Sample records for strong learning bias
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Learning bias, cultural evolution of language, and the biological evolution of the language faculty.
Smith, Kenny
2011-04-01
The biases of individual language learners act to determine the learnability and cultural stability of languages: learners come to the language learning task with biases which make certain linguistic systems easier to acquire than others. These biases are repeatedly applied during the process of language transmission, and consequently should effect the types of languages we see in human populations. Understanding the cultural evolutionary consequences of particular learning biases is therefore central to understanding the link between language learning in individuals and language universals, common structural properties shared by all the world’s languages. This paper reviews a range of models and experimental studies which show that weak biases in individual learners can have strong effects on the structure of socially learned systems such as language, suggesting that strong universal tendencies in language structure do not require us to postulate strong underlying biases or constraints on language learning. Furthermore, understanding the relationship between learner biases and language design has implications for theories of the evolution of those learning biases: models of gene-culture coevolution suggest that, in situations where a cultural dynamic mediates between properties of individual learners and properties of language in this way, biological evolution is unlikely to lead to the emergence of strong constraints on learning.
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Attentional Bias in Human Category Learning: The Case of Deep Learning.
Hanson, Catherine; Caglar, Leyla Roskan; Hanson, Stephen José
2018-01-01
Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987) showed that stimuli can have structures with features that are statistically uncorrelated (separable) or statistically correlated (integral) within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974). In contrast to humans, a single hidden layer backpropagation (BP) neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993). This "failure" to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1) by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2) by investigating whether a Deep Learning (DL) network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc.), would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993). Second, we show that using the same low dimensional stimuli, Deep Learning (DL), unlike BP but similar to humans, learns separable category structures more quickly than integral category structures
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Attentional Bias in Human Category Learning: The Case of Deep Learning
Directory of Open Access Journals (Sweden)
Catherine Hanson
2018-04-01
Full Text Available Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987 showed that stimuli can have structures with features that are statistically uncorrelated (separable or statistically correlated (integral within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974. In contrast to humans, a single hidden layer backpropagation (BP neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993. This “failure” to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1 by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2 by investigating whether a Deep Learning (DL network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc., would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993. Second, we show that using the same low dimensional stimuli, Deep Learning (DL, unlike BP but similar to humans, learns separable category structures more quickly than integral category
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Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro
2018-05-09
Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.
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The evolution of social learning rules: payoff-biased and frequency-dependent biased transmission.
Kendal, Jeremy; Giraldeau, Luc-Alain; Laland, Kevin
2009-09-21
Humans and other animals do not use social learning indiscriminately, rather, natural selection has favoured the evolution of social learning rules that make selective use of social learning to acquire relevant information in a changing environment. We present a gene-culture coevolutionary analysis of a small selection of such rules (unbiased social learning, payoff-biased social learning and frequency-dependent biased social learning, including conformism and anti-conformism) in a population of asocial learners where the environment is subject to a constant probability of change to a novel state. We define conditions under which each rule evolves to a genetically polymorphic equilibrium. We find that payoff-biased social learning may evolve under high levels of environmental variation if the fitness benefit associated with the acquired behaviour is either high or low but not of intermediate value. In contrast, both conformist and anti-conformist biases can become fixed when environment variation is low, whereupon the mean fitness in the population is higher than for a population of asocial learners. Our examination of the population dynamics reveals stable limit cycles under conformist and anti-conformist biases and some highly complex dynamics including chaos. Anti-conformists can out-compete conformists when conditions favour a low equilibrium frequency of the learned behaviour. We conclude that evolution, punctuated by the repeated successful invasion of different social learning rules, should continuously favour a reduction in the equilibrium frequency of asocial learning, and propose that, among competing social learning rules, the dominant rule will be the one that can persist with the lowest frequency of asocial learning.
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Cognitive Bias for Learning Speech Sounds From a Continuous Signal Space Seems Nonlinguistic
Directory of Open Access Journals (Sweden)
Sabine van der Ham
2015-10-01
Full Text Available When learning language, humans have a tendency to produce more extreme distributions of speech sounds than those observed most frequently: In rapid, casual speech, vowel sounds are centralized, yet cross-linguistically, peripheral vowels occur almost universally. We investigate whether adults’ generalization behavior reveals selective pressure for communication when they learn skewed distributions of speech-like sounds from a continuous signal space. The domain-specific hypothesis predicts that the emergence of sound categories is driven by a cognitive bias to make these categories maximally distinct, resulting in more skewed distributions in participants’ reproductions. However, our participants showed more centered distributions, which goes against this hypothesis, indicating that there are no strong innate linguistic biases that affect learning these speech-like sounds. The centralization behavior can be explained by a lack of communicative pressure to maintain categories.
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Vowel bias in Danish word-learning
DEFF Research Database (Denmark)
Højen, Anders; Nazzi, Thierry
2016-01-01
The present study explored whether the phonological bias favoring consonants found in French-learning infants and children when learning new words (Havy & Nazzi, 2009; Nazzi, 2005) is language-general, as proposed by Nespor, Peña and Mehler (2003), or varies across languages, perhaps as a functio...
