as well as the uncertainty in estimates potentially influenced by the biases. © The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

A robust nonlinear filter for image restoration.

Science.gov (United States)

Koivunen, V

1995-01-01

A class of nonlinear regression filters based on robust estimation theory is introduced. The goal of the filtering is to recover a high-quality image from degraded observations. Models for desired image structures and contaminating processes are employed, but deviations from strict assumptions are allowed since the assumptions on signal and noise are typically only approximately true. The robustness of filters is usually addressed only in a distributional sense, i.e., the actual error distribution deviates from the nominal one. In this paper, the robustness is considered in a broad sense since the outliers may also be due to inappropriate signal model, or there may be more than one statistical population present in the processing window, causing biased estimates. Two filtering algorithms minimizing a least trimmed squares criterion are provided. The design of the filters is simple since no scale parameters or context-dependent threshold values are required. Experimental results using both real and simulated data are presented. The filters effectively attenuate both impulsive and nonimpulsive noise while recovering the signal structure and preserving interesting details.

Awareness and minimisation of systematic bias in research.

LENUS (Irish Health Repository)

Malone, Helen

2014-03-01

A major goal of nursing and midwifery is the delivery of evidence-based practice. Consequently, it is essential for the quality and safety of patient\\/client care that policy makers, educators and practitioners are aware of the presence of potential systematic bias in research practice and research publications so that only sound evidence translates into practice. The main aim of this paper is to highlight the need for ongoing awareness of the potential presence of systematic bias in research practice, to explore commonly reported types of systematic bias and to report some methods that can be applied to minimise systematic bias in research.

Nonresponse bias in randomized controlled experiments in criminology: Putting the Queensland Community Engagement Trial (QCET) under a microscope.

Science.gov (United States)

Antrobus, Emma; Elffers, Henk; White, Gentry; Mazerolle, Lorraine

2013-01-01

The goal of this article is to examine whether or not the results of the Queensland Community Engagement Trial (QCET)-a randomized controlled trial that tested the impact of procedural justice policing on citizen attitudes toward police-were affected by different types of nonresponse bias. We use two methods (Cochrane and Elffers methods) to explore nonresponse bias: First, we assess the impact of the low response rate by examining the effects of nonresponse group differences between the experimental and control conditions and pooled variance under different scenarios. Second, we assess the degree to which item response rates are influenced by the control and experimental conditions. Our analysis of the QCET data suggests that our substantive findings are not influenced by the low response rate in the trial. The results are robust even under extreme conditions, and statistical significance of the results would only be compromised in cases where the pooled variance was much larger for the nonresponse group and the difference between experimental and control conditions was greatly diminished. We also find that there were no biases in the item response rates across the experimental and control conditions. RCTs that involve field survey responses-like QCET-are potentially compromised by low response rates and how item response rates might be influenced by the control or experimental conditions. Our results show that the QCET results were not sensitive to the overall low response rate across the experimental and control conditions and the item response rates were not significantly different across the experimental and control groups. Overall, our analysis suggests that the results of QCET are robust and any biases in the survey responses do not significantly influence the main experimental findings.

Information visualisation for science and policy: engaging users and avoiding bias.

Science.gov (United States)

McInerny, Greg J; Chen, Min; Freeman, Robin; Gavaghan, David; Meyer, Miriah; Rowland, Francis; Spiegelhalter, David J; Stefaner, Moritz; Tessarolo, Geizi; Hortal, Joaquin

2014-03-01

Visualisations and graphics are fundamental to studying complex subject matter. However, beyond acknowledging this value, scientists and science-policy programmes rarely consider how visualisations can enable discovery, create engaging and robust reporting, or support online resources. Producing accessible and unbiased visualisations from complicated, uncertain data requires expertise and knowledge from science, policy, computing, and design. However, visualisation is rarely found in our scientific training, organisations, or collaborations. As new policy programmes develop [e.g., the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES)], we need information visualisation to permeate increasingly both the work of scientists and science policy. The alternative is increased potential for missed discoveries, miscommunications, and, at worst, creating a bias towards the research that is easiest to display. Copyright © 2014 Elsevier Ltd. All rights reserved.

Attention bias in earthquake-exposed survivors: an event-related potential study.

Science.gov (United States)

Zhang, Yan; Kong, Fanchang; Han, Li; Najam Ul Hasan, Abbasi; Chen, Hong

2014-12-01

The Chinese Wenchuan earthquake, which happened on the 28th of May in 2008, may leave deep invisible scars in individuals. China has a large number of children and adolescents, who tend to be most vulnerable because they are in an early stage of human development and possible post-traumatic psychological distress may have a life-long consequence. Trauma survivors without post-traumatic stress disorder (PTSD) have received little attention in previous studies, especially in event-related potential (ERP) studies. We compared the attention bias to threat stimuli between the earthquake-exposed group and the control group in a masked version of the dot probe task. The target probe presented at the same space location consistent with earthquake-related words was the congruent trial, while in the space location of neutral words was the incongruent trial. Thirteen earthquake-exposed middle school students without PTSD and 13 matched controls were included in this investigation. The earthquake-exposed group showed significantly faster RTs to congruent trials than to incongruent trials. The earthquake-exposed group produced significantly shorter C1 and P1 latencies and larger C1, P1 and P2 amplitudes than the control group. In particular, enhanced P1 amplitude to threat stimuli was observed in the earthquake-exposed group. These findings are in agreement with the prediction that earthquake-exposed survivors have an attention bias to threat stimuli. The traumatic event had a much greater effect on earthquake-exposed survivors even if they showed no PTSD symptoms than individuals in the controls. These results will provide neurobiological evidences for effective intervention and prevention to post-traumatic mental problems. Copyright © 2014 Elsevier B.V. All rights reserved.

Heterogeneous Causal Effects and Sample Selection Bias

DEFF Research Database (Denmark)

Breen, Richard; Choi, Seongsoo; Holm, Anders

2015-01-01

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

The mediating role of state maladaptive emotion regulation in the relation between social anxiety symptoms and self-evaluation bias.

Science.gov (United States)

Sarfan, Laurel D; Cody, Meghan W; Clerkin, Elise M

2018-03-16

Although social anxiety symptoms are robustly linked to biased self-evaluations across time, the mechanisms of this relation remain unclear. The present study tested three maladaptive emotion regulation strategies - state post-event processing, state experiential avoidance, and state expressive suppression - as potential mediators of this relation. Undergraduate participants (N = 88; 61.4% Female) rated their social skill in an impromptu conversation task and then returned to the laboratory approximately two days later to evaluate their social skill in the conversation again. Consistent with expectations, state post-event processing and state experiential avoidance mediated the relation between social anxiety symptoms and worsening self-evaluations of social skill (controlling for research assistant evaluations), particularly for positive qualities (e.g. appeared confident, demonstrated social skill). State expressive suppression did not mediate the relation between social anxiety symptoms and changes in self-evaluation bias across time. These findings highlight the role that spontaneous, state experiential avoidance and state post-event processing may play in the relation between social anxiety symptoms and worsening self-evaluation biases of social skill across time.

Electronic transport in Thue-Morse gapped graphene superlattice under applied bias

Science.gov (United States)

Wang, Mingjing; Zhang, Hongmei; Liu, De

2018-04-01

We investigate theoretically the electronic transport properties of Thue-Morse gapped graphene superlattice under an applied electric field. The results indicate that the combined effect of the band gap and the applied bias breaks the angular symmetry of the transmission coefficient. The zero-averaged wave-number gap can be greatly modulated by the band gap and the applied bias, but its position is robust against change of the band gap. Moreover, the conductance and the Fano factor are strongly dependent not only on the Fermi energy but also on the band gap and the applied bias. In the vicinity of the new Dirac point, the minimum value of the conductance obviously decreases and the Fano factor gradually forms a Poissonian value plateau with increasing of the band gap.

Biased limiter experiments on text

International Nuclear Information System (INIS)

Phillips, P.E.; Wootton, A.J.; Rowan, W.L.; Ritz, C.P.; Rhodes, T.L.; Bengtson, R.D.; Hodge, W.L.; Durst, R.D.; McCool, S.C.; Richards, B.; Gentle, K.W.; Schoch, P.; Forster, J.C.; Hickok, R.L.; Evans, T.E.

1987-01-01

Experiments using an electrically biased limiter have been performed on the Texas Experimental Tokamak (TEXT). A small movable limiter is inserted past the main poloidal ring limiter (which is electrically connected to the vacuum vessel) and biased at V Lim with respect to it. The floating potential, plasma potential and shear layer position can be controlled. With vertical strokeV Lim vertical stroke ≥ 50 V the plasma density increases. For V Lim Lim > 0 the results obtained are inconclusive. Variation of V Lim changes the electrostatic turbulence which may explain the observed total flux changes. (orig.)

First principles molecular dynamics of metal/water interfaces under bias potential

Science.gov (United States)

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

2014-03-01

Understanding the interaction of the water-metal system at an atomic level is extremely important in electrocatalysts for fuel cells, photocatalysis among other systems. The question of the interface energetics involves a detailed study of the nature of the interactions between water-water and water-substrate. A first principles description of all components of the system is the most appropriate methodology in order to advance understanding of electrochemically processes. In this work we describe, using first principles molecular dynamics simulations, the dynamics of a combined surface(Au and Pd)/water system both in the presence and absence of an external bias potential applied to the electrodes, as one would come across in electrochemistry. This is accomplished using a combination of density functional theory (DFT) and non-equilibrium Green's functions methods (NEGF), thus accounting for the fact that one is dealing with an out-of-equilibrium open system, with and without van der Waals interactions. DOE Early Career Award No. DE-SC0003871.

Incidental encoding of emotional pictures: affective bias studied through event related brain potentials.

Science.gov (United States)

Tapia, Manuel; Carretié, Luis; Sierra, Benjamín; Mercado, Francisco

2008-06-01

Emotional stimuli are better remembered than neutral stimuli. Most of the studies taking into account this emotional bias refer to explicit memory, use behavioral measures of the recall and predict better recall of negative stimuli. The few studies taking into account implicit memory and the valence emotional dimension are inconclusive on the effect of the stimulus' emotional valence. In the present study, 120 pictures (30 positive, 30 negative, 30 relaxing and 30 neutral) were shown to, and assessed by, 28 participants (study phase). Subsequently, event related brain potentials (ERPs) were recorded during the presentation of 120 new (shown for the first time) and 120 old (already shown in the study phase) pictures (test phase). No explicit instructions or clues related to recovery were given to participants, and a distractor task was employed, in order to maintain implicit the memory assessment. As expected from other studies' data, our results showed that old stimuli elicited an enhanced late positive component 450 ms after stimulus onset (repetition effect). Moreover, this effect was modulated by the stimuli's emotional valence, since the most positively valenced stimuli were associated with a decreased repetition effect with respect to the most negatively valenced stimuli. This effect was located at ventromedial prefrontal cortex. These results suggest the existence of a valence-mediated bias in implicit memory.

A Robust Mass Estimator for Dark Matter Subhalo Perturbations in Strong Gravitational Lenses

Energy Technology Data Exchange (ETDEWEB)

Minor, Quinn E. [Department of Science, Borough of Manhattan Community College, City University of New York, New York, NY 10007 (United States); Kaplinghat, Manoj [Department of Physics and Astronomy, University of California, Irvine CA 92697 (United States); Li, Nan [Department of Astronomy and Astrophysics, The University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637 (United States)

2017-08-20

A few dark matter substructures have recently been detected in strong gravitational lenses through their perturbations of highly magnified images. We derive a characteristic scale for lensing perturbations and show that they are significantly larger than the perturber’s Einstein radius. We show that the perturber’s projected mass enclosed within this radius, scaled by the log-slope of the host galaxy’s density profile, can be robustly inferred even if the inferred density profile and tidal radius of the perturber are biased. We demonstrate the validity of our analytic derivation using several gravitational lens simulations where the tidal radii and the inner log-slopes of the density profile of the perturbing subhalo are allowed to vary. By modeling these simulated data, we find that our mass estimator, which we call the effective subhalo lensing mass, is accurate to within about 10% or smaller in each case, whereas the inferred total subhalo mass can potentially be biased by nearly an order of magnitude. We therefore recommend that the effective subhalo lensing mass be reported in future lensing reconstructions, as this will allow for a more accurate comparison with the results of dark matter simulations.

[Correlation of codon biases and potential secondary structures with mRNA translation efficiency in unicellular organisms].

Science.gov (United States)

Vladimirov, N V; Likhoshvaĭ, V A; Matushkin, Iu G

2007-01-01

Gene expression is known to correlate with degree of codon bias in many unicellular organisms. However, such correlation is absent in some organisms. Recently we demonstrated that inverted complementary repeats within coding DNA sequence must be considered for proper estimation of translation efficiency, since they may form secondary structures that obstruct ribosome movement. We have developed a program for estimation of potential coding DNA sequence expression in defined unicellular organism using its genome sequence. The program computes elongation efficiency index. Computation is based on estimation of coding DNA sequence elongation efficiency, taking into account three key factors: codon bias, average number of inverted complementary repeats, and free energy of potential stem-loop structures formed by the repeats. The influence of these factors on translation is numerically estimated. An optimal proportion of these factors is computed for each organism individually. Quantitative translational characteristics of 384 unicellular organisms (351 bacteria, 28 archaea, 5 eukaryota) have been computed using their annotated genomes from NCBI GenBank. Five potential evolutionary strategies of translational optimization have been determined among studied organisms. A considerable difference of preferred translational strategies between Bacteria and Archaea has been revealed. Significant correlations between elongation efficiency index and gene expression levels have been shown for two organisms (S. cerevisiae and H. pylori) using available microarray data. The proposed method allows to estimate numerically the coding DNA sequence translation efficiency and to optimize nucleotide composition of heterologous genes in unicellular organisms. http://www.mgs.bionet.nsc.ru/mgs/programs/eei-calculator/.

Assessing the utility of frequency dependent nudging for reducing biases in biogeochemical models

Science.gov (United States)

Lagman, Karl B.; Fennel, Katja; Thompson, Keith R.; Bianucci, Laura

2014-09-01

Bias errors, resulting from inaccurate boundary and forcing conditions, incorrect model parameterization, etc. are a common problem in environmental models including biogeochemical ocean models. While it is important to correct bias errors wherever possible, it is unlikely that any environmental model will ever be entirely free of such errors. Hence, methods for bias reduction are necessary. A widely used technique for online bias reduction is nudging, where simulated fields are continuously forced toward observations or a climatology. Nudging is robust and easy to implement, but suppresses high-frequency variability and introduces artificial phase shifts. As a solution to this problem Thompson et al. (2006) introduced frequency dependent nudging where nudging occurs only in prescribed frequency bands, typically centered on the mean and the annual cycle. They showed this method to be effective for eddy resolving ocean circulation models. Here we add a stability term to the previous form of frequency dependent nudging which makes the method more robust for non-linear biological models. Then we assess the utility of frequency dependent nudging for biological models by first applying the method to a simple predator-prey model and then to a 1D ocean biogeochemical model. In both cases we only nudge in two frequency bands centered on the mean and the annual cycle, and then assess how well the variability in higher frequency bands is recovered. We evaluate the effectiveness of frequency dependent nudging in comparison to conventional nudging and find significant improvements with the former.

Systematic Biases in Weak Lensing Cosmology with the Dark Energy Survey

Energy Technology Data Exchange (ETDEWEB)

Samuroff, Simon [Manchester U.

2017-01-01

impact to be subdominant to statistical error at the! current level of precision. Another major uncertainity in shear cosmology is the accuracy of our ensemble redshift distributions. Chapter 5 presents a numerical investigation into the combined constraining power of cosmic shear, galaxy clustering and their cross-correlation in DES Y1, and the potential for internal calibration of redshift errors. Introducing a moderate uniform bias into the redshift distributions used to model the weak lensing (WL) galaxies is shown to produce a $> 2\\sigma$ bias in $S_8$. We demonstrate that this cosmological bias can be eliminated by marginalising over redshift error nuisance parameters. Strikingly, the cosmological constraint of the combined dataset is largely undiminished by the loss of prior information on the WL distributions. We demonstrate that this implicit self-calibration is the result of complementary degeneracy directions in the combined data. In Chapter 6 we present the preliminary results of an investigation into galaxy intrin sic alignments. Using the DES Y1 data, we show a clear dependence in alignment amplitude on galaxy type, in agreement with previous results. We subject these findings to a series of initial robustness tests. We conclude with a short overview of the work presented, and discuss prospects for the future.

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

Science.gov (United States)

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.

Approach-Induced Biases in Human Information Sampling.

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Laurence T Hunt

2016-11-01

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

The endowment effect, status quo bias and loss aversion: rational alternative explanation

NARCIS (Netherlands)

Dupont, D.Y.; Lee, Gabriel S.

2002-01-01

The endowment effect, status quo bias, and loss aversion are robust and well documented results from experimental psychology. They introduce a wedge between the prices at which one is willing to sell or buy a good. The objective of this paper is to address this wedge. We show that the presence of

The endowment effect, status quo bias and loss aversion : rational alternative explanation

NARCIS (Netherlands)

Dupont, D.Y.; Lee, G.S.

2002-01-01

The endowment effect, status quo bias, and loss aversion are robust and well documented results from experimental psychology. They introduce a wedge between the prices at which one is willing to sell or buy a good. The objective of this paper is to address this wedge. We show that the presence of

The impact of individual biases on consensus formation.

Directory of Open Access Journals (Sweden)

Marta Sales-Pardo

Full Text Available Social groups of interacting agents display an ability to coordinate in the absence of a central authority, a phenomenon that has been recently amplified by the widespread availability of social networking technologies. Models of opinion formation in a population of agents have proven a very useful tool to investigate these phenomena that arise independently of the heterogeneities across individuals and can be used to identify the factors that determine whether widespread consensus on an initial small majority is reached. Recently, we introduced a model in which individual agents can have conservative and partisan biases. Numerical simulations for finite populations showed that while the inclusion of conservative agents in a population enhances the population's efficiency in reaching consensus on the initial majority opinion, even a small fraction of partisans leads the population to converge on the opinion initially held by a minority. To further understand the mechanisms leading to our previous numerical results, we investigate analytically the noise driven transition from a regime in which the population reaches a majority consensus (efficient, to a regime in which the population settles in deadlock (non-efficient. We show that the mean-field solution captures what we observe in model simulations. Populations of agents with no opinion bias show a continuous transition to a deadlock regime, while populations with an opinion bias, show a discontinuous transition between efficient and partisan regimes. Furthermore, the analytical solution reveals that populations with an increasing fraction of conservative agents are more robust against noise than a population of naive agents because in the efficient regime there are relatively more conservative than naive agents holding the majority opinion. In contrast, populations with partisan agents are less robust to noise with an increasing fraction of partisans, because in the efficient regime there are

National South African HIV prevalence estimates robust despite substantial test non-participation

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Guy Harling

2017-07-01

Full Text Available Background. South African (SA national HIV seroprevalence estimates are of crucial policy relevance in the country, and for the worldwide HIV response. However, the most recent nationally representative HIV test survey in 2012 had 22% test non-participation, leaving the potential for substantial bias in current seroprevalence estimates, even after controlling for selection on observed factors. Objective. To re-estimate national HIV prevalence in SA, controlling for bias due to selection on both observed and unobserved factors in the 2012 SA National HIV Prevalence, Incidence and Behaviour Survey. Methods. We jointly estimated regression models for consent to test and HIV status in a Heckman-type bivariate probit framework. As selection variable, we used assigned interviewer identity, a variable known to predict consent but highly unlikely to be associated with interviewees’ HIV status. From these models, we estimated the HIV status of interviewed participants who did not test. Results. Of 26 710 interviewed participants who were invited to test for HIV, 21.3% of females and 24.3% of males declined. Interviewer identity was strongly correlated with consent to test for HIV; declining a test was weakly associated with HIV serostatus. Our HIV prevalence estimates were not significantly different from those using standard methods to control for bias due to selection on observed factors: 15.1% (95% confidence interval (CI 12.1 - 18.6 v. 14.5% (95% CI 12.8 - 16.3 for 15 - 49-year-old males; 23.3% (95% CI 21.7 - 25.8 v. 23.2% (95% CI 21.3 - 25.1 for 15 - 49-year-old females. Conclusion. The most recent SA HIV prevalence estimates are robust under the strongest available test for selection bias due to missing data. Our findings support the reliability of inferences drawn from such data.

Tax-Rate Biases in Tax-Planning Decisions: Experimental Evidence

OpenAIRE

Amberger, Harald; Eberhartinger, Eva; Kasper, Helmut

2016-01-01

Contrary to standard economic theory, recent empirical findings suggest that firms do not always engage in economically optimal tax planning. We conduct a laboratory experiment and find robust evidence that decision biases offer a behavioral explanation for suboptimal tax planning. When facing time pressure in an intra-group cross-border financing decision, subjects apply heuristics based on the salience of statutory tax rates. This stirs decision makers to underestimate the effects of tax-ba...

Bias changing molecule–lead couple and inducing low bias negative differential resistance for electrons acceptor predicted by first-principles study

International Nuclear Information System (INIS)

Min, Y.; Fang, J.H.; Zhong, C.G.; Dong, Z.C.; Zhao, Z.Y.; Zhou, P.X.; Yao, K.L.

2015-01-01

A first-principles study of the transport properties of 3,13-dimercaptononacene–6,21-dione molecule sandwiched between two gold leads is reported. The strong effect of negative differential resistance with large peak-to-valley ratio of 710% is present under low bias. We found that bias can change molecule–lead couple and induce low bias negative differential resistance for electrons acceptor, which may promise the potential applications in molecular devices with low-power dissipation in the future. - Highlights: • Acceptor is constructed to negative differential resistor (NDR). • NDR effect is present under low bias. • Bias change molecule–lead couple and induce NDR effect

Robust spin transfer torque in antiferromagnetic tunnel junctions

KAUST Repository

Saidaoui, Hamed Ben Mohamed

2017-04-18

We theoretically study the current-induced spin torque in antiferromagnetic tunnel junctions, composed of two semi-infinite antiferromagnetic layers separated by a tunnel barrier, in both clean and disordered regimes. We find that the torque enabling electrical manipulation of the Néel antiferromagnetic order parameter is out of plane, ∼n×p, while the torque competing with the antiferromagnetic exchange is in plane, ∼n×(p×n). Here, p and n are the Néel order parameter direction of the reference and free layers, respectively. Their bias dependence shows behavior similar to that in ferromagnetic tunnel junctions, the in-plane torque being mostly linear in bias, while the out-of-plane torque is quadratic. Most importantly, we find that the spin transfer torque in antiferromagnetic tunnel junctions is much more robust against disorder than that in antiferromagnetic metallic spin valves due to the tunneling nature of spin transport.

Music for a Brighter World: Brightness Judgment Bias by Musical Emotion.

Science.gov (United States)

Bhattacharya, Joydeep; Lindsen, Job P

2016-01-01

A prevalent conceptual metaphor is the association of the concepts of good and evil with brightness and darkness, respectively. Music cognition, like metaphor, is possibly embodied, yet no study has addressed the question whether musical emotion can modulate brightness judgment in a metaphor consistent fashion. In three separate experiments, participants judged the brightness of a grey square that was presented after a short excerpt of emotional music. The results of Experiment 1 showed that short musical excerpts are effective emotional primes that cross-modally influence brightness judgment of visual stimuli. Grey squares were consistently judged as brighter after listening to music with a positive valence, as compared to music with a negative valence. The results of Experiment 2 revealed that the bias in brightness judgment does not require an active evaluation of the emotional content of the music. By applying a different experimental procedure in Experiment 3, we showed that this brightness judgment bias is indeed a robust effect. Altogether, our findings demonstrate a powerful role of musical emotion in biasing brightness judgment and that this bias is aligned with the metaphor viewpoint.

Robust power spectral estimation for EEG data.

Science.gov (United States)

Melman, Tamar; Victor, Jonathan D

2016-08-01

Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. Using the multitaper method (Thomson, 1982) as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigating d-cycloserine as a potential pharmacological enhancer of an emotional bias learning procedure.

Science.gov (United States)

Woud, Marcella L; Blackwell, Simon E; Steudte-Schmiedgen, Susann; Browning, Michael; Holmes, Emily A; Harmer, Catherine J; Margraf, Jürgen; Reinecke, Andrea

2018-05-01

The partial N-methyl-D-aspartate receptor agonist d-cycloserine may enhance psychological therapies. However, its exact mechanism of action is still being investigated. Cognitive bias modification techniques allow isolation of cognitive processes and thus investigation of how they may be affected by d-cycloserine. We used a cognitive bias modification paradigm targeting appraisals of a stressful event, Cognitive Bias Modification-Appraisal, to investigate whether d-cycloserine enhanced the modification of appraisal, and whether it caused greater reduction in indices of psychopathology. Participants received either 250 mg of d-cycloserine ( n=19) or placebo ( n=19). As a stressor task, participants recalled a negative life event, followed by positive Cognitive Bias Modification-Appraisal training. Before and after Cognitive Bias Modification-Appraisal, appraisals and indices of psychopathology related to the stressor were assessed. Cognitive Bias Modification-Appraisal successfully modified appraisals, but d-cycloserine did not affect appraisals post-training. There were no post-training group differences in frequency of intrusions. Interestingly, d-cycloserine led to a greater reduction in distress and impact on state mood from recalling the event, and lower distress post-training was associated with fewer intrusions. Therefore, d-cycloserine may affect emotional reactivity to recalling a negative event when combined with induction of a positive appraisal style, but via a mechanism other than enhanced learning of the appraisal style.

Bias During the Evaluation of Animal Studies?

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Andrew Knight

2012-02-01

Full Text Available My recent book entitled The Costs and Benefits of Animal Experiments seeks to answer a key question within animal ethics, namely: is animal experimentation ethically justifiable? Or, more precisely, is it justifiable within the utilitarian cost:benefit framework that fundamentally underpins most regulations governing animal experimentation? To answer this question I reviewed more than 500 scientific publications describing animal studies, animal welfare impacts, and alternative research, toxicity testing and educational methodologies. To minimise bias I focused primarily on large-scale systematic reviews that had examined the human clinical and toxicological utility of animal studies. Despite this, Dr. Susanne Prankel recently reviewed my book in this journal, essentially accusing me of bias. However, she failed to provide any substantive evidence to refute my conclusions, let alone evidence of similar weight to that on which they are based. Those conclusions are, in fact, firmly based on utilitarian ethical reasoning, informed by scientific evidence of considerable strength, and I believe they are robust.

Bias During the Evaluation of Animal Studies?

Science.gov (United States)

Knight, Andrew

2012-02-23

My recent book entitled The Costs and Benefits of Animal Experiments seeks to answer a key question within animal ethics, namely: is animal experimentation ethically justifiable? Or, more precisely, is it justifiable within the utilitarian cost:benefit framework that fundamentally underpins most regulations governing animal experimentation? To answer this question I reviewed more than 500 scientific publications describing animal studies, animal welfare impacts, and alternative research, toxicity testing and educational methodologies. To minimise bias I focused primarily on large-scale systematic reviews that had examined the human clinical and toxicological utility of animal studies. Despite this, Dr. Susanne Prankel recently reviewed my book in this journal, essentially accusing me of bias. However, she failed to provide any substantive evidence to refute my conclusions, let alone evidence of similar weight to that on which they are based. Those conclusions are, in fact, firmly based on utilitarian ethical reasoning, informed by scientific evidence of considerable strength, and I believe they are robust.

Response of the plasma to the size of an anode electrode biased near the plasma potential

International Nuclear Information System (INIS)

Barnat, E. V.; Laity, G. R.; Baalrud, S. D.

2014-01-01

As the size of a positively biased electrode increases, the nature of the interface formed between the electrode and the host plasma undergoes a transition from an electron-rich structure (electron sheath) to an intermediate structure containing both ion and electron rich regions (double layer) and ultimately forms an electron-depleted structure (ion sheath). In this study, measurements are performed to further test how the size of an electron-collecting electrode impacts the plasma discharge the electrode is immersed in. This is accomplished using a segmented disk electrode in which individual segments are individually biased to change the effective surface area of the anode. Measurements of bulk plasma parameters such as the collected current density, plasma potential, electron density, electron temperature and optical emission are made as both the size and the bias placed on the electrode are varied. Abrupt transitions in the plasma parameters resulting from changing the electrode surface area are identified in both argon and helium discharges and are compared to the interface transitions predicted by global current balance [S. D. Baalrud, N. Hershkowitz, and B. Longmier, Phys. Plasmas 14, 042109 (2007)]. While the size-dependent transitions in argon agree, the size-dependent transitions observed in helium systematically occur at lower electrode sizes than those nominally derived from prediction. The discrepancy in helium is anticipated to be caused by the finite size of the interface that increases the effective area offered to the plasma for electron loss to the electrode

Potential sources of bias in the use of Escherichia coli to measure waterborne diarrhoea risk in low-income settings.

Science.gov (United States)

Ercumen, Ayse; Arnold, Benjamin F; Naser, Abu Mohd; Unicomb, Leanne; Colford, John M; Luby, Stephen P

2017-01-01

Escherichia coli is the standard water quality indicator for diarrhoea risk. Yet, the association between E. coli and diarrhoea is inconsistent across studies without a systematic assessment of methodological differences behind this variation. Most studies measure water quality cross-sectionally with diarrhoea, risking exposure misclassification and reverse causation. Studies use different recall windows for self-reported diarrhoea; longer periods increase potential outcome misclassification through misrecall. Control of confounding is inconsistent across studies. Additionally, diarrhoea measured in unblinded intervention trials can present courtesy bias. We utilised measurements from a randomised trial of water interventions in Bangladesh to assess how these factors affect the E. coli-diarrhoea association. We compared cross-sectional versus prospective measurements of water quality and diarrhoea, 2-versus 7-day symptom recall periods, estimates with and without controlling for confounding and using measurements from control versus intervention arms of the trial. In the control arm, 2-day diarrhoea prevalence, measured prospectively 1 month after water quality, significantly increased with log 10 E. coli (PR = 1.50, 1.02-2.20). This association weakened when we used 7-day recall (PR = 1.18, 0.88-1.57), cross-sectional measurements of E. coli and diarrhoea (PR = 1.11, 0.79-1.56) or did not control for confounding (PR = 1.20, 0.88-1.62). Including data from intervention arms led to less interpretable associations, potentially due to courtesy bias, effect modification and/or reverse causation. By systematically addressing potential sources of bias, our analysis demonstrates a clear relationship between E. coli in drinking water and diarrhoea, suggesting that the continued use of E. coli as an indicator of waterborne diarrhoea risk is justified. © 2016 John Wiley & Sons Ltd.

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

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Isaac Mugume

2016-01-01

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

Revisiting Robustness and Evolvability: Evolution in Weighted Genotype Spaces

Science.gov (United States)

Partha, Raghavendran; Raman, Karthik

2014-01-01

Robustness and evolvability are highly intertwined properties of biological systems. The relationship between these properties determines how biological systems are able to withstand mutations and show variation in response to them. Computational studies have explored the relationship between these two properties using neutral networks of RNA sequences (genotype) and their secondary structures (phenotype) as a model system. However, these studies have assumed every mutation to a sequence to be equally likely; the differences in the likelihood of the occurrence of various mutations, and the consequence of probabilistic nature of the mutations in such a system have previously been ignored. Associating probabilities to mutations essentially results in the weighting of genotype space. We here perform a comparative analysis of weighted and unweighted neutral networks of RNA sequences, and subsequently explore the relationship between robustness and evolvability. We show that assuming an equal likelihood for all mutations (as in an unweighted network), underestimates robustness and overestimates evolvability of a system. In spite of discarding this assumption, we observe that a negative correlation between sequence (genotype) robustness and sequence evolvability persists, and also that structure (phenotype) robustness promotes structure evolvability, as observed in earlier studies using unweighted networks. We also study the effects of base composition bias on robustness and evolvability. Particularly, we explore the association between robustness and evolvability in a sequence space that is AU-rich – sequences with an AU content of 80% or higher, compared to a normal (unbiased) sequence space. We find that evolvability of both sequences and structures in an AU-rich space is lesser compared to the normal space, and robustness higher. We also observe that AU-rich populations evolving on neutral networks of phenotypes, can access less phenotypic variation compared to

On robust parameter estimation in brain-computer interfacing

Science.gov (United States)

Samek, Wojciech; Nakajima, Shinichi; Kawanabe, Motoaki; Müller, Klaus-Robert

2017-12-01

Objective. The reliable estimation of parameters such as mean or covariance matrix from noisy and high-dimensional observations is a prerequisite for successful application of signal processing and machine learning algorithms in brain-computer interfacing (BCI). This challenging task becomes significantly more difficult if the data set contains outliers, e.g. due to subject movements, eye blinks or loose electrodes, as they may heavily bias the estimation and the subsequent statistical analysis. Although various robust estimators have been developed to tackle the outlier problem, they ignore important structural information in the data and thus may not be optimal. Typical structural elements in BCI data are the trials consisting of a few hundred EEG samples and indicating the start and end of a task. Approach. This work discusses the parameter estimation problem in BCI and introduces a novel hierarchical view on robustness which naturally comprises different types of outlierness occurring in structured data. Furthermore, the class of minimum divergence estimators is reviewed and a robust mean and covariance estimator for structured data is derived and evaluated with simulations and on a benchmark data set. Main results. The results show that state-of-the-art BCI algorithms benefit from robustly estimated parameters. Significance. Since parameter estimation is an integral part of various machine learning algorithms, the presented techniques are applicable to many problems beyond BCI.

Empathy, theory of mind, and individual differences in the appropriation bias among 4- and 5-year-olds.

Science.gov (United States)

Ford, Ruth M; Lobao, Sheila N; Macaulay, Catrin; Herdman, Lynsey M

2011-12-01

Evidence that young children often claim ownership of their partner's contributions to an earlier collaborative activity, the appropriation bias, has been attributed to shared intentionality (Cognitive Development (1998) 13, 91-108). The current investigation explored this notion by examining individual differences in the bias among 4- and 5-year-olds as a function of empathy and theory of mind. On two occasions, children joined an adult and two dolls (with each doll being operated by one of the humans) in a picture matching board game before being asked to remember who placed each picture. Children showed a robust appropriation bias despite excellent recognition memory for the studied pictures (Study 1) and particularly in relation to the human sources (Study 2). Whereas higher levels of self-reported empathy were associated with a greater frequency of appropriation errors and fewer correct attributions for pictures placed by the adult and her doll partner, the opposite pattern emerged for theory of mind. Moreover, the positive relations between theory of mind and source monitoring accuracy remained robust after controlling for general ability and inhibitory skills. We consider the implications of these findings for understanding the processes driving the appropriation bias. Copyright © 2011 Elsevier Inc. All rights reserved.

Infrared Resummation for Biased Tracers in Redshift Space arXiv

CERN Document Server

Ivanov, Mikhail M.

We incorporate the effects of redshift space distortions and non-linear bias in time-sliced perturbation theory (TSPT). This is done via a new method that allows to map cosmological correlation functions from real to redshift space. This mapping preserves a transparent infrared (IR) structure of the theory and provides us with an efficient tool to study non-linear infrared effects altering the pattern of baryon acoustic oscillations (BAO) in redshift space. We give an accurate description of the BAO by means of a systematic resummation of Feynman diagrams guided by well-defined power counting rules. This establishes IR resummation within TSPT as a robust and complete procedure and provides a consistent theoretical model for the BAO feature in the statistics of biased tracers in redshift space.

Counteracting estimation bias and social influence to improve the wisdom of crowds.

Science.gov (United States)

Kao, Albert B; Berdahl, Andrew M; Hartnett, Andrew T; Lutz, Matthew J; Bak-Coleman, Joseph B; Ioannou, Christos C; Giam, Xingli; Couzin, Iain D

2018-04-01

Aggregating multiple non-expert opinions into a collective estimate can improve accuracy across many contexts. However, two sources of error can diminish collective wisdom: individual estimation biases and information sharing between individuals. Here, we measure individual biases and social influence rules in multiple experiments involving hundreds of individuals performing a classic numerosity estimation task. We first investigate how existing aggregation methods, such as calculating the arithmetic mean or the median, are influenced by these sources of error. We show that the mean tends to overestimate, and the median underestimate, the true value for a wide range of numerosities. Quantifying estimation bias, and mapping individual bias to collective bias, allows us to develop and validate three new aggregation measures that effectively counter sources of collective estimation error. In addition, we present results from a further experiment that quantifies the social influence rules that individuals employ when incorporating personal estimates with social information. We show that the corrected mean is remarkably robust to social influence, retaining high accuracy in the presence or absence of social influence, across numerosities and across different methods for averaging social information. Using knowledge of estimation biases and social influence rules may therefore be an inexpensive and general strategy to improve the wisdom of crowds. © 2018 The Author(s).

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

Science.gov (United States)

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

2017-01-03

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

Recent Advances in Attention Bias Modification for Substance Addictions

Directory of Open Access Journals (Sweden)

Melvyn Weibin Zhang

2018-04-01

Full Text Available Research on attentional bias modification has increased since 2014. A recent meta-analysis demonstrates evidence for bias modification for substance disorders, including alcohol and tobacco use disorders. Several pharmacological trials have shown that pharmacological agents can attenuate and modify such attentional bias. The pharmacological trials that have appeared to date have produced mixed results, which has clinical implications. Developments in Internet and mobile technologies have transformed how attention bias modification is currently being achieved. There remains great potential for further research that examines the efficacy of technology-aided attention bias interventions.

Health risk perception, optimistic bias, and personal satisfaction.

Science.gov (United States)

Bränström, Richard; Brandberg, Yvonne

2010-01-01

To examine change in risk perception and optimistic bias concerning behavior-linked health threats and environmental health threats between adolescence and young adulthood and how these factors related to personal satisfaction. In 1996 and 2002, 1624 adolescents responded to a mailed questionnaire. Adolescents showed strong positive optimistic bias concerning behaviorlinked risks, and this optimistic bias increased with age. Increase in optimistic bias over time predicted increase in personal satisfaction. The capacity to process and perceive potential threats in a positive manner might be a valuable human ability positively influencing personal satisfaction and well-being.