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A strong deletion bias in nonallelic gene conversion.
Directory of Open Access Journals (Sweden)
Raquel Assis
Full Text Available Gene conversion is the unidirectional transfer of genetic information between orthologous (allelic or paralogous (nonallelic genomic segments. Though a number of studies have examined nucleotide replacements, little is known about length difference mutations produced by gene conversion. Here, we investigate insertions and deletions produced by nonallelic gene conversion in 338 Drosophila and 10,149 primate paralogs. Using a direct phylogenetic approach, we identify 179 insertions and 614 deletions in Drosophila paralogs, and 132 insertions and 455 deletions in primate paralogs. Thus, nonallelic gene conversion is strongly deletion-biased in both lineages, with almost 3.5 times as many conversion-induced deletions as insertions. In primates, the deletion bias is considerably stronger for long indels and, in both lineages, the per-site rate of gene conversion is orders of magnitudes higher than that of ordinary mutation. Due to this high rate, deletion-biased nonallelic gene conversion plays a key role in genome size evolution, leading to the cooperative shrinkage and eventual disappearance of selectively neutral paralogs.
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Confirmation bias in human reinforcement learning: Evidence from counterfactual feedback processing
Lefebvre, Germain; Blakemore, Sarah-Jayne
2017-01-01
Previous studies suggest that factual learning, that is, learning from obtained outcomes, is biased, such that participants preferentially take into account positive, as compared to negative, prediction errors. However, whether or not the prediction error valence also affects counterfactual learning, that is, learning from forgone outcomes, is unknown. To address this question, we analysed the performance of two groups of participants on reinforcement learning tasks using a computational model that was adapted to test if prediction error valence influences learning. We carried out two experiments: in the factual learning experiment, participants learned from partial feedback (i.e., the outcome of the chosen option only); in the counterfactual learning experiment, participants learned from complete feedback information (i.e., the outcomes of both the chosen and unchosen option were displayed). In the factual learning experiment, we replicated previous findings of a valence-induced bias, whereby participants learned preferentially from positive, relative to negative, prediction errors. In contrast, for counterfactual learning, we found the opposite valence-induced bias: negative prediction errors were preferentially taken into account, relative to positive ones. When considering valence-induced bias in the context of both factual and counterfactual learning, it appears that people tend to preferentially take into account information that confirms their current choice. PMID:28800597
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Confirmation bias in human reinforcement learning: Evidence from counterfactual feedback processing.
Palminteri, Stefano; Lefebvre, Germain; Kilford, Emma J; Blakemore, Sarah-Jayne
2017-08-01
Previous studies suggest that factual learning, that is, learning from obtained outcomes, is biased, such that participants preferentially take into account positive, as compared to negative, prediction errors. However, whether or not the prediction error valence also affects counterfactual learning, that is, learning from forgone outcomes, is unknown. To address this question, we analysed the performance of two groups of participants on reinforcement learning tasks using a computational model that was adapted to test if prediction error valence influences learning. We carried out two experiments: in the factual learning experiment, participants learned from partial feedback (i.e., the outcome of the chosen option only); in the counterfactual learning experiment, participants learned from complete feedback information (i.e., the outcomes of both the chosen and unchosen option were displayed). In the factual learning experiment, we replicated previous findings of a valence-induced bias, whereby participants learned preferentially from positive, relative to negative, prediction errors. In contrast, for counterfactual learning, we found the opposite valence-induced bias: negative prediction errors were preferentially taken into account, relative to positive ones. When considering valence-induced bias in the context of both factual and counterfactual learning, it appears that people tend to preferentially take into account information that confirms their current choice.
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Learning-style bias and the development of psychopathy.
Moul, Caroline; Dadds, Mark R
2013-02-01
In accordance with a recently proposed account of amygdala function in psychopathy, it is hypothesized that people with high levels of psychopathic personality traits have a bias in learning style to encode the general valence, and neglect the specific-features, of an outcome. We present a novel learning task designed to operationalize these biases in learning style. The results from pilot samples of healthy adults and children and from a clinical sample of children with conduct problems provide support for the validity of the learning task as a measure of learning style and demonstrate a significant relationship between general-valence style learning and psychopathic personality traits. It is suggested that this relationship may be important for the aetiology of the social-cognitive deficits exhibited by psychopaths. These preliminary results suggest that this measure of learning style has the potential to be utilized as a research tool and may assist with the early identification, and treatment, of children with conduct problems and high levels of callous-unemotional traits.
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Bias Correction in a Stable AD (1,1) Model: Weak versus Strong Exogeneity
van Giersbergen, N.P.A.