TCABR Tokamak scrape-off layer turbulence with DC biasing

International Nuclear Information System (INIS)

Heller, M.V.A.P.; Ferreira, A.A.; Caldas, I.L.; Nascimento, I.C.

2004-01-01

Turbulence and particle transport in plasma scrape-off layer have been controlled by external electric fields. This control can be achieved by a biasing electrode located inside the plasma. We investigate plasma turbulence changes in the scrape-off layer of TCABR tokamak introduced by DC biasing an electrode inside the plasma. Our investigation is based on the alterations observed on the wavelet power spectra and on the intermittent burst sequences of plasma potential and density fluctuations measured by a set of Langmuir probes. Biasing the electrode changes the turbulence statistics and the bursts intermittence. With the imposed external electric field, fluctuation amplitudes, phase velocities, and anomalous particle transport are modified. Transport reduction for higher frequencies induced by the biasing could be due to the strong de-phasing between density and potential fluctuations. The mode coupling increases with the perturbation for the high frequency broadband fluctuations. The total (laminar and bursting) radial particle transport is reduced by about 25% by DC biasing. Bursts contribution to total transport is 15% and for the studied conditions this contribution does not change much with the bias perturbation

Stochastic bias-correction of daily rainfall scenarios for hydrological applications

Directory of Open Access Journals (Sweden)

I. Portoghese

2011-09-01

Full Text Available The accuracy of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes. In fact, the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows and groundwater recharge.

In this study, a comparison between statistical properties of rainfall observations and model control simulations from a Regional Climate Model (RCM was performed through a robust and meaningful representation of the precipitation process. The output of the adopted RCM was analysed and re-scaled exploiting the structure of a stochastic model of the point rainfall process. In particular, the stochastic model is able to adequately reproduce the rainfall intermittency at the synoptic scale, which is one of the crucial aspects for the Mediterranean environments. Possible alteration in the local rainfall regime was investigated by means of the historical daily time-series from a dense rain-gauge network, which were also used for the analysis of the RCM bias in terms of dry and wet periods and storm intensity. The result is a stochastic scheme for bias-correction at the RCM-cell scale, which produces a realistic representation of the daily rainfall intermittency and precipitation depths, though a residual bias in the storm intensity of longer storm events persists.

Robust random telegraph conductivity noise in single crystals of the ferromagnetic insulating manganite La0.86Ca0.14MnO3

Science.gov (United States)

Przybytek, J.; Fink-Finowicki, J.; Puźniak, R.; Shames, A.; Markovich, V.; Mogilyansky, D.; Jung, G.

2017-03-01

Robust random telegraph conductivity fluctuations have been observed in La0.86Ca0.14MnO3 manganite single crystals. At room temperatures, the spectra of conductivity fluctuations are featureless and follow a 1 /f shape in the entire experimental frequency and bias range. Upon lowering the temperature, clear Lorentzian bias-dependent excess noise appears on the 1 /f background and eventually dominates the spectral behavior. In the time domain, fully developed Lorentzian noise appears as pronounced two-level random telegraph noise with a thermally activated switching rate, which does not depend on bias current and applied magnetic field. The telegraph noise is very robust and persists in the exceptionally wide temperature range of more than 50 K. The amplitude of the telegraph noise decreases exponentially with increasing bias current in exactly the same manner as the sample resistance increases with the current, pointing out the dynamic current redistribution between percolation paths dominated by phase-separated clusters with different conductivity as a possible origin of two-level conductivity fluctuations.

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

Directory of Open Access Journals (Sweden)

Chao-Chen Gu

2018-01-01

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

Super-delta: a new differential gene expression analysis procedure with robust data normalization.

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Liu, Yuhang; Zhang, Jinfeng; Qiu, Xing

2017-12-21

Normalization is an important data preparation step in gene expression analyses, designed to remove various systematic noise. Sample variance is greatly reduced after normalization, hence the power of subsequent statistical analyses is likely to increase. On the other hand, variance reduction is made possible by borrowing information across all genes, including differentially expressed genes (DEGs) and outliers, which will inevitably introduce some bias. This bias typically inflates type I error; and can reduce statistical power in certain situations. In this study we propose a new differential expression analysis pipeline, dubbed as super-delta, that consists of a multivariate extension of the global normalization and a modified t-test. A robust procedure is designed to minimize the bias introduced by DEGs in the normalization step. The modified t-test is derived based on asymptotic theory for hypothesis testing that suitably pairs with the proposed robust normalization. We first compared super-delta with four commonly used normalization methods: global, median-IQR, quantile, and cyclic loess normalization in simulation studies. Super-delta was shown to have better statistical power with tighter control of type I error rate than its competitors. In many cases, the performance of super-delta is close to that of an oracle test in which datasets without technical noise were used. We then applied all methods to a collection of gene expression datasets on breast cancer patients who received neoadjuvant chemotherapy. While there is a substantial overlap of the DEGs identified by all of them, super-delta were able to identify comparatively more DEGs than its competitors. Downstream gene set enrichment analysis confirmed that all these methods selected largely consistent pathways. Detailed investigations on the relatively small differences showed that pathways identified by super-delta have better connections to breast cancer than other methods. As a new pipeline, super

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

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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.

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

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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.

Opinions and potential solutions regarding dissemination bias from funding agencies of biomedical research in Europe.

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Pardo-Hernandez, Hector; Urrútia, Gerard; Meerpohl, Joerg J; Marušić, Ana; Wager, Elizabeth; Bonfill, Xavier

2018-02-01

Several studies have found that about half of research results from clinical trials are never published. Until now, there has been little information on the views that funding agencies of biomedical research in Europe have regarding this issue and its possible solutions. An electronic survey was conducted among funding agencies from 34 European countries. Participants were asked about their opinions, policies, and potential solutions regarding dissemination bias. On the basis of the results of this survey and the input of the OPEN Consortium and of representatives of stakeholder groups in the knowledge generation process, we formulated recommendations for funding agencies to reduce dissemination bias. We received responses from 64 funding agencies of biomedical medicine from most European countries, out of 245 that were contacted (26%). Of these, 56 funded research at the national and/or international level and were therefore eligible to participate. Policies encouraging publication increased over time: 33 (58.9%) of agencies enforced them in 2005 compared to 38 (67.6%) in 2012. However, only 13 (23.2%) had knowledge of the publications related to research funded in 2005, 23 (41.1%) were able to provide only an estimate, and 20 (35.7%) did not know at all. Regarding recommendations to control dissemination bias, we propose that funding agencies request the dissemination of research results irrespective of the direction of findings. We also call for measures that allow evaluating funded projects past the contractual period and until dissemination of results. Funding agencies should create publicly accessible databases with information on funded projects and dissemination efforts. Despite having policies to encourage publication of results, most funding agencies fail to implement such measures or to ensure compliance. We propose recommendations that could be incorporated in the blueprint of calls for proposals and contracts agreed upon by funding agencies and grant

Mitigating Evidentiary Bias in Planning and Policy-Making; Comment on “Reflective Practice: How the World Bank Explored Its Own Biases?”

Directory of Open Access Journals (Sweden)

Justin Parkhurst

2017-02-01

Full Text Available The field of cognitive psychology has increasingly provided scientific insights to explore how humans are subject to unconscious sources of evidentiary bias, leading to errors that can affect judgement and decision-making. Increasingly these insights are being applied outside the realm of individual decision-making to the collective arena of policy-making as well. A recent editorial in this journal has particularly lauded the work of the World Bank for undertaking an open and critical reflection on sources of unconscious bias in its own expert staff that could undermine achievement of its key goals. The World Bank case indeed serves as a remarkable case of a global policy-making agency making its own critical reflections transparent for all to see. Yet the recognition that humans are prone to cognitive errors has been known for centuries, and the scientific exploration of such biases provided by cognitive psychology is now well-established. What still remains to be developed, however, is a widespread body of work that can inform efforts to institutionalise strategies to mitigate the multiple sources and forms of evidentiary bias arising within administrative and policy-making environments. Addressing this gap will require a programme of conceptual and empirical work that supports robust development and evaluation of institutional bias mitigation strategies. The cognitive sciences provides a scientific basis on which to proceed, but a critical priority will now be the application of that science to improve policy-making within those agencies taking responsibility for social welfare and development programmes.

Autocalibration method for non-stationary CT bias correction.

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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.

Unbiased tensor-based morphometry: improved robustness and sample size estimates for Alzheimer's disease clinical trials.

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Hua, Xue; Hibar, Derrek P; Ching, Christopher R K; Boyle, Christina P; Rajagopalan, Priya; Gutman, Boris A; Leow, Alex D; Toga, Arthur W; Jack, Clifford R; Harvey, Danielle; Weiner, Michael W; Thompson, Paul M

2013-02-01

Various neuroimaging measures are being evaluated for tracking Alzheimer's disease (AD) progression in therapeutic trials, including measures of structural brain change based on repeated scanning of patients with magnetic resonance imaging (MRI). Methods to compute brain change must be robust to scan quality. Biases may arise if any scans are thrown out, as this can lead to the true changes being overestimated or underestimated. Here we analyzed the full MRI dataset from the first phase of Alzheimer's Disease Neuroimaging Initiative (ADNI-1) from the first phase of Alzheimer's Disease Neuroimaging Initiative (ADNI-1) and assessed several sources of bias that can arise when tracking brain changes with structural brain imaging methods, as part of a pipeline for tensor-based morphometry (TBM). In all healthy subjects who completed MRI scanning at screening, 6, 12, and 24months, brain atrophy was essentially linear with no detectable bias in longitudinal measures. In power analyses for clinical trials based on these change measures, only 39AD patients and 95 mild cognitive impairment (MCI) subjects were needed for a 24-month trial to detect a 25% reduction in the average rate of change using a two-sided test (α=0.05, power=80%). Further sample size reductions were achieved by stratifying the data into Apolipoprotein E (ApoE) ε4 carriers versus non-carriers. We show how selective data exclusion affects sample size estimates, motivating an objective comparison of different analysis techniques based on statistical power and robustness. TBM is an unbiased, robust, high-throughput imaging surrogate marker for large, multi-site neuroimaging studies and clinical trials of AD and MCI. Copyright © 2012 Elsevier Inc. All rights reserved.

Music for a Brighter World: Brightness Judgment Bias by Musical Emotion.

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Joydeep Bhattacharya

Full Text Available A prevalent conceptual metaphor is the association of the concepts of good and evil with brightness and darkness, respectively. Music cognition, like metaphor, is possibly embodied, yet no study has addressed the question whether musical emotion can modulate brightness judgment in a metaphor consistent fashion. In three separate experiments, participants judged the brightness of a grey square that was presented after a short excerpt of emotional music. The results of Experiment 1 showed that short musical excerpts are effective emotional primes that cross-modally influence brightness judgment of visual stimuli. Grey squares were consistently judged as brighter after listening to music with a positive valence, as compared to music with a negative valence. The results of Experiment 2 revealed that the bias in brightness judgment does not require an active evaluation of the emotional content of the music. By applying a different experimental procedure in Experiment 3, we showed that this brightness judgment bias is indeed a robust effect. Altogether, our findings demonstrate a powerful role of musical emotion in biasing brightness judgment and that this bias is aligned with the metaphor viewpoint.

Potential sources of analytical bias and error in selected trace element data-quality analyses

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Paul, Angela P.; Garbarino, John R.; Olsen, Lisa D.; Rosen, Michael R.; Mebane, Christopher A.; Struzeski, Tedmund M.

2016-09-28

Potential sources of analytical bias and error associated with laboratory analyses for selected trace elements where concentrations were greater in filtered samples than in paired unfiltered samples were evaluated by U.S. Geological Survey (USGS) Water Quality Specialists in collaboration with the USGS National Water Quality Laboratory (NWQL) and the Branch of Quality Systems (BQS).Causes for trace-element concentrations in filtered samples to exceed those in associated unfiltered samples have been attributed to variability in analytical measurements, analytical bias, sample contamination either in the field or laboratory, and (or) sample-matrix chemistry. These issues have not only been attributed to data generated by the USGS NWQL but have been observed in data generated by other laboratories. This study continues the evaluation of potential analytical bias and error resulting from matrix chemistry and instrument variability by evaluating the performance of seven selected trace elements in paired filtered and unfiltered surface-water and groundwater samples collected from 23 sampling sites of varying chemistries from six States, matrix spike recoveries, and standard reference materials.Filtered and unfiltered samples have been routinely analyzed on separate inductively coupled plasma-mass spectrometry instruments. Unfiltered samples are treated with hydrochloric acid (HCl) during an in-bottle digestion procedure; filtered samples are not routinely treated with HCl as part of the laboratory analytical procedure. To evaluate the influence of HCl on different sample matrices, an aliquot of the filtered samples was treated with HCl. The addition of HCl did little to differentiate the analytical results between filtered samples treated with HCl from those samples left untreated; however, there was a small, but noticeable, decrease in the number of instances where a particular trace-element concentration was greater in a filtered sample than in the associated

Children's Attentional Biases and "5-HTTLPR" Genotype: Potential Mechanisms Linking Mother and Child Depression

Science.gov (United States)

Gibb, Brandon E.; Benas, Jessica S.; Grassia, Marie; McGeary, John

2009-01-01

In this study, we examined the roles of specific cognitive (attentional bias) and genetic ("5-HTTLPR") risk factors in the intergenerational transmission of depression. Focusing first on the link between maternal history of major depressive disorder (MDD) and children's attentional biases, we found that children of mothers with a history…

Kendall-Theil Robust Line (KTRLine--version 1.0)-A Visual Basic Program for Calculating and Graphing Robust Nonparametric Estimates of Linear-Regression Coefficients Between Two Continuous Variables

Science.gov (United States)

Granato, Gregory E.

2006-01-01

The Kendall-Theil Robust Line software (KTRLine-version 1.0) is a Visual Basic program that may be used with the Microsoft Windows operating system to calculate parameters for robust, nonparametric estimates of linear-regression coefficients between two continuous variables. The KTRLine software was developed by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, for use in stochastic data modeling with local, regional, and national hydrologic data sets to develop planning-level estimates of potential effects of highway runoff on the quality of receiving waters. The Kendall-Theil robust line was selected because this robust nonparametric method is resistant to the effects of outliers and nonnormality in residuals that commonly characterize hydrologic data sets. The slope of the line is calculated as the median of all possible pairwise slopes between points. The intercept is calculated so that the line will run through the median of input data. A single-line model or a multisegment model may be specified. The program was developed to provide regression equations with an error component for stochastic data generation because nonparametric multisegment regression tools are not available with the software that is commonly used to develop regression models. The Kendall-Theil robust line is a median line and, therefore, may underestimate total mass, volume, or loads unless the error component or a bias correction factor is incorporated into the estimate. Regression statistics such as the median error, the median absolute deviation, the prediction error sum of squares, the root mean square error, the confidence interval for the slope, and the bias correction factor for median estimates are calculated by use of nonparametric methods. These statistics, however, may be used to formulate estimates of mass, volume, or total loads. The program is used to read a two- or three-column tab-delimited input file with variable names in the first row and

Enhanced confinement with plasma biasing in the MST reversed field pinch

International Nuclear Information System (INIS)

Craig, D.; Almagri, A.F.; Anderson, J.K.

1997-06-01

We report an increase in particle confinement with plasma biasing in a reversed field pinch. Miniature plasma sources are used as electrodes to negatively bias the plasma at the edge (r/a ∼ 0.9). Particle content increases and H α radiation decreases upon application of bias and global particle confinement roughly doubles as a result. Measurements of plasma potential, impurity flow, and floating potential fluctuations indicate that strong flows are produced and that electrostatic fluctuations are reduced

Moderate intra-group bias maximizes cooperation on interdependent populations.

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Changbing Tang

Full Text Available Evolutionary game theory on spatial structures has received increasing attention during the past decades. However, the majority of these achievements focuses on single and static population structures, which is not fully consistent with the fact that real structures are composed of many interactive groups. These groups are interdependent on each other and present dynamical features, in which individuals mimic the strategy of neighbors and switch their partnerships continually. It is however unclear how the dynamical and interdependent interactions among groups affect the evolution of collective behaviors. In this work, we employ the prisoner's dilemma game to investigate how the dynamics of structure influences cooperation on interdependent populations, where populations are represented by group structures. It is found that the more robust the links between cooperators (or the more fragile the links between cooperators and defectors, the more prevalent of cooperation. Furthermore, theoretical analysis shows that the intra-group bias can favor cooperation, which is only possible when individuals are likely to attach neighbors within the same group. Yet, interestingly, cooperation can be even inhibited for large intra-group bias, allowing the moderate intra-group bias maximizes the cooperation level.

Long-branch attraction bias and inconsistency in Bayesian phylogenetics.

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Kolaczkowski, Bryan; Thornton, Joseph W

2009-12-09

Bayesian inference (BI) of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML), so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI's long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias--which is apparent under both controlled simulation conditions and in analyses of empirical sequence data--also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI's bias is caused by one of the method's stated advantages--that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis.

Causes of model dry and warm bias over central U.S. and impact on climate projections.

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Lin, Yanluan; Dong, Wenhao; Zhang, Minghua; Xie, Yuanyu; Xue, Wei; Huang, Jianbin; Luo, Yong

2017-10-12

Climate models show a conspicuous summer warm and dry bias over the central United States. Using results from 19 climate models in the Coupled Model Intercomparison Project Phase 5 (CMIP5), we report a persistent dependence of warm bias on dry bias with the precipitation deficit leading the warm bias over this region. The precipitation deficit is associated with the widespread failure of models in capturing strong rainfall events in summer over the central U.S. A robust linear relationship between the projected warming and the present-day warm bias enables us to empirically correct future temperature projections. By the end of the 21st century under the RCP8.5 scenario, the corrections substantially narrow the intermodel spread of the projections and reduce the projected temperature by 2.5 K, resulting mainly from the removal of the warm bias. Instead of a sharp decrease, after this correction the projected precipitation is nearly neutral for all scenarios.Climate models repeatedly show a warm and dry bias over the central United States, but the origin of this bias remains unclear. Here the authors associate this bias to precipitation deficits in models and after applying a correction, projected precipitation in this region shows no significant changes.

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

Science.gov (United States)

Lubow, Bruce C; Ransom, Jason I

2016-01-01

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

Robustness of Long Span Reciprocal Timber Structures

DEFF Research Database (Denmark)

Balfroid, Nathalie; Kirkegaard, Poul Henning

2011-01-01

engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper makes a discussion of such robustness issues related to the future development of reciprocal timber structures. The paper concludes that these kind of structures can have...... a potential as long span timber structures in real projects if they are carefully designed with respect to the overall robustness strategies.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. The interest has also been facilitated due to recently severe structural failures...

GALAXY BIAS AND ITS EFFECTS ON THE BARYON ACOUSTIC OSCILLATION MEASUREMENTS

International Nuclear Information System (INIS)

Mehta, Kushal T.; Eckel, Jonathan; Eisenstein, Daniel J.; Metchnik, Marc; Pinto, Philip; Xu Xiaoying; Seo, Hee-Jong

2011-01-01

The baryon acoustic oscillation (BAO) feature in the clustering of matter in the universe serves as a robust standard ruler and hence can be used to map the expansion history of the universe. We use high force resolution simulations to analyze the effects of galaxy bias on the measurements of the BAO signal. We apply a variety of Halo Occupation Distributions (HODs) and produce biased mass tracers to mimic different galaxy populations. We investigate whether galaxy bias changes the nonlinear shifts on the acoustic scale relative to the underlying dark matter distribution presented by Seo et al. For the less biased HOD models (b 3) show a shift at moderate significance (0.79% ± 0.31% for the most extreme case). We test the one-step reconstruction technique introduced by Eisenstein et al. in the case of realistic galaxy bias and shot noise. The reconstruction scheme increases the correlation between the initial and final (z = 1) density fields, achieving an equivalent level of correlation at nearly twice the wavenumber after reconstruction. Reconstruction reduces the shifts and errors on the shifts. We find that after reconstruction the shifts from the galaxy cases and the dark matter case are consistent with each other and with no shift. The 1σ systematic errors on the distance measurements inferred from our BAO measurements with various HODs after reconstruction are about 0.07%-0.15%.

Effects of biases in domain wall network evolution. II. Quantitative analysis

Science.gov (United States)

Correia, J. R. C. C. C.; Leite, I. S. C. R.; Martins, C. J. A. P.

2018-04-01

Domain walls form at phase transitions which break discrete symmetries. In a cosmological context, they often overclose the Universe (contrary to observational evidence), although one may prevent this by introducing biases or forcing anisotropic evolution of the walls. In a previous work [Correia et al., Phys. Rev. D 90, 023521 (2014), 10.1103/PhysRevD.90.023521], we numerically studied the evolution of various types of biased domain wall networks in the early Universe, confirming that anisotropic networks ultimately reach scaling while those with a biased potential or biased initial conditions decay. We also found that the analytic decay law obtained by Hindmarsh was in good agreement with simulations of biased potentials, but not of biased initial conditions, and suggested that the difference was related to the Gaussian approximation underlying the analytic law. Here, we extend our previous work in several ways. For the cases of biased potential and biased initial conditions, we study in detail the field distributions in the simulations, confirming that the validity (or not) of the Gaussian approximation is the key difference between the two cases. For anisotropic walls, we carry out a more extensive set of numerical simulations and compare them to the canonical velocity-dependent one-scale model for domain walls, finding that the model accurately predicts the linear scaling regime after isotropization. Overall, our analysis provides a quantitative description of the cosmological evolution of these networks.

Potential for bias in 21st century semiempirical sea level projections

DEFF Research Database (Denmark)

Jevrejeva, S.; Moore, J. C.; Grinsted, A.

2012-01-01

by satellite altimetry. Nonradiative forcing contributors, such as long-term adjustment of Greenland and Antarctica ice sheets since Last Glacial Maximum, abyssal ocean warming, and terrestrial water storage, may bias model calibration which, if corrected for, tend to reduce median sea level projections...

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

Science.gov (United States)

Chen, Yunjie; Zhang, Jianwei; Macione, Jim

2009-10-01

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

Biases in Quality Attribution to Mother-Child and Caregiver-Child Interaction.

Science.gov (United States)

Shpancer, Noam; Britner, Preston A.

1995-01-01

Examined the possible existence, direction, and nature of subconscious, cognitive biases in participants' quality attributions to maternal and nonmaternal child-care interactions, the relationship of such biases to subject's background, and their attitudes toward child care and maternal employment. Potential explanations for the biases and the…

Robust Means Modeling: An Alternative for Hypothesis Testing of Independent Means under Variance Heterogeneity and Nonnormality

Science.gov (United States)

Fan, Weihua; Hancock, Gregory R.

2012-01-01

This study proposes robust means modeling (RMM) approaches for hypothesis testing of mean differences for between-subjects designs in order to control the biasing effects of nonnormality and variance inequality. Drawing from structural equation modeling (SEM), the RMM approaches make no assumption of variance homogeneity and employ robust…

Electrode and limiter biasing experiments on the tokamak ISTTOK

International Nuclear Information System (INIS)

Silva, C.; Figueiredo, H.; Cabral, J.A.C.; Nedzelsky, I.; Varandas, C.A.F.

2003-01-01

In this contribution limiter and electrode biasing experiments are compared, in particular in what concerns their effects on the edge plasma parameters. For electrode AC bias a substantial increase (>50%) in the average plasma density is observed with positive voltage, without significant changes in the edge density, leading to steeper profiles. The ratio n e /Hα also increases significantly (>20%), indicating an improvement in gross particle confinement. The plasma potential profile is strongly modified as both the edge E r and its shear increase significantly. For positive limiter bias an increase in the average plasma density and the radiation losses is observed, resulting in almost no modification, or a slight, in particle confinement. Preliminary results of simultaneous electrode and limiter bias experiments show that the control of the plasma potential profile is very limited, since negative voltages do not modify the plasma parameters significantly. (author)

Investigation of attentional bias in obsessive compulsive disorder with and without depression in visual search.

Directory of Open Access Journals (Sweden)

Sharon Morein-Zamir

Full Text Available Whether Obsessive Compulsive Disorder (OCD is associated with an increased attentional bias to emotive stimuli remains controversial. Additionally, it is unclear whether comorbid depression modulates abnormal emotional processing in OCD. This study examined attentional bias to OC-relevant scenes using a visual search task. Controls, non-depressed and depressed OCD patients searched for their personally selected positive images amongst their negative distractors, and vice versa. Whilst the OCD groups were slower than healthy individuals in rating the images, there were no group differences in the magnitude of negative bias to concern-related scenes. A second experiment employing a common set of images replicated the results on an additional sample of OCD patients. Although there was a larger bias to negative OC-related images without pre-exposure overall, no group differences in attentional bias were observed. However, OCD patients subsequently rated the images more slowly and more negatively, again suggesting post-attentional processing abnormalities. The results argue against a robust attentional bias in OCD patients, regardless of their depression status and speak to generalized difficulties disengaging from negative valence stimuli. Rather, post-attentional processing abnormalities may account for differences in emotional processing in OCD.

The L0 Regularized Mumford-Shah Model for Bias Correction and Segmentation of Medical Images.

Science.gov (United States)

Duan, Yuping; Chang, Huibin; Huang, Weimin; Zhou, Jiayin; Lu, Zhongkang; Wu, Chunlin

2015-11-01

We propose a new variant of the Mumford-Shah model for simultaneous bias correction and segmentation of images with intensity inhomogeneity. First, based on the model of images with intensity inhomogeneity, we introduce an L0 gradient regularizer to model the true intensity and a smooth regularizer to model the bias field. In addition, we derive a new data fidelity using the local intensity properties to allow the bias field to be influenced by its neighborhood. Second, we use a two-stage segmentation method, where the fast alternating direction method is implemented in the first stage for the recovery of true intensity and bias field and a simple thresholding is used in the second stage for segmentation. Different from most of the existing methods for simultaneous bias correction and segmentation, we estimate the bias field and true intensity without fixing either the number of the regions or their values in advance. Our method has been validated on medical images of various modalities with intensity inhomogeneity. Compared with the state-of-art approaches and the well-known brain software tools, our model is fast, accurate, and robust with initializations.

Unbiased tensor-based morphometry: Improved robustness and sample size estimates for Alzheimer’s disease clinical trials

Science.gov (United States)

Hua, Xue; Hibar, Derrek P.; Ching, Christopher R.K.; Boyle, Christina P.; Rajagopalan, Priya; Gutman, Boris A.; Leow, Alex D.; Toga, Arthur W.; Jack, Clifford R.; Harvey, Danielle; Weiner, Michael W.; Thompson, Paul M.

2013-01-01

Various neuroimaging measures are being evaluated for tracking Alzheimer’s disease (AD) progression in therapeutic trials, including measures of structural brain change based on repeated scanning of patients with magnetic resonance imaging (MRI). Methods to compute brain change must be robust to scan quality. Biases may arise if any scans are thrown out, as this can lead to the true changes being overestimated or underestimated. Here we analyzed the full MRI dataset from the first phase of Alzheimer’s Disease Neuroimaging Initiative (ADNI-1) from the first phase of Alzheimer’s Disease Neuroimaging Initiative (ADNI-1) and assessed several sources of bias that can arise when tracking brain changes with structural brain imaging methods, as part of a pipeline for tensor-based morphometry (TBM). In all healthy subjects who completed MRI scanning at screening, 6, 12, and 24 months, brain atrophy was essentially linear with no detectable bias in longitudinal measures. In power analyses for clinical trials based on these change measures, only 39 AD patients and 95 mild cognitive impairment (MCI) subjects were needed for a 24-month trial to detect a 25% reduction in the average rate of change using a two-sided test (α=0.05, power=80%). Further sample size reductions were achieved by stratifying the data into Apolipoprotein E (ApoE) ε4 carriers versus non-carriers. We show how selective data exclusion affects sample size estimates, motivating an objective comparison of different analysis techniques based on statistical power and robustness. TBM is an unbiased, robust, high-throughput imaging surrogate marker for large, multi-site neuroimaging studies and clinical trials of AD and MCI. PMID:23153970

The Biases of Thinking Fast and Thinking Slow

OpenAIRE

Streeb, Dirk; Chen, Min; Keim, Daniel A.

2017-01-01

Visualization is a human-centric process, which is inevitably as- sociated with potential biases in humans’ judgment and decision making. While the discussions on humans’ biases have been heavily influenced the work of Daniel Kahneman as summarized in his book “Thinking, Fast and Slow” [8], there have also been viewpoints in psychology in favor of heuristics (e.g., [6]). In this paper, we present a balanced discourse on the humans’ heuristics and biases as the two sides of the same coin. In p...

Negativity Bias in Dangerous Drivers.

Directory of Open Access Journals (Sweden)

Jing Chai

Full Text Available The behavioral and cognitive characteristics of dangerous drivers differ significantly from those of safe drivers. However, differences in emotional information processing have seldom been investigated. Previous studies have revealed that drivers with higher anger/anxiety trait scores are more likely to be involved in crashes and that individuals with higher anger traits exhibit stronger negativity biases when processing emotions compared with control groups. However, researchers have not explored the relationship between emotional information processing and driving behavior. In this study, we examined the emotional information processing differences between dangerous drivers and safe drivers. Thirty-eight non-professional drivers were divided into two groups according to the penalty points that they had accrued for traffic violations: 15 drivers with 6 or more points were included in the dangerous driver group, and 23 drivers with 3 or fewer points were included in the safe driver group. The emotional Stroop task was used to measure negativity biases, and both behavioral and electroencephalograph data were recorded. The behavioral results revealed stronger negativity biases in the dangerous drivers than in the safe drivers. The bias score was correlated with self-reported dangerous driving behavior. Drivers with strong negativity biases reported having been involved in mores crashes compared with the less-biased drivers. The event-related potentials (ERPs revealed that the dangerous drivers exhibited reduced P3 components when responding to negative stimuli, suggesting decreased inhibitory control of information that is task-irrelevant but emotionally salient. The influence of negativity bias provides one possible explanation of the effects of individual differences on dangerous driving behavior and traffic crashes.

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

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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.

Robustness-related issues in speaker recognition

CERN Document Server

Zheng, Thomas Fang

2017-01-01

This book presents an overview of speaker recognition technologies with an emphasis on dealing with robustness issues. Firstly, the book gives an overview of speaker recognition, such as the basic system framework, categories under different criteria, performance evaluation and its development history. Secondly, with regard to robustness issues, the book presents three categories, including environment-related issues, speaker-related issues and application-oriented issues. For each category, the book describes the current hot topics, existing technologies, and potential research focuses in the future. The book is a useful reference book and self-learning guide for early researchers working in the field of robust speech recognition.

Effects of limiter biasing on the ATF torsatron

International Nuclear Information System (INIS)

Uckan, T.; Baylor, L.R.; Bell, J.D.; Bigelow, T.S.; England, A.C.; Harris, J.H.; Isler, R.C.; Jernigan, T.C.; Lyon, J.F.; Ma, C.H.; Mioduszewski, P.K.; Murakami, M.; Rasmussen, D.A.; Wilgen, J.B.; Aceto, S.C.; Zielinski, J.J.

1992-09-01

Positive limiter biasing on the currentless Advanced Toroidal Facility (ATF) torsatron produces a significant increase in the particle confinement with no improvement in the energy confinement. Experiments have been carried out in 1-T plasmas with ∼400 kill of electron cyclotron heating ECM. Two rail limiters located at the last closed flux surface (LCFS), one at the top and one at the bottom of the device, are biased at positive and negative potentials with respect to the vessel. When the limiters are positively biased at up to 300 V, the density increases sharply to the ECH cutoff value. At the same time, the H α radiation drops, indicating that the particle confinement improves. When the density is kept constant, the H α radiation is further reduced and there is almost no change in the plasma stored energy. Under these conditions, the density profile becomes peaked and the electric field becomes outward-pointing outside the LCFS and more negative inside the LCFS. In contrast, negative biasing yields some reduction of the density and stored energy at constant gas feed, and the plasma potential profile remains the same. Biasing has almost no effect on the intrinsic impurity levels in the plasma

Robustness Analysis of Typologies of Reciprocal Timber Structures

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Parigi, Dario

2013-01-01

to the future development of typologies of reciprocal timber structures. The paper concludes that these kinds of structures can have a potential as long span timber structures in real projects if they are carefully designed with respect to the overall robustness strategies.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures many modern building...... codes consider the need for robustness in structures and provides strategies and methods to obtain robustness. Therefore a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper outlines robustness issues related...

Robustness Metrics: Consolidating the multiple approaches to quantify Robustness

DEFF Research Database (Denmark)

Göhler, Simon Moritz; Eifler, Tobias; Howard, Thomas J.

2016-01-01

robustness metrics; 3) Functional expectancy and dispersion robustness metrics; and 4) Probability of conformance robustness metrics. The goal was to give a comprehensive overview of robustness metrics and guidance to scholars and practitioners to understand the different types of robustness metrics...

Understanding robustness as an image of sustainable agriculture

NARCIS (Netherlands)

Goede, de D.M.

2014-01-01

The general aim of the research described in this thesis is to contribute to a better understanding of the conceptualisation of robustness in agricultural science as well as its relevance to sustainability. Robustness rapidly gained attention as a potential solution for a variety of

Maximizing potential impact of experimental research into cognitive processes in health psychology: A systematic approach to material development.

Science.gov (United States)

Hughes, Alicia M; Gordon, Rola; Chalder, Trudie; Hirsch, Colette R; Moss-Morris, Rona

2016-11-01

There is an abundance of research into cognitive processing biases in clinical psychology including the potential for applying cognitive bias modification techniques to assess the causal role of biases in maintaining anxiety and depression. Within the health psychology field, there is burgeoning interest in applying these experimental methods to assess potential cognitive biases in relation to physical health conditions and health-related behaviours. Experimental research in these areas could inform theoretical development by enabling measurement of implicit cognitive processes that may underlie unhelpful illness beliefs and help drive health-related behaviours. However, to date, there has been no systematic approach to adapting existing experimental paradigms for use within physical health research. Many studies fail to report how materials were developed for the population of interest or have used untested materials developed ad hoc. The lack of protocol for developing stimuli specificity has contributed to large heterogeneity in methodologies and findings. In this article, we emphasize the need for standardized methods for stimuli development and replication in experimental work, particularly as it extends beyond its original anxiety and depression scope to other physical conditions. We briefly describe the paradigms commonly used to assess cognitive biases in attention and interpretation and then describe the steps involved in comprehensive/robust stimuli development for attention and interpretation paradigms using illustrative examples from two conditions: chronic fatigue syndrome and breast cancer. This article highlights the value of preforming rigorous stimuli development and provides tools to aid researchers engage in this process. We believe this work is worthwhile to establish a body of high-quality and replicable experimental research within the health psychology literature. Statement of contribution What is already known on this subject? Cognitive

Context effects and observer bias--implications for forensic odontology.

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Page, Mark; Taylor, Jane; Blenkin, Matt

2012-01-01

Psychologists have long recognized the effects of contextual and extraneous information on decision making. Such information renders the subject susceptible to both motivational and cognitive bias; yet, it is difficult to assess the extent to which these influence forensic odontologists opinions as there have been no studies to date on this subject. This article explores the various types of contextual effects and biasing influences that potentially impact on the analysis of bitemarks in forensic odontology. It appears that the current practice of bitemark analysis is rich in sources of potentially biasing influences. In addition to the fundamental recognition that some form of bias is likely to exist, ways in which these should be minimized include: separation of the collection and analysis phases; limiting the amount of contextual information available to the odontologist responsible for the analysis; and ensuring that evidence that is ambiguous or of poor quality is identified as such prior to analysis. © 2011 American Academy of Forensic Sciences.

Long-branch attraction bias and inconsistency in Bayesian phylogenetics.

Directory of Open Access Journals (Sweden)

Bryan Kolaczkowski

Full Text Available Bayesian inference (BI of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML, so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI's long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias--which is apparent under both controlled simulation conditions and in analyses of empirical sequence data--also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI's bias is caused by one of the method's stated advantages--that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis.

Sources of bias in clinical ethics case deliberation.

Science.gov (United States)

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.

Approach bias for food cues in obese individuals.

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Kemps, Eva; Tiggemann, Marika

2015-01-01

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

Cognitive bias in symptomatic and recovered agoraphobics.

Science.gov (United States)

Stoler, L S; McNally, R J

1991-01-01

Symptomatic agoraphobics, recovered agoraphobics, and normal control subjects completed a series of sentence stems that had either ambiguous or unambiguous meanings, and had either a potentially threatening or a nonthreatening connotation. The written completions made by subjects to these stems were classified as indicating either a biased (i.e. threat-related) or unbiased interpretation of the meaning of the stem, and if a biased interpretation was made, whether the subject indicated efforts at adaptive coping with the perceived threat. Results indicated that symptomatic agoraphobics exhibited strong biases for interpreting information as threatening, relative to normal control subjects. Moreover, recovered agoraphobics resembled symptomatic agoraphobics more than normal control subjects, thus indicating that cognitive biases may persist following cessation of panic attacks and reductions in avoidance behavior. However, recovered agoraphobics also exhibited tendencies to cope adaptively with perceived threats whereas symptomatic agoraphobics did not.

Robust Control Methods for On-Line Statistical Learning

Directory of Open Access Journals (Sweden)

Capobianco Enrico

2001-01-01

Full Text Available The issue of controlling that data processing in an experiment results not affected by the presence of outliers is relevant for statistical control and learning studies. Learning schemes should thus be tested for their capacity of handling outliers in the observed training set so to achieve reliable estimates with respect to the crucial bias and variance aspects. We describe possible ways of endowing neural networks with statistically robust properties by defining feasible error criteria. It is convenient to cast neural nets in state space representations and apply both Kalman filter and stochastic approximation procedures in order to suggest statistically robustified solutions for on-line learning.

Nonlinear robust hierarchical control for nonlinear uncertain systems

Directory of Open Access Journals (Sweden)

Leonessa Alexander

1999-01-01

Full Text Available A nonlinear robust control-system design framework predicated on a hierarchical switching controller architecture parameterized over a set of moving nominal system equilibria is developed. Specifically, using equilibria-dependent Lyapunov functions, a hierarchical nonlinear robust control strategy is developed that robustly stabilizes a given nonlinear system over a prescribed range of system uncertainty by robustly stabilizing a collection of nonlinear controlled uncertain subsystems. The robust switching nonlinear controller architecture is designed based on a generalized (lower semicontinuous Lyapunov function obtained by minimizing a potential function over a given switching set induced by the parameterized nominal system equilibria. The proposed framework robustly stabilizes a compact positively invariant set of a given nonlinear uncertain dynamical system with structured parametric uncertainty. Finally, the efficacy of the proposed approach is demonstrated on a jet engine propulsion control problem with uncertain pressure-flow map data.

Galaxy Bias and its Effects on the Baryon Acoustic Oscillations Measurements

International Nuclear Information System (INIS)

Mehta, Kushal T.; Seo, Hee-Jong; Eckel, Jonathan; Eisenstein, Daniel J.; Metchnik, Marc; Pinto, Philip; Xu, Xiaoying

2011-01-01

The baryon acoustic oscillation (BAO) feature in the clustering of matter in the universe serves as a robust standard ruler and hence can be used to map the expansion history of the universe. We use high force resolution simulations to analyze the effects of galaxy bias on the measurements of the BAO signal. We apply a variety of Halo Occupation Distributions (HODs) and produce biased mass tracers to mimic different galaxy populations. We investigate whether galaxy bias changes the non-linear shifts on the acoustic scale relative to the underlying dark matter distribution presented by Seo et al. (2009). For the less biased HOD models (b 3) show a shift at moderate significance (0.79% ± 0.31% for the most extreme case). We test the one-step reconstruction technique introduced by Eisenstein et al. (2007) in the case of realistic galaxy bias and shot noise. The reconstruction scheme increases the correlation between the initial and final (z = 1) density fields achieving an equivalent level of correlation at nearly twice the wavenumber after reconstruction. Reconstruction reduces the shifts and errors on the shifts. We find that after reconstruction the shifts from the galaxy cases and the dark matter case are consistent with each other and with no shift. The 1σ systematic errors on the distance measurements inferred from our BAO measurements with various HODs after reconstruction are about 0.07%-0.15%.

Eliminating the Effect of Rating Bias on Reputation Systems

Directory of Open Access Journals (Sweden)

Leilei Wu

2018-01-01

Full Text Available The ongoing rapid development of the e-commercial and interest-base websites makes it more pressing to evaluate objects’ accurate quality before recommendation. The objects’ quality is often calculated based on their historical information, such as selected records or rating scores. Usually high quality products obtain higher average ratings than low quality products regardless of rating biases or errors. However, many empirical cases demonstrate that consumers may be misled by rating scores added by unreliable users or deliberate tampering. In this case, users’ reputation, that is, the ability to rate trustily and precisely, makes a big difference during the evaluation process. Thus, one of the main challenges in designing reputation systems is eliminating the effects of users’ rating bias. To give an objective evaluation of each user’s reputation and uncover an object’s intrinsic quality, we propose an iterative balance (IB method to correct users’ rating biases. Experiments on two datasets show that the IB method is a highly self-consistent and robust algorithm and it can accurately quantify movies’ actual quality and users’ stability of rating. Compared with existing methods, the IB method has higher ability to find the “dark horses,” that is, not so popular yet good movies, in the Academy Awards.

Multicultural experiences reduce intergroup bias through epistemic unfreezing.

Science.gov (United States)

Tadmor, Carmit T; Hong, Ying-Yi; Chao, Melody M; Wiruchnipawan, Fon; Wang, Wei

2012-11-01

In 6 studies, we systematically explored for the 1st time the ameliorative effects of multicultural experience on intergroup bias and investigated the role of epistemic unfreezing as the motivational mechanism underlying these effects. We found that multicultural exposure led to a reduction in stereotype endorsement (Studies 1, 4, and 6), symbolic racism (Study 5), and discriminatory hiring decisions (Study 2). We further demonstrated that experimental exposure to multicultural experience caused a reduction in need for cognitive closure (NFCC; Studies 3 and 6) and that the ameliorative effects of multiculturalism experience on intergroup bias were fully mediated by lower levels of NFCC (Studies 4, 5, and 6). The beneficial effects of multiculturalism were found regardless of the targeted stereotype group (African Americans, Ethiopians, homosexuals, and native Israelis), regardless of whether multicultural experience was measured or manipulated, and regardless of the population sampled (Caucasian Americans or native Israelis), demonstrating the robustness of this phenomenon. Overall, these results demonstrate that multicultural experience plays a critical role in increasing social tolerance through its relationship to motivated cognitive processes.

Robust PV Degradation Methodology and Application

Energy Technology Data Exchange (ETDEWEB)

Jordan, Dirk [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Deline, Christopher A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kurtz, Sarah [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kimball, Greg [SunPower; Anderson, Mike [SunPower

2017-11-15

The degradation rate plays an important role in predicting and assessing the long-term energy generation of PV systems. Many methods have been proposed for extracting the degradation rate from operational data of PV systems, but most of the published approaches are susceptible to bias due to inverter clipping, module soiling, temporary outages, seasonality, and sensor degradation. In this manuscript, we propose a methodology for determining PV degradation leveraging available modeled clear-sky irradiance data rather than site sensor data, and a robust year-over-year (YOY) rate calculation. We show the method to provide reliable degradation rate estimates even in the case of sensor drift, data shifts, and soiling. Compared with alternate methods, we demonstrate that the proposed method delivers the lowest uncertainty in degradation rate estimates for a fleet of 486 PV systems.

Robustness of digital artist authentication

DEFF Research Database (Denmark)

Jacobsen, Robert; Nielsen, Morten

In many cases it is possible to determine the authenticity of a painting from digital reproductions of the paintings; this has been demonstrated for a variety of artists and with different approaches. Common to all these methods in digital artist authentication is that the potential of the method...... is in focus, while the robustness has not been considered, i.e. the degree to which the data collection process influences the decision of the method. However, in order for an authentication method to be successful in practice, it needs to be robust to plausible error sources from the data collection....... In this paper we investigate the robustness of the newly proposed authenticity method introduced by the authors based on second generation multiresolution analysis. This is done by modelling a number of realistic factors that can occur in the data collection....

A method for additive bias correction in cross-cultural surveys

DEFF Research Database (Denmark)

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

2001-01-01

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

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

Science.gov (United States)

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

2003-10-01

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

Low-bias flat band-stop filter based on velocity modulated gaussian graphene superlattice

Science.gov (United States)

Sattari-Esfahlan, S. M.; Shojaei, S.

2018-05-01

Transport properties of biased planar Gaussian graphene superlattice (PGGSL) with Fermi velocity barrier is investigated by transfer matrix method (TMM). It is observed that enlargement of bias voltage over miniband width breaks the miniband to WSLs leads to suppressing resonant tunneling. Transmission spectrum shows flat wide stop-band property controllable by external bias voltage with stop-band width of near 200 meV. The simulations demonstrate that strong velocity barriers prevent tunneling of Dirac electrons leading to controllable enhancement of stop-band width. By increasing ratio of Fermi velocity in barriers to wells υc stop-band width increase. As wide transmission stop-band width (BWT) of filter is tunable from 40 meV to 340 meV is obtained by enhancing ratio of υc from 0.2 to 1.5, respectively. Proposed structure suggests easy tunable wide band-stop electronic filter with a modulated flat stop-band characteristic by height of electrostatic barrier and structural parameters. Robust sensitivity of band width to velocity barrier intensity in certain bias voltages and flat band feature of proposed filter may be opens novel venue in GSL based flat band low noise filters and velocity modulation devices.

Colour vision and response bias in a coral reef fish.

Science.gov (United States)

Cheney, Karen L; Newport, Cait; McClure, Eva C; Marshall, N Justin

2013-08-01

Animals use coloured signals for a variety of communication purposes, including to attract potential mates, recognize individuals, defend territories and warn predators of secondary defences (aposematism). To understand the mechanisms that drive the evolution and design of such visual signals, it is important to understand the visual systems and potential response biases of signal receivers. Here, we provide raw data on the spectral capabilities of a coral reef fish, the Picasso triggerfish Rhinecanthus aculeatus, which is potentially trichromatic with three cone sensitivities of 413 nm (single cone), 480 nm (double cone, medium sensitivity) and 528 nm (double cone, long sensitivity), and a rod sensitivity of 498 nm. The ocular media have a 50% transmission cut off at 405 nm. Behavioural experiments confirmed colour vision over their spectral range; triggerfish were significantly more likely to choose coloured stimuli over grey distractors, irrespective of luminance. We then examined whether response biases existed towards coloured and patterned stimuli to provide insight into how visual signals - in particular, aposematic colouration - may evolve. Triggerfish showed a preferential foraging response bias to red and green stimuli, in contrast to blue and yellow, irrespective of pattern. There was no response bias to patterned over monochromatic non-patterned stimuli. A foraging response bias towards red in fish differs from that of avian predators, who often avoid red food items. Red is frequently associated with warning colouration in terrestrial environments (ladybirds, snakes, frogs), whilst blue is used in aquatic environments (blue-ringed octopus, nudibranchs); whether the design of warning (aposematic) displays is a cause or consequence of response biases is unclear.

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

Science.gov (United States)

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

2012-01-01

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

Effects of Cognitive Bias Modification Training via Smartphones

OpenAIRE

Ranming Yang; Ranming Yang; Lixia Cui; Feng Li; Jing Xiao; Qin Zhang; Tian P. S. Oei; Tian P. S. Oei

2017-01-01

Background and Objectives: Negative cognitive biases have been linked to anxiety and mood problems. Accumulated data from laboratory studies show that positive and negative interpretation styles with accompanying changes in mood can be induced through cognitive bias modification (CBM) paradigms. Despite the therapeutic potential of positive training effects, few studies have explored training paradigms administered via smartphones. The current study aimed to compare the effectiveness of three...

Attentional bias modification encourages healthy eating.

Science.gov (United States)

Kakoschke, Naomi; Kemps, Eva; Tiggemann, Marika

2014-01-01

The continual exposure to unhealthy food cues in the environment encourages poor dietary habits, in particular consuming too much fat and sugar, and not enough fruit and vegetables. According to Berridge's (2009) model of food reward, unhealthy eating is a behavioural response to biased attentional processing. The present study used an established attentional bias modification paradigm to discourage the consumption of unhealthy food and instead promote healthy eating. Participants were 146 undergraduate women who were randomly assigned to two groups: one was trained to direct their attention toward pictures of healthy food ('attend healthy' group) and the other toward unhealthy food ('attend unhealthy' group). It was found that participants trained to attend to healthy food cues demonstrated an increased attentional bias for such cues and ate relatively more of the healthy than unhealthy snacks compared to the 'attend unhealthy' group. Theoretically, the results support the postulated link between biased attentional processing and consumption (Berridge, 2009). At a practical level, they offer potential scope for interventions that focus on eating well. Copyright © 2013 Elsevier Ltd. All rights reserved.

Robustness Issues for Design of Innovative Timber Structures

DEFF Research Database (Denmark)

Hald, Frederik; Kirkegaard, Poul Henning; Sørensen, John Dalsgaard

2013-01-01

Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious conse-quences in case of failure. The present paper summaries issues with respect to robustness of timber structures. Two different...... large span timber structures are analyzed and based on these analyses the paper presents guidelines for the future development of innovative timber struc-tures which are robust with respect to design and execution errors, unforeseen degradation and other potential hazards....

Sympathetic bias.

Science.gov (United States)

Levy, David M; Peart, Sandra J

2008-06-01

We wish to deal with investigator bias in a statistical context. We sketch how a textbook solution to the problem of "outliers" which avoids one sort of investigator bias, creates the temptation for another sort. We write down a model of the approbation seeking statistician who is tempted by sympathy for client to violate the disciplinary standards. We give a simple account of one context in which we might expect investigator bias to flourish. Finally, we offer tentative suggestions to deal with the problem of investigator bias which follow from our account. As we have given a very sparse and stylized account of investigator bias, we ask what might be done to overcome this limitation.

Incentive-Compatible Robust Line Planning

Science.gov (United States)

Bessas, Apostolos; Kontogiannis, Spyros; Zaroliagis, Christos

The problem of robust line planning requests for a set of origin-destination paths (lines) along with their frequencies in an underlying railway network infrastructure, which are robust to fluctuations of real-time parameters of the solution. In this work, we investigate a variant of robust line planning stemming from recent regulations in the railway sector that introduce competition and free railway markets, and set up a new application scenario: there is a (potentially large) number of line operators that have their lines fixed and operate as competing entities issuing frequency requests, while the management of the infrastructure itself remains the responsibility of a single entity, the network operator. The line operators are typically unwilling to reveal their true incentives, while the network operator strives to ensure a fair (or socially optimal) usage of the infrastructure, e.g., by maximizing the (unknown to him) aggregate incentives of the line operators.

PARAMETER COORDINATION AND ROBUST OPTIMIZATION FOR MULTIDISCIPLINARY DESIGN

Institute of Scientific and Technical Information of China (English)

HU Jie; PENG Yinghong; XIONG Guangleng

2006-01-01

A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.

Introducing etch kernels for efficient pattern sampling and etch bias prediction

Science.gov (United States)

Weisbuch, François; Lutich, Andrey; Schatz, Jirka

2018-01-01

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

Combination of biased forecasts: Bias correction or bias based weights?

OpenAIRE

Wenzel, Thomas

1999-01-01

Most of the literature on combination of forecasts deals with the assumption of unbiased individual forecasts. Here, we consider the case of biased forecasts and discuss two different combination techniques resulting in an unbiased forecast. On the one hand we correct the individual forecasts, and on the other we calculate bias based weights. A simulation study gives some insight in the situations where we should use the different methods.

Estimation bias and bias correction in reduced rank autoregressions

DEFF Research Database (Denmark)

Nielsen, Heino Bohn

2017-01-01

This paper characterizes the finite-sample bias of the maximum likelihood estimator (MLE) in a reduced rank vector autoregression and suggests two simulation-based bias corrections. One is a simple bootstrap implementation that approximates the bias at the MLE. The other is an iterative root...

Potential bias factors that affect the course evaluation of students in preclinical courses

Directory of Open Access Journals (Sweden)

Su Jin Chae

2017-06-01

Full Text Available Purpose We aim to identify what potential bias factors affected students’ overall course evaluation, and to observe what factors should be considered in the curriculum evaluation system of medical schools. Methods This study analyzed students’ ratings of preclinical instructions at the Ajou University School of Medicine. The ratings of instructions involved 41 first-year and 45 second-year medical students. Results There was a statistically significant difference between years of study and ratings’ scoring. Learning difficulty, learning amount, student assessment, and teacher preparation from second-year students were significantly higher than first-year students (p<0.05. The analysis results revealed that student assessment was the predictor of ratings from first-year students, while teacher preparation was the predictor of ratings from second-year students. Conclusion We found significant interactions between year of study and the students’ rating results. We were able to confirm that satisfaction of instructions factors perceived by medical students were different for the characteristics of courses. Our results may be an important resource for evaluating preclinical curriculums.

Affective Biases in Humans and Animals.

Science.gov (United States)

Robinson, E S J; Roiser, J P

Depression is one of the most common but poorly understood psychiatric conditions. Although drug treatments and psychological therapies are effective in some patients, many do not achieve full remission and some patients receive no apparent benefit. Developing new improved treatments requires a better understanding of the aetiology of symptoms and evaluation of novel therapeutic targets in pre-clinical studies. Recent developments in our understanding of the basic cognitive processes that may contribute to the development of depression and its treatment offer new opportunities for both clinical and pre-clinical research. This chapter discusses the clinical evidence supporting a cognitive neuropsychological model of depression and antidepressant efficacy, and how this information may be usefully translated to pre-clinical investigation. Studies using neuropsychological tests in depressed patients and at risk populations have revealed basic negative emotional biases and disrupted reward and punishment processing, which may also impact on non-affective cognition. These affective biases are sensitive to antidepressant treatments with early onset effects observed, suggesting an important role in recovery. This clinical work into affective biases has also facilitated back-translation to animals and the development of assays to study affective biases in rodents. These animal studies suggest that, similar to humans, rodents in putative negative affective states exhibit negative affective biases on decision-making and memory tasks. Antidepressant treatments also induce positive biases in these rodent tasks, supporting the translational validity of this approach. Although still in the early stages of development and validation, affective biases in depression have the potential to offer new insights into the clinical condition, as well as facilitating the development of more translational approaches for pre-clinical studies.

Design of Robust Neural Network Classifiers

DEFF Research Database (Denmark)

Larsen, Jan; Andersen, Lars Nonboe; Hintz-Madsen, Mads

1998-01-01

This paper addresses a new framework for designing robust neural network classifiers. The network is optimized using the maximum a posteriori technique, i.e., the cost function is the sum of the log-likelihood and a regularization term (prior). In order to perform robust classification, we present...... a modified likelihood function which incorporates the potential risk of outliers in the data. This leads to the introduction of a new parameter, the outlier probability. Designing the neural classifier involves optimization of network weights as well as outlier probability and regularization parameters. We...... suggest to adapt the outlier probability and regularisation parameters by minimizing the error on a validation set, and a simple gradient descent scheme is derived. In addition, the framework allows for constructing a simple outlier detector. Experiments with artificial data demonstrate the potential...

Oxytocin eliminates the own-race bias in face recognition memory☆

Science.gov (United States)

Blandón-Gitlin, Iris; Pezdek, Kathy; Saldivar, Sesar; Steelman, Erin

2015-01-01

The neuropeptide Oxytocin influences a number of social behaviors, including processing of faces. We examined whether Oxytocin facilitates the processing of out-group faces and reduce the own-race bias (ORB). The ORB is a robust phenomenon characterized by poor recognition memory of other-race faces compared to the same-race faces. In Experiment 1, participants received intranasal solutions of Oxytocin or placebo prior to viewing White and Black faces. On a subsequent recognition test, whereas in the placebo condition the same-race faces were better recognized than other-race faces, in the Oxytocin condition Black and White faces were equally well recognized, effectively eliminating the ORB. In Experiment 2, Oxytocin was administered after the study phase. The ORB resulted, but Oxytocin did not significantly reduce the effect. This study is the first to show that Oxytocin can enhance face memory of out-group members and underscore the importance of social encoding mechanisms underlying the own-race bias. PMID:23872107

Potential of bias correction for downscaling passive microwave and soil moisture data

Science.gov (United States)

Passive microwave satellites such as SMOS (Soil Moisture and Ocean Salinity) or SMAP (Soil Moisture Active Passive) observe brightness temperature (TB) and retrieve soil moisture at a spatial resolution greater than most hydrological processes. Bias correction is proposed as a simple method to disag...

Biases in Visual, Auditory, and Audiovisual Perception of Space

Science.gov (United States)

Odegaard, Brian; Wozny, David R.; Shams, Ladan

2015-01-01

Localization of objects and events in the environment is critical for survival, as many perceptual and motor tasks rely on estimation of spatial location. Therefore, it seems reasonable to assume that spatial localizations should generally be accurate. Curiously, some previous studies have reported biases in visual and auditory localizations, but these studies have used small sample sizes and the results have been mixed. Therefore, it is not clear (1) if the reported biases in localization responses are real (or due to outliers, sampling bias, or other factors), and (2) whether these putative biases reflect a bias in sensory representations of space or a priori expectations (which may be due to the experimental setup, instructions, or distribution of stimuli). Here, to address these questions, a dataset of unprecedented size (obtained from 384 observers) was analyzed to examine presence, direction, and magnitude of sensory biases, and quantitative computational modeling was used to probe the underlying mechanism(s) driving these effects. Data revealed that, on average, observers were biased towards the center when localizing visual stimuli, and biased towards the periphery when localizing auditory stimuli. Moreover, quantitative analysis using a Bayesian Causal Inference framework suggests that while pre-existing spatial biases for central locations exert some influence, biases in the sensory representations of both visual and auditory space are necessary to fully explain the behavioral data. How are these opposing visual and auditory biases reconciled in conditions in which both auditory and visual stimuli are produced by a single event? Potentially, the bias in one modality could dominate, or the biases could interact/cancel out. The data revealed that when integration occurred in these conditions, the visual bias dominated, but the magnitude of this bias was reduced compared to unisensory conditions. Therefore, multisensory integration not only improves the

Biases in Visual, Auditory, and Audiovisual Perception of Space.

Directory of Open Access Journals (Sweden)

Brian Odegaard

2015-12-01

Full Text Available Localization of objects and events in the environment is critical for survival, as many perceptual and motor tasks rely on estimation of spatial location. Therefore, it seems reasonable to assume that spatial localizations should generally be accurate. Curiously, some previous studies have reported biases in visual and auditory localizations, but these studies have used small sample sizes and the results have been mixed. Therefore, it is not clear (1 if the reported biases in localization responses are real (or due to outliers, sampling bias, or other factors, and (2 whether these putative biases reflect a bias in sensory representations of space or a priori expectations (which may be due to the experimental setup, instructions, or distribution of stimuli. Here, to address these questions, a dataset of unprecedented size (obtained from 384 observers was analyzed to examine presence, direction, and magnitude of sensory biases, and quantitative computational modeling was used to probe the underlying mechanism(s driving these effects. Data revealed that, on average, observers were biased towards the center when localizing visual stimuli, and biased towards the periphery when localizing auditory stimuli. Moreover, quantitative analysis using a Bayesian Causal Inference framework suggests that while pre-existing spatial biases for central locations exert some influence, biases in the sensory representations of both visual and auditory space are necessary to fully explain the behavioral data. How are these opposing visual and auditory biases reconciled in conditions in which both auditory and visual stimuli are produced by a single event? Potentially, the bias in one modality could dominate, or the biases could interact/cancel out. The data revealed that when integration occurred in these conditions, the visual bias dominated, but the magnitude of this bias was reduced compared to unisensory conditions. Therefore, multisensory integration not only

Uncertainty plus prior equals rational bias: an intuitive Bayesian probability weighting function.

Science.gov (United States)

Fennell, John; Baddeley, Roland

2012-10-01

Empirical research has shown that when making choices based on probabilistic options, people behave as if they overestimate small probabilities, underestimate large probabilities, and treat positive and negative outcomes differently. These distortions have been modeled using a nonlinear probability weighting function, which is found in several nonexpected utility theories, including rank-dependent models and prospect theory; here, we propose a Bayesian approach to the probability weighting function and, with it, a psychological rationale. In the real world, uncertainty is ubiquitous and, accordingly, the optimal strategy is to combine probability statements with prior information using Bayes' rule. First, we show that any reasonable prior on probabilities leads to 2 of the observed effects; overweighting of low probabilities and underweighting of high probabilities. We then investigate 2 plausible kinds of priors: informative priors based on previous experience and uninformative priors of ignorance. Individually, these priors potentially lead to large problems of bias and inefficiency, respectively; however, when combined using Bayesian model comparison methods, both forms of prior can be applied adaptively, gaining the efficiency of empirical priors and the robustness of ignorance priors. We illustrate this for the simple case of generic good and bad options, using Internet blogs to estimate the relevant priors of inference. Given this combined ignorant/informative prior, the Bayesian probability weighting function is not only robust and efficient but also matches all of the major characteristics of the distortions found in empirical research. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Hemispheric biases and the control of visuospatial attention: an ERP study

Directory of Open Access Journals (Sweden)

Banich Marie T

2005-08-01

Full Text Available Abstract Background We examined whether individual differences in hemispheric utilization can interact with the intrinsic attentional biases of the cerebral hemispheres. Evidence suggests that the hemispheres have competing biases to direct attention contralaterally, with the left hemisphere (LH having a stronger bias than the right hemisphere. There is also evidence that individuals have characteristic biases to utilize one hemisphere more than the other for processing information, which can induce a bias to direct attention to contralateral space. We predicted that LH-biased individuals would display a strong rightward attentional bias, which would create difficulty in selectively attending to target stimuli in the left visual field (LVF as compared to right in the performance of a bilateral flanker task. Results Consistent with our hypothesis, flanker interference effects were found on the N2c event-related brain potential and error rate for LH-biased individuals in the Attend-LVF condition. The error rate effect was correlated with the degree of hemispheric utilization bias for the LH-Bias group. Conclusion We conclude that hemispheric utilization bias can enhance a hemisphere's contralateral attentional bias, at least for individuals with a LH utilization bias. Hemispheric utilization bias may play an important and largely unrecognized role in visuospatial attention.

Robust design optimization using the price of robustness, robust least squares and regularization methods

Science.gov (United States)

Bukhari, Hassan J.

2017-12-01

In this paper a framework for robust optimization of mechanical design problems and process systems that have parametric uncertainty is presented using three different approaches. Robust optimization problems are formulated so that the optimal solution is robust which means it is minimally sensitive to any perturbations in parameters. The first method uses the price of robustness approach which assumes the uncertain parameters to be symmetric and bounded. The robustness for the design can be controlled by limiting the parameters that can perturb.The second method uses the robust least squares method to determine the optimal parameters when data itself is subjected to perturbations instead of the parameters. The last method manages uncertainty by restricting the perturbation on parameters to improve sensitivity similar to Tikhonov regularization. The methods are implemented on two sets of problems; one linear and the other non-linear. This methodology will be compared with a prior method using multiple Monte Carlo simulation runs which shows that the approach being presented in this paper results in better performance.

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

Science.gov (United States)

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

2014-01-01

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

A procedure for eliminating additive bias from cross-cultural survey data

DEFF Research Database (Denmark)

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

2005-01-01

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

Disruption avoidance in the SINP-Tokamak by means of electrode-biasing at the plasma edge

Energy Technology Data Exchange (ETDEWEB)

Basu, Debjyoti [Saha Institute of Nuclear Physics, 1/AF-Bidhannagar, Kolkata 700064, WB (India); Instituto de Ciencias Nucleares-UNAM, Mexico D.F. 04510 (Mexico); Pal, Rabindranath [Saha Institute of Nuclear Physics, 1/AF-Bidhannagar, Kolkata 700064, WB (India); Martinell, Julio J. [Instituto de Ciencias Nucleares-UNAM, Mexico D.F. 04510 (Mexico); Ghosh, Joydeep; Chattopadhyay, Prabal K. [Institute for Plasma Research, Gandhinagar (India)

2013-05-15

Control of plasma disruption by a biased edge electrode is reported in SINP-Tokamak. The features that characterize a plasma disruption are reduced with increasing bias potential. The disruption can be completely suppressed with the concomitant stabilization of observed MHD modes that are allegedly precursors of the disruption. An m = 3/n = 1 tearing mode, which apparently causes disruption can be stabilized when a negative biasing potential is applied near the edge. These changes in the disruptive behavior with edge biasing are hypothesized to be due to changes in the current density profile.

Disruption avoidance in the SINP-Tokamak by means of electrode-biasing at the plasma edge

International Nuclear Information System (INIS)

Basu, Debjyoti; Pal, Rabindranath; Martinell, Julio J.; Ghosh, Joydeep; Chattopadhyay, Prabal K.

2013-01-01

Control of plasma disruption by a biased edge electrode is reported in SINP-Tokamak. The features that characterize a plasma disruption are reduced with increasing bias potential. The disruption can be completely suppressed with the concomitant stabilization of observed MHD modes that are allegedly precursors of the disruption. An m = 3/n = 1 tearing mode, which apparently causes disruption can be stabilized when a negative biasing potential is applied near the edge. These changes in the disruptive behavior with edge biasing are hypothesized to be due to changes in the current density profile

Advection of Potential Temperature in the Atmosphere of Irradiated Exoplanets: A Robust Mechanism to Explain Radius Inflation

Science.gov (United States)

Tremblin, P.; Chabrier, G.; Mayne, N. J.; Amundsen, D. S.; Baraffe, I.; Debras, F.; Drummond, B.; Manners, J.; Fromang, S.

2017-01-01

The anomalously large radii of strongly irradiated exoplanets have remained a major puzzle in astronomy. Based on a two-dimensional steady-state atmospheric circulation model, the validity of which is assessed by comparison to three-dimensional calculations, we reveal a new mechanism, namely the advection of the potential temperature due to mass and longitudinal momentum conservation, a process occurring in the Earth's atmosphere or oceans. In the deep atmosphere, the vanishing heating flux forces the atmospheric structure to converge to a hotter adiabat than the one obtained with 1D calculations, implying a larger radius for the planet. Not only do the calculations reproduce the observed radius of HD 209458b, but also reproduce the observed correlation between radius inflation and irradiation for transiting planets. Vertical advection of potential temperature induced by non-uniform atmospheric heating thus provides a robust mechanism to explain the inflated radii of irradiated hot Jupiters.

Advection of Potential Temperature in the Atmosphere of Irradiated Exoplanets: A Robust Mechanism to Explain Radius Inflation

International Nuclear Information System (INIS)

Tremblin, P.; Chabrier, G.; Mayne, N. J.; Baraffe, I.; Debras, F.; Drummond, B.; Manners, J.; Amundsen, D. S.; Fromang, S.

2017-01-01

The anomalously large radii of strongly irradiated exoplanets have remained a major puzzle in astronomy. Based on a two-dimensional steady-state atmospheric circulation model, the validity of which is assessed by comparison to three-dimensional calculations, we reveal a new mechanism, namely the advection of the potential temperature due to mass and longitudinal momentum conservation, a process occurring in the Earth’s atmosphere or oceans. In the deep atmosphere, the vanishing heating flux forces the atmospheric structure to converge to a hotter adiabat than the one obtained with 1D calculations, implying a larger radius for the planet. Not only do the calculations reproduce the observed radius of HD 209458b, but also reproduce the observed correlation between radius inflation and irradiation for transiting planets. Vertical advection of potential temperature induced by non-uniform atmospheric heating thus provides a robust mechanism to explain the inflated radii of irradiated hot Jupiters.

Advection of Potential Temperature in the Atmosphere of Irradiated Exoplanets: A Robust Mechanism to Explain Radius Inflation

Energy Technology Data Exchange (ETDEWEB)

Tremblin, P. [Maison de la Simulation, CEA-CNRS-INRIA-UPS-UVSQ, USR 3441, CEA Paris-Saclay, F-91191 Gif-Sur-Yvette (France); Chabrier, G.; Mayne, N. J.; Baraffe, I.; Debras, F.; Drummond, B.; Manners, J. [Astrophysics Group, University of Exeter, EX4 4QL Exeter (United Kingdom); Amundsen, D. S. [Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10025 (United States); Fromang, S., E-mail: pascal.tremblin@cea.fr [Laboratoire AIM, CEA/DSM-CNRS-Université Paris 7, Irfu/Service d’Astrophysique, CEA Paris-Saclay, F-91191 Gif-sur-Yvette (France)

2017-05-20

The anomalously large radii of strongly irradiated exoplanets have remained a major puzzle in astronomy. Based on a two-dimensional steady-state atmospheric circulation model, the validity of which is assessed by comparison to three-dimensional calculations, we reveal a new mechanism, namely the advection of the potential temperature due to mass and longitudinal momentum conservation, a process occurring in the Earth’s atmosphere or oceans. In the deep atmosphere, the vanishing heating flux forces the atmospheric structure to converge to a hotter adiabat than the one obtained with 1D calculations, implying a larger radius for the planet. Not only do the calculations reproduce the observed radius of HD 209458b, but also reproduce the observed correlation between radius inflation and irradiation for transiting planets. Vertical advection of potential temperature induced by non-uniform atmospheric heating thus provides a robust mechanism to explain the inflated radii of irradiated hot Jupiters.

On the Borders of Harmful and Helpful Beauty Biases

Directory of Open Access Journals (Sweden)

Maria Agthe

2016-06-01

Full Text Available Research with European Caucasian samples demonstrates that attractiveness-based biases in social evaluation depend on the constellation of the sex of the evaluator and the sex of the target: Whereas people generally show positive biases toward attractive opposite-sex persons, they show less positive or even negative biases toward attractive same-sex persons. By examining these biases both within and between different ethnicities, the current studies provide new evidence for both the generalizability and the specificity of these attractiveness-based social perception biases. Examining within-ethnicity effects, Study 1 is the first to demonstrate that samples from diverse ethnic backgrounds parallel the finding of European Caucasian samples: The advantageous or adverse effects of attractiveness depend on the gender constellation of the evaluator and the evaluated person. Examining between-ethnicity effects, Study 2 found that these attractiveness-based biases emerge almost exclusively toward targets of the evaluator’s own ethnic background; these biases were reduced or eliminated for cross-ethnicity evaluations and interaction intentions. We discuss these findings in light of evolutionary principles and reflect on potential interactions between culture and evolved cognitive mechanisms.

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology

Science.gov (United States)

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental

Looking into the future: An inward bias in aesthetic experience driven only by gaze cues.

Science.gov (United States)

Chen, Yi-Chia; Colombatto, Clara; Scholl, Brian J

2018-07-01

The inward bias is an especially powerful principle of aesthetic experience: In framed images (e.g. photographs), we prefer peripheral figures that face inward (vs. outward). Why does this bias exist? Since agents tend to act in the direction in which they are facing, one intriguing possibility is that the inward bias reflects a preference to view scenes from a perspective that will allow us to witness those predicted future actions. This account has been difficult to test with previous displays, in which facing direction is often confounded with either global shape profiles or the relative locations of salient features (since e.g. someone's face is generally more visually interesting than the back of their head). But here we demonstrate a robust inward bias in aesthetic judgment driven by a cue that is socially powerful but visually subtle: averted gaze. Subjects adjusted the positions of people in images to maximize the images' aesthetic appeal. People with direct gaze were not placed preferentially in particular regions, but people with averted gaze were reliably placed so that they appeared to be looking inward. This demonstrates that the inward bias can arise from visually subtle features, when those features signal how future events may unfold. Copyright © 2018. Published by Elsevier B.V.

Effect of electro-acupuncture intervention on cognition attention bias in heroin addiction abstinence-a dot-probe-based event-related potential study.

Science.gov (United States)

Jiang, Ying-Ping; Liu, Hao; Xu, Ping; Wang, Yan; Lu, Guang-Hua

2011-04-01

To study the changes of cognitive attention-related brain function in the heroin addicts before and after electro-acupuncture (EA) intervention for exploring the concerned neuro-mechanism of addictive relapse and the central action role of EA intervention. Adopting event-related potential (ERP) technique, the ERP at 64 electrode spots in 10 heroin addicts (test group) were recorded before and after EA intervention with dot-probe experimental form during implementing cognitive task on positive emotional clue (PEC), negative emotional clues (NEC), and heroin-related clue (HRC). The P200 amplitude components on the selected observation points (Fz, Cz, and Pz) were analyzed and compared with those obtained from 10 healthy subjects as the control. Before EA, the ERP of attention on HRC in the test group was higher than that on PEC and NEC (Pattention on HRC at Cz and Pz was significantly lowered (P PEC > HRC, but in the control group, it showed PEC > HRC at all three observation points and PEC > NEC at Pz. Heroin addicts show attention bias to HRC, which could be significantly reduced by EA intervention, illustrating that EA could effectively inhibit the attention bias to heroin and so might have potential for lowering the relapse rate.

Advanced Biasing Experiments on the C-2 Field-Reversed Configuration Device

Science.gov (United States)

Thompson, Matthew; Korepanov, Sergey; Garate, Eusebio; Yang, Xiaokang; Gota, Hiroshi; Douglass, Jon; Allfrey, Ian; Valentine, Travis; Uchizono, Nolan; TAE Team

2014-10-01

The C-2 experiment seeks to study the evolution, heating and sustainment effects of neutral beam injection on field-reversed configuration (FRC) plasmas. Recently, substantial improvements in plasma performance were achieved through the application of edge biasing with coaxial plasma guns located in the divertors. Edge biasing provides rotation control that reduces instabilities and E × B shear that improves confinement. Typically, the plasma gun arcs are run at ~ 10 MW for the entire shot duration (~ 5 ms), which will become unsustainable as the plasma duration increases. We have conducted several advanced biasing experiments with reduced-average-power plasma gun operating modes and alternative biasing cathodes in an effort to develop an effective biasing scenario applicable to steady state FRC plasmas. Early results show that several techniques can potentially provide effective, long-duration edge biasing.

Magnification bias as a novel probe for primordial magnetic fields

International Nuclear Information System (INIS)

Camera, S.; Fedeli, C.; Moscardini, L.

2014-01-01

In this paper we investigate magnetic fields generated in the early Universe. These fields are important candidates at explaining the origin of astrophysical magnetism observed in galaxies and galaxy clusters, whose genesis is still by and large unclear. Compared to the standard inflationary power spectrum, intermediate to small scales would experience further substantial matter clustering, were a cosmological magnetic field present prior to recombination. As a consequence, the bias and redshift distribution of galaxies would also be modified. Hitherto, primordial magnetic fields (PMFs) have been tested and constrained with a number of cosmological observables, e.g. the cosmic microwave background radiation, galaxy clustering and, more recently, weak gravitational lensing. Here, we explore the constraining potential of the density fluctuation bias induced by gravitational lensing magnification onto the galaxy-galaxy angular power spectrum. Such an effect is known as magnification bias. Compared to the usual galaxy clustering approach, magnification bias helps in lifting the pathological degeneracy present amongst power spectrum normalisation and galaxy bias. This is because magnification bias cross-correlates galaxy number density fluctuations of nearby objects with weak lensing distortions of high-redshift sources. Thus, it takes advantage of the gravitational deflection of light, which is insensitive to galaxy bias but powerful in constraining the density fluctuation amplitude. To scrutinise the potentiality of this method, we adopt a deep and wide-field spectroscopic galaxy survey. We show that magnification bias does contain important information on primordial magnetism, which will be useful in combination with galaxy clustering and shear. We find we shall be able to rule out at 95.4% CL amplitudes of PMFs larger than 5 × 10 −4 nG for values of the PMF power spectral index n B ∼ 0

Robust estimation of event-related potentials via particle filter.

Science.gov (United States)

Fukami, Tadanori; Watanabe, Jun; Ishikawa, Fumito

2016-03-01

In clinical examinations and brain-computer interface (BCI) research, a short electroencephalogram (EEG) measurement time is ideal. The use of event-related potentials (ERPs) relies on both estimation accuracy and processing time. We tested a particle filter that uses a large number of particles to construct a probability distribution. We constructed a simple model for recording EEG comprising three components: ERPs approximated via a trend model, background waves constructed via an autoregressive model, and noise. We evaluated the performance of the particle filter based on mean squared error (MSE), P300 peak amplitude, and latency. We then compared our filter with the Kalman filter and a conventional simple averaging method. To confirm the efficacy of the filter, we used it to estimate ERP elicited by a P300 BCI speller. A 400-particle filter produced the best MSE. We found that the merit of the filter increased when the original waveform already had a low signal-to-noise ratio (SNR) (i.e., the power ratio between ERP and background EEG). We calculated the amount of averaging necessary after applying a particle filter that produced a result equivalent to that associated with conventional averaging, and determined that the particle filter yielded a maximum 42.8% reduction in measurement time. The particle filter performed better than both the Kalman filter and conventional averaging for a low SNR in terms of both MSE and P300 peak amplitude and latency. For EEG data produced by the P300 speller, we were able to use our filter to obtain ERP waveforms that were stable compared with averages produced by a conventional averaging method, irrespective of the amount of averaging. We confirmed that particle filters are efficacious in reducing the measurement time required during simulations with a low SNR. Additionally, particle filters can perform robust ERP estimation for EEG data produced via a P300 speller. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Modified generalized method of moments for a robust estimation of polytomous logistic model

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Xiaoshan Wang

2014-07-01

Full Text Available The maximum likelihood estimation (MLE method, typically used for polytomous logistic regression, is prone to bias due to both misclassification in outcome and contamination in the design matrix. Hence, robust estimators are needed. In this study, we propose such a method for nominal response data with continuous covariates. A generalized method of weighted moments (GMWM approach is developed for dealing with contaminated polytomous response data. In this approach, distances are calculated based on individual sample moments. And Huber weights are applied to those observations with large distances. Mellow-type weights are also used to downplay leverage points. We describe theoretical properties of the proposed approach. Simulations suggest that the GMWM performs very well in correcting contamination-caused biases. An empirical application of the GMWM estimator on data from a survey demonstrates its usefulness.

Gender anomalies in stated preference surveys – are biases really gender dependent?

DEFF Research Database (Denmark)

Ladenburg, Jacob; Olsen, Søren Bøye

2010-01-01

The potential for a number of common but severe biases in stated preference method surveys being gender dependent has been largely overlooked in the literature. In this paper we summarize results from three Choice Experiment studies that find evidence in favor of gender differences in vulnerability...... set up a novel theoretical model, which provides an explanation for gender specific susceptibility to biases. We conclude that biases can indeed be gender dependent. Hence, researchers should not simply disregard potential gender differences, but rather take them into account and examine the extent...... of them when performing surveys. Finally, we give suggestions for future research in this area....

Perceptive biases in major depressive episode.

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Marine Naudin

Full Text Available INTRODUCTION: Alterations in emotional processing occur during a major depressive episode (MDE, and olfaction and facial expressions have implications in emotional and social interactions. To gain a better understanding of these processes, we characterized the perceptive sensorial biases, potential links, and potential remission after antidepressant treatment of MDE. METHODS: We recruited 22 patients with acute MDE, both before and after three months of antidepressant treatment, and 41 healthy volunteers matched by age and smoking status. The participants underwent a clinical assessment (Mini International Neuropsychiatry Interview, Montgomery-Åsberg Depression Rating Scale, State-Trait Anxiety Inventory, Physical and Social Anhedonia scales, Pleasure-Displeasure Scale, an olfactory evaluation (hedonic aspect, familiarity and emotional impact of odors, and a computerized Facial Affect Recognition task. RESULTS: MDE was associated with an olfactory bias concerning hedonic and emotional aspects, including negative olfactory alliesthesia (unpleasant odorants perceived as more unpleasant, facial emotion expression recognition (happy facial expressions, and in part olfactory anhedonia (pleasant odorants perceived as less pleasant. In addition, the results revealed that these impairments represent state markers of MDE, suggesting that the patients recovered the same sensory processing as healthy subjects after antidepressant treatment. DISCUSSION: This study demonstrated that MDE is associated with negative biases toward olfactory perception and the recognition of facial emotional expressions. The link between these two sensory parameters suggests common underlying processes.

Nonlinear vs. linear biasing in Trp-cage folding simulations

Energy Technology Data Exchange (ETDEWEB)

Spiwok, Vojtěch, E-mail: spiwokv@vscht.cz; Oborský, Pavel; Králová, Blanka [Department of Biochemistry and Microbiology, University of Chemistry and Technology, Prague, Technická 3, Prague 6 166 28 (Czech Republic); Pazúriková, Jana [Institute of Computer Science, Masaryk University, Botanická 554/68a, 602 00 Brno (Czech Republic); Křenek, Aleš [Institute of Computer Science, Masaryk University, Botanická 554/68a, 602 00 Brno (Czech Republic); Center CERIT-SC, Masaryk Univerzity, Šumavská 416/15, 602 00 Brno (Czech Republic)

2015-03-21

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.

Robust Learning Control Design for Quantum Unitary Transformations.

Science.gov (United States)

Wu, Chengzhi; Qi, Bo; Chen, Chunlin; Dong, Daoyi

2017-12-01

Robust control design for quantum unitary transformations has been recognized as a fundamental and challenging task in the development of quantum information processing due to unavoidable decoherence or operational errors in the experimental implementation of quantum operations. In this paper, we extend the systematic methodology of sampling-based learning control (SLC) approach with a gradient flow algorithm for the design of robust quantum unitary transformations. The SLC approach first uses a "training" process to find an optimal control strategy robust against certain ranges of uncertainties. Then a number of randomly selected samples are tested and the performance is evaluated according to their average fidelity. The approach is applied to three typical examples of robust quantum transformation problems including robust quantum transformations in a three-level quantum system, in a superconducting quantum circuit, and in a spin chain system. Numerical results demonstrate the effectiveness of the SLC approach and show its potential applications in various implementation of quantum unitary transformations.

Bias and Uncertainty in Regression-Calibrated Models of Groundwater Flow in Heterogeneous Media

DEFF Research Database (Denmark)

Cooley, R.L.; Christensen, Steen

2006-01-01

small. Model error is accounted for in the weighted nonlinear regression methodology developed to estimate θ* and assess model uncertainties by incorporating the second-moment matrix of the model errors into the weight matrix. Techniques developed by statisticians to analyze classical nonlinear...... are reduced in magnitude. Biases, correction factors, and confidence and prediction intervals were obtained for a test problem for which model error is large to test robustness of the methodology. Numerical results conform with the theoretical analysis....

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

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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.

Perceptual Robust Design

DEFF Research Database (Denmark)

Pedersen, Søren Nygaard

The research presented in this PhD thesis has focused on a perceptual approach to robust design. The results of the research and the original contribution to knowledge is a preliminary framework for understanding, positioning, and applying perceptual robust design. Product quality is a topic...... been presented. Therefore, this study set out to contribute to the understanding and application of perceptual robust design. To achieve this, a state-of-the-art and current practice review was performed. From the review two main research problems were identified. Firstly, a lack of tools...... for perceptual robustness was found to overlap with the optimum for functional robustness and at most approximately 2.2% out of the 14.74% could be ascribed solely to the perceptual robustness optimisation. In conclusion, the thesis have offered a new perspective on robust design by merging robust design...

Assessing the Potential for Bias From Nonresponse to a Study Follow-up Interview: An Example From the Agricultural Health Study.

Science.gov (United States)

Rinsky, Jessica L; Richardson, David B; Wing, Steve; Beard, John D; Alavanja, Michael; Beane Freeman, Laura E; Chen, Honglei; Henneberger, Paul K; Kamel, Freya; Sandler, Dale P; Hoppin, Jane A

2017-08-15

Prospective cohort studies are important tools for identifying causes of disease. However, these studies are susceptible to attrition. When information collected after enrollment is through interview or exam, attrition leads to missing information for nonrespondents. The Agricultural Health Study enrolled 52,394 farmers in 1993-1997 and collected additional information during subsequent interviews. Forty-six percent of enrolled farmers responded to the 2005-2010 interview; 7% of farmers died prior to the interview. We examined whether response was related to attributes measured at enrollment. To characterize potential bias from attrition, we evaluated differences in associations between smoking and incidence of 3 cancer types between the enrolled cohort and the subcohort of 2005-2010 respondents, using cancer registry information. In the subcohort we evaluated the ability of inverse probability weighting (IPW) to reduce bias. Response was related to age, state, race/ethnicity, education, marital status, smoking, and alcohol consumption. When exposure and outcome were associated and case response was differential by exposure, some bias was observed; IPW conditional on exposure and covariates failed to correct estimates. When response was nondifferential, subcohort and full-cohort estimates were similar, making IPW unnecessary. This example provides a demonstration of investigating the influence of attrition in cohort studies using information that has been self-reported after enrollment. © 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.

Recognizing Our Cultural Biases as Counsellor Supervisors: A Reflective Learning Approach

Science.gov (United States)

Brinson, Jesse A.

2004-01-01

This article encourages supervisors, in general, and counsellor supervisors, in particular, to engage in reflective learning as a way to identify their cultural biases. Awareness of counsellor bias has been addressed by ethical standards outlined for professional helpers. This article presents reflective learning as a potentially useful strategy…

Quantifying selective reporting and the Proteus phenomenon for multiple datasets with similar bias.

Directory of Open Access Journals (Sweden)

Thomas Pfeiffer

2011-03-01

Full Text Available Meta-analyses play an important role in synthesizing evidence from diverse studies and datasets that address similar questions. A major obstacle for meta-analyses arises from biases in reporting. In particular, it is speculated that findings which do not achieve formal statistical significance are less likely reported than statistically significant findings. Moreover, the patterns of bias can be complex and may also depend on the timing of the research results and their relationship with previously published work. In this paper, we present an approach that is specifically designed to analyze large-scale datasets on published results. Such datasets are currently emerging in diverse research fields, particularly in molecular medicine. We use our approach to investigate a dataset on Alzheimer's disease (AD that covers 1167 results from case-control studies on 102 genetic markers. We observe that initial studies on a genetic marker tend to be substantially more biased than subsequent replications. The chances for initial, statistically non-significant results to be published are estimated to be about 44% (95% CI, 32% to 63% relative to statistically significant results, while statistically non-significant replications have almost the same chance to be published as statistically significant replications (84%; 95% CI, 66% to 107%. Early replications tend to be biased against initial findings, an observation previously termed Proteus phenomenon: The chances for non-significant studies going in the same direction as the initial result are estimated to be lower than the chances for non-significant studies opposing the initial result (73%; 95% CI, 55% to 96%. Such dynamic patterns in bias are difficult to capture by conventional methods, where typically simple publication bias is assumed to operate. Our approach captures and corrects for complex dynamic patterns of bias, and thereby helps generating conclusions from published results that are more robust

Interwell radiative recombination in the presence of random potential fluctuations in GaAs/AlGaAs biased double quantum wells

DEFF Research Database (Denmark)

Timofeev, V.B.; Larionov, A.V.; Ioselevich, A.S.

1998-01-01

narrowing with temperature increase from 4.5 to 30 K. A theoretical model is presented which explains the observed narrowing in terms of lateral thermally activated tunneling of spatially separated e-h pairs localized by random potential fluctuations in the quantum wells. (C) 1998 American Institute......The interwell radiative recombination from biased double quantum wells (DQW) in pin GaAs/AlGaAs heterostructures is investigated at different temperatures and external electrical fields. The luminescence line of interwell recombination of spatially separated electron-hole pairs exhibits systematic...

Own-Group Face Recognition Bias: The Effects of Location and Reputation

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Linlin Yan

2017-10-01

Full Text Available In the present study, we examined whether social categorization based on university affiliation can induce an advantage in recognizing faces. Moreover, we investigated how the reputation or location of the university affected face recognition performance using an old/new paradigm. We assigned five different university labels to the faces: participants’ own university and four other universities. Among the four other university labels, we manipulated the academic reputation and geographical location of these universities relative to the participants’ own university. The results showed that an own-group face recognition bias emerged for faces with own-university labels comparing to those with other-university labels. Furthermore, we found a robust own-group face recognition bias only when the other university was located in a different city far away from participants’ own university. Interestingly, we failed to find the influence of university reputation on own-group face recognition bias. These results suggest that categorizing a face as a member of one’s own university is sufficient to enhance recognition accuracy and the location will play a more important role in the effect of social categorization on face recognition than reputation. The results provide insight into the role of motivational factors underlying the university membership in face perception.

Racial bias in implicit danger associations generalizes to older male targets.

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Gustav J W Lundberg

Full Text Available Across two experiments, we examined whether implicit stereotypes linking younger (~28-year-old Black versus White men with violence and criminality extend to older (~68-year-old Black versus White men. In Experiment 1, participants completed a sequential priming task wherein they categorized objects as guns or tools after seeing briefly-presented facial images of men who varied in age (younger versus older and race (Black versus White. In Experiment 2, we used different face primes of younger and older Black and White men, and participants categorized words as 'threatening' or 'safe.' Results consistently revealed robust racial biases in object and word identification: Dangerous objects and words were identified more easily (faster response times, lower error rates, and non-dangerous objects and words were identified less easily, after seeing Black face primes than after seeing White face primes. Process dissociation procedure analyses, which aim to isolate the unique contributions of automatic and controlled processes to task performance, further indicated that these effects were driven entirely by racial biases in automatic processing. In neither experiment did prime age moderate racial bias, suggesting that the implicit danger associations commonly evoked by younger Black versus White men appear to generalize to older Black versus White men.

Scanning of speechless comics changes spatial biases in mental model construction.

Science.gov (United States)

Román, Antonio; Flumini, Andrea; Santiago, Julio

2018-08-05

The mental representation of both time and number shows lateral spatial biases, which can be affected by habitual reading and writing direction. However, this effect is in place before children begin to read. One potential early cause is the experiences of looking at picture books together with a carer, as those images also follow the directionality of the script. What is the underlying mechanism for this effect? In the present study, we test the possibility that such experiences induce spatial biases in mental model construction, a mechanism which is a good candidate to induce the biases observed with numbers and times. We presented a speechless comic in either standard (left-to-right) or mirror-reversed (right-to-left) form to adult Spanish participants. We then asked them to draw the scene depicted by sentences like 'the square is between the cross and the circle'. The position of the lateral objects in these drawings reveals the spatial biases at work when building mental models in working memory. Under conditions of highly consistent directionality, the mirror comic changed pre-existing lateral biases. Processes of mental model construction in working memory stand as a potential mechanism for the generation of spatial biases for time and number.This article is part of the theme issue 'Varieties of abstract concepts: development, use and representation in the brain'. © 2018 The Author(s).

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

International Nuclear Information System (INIS)

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

2014-01-01

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 CO 2 , 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 CO 2 . 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

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

Science.gov (United States)

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

Robustness of Adaptive Survey Designs to Inaccuracy of Design Parameters

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Burger Joep

2017-09-01

Full Text Available Adaptive survey designs (ASDs optimize design features, given 1 the interactions between the design features and characteristics of sampling units and 2 a set of constraints, such as a budget and a minimum number of respondents. Estimation of the interactions is subject to both random and systematic error. In this article, we propose and evaluate four viewpoints to assess robustness of ASDs to inaccuracy of design parameter estimates: the effect of both imprecision and bias on both ASD structure and ASD performance. We additionally propose three distance measures to compare the structure of ASDs. The methodology is illustrated using a simple simulation study and a more complex but realistic case study on the Dutch Travel Survey. The proposed methodology can be applied to other ASD optimization problems. In our simulation study and case study, the ASD was fairly robust to imprecision, but not to realistic dynamics in the design parameters. To deal with the sensitivity of ASDs to changing design parameters, we recommend to learn and update the design parameters.

Journal bias or author bias?

Science.gov (United States)

Harris, Ian

2016-01-01

I read with interest the comment by Mark Wilson in the Indian Journal of Medical Ethics regarding bias and conflicts of interest in medical journals. Wilson targets one journal (the New England Journal of Medicine: NEJM) and one particular "scandal" to make his point that journals' decisions on publication are biased by commercial conflicts of interest (CoIs). It is interesting that he chooses the NEJM which, by his own admission, had one of the strictest CoI policies and had published widely on this topic. The feeling is that if the NEJM can be guilty, they can all be guilty.

Robust bearing estimation for 3-component stations

International Nuclear Information System (INIS)

CLAASSEN, JOHN P.

2000-01-01

A robust bearing estimation process for 3-component stations has been developed and explored. The method, called SEEC for Search, Estimate, Evaluate and Correct, intelligently exploits the inherent information in the arrival at every step of the process to achieve near-optimal results. In particular the approach uses a consistent framework to define the optimal time-frequency windows on which to make estimates, to make the bearing estimates themselves, to construct metrics helpful in choosing the better estimates or admitting that the bearing is immeasurable, and finally to apply bias corrections when calibration information is available to yield a single final estimate. The algorithm was applied to a small but challenging set of events in a seismically active region. It demonstrated remarkable utility by providing better estimates and insights than previously available. Various monitoring implications are noted from these findings

Developmental precursors of young school-age children's hostile attribution bias.

Science.gov (United States)

Choe, Daniel Ewon; Lane, Jonathan D; Grabell, Adam S; Olson, Sheryl L

2013-12-01

This prospective longitudinal study provides evidence of preschool-age precursors of hostile attribution bias in young school-age children, a topic that has received little empirical attention. We examined multiple risk domains, including laboratory and observational assessments of children's social-cognition, general cognitive functioning, effortful control, and peer aggression. Preschoolers (N = 231) with a more advanced theory-of-mind, better emotion understanding, and higher IQ made fewer hostile attributions of intent in the early school years. Further exploration of these significant predictors revealed that only certain components of these capacities (i.e., nonstereotypical emotion understanding, false-belief explanation, and verbal IQ) were robust predictors of a hostile attribution bias in young school-age children and were especially strong predictors among children with more advanced effortful control. These relations were prospective in nature-the effects of preschool variables persisted after accounting for similar variables at school age. We conclude by discussing the implications of our findings for future research and prevention. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Oxytocin eliminates the own-race bias in face recognition memory.

Science.gov (United States)

Blandón-Gitlin, Iris; Pezdek, Kathy; Saldivar, Sesar; Steelman, Erin

2014-09-11

The neuropeptide Oxytocin influences a number of social behaviors, including processing of faces. We examined whether Oxytocin facilitates the processing of out-group faces and reduce the own-race bias (ORB). The ORB is a robust phenomenon characterized by poor recognition memory of other-race faces compared to the same-race faces. In Experiment 1, participants received intranasal solutions of Oxytocin or placebo prior to viewing White and Black faces. On a subsequent recognition test, whereas in the placebo condition the same-race faces were better recognized than other-race faces, in the Oxytocin condition Black and White faces were equally well recognized, effectively eliminating the ORB. In Experiment 2, Oxytocin was administered after the study phase. The ORB resulted, but Oxytocin did not significantly reduce the effect. This study is the first to show that Oxytocin can enhance face memory of out-group members and underscore the importance of social encoding mechanisms underlying the own-race bias. This article is part of a Special Issue entitled Oxytocin and Social Behav. Copyright © 2013 Elsevier B.V. All rights reserved.

A Short note on Accent–bias, Social Identity and Ethnocentrism

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Rahul Chakraborty

2017-08-01

Full Text Available This paper discusses the interrelations among accent-based biases, social identity and ethnocentrism. Construction of social identity creates a set of ethnocentric values within a person, which indirectly or directly plays a pivotal role in generating accent related biases. Starting with Tajfel’s (1959 social identity theory and then the discussion of ethnocentrism, accent related biases have a long documented origin, development and consequences. People construct their social identity based on numerous variables and then their in-group and out-group memberships are established. Ethnocentrism, as a variable, influences listeners’ accent perception and subsequent judgment regarding their perceived accent. The degree of ethnocentrism is related to speakers’ potential accent biases. As legal safeguard against accent related biases is absent, active resistance and awareness-initiation are expected from speech language pathologists and the concerned community in general. Role of training institutions is discussed.

Evaluation of bias-correction methods for ensemble streamflow volume forecasts

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T. Hashino

2007-01-01

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

Effects of Cognitive Bias Modification Training via Smartphones

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Ranming Yang

2017-08-01

Full Text Available Background and Objectives: Negative cognitive biases have been linked to anxiety and mood problems. Accumulated data from laboratory studies show that positive and negative interpretation styles with accompanying changes in mood can be induced through cognitive bias modification (CBM paradigms. Despite the therapeutic potential of positive training effects, few studies have explored training paradigms administered via smartphones. The current study aimed to compare the effectiveness of three different types of training programmes (cognitive bias modification-attention, CBM-A; cognitive bias modification-interpretation, CBM-I; attention and interpretation modification, AIM administered via smart-phones by using a control condition (CC.Methods:Seventy-six undergraduate participants with high social anxiety (Liebowitz Social Anxiety Scale, LSAS ≥ 30 were randomly assigned to four groups: CBM-A (n = 20, CBM-I (n = 20, AIM (n = 16, and CC (n = 20.Results: The results showed that the effects of CBM training, CBM-I training, or AIM training vs. CC for attention yielded no significant differences in dot-probe attention bias scores. The CBM-I group showed significantly less threat interpretation and more benign interpretation than the CC group on interpretation bias scores.Conclusions: The present results supported the feasibility of delivering CBM-I via smartphones, but the effectiveness of CBM-A and AIM training via smartphones was limited.

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

Science.gov (United States)

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.

Designing Phononic Crystals with Wide and Robust Band Gaps

Science.gov (United States)

Jia, Zian; Chen, Yanyu; Yang, Haoxiang; Wang, Lifeng

2018-04-01

Phononic crystals (PnCs) engineered to manipulate and control the propagation of mechanical waves have enabled the design of a range of novel devices, such as waveguides, frequency modulators, and acoustic cloaks, for which wide and robust phononic band gaps are highly preferable. While numerous PnCs have been designed in recent decades, to the best of our knowledge, PnCs that possess simultaneous wide and robust band gaps (to randomness and deformations) have not yet been reported. Here, we demonstrate that by combining the band-gap formation mechanisms of Bragg scattering and local resonances (the latter one is dominating), PnCs with wide and robust phononic band gaps can be established. The robustness of the phononic band gaps are then discussed from two aspects: robustness to geometric randomness (manufacture defects) and robustness to deformations (mechanical stimuli). Analytical formulations further predict the optimal design parameters, and an uncertainty analysis quantifies the randomness effect of each designing parameter. Moreover, we show that the deformation robustness originates from a local resonance-dominant mechanism together with the suppression of structural instability. Importantly, the proposed PnCs require only a small number of layers of elements (three unit cells) to obtain broad, robust, and strong attenuation bands, which offer great potential in designing flexible and deformable phononic devices.

Designing Phononic Crystals with Wide and Robust Band Gaps

Energy Technology Data Exchange (ETDEWEB)

Chen, Yanyu [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jia, Zian [State University of New York at Stony Brook; Yang, Haoxiang [State University of New York at Stony Brook; Wang, Lifeng [State University of New York at Stony Brook

2018-04-16

Phononic crystals (PnCs) engineered to manipulate and control the propagation of mechanical waves have enabled the design of a range of novel devices, such as waveguides, frequency modulators, and acoustic cloaks, for which wide and robust phononic band gaps are highly preferable. While numerous PnCs have been designed in recent decades, to the best of our knowledge, PnCs that possess simultaneous wide and robust band gaps (to randomness and deformations) have not yet been reported. Here, we demonstrate that by combining the band-gap formation mechanisms of Bragg scattering and local resonances (the latter one is dominating), PnCs with wide and robust phononic band gaps can be established. The robustness of the phononic band gaps are then discussed from two aspects: robustness to geometric randomness (manufacture defects) and robustness to deformations (mechanical stimuli). Analytical formulations further predict the optimal design parameters, and an uncertainty analysis quantifies the randomness effect of each designing parameter. Moreover, we show that the deformation robustness originates from a local resonance-dominant mechanism together with the suppression of structural instability. Importantly, the proposed PnCs require only a small number of layers of elements (three unit cells) to obtain broad, robust, and strong attenuation bands, which offer great potential in designing flexible and deformable phononic devices.

A PET reconstruction formulation that enforces non-negativity in projection space for bias reduction in Y-90 imaging

Science.gov (United States)

Lim, Hongki; Dewaraja, Yuni K.; Fessler, Jeffrey A.

2018-02-01

Most existing PET image reconstruction methods impose a nonnegativity constraint in the image domain that is natural physically, but can lead to biased reconstructions. This bias is particularly problematic for Y-90 PET because of the low probability positron production and high random coincidence fraction. This paper investigates a new PET reconstruction formulation that enforces nonnegativity of the projections instead of the voxel values. This formulation allows some negative voxel values, thereby potentially reducing bias. Unlike the previously reported NEG-ML approach that modifies the Poisson log-likelihood to allow negative values, the new formulation retains the classical Poisson statistical model. To relax the non-negativity constraint embedded in the standard methods for PET reconstruction, we used an alternating direction method of multipliers (ADMM). Because choice of ADMM parameters can greatly influence convergence rate, we applied an automatic parameter selection method to improve the convergence speed. We investigated the methods using lung to liver slices of XCAT phantom. We simulated low true coincidence count-rates with high random fractions corresponding to the typical values from patient imaging in Y-90 microsphere radioembolization. We compared our new methods with standard reconstruction algorithms and NEG-ML and a regularized version thereof. Both our new method and NEG-ML allow more accurate quantification in all volumes of interest while yielding lower noise than the standard method. The performance of NEG-ML can degrade when its user-defined parameter is tuned poorly, while the proposed algorithm is robust to any count level without requiring parameter tuning.

Zero bias thermally stimulated currents in synthetic diamond

Science.gov (United States)

Mori, R.; Miglio, S.; Bruzzi, M.; Bogani, F.; De Sio, A.; Pace, E.

2009-06-01

Zero bias thermally stimulated currents (ZBTSCs) have been observed in single crystal high pressure high temperature (HPHT) and polycrystalline chemical vapor deposited (pCVD) diamond films. The ZBTSC technique is characterized by an increased sensitivity with respect to a standard TSC analysis. Due to the absence of the thermally activated background current, new TSC peaks have been observed in both HPHT and pCVD diamond films, related to shallow activation energies usually obscured by the emission of the dominant impurities. The ZBTSC peaks are explained in terms of defect discharge in the nonequilibrium potential distribution created by a nonuniform traps filling at the metal-diamond junctions. The electric field due to the charged defects has been estimated in a quasizero bias TSC experiment by applying an external bias.

Effect of top gate potential on bias-stress for dual gate amorphous indium-gallium-zinc-oxide thin film transistor

Energy Technology Data Exchange (ETDEWEB)

Chun, Minkyu; Um, Jae Gwang; Park, Min Sang; Chowdhury, Md Delwar Hossain; Jang, Jin, E-mail: jjang@khu.ac.kr [Advanced Display Research Center and Department of Information Display, Kyung Hee University, Seoul 02447 (Korea, Republic of)

2016-07-15

We report the abnormal behavior of the threshold voltage (V{sub TH}) shift under positive bias Temperature stress (PBTS) and negative bias temperature stress (NBTS) at top/bottom gate in dual gate amorphous indium-gallium-zinc-oxide (a-IGZO) thin-film transistors (TFTs). It is found that the PBTS at top gate shows negative transfer shift and NBTS shows positive transfer shift for both top and bottom gate sweep. The shift of bottom/top gate sweep is dominated by top gate bias (V{sub TG}), while bottom gate bias (V{sub BG}) is less effect than V{sub TG}. The X-ray photoelectron spectroscopy (XPS) depth profile provides the evidence of In metal diffusion to the top SiO{sub 2}/a-IGZO and also the existence of large amount of In{sup +} under positive top gate bias around top interfaces, thus negative transfer shift is observed. On the other hand, the formation of OH{sup −} at top interfaces under the stress of negative top gate bias shows negative transfer shift. The domination of V{sub TG} both on bottom/top gate sweep after PBTS/NBTS is obviously occurred due to thin active layer.

Assessing implicit gender bias in Medical Student Performance Evaluations.

Science.gov (United States)

Axelson, Rick D; Solow, Catherine M; Ferguson, Kristi J; Cohen, Michael B

2010-09-01

For medical schools, the increasing presence of women makes it especially important that potential sources of gender bias be identified and removed from student evaluation methods. Our study looked for patterns of gender bias in adjective data used to inform our Medical Student Performance Evaluations (MSPEs). Multigroup Confirmatory Factor Analysis (CFA) was used to model the latent structure of the adjectives attributed to students (n = 657) and to test for systematic scoring errors by gender. Gender bias was evident in two areas: (a) women were more likely than comparable men to be described as ''compassionate,'' ''sensitive,'' and ''enthusiastic'' and (b) men were more likely than comparable women to be seen as ''quick learners.'' The gender gap in ''quick learner'' attribution grows with increasing student proficiency; men's rate of increase is over twice that of women's. Technical and nontechnical approaches for ameliorating the impact of gender bias on student recommendations are suggested.

Influence of the impurity-scattering on zero-bias conductance peak in ferromagnet/insulator/d-wave superconductor junctions

CERN Document Server

Yoshida, N; Itoh, H; Tanaka, Y; Inoue, J I; Kashiwaya, S

2003-01-01

Effects of impurity-scattering on a zero-bias conductance peak in ferromagnet/insulator/d-wave superconductor junctions are theoretically studied. The impurities are introduced through the random potential in ferromagnets near the junction interface. As in the case of normal-metal/insulator/d-wave superconductor junctions, the magnitude of zero-bias conductance peak decreases with increasing the degree of disorder. However, when the magnitude of the exchange potential in ferromagnet is sufficiently large, the random potential can enhance the zero-bias conductance peak in ferromagnetic junctions. (author)

Robust multivariate analysis

CERN Document Server

J Olive, David

2017-01-01

This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given.  The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory.   The robust techniques  are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis.  A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...

MIDAS robust trend estimator for accurate GPS station velocities without step detection

Science.gov (United States)

Blewitt, Geoffrey; Kreemer, Corné; Hammond, William C.; Gazeaux, Julien

2016-03-01

Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil-Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj-xi)/(tj-ti) computed between all data pairs i > j. For normally distributed data, Theil-Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil-Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one-sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root-mean-square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences.

Direct integration of intensity-level data from Affymetrix and Illumina microarrays improves statistical power for robust reanalysis

Directory of Open Access Journals (Sweden)

Turnbull Arran K

2012-08-01

Full Text Available Abstract Background Affymetrix GeneChips and Illumina BeadArrays are the most widely used commercial single channel gene expression microarrays. Public data repositories are an extremely valuable resource, providing array-derived gene expression measurements from many thousands of experiments. Unfortunately many of these studies are underpowered and it is desirable to improve power by combining data from more than one study; we sought to determine whether platform-specific bias precludes direct integration of probe intensity signals for combined reanalysis. Results Using Affymetrix and Illumina data from the microarray quality control project, from our own clinical samples, and from additional publicly available datasets we evaluated several approaches to directly integrate intensity level expression data from the two platforms. After mapping probe sequences to Ensembl genes we demonstrate that, ComBat and cross platform normalisation (XPN, significantly outperform mean-centering and distance-weighted discrimination (DWD in terms of minimising inter-platform variance. In particular we observed that DWD, a popular method used in a number of previous studies, removed systematic bias at the expense of genuine biological variability, potentially reducing legitimate biological differences from integrated datasets. Conclusion Normalised and batch-corrected intensity-level data from Affymetrix and Illumina microarrays can be directly combined to generate biologically meaningful results with improved statistical power for robust, integrated reanalysis.

Surprise, Memory, and Retrospective Judgment Making: Testing Cognitive Reconstruction Theories of the Hindsight Bias Effect

Science.gov (United States)

Ash, Ivan K.

2009-01-01

Hindsight bias has been shown to be a pervasive and potentially harmful decision-making bias. A review of 4 competing cognitive reconstruction theories of hindsight bias revealed conflicting predictions about the role and effect of expectation or surprise in retrospective judgment formation. Two experiments tested these predictions examining the…

CPI Bias in Korea

Directory of Open Access Journals (Sweden)

Chul Chung

2007-12-01

Full Text Available We estimate the CPI bias in Korea by employing the approach of Engel’s Law as suggested by Hamilton (2001. This paper is the first attempt to estimate the bias using Korean panel data, Korean Labor and Income Panel Study(KLIPS. Following Hamilton’s model with non­linear specification correction, our estimation result shows that the cumulative CPI bias over the sample period (2000-2005 was 0.7 percent annually. This CPI bias implies that about 21 percent of the inflation rate during the period can be attributed to the bias. In light of purchasing power parity, we provide an interpretation of the estimated bias.

Opposing Forces of A/T-Biased Mutations and G/C-Biased Gene Conversions Shape the Genome of the Nematode Pristionchus pacificus

Science.gov (United States)

Weller, Andreas M.; Rödelsperger, Christian; Eberhardt, Gabi; Molnar, Ruxandra I.; Sommer, Ralf J.

2014-01-01

Base substitution mutations are a major source of genetic novelty and mutation accumulation line (MAL) studies revealed a nearly universal AT bias in de novo mutation spectra. While a comparison of de novo mutation spectra with the actual nucleotide composition in the genome suggests the existence of general counterbalancing mechanisms, little is known about the evolutionary and historical details of these opposing forces. Here, we correlate MAL-derived mutation spectra with patterns observed from population resequencing. Variation observed in natural populations has already been subject to evolutionary forces. Distinction between rare and common alleles, the latter of which are close to fixation and of presumably older age, can provide insight into mutational processes and their influence on genome evolution. We provide a genome-wide analysis of de novo mutations in 22 MALs of the nematode Pristionchus pacificus and compare the spectra with natural variants observed in resequencing of 104 natural isolates. MALs show an AT bias of 5.3, one of the highest values observed to date. In contrast, the AT bias in natural variants is much lower. Specifically, rare derived alleles show an AT bias of 2.4, whereas common derived alleles close to fixation show no AT bias at all. These results indicate the existence of a strong opposing force and they suggest that the GC content of the P. pacificus genome is in equilibrium. We discuss GC-biased gene conversion as a potential mechanism acting against AT-biased mutations. This study provides insight into genome evolution by combining MAL studies with natural variation. PMID:24414549

Robustness of Structures

DEFF Research Database (Denmark)

Faber, Michael Havbro; Vrouwenvelder, A.C.W.M.; Sørensen, John Dalsgaard

2011-01-01

In 2005, the Joint Committee on Structural Safety (JCSS) together with Working Commission (WC) 1 of the International Association of Bridge and Structural Engineering (IABSE) organized a workshop on robustness of structures. Two important decisions resulted from this workshop, namely...... ‘COST TU0601: Robustness of Structures’ was initiated in February 2007, aiming to provide a platform for exchanging and promoting research in the area of structural robustness and to provide a basic framework, together with methods, strategies and guidelines enhancing robustness of structures...... the development of a joint European project on structural robustness under the COST (European Cooperation in Science and Technology) programme and the decision to develop a more elaborate document on structural robustness in collaboration between experts from the JCSS and the IABSE. Accordingly, a project titled...

A system for biasing a differential amplifier

International Nuclear Information System (INIS)

Barbier, Daniel; Ittel, J.M.; Poujois, Robert

1975-01-01

This invention concerns a system for biasing a differential amplifier. It particularly applies to the integrated differential amplifiers designed with MOS field effect transistors. Variations in the technological parameters may well cause the amplifying transistors to work outside their usual operational area, in other words outside the linear part of the transfer characteristic. To ensure that these transistors function correctly, it is necessary that the value of the voltage difference at the output be equally null. To do this and to centre on the so called 'rest' point of the amplifier transfer charateristic, the condition will be set that the output potentials of each amplifier transistor should have a zero value or a constant value as sum. With this in view, the bias on the source (generally a transistor powered by its grid bias voltage) supplying current to the two amplifying transistors fitted in parallel, is permanently adjusted in a suitable manner [fr

Codon Bias Patterns of E. coli's Interacting Proteins.

Directory of Open Access Journals (Sweden)

Maddalena Dilucca

Full Text Available Synonymous codons, i.e., DNA nucleotide triplets coding for the same amino acid, are used differently across the variety of living organisms. The biological meaning of this phenomenon, known as codon usage bias, is still controversial. In order to shed light on this point, we propose a new codon bias index, CompAI, that is based on the competition between cognate and near-cognate tRNAs during translation, without being tuned to the usage bias of highly expressed genes. We perform a genome-wide evaluation of codon bias for E.coli, comparing CompAI with other widely used indices: tAI, CAI, and Nc. We show that CompAI and tAI capture similar information by being positively correlated with gene conservation, measured by the Evolutionary Retention Index (ERI, and essentiality, whereas, CAI and Nc appear to be less sensitive to evolutionary-functional parameters. Notably, the rate of variation of tAI and CompAI with ERI allows to obtain sets of genes that consistently belong to specific clusters of orthologous genes (COGs. We also investigate the correlation of codon bias at the genomic level with the network features of protein-protein interactions in E.coli. We find that the most densely connected communities of the network share a similar level of codon bias (as measured by CompAI and tAI. Conversely, a small difference in codon bias between two genes is, statistically, a prerequisite for the corresponding proteins to interact. Importantly, among all codon bias indices, CompAI turns out to have the most coherent distribution over the communities of the interactome, pointing to the significance of competition among cognate and near-cognate tRNAs for explaining codon usage adaptation. Notably, CompAI may potentially correlate with translation speed measurements, by accounting for the specific delay induced by wobble-pairing between codons and anticodons.

Model for an irreversible bias current in the superconducting qubit measurement process

International Nuclear Information System (INIS)

Hutchinson, G. D.; Williams, D. A.; Holmes, C. A.; Stace, T. M.; Spiller, T. P.; Barrett, S. D.; Milburn, G. J.; Hasko, D. G.

2006-01-01

The superconducting charge-phase ''quantronium'' qubit is considered in order to develop a model for the measurement process used in the experiment of Vion et al. [Science 296, 886 (2002)]. For this model we propose a method for including the bias current in the readout process in a fundamentally irreversible way, which to first order is approximated by the Josephson junction tilted-washboard potential phenomenology. The decohering bias current is introduced in the form of a Lindblad operator and the Wigner function for the current-biased readout Josephson junction is derived and analyzed. During the readout current pulse used in the quantronium experiment we find that the coherence of the qubit initially prepared in a symmetric superposition state is lost at a time of 0.2 ns after the bias current pulse has been applied, a time scale that is much shorter than the experimental readout time. Additionally we look at the effect of Johnson-Nyquist noise with zero mean from the current source during the qubit manipulation and show that the decoherence due to the irreversible bias current description is an order of magnitude smaller than that found through adding noise to the reversible tilted-washboard potential model. Our irreversible bias current model is also applicable to persistent-current-based qubits where the state is measured according to its flux via a small-inductance direct-current superconducting quantum interference device

Robustness of inflation to inhomogeneous initial conditions

Energy Technology Data Exchange (ETDEWEB)

Clough, Katy; Lim, Eugene A. [Theoretical Particle Physics and Cosmology Group, Physics Department, Kings College London, Strand, London WC2R 2LS (United Kingdom); DiNunno, Brandon S.; Fischler, Willy; Flauger, Raphael; Paban, Sonia, E-mail: katy.clough@kcl.ac.uk, E-mail: eugene.a.lim@gmail.com, E-mail: bsd86@physics.utexas.edu, E-mail: fischler@physics.utexas.edu, E-mail: flauger@physics.utexas.edu, E-mail: paban@physics.utexas.edu [Department of Physics, The University of Texas at Austin, Austin, TX, 78712 (United States)

2017-09-01

We consider the effects of inhomogeneous initial conditions in both the scalar field profile and the extrinsic curvature on different inflationary models. In particular, we compare the robustness of small field inflation to that of large field inflation, using numerical simulations with Einstein gravity in 3+1 dimensions. We find that small field inflation can fail in the presence of subdominant gradient energies, suggesting that it is much less robust to inhomogeneities than large field inflation, which withstands dominant gradient energies. However, we also show that small field inflation can be successful even if some regions of spacetime start out in the region of the potential that does not support inflation. In the large field case, we confirm previous results that inflation is robust if the inflaton occupies the inflationary part of the potential. Furthermore, we show that increasing initial scalar gradients will not form sufficiently massive inflation-ending black holes if the initial hypersurface is approximately flat. Finally, we consider the large field case with a varying extrinsic curvature K , such that some regions are initially collapsing. We find that this may again lead to local black holes, but overall the spacetime remains inflationary if the spacetime is open, which confirms previous theoretical studies.

Return Predictability, Model Uncertainty, and Robust Investment

DEFF Research Database (Denmark)

Lukas, Manuel

Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...... find that confidence sets are very wide, change significantly with the predictor variables, and frequently include expected utilities for which the investor prefers not to invest. The latter motivates a robust investment strategy maximizing the minimal element of the confidence set. The robust investor...... allocates a much lower share of wealth to stocks compared to a standard investor....

An assessment of change in risk perception and optimistic bias for hurricanes among Gulf Coast residents.

Science.gov (United States)

Trumbo, Craig; Meyer, Michelle A; Marlatt, Holly; Peek, Lori; Morrissey, Bridget

2014-06-01

This study focuses on levels of concern for hurricanes among individuals living along the Gulf Coast during the quiescent two-year period following the exceptionally destructive 2005 hurricane season. A small study of risk perception and optimistic bias was conducted immediately following Hurricanes Katrina and Rita. Two years later, a follow-up was done in which respondents were recontacted. This provided an opportunity to examine changes, and potential causal ordering, in risk perception and optimistic bias. The analysis uses 201 panel respondents who were matched across the two mail surveys. Measures included hurricane risk perception, optimistic bias for hurricane evacuation, past hurricane experience, and a small set of demographic variables (age, sex, income, and education). Paired t-tests were used to compare scores across time. Hurricane risk perception declined and optimistic bias increased. Cross-lagged correlations were used to test the potential causal ordering between risk perception and optimistic bias, with a weak effect suggesting the former affects the latter. Additional cross-lagged analysis using structural equation modeling was used to look more closely at the components of optimistic bias (risk to self vs. risk to others). A significant and stronger potentially causal effect from risk perception to optimistic bias was found. Analysis of the experience and demographic variables' effects on risk perception and optimistic bias, and their change, provided mixed results. The lessening of risk perception and increase in optimistic bias over the period of quiescence suggest that risk communicators and emergency managers should direct attention toward reversing these trends to increase disaster preparedness. © 2013 Society for Risk Analysis.

Biased information processing in the escalation paradigm: information search and information evaluation as potential mediators of escalating commitment.

Science.gov (United States)

Schultze, Thomas; Pfeiffer, Felix; Schulz-Hardt, Stefan

2012-01-01

Escalation of commitment denotes decision makers' increased reinvestment of resources in a losing course of action. Despite the relevance of this topic, little is known about how information is processed in escalation situations, that is, whether decision makers who receive negative outcome feedback on their initial decision search for and/or process information biasedly and whether these biases contribute to escalating commitment. Contrary to a widely cited study by E. J. Conlon and J. M. Parks (1987), in 3 experiments, the authors found that biases do not occur on the level of information search. Neither in a direct replication and extension of the original study with largely increased test power (Experiment 1) nor under methodologically improved conditions (Experiments 2 and 3) did decision makers responsible for failure differ from nonresponsible decision makers with regards to information search, and no selective search for information supporting the initial decision or voting for further reinvestment was observed. However, Experiments 3 and 4 show that the evaluation of the previously sought information is biased among participants who were responsible for initiating the course of action. Mediation analyses show that this evaluation bias in favor of reinvestment partially mediated the responsibility effect on escalation of commitment.

Approximate Bias Correction in Econometrics

OpenAIRE

James G. MacKinnon; Anthony A. Smith Jr.

1995-01-01

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

The anchoring bias reflects rational use of cognitive resources.

Science.gov (United States)

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.

Competing risk bias was common in Kaplan-Meier risk estimates published in prominent medical journals.

Science.gov (United States)

van Walraven, Carl; McAlister, Finlay A

2016-01-01

Risk estimates from Kaplan-Meier curves are well known to medical researchers, reviewers, and editors. In this study, we determined the proportion of Kaplan-Meier analyses published in prominent medical journals that are potentially biased because of competing events ("competing risk bias"). We randomly selected 100 studies that had at least one Kaplan-Meier analysis and were recently published in prominent medical journals. Susceptibility to competing risk bias was determined by examining the outcome and potential competing events. In susceptible studies, bias was quantified using a previously validated prediction model when the number of outcomes and competing events were given. Forty-six studies (46%) contained Kaplan-Meier analyses susceptible to competing risk bias. Sixteen studies (34.8%) susceptible to competing risk cited the number of outcomes and competing events; in six of these studies (6/16, 37.5%), the outcome risk from the Kaplan-Meier estimate (relative to the true risk) was biased upward by 10% or more. Almost half of Kaplan-Meier analyses published in medical journals are susceptible to competing risk bias and may overestimate event risk. This bias was found to be quantitatively important in a third of such studies. Copyright © 2016 Elsevier Inc. All rights reserved.

Reflective Practice: How the World Bank Explored Its Own Biases?

Science.gov (United States)

McKee, Martin; Stuckler, David

2015-12-10

While many international organisations have independent evaluations, including the International Monetary Fund (IMF) and World Health organization (WHO), uniquely the World Bank in its 2015 World Development Report sought to ascertain the potential biases that influence how its staff interpret evidence and influence policy. Here, we describe the World Bank's study design, including experiments to ascertain the impact on Bank staff's judgements of complexity, confirmation bias, sunk cost bias, and an understanding of the wishes of those whom they seek to help. We then review the Bank's proposed mechanisms to minimise the impact of the biases they identified. We argue that this approach, that we refer to as 'reflective practice,' deserves to be adopted more widely among institutions that seek to use evidence from research to inform policy and practice. © 2016 by Kerman University of Medical Sciences.

Attentional bias modification based on visual probe task: methodological issues, results and clinical relevance

Directory of Open Access Journals (Sweden)

Fernanda Machado Lopes

2015-12-01

Full Text Available Introduction: Attentional bias, the tendency that a person has to drive or maintain attention to a specific class of stimuli, may play an important role in the etiology and persistence of mental disorders. Attentional bias modification has been studied as a form of additional treatment related to automatic processing. Objectives: This systematic literature review compared and discussed methods, evidence of success and potential clinical applications of studies about attentional bias modification (ABM using a visual probe task. Methods: The Web of Knowledge, PubMed and PsycInfo were searched using the keywords attentional bias modification, attentional bias manipulation and attentional bias training. We selected empirical studies about ABM training using a visual probe task written in English and published between 2002 and 2014. Results: Fifty-seven studies met inclusion criteria. Most (78% succeeded in training attention in the predicted direction, and in 71% results were generalized to other measures correlated with the symptoms. Conclusions: ABM has potential clinical utility, but to standardize methods and maximize applicability, future studies should include clinical samples and be based on findings of studies about its effectiveness.

Evaluation of bias associated with high-multiplex, target-specific pre-amplification

Directory of Open Access Journals (Sweden)

Steven T. Okino

2016-01-01

Full Text Available We developed a novel PCR-based pre-amplification (PreAmp technology that can increase the abundance of over 350 target genes one million-fold. To assess potential bias introduced by PreAmp we utilized ERCC RNA reference standards, a model system that quantifies measurement error in RNA analysis. We assessed three types of bias: amplification bias, dynamic range bias and fold-change bias. We show that our PreAmp workflow introduces only minimal amplification and fold-change bias under stringent conditions. We do detect dynamic range bias if a target gene is highly abundant and PreAmp occurred for 16 or more PCR cycles; however, this type of bias is easily correctable. To assess PreAmp bias in a gene expression profiling experiment, we analyzed a panel of genes that are regulated during differentiation using the NTera2 stem cell model system. We find that results generated using PreAmp are similar to results obtained using standard qPCR (without the pre-amplification step. Importantly, PreAmp maintains patterns of gene expression changes across samples; the same biological insights would be derived from a PreAmp experiment as with a standard gene expression profiling experiment. We conclude that our PreAmp technology can facilitate analysis of extremely limited samples in gene expression quantification experiments.

DC-dynamic biasing for >50× switching time improvement in severely underdamped fringing-field electrostatic MEMS actuators

International Nuclear Information System (INIS)

Small, J; Liu, X; Fruehling, A; Garg, A; Peroulis, D

2012-01-01

This paper presents the design and experimental validation of dc-dynamic biasing for > 50× switching time improvement in severely underdamped fringing-field electrostatic MEMS actuators. The electrostatic fringing-field actuator is used to demonstrate the concept due to its robust device design and inherently low damping conditions. In order to accurately quantify the gap height versus voltage characteristics, a heuristic model is developed. The difference between the heuristic model and numerical simulation is less than 5.6% for typical MEMS geometries. MEMS fixed–fixed beams are fabricated and measured for experimental validation. Good agreement is observed between the calculated and measured results. For a given voltage, the measured and calculated displacements are typically within 10%. Lastly, the derived model is used to design a dc-dynamic bias waveform to improve the switching time of the underdamped MEMS actuators. With dynamic biasing, the measured up-to-down and down-to-up switching time of the actuator is ∼35 μs. On the other hand, coventional step biasing results in a switching time of ∼2 ms for both up-to-down and down-to-up states. (paper)

Affective forecasting and self-rated symptoms of depression, anxiety, and hypomania: evidence for a dysphoric forecasting bias.

Science.gov (United States)

Hoerger, Michael; Quirk, Stuart W; Chapman, Benjamin P; Duberstein, Paul R

2012-01-01

Emerging research has examined individual differences in affective forecasting; however, we are aware of no published study to date linking psychopathology symptoms to affective forecasting problems. Pitting cognitive theory against depressive realism theory, we examined whether dysphoria was associated with negatively biased affective forecasts or greater accuracy. Participants (n=325) supplied predicted and actual emotional reactions for three days surrounding an emotionally evocative relational event, Valentine's Day. Predictions were made a month prior to the holiday. Consistent with cognitive theory, we found evidence for a dysphoric forecasting bias-the tendency of individuals in dysphoric states to overpredict negative emotional reactions to future events. The dysphoric forecasting bias was robust across ratings of positive and negative affect, forecasts for pleasant and unpleasant scenarios, continuous and categorical operationalisations of dysphoria, and three time points of observation. Similar biases were not observed in analyses examining the independent effects of anxiety and hypomania. Findings provide empirical evidence for the long-assumed influence of depressive symptoms on future expectations. The present investigation has implications for affective forecasting studies examining information-processing constructs, decision making, and broader domains of psychopathology.

Affective Forecasting and Self-Rated Symptoms of Depression, Anxiety, and Hypomania: Evidence for a Dysphoric Forecasting Bias

Science.gov (United States)

Hoerger, Michael; Quirk, Stuart W.; Chapman, Benjamin P.; Duberstein, Paul R.

2011-01-01

Emerging research has examined individual differences in affective forecasting; however, we are aware of no published study to date linking psychopathology symptoms to affective forecasting problems. Pitting cognitive theory against depressive realism theory, we examined whether dysphoria was associated with negatively biased affective forecasts or greater accuracy. Participants (n = 325) supplied predicted and actual emotional reactions for three days surrounding an emotionally-evocative relational event, Valentine’s Day. Predictions were made a month prior to the holiday. Consistent with cognitive theory, we found evidence for a dysphoric forecasting bias – the tendency of individuals in dysphoric states to overpredict negative emotional reactions to future events. The dysphoric forecasting bias was robust across ratings of positive and negative affect, forecasts for pleasant and unpleasant scenarios, continuous and categorical operationalizations of dysphoria, and three time points of observation. Similar biases were not observed in analyses examining the independent effects of anxiety and hypomania. Findings provide empirical evidence for the long assumed influence of depressive symptoms on future expectations. The present investigation has implications for affective forecasting studies examining information processing constructs, decision making, and broader domains of psychopathology. PMID:22397734

Is it feasible to estimate radiosonde biases from interlaced measurements?

Science.gov (United States)

Kremser, Stefanie; Tradowsky, Jordis S.; Rust, Henning W.; Bodeker, Greg E.

2018-05-01

Upper-air measurements of essential climate variables (ECVs), such as temperature, are crucial for climate monitoring and climate change detection. Because of the internal variability of the climate system, many decades of measurements are typically required to robustly detect any trend in the climate data record. It is imperative for the records to be temporally homogeneous over many decades to confidently estimate any trend. Historically, records of upper-air measurements were primarily made for short-term weather forecasts and as such are seldom suitable for studying long-term climate change as they lack the required continuity and homogeneity. Recognizing this, the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) has been established to provide reference-quality measurements of climate variables, such as temperature, pressure, and humidity, together with well-characterized and traceable estimates of the measurement uncertainty. To ensure that GRUAN data products are suitable to detect climate change, a scientifically robust instrument replacement strategy must always be adopted whenever there is a change in instrumentation. By fully characterizing any systematic differences between the old and new measurement system a temporally homogeneous data series can be created. One strategy is to operate both the old and new instruments in tandem for some overlap period to characterize any inter-instrument biases. However, this strategy can be prohibitively expensive at measurement sites operated by national weather services or research institutes. An alternative strategy that has been proposed is to alternate between the old and new instruments, so-called interlacing, and then statistically derive the systematic biases between the two instruments. Here we investigate the feasibility of such an approach specifically for radiosondes, i.e. flying the old and new instruments on alternating days. Synthetic data sets are used to explore the

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

Science.gov (United States)

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.

Simulating publication bias

DEFF Research Database (Denmark)

Paldam, Martin

is censoring: selection by the size of estimate; SR3 selects the optimal combination of fit and size; and SR4 selects the first satisficing result. The last four SRs are steered by priors and result in bias. The MST and the FAT-PET have been developed for detection and correction of such bias. The simulations......Economic research typically runs J regressions for each selected for publication – it is often selected as the ‘best’ of the regressions. The paper examines five possible meanings of the word ‘best’: SR0 is ideal selection with no bias; SR1 is polishing: selection by statistical fit; SR2...... are made by data variation, while the model is the same. It appears that SR0 generates narrow funnels much at odds with observed funnels, while the other four funnels look more realistic. SR1 to SR4 give the mean a substantial bias that confirms the prior causing the bias. The FAT-PET MRA works well...

Defining robustness protocols: a method to include and evaluate robustness in clinical plans

International Nuclear Information System (INIS)

McGowan, S E; Albertini, F; Lomax, A J; Thomas, S J

2015-01-01

We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties. (paper)

Defining robustness protocols: a method to include and evaluate robustness in clinical plans

Science.gov (United States)

McGowan, S. E.; Albertini, F.; Thomas, S. J.; Lomax, A. J.

2015-04-01

We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties.

Engineering Robustness of Microbial Cell Factories.

Science.gov (United States)

Gong, Zhiwei; Nielsen, Jens; Zhou, Yongjin J

2017-10-01

Metabolic engineering and synthetic biology offer great prospects in developing microbial cell factories capable of converting renewable feedstocks into fuels, chemicals, food ingredients, and pharmaceuticals. However, prohibitively low production rate and mass concentration remain the major hurdles in industrial processes even though the biosynthetic pathways are comprehensively optimized. These limitations are caused by a variety of factors unamenable for host cell survival, such as harsh industrial conditions, fermentation inhibitors from biomass hydrolysates, and toxic compounds including metabolic intermediates and valuable target products. Therefore, engineered microbes with robust phenotypes is essential for achieving higher yield and productivity. In this review, the recent advances in engineering robustness and tolerance of cell factories is described to cope with these issues and briefly introduce novel strategies with great potential to enhance the robustness of cell factories, including metabolic pathway balancing, transporter engineering, and adaptive laboratory evolution. This review also highlights the integration of advanced systems and synthetic biology principles toward engineering the harmony of overall cell function, more than the specific pathways or enzymes. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A study on investors’ personality characteristics and behavioral biases: Conservatism bias and availability bias in the Tehran Stock Exchange

Directory of Open Access Journals (Sweden)

Mahmoud Moradi

2013-04-01

Full Text Available Most economic and finance theories are based on the assumption that during economic decision making, people would act totally rational and consider all available information. Nevertheless, behavioral finance focuses on studying of the role of psychological factors on economic participants’ behavior. The study shows that in real-world environment, people are influenced by emotional and cognitive errors and may make irrational financial decisions. In many cases, the participants of financial markets are not aware of their talents for error in decision making, so they are dissatisfied with their investments by considering some behavioral biases decisions. These decisions may often yield undesirable outcomes, which could influence economy, significantly. This paper presents a survey on the relationship between personality dimensions with behavioral biases and availability bias among investment managers in the Tehran Stock Exchange using SPSS software, descriptive and inferential statistics. The necessary data are collected through questionnaire and they are analyzed using some statistical tests. The preliminary results indicate that there is a relationship between personality dimensions and behavioral biases like conservatism bias and availability bias among the investors in the Tehran Stock Exchange.

Operator Bias in the Estimation of Arc Efficiency in Gas Tungsten Arc Welding

Directory of Open Access Journals (Sweden)

Fredrik Sikström

2015-03-01

Full Text Available In this paper the operator bias in the measurement process of arc efficiency in stationary direct current electrode negative gas tungsten arc welding is discussed. An experimental study involving 15 operators (enough to reach statistical significance has been carried out with the purpose to estimate the arc efficiency from a specific procedure for calorimetric experiments. The measurement procedure consists of three manual operations which introduces operator bias in the measurement process. An additional relevant experiment highlights the consequences of estimating the arc voltage by measuring the potential between the terminals of the welding power source instead of measuring the potential between the electrode contact tube and the workpiece. The result of the study is a statistical evaluation of the operator bias influence on the estimate, showing that operator bias is negligible in the estimate considered here. On the contrary the consequences of neglecting welding leads voltage drop results in a significant under estimation of the arc efficiency.

Content specificity of attention bias to threat in anxiety disorders: a meta-analysis.

Science.gov (United States)

Pergamin-Hight, Lee; Naim, Reut; Bakermans-Kranenburg, Marian J; van IJzendoorn, Marinus H; Bar-Haim, Yair

2015-02-01

Despite the established evidence for threat-related attention bias in anxiety, the mechanisms underlying this bias remain unclear. One important unresolved question is whether disorder-congruent threats capture attention to a greater extent than do more general or disorder-incongruent threat stimuli. Evidence for attention bias specificity in anxiety would implicate involvement of previous learning and memory processes in threat-related attention bias, whereas lack of content specificity would point to perturbations in more generic attention processes. Enhanced clarity of mechanism could have clinical implications for the stimuli types used in Attention Bias Modification Treatments (ABMT). Content specificity of threat-related attention bias in anxiety and potential moderators of this effect were investigated. A systematic search identified 37 samples from 29 articles (N=866). Relevant data were extracted based on specific coding rules, and Cohen's d effect size was used to estimate bias specificity effects. The results indicate greater attention bias toward disorder-congruent relative to disorder-incongruent threat stimuli (d=0.28, pattention tasks, or type of disorder-incongruent stimuli. No evidence of publication bias was observed. Implications for threat bias in anxiety and ABMT are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

Starrfelt, Jostein; Liow, Lee Hsiang

2016-04-05

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

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

Science.gov (United States)

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.

Visual attention and the neuroimage bias.

Directory of Open Access Journals (Sweden)

D A Baker

Full Text Available Several highly-cited experiments have presented evidence suggesting that neuroimages may unduly bias laypeople's judgments of scientific research. This finding has been especially worrisome to the legal community in which neuroimage techniques may be used to produce evidence of a person's mental state. However, a more recent body of work that has looked directly at the independent impact of neuroimages on layperson decision-making (both in legal and more general arenas, and has failed to find evidence of bias. To help resolve these conflicting findings, this research uses eye tracking technology to provide a measure of attention to different visual representations of neuroscientific data. Finding an effect of neuroimages on the distribution of attention would provide a potential mechanism for the influence of neuroimages on higher-level decisions. In the present experiment, a sample of laypeople viewed a vignette that briefly described a court case in which the defendant's actions might have been explained by a neurological defect. Accompanying these vignettes was either an MRI image of the defendant's brain, or a bar graph depicting levels of brain activity-two competing visualizations that have been the focus of much of the previous research on the neuroimage bias. We found that, while laypeople differentially attended to neuroimagery relative to the bar graph, this did not translate into differential judgments in a way that would support the idea of a neuroimage bias.

Effects of three types of potentially biasing information on symptom severity judgments for major depressive episode.

Science.gov (United States)

Mumma, Gregory H

2002-10-01

Two experiments examined the effects of potentially biasing information on judgments of symptom severity pertaining to the diagnosis of major depressive episode (MDE). In both experiments, clinicians viewed videotapes of two actor-simulated patients responding to questions from a standardized diagnostic interview. In Study 1, an expectancy effect was found for both patients such that prior information about a clear-cut history of depression resulted in lower rated severity of current symptoms. In addition, a halo effect was observed for one patient in Study 1 and both patients in Study 2: Clear-cut depressive nonverbal behavior (DNVB) resulted in greater rated severity for symptoms that should not have been affected (e.g., appetite/weight change, suicidal ideation). Clear-cut versus near-threshold information for the two essential criteria for MDE did not affect subsequent judgments in either study. Implications for diagnostic interviewing are discussed. Copyright 2002 Wiley Periodicals, Inc. J Clin Psychol 58: 1327-1345, 2002.

Can statistic adjustment of OR minimize the potential confounding bias for meta-analysis of case-control study? A secondary data analysis.

Science.gov (United States)

Liu, Tianyi; Nie, Xiaolu; Wu, Zehao; Zhang, Ying; Feng, Guoshuang; Cai, Siyu; Lv, Yaqi; Peng, Xiaoxia

2017-12-29

Different confounder adjustment strategies were used to estimate odds ratios (ORs) in case-control study, i.e. how many confounders original studies adjusted and what the variables are. This secondary data analysis is aimed to detect whether there are potential biases caused by difference of confounding factor adjustment strategies in case-control study, and whether such bias would impact the summary effect size of meta-analysis. We included all meta-analyses that focused on the association between breast cancer and passive smoking among non-smoking women, as well as each original case-control studies included in these meta-analyses. The relative deviations (RDs) of each original study were calculated to detect how magnitude the adjustment would impact the estimation of ORs, compared with crude ORs. At the same time, a scatter diagram was sketched to describe the distribution of adjusted ORs with different number of adjusted confounders. Substantial inconsistency existed in meta-analysis of case-control studies, which would influence the precision of the summary effect size. First, mixed unadjusted and adjusted ORs were used to combine individual OR in majority of meta-analysis. Second, original studies with different adjustment strategies of confounders were combined, i.e. the number of adjusted confounders and different factors being adjusted in each original study. Third, adjustment did not make the effect size of original studies trend to constringency, which suggested that model fitting might have failed to correct the systematic error caused by confounding. The heterogeneity of confounder adjustment strategies in case-control studies may lead to further bias for summary effect size in meta-analyses, especially for weak or medium associations so that the direction of causal inference would be even reversed. Therefore, further methodological researches are needed, referring to the assessment of confounder adjustment strategies, as well as how to take this kind

Media bias under direct and indirect government control: when is the bias smaller?

OpenAIRE

Abhra Roy

2015-01-01

We present an analytical framework to compare media bias under direct and indirect government control. In this context, we show that direct control can lead to a smaller bias and higher welfare than indirect control. We further show that the size of the advertising market affects media bias only under direct control. Media bias, under indirect control, is not affected by the size of the advertising market.

Methodologies for Measuring Judicial Performance: The Problem of Bias

Directory of Open Access Journals (Sweden)

Jennifer Elek

2014-12-01

Full Text Available Concerns about gender and racial bias in the survey-based evaluations of judicial performance common in the United States have persisted for decades. Consistent with a large body of basic research in the psychological sciences, recent studies confirm that the results from these JPE surveys are systematically biased against women and minority judges. In this paper, we explain the insidious manner in which performance evaluations may be biased, describe some techniques that may help to reduce expressions of bias in judicial performance evaluation surveys, and discuss the potential problem such biases may pose in other common methods of performance evaluation used in the United States and elsewhere. We conclude by highlighting the potential adverse consequences of judicial performance evaluation programs that rely on biased measurements. Durante décadas ha habido una preocupación por la discriminación por género y racial en las evaluaciones del rendimiento judicial basadas en encuestas, comunes en Estados Unidos. De acuerdo con un gran corpus de investigación básica en las ciencias psicológicas, estudios recientes confirman que los resultados de estas encuestas de evaluación del rendimiento judicial están sistemáticamente sesgados contra las mujeres y los jueces de minorías. En este artículo se explica la manera insidiosa en que las evaluaciones de rendimiento pueden estar sesgadas, se describen algunas técnicas que pueden ayudar a reducir las expresiones de sesgo en los estudios de evaluación del rendimiento judicial, y se debate el problema potencial que estos sesgos pueden plantear en otros métodos comunes de evaluación del rendimiento utilizados en Estados Unidos y otros países. Se concluye destacando las posibles consecuencias adversas de los programas de evaluación del rendimiento judicial que se basan en mediciones sesgadas. DOWNLOAD THIS PAPER FROM SSRN: http://ssrn.com/abstract=2533937

Numerical modelling of pump limiter biasing on TEXTOR-94 and Tore Supra

International Nuclear Information System (INIS)

Gerhauser, H.; Claassen, H.A.; Mank, G.; Zagorski, R.; Loarer, T.; Gunn, J.; Boucher, C.

2002-01-01

The two-dimensional multifluid code TECXY has been used to model the biasing (with respect to the first wall) of the toroidal belt limiter ALT-II on the tokamak TEXTOR-94 and of the new toroidal pump limiter being installed on Tore Supra tokamak in the framework of the CIEL project. It is well known that the edge flow pattern can be influenced by the poloidal electric drifts from imposing radial electric fields. The modelling with TECXY introduces imprinted bias currents in the scrape-off layer (SOL) for the case of negative (limiter) biasing, and imprinted bias potentials for the case of positive biasing. This allowed us to simulate sufficiently well the experimental I-V characteristics for either biasing of ALT-II and also reproduced the essential features and trends of the observed plasma profiles in the SOL of TEXTOR-94. For negative biasing a moderate improvement of the pumping exhaust efficiency can be achieved in the case of TEXTOR. For Tore Supra, however, only a negligible improvement of the limiter performance with biasing can be predicted, which is explained by the relatively weak drift flows in Tore Supra. (author)

Large-scale galaxy bias

Science.gov (United States)

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.

A father effect explains sex-ratio bias.

Science.gov (United States)

Malo, Aurelio F; Martinez-Pastor, Felipe; Garcia-Gonzalez, Francisco; Garde, Julián; Ballou, Jonathan D; Lacy, Robert C

2017-08-30

Sex ratio allocation has important fitness consequences, and theory predicts that parents should adjust offspring sex ratio in cases where the fitness returns of producing male and female offspring vary. The ability of fathers to bias offspring sex ratios has traditionally been dismissed given the expectation of an equal proportion of X- and Y-chromosome-bearing sperm (CBS) in ejaculates due to segregation of sex chromosomes at meiosis. This expectation has been recently refuted. Here we used Peromyscus leucopus to demonstrate that sex ratio is explained by an exclusive effect of the father, and suggest a likely mechanism by which male-driven sex-ratio bias is attained. We identified a male sperm morphological marker that is associated with the mechanism leading to sex ratio bias; differences among males in the sperm nucleus area (a proxy for the sex chromosome that the sperm contains) explain 22% variation in litter sex ratio. We further show the role played by the sperm nucleus area as a mediator in the relationship between individual genetic variation and sex-ratio bias. Fathers with high levels of genetic variation had ejaculates with a higher proportion of sperm with small nuclei area. This, in turn, led to siring a higher proportion of sons (25% increase in sons per 0.1 decrease in the inbreeding coefficient). Our results reveal a plausible mechanism underlying unexplored male-driven sex-ratio biases. We also discuss why this pattern of paternal bias can be adaptive. This research puts to rest the idea that father contribution to sex ratio variation should be disregarded in vertebrates, and will stimulate research on evolutionary constraints to sex ratios-for example, whether fathers and mothers have divergent, coinciding, or neutral sex allocation interests. Finally, these results offer a potential explanation for those intriguing cases in which there are sex ratio biases, such as in humans. © 2017 The Author(s).

Flow cytometric sexing of spider sperm reveals an equal sperm production ratio in a female-biased species

DEFF Research Database (Denmark)

Vanthournout, Bram; Deswarte, K; Hammad, H

2014-01-01

research. Pinpointing the underlying mechanism of sex ratio bias is challenging owing to the multitude of potential sex ratio-biasing factors. In the dwarf spider, Oedothorax gibbosus, infection with the bacterial endosymbiont Wolbachia results in a female bias. However, pedigree analysis reveals...

Research Priorities for Robust and Beneficial Artificial Intelligence

OpenAIRE

Russell, Stuart; Dewey, Daniel; Tegmark, Max

2015-01-01

Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to investigate how to maximize these benefits while avoiding potential pitfalls. This article gives numerous examples (which should by no means be construed as an exhaustive list) of such worthwhile research aimed at ensuring that AI remains robust and beneficial.

Methods for robustness programming

NARCIS (Netherlands)

Olieman, N.J.

2008-01-01

Robustness of an object is defined as the probability that an object will have properties as required. Robustness Programming (RP) is a mathematical approach for Robustness estimation and Robustness optimisation. An example in the context of designing a food product, is finding the best composition

Classification based upon gene expression data: bias and precision of error rates.

Science.gov (United States)

Wood, Ian A; Visscher, Peter M; Mengersen, Kerrie L

2007-06-01

Gene expression data offer a large number of potentially useful predictors for the classification of tissue samples into classes, such as diseased and non-diseased. The predictive error rate of classifiers can be estimated using methods such as cross-validation. We have investigated issues of interpretation and potential bias in the reporting of error rate estimates. The issues considered here are optimization and selection biases, sampling effects, measures of misclassification rate, baseline error rates, two-level external cross-validation and a novel proposal for detection of bias using the permutation mean. Reporting an optimal estimated error rate incurs an optimization bias. Downward bias of 3-5% was found in an existing study of classification based on gene expression data and may be endemic in similar studies. Using a simulated non-informative dataset and two example datasets from existing studies, we show how bias can be detected through the use of label permutations and avoided using two-level external cross-validation. Some studies avoid optimization bias by using single-level cross-validation and a test set, but error rates can be more accurately estimated via two-level cross-validation. In addition to estimating the simple overall error rate, we recommend reporting class error rates plus where possible the conditional risk incorporating prior class probabilities and a misclassification cost matrix. We also describe baseline error rates derived from three trivial classifiers which ignore the predictors. R code which implements two-level external cross-validation with the PAMR package, experiment code, dataset details and additional figures are freely available for non-commercial use from http://www.maths.qut.edu.au/profiles/wood/permr.jsp

Assessing bias associated with geocoding of historical residence in epidemiology research

Directory of Open Access Journals (Sweden)

Daikwon Han

2013-05-01

Full Text Available The use of geocoded historical residence as proxy for retrospective assessment of exposure in early life is increasing in epidemiological studies of chronic health outcomes. Dealing with historical residence poses challenges, primarily due to higher uncertainties associated with data collection and processing. A possible source of bias is connected with the exclusion of subjects, who cannot, for various reasons, be geocoded. We evaluated the potential bias that may arise due to incomplete geocoding, using birth residence data collected as part of a population-based case-control study of breast cancer in western New York state. We found that geocoded and non-geocoded populations did not differ in the distribution of most risk factors compared, and that the geocoding status did not modify the spatial patterns of the study populations. However, the results emphasize the need for epidemiological studies to consider the potential biases that may be introduced by geocoding of historical residence when investigating retrospectively chronic disease and early-life exposure.

Robust Optimal Design of Quantum Electronic Devices

Directory of Open Access Journals (Sweden)

Ociel Morales

2018-01-01

Full Text Available We consider the optimal design of a sequence of quantum barriers, in order to manufacture an electronic device at the nanoscale such that the dependence of its transmission coefficient on the bias voltage is linear. The technique presented here is easily adaptable to other response characteristics. There are two distinguishing features of our approach. First, the transmission coefficient is determined using a semiclassical approximation, so we can explicitly compute the gradient of the objective function. Second, in contrast with earlier treatments, manufacturing uncertainties are incorporated in the model through random variables; the optimal design problem is formulated in a probabilistic setting and then solved using a stochastic collocation method. As a measure of robustness, a weighted sum of the expectation and the variance of a least-squares performance metric is considered. Several simulations illustrate the proposed technique, which shows an improvement in accuracy over 69% with respect to brute-force, Monte-Carlo-based methods.

Ion acceleration in a helicon source due to the self-bias effect

International Nuclear Information System (INIS)

Wiebold, Matt; Sung, Yung-Ta; Scharer, John E.

2012-01-01

Time-averaged plasma potential differences up to 165 V over several hundred Debye lengths are observed in low pressure (p n i ≈ 7 kT e in some cases. RF power up to 500 W at 13.56 MHz is supplied to a half-turn, double-helix antenna in the presence of a nozzle magnetic field, adjustable up to 1 kG. A retarding potential analyzer (RPA) measures the ion energy distribution function (IEDF) and a swept emissive probe measures the plasma potential. Single and double probes measure the electron density and temperature. Two distinct mode hops, the capacitive-inductive (E-H) and inductive-helicon (H-W) transitions, are identified by jumps in density as RF power is increased. In the capacitive (E) mode, large fluctuations of the plasma potential (V p-p ≳140V, V p-p /V p ≈150%) exist at the RF frequency and its harmonics. The more mobile electrons can easily respond to RF-timescale gradients in the plasma potential whereas the inertially constrained ions cannot, leading to an initial flux imbalance and formation of a self-bias voltage between the source and expansion chambers. In the capacitive mode, the ion acceleration is not well described by an ambipolar relation, while in the inductive and helicon modes the ion acceleration more closely follows an ambipolar relation. The scaling of the potential gradient with the argon flow rate and RF power are investigated, with the largest potential gradients observed for the lowest flow rates in the capacitive mode. The magnitude of the self-bias voltage agrees with that predicted for RF self-bias at a wall. Rapid fluctuations in the plasma potential result in a time-dependent axial electron flux that acts to “neutralize” the accelerated ion population, resulting in a zero net time-averaged current through the acceleration region when an insulating upstream boundary condition is enforced. Grounding the upstream endplate increases the self-bias voltage compared to a floating endplate.

Large-scale galaxy bias

Science.gov (United States)

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.

The role of cognitive biases in short-term psychodynamic psychotherapy.

Science.gov (United States)

Kramer, Ueli; Ortega, Diana; Ambresin, Gilles; Despland, Jean-Nicolas; de Roten, Yves

2018-06-01

The concept of biased thinking - or cognitive biases - is relevant to psychotherapy research and clinical conceptualization, beyond cognitive theories. The present naturalistic study aimed to examine the changes in biased thinking over the course of a short-term dynamic psychotherapy (STDP) and to discover potential links between these changes and symptomatic improvement. This study focuses on 32 self-referred patients consulting for Adjustment Disorder according to DSM-IV-TR. The therapists were experienced psychodynamically oriented psychiatrists and psychotherapists. Coding of cognitive biases (using the Cognitive Errors Rating Scale; CERS) was made by external raters based on transcripts of interviews of psychotherapy; the reliability of these ratings on a randomly chosen 24% of all sessions was established. Based on the Symptom Check List SCL-90-R given before and after, the Reliable Change Index (RCI) was used. The assessment of cognitive errors was done at three time points: early (session 4-7), mid-treatment (session 12-17), and close to the end (after session 20) of the treatment. The results showed that the total frequency of cognitive biases was stable over time (p = .20), which was true both for positive and for negative cognitive biases. In exploring the three main subscales of the CERS, we found a decrease in selective abstraction (p = .02) and an increase in personalization (p = .05). A significant link between RCI scores (outcome) and frequency of positive cognitive biases was found, suggesting that biases towards the positive might have a protective function in psychotherapy. Therapists may be attentive to changes in biased thinking across short-term dynamic psychotherapy for adjustment disorder. Therapists may foster the emergence of positive cognitive biases at mid-treatment for adjustment disorder. © 2017 The British Psychological Society.

Information environment, behavioral biases, and home bias in analysts’ recommendations

DEFF Research Database (Denmark)

Farooq, Omar; Taouss, Mohammed

2012-01-01

Can information environment of a firm explain home bias in analysts’ recommendations? Can the extent of agency problems explain optimism difference between foreign and local analysts? This paper answers these questions by documenting the effect of information environment on home bias in analysts’...

Robustness in laying hens

NARCIS (Netherlands)

Star, L.

2008-01-01

The aim of the project ‘The genetics of robustness in laying hens’ was to investigate nature and regulation of robustness in laying hens under sub-optimal conditions and the possibility to increase robustness by using animal breeding without loss of production. At the start of the project, a robust

Bias-limited extraction of cosmological parameters

Energy Technology Data Exchange (ETDEWEB)

Shimon, Meir; Itzhaki, Nissan; Rephaeli, Yoel, E-mail: meirs@wise.tau.ac.il, E-mail: nitzhaki@post.tau.ac.il, E-mail: yoelr@wise.tau.ac.il [School of Physics and Astronomy, Tel Aviv University, Tel Aviv 69978 (Israel)

2013-03-01

It is known that modeling uncertainties and astrophysical foregrounds can potentially introduce appreciable bias in the deduced values of cosmological parameters. While it is commonly assumed that these uncertainties will be accounted for to a sufficient level of precision, the level of bias has not been properly quantified in most cases of interest. We show that the requirement that the bias in derived values of cosmological parameters does not surpass nominal statistical error, translates into a maximal level of overall error O(N{sup −½}) on |ΔP(k)|/P(k) and |ΔC{sub l}|/C{sub l}, where P(k), C{sub l}, and N are the matter power spectrum, angular power spectrum, and number of (independent Fourier) modes at a given scale l or k probed by the cosmological survey, respectively. This required level has important consequences on the precision with which cosmological parameters are hoped to be determined by future surveys: in virtually all ongoing and near future surveys N typically falls in the range 10{sup 6}−10{sup 9}, implying that the required overall theoretical modeling and numerical precision is already very high. Future redshifted-21-cm observations, projected to sample ∼ 10{sup 14} modes, will require knowledge of the matter power spectrum to a fantastic 10{sup −7} precision level. We conclude that realizing the expected potential of future cosmological surveys, which aim at detecting 10{sup 6}−10{sup 14} modes, sets the formidable challenge of reducing the overall level of uncertainty to 10{sup −3}−10{sup −7}.

Is there room for 'development' in developmental models of information processing biases to threat in children and adolescents?

Science.gov (United States)

Field, Andy P; Lester, Kathryn J

2010-12-01

Clinical and experimental theories assume that processing biases in attention and interpretation are a causal mechanism through which anxiety develops. Despite growing evidence that these processing biases are present in children and, therefore, develop long before adulthood, these theories ignore the potential role of child development. This review attempts to place information processing biases within a theoretical developmental framework. We consider whether child development has no impact on information processing biases to threat (integral bias model), or whether child development influences information processing biases and if so whether it does so by moderating the expression of an existing bias (moderation model) or by affecting the acquisition of a bias (acquisition model). We examine the extent to which these models fit with existing theory and research evidence and outline some methodological issues that need to be considered when drawing conclusions about the potential role of child development in the information processing of threat stimuli. Finally, we speculate about the developmental processes that might be important to consider in future research.

Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators.

Science.gov (United States)

Vansteelandt, Stijn; Walter, Stefan; Tchetgen Tchetgen, Eric

2018-07-01

Mendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis of such studies sensitive to survivor bias, a type of selection bias. A particular concern is that the instrumental variable conditions, even when valid for the source population, may be violated for the selective population of individuals who survive the onset of the study. This is potentially very damaging because Mendelian randomization studies are known to be sensitive to bias due to even minor violations of the instrumental variable conditions. Interestingly, the instrumental variable conditions continue to hold within certain risk sets of individuals who are still alive at a given age when the instrument and unmeasured confounders exert additive effects on the exposure, and moreover, the exposure and unmeasured confounders exert additive effects on the hazard of death. In this article, we will exploit this property to derive a two-stage instrumental variable estimator for the effect of exposure on mortality, which is insulated against the above described selection bias under these additivity assumptions.

Capturing Dynamics of Biased Attention: Are New Attention Variability Measures the Way Forward?

Directory of Open Access Journals (Sweden)

Anne-Wil Kruijt

Full Text Available New indices, calculated on data from the widely used Dot Probe Task, were recently proposed to capture variability in biased attention allocation. We observed that it remains unclear which data pattern is meant to be indicative of dynamic bias and thus to be captured by these indices. Moreover, we hypothesized that the new indices are sensitive to SD differences at the response time (RT level in the absence of bias.Randomly generated datasets were analyzed to assess properties of the Attention Bias Variability (ABV and Trial Level Bias Score (TL-BS indices. Sensitivity to creating differences in 1 RT standard deviation, 2 mean RT, and 3 bias magnitude were assessed. In addition, two possible definitions of dynamic attention bias were explored by creating differences in 4 frequency of bias switching, and 5 bias magnitude in the presence of constant switching.ABV and TL-BS indices were found highly sensitive to increasing SD at the response time level, insensitive to increasing bias, linearly sensitive to increasing bias magnitude in the presence of bias switches, and non-linearly sensitive to increasing the frequency of bias switches. The ABV index was also found responsive to increasing mean response times in the absence of bias.Recently proposed DPT derived variability indices cannot uncouple measurement error from bias variability. Significant group differences may be observed even if there is no bias present in any individual dataset. This renders the new indices in their current form unfit for empirical purposes. Our discussion focuses on fostering debate and ideas for new research to validate the potentially very important notion of biased attention being dynamic.

A propensity score approach to correction for bias due to population stratification using genetic and non-genetic factors.

Science.gov (United States)

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.

Sample Size and Robustness of Inferences from Logistic Regression in the Presence of Nonlinearity and Multicollinearity

OpenAIRE

Bergtold, Jason S.; Yeager, Elizabeth A.; Featherstone, Allen M.

2011-01-01

The logistic regression models has been widely used in the social and natural sciences and results from studies using this model can have significant impact. Thus, confidence in the reliability of inferences drawn from these models is essential. The robustness of such inferences is dependent on sample size. The purpose of this study is to examine the impact of sample size on the mean estimated bias and efficiency of parameter estimation and inference for the logistic regression model. A numbe...

Training interpretation biases among individuals with body dysmorphic disorder symptoms.

Science.gov (United States)

Premo, Julie E; Sarfan, Laurel D; Clerkin, Elise M

2016-03-01

The current study provided an initial test of a Cognitive Bias Modification for Interpretations (CBM-I) training paradigm among a sample with elevated BDD symptoms (N=86). As expected, BDD-relevant interpretations were reduced among participants who completed a positive (vs. comparison) training program. Results also pointed to the intriguing possibility that modifying biased appearance-relevant interpretations is causally related to changes in biased, socially relevant interpretations. Further, providing support for cognitive behavioral models, residual change in interpretations was associated with some aspects of in vivo stressor responding. However, contrary to expectations there were no significant effects of condition on emotional vulnerability to a BDD stressor, potentially because participants in both training conditions experienced reductions in biased socially-threatening interpretations following training (suggesting that the "comparison" condition was not inert). These findings have meaningful theoretical and clinical implications, and fit with transdiagnostic conceptualizations of psychopathology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Robustness-based evaluation of hydropower infrastructure design under climate change

Directory of Open Access Journals (Sweden)

Mehmet Ümit Taner

2017-01-01

Full Text Available The conventional tools of decision-making in water resources infrastructure planning have been developed for problems with well-characterized uncertainties and are ill-suited for problems involving climate nonstationarity. In the past 20 years, a predict-then-act-based approach to the incorporation of climate nonstationarity has been widely adopted in which the outputs of bias-corrected climate model projections are used to evaluate planning options. However, the ambiguous nature of results has often proved unsatisfying to decision makers. This paper presents the use of a bottom-up, decision scaling framework for the evaluation of water resources infrastructure design alternatives regarding their robustness to climate change and expected value of performance. The analysis begins with an assessment of the vulnerability of the alternative designs under a wide domain of systematically-generated plausible future climates and utilizes downscaled climate projections ex post to inform likelihoods within a risk-based evaluation. The outcomes under different project designs are compared by way of a set of decision criteria, including the performance under the most likely future, expected value of performance across all evaluated futures and robustness. The method is demonstrated for the design of a hydropower system in sub-Saharan Africa and is compared to the results that would be found using a GCM-based, scenario-led analysis. The results indicate that recommendations from the decision scaling analysis can be substantially different from the scenario-led approach, alleviate common shortcomings related to the use of climate projections in water resources planning, and produce recommendations that are more robust to future climate uncertainty.

Impact of chlorophyll bias on the tropical Pacific mean climate in an earth system model

Science.gov (United States)

Lim, Hyung-Gyu; Park, Jong-Yeon; Kug, Jong-Seong

2017-12-01

Climate modeling groups nowadays develop earth system models (ESMs) by incorporating biogeochemical processes in their climate models. The ESMs, however, often show substantial bias in simulated marine biogeochemistry which can potentially introduce an undesirable bias in physical ocean fields through biogeophysical interactions. This study examines how and how much the chlorophyll bias in a state-of-the-art ESM affects the mean and seasonal cycle of tropical Pacific sea-surface temperature (SST). The ESM used in the present study shows a sizeable positive bias in the simulated tropical chlorophyll. We found that the correction of the chlorophyll bias can reduce the ESM's intrinsic cold SST mean bias in the equatorial Pacific. The biologically-induced cold SST bias is strongly affected by seasonally-dependent air-sea coupling strength. In addition, the correction of chlorophyll bias can improve the annual cycle of SST by up to 25%. This result suggests a possible modeling approach in understanding the two-way interactions between physical and chlorophyll biases by biogeophysical effects.

Evaluating survey quality in health services research: a decision framework for assessing nonresponse bias.

Science.gov (United States)

Halbesleben, Jonathon R B; Whitman, Marilyn V

2013-06-01

To address the issue of nonresponse as problematic and offer appropriate strategies for assessing nonresponse bias. A review of current strategies used to assess the quality of survey data and the challenges associated with these strategies is provided along with appropriate post-data collection techniques that researchers should consider. Response rates are an incomplete assessment of survey data quality, and quick reactions to response rate should be avoided. Based on a five-question decision making framework, we offer potential ways to assess nonresponse bias, along with a description of the advantages and disadvantages to each. It is important that the quality of survey data be considered to assess the relative contribution to the literature of a given study. Authors and funding agencies should consider the potential effects of nonresponse bias both before and after survey administration and report the results of assessments of nonresponse bias in addition to response rates. © Health Research and Educational Trust.

Measuring Program Quality, Part 2: Addressing Potential Cultural Bias in a Rater Reliability Exam

Science.gov (United States)

Richer, Amanda; Charmaraman, Linda; Ceder, Ineke

2018-01-01

Like instruments used in afterschool programs to assess children's social and emotional growth or to evaluate staff members' performance, instruments used to evaluate program quality should be free from bias. Practitioners and researchers alike want to know that assessment instruments, whatever their type or intent, treat all people fairly and do…

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

Science.gov (United States)

Zhang, Zhengzhong; Jiang, Liang

2014-09-01

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

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

Science.gov (United States)

Zhang, Zhengzhong; Jiang, Liang

2014-09-12

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

Evaluating codon bias perspective in barbiturase gene using ...

African Journals Online (AJOL)

Abdullah

2014-01-08

Jan 8, 2014 ... along with codon usage was done to reveal dynamics of gene evolution and expression ... analysis is a potent approach for detecting mutations, selection methods and finding rationale of biased and unbiased gene changes and hence, evolutionary ... in the perception of the molecular basics plus potential.

Ligation bias in illumina next-generation DNA libraries: implications for sequencing ancient genomes.

Directory of Open Access Journals (Sweden)

Andaine Seguin-Orlando

Full Text Available 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.

Bond and Equity Home Bias and Foreign Bias: an International Study

OpenAIRE

VanPée, Rosanne; De Moor, Lieven

2012-01-01

In this paper we explore tentatively and formally the differences between bond and equity home bias and foreign bias based on one large scale dataset including developed and emerging markets for the period 2001 to 2010. We set the stage by tentatively and formally linking the diversion of bond and equity home bias in OECD countries to the increasing public debt issues under the form of government bonds i.e. the supply-driven argument. Unlike Fidora et al. (2007) we do not find that exchange r...

Improved Electron Yield and Spin-Polarization from III-V Photocathodes Via Bias Enhanced Carrier Drift

International Nuclear Information System (INIS)

Mulhollan, Gregory A.; Bierman, John; Brachmann, Axel; Clendenin, James E.; Garwin, Edward; Kirby, Robert; Luh, Dah-An

2005-01-01

Spin-polarized electrons are commonly used in high energy physics. Future work will benefit from greater polarization. Polarizations approaching 90% have been achieved at the expense of yield. The primary paths to higher polarization are material design and electron transport. Our work addresses the latter. Photoexcited electrons may be preferentially emitted or suppressed by an electric field applied across the active region. We are tuning this forward bias for maximum polarization and yield, together with other parameters, e.g., doping profile. Preliminary measurements have been carried out on bulk and thin film GaAs. As expected, the yield change far from the bandgap is quite large for bulk material. The bias is applied to the bottom (non-activated) side of the cathode so that the accelerating potential as measured with respect to the ground potential chamber walls is unchanged for different front-to-back cathode bias values. The size of the bias to cause an appreciable effect is rather small reflecting the low drift kinetic energy in the zero bias case

Ion acceleration in a helicon source due to the self-bias effect

Energy Technology Data Exchange (ETDEWEB)

Wiebold, Matt; Sung, Yung-Ta; Scharer, John E. [University of Wisconsin-Madison, Electrical and Computer Engineering, Madison, Wisconsin 53706 (United States)

2012-05-15

Time-averaged plasma potential differences up to 165 V over several hundred Debye lengths are observed in low pressure (p{sub n} < 1 mTorr) expanding argon plasmas in the Madison Helicon eXperiment (MadHeX). The potential gradient leads to ion acceleration greater than that predicted by ambipolar expansion, exceeding E{sub i} Almost-Equal-To 7 kT{sub e} in some cases. RF power up to 500 W at 13.56 MHz is supplied to a half-turn, double-helix antenna in the presence of a nozzle magnetic field, adjustable up to 1 kG. A retarding potential analyzer (RPA) measures the ion energy distribution function (IEDF) and a swept emissive probe measures the plasma potential. Single and double probes measure the electron density and temperature. Two distinct mode hops, the capacitive-inductive (E-H) and inductive-helicon (H-W) transitions, are identified by jumps in density as RF power is increased. In the capacitive (E) mode, large fluctuations of the plasma potential (V{sub p-p} Greater-Than-Or-Equivalent-To 140V, V{sub p-p}/V{sub p} Almost-Equal-To 150%) exist at the RF frequency and its harmonics. The more mobile electrons can easily respond to RF-timescale gradients in the plasma potential whereas the inertially constrained ions cannot, leading to an initial flux imbalance and formation of a self-bias voltage between the source and expansion chambers. In the capacitive mode, the ion acceleration is not well described by an ambipolar relation, while in the inductive and helicon modes the ion acceleration more closely follows an ambipolar relation. The scaling of the potential gradient with the argon flow rate and RF power are investigated, with the largest potential gradients observed for the lowest flow rates in the capacitive mode. The magnitude of the self-bias voltage agrees with that predicted for RF self-bias at a wall. Rapid fluctuations in the plasma potential result in a time-dependent axial electron flux that acts to 'neutralize' the accelerated ion

Deceleration of probe beam by stage bias potential improves resolution of serial block-face scanning electron microscopic images.

Science.gov (United States)

Bouwer, James C; Deerinck, Thomas J; Bushong, Eric; Astakhov, Vadim; Ramachandra, Ranjan; Peltier, Steven T; Ellisman, Mark H

2017-01-01

Serial block-face scanning electron microscopy (SBEM) is quickly becoming an important imaging tool to explore three-dimensional biological structure across spatial scales. At probe-beam-electron energies of 2.0 keV or lower, the axial resolution should improve, because there is less primary electron penetration into the block face. More specifically, at these lower energies, the interaction volume is much smaller, and therefore, surface detail is more highly resolved. However, the backscattered electron yield for metal contrast agents and the backscattered electron detector sensitivity are both sub-optimal at these lower energies, thus negating the gain in axial resolution. We found that the application of a negative voltage (reversal potential) applied to a modified SBEM stage creates a tunable electric field at the sample. This field can be used to decrease the probe-beam-landing energy and, at the same time, alter the trajectory of the signal to increase the signal collected by the detector. With decelerated low landing-energy electrons, we observed that the probe-beam-electron-penetration depth was reduced to less than 30 nm in epoxy-embedded biological specimens. Concurrently, a large increase in recorded signal occurred due to the re-acceleration of BSEs in the bias field towards the objective pole piece where the detector is located. By tuning the bias field, we were able to manipulate the trajectories of the  primary and secondary electrons, enabling the spatial discrimination of these signals using an advanced ring-type BSE detector configuration or a standard monolithic BSE detector coupled with a blocking aperture.

Robust Denaturation of Villin Headpiece by MoS2 Nanosheet: Potential Molecular Origin of the Nanotoxicity

Science.gov (United States)

Gu, Zonglin; Yang, Zaixing; Kang, Seung-Gu; Yang, Jerry R.; Luo, Judong; Zhou, Ruhong

2016-06-01

MoS2 nanosheet, a new two-dimensional transition metal dichalcogenides nanomaterial, has attracted significant attentions lately due to many potential promising biomedical applications. Meanwhile, there is also a growing concern on its biocompatibility, with little known on its interactions with various biomolecules such as proteins. In this study, we use all-atom molecular dynamics simulations to investigate the interaction of a MoS2 nanosheet with Villin Headpiece (HP35), a model protein widely used in protein folding studies. We find that MoS2 exhibits robust denaturing capability to HP35, with its secondary structures severely destroyed within hundreds of nanosecond simulations. Both aromatic and basic residues are critical for the protein anchoring onto MoS2 surface, which then triggers the successive protein unfolding process. The main driving force behind the adsorption process is the dispersion interaction between protein and MoS2 monolayer. Moreover, water molecules at the interface between some key hydrophobic residues (e.g. Trp-64) and MoS2 surface also help to accelerate the process driven by nanoscale drying, which provides a strong hydrophobic force. These findings might have shed new light on the potential nanotoxicity of MoS2 to proteins with atomic details, which should be helpful in guiding future biomedical applications of MoS2 with its nanotoxicity mitigated.

Weight bias in work settings - a qualitative review.

Science.gov (United States)

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.

On the Interplay between Entropy and Robustness of Gene Regulatory Networks

Directory of Open Access Journals (Sweden)

Bor-Sen Chen

2010-05-01

Full Text Available The interplay between entropy and robustness of gene network is a core mechanism of systems biology. The entropy is a measure of randomness or disorder of a physical system due to random parameter fluctuation and environmental noises in gene regulatory networks. The robustness of a gene regulatory network, which can be measured as the ability to tolerate the random parameter fluctuation and to attenuate the effect of environmental noise, will be discussed from the robust H∞ stabilization and filtering perspective. In this review, we will also discuss their balancing roles in evolution and potential applications in systems and synthetic biology.

Smokers exhibit biased neural processing of smoking and affective images.

Science.gov (United States)

Oliver, Jason A; Jentink, Kade G; Drobes, David J; Evans, David E

2016-08-01

There has been growing interest in the role that implicit processing of drug cues can play in motivating drug use behavior. However, the extent to which drug cue processing biases relate to the processing biases exhibited to other types of evocative stimuli is largely unknown. The goal of the present study was to determine how the implicit cognitive processing of smoking cues relates to the processing of affective cues using a novel paradigm. Smokers (n = 50) and nonsmokers (n = 38) completed a picture-viewing task, in which participants were presented with a series of smoking, pleasant, unpleasant, and neutral images while engaging in a distractor task designed to direct controlled resources away from conscious processing of image content. Electroencephalogram recordings were obtained throughout the task for extraction of event-related potentials (ERPs). Smokers exhibited differential processing of smoking cues across 3 different ERP indices compared with nonsmokers. Comparable effects were found for pleasant cues on 2 of these indices. Late cognitive processing of smoking and pleasant cues was associated with nicotine dependence and cigarette use. Results suggest that cognitive biases may extend across classes of stimuli among smokers. This raises important questions about the fundamental meaning of cognitive biases, and suggests the need to consider generalized cognitive biases in theories of drug use behavior and interventions based on cognitive bias modification. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Robust inference in the negative binomial regression model with an application to falls data.

Science.gov (United States)

Aeberhard, William H; Cantoni, Eva; Heritier, Stephane

2014-12-01

A popular way to model overdispersed count data, such as the number of falls reported during intervention studies, is by means of the negative binomial (NB) distribution. Classical estimating methods are well-known to be sensitive to model misspecifications, taking the form of patients falling much more than expected in such intervention studies where the NB regression model is used. We extend in this article two approaches for building robust M-estimators of the regression parameters in the class of generalized linear models to the NB distribution. The first approach achieves robustness in the response by applying a bounded function on the Pearson residuals arising in the maximum likelihood estimating equations, while the second approach achieves robustness by bounding the unscaled deviance components. For both approaches, we explore different choices for the bounding functions. Through a unified notation, we show how close these approaches may actually be as long as the bounding functions are chosen and tuned appropriately, and provide the asymptotic distributions of the resulting estimators. Moreover, we introduce a robust weighted maximum likelihood estimator for the overdispersion parameter, specific to the NB distribution. Simulations under various settings show that redescending bounding functions yield estimates with smaller biases under contamination while keeping high efficiency at the assumed model, and this for both approaches. We present an application to a recent randomized controlled trial measuring the effectiveness of an exercise program at reducing the number of falls among people suffering from Parkinsons disease to illustrate the diagnostic use of such robust procedures and their need for reliable inference. © 2014, The International Biometric Society.

Modifications of plasma edge electric field and confinement properties by limiter biasing on the KT-5C tokamak

International Nuclear Information System (INIS)

Hui Gao; Kan Zhai; Yizhi Wen; Shude Wan; Guiding Wang; Changxun Yu

1995-01-01

Experiments using a biased multiblock limiter in the KT-5C tokamak show that positive biasing is more effective than negative biasing in modifying the edge electric field, suppressing fluctuations and improving plasma confinement. The biasing effect varies with the limiter area, the toroidal magnetic field and the biasing voltage. By positive biasing, the edge profiles of the plasma potential, the electron temperature and the density become steeper, resulting in a reduced edge particle flux, an increased global particle confinement time and lower fluctuation levels of the edge plasma. (author)

Robust Growth Determinants

OpenAIRE

Doppelhofer, Gernot; Weeks, Melvyn

2011-01-01

This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsi- monious mixture modeling that allows for fat-tailed errors compared to the normal benchmark case. Applying robust model averaging to growth determinants, the paper finds that eight out of eighteen variables found to be significantly related to economic growth ...

Camera trap placement and the potential for bias due to trails and other features.

Science.gov (United States)

Kolowski, Joseph M; Forrester, Tavis D

2017-01-01

Camera trapping has become an increasingly widespread tool for wildlife ecologists, with large numbers of studies relying on photo capture rates or presence/absence information. It is increasingly clear that camera placement can directly impact this kind of data, yet these biases are poorly understood. We used a paired camera design to investigate the effect of small-scale habitat features on species richness estimates, and capture rate and detection probability of several mammal species in the Shenandoah Valley of Virginia, USA. Cameras were deployed at either log features or on game trails with a paired camera at a nearby random location. Overall capture rates were significantly higher at trail and log cameras compared to their paired random cameras, and some species showed capture rates as much as 9.7 times greater at feature-based cameras. We recorded more species at both log (17) and trail features (15) than at their paired control cameras (13 and 12 species, respectively), yet richness estimates were indistinguishable after 659 and 385 camera nights of survey effort, respectively. We detected significant increases (ranging from 11-33%) in detection probability for five species resulting from the presence of game trails. For six species detection probability was also influenced by the presence of a log feature. This bias was most pronounced for the three rodents investigated, where in all cases detection probability was substantially higher (24.9-38.2%) at log cameras. Our results indicate that small-scale factors, including the presence of game trails and other features, can have significant impacts on species detection when camera traps are employed. Significant biases may result if the presence and quality of these features are not documented and either incorporated into analytical procedures, or controlled for in study design.

Trading Robustness Requirements in Mars Entry Trajectory Design

Science.gov (United States)

Lafleur, Jarret M.

2009-01-01

One of the most important metrics characterizing an atmospheric entry trajectory in preliminary design is the size of its predicted landing ellipse. Often, requirements for this ellipse are set early in design and significantly influence both the expected scientific return from a particular mission and the cost of development. Requirements typically specify a certain probability level (6-level) for the prescribed ellipse, and frequently this latter requirement is taken at 36. However, searches for the justification of 36 as a robustness requirement suggest it is an empirical rule of thumb borrowed from non-aerospace fields. This paper presents an investigation into the sensitivity of trajectory performance to varying robustness (6-level) requirements. The treatment of robustness as a distinct objective is discussed, and an analysis framework is presented involving the manipulation of design variables to effect trades between performance and robustness objectives. The scenario for which this method is illustrated is the ballistic entry of an MSL-class Mars entry vehicle. Here, the design variable is entry flight path angle, and objectives are parachute deploy altitude performance and error ellipse robustness. Resulting plots show the sensitivities between these objectives and trends in the entry flight path angles required to design to these objectives. Relevance to the trajectory designer is discussed, as are potential steps for further development and use of this type of analysis.

Electrophysiology of blunted emotional bias in psychopathic personality.

Science.gov (United States)

Carolan, Patrick L; Jaspers-Fayer, Fern; Asmaro, Deyar T; Douglas, Kevin S; Liotti, Mario

2014-01-01

Diminished emotional capacity is a core characteristic of psychopathic personality. We examined behavioral and electrophysiological differences in attentional bias to emotional material in 34 healthy individuals rated high or low in psychopathic traits using the short form of the Psychopathic Personality Inventory-Revised (18 high-trait, 16 low-trait). While performing an emotional Stroop task, high-trait participants displayed reduced emotional modulation of the late positive potential (LPP, 400-600 ms), and early anterior positivity (EAP, 200-300 ms) amplitudes. Results suggest blunted bias to affective content in psychopathic personality, characterized by diminished early capture to emotional salience (EAP) and dampened cognitive emotional processing (LPP). Copyright © 2013 Society for Psychophysiological Research.

A potential gender bias in assessing quality of life - a standard gamble experiment among university students.

Science.gov (United States)

Obaidi, Leath Al; Mahlich, Jörg

2015-01-01

There are several methodologies that can be used for evaluating patients' perception of their quality of life. Most commonly, utilities are directly elicited by means of either the time-trade-off or the standard-gamble method. In both methods, risk attitudes determine the quality of life values. Quality of life values among 31 Austrian undergraduate students were elicited by means of the standard gamble approach. The impact of several variables such as gender, side job, length of study, and living arrangements on the quality of life were identified using different types of regression techniques (ordinary least squares, generalized linear model, Betafit). Significant evidence was found that females are associated with a higher quality of life in all specifications of our estimations. The observed gender differences in quality of life can be attributed to a higher degree of risk aversion of women. A higher risk aversion leads to a higher valuation of given health states and a potential gender bias in health economic evaluations. This result could have implications for health policy planners when it comes to budget allocation decisions.

More recent robust methods for the estimation of mean and standard deviation of data

International Nuclear Information System (INIS)

Kanisch, G.

2003-01-01

Outliers in a data set result in biased values of mean and standard deviation. One way to improve the estimation of a mean is to apply tests to identify outliers and to exclude them from the calculations. Tests according to Grubbs or to Dixon, which are frequently used in practice, especially within laboratory intercomparisons, are not very efficient in identifying outliers. Since more than ten years now so-called robust methods are used more and more, which determine mean and standard deviation by iteration and down-weighting values far from the mean, thereby diminishing the impact of outliers. In 1989 the Analytical Methods Committee of the British Royal Chemical Society published such a robust method. Since 1993 the US Environmental Protection Agency published a more efficient and quite versatile method. Mean and standard deviation are calculated by iteration and application of a special weight function for down-weighting outlier candidates. In 2000, W. Cofino et al. published a very efficient robust method which works quite different from the others. It applies methods taken from the basics of quantum mechanics, such as ''wave functions'' associated with each laboratory mean value and matrix algebra (solving eigenvalue problems). In contrast to the other ones, this method includes the individual measurement uncertainties. (orig.)

Evidence of Cognitive Bias in Decision Making Around Implantable-Cardioverter Defibrillators: A Qualitative Framework Analysis.

Science.gov (United States)

Matlock, Daniel D; Jones, Jacqueline; Nowels, Carolyn T; Jenkins, Amy; Allen, Larry A; Kutner, Jean S

2017-11-01

Studies have demonstrated that patients with primary prevention implantable cardioverter-defibrillators (ICDs) often misunderstand the ICD. Advances in behavioral economics demonstrate that some misunderstandings may be due to cognitive biases. We aimed to explore the influence of cognitive bias on ICD decision making. We used a qualitative framework analysis including 9 cognitive biases: affect heuristic, affective forecasting, anchoring, availability, default effects, halo effects, optimism bias, framing effects, and state dependence. We interviewed 48 patients from 4 settings in Denver. The majority were male (n = 32). Overall median age was 61 years. We found frequent evidence for framing, default, and halo effects; some evidence of optimism bias, affect heuristic, state dependence, anchoring and availability bias; and little or no evidence of affective forecasting. Framing effects were apparent in overestimation of benefits and downplaying or omitting potential harms. We found evidence of cognitive bias in decision making for ICD implantation. The majority of these biases appeared to encourage ICD treatment. Published by Elsevier Inc.

RF plasma-driven hydrogen permeation through a biased iron membrane

International Nuclear Information System (INIS)

Banno, T.; Waelbroeck, F.; Winter, J.

1984-01-01

The steady-state RF plasma-driven hydrogen permeation through an electrically biased iron membrane has been investigated as a function of the bias potential Vsub(M) for membrane temperatures in the range of 150-400 0 C. Vsub(M) has been gradually increased positively from the floating potential of the membrane. The permeation flux decreases when Vsub(M) increases at low voltages: positive hydrogen ions are repelled. The membrane temperature does not influence this effect measurably. The permeation flux starts to increase when Vsub(M) is raised higher, i.e. when energetic electrons strike the surface. This phenomenon shows a pronounced temperature dependence - the enhancement is largest for the lowest temperatures. The effect is interpreted in terms of an electron-induced dissociation of hydrogen molecules on the membrane surface. (orig.)

Attention bias towards negative emotional information and its relationship with daily worry in the context of acute stress: An eye-tracking study.

Science.gov (United States)

Macatee, Richard J; Albanese, Brian J; Schmidt, Norman B; Cougle, Jesse R

2017-03-01

Cognitive theories of anxiety psychopathology cite biased attention towards threat as a central vulnerability and maintaining factor. However, many studies have found threat bias indices to have poor reliability and have failed to observe the theorized relationship between threat bias and anxiety symptoms; this may be due to the non-unitary nature of threat bias and the influence of state-level variables on its expression. Accumulating data suggests that state anxious mood is important for the robust expression of threat bias and for relations to emerge between threat bias and symptoms, though this possibility has not been experimentally tested. Eye-tracking was used to assess multiple forms of threat bias (i.e., early vigilance, sustained attention, facilitated engagement, delayed disengagement) thought to be related to anxiety. A non-clinical sample (N = 165) was recruited to test the hypothesis that biased attention towards threat, but not dysphoric or positive emotional stimuli, during an anxious mood induction, but not at a pre-stress baseline, would prospectively predict greater worry symptoms on days in which more naturalistic stressors occurred. Results revealed the hypothesized moderation effect for sustained attention towards threat after the mood induction but not at baseline, though sustained attention towards dysphoric stimuli also moderated the effect of stressors on worry. Worry-relevant sustained attention towards negative emotional stimuli may be a partially mood-context dependent phenomenon. Copyright © 2016 Elsevier Ltd. All rights reserved.

Towards quantum signatures in a swept-bias Josephson junction

Energy Technology Data Exchange (ETDEWEB)

Losert, Harald; Vogel, Karl; Schleich, Wolfgang P. [Institut fuer Quantenphysik and Center for Integrated Quantum Science and Technology (IQST), Universitaet Ulm, D-89069 Ulm (Germany)

2016-07-01

Josephson junctions are one of the best examples for the observation of macroscopic quantum tunneling. The phase difference in a current-biased Josephson junction behaves like the position of a particle in a tilted washboard potential. The escape of this phase-particle corresponds to the voltage switching of the associated junction. Quantum mechanically, the escape from the washboard potential can be explained as tunneling from the ground state, or an excited state. However, it has been shown, that in the case of periodic driving the experimental data for quantum mechanical key features, e.g. Rabi oscillations or energy level quantization, can be reproduced by a completely classical description. Motivated by this discussion, we investigate a swept-bias Josephson junction in the case of a large critical current. In particular, we contrast the switching current distributions resulting from a quantum mechanical and classical description of the time evolution.

Biases in categorization

NARCIS (Netherlands)

Das-Smaal, E.A.

1990-01-01

On what grounds can we conclude that an act of categorization is biased? In this chapter, it is contended that in the absence of objective norms of what categories actually are, biases in categorization can only be specified in relation to theoretical understandings of categorization. Therefore, the

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

Science.gov (United States)

Hirsch, Robert M.

2014-01-01

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

Cognitive Dissonance, Confirmatory Bias and Inadequate Information Processing: Evidence from Experimental Auctions

OpenAIRE

Cao, Ying; Just, David R.; Wansink, Brian

2014-01-01

Using psychological terms such as cognitive dissonance and confirmation bias, this study reveals how individual consumers inadequately process (food safety) information, pay limited attention to signals, and make purchase decisions that are bias towards their initial choices. While it is expected that reading extra information about potential risk associated with the food decreases consumers' willingness to pay (WTP), the magnitude of the impact varies across individuals. In general, consumer...

Biased Agonism of Endogenous Opioid Peptides at the μ-Opioid Receptor.

Science.gov (United States)

Thompson, Georgina L; Lane, J Robert; Coudrat, Thomas; Sexton, Patrick M; Christopoulos, Arthur; Canals, Meritxell

2015-08-01

Biased agonism is having a major impact on modern drug discovery, and describes the ability of distinct G protein-coupled receptor (GPCR) ligands to activate different cell signaling pathways, and to result in different physiologic outcomes. To date, most studies of biased agonism have focused on synthetic molecules targeting various GPCRs; however, many of these receptors have multiple endogenous ligands, suggesting that "natural" bias may be an unappreciated feature of these GPCRs. The μ-opioid receptor (MOP) is activated by numerous endogenous opioid peptides, remains an attractive therapeutic target for the treatment of pain, and exhibits biased agonism in response to synthetic opiates. The aim of this study was to rigorously assess the potential for biased agonism in the actions of endogenous opioids at the MOP in a common cellular background, and compare these to the effects of the agonist d-Ala2-N-MePhe4-Gly-ol enkephalin (DAMGO). We investigated activation of G proteins, inhibition of cAMP production, extracellular signal-regulated kinase 1 and 2 phosphorylation, β-arrestin 1/2 recruitment, and MOP trafficking, and applied a novel analytical method to quantify biased agonism. Although many endogenous opioids displayed signaling profiles similar to that of DAMGO, α-neoendorphin, Met-enkephalin-Arg-Phe, and the putatively endogenous peptide endomorphin-1 displayed particularly distinct bias profiles. These may represent examples of natural bias if it can be shown that they have different signaling properties and physiologic effects in vivo compared with other endogenous opioids. Understanding how endogenous opioids control physiologic processes through biased agonism can reveal vital information required to enable the design of biased opioids with improved pharmacological profiles and treat diseases involving dysfunction of the endogenous opioid system. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

Quality of reporting and risk of bias in therapeutic otolaryngology publications.

Science.gov (United States)

Kaper, N M; Swart, K M A; Grolman, W; Van Der Heijden, G J M G

2018-01-01

High-quality trials have the potential to influence clinical practice. Ten otolaryngology journals with the highest 2011 impact factors were selected and publications from 2010 were extracted. From all medical journals, the 20 highest impact factor journals were selected, and publications related to otolaryngology for 2010 and 2011 were extracted. For all publications, the reporting quality and risk of bias were assessed. The impact factor was 1.8-2.8 for otolaryngology journals and 6.0-101.8 for medical journals. Of 1500 otolaryngology journal articles, 262 were therapeutic studies; 94 had a high reporting quality and 5 a low risk of bias. Of 10 967 medical journal articles, 76 were therapeutic studies; 57 had a high reporting quality and 8 a low risk of bias. Reporting quality was high for 45 per cent of otolaryngology-related publications and 9 per cent met quality standards. General journals had higher impact factors than otolaryngology journals. Reporting quality was higher and risk of bias lower in general journals than in otolaryngology journals. Nevertheless, 76 per cent of articles in high impact factor journals carried a high risk of bias. Better reported and designed studies are the goal, with less risk of bias, especially in otolaryngology journals.

Polyglutamine repeats are associated to specific sequence biases that are conserved among eukaryotes.

Directory of Open Access Journals (Sweden)

Matteo Ramazzotti

Full Text Available Nine human neurodegenerative diseases, including Huntington's disease and several spinocerebellar ataxia, are associated to the aggregation of proteins comprising an extended tract of consecutive glutamine residues (polyQs once it exceeds a certain length threshold. This event is believed to be the consequence of the expansion of polyCAG codons during the replication process. This is in apparent contradiction with the fact that many polyQs-containing proteins remain soluble and are encoded by invariant genes in a number of eukaryotes. The latter suggests that polyQs expansion and/or aggregation might be counter-selected through a genetic and/or protein context. To identify this context, we designed a software that scrutinize entire proteomes in search for imperfect polyQs. The nature of residues flanking the polyQs and that of residues other than Gln within polyQs (insertions were assessed. We discovered strong amino acid residue biases robustly associated to polyQs in the 15 eukaryotic proteomes we examined, with an over-representation of Pro, Leu and His and an under-representation of Asp, Cys and Gly amino acid residues. These biases are conserved amongst unrelated proteins and are independent of specific functional classes. Our findings suggest that specific residues have been co-selected with polyQs during evolution. We discuss the possible selective pressures responsible of the observed biases.

The Effect of Self-Explaining on Robust Learning

Science.gov (United States)

Hausmann, Robert G. M.; VanLehn, Kurt

2010-01-01

Self-explaining is a domain-independent learning strategy that generally leads to a robust understanding of the domain material. However, there are two potential explanations for its effectiveness. First, self-explanation generates additional "content" that does not exist in the instructional materials. Second, when compared to…

Quantifying lead-time bias in risk factor studies of cancer through simulation.

Science.gov (United States)

Jansen, Rick J; Alexander, Bruce H; Anderson, Kristin E; Church, Timothy R

2013-11-01

Lead-time is inherent in early detection and creates bias in observational studies of screening efficacy, but its potential to bias effect estimates in risk factor studies is not always recognized. We describe a form of this bias that conventional analyses cannot address and develop a model to quantify it. Surveillance Epidemiology and End Results (SEER) data form the basis for estimates of age-specific preclinical incidence, and log-normal distributions describe the preclinical duration distribution. Simulations assume a joint null hypothesis of no effect of either the risk factor or screening on the preclinical incidence of cancer, and then quantify the bias as the risk-factor odds ratio (OR) from this null study. This bias can be used as a factor to adjust observed OR in the actual study. For this particular study design, as average preclinical duration increased, the bias in the total-physical activity OR monotonically increased from 1% to 22% above the null, but the smoking OR monotonically decreased from 1% above the null to 5% below the null. The finding of nontrivial bias in fixed risk-factor effect estimates demonstrates the importance of quantitatively evaluating it in susceptible studies. Copyright © 2013 Elsevier Inc. All rights reserved.

ROBUST CYLINDER FITTING IN THREE-DIMENSIONAL POINT CLOUD DATA

Directory of Open Access Journals (Sweden)

A. Nurunnabi

2017-05-01

Full Text Available This paper investigates the problems of cylinder fitting in laser scanning three-dimensional Point Cloud Data (PCD. Most existing methods require full cylinder data, do not study the presence of outliers, and are not statistically robust. But especially mobile laser scanning often has incomplete data, as street poles for example are only scanned from the road. Moreover, existence of outliers is common. Outliers may occur as random or systematic errors, and may be scattered and/or clustered. In this paper, we present a statistically robust cylinder fitting algorithm for PCD that combines Robust Principal Component Analysis (RPCA with robust regression. Robust principal components as obtained by RPCA allow estimating cylinder directions more accurately, and an existing efficient circle fitting algorithm following robust regression principles, properly fit cylinder. We demonstrate the performance of the proposed method on artificial and real PCD. Results show that the proposed method provides more accurate and robust results: (i in the presence of noise and high percentage of outliers, (ii for incomplete as well as complete data, (iii for small and large number of points, and (iv for different sizes of radius. On 1000 simulated quarter cylinders of 1m radius with 10% outliers a PCA based method fit cylinders with a radius of on average 3.63 meter (m; the proposed method on the other hand fit cylinders of on average 1.02 m radius. The algorithm has potential in applications such as fitting cylindrical (e.g., light and traffic poles, diameter at breast height estimation for trees, and building and bridge information modelling.

Cognitive bias measurement and social anxiety disorder: Correlating self-report data and attentional bias

Directory of Open Access Journals (Sweden)

Alexander Miloff

2015-09-01

Full Text Available Social anxiety disorder (SAD and attentional bias are theoretically connected in cognitive behavioral therapeutic models. In fact, there is an emerging field focusing on modifying attentional bias as a stand-alone treatment. However, it is unclear to what degree these attentional biases are present before commencing treatment. The purpose of this study was to measure pre-treatment attentional bias in 153 participants diagnosed with SAD using a home-based Internet version of the dot-probe paradigm. Results showed no significant correlation for attentional bias (towards or away from negative words or faces and the self-rated version of the Liebowitz Social Anxiety Scale (LSAS-SR. However, two positive correlations were found for the secondary measures Generalized Anxiety Disorder 7 (GAD-7 and Patient Health Questionnaire 9 (PHQ-9. These indicated that those with elevated levels of anxiety and depression had a higher bias towards negative faces in neutral–negative and positive–negative valence combinations, respectively. The unreliability of the dot-probe paradigm and home-based Internet delivery are discussed to explain the lack of correlations between LSAS-SR and attentional bias. Changes to the dot-probe task are suggested that could improve reliability.

Sampling bias in an internet treatment trial for depression.

Science.gov (United States)

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

2012-10-23

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

Ensemble stacking mitigates biases in inference of synaptic connectivity

Directory of Open Access Journals (Sweden)

Brendan Chambers

2018-03-01

Full Text Available A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches. Mapping the routing of spikes through local circuitry is crucial for understanding neocortical computation. Under appropriate experimental conditions, these maps can be used to infer likely patterns of synaptic recruitment, linking activity to underlying anatomical connections. Such inferences help to reveal the synaptic implementation of population dynamics and computation. We compare a number of standard functional measures to infer underlying connectivity. We find that regularization impacts measures

Robustness of structures

DEFF Research Database (Denmark)

Vrouwenvelder, T.; Sørensen, John Dalsgaard

2009-01-01

After the collapse of the World Trade Centre towers in 2001 and a number of collapses of structural systems in the beginning of the century, robustness of structural systems has gained renewed interest. Despite many significant theoretical, methodical and technological advances, structural...... of robustness for structural design such requirements are not substantiated in more detail, nor have the engineering profession been able to agree on an interpretation of robustness which facilitates for its uantification. A European COST action TU 601 on ‘Robustness of structures' has started in 2007...... by a group of members of the CSS. This paper describes the ongoing work in this action, with emphasis on the development of a theoretical and risk based quantification and optimization procedure on the one side and a practical pre-normative guideline on the other....

A wide-bandwidth and high-sensitivity robust microgyroscope

International Nuclear Information System (INIS)

Sahin, Korhan; Sahin, Emre; Akin, Tayfun; Alper, Said Emre

2009-01-01

This paper reports a microgyroscope design concept with the help of a 2 degrees of freedom (DoF) sense mode to achieve a wide bandwidth without sacrificing mechanical and electronic sensitivity and to obtain robust operation against variations under ambient conditions. The design concept is demonstrated with a tuning fork microgyroscope fabricated with an in-house silicon-on-glass micromachining process. When the fabricated gyroscope is operated with a relatively wide bandwidth of 1 kHz, measurements show a relatively high raw mechanical sensitivity of 131 µV (° s −1 ) −1 . The variation in the amplified mechanical sensitivity (scale factor) of the gyroscope is measured to be less than 0.38% for large ambient pressure variations such as from 40 to 500 mTorr. The bias instability and angle random walk of the gyroscope are measured to be 131° h −1 and 1.15° h −1/2 , respectively

Robust Semi-Supervised Manifold Learning Algorithm for Classification

Directory of Open Access Journals (Sweden)

Mingxia Chen

2018-01-01

Full Text Available In the recent years, manifold learning methods have been widely used in data classification to tackle the curse of dimensionality problem, since they can discover the potential intrinsic low-dimensional structures of the high-dimensional data. Given partially labeled data, the semi-supervised manifold learning algorithms are proposed to predict the labels of the unlabeled points, taking into account label information. However, these semi-supervised manifold learning algorithms are not robust against noisy points, especially when the labeled data contain noise. In this paper, we propose a framework for robust semi-supervised manifold learning (RSSML to address this problem. The noisy levels of the labeled points are firstly predicted, and then a regularization term is constructed to reduce the impact of labeled points containing noise. A new robust semi-supervised optimization model is proposed by adding the regularization term to the traditional semi-supervised optimization model. Numerical experiments are given to show the improvement and efficiency of RSSML on noisy data sets.

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

Science.gov (United States)

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.

The Selective Advantage of Synonymous Codon Usage Bias in Salmonella.

Directory of Open Access Journals (Sweden)

Gerrit Brandis

2016-03-01

Full Text Available The genetic code in mRNA is redundant, with 61 sense codons translated into 20 different amino acids. Individual amino acids are encoded by up to six different codons but within codon families some are used more frequently than others. This phenomenon is referred to as synonymous codon usage bias. The genomes of free-living unicellular organisms such as bacteria have an extreme codon usage bias and the degree of bias differs between genes within the same genome. The strong positive correlation between codon usage bias and gene expression levels in many microorganisms is attributed to selection for translational efficiency. However, this putative selective advantage has never been measured in bacteria and theoretical estimates vary widely. By systematically exchanging optimal codons for synonymous codons in the tuf genes we quantified the selective advantage of biased codon usage in highly expressed genes to be in the range 0.2-4.2 x 10-4 per codon per generation. These data quantify for the first time the potential for selection on synonymous codon choice to drive genome-wide sequence evolution in bacteria, and in particular to optimize the sequences of highly expressed genes. This quantification may have predictive applications in the design of synthetic genes and for heterologous gene expression in biotechnology.

Empathy costs: Negative emotional bias in high empathisers.

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Chikovani, George; Babuadze, Lasha; Iashvili, Nino; Gvalia, Tamar; Surguladze, Simon

2015-09-30

Excessive empathy has been associated with compassion fatigue in health professionals and caregivers. We investigated an effect of empathy on emotion processing in 137 healthy individuals of both sexes. We tested a hypothesis that high empathy may underlie increased sensitivity to negative emotion recognition which may interact with gender. Facial emotion stimuli comprised happy, angry, fearful, and sad faces presented at different intensities (mild and prototypical) and different durations (500ms and 2000ms). The parameters of emotion processing were represented by discrimination accuracy, response bias and reaction time. We found that higher empathy was associated with better recognition of all emotions. We also demonstrated that higher empathy was associated with response bias towards sad and fearful faces. The reaction time analysis revealed that higher empathy in females was associated with faster (compared with males) recognition of mildly sad faces of brief duration. We conclude that although empathic abilities were providing for advantages in recognition of all facial emotional expressions, the bias towards emotional negativity may potentially carry a risk for empathic distress. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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

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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.

Resolving Multi-Stakeholder Robustness Asymmetries in Coupled Agricultural and Urban Systems

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Li, Yu; Giuliani, Matteo; Castelletti, Andrea; Reed, Patrick

2016-04-01

The evolving pressures from a changing climate and society are increasingly motivating decision support frameworks that consider the robustness of management actions across many possible futures. Focusing on robustness is helpful for investigating key vulnerabilities within current water systems and for identifying potential tradeoffs across candidate adaptation responses. To date, most robustness studies assume a social planner perspective by evaluating highly aggregated measures of system performance. This aggregate treatment of stakeholders does not explore the equity or intrinsic multi-stakeholder conflicts implicit to the system-wide measures of performance benefits and costs. The commonly present heterogeneity across complex management interests, however, may produce strong asymmetries for alternative adaptation options, designed to satisfy system-level targets. In this work, we advance traditional robustness decision frameworks by replacing the centralized social planner with a bottom-up, agent-based approach, where stakeholders are modeled as individuals, and represented as potentially self-interested agents. This agent-based model enables a more explicit exploration of the potential inequities and asymmetries in the distribution of the system-wide benefit. The approach is demonstrated by exploring the potential conflicts between urban flooding and agricultural production in the Lake Como system (Italy). Lake Como is a regulated lake that is operated to supply water to the downstream agricultural district (Muzza as the pilot study area in this work) composed of a set of farmers with heterogeneous characteristics in terms of water allocation, cropping patterns, and land properties. Supplying water to farmers increases the risk of floods along the lakeshore and therefore the system is operated based on the tradeoff between these two objectives. We generated an ensemble of co-varying climate and socio-economic conditions and evaluated the robustness of the

Photovoltaic Bias Generator

Science.gov (United States)

2018-02-01

Department of the Army position unless so designated by other authorized documents. Citation of manufacturer’s or trade names does not constitute an... Interior view of the photovoltaic bias generator showing wrapped-wire side of circuit board...3 Fig. 4 Interior view of the photovoltaic bias generator showing component side of circuit board

The own-age bias in face memory is unrelated to differences in attention--evidence from event-related potentials.

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Neumann, Markus F; End, Albert; Luttmann, Stefanie; Schweinberger, Stefan R; Wiese, Holger

2015-03-01

Participants are more accurate at remembering faces from their own relative to a different age group (the own-age bias, or OAB). A recent socio-cognitive account has suggested that differential allocation of attention to old versus young faces underlies this phenomenon. Critically, empirical evidence for a direct relationship between attention to own- versus other-age faces and the OAB in memory is lacking. To fill this gap, we tested the roles of attention in three different experimental paradigms, and additionally analyzed event-related brain potentials (ERPs). In Experiment 1, we compared the learning of old and young faces during focused versus divided attention, but revealed similar OABs in subsequent memory for both attention conditions. Similarly, manipulating attention during learning did not differentially affect the ERPs elicited by young versus old faces. In Experiment 2, we examined the repetition effects from task-irrelevant old and young faces presented under varying attentional loads on the N250r ERP component as an index of face recognition. Independent of load, the N250r effects were comparable for both age categories. Finally, in Experiment 3 we measured the N2pc as an index of attentional selection of old versus young target faces in a visual search task. The N2pc was not significantly different for the young versus the old target search conditions, suggesting similar orientations of attention to either face age group. Overall, we propose that the OAB in memory is largely unrelated to early attentional processes. Our findings therefore contrast with the predictions from socio-cognitive accounts on own-group biases in recognition memory, and are more easily reconciled with expertise-based models.

Bias-correction in vector autoregressive models

DEFF Research Database (Denmark)

Engsted, Tom; Pedersen, Thomas Quistgaard

2014-01-01

We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study......, we show that when the model is stationary this simple bias formula compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models, the analytical bias formula performs noticeably worse than bootstrapping. Both methods yield a notable...... improvement over ordinary least squares. We pay special attention to the risk of pushing an otherwise stationary model into the non-stationary region of the parameter space when correcting for bias. Finally, we consider a recently proposed reduced-bias weighted least squares estimator, and we find...

Sex-biased phoretic mite load on two seaweed flies: Coelopa frigida and Coelopa pilipes.

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Gilburn, Andre S; Stewart, Katie M; Edward, Dominic A

2009-12-01

Two hypotheses explain male-biased parasitism. Physiological costs of male sexually selected characteristics can reduce immunocompetence. Alternatively, ecological differences could generate male-biased parasitism. One method of comparing the importance of the two theories is to investigate patterns of phoresy, which are only likely to be generated by ecological rather than immunological differences between the sexes. Here we studied the pattern of phoresy of the mite, Thinoseius fucicola, on two species of seaweed fly hosts, Coelopa frigida and Coelopa pilipes. We found a highly male-biased pattern of phoresy of T. fucicola on both species. These are the first reported instances of sex-biased phoresy in a solely phoretic parasite. We also show the first two cases of size-biased phoresy. We suggest that ecological factors, particularly, male mate searching, generated male biased patterns of phoresy. We highlight the potential importance of studies of phoresy in determining the relative roles of the immunocompetence and ecological theories in generating male-biased parasitism. We suggest that more studies of patterns of phoresy are carried out to allow detailed comparisons with patterns of parasitism.

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

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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.

Facial expression judgments support a socio-relational model, rather than a negativity bias model of political psychology.

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Vigil, Jacob M; Strenth, Chance

2014-06-01

Self-reported opinions and judgments may be more rooted in expressive biases than in cognitive processing biases, and ultimately operate within a broader behavioral style for advertising the capacity - versus the trustworthiness - dimension of human reciprocity potential. Our analyses of facial expression judgments of likely voters are consistent with this thesis, and directly contradict one major prediction from the authors' "negativity-bias" model.

Robustness of Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

2008-01-01

This paper describes the background of the robustness requirements implemented in the Danish Code of Practice for Safety of Structures and in the Danish National Annex to the Eurocode 0, see (DS-INF 146, 2003), (DS 409, 2006), (EN 1990 DK NA, 2007) and (Sørensen and Christensen, 2006). More...... frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new structures essential....... According to Danish design rules robustness shall be documented for all structures in high consequence class. The design procedure to document sufficient robustness consists of: 1) Review of loads and possible failure modes / scenarios and determination of acceptable collapse extent; 2) Review...

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

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

2012-06-01

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

Dynamics robustness of cascading systems.

Directory of Open Access Journals (Sweden)

Jonathan T Young

2017-03-01

Full Text Available A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1 Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2 Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it

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

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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

Alternative global goodness metrics and sensitivity analysis: heuristics to check the robustness of conclusions from studies comparing virtual screening methods.

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Sheridan, Robert P

2008-02-01

We introduce two ways of testing the robustness of conclusions from studies comparing virtual screening methods: alternative "global goodness" metrics and sensitivity analysis. While the robustness tests cannot eliminate all biases in virtual screening comparisons, they are useful as a "reality check" for any given study. To illustrate this, we apply them to a set of enrichments published in McGaughey et al. (J. Chem. Inf. Model. 2007, 47, 1504-1519) where 11 target protein/ligand combinations are tested on 2D and 3D similarity methods, plus docking. The major conclusions in that paper, for instance, that ligand-based methods are better than docking methods, hold up. However, some minor conclusions, such as Glide being the best docking method, do not.

Opinion dynamics with confirmation bias.

Directory of Open Access Journals (Sweden)

Armen E Allahverdyan

Full Text Available 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.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.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.

Robust and distributed hypothesis testing

CERN Document Server

Gül, Gökhan

2017-01-01

This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the boo...

Robustness Property of Robust-BD Wald-Type Test for Varying-Dimensional General Linear Models

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Xiao Guo

2018-03-01

Full Text Available An important issue for robust inference is to examine the stability of the asymptotic level and power of the test statistic in the presence of contaminated data. Most existing results are derived in finite-dimensional settings with some particular choices of loss functions. This paper re-examines this issue by allowing for a diverging number of parameters combined with a broader array of robust error measures, called “robust- BD ”, for the class of “general linear models”. Under regularity conditions, we derive the influence function of the robust- BD parameter estimator and demonstrate that the robust- BD Wald-type test enjoys the robustness of validity and efficiency asymptotically. Specifically, the asymptotic level of the test is stable under a small amount of contamination of the null hypothesis, whereas the asymptotic power is large enough under a contaminated distribution in a neighborhood of the contiguous alternatives, thus lending supports to the utility of the proposed robust- BD Wald-type test.

Accounting for biases in riboprofiling data indicates a major role for proline in stalling translation.

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Artieri, Carlo G; Fraser, Hunter B

2014-12-01

The recent advent of ribosome profiling-sequencing of short ribosome-bound fragments of mRNA-has offered an unprecedented opportunity to interrogate the sequence features responsible for modulating translational rates. Nevertheless, numerous analyses of the first riboprofiling data set have produced equivocal and often incompatible results. Here we analyze three independent yeast riboprofiling data sets, including two with much higher coverage than previously available, and find that all three show substantial technical sequence biases that confound interpretations of ribosomal occupancy. After accounting for these biases, we find no effect of previously implicated factors on ribosomal pausing. Rather, we find that incorporation of proline, whose unique side-chain stalls peptide synthesis in vitro, also slows the ribosome in vivo. We also reanalyze a method that implicated positively charged amino acids as the major determinant of ribosomal stalling and demonstrate that it produces false signals of stalling in low-coverage data. Our results suggest that any analysis of riboprofiling data should account for sequencing biases and sparse coverage. To this end, we establish a robust methodology that enables analysis of ribosome profiling data without prior assumptions regarding which positions spanned by the ribosome cause stalling. © 2014 Artieri and Fraser; Published by Cold Spring Harbor Laboratory Press.

Robust Linear Models for Cis-eQTL Analysis.

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Rantalainen, Mattias; Lindgren, Cecilia M; Holmes, Christopher C

2015-01-01

Expression Quantitative Trait Loci (eQTL) analysis enables characterisation of functional genetic variation influencing expression levels of individual genes. In outbread populations, including humans, eQTLs are commonly analysed using the conventional linear model, adjusting for relevant covariates, assuming an allelic dosage model and a Gaussian error term. However, gene expression data generally have noise that induces heavy-tailed errors relative to the Gaussian distribution and often include atypical observations, or outliers. Such departures from modelling assumptions can lead to an increased rate of type II errors (false negatives), and to some extent also type I errors (false positives). Careful model checking can reduce the risk of type-I errors but often not type II errors, since it is generally too time-consuming to carefully check all models with a non-significant effect in large-scale and genome-wide studies. Here we propose the application of a robust linear model for eQTL analysis to reduce adverse effects of deviations from the assumption of Gaussian residuals. We present results from a simulation study as well as results from the analysis of real eQTL data sets. Our findings suggest that in many situations robust models have the potential to provide more reliable eQTL results compared to conventional linear models, particularly in respect to reducing type II errors due to non-Gaussian noise. Post-genomic data, such as that generated in genome-wide eQTL studies, are often noisy and frequently contain atypical observations. Robust statistical models have the potential to provide more reliable results and increased statistical power under non-Gaussian conditions. The results presented here suggest that robust models should be considered routinely alongside other commonly used methodologies for eQTL analysis.

Quantifying Heuristic Bias: Anchoring, Availability, and Representativeness.

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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

Sensitivity and bias in decision-making under risk: evaluating the perception of reward, its probability and value.

Directory of Open Access Journals (Sweden)

Madeleine E Sharp

Full Text Available BACKGROUND: There are few clinical tools that assess decision-making under risk. Tests that characterize sensitivity and bias in decisions between prospects varying in magnitude and probability of gain may provide insights in conditions with anomalous reward-related behaviour. OBJECTIVE: We designed a simple test of how subjects integrate information about the magnitude and the probability of reward, which can determine discriminative thresholds and choice bias in decisions under risk. DESIGN/METHODS: Twenty subjects were required to choose between two explicitly described prospects, one with higher probability but lower magnitude of reward than the other, with the difference in expected value between the two prospects varying from 3 to 23%. RESULTS: Subjects showed a mean threshold sensitivity of 43% difference in expected value. Regarding choice bias, there was a 'risk premium' of 38%, indicating a tendency to choose higher probability over higher reward. An analysis using prospect theory showed that this risk premium is the predicted outcome of hypothesized non-linearities in the subjective perception of reward value and probability. CONCLUSIONS: This simple test provides a robust measure of discriminative value thresholds and biases in decisions under risk. Prospect theory can also make predictions about decisions when subjective perception of reward or probability is anomalous, as may occur in populations with dopaminergic or striatal dysfunction, such as Parkinson's disease and schizophrenia.

Sensitivity and Bias in Decision-Making under Risk: Evaluating the Perception of Reward, Its Probability and Value

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Sharp, Madeleine E.; Viswanathan, Jayalakshmi; Lanyon, Linda J.; Barton, Jason J. S.

2012-01-01

Background There are few clinical tools that assess decision-making under risk. Tests that characterize sensitivity and bias in decisions between prospects varying in magnitude and probability of gain may provide insights in conditions with anomalous reward-related behaviour. Objective We designed a simple test of how subjects integrate information about the magnitude and the probability of reward, which can determine discriminative thresholds and choice bias in decisions under risk. Design/Methods Twenty subjects were required to choose between two explicitly described prospects, one with higher probability but lower magnitude of reward than the other, with the difference in expected value between the two prospects varying from 3 to 23%. Results Subjects showed a mean threshold sensitivity of 43% difference in expected value. Regarding choice bias, there was a ‘risk premium’ of 38%, indicating a tendency to choose higher probability over higher reward. An analysis using prospect theory showed that this risk premium is the predicted outcome of hypothesized non-linearities in the subjective perception of reward value and probability. Conclusions This simple test provides a robust measure of discriminative value thresholds and biases in decisions under risk. Prospect theory can also make predictions about decisions when subjective perception of reward or probability is anomalous, as may occur in populations with dopaminergic or striatal dysfunction, such as Parkinson's disease and schizophrenia. PMID:22493669

Estimating open population site occupancy from presence-absence data lacking the robust design.

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Dail, D; Madsen, L

2013-03-01

Many animal monitoring studies seek to estimate the proportion of a study area occupied by a target population. The study area is divided into spatially distinct sites where the detected presence or absence of the population is recorded, and this is repeated in time for multiple seasons. However, when occupied sites are detected with probability p Ecology 84, 2200-2207) developed a multiseason model for estimating seasonal site occupancy (ψt ) while accounting for unknown p. Their model performs well when observations are collected according to the robust design, where multiple sampling occasions occur during each season; the repeated sampling aids in the estimation p. However, their model does not perform as well when the robust design is lacking. In this paper, we propose an alternative likelihood model that yields improved seasonal estimates of p and Ψt in the absence of the robust design. We construct the marginal likelihood of the observed data by conditioning on, and summing out, the latent number of occupied sites during each season. A simulation study shows that in cases without the robust design, the proposed model estimates p with less bias than the MacKenzie et al. model and hence improves the estimates of Ψt . We apply both models to a data set consisting of repeated presence-absence observations of American robins (Turdus migratorius) with yearly survey periods. The two models are compared to a third estimator available when the repeated counts (from the same study) are considered, with the proposed model yielding estimates of Ψt closest to estimates from the point count model. Copyright © 2013, The International Biometric Society.

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

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Vetter, Thomas R; Mascha, Edward J

2017-09-01

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

The impact of virtual reality on implicit racial bias and mock legal decisions.

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Salmanowitz, Natalie

2018-05-01

Implicit racial biases are one of the most vexing problems facing current society. These split-second judgments are not only widely prevalent, but also are notoriously difficult to overcome. Perhaps most concerning, implicit racial biases can have consequential impacts on decisions in the courtroom, where scholars have been unable to provide a viable mitigation strategy. This article examines the influence of a short virtual reality paradigm on implicit racial biases and evaluations of legal scenarios. After embodying a black avatar in the virtual world, participants produced significantly lower implicit racial bias scores than those who experienced a sham version of the virtual reality paradigm. Additionally, these participants more conservatively evaluated an ambiguous legal case, rating vague evidence as less indicative of guilt and rendering more Not Guilty verdicts. As the first experiment of its kind, this study demonstrates the potential of virtual reality to address implicit racial bias in the courtroom setting.

The impact of virtual reality on implicit racial bias and mock legal decisions

Science.gov (United States)

Salmanowitz, Natalie

2018-01-01

Abstract Implicit racial biases are one of the most vexing problems facing current society. These split-second judgments are not only widely prevalent, but also are notoriously difficult to overcome. Perhaps most concerning, implicit racial biases can have consequential impacts on decisions in the courtroom, where scholars have been unable to provide a viable mitigation strategy. This article examines the influence of a short virtual reality paradigm on implicit racial biases and evaluations of legal scenarios. After embodying a black avatar in the virtual world, participants produced significantly lower implicit racial bias scores than those who experienced a sham version of the virtual reality paradigm. Additionally, these participants more conservatively evaluated an ambiguous legal case, rating vague evidence as less indicative of guilt and rendering more Not Guilty verdicts. As the first experiment of its kind, this study demonstrates the potential of virtual reality to address implicit racial bias in the courtroom setting. PMID:29707220

Payoff Information Biases a Fast Guess Process in Perceptual Decision Making under Deadline Pressure: Evidence from Behavior, Evoked Potentials, and Quantitative Model Comparison.

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Noorbaloochi, Sharareh; Sharon, Dahlia; McClelland, James L

2015-08-05

We used electroencephalography (EEG) and behavior to examine the role of payoff bias in a difficult two-alternative perceptual decision under deadline pressure in humans. The findings suggest that a fast guess process, biased by payoff and triggered by stimulus onset, occurred on a subset of trials and raced with an evidence accumulation process informed by stimulus information. On each trial, the participant judged whether a rectangle was shifted to the right or left and responded by squeezing a right- or left-hand dynamometer. The payoff for each alternative (which could be biased or unbiased) was signaled 1.5 s before stimulus onset. The choice response was assigned to the first hand reaching a squeeze force criterion and reaction time was defined as time to criterion. Consistent with a fast guess account, fast responses were strongly biased toward the higher-paying alternative and the EEG exhibited an abrupt rise in the lateralized readiness potential (LRP) on a subset of biased payoff trials contralateral to the higher-paying alternative ∼ 150 ms after stimulus onset and 50 ms before stimulus information influenced the LRP. This rise was associated with poststimulus dynamometer activity favoring the higher-paying alternative and predicted choice and response time. Quantitative modeling supported the fast guess account over accounts of payoff effects supported in other studies. Our findings, taken with previous studies, support the idea that payoff and prior probability manipulations produce flexible adaptations to task structure and do not reflect a fixed policy for the integration of payoff and stimulus information. Humans and other animals often face situations in which they must make choices based on uncertain sensory information together with information about expected outcomes (gains or losses) about each choice. We investigated how differences in payoffs between available alternatives affect neural activity, overt choice, and the timing of choice

Self-face Captures, Holds, and Biases Attention.

Science.gov (United States)

Wójcik, Michał J; Nowicka, Maria M; Kotlewska, Ilona; Nowicka, Anna

2017-01-01

The implicit self-recognition process may take place already in the pre-attentive stages of perception. After a silent stimulus has captured attention, it is passed on to the attentive stage where it can affect decision making and responding. Numerous studies show that the presence of self-referential information affects almost every cognitive level. These effects may share a common and fundamental basis in an attentional mechanism, conceptualized as attentional bias: the exaggerated deployment of attentional resources to a salient stimulus. A gold standard in attentional bias research is the dot-probe paradigm. In this task, a prominent stimulus (cue) and a neutral stimulus are presented in different spatial locations, followed by the presentation of a target. In the current study we aimed at investigating whether the self-face captures, holds and biases attention when presented as a task-irrelevant stimulus. In two dot-probe experiments coupled with the event-related potential (ERP) technique we analyzed the following relevant ERPs components: N2pc and SPCN which reflect attentional shifts and the maintenance of attention, respectively. An inter-stimulus interval separating face-cues and probes (800 ms) was introduced only in the first experiment. In line with our predictions, in Experiment 1 the self-face elicited the N2pc and the SPCN component. In Experiment 2 in addition to N2pc, an attentional bias was observed. Our results indicate that unintentional self-face processing disables the top-down control setting to filter out distractors, thus leading to the engagement of attentional resources and visual short-term memory.

Self-face Captures, Holds, and Biases Attention

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Michał J. Wójcik

2018-01-01

Full Text Available The implicit self-recognition process may take place already in the pre-attentive stages of perception. After a silent stimulus has captured attention, it is passed on to the attentive stage where it can affect decision making and responding. Numerous studies show that the presence of self-referential information affects almost every cognitive level. These effects may share a common and fundamental basis in an attentional mechanism, conceptualized as attentional bias: the exaggerated deployment of attentional resources to a salient stimulus. A gold standard in attentional bias research is the dot-probe paradigm. In this task, a prominent stimulus (cue and a neutral stimulus are presented in different spatial locations, followed by the presentation of a target. In the current study we aimed at investigating whether the self-face captures, holds and biases attention when presented as a task-irrelevant stimulus. In two dot-probe experiments coupled with the event-related potential (ERP technique we analyzed the following relevant ERPs components: N2pc and SPCN which reflect attentional shifts and the maintenance of attention, respectively. An inter-stimulus interval separating face-cues and probes (800 ms was introduced only in the first experiment. In line with our predictions, in Experiment 1 the self-face elicited the N2pc and the SPCN component. In Experiment 2 in addition to N2pc, an attentional bias was observed. Our results indicate that unintentional self-face processing disables the top-down control setting to filter out distractors, thus leading to the engagement of attentional resources and visual short-term memory.

Satellite network robust QoS-aware routing

CERN Document Server

Long, Fei

2014-01-01

Satellite Network Robust QoS-aware Routing presents a novel routing strategy for satellite networks. This strategy is useful for the design of multi-layered satellite networks as it can greatly reduce the number of time slots in one system cycle. The traffic prediction and engineering approaches make the system robust so that the traffic spikes can be handled effectively. The multi-QoS optimization routing algorithm can satisfy various potential user requirements. Clear and sufficient illustrations are also presented in the book. As the chapters cover the above topics independently, readers from different research backgrounds in constellation design, multi-QoS routing, and traffic engineering can benefit from the book.   Fei Long is a senior engineer at Beijing R&D Center of 54th Research Institute of China Electronics Technology Group Corporation.

[Potential selection bias in telephone surveys: landline and mobile phones].

Science.gov (United States)

Garcia-Continente, Xavier; Pérez-Giménez, Anna; López, María José; Nebot, Manel

2014-01-01

The increasing use of mobile phones in the last decade has decreased landline telephone coverage in Spanish households. This study aimed to analyze sociodemographic characteristics and health indicators by type of telephone service (mobile phone vs. landline or landline and mobile phone). Two telephone surveys were conducted in Spanish samples (February 2010 and February 2011). Multivariate logistic regression analyses were performed to analyze differences in the main sociodemographic characteristics and health indicators according to the type of telephone service available in Spanish households. We obtained 2027 valid responses (1627 landline telephones and 400 mobile phones). Persons contacted through a mobile phone were more likely to be a foreigner, to belong to the manual social class, to have a lower educational level, and to be a smoker than those contacted through a landline telephone. The profile of the population that has only a mobile phone differs from that with a landline telephone. Therefore, telephone surveys that exclude mobile phones could show a selection bias. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

Emotional sensitization highlights the attentional bias in blood-injection-injury phobics: an ERP study.

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Sarlo, Michela; Buodo, Giulia; Devigili, Andrea; Munafò, Marianna; Palomba, Daniela

2011-02-18

The presence of an attentional bias towards disorder-related stimuli has not been consistently demonstrated in blood phobics. The present study was aimed at investigating whether or not an attentional bias, as measured by event-related potentials (ERPs), could be highlighted in blood phobics by inducing cognitive-emotional sensitization through the repetitive presentation of different disorder-related pictures. The mean amplitudes of the N100, P200, P300 and late positive potentials to picture onset were assessed along with subjective ratings of valence and arousal in 13 blood phobics and 12 healthy controls. Blood phobics, but not controls, showed a linear increase of subjective arousal over time, suggesting that cognitive-emotional sensitization did occur. The analysis of cortical responses showed larger N100 and smaller late positive potentials in phobics than in controls in response to mutilations. These findings suggest that cognitive-emotional sensitization induced an attentional bias in blood phobics during picture viewing, involving early selective encoding and late cognitive avoidance of disorder-related stimuli depicting mutilations. © 2010 Elsevier Ireland Ltd. All rights reserved.

Depression, not PTSD, is associated with attentional biases for emotional visual cues in early traumatized individuals with PTSD

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Charlotte Elisabeth Wittekind

2015-01-01

Full Text Available Using variants of the emotional Stroop task (EST, a large number of studies demonstrated attentional biases in individuals with PTSD across different types of trauma. However, the specificity and robustness of the emotional Stroop effect in PTSD were questioned recently. In particular, the paradigm cannot disentangle underlying cognitive mechanisms. Transgenerational studies provide evidence that consequences of trauma are not limited to the traumatized people, but extend to close relatives, especially the children. To further investigate attentional biases in PTSD and to shed light on the underlying cognitive mechanism(s, a spatial-cueing paradigm with pictures of different emotional valence (neutral, anxiety, depression, trauma was administered to individuals displaced as children during World War II with (n = 22 and without PTSD (n = 26 as well as to nontraumatized controls (n = 22. To assess whether parental PTSD is associated with biased information processing in children, each one adult offspring was also included in the study. PTSD was not associated with attentional biases for trauma-related stimuli. There was no evidence for a transgenerational transmission of biased information processing. However, when samples were regrouped based on current depression, a reduced inhibition of return (IOR effect emerged for depression-related cues. IOR refers to the phenomenon that with longer intervals between cue and target the validity effect is reversed: uncued locations are associated with shorter and cued locations with longer RTs. The results diverge from EST studies and demonstrate that findings on attentional biases yield equivocal results across different paradigms. Attentional biases for trauma-related material may only appear for verbal but not for visual stimuli in an elderly population with childhood trauma with PTSD. Future studies should more closely investigate whether findings from younger trauma populations also manifest in older

Automatic segmentation for brain MR images via a convex optimized segmentation and bias field correction coupled model.

Science.gov (United States)

Chen, Yunjie; Zhao, Bo; Zhang, Jianwei; Zheng, Yuhui

2014-09-01

Accurate segmentation of magnetic resonance (MR) images remains challenging mainly due to the intensity inhomogeneity, which is also commonly known as bias field. Recently active contour models with geometric information constraint have been applied, however, most of them deal with the bias field by using a necessary pre-processing step before segmentation of MR data. This paper presents a novel automatic variational method, which can segment brain MR images meanwhile correcting the bias field when segmenting images with high intensity inhomogeneities. We first define a function for clustering the image pixels in a smaller neighborhood. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. In order to reduce the effect of the noise, the local intensity variations are described by the Gaussian distributions with different means and variances. Then, the objective functions are integrated over the entire domain. In order to obtain the global optimal and make the results independent of the initialization of the algorithm, we reconstructed the energy function to be convex and calculated it by using the Split Bregman theory. A salient advantage of our method is that its result is independent of initialization, which allows robust and fully automated application. Our method is able to estimate the bias of quite general profiles, even in 7T MR images. Moreover, our model can also distinguish regions with similar intensity distribution with different variances. The proposed method has been rigorously validated with images acquired on variety of imaging modalities with promising results. Copyright © 2014 Elsevier Inc. All rights reserved.

Robustness Beamforming Algorithms

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Sajad Dehghani

2014-04-01

Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.

Economic Justification Of Robust Or Adaptive Planning And Design Of Resilient Water Resources Systems Under Deep Uncertainty: A Case Study In The Iolanda Water Treatment Plant Of Lusaka, Zambia

Science.gov (United States)

Mendoza, G.; Tkach, M.; Kucharski, J.; Chaudhry, R.

2017-12-01

This discussion is focused around the application of a bottom-up vulnerability assessment procedure for planning of climate resilience to a water treament plant for teh city of Iolanda, Zambia. This project is a Millennium Challenge Corporation (MCC) innitiaive with technical support by the UNESCO category II, International Center for Integrated Water Resources Management (ICIWaRM) with secretariat at the US Army Corps of Engineers Institute for Water Resources. The MCC is an innovative and independent U.S. foreign aid agency that is helping lead the fight against global poverty. The bottom-up vulnerability assessmentt framework examines critical performance thresholds, examines the external drivers that would lead to failure, establishes plausibility and analytical uncertainty that would lead to failure, and provides the economic justification for robustness or adaptability. This presentation will showcase the experiences in the application of the bottom-up framework to a region that is very vulnerable to climate variability, has poor instituional capacities, and has very limited data. It will illustrate the technical analysis and a decision process that led to a non-obvious climate robust solution. Most importantly it will highlight the challenges of utilizing discounted cash flow analysis (DCFA), such as net present value, in justifying robust or adaptive solutions, i.e. comparing solution under different future risks. We highlight a solution to manage the potential biases these DCFA procedures can incur.

Gender-Biased Expectations of Altruism in Adolescents

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Mauricio Salgado

2018-04-01

Full Text Available Research suggests that women, but not men, manifest gender-biased expectations of altruism: while women expect other women to be more altruistic, men expect women to be as generous as men. Do adolescents expect women and men to behave differently regarding altruism? I analyse adolescents' gender beliefs about altruism using a modified Dictator Game. Results indicate that adolescents believe that others of same gender are more altruistic than others of the opposite gender. I also found that adolescents' agreement with the existence of different societal roles for men and women moderates the relationship between gender and gender beliefs. Although it was expected that adolescents who agree with different gender roles would expect women to be more generous, surprisingly, the results presented here confirm this only for male adolescents, but in the opposite direction: the more male adolescents agree with the existence of different gender roles, the more they seem to believe that men are more generous than women. Meanwhile, female adolescents believe that women are more altruistic unconditionally. Thus, the previously documented bias seems to be already in place during adolescence, above and beyond other confounding factors. Adolescents' in-group bias, and their socialization into different cultural values regarding gender roles are discussed as potential explanatory mechanisms for these gender beliefs.

Sampling of temporal networks: Methods and biases

Science.gov (United States)

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

2017-11-01

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

Interpreting trial results following use of different intention-to-treat approaches for preventing attrition bias: a meta-epidemiological study protocol

OpenAIRE

Dossing, Anna; Tarp, Simon; Furst, Daniel E; Gluud, Christian; Beyene, Joseph; Hansen, Bjarke B; Bliddal, Henning; Christensen, Robin

2014-01-01

Introduction When participants drop out of randomised clinical trials, as frequently happens, the intention-to-treat (ITT) principle does not apply, potentially leading to attrition bias. Data lost from patient dropout/lack of follow-up are statistically addressed by imputing, a procedure prone to bias. Deviations from the original definition of ITT are referred to as modified intention-to-treat (mITT). As yet, the impact of the potential bias associated with mITT has not been assessed. Our o...

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

Science.gov (United States)

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.

Topotactic changes on η-Mo4O11 caused by biased atomic force microscope tip and cw-laser

International Nuclear Information System (INIS)

Borovšak, Miloš; Šutar, Petra; Goreshnik, Evgeny; Mihailovic, Dragan

2015-01-01

Highlights: • We report influencing electronic properties of η-Mo 4 O 11 . • With the biased AFM tip we induce the surface potential changes on η-Mo 4 O 11 . • We used cw-laser to induced similar effect on surface potential on η-Mo 4 O 11 . • We do not influence the surface and topography of the samples. • No change in topography of samples indicates the topotactic transformation. - Abstract: We present topotactic changes on Mo 4 O 11 crystals induced by a biased atomic force microscope tip and continuous laser. The transformation does not change the topography of the samples, while the surface potential shows remarkable changes on areas where the biased AFM tip was applied. No structural changes were observed by Raman spectroscopy, but AFM scans revealed changes to surface potential due to laser illumination. The observed phenomenon could be potentially useful for memristive memory devices considering the fact that properties of other molybdenum oxides vary from metallic to insulators.

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

Science.gov (United States)

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 in clinical intervention research

DEFF Research Database (Denmark)

Gluud, Lise Lotte

2006-01-01

Research on bias in clinical trials may help identify some of the reasons why investigators sometimes reach the wrong conclusions about intervention effects. Several quality components for the assessment of bias control have been suggested, but although they seem intrinsically valid, empirical...... evidence is needed to evaluate their effects on the extent and direction of bias. This narrative review summarizes the findings of methodological studies on the influence of bias in clinical trials. A number of methodological studies suggest that lack of adequate randomization in published trial reports...

Selection bias in the reported performances of AD classification pipelines

Directory of Open Access Journals (Sweden)

Alex F. Mendelson

2017-01-01

Full Text Available The last decade has seen a great proliferation of supervised learning pipelines for individual diagnosis and prognosis in Alzheimer's disease. As more pipelines are developed and evaluated in the search for greater performance, only those results that are relatively impressive will be selected for publication. We present an empirical study to evaluate the potential for optimistic bias in classification performance results as a result of this selection. This is achieved using a novel, resampling-based experiment design that effectively simulates the optimisation of pipeline specifications by individuals or collectives of researchers using cross validation with limited data. Our findings indicate that bias can plausibly account for an appreciable fraction (often greater than half of the apparent performance improvement associated with the pipeline optimisation, particularly in small samples. We discuss the consistency of our findings with patterns observed in the literature and consider strategies for bias reduction and mitigation.

Biases in medication prescribing: the case of second-generation antipsychotics.

Science.gov (United States)

Makhinson, Michael

2010-01-01

The shift from first-generation antipsychotic medications to second-generation antipsychotic medications initially caused a wave of excitement about the potential for improved and broader efficacy of these medications concurrent with an improved side-effect profile. Recent data from high-quality research analyses have subsequently raised significant questions about these claims. This research evidence has, however, not altered prescribing behavior in a way that would be expected from fully rational evaluation of the evidence. Prescribing decisions represent poorly understood, complex behaviors influenced by a number of external and internal forces, some of which may be elucidated by advances in social and cognitive psychology. In this article, the decision to prescribe first- versus second-generation antipsychotic medications is examined, and specific social psychological biases and individual cognitive biases are hypothesized to be significant influences on clinicians. These biases may perpetuate disparity between research evidence and clinical practice.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Impurity effects on electrical conductivity of doped bilayer graphene in the presence of a bias voltage

International Nuclear Information System (INIS)

Lotfi, E; Rezania, H; Arghavaninia, B; Yarmohammadi, M

2016-01-01

We address the electrical conductivity of bilayer graphene as a function of temperature, impurity concentration, and scattering strength in the presence of a finite bias voltage at finite doping, beginning with a description of the tight-binding model using the linear response theory and Green’s function approach. Our results show a linear behavior at high doping for the case of high bias voltage. The effects of electron doping on the electrical conductivity have been studied via changing the electronic chemical potential. We also discuss and analyze how the bias voltage affects the temperature behavior of the electrical conductivity. Finally, we study the behavior of the electrical conductivity as a function of the impurity concentration and scattering strength for different bias voltages and chemical potentials respectively. The electrical conductivity is found to be monotonically decreasing with impurity scattering strength due to the increased scattering among electrons at higher impurity scattering strength. (paper)

Model-based control of observer bias for the analysis of presence-only data in ecology.

Directory of Open Access Journals (Sweden)

David I Warton

Full Text Available Presence-only data, where information is available concerning species presence but not species absence, are subject to bias due to observers being more likely to visit and record sightings at some locations than others (hereafter "observer bias". In this paper, we describe and evaluate a model-based approach to accounting for observer bias directly--by modelling presence locations as a function of known observer bias variables (such as accessibility variables in addition to environmental variables, then conditioning on a common level of bias to make predictions of species occurrence free of such observer bias. We implement this idea using point process models with a LASSO penalty, a new presence-only method related to maximum entropy modelling, that implicitly addresses the "pseudo-absence problem" of where to locate pseudo-absences (and how many. The proposed method of bias-correction is evaluated using systematically collected presence/absence data for 62 plant species endemic to the Blue Mountains near Sydney, Australia. It is shown that modelling and controlling for observer bias significantly improves the accuracy of predictions made using presence-only data, and usually improves predictions as compared to pseudo-absence or "inventory" methods of bias correction based on absences from non-target species. Future research will consider the potential for improving the proposed bias-correction approach by estimating the observer bias simultaneously across multiple species.

Human and animal evidence of potential transgenerational inheritance of health effects: An evidence map and state-of-the-science evaluation.

Science.gov (United States)

Walker, Vickie R; Boyles, Abee L; Pelch, Katherine E; Holmgren, Stephanie D; Shapiro, Andrew J; Blystone, Chad R; Devito, Michael J; Newbold, Retha R; Blain, Robyn; Hartman, Pamela; Thayer, Kristina A; Rooney, Andrew A

2018-06-01

An increasing number of reports suggest early life exposures result in adverse effects in offspring who were never directly exposed; this phenomenon is termed "transgenerational inheritance." Given concern for public health implications for potential effects of exposures transmitted to subsequent generations, it is critical to determine how widespread and robust this phenomenon is and to identify the range of exposures and possible outcomes. This scoping report examines the evidence for transgenerational inheritance associated with exposure to a wide range of stressors in humans and animals to identify areas of consistency, uncertainty, data gaps, and to evaluate general risk of bias issues for the transgenerational study design. A protocol was developed to collect and categorize the literature into a systematic evidence map for transgenerational inheritance by health effects, exposures, and evidence streams following the Office of Health Assessment and Translation (OHAT) approach for conducting literature-based health assessments. A PubMed search yielded 63,758 unique records from which 257 relevant studies were identified and categorized into a systematic evidence map by evidence streams (46 human and 211 animal), broad health effect categories, and exposures. Data extracted from the individual studies are available in the Health Assessment Workspace Collaborative (HAWC) program. There are relatively few bodies of evidence where multiple studies evaluated the same exposure and the same or similar outcomes. Studies evaluated for risk of bias generally had multiple issues in design or conduct. The evidence mapping illustrated that risk of bias, few studies, and heterogeneity in exposures and endpoints examined present serious limitations to available bodies of evidence for assessing transgenerational effects. Targeted research is suggested to addressed inconsistencies and risk of bias issues identified, and thereby establish more robust bodies of evidence to

Attentional bias mediates the effect of neurostimulation on emotional vulnerability.

Science.gov (United States)

Chen, Nigel T M; Basanovic, Julian; Notebaert, Lies; MacLeod, Colin; Clarke, Patrick J F

2017-10-01

Transcranial direct current stimulation (tDCS) is a neuromodulatory technique which has garnered recent interest in the potential treatment for emotion-based psychopathology. While accumulating evidence suggests that tDCS may attenuate emotional vulnerability, critically, little is known about underlying mechanisms of this effect. The present study sought to clarify this by examining the possibility that tDCS may affect emotional vulnerability via its capacity to modulate attentional bias towards threatening information. Fifty healthy participants were randomly assigned to receive either anodal tDCS (2 mA/min) stimulation to the left dorsolateral prefrontal cortex (DLPFC), or sham. Participants were then eye tracked during a dual-video stressor task designed to elicit emotional reactivity, while providing a concurrent in-vivo measure of attentional bias. Greater attentional bias towards threatening information was associated with greater emotional reactivity to the stressor task. Furthermore, the active tDCS group showed reduced attentional bias to threat, compared to the sham group. Importantly, attentional bias was found to statistically mediate the effect of tDCS on emotional reactivity, while no direct effect of tDCS on emotional reactivity was observed. The findings are consistent with the notion that the effect of tDCS on emotional vulnerability may be mediated by changes in attentional bias, holding implications for the application of tDCS in emotion-based psychopathology. The findings also highlight the utility of in-vivo eye tracking measures in the examination of the mechanisms associated with DLPFC neuromodulation in emotional vulnerability. Copyright © 2017 Elsevier Ltd. All rights reserved.

Efficient and robust estimation for longitudinal mixed models for binary data

DEFF Research Database (Denmark)

Holst, René

2009-01-01

This paper proposes a longitudinal mixed model for binary data. The model extends the classical Poisson trick, in which a binomial regression is fitted by switching to a Poisson framework. A recent estimating equations method for generalized linear longitudinal mixed models, called GEEP, is used...... as a vehicle for fitting the conditional Poisson regressions, given a latent process of serial correlated Tweedie variables. The regression parameters are estimated using a quasi-score method, whereas the dispersion and correlation parameters are estimated by use of bias-corrected Pearson-type estimating...... equations, using second moments only. Random effects are predicted by BLUPs. The method provides a computationally efficient and robust approach to the estimation of longitudinal clustered binary data and accommodates linear and non-linear models. A simulation study is used for validation and finally...

Robust EM Continual Reassessment Method in Oncology Dose Finding

Science.gov (United States)

Yuan, Ying; Yin, Guosheng

2012-01-01

The continual reassessment method (CRM) is a commonly used dose-finding design for phase I clinical trials. Practical applications of this method have been restricted by two limitations: (1) the requirement that the toxicity outcome needs to be observed shortly after the initiation of the treatment; and (2) the potential sensitivity to the prespecified toxicity probability at each dose. To overcome these limitations, we naturally treat the unobserved toxicity outcomes as missing data, and use the expectation-maximization (EM) algorithm to estimate the dose toxicity probabilities based on the incomplete data to direct dose assignment. To enhance the robustness of the design, we propose prespecifying multiple sets of toxicity probabilities, each set corresponding to an individual CRM model. We carry out these multiple CRMs in parallel, across which model selection and model averaging procedures are used to make more robust inference. We evaluate the operating characteristics of the proposed robust EM-CRM designs through simulation studies and show that the proposed methods satisfactorily resolve both limitations of the CRM. Besides improving the MTD selection percentage, the new designs dramatically shorten the duration of the trial, and are robust to the prespecification of the toxicity probabilities. PMID:22375092

Benefits of being biased!

Indian Academy of Sciences (India)

Administrator

Journal of Genetics, Vol. 83, No. 2, August 2004. Keywords. codon bias; alcohol dehydrogenase; Darwinian ... RESEARCH COMMENTARY. Benefits of being biased! SUTIRTH DEY*. Evolutionary Biology Laboratory, Evolutionary & Organismal Biology Unit,. Jawaharlal Nehru Centre for Advanced Scientific Research,.

Robust quantum optimizer with full connectivity.

Science.gov (United States)

Nigg, Simon E; Lörch, Niels; Tiwari, Rakesh P

2017-04-01

Quantum phenomena have the potential to speed up the solution of hard optimization problems. For example, quantum annealing, based on the quantum tunneling effect, has recently been shown to scale exponentially better with system size than classical simulated annealing. However, current realizations of quantum annealers with superconducting qubits face two major challenges. First, the connectivity between the qubits is limited, excluding many optimization problems from a direct implementation. Second, decoherence degrades the success probability of the optimization. We address both of these shortcomings and propose an architecture in which the qubits are robustly encoded in continuous variable degrees of freedom. By leveraging the phenomenon of flux quantization, all-to-all connectivity with sufficient tunability to implement many relevant optimization problems is obtained without overhead. Furthermore, we demonstrate the robustness of this architecture by simulating the optimal solution of a small instance of the nondeterministic polynomial-time hard (NP-hard) and fully connected number partitioning problem in the presence of dissipation.

Sources of Response Bias in Older Ethnic Minorities: A Case of Korean American Elderly

Science.gov (United States)

Kim, Miyong T.; Ko, Jisook; Yoon, Hyunwoo; Kim, Kim B.; Jang, Yuri

2015-01-01

The present study was undertaken to investigate potential sources of response bias in empirical research involving older ethnic minorities and to identify prudent strategies to reduce those biases, using Korean American elderly (KAE) as an example. Data were obtained from three independent studies of KAE (N=1,297; age ≥60) in three states (Florida, New York, and Maryland) from 2000 to 2008. Two common measures, Pearlin’s Mastery Scale and the CES-D scale, were selected for a series of psychometric tests based on classical measurement theory. Survey items were analyzed in depth, using psychometric properties generated from both exploratory factor analysis and confirmatory factor analysis as well as correlational analysis. Two types of potential sources of bias were identified as the most significant contributors to increases in error variances for these psychological instruments. Error variances were most prominent when (1) items were not presented in a manner that was culturally or contextually congruent with respect to the target population and/or (2) the response anchors for items were mixed (e.g., positive vs. negative). The systemic patterns and magnitudes of the biases were also cross-validated for the three studies. The results demonstrate sources and impacts of measurement biases in studies of older ethnic minorities. The identified response biases highlight the need for re-evaluation of current measurement practices, which are based on traditional recommendations that response anchors should be mixed or that the original wording of instruments should be rigidly followed. Specifically, systematic guidelines for accommodating cultural and contextual backgrounds into instrument design are warranted. PMID:26049971

Robustness Analyses of Timber Structures

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Hald, Frederik

2013-01-01

The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many mo...... with respect to robustness of timber structures and will discuss the consequences of such robustness issues related to the future development of timber structures.......The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many...... modern building codes consider the need for the robustness of structures and provide strategies and methods to obtain robustness. Therefore, a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper summaries issues...

Correction of gene expression data: Performance-dependency on inter-replicate and inter-treatment biases.

Science.gov (United States)

Darbani, Behrooz; Stewart, C Neal; Noeparvar, Shahin; Borg, Søren

2014-10-20

This report investigates for the first time the potential inter-treatment bias source of cell number for gene expression studies. Cell-number bias can affect gene expression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction efficiencies. For maximal reliability of analysis, therefore, comparisons should be performed at the cellular level. This could be accomplished using an appropriate correction method that can detect and remove the inter-treatment bias for cell-number. Based on inter-treatment variations of reference genes, we introduce an analytical approach to examine the suitability of correction methods by considering the inter-treatment bias as well as the inter-replicate variance, which allows use of the best correction method with minimum residual bias. Analyses of RNA sequencing and microarray data showed that the efficiencies of correction methods are influenced by the inter-treatment bias as well as the inter-replicate variance. Therefore, we recommend inspecting both of the bias sources in order to apply the most efficient correction method. As an alternative correction strategy, sequential application of different correction approaches is also advised. Copyright © 2014 Elsevier B.V. All rights reserved.

Bias aware Kalman filters

DEFF Research Database (Denmark)

Drecourt, J.-P.; Madsen, H.; Rosbjerg, Dan

2006-01-01

This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model state....... The colored noise filter formulation is extended to correct both time correlated and uncorrelated model error components. A more stable version of the separate filter without feedback is presented. The filters are implemented in an ensemble framework using Latin hypercube sampling. The techniques...... are illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 2005 Elsevier Ltd. All rights reserved....

Impurity-induced anisotropic semiconductor-semimetal transition in monolayer biased black phosphorus

Science.gov (United States)

Bui, D. H.; Yarmohammadi, Mohsen

2018-07-01

Taking into account the electron-impurity interaction within the continuum approximation of tight-binding model, the Born approximation, and the Green's function method, the main features of anisotropic electronic phase transition are investigated in monolayer biased black phosphorus (BP). To this end, we concentrated on the disordered electronic density of states (DOS), which gives useful information for electro-optical devices. Increasing the impurity concentration in both unbiased and biased impurity-infected single-layer BP, in addition to the decrease of the band gap, independent of the direction, leads to the midgap states and an extra Van Hove singularity inside and outside of the band gap, respectively. Furthermore, strong impurity scattering potentials lead to a semiconductor-semimetal transition and one more Van Hove singularity in x-direction of unbiased BP and surprisingly, this transition does not occur in biased BP. We found that there is no phase transition in y-direction. Since real applications require structures with modulated band gaps, we have studied the influence of different bias voltages on the disordered DOS in both directions, resulting in the increase of the band gap.

New Trends in Magnetic Exchange Bias

Science.gov (United States)

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

2005-05-01

-of-plane exchange bias, depending on the field cooling direction. This is of particular interest since it allows probing of the three-dimensional spin structure of the AF layer. The interface magnetic configuration is extremely important in the perpendicular geometry, as the short-range exchange coupling competes with a long-range dipolar interaction; the induced uniaxial anisotropy must overcome the demagnetization energy to establish perpendicular anisotropy films. Those new studies are of primary importance for the magnetic media industry as perpendicular recording exhibits potential for strongly increased storage densities. 3. Parameters tuning exchange bias in polycrystalline samples and magnetic configurations: Different parameters can be used to tune the exchange bias coupling in polycrystalline samples similar to those used in devices. Particularly fascinating aspects are the questions of the appearance of exchange bias or coercivity in ferromagnet/antiferromagnet heterostructures, and its relation to magnetic configurations formed on either side of the interface. Several papers report on either growth choices or post preparation treatments that enable tuning of the exchange bias in bilayers. The additional complexity and novel features of the exchange coupled interface make the problem particularly rich. 4. Dynamics and magnetization reversal: Linear response experiments, such as ferromagnetic resonance, have been used with great success to identify interface, surface anisotropies and interlayer exchange in multilayer systems. The exchange bias structure is particularly well suited to study because interface driven changes in the spin wave frequencies in the ferromagnet can be readily related to interlayer exchange and anisotropy parameters associated with the antiferromagnet. Because the exchange bias is intimately connected with details of the magnetization process during reversal and the subsequent formation of hysteresis, considerations of time dependence and

Attention bias and anxiety in young children exposed to family violence

Science.gov (United States)

Briggs-Gowan, Margaret J.; Pollak, Seth D.; Grasso, Damion; Voss, Joel; Mian, Nicholas D.; Zobel, Elvira; McCarthy, Kimberly J.; Wakschlag, Lauren S.; Pine, Daniel S.

2015-01-01

Background Attention bias towards threat is associated with anxiety in older youth and adults and has been linked with violence exposure. Attention bias may moderate the relationship between violence exposure and anxiety in young children. Capitalizing on measurement advances, the current study examines these relationships at a younger age than previously possible. Methods Young children (mean age 4.7, ±0.8) from a cross-sectional sample oversampled for violence exposure (N = 218) completed the dot-probe task to assess their attention biases. Observed fear/anxiety was characterized with a novel observational paradigm, the Anxiety Diagnostic Observation Schedule. Mother-reported symptoms were assessed with the Preschool-Age Psychiatric Assessment and Trauma Symptom Checklist for Young Children. Violence exposure was characterized with dimensional scores reflecting probability of membership in two classes derived via latent class analysis from the Conflict Tactics Scales: Abuse and Harsh Parenting. Results Family violence predicted greater child anxiety and trauma symptoms. Attention bias moderated the relationship between violence and anxiety. Conclusions Attention bias towards threat may strengthen the effects of family violence on the development of anxiety, with potentially cascading effects across childhood. Such associations may be most readily detected when using observational measures of childhood anxiety. PMID:26716142

Investigating robustness of interatomic potentials with universal interface

International Nuclear Information System (INIS)

Jelinek, Bohumir; Felicelli, Sergio D; Solanki, Kiran; Peters, John F

2012-01-01

We present a set of Python routines to perform basic tests of classical atomistic potentials and their example applications. These routines are implemented using universal Atomic Simulation Environment (ASE) and LAMMPS molecular dynamics code. ASE is utilized to create atomic configurations, to write input scripts for LAMMPS, and to read results from output files. Evaluated properties are formation energies and volumes of simple point defects (vacancies, substitutions, and interstitials), formation energies of basic surfaces, heats of formation of simple binary compounds, and elastic constants. The flexibility of LAMMPS allows easy switching between different semi-empirical potentials, while the universality of ASE allows to compare results with a variety of electronic structure codes.

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

Science.gov (United States)

Borgen, Nicolai T

2018-05-01

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

Administrative bias in South Africa

Directory of Open Access Journals (Sweden)

E S Nwauche

2005-01-01

Full Text Available This article reviews the interpretation of section 6(2(aii of the Promotion of Administrative Justice Act which makes an administrator “biased or reasonably suspected of bias” a ground of judicial review. In this regard, the paper reviews the determination of administrative bias in South Africa especially highlighting the concept of institutional bias. The paper notes that inspite of the formulation of the bias ground of review the test for administrative bias is the reasonable apprehension test laid down in the case of President of South Africa v South African Rugby Football Union(2 which on close examination is not the same thing. Accordingly the paper urges an alternative interpretation that is based on the reasonable suspicion test enunciated in BTR Industries South Africa (Pty Ltd v Metal and Allied Workers Union and R v Roberts. Within this context, the paper constructs a model for interpreting the bias ground of review that combines the reasonable suspicion test as interpreted in BTR Industries and R v Roberts, the possibility of the waiver of administrative bias, the curative mechanism of administrative appeal as well as some level of judicial review exemplified by the jurisprudence of article 6(1 of the European Convention of Human Rights, especially in the light of the contemplation of the South African Magistrate Court as a jurisdictional route of judicial review.

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

Science.gov (United States)

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.

Multi-wavelength approach towards on-product overlay accuracy and robustness

Science.gov (United States)

Bhattacharyya, Kaustuve; Noot, Marc; Chang, Hammer; Liao, Sax; Chang, Ken; Gosali, Benny; Su, Eason; Wang, Cathy; den Boef, Arie; Fouquet, Christophe; Huang, Guo-Tsai; Chen, Kai-Hsiung; Cheng, Kevin; Lin, John

2018-03-01

Success of diffraction-based overlay (DBO) technique1,4,5 in the industry is not just for its good precision and low toolinduced shift, but also for the measurement accuracy2 and robustness that DBO can provide. Significant efforts are put in to capitalize on the potential that DBO has to address measurement accuracy and robustness. Introduction of many measurement wavelength choices (continuous wavelength) in DBO is one of the key new capabilities in this area. Along with the continuous choice of wavelengths, the algorithms (fueled by swing-curve physics) on how to use these wavelengths are of high importance for a robust recipe setup that can avoid the impact from process stack variations (symmetric as well as asymmetric). All these are discussed. Moreover, another aspect of boosting measurement accuracy and robustness is discussed that deploys the capability to combine overlay measurement data from multiple wavelength measurements. The goal is to provide a method to make overlay measurements immune from process stack variations and also to report health KPIs for every measurement. By combining measurements from multiple wavelengths, a final overlay measurement is generated. The results show a significant benefit in accuracy and robustness against process stack variation. These results are supported by both measurement data as well as simulation from many product stacks.

Automation bias: empirical results assessing influencing factors.

Science.gov (United States)

Goddard, Kate; Roudsari, Abdul; Wyatt, Jeremy C

2014-05-01

To investigate the rate of automation bias - the propensity of people to over rely on automated advice and the factors associated with it. Tested factors were attitudinal - trust and confidence, non-attitudinal - decision support experience and clinical experience, and environmental - task difficulty. The paradigm of simulated decision support advice within a prescribing context was used. The study employed within participant before-after design, whereby 26 UK NHS General Practitioners were shown 20 hypothetical prescribing scenarios with prevalidated correct and incorrect answers - advice was incorrect in 6 scenarios. They were asked to prescribe for each case, followed by being shown simulated advice. Participants were then asked whether they wished to change their prescription, and the post-advice prescription was recorded. Rate of overall decision switching was captured. Automation bias was measured by negative consultations - correct to incorrect prescription switching. Participants changed prescriptions in 22.5% of scenarios. The pre-advice accuracy rate of the clinicians was 50.38%, which improved to 58.27% post-advice. The CDSS improved the decision accuracy in 13.1% of prescribing cases. The rate of automation bias, as measured by decision switches from correct pre-advice, to incorrect post-advice was 5.2% of all cases - a net improvement of 8%. More immediate factors such as trust in the specific CDSS, decision confidence, and task difficulty influenced rate of decision switching. Lower clinical experience was associated with more decision switching. Age, DSS experience and trust in CDSS generally were not significantly associated with decision switching. This study adds to the literature surrounding automation bias in terms of its potential frequency and influencing factors. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Electrophysiological Evidence for Elimination of the Positive Bias in Elderly Adults with Depressive Symptoms

Directory of Open Access Journals (Sweden)

Huixia Zhou

2018-03-01

Full Text Available BackgroundDepressed populations demonstrate a greater tendency to have negative interpretations on ambiguous situations. Cognitive theories concerning depression proposed that such a negative bias plays an important role in developing and maintaining depression. There is now fairly consistent evidence arising from different stimuli and assessment methods that depression is featured by such a bias. The current study aimed to explore the neural signatures associated with the interpretation bias in the elderly with depressive symptoms confronted with different facial expressions using event-related brain potentials (ERPs.MethodsParticipants were 14 community-dwelling older adults with depressive symptoms assessed by the Center for Epidemiologic Studies Depression scale scores. We collected event-related potentials of their brain compared to that of 14 healthy aged-matched adults. The late positive potential (LPP was used to examine cognitive-affective processes associated with judgment of emotional facial expressions between the two groups.ResultsOld adults with depressive symptoms have much smaller amplitude than healthy older adults irrespective of the prime types. When processing the targets, the two groups showed different patterns regarding the LPP. The healthy control group revealed no differences between ambiguous and happy primes, irrespective of whether the targets were sad or happy facial expressions. However, significant differences were found between happy and sad and between ambiguous and sad primes. Such a pattern indicates a positive bias in healthy elderly adults. Regarding the elderly with depressive symptoms, there were no significant differences between ambiguous versus happy, ambiguous versus sad primes, and happy versus sad primes. Concerning reaction times, there was no group difference. Thus, the findings provide some support for cognitive theories of depression.ConclusionThe current study shows that there is an association

Preferences, country bias, and international trade

NARCIS (Netherlands)

S. Roy (Santanu); J.M.A. Viaene (Jean-Marie)

1998-01-01

textabstractAnalyzes international trade where consumer preferences exhibit country bias. Why country biases arise; How trade can occur in the presence of country bias; Implication for the pattern of trade and specialization.

Biases in casino betting

Directory of Open Access Journals (Sweden)

James Sundali

2006-07-01

Full Text Available We examine two departures of individual perceptions of randomness from probability theory: the hot hand and the gambler's fallacy, and their respective opposites. This paper's first contribution is to use data from the field (individuals playing roulette in a casino to demonstrate the existence and impact of these biases that have been previously documented in the lab. Decisions in the field are consistent with biased beliefs, although we observe significant individual heterogeneity in the population. A second contribution is to separately identify these biases within a given individual, then to examine their within-person correlation. We find a positive and significant correlation across individuals between hot hand and gambler's fallacy biases, suggesting a common (root cause of the two related errors. We speculate as to the source of this correlation (locus of control, and suggest future research which could test this speculation.

Robustness for slope stability modelling under deep uncertainty

Science.gov (United States)

Almeida, Susana; Holcombe, Liz; Pianosi, Francesca; Wagener, Thorsten

2015-04-01

Landslides can have large negative societal and economic impacts, such as loss of life and damage to infrastructure. However, the ability of slope stability assessment to guide management is limited by high levels of uncertainty in model predictions. Many of these uncertainties cannot be easily quantified, such as those linked to climate change and other future socio-economic conditions, restricting the usefulness of traditional decision analysis tools. Deep uncertainty can be managed more effectively by developing robust, but not necessarily optimal, policies that are expected to perform adequately under a wide range of future conditions. Robust strategies are particularly valuable when the consequences of taking a wrong decision are high as is often the case of when managing natural hazard risks such as landslides. In our work a physically based numerical model of hydrologically induced slope instability (the Combined Hydrology and Stability Model - CHASM) is applied together with robust decision making to evaluate the most important uncertainties (storm events, groundwater conditions, surface cover, slope geometry, material strata and geotechnical properties) affecting slope stability. Specifically, impacts of climate change on long-term slope stability are incorporated, accounting for the deep uncertainty in future climate projections. Our findings highlight the potential of robust decision making to aid decision support for landslide hazard reduction and risk management under conditions of deep uncertainty.

Impulsivity moderates the effect of approach bias modification on healthy food consumption.

Science.gov (United States)

Kakoschke, Naomi; Kemps, Eva; Tiggemann, Marika

2017-10-01

The study aimed to modify approach bias for healthy and unhealthy food and to determine its effect on subsequent food consumption. In addition, we investigated the potential moderating role of impulsivity in the effect of approach bias re-training on food consumption. Participants were 200 undergraduate women (17-26 years) who were randomly allocated to one of five conditions of an approach-avoidance task varying in the training of an approach bias for healthy food, unhealthy food, and non-food cues in a single session of 10 min. Outcome variables were approach bias for healthy and unhealthy food and the proportion of healthy relative to unhealthy snack food consumed. As predicted, approach bias for healthy food significantly increased in the 'avoid unhealthy food/approach healthy food' condition. Importantly, the effect of training on snack consumption was moderated by trait impulsivity. Participants high in impulsivity consumed a greater proportion of healthy snack food following the 'avoid unhealthy food/approach healthy food' training. This finding supports the suggestion that automatic processing of appetitive cues has a greater influence on consumption behaviour in individuals with poor self-regulatory control. Copyright © 2017 Elsevier Ltd. All rights reserved.

All-organic superhydrophobic coatings with mechanochemical robustness and liquid impalement resistance

Science.gov (United States)

Peng, Chaoyi; Chen, Zhuyang; Tiwari, Manish K.

2018-03-01

Superhydrophobicity is a remarkable evolutionary adaption manifested by several natural surfaces. Artificial superhydrophobic coatings with good mechanical robustness, substrate adhesion and chemical robustness have been achieved separately. However, a simultaneous demonstration of these features along with resistance to liquid impalement via high-speed drop/jet impact is challenging. Here, we describe all-organic, flexible superhydrophobic nanocomposite coatings that demonstrate strong mechanical robustness under cyclic tape peels and Taber abrasion, sustain exposure to highly corrosive media, namely aqua regia and sodium hydroxide solutions, and can be applied to surfaces through scalable techniques such as spraying and brushing. In addition, the mechanical flexibility of our coatings enables impalement resistance to high-speed drops and turbulent jets at least up to 35 m s-1 and a Weber number of 43,000. With multifaceted robustness and scalability, these coatings should find potential usage in harsh chemical engineering as well as infrastructure, transport vehicles and communication equipment.

What we don't know can hurt us: Nonresponse bias assessment in birth defects research.

Science.gov (United States)

Strassle, Paula D; Cassell, Cynthia H; Shapira, Stuart K; Tinker, Sarah C; Meyer, Robert E; Grosse, Scott D

2015-07-01

Nonresponse bias assessment is an important and underutilized tool in survey research to assess potential bias due to incomplete participation. This study illustrates a nonresponse bias sensitivity assessment using a survey on perceived barriers to care for children with orofacial clefts in North Carolina. Children born in North Carolina between 2001 and 2004 with an orofacial cleft were eligible for inclusion. Vital statistics data, including maternal and child characteristics, were available on all eligible subjects. Missing 'responses' from nonparticipants were imputed using assumptions based on the distribution of responses, survey method (mail or phone), and participant maternal demographics. Overall, 245 of 475 subjects (51.6%) responded to either a mail or phone survey. Cost as a barrier to care was reported by 25.0% of participants. When stratified by survey type, 28.3% of mail respondents and 17.2% of phone respondents reported cost as a barrier. Under various assumptions, the bias-adjusted estimated prevalence of cost as barrier to care ranged from 16.1% to 30.0%. Maternal age, education, race, and marital status at time of birth were not associated with subjects reporting cost as a barrier. As survey response rates continue to decline, the importance of assessing the potential impact of nonresponse bias has become more critical. Birth defects research is particularly conducive to nonresponse bias analysis, especially when birth defect registries and birth certificate records are used. Future birth defect studies which use population-based surveillance data and have incomplete participation could benefit from this type of nonresponse bias assessment. Birth Defects Research (Part A) 103:603-609, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

International Conference on Robust Statistics

CERN Document Server

Filzmoser, Peter; Gather, Ursula; Rousseeuw, Peter

2003-01-01

Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.

An inclusive taxonomy of behavioral biases

Directory of Open Access Journals (Sweden)

David Peón

2017-07-01

Full Text Available This paper overviews the theoretical and empirical research on behavioral biases and their influence in the literature. To provide a systematic exposition, we present a unified framework that takes the reader through an original taxonomy, based on the reviews of relevant authors in the field. In particular, we establish three broad categories that may be distinguished: heuristics and biases; choices, values and frames; and social factors. We then describe the main biases within each category, and revise the main theoretical and empirical developments, linking each bias with other biases and anomalies that are related to them, according to the literature.

Probing Biased Signaling in Chemokine Receptors

DEFF Research Database (Denmark)

Amarandi, Roxana Maria; Hjortø, Gertrud Malene; Rosenkilde, Mette Marie

2016-01-01

The chemokine system mediates leukocyte migration during homeostatic and inflammatory processes. Traditionally, it is described as redundant and promiscuous, with a single chemokine ligand binding to different receptors and a single receptor having several ligands. Signaling of chemokine receptors...... of others has been termed signaling bias and can accordingly be grouped into ligand bias, receptor bias, and tissue bias. Bias has so far been broadly overlooked in the process of drug development. The low number of currently approved drugs targeting the chemokine system, as well as the broad range...... of failed clinical trials, reflects the need for a better understanding of the chemokine system. Thus, understanding the character, direction, and consequence of biased signaling in the chemokine system may aid the development of new therapeutics. This review describes experiments to assess G protein...

Robust Scientists

DEFF Research Database (Denmark)

Gorm Hansen, Birgitte