2001-01-01
This paper compares the behaviour of a bias-corrected estimator assuming strongly exogenous regressors to the behaviour of a bias-corrected estimator assuming weakly exogenous regressors, when in fact the marginal model contains a feedback mechanism. To this end, the effects of a feedback mechanism
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Monte Carlo learning/biasing experiment with intelligent random numbers
International Nuclear Information System (INIS)
Booth, T.E.
1985-01-01
A Monte Carlo learning and biasing technique is described that does its learning and biasing in the random number space rather than the physical phase-space. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed. 12 refs
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Active and Adaptive Learning from Biased Data with Applications in Astronomy
DEFF Research Database (Denmark)
Kremer, Jan
This thesis addresses the problem of machine learning from biased datasets in the context of astronomical applications. In astronomy there are many cases in which the training sample does not follow the true distribution. The thesis examines different types of biases and proposes algorithms...... set. Against this background, the thesis begins with a survey of active learning algorithms for the support vector machine. If the cost of additional labeling is prohibitive, unlabeled data can often be utilized instead and the sample selection bias can be overcome through domain adaptation, that is...... to handle them. During learning and when applying the predictive model, active learning enables algorithms to select training examples from a pool of unlabeled data and to request the labels. This allows for selecting examples that maximize the algorithm's accuracy despite an initial bias in the training...
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Learning biases predict a word order universal.
Culbertson, Jennifer; Smolensky, Paul; Legendre, Géraldine
2012-03-01
How recurrent typological patterns, or universals, emerge from the extensive diversity found across the world's languages constitutes a central question for linguistics and cognitive science. Recent challenges to a fundamental assumption of generative linguistics-that universal properties of the human language acquisition faculty constrain the types of grammatical systems which can occur-suggest the need for new types of empirical evidence connecting typology to biases of learners. Using an artificial language learning paradigm in which adult subjects are exposed to a mix of grammatical systems (similar to a period of linguistic change), we show that learners' biases mirror a word-order universal, first proposed by Joseph Greenberg, which constrains typological patterns of adjective, numeral, and noun ordering. We briefly summarize the results of a probabilistic model of the hypothesized biases and their effect on learning, and discuss the broader implications of the results for current theories of the origins of cross-linguistic word-order preferences. Copyright © 2011 Elsevier B.V. All rights reserved.
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Recognizing Our Cultural Biases as Counsellor Supervisors: A Reflective Learning Approach
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…
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Analysis of the giant magnetostrictive actuator with strong bias magnetic field
Energy Technology Data Exchange (ETDEWEB)
Xue, Guangming, E-mail: yy0youxia@163.com; He, Zhongbo; Li, Dongwei; Yang, Zhaoshu; Zhao, Zhenglong
2015-11-15
Giant magnetostrictive actuator with strong bias magnetic field is designed to control the injector bullet valve opening and closing. The relationship between actuator displacement amplitude and input signal direction is analyzed. And based on the approximate linearity of strain-magnetic field, second-order system model of the actuator displacement is established. Experimental system suitable for the actuator is designed. The experimental results show that, the square voltage amplitude being 12 V, the actuator displacement amplitude is about 17 μm with backward direction signal input while being 1.5 μm under forward direction signal. From the results, the suitable input direction is confirmed to be backward. With exciting frequncy lower than 200 Hz, the error between the model and experimental result is less than 1.7 μm. So the model is validated under the low-frequency signal input. The testing displacement-voltage curves are approximately straight lines. But due to the biased position, the line slope and the displacement-voltage linearity change as the input voltage changes. - Highlights: • Giant magnetostrictive actuator with strong bias magnetic field is designed. • The relationship between actuator displacement amplitude and input current direction is analyzed. • The model of the actuator displacement is established and its accuracy is verified by the test. • The actuator displacement-voltage curves are achieved by the test, and the curves’ characteristics are analyzed theoretically.
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Social anxiety is characterized by biased learning about performance and the self.
Koban, Leonie; Schneider, Rebecca; Ashar, Yoni K; Andrews-Hanna, Jessica R; Landy, Lauren; Moscovitch, David A; Wager, Tor D; Arch, Joanna J
2017-12-01
People learn about their self from social information, and recent work suggests that healthy adults show a positive bias for learning self-related information. In contrast, social anxiety disorder (SAD) is characterized by a negative view of the self, yet what causes and maintains this negative self-view is not well understood. Here the authors use a novel experimental paradigm and computational model to test the hypothesis that biased social learning regarding self-evaluation and self-feelings represents a core feature that distinguishes adults with SAD from healthy controls. Twenty-one adults with SAD and 35 healthy controls (HCs) performed a speech in front of 3 judges. They subsequently evaluated themselves and received performance feedback from the judges and then rated how they felt about themselves and the judges. Affective updating (i.e., change in feelings about the self over time, in response to feedback from the judges) was modeled using an adapted Rescorla-Wagner learning model. HCs demonstrated a positivity bias in affective updating, which was absent in SAD. Further, self-performance ratings revealed group differences in learning from positive feedback-a difference that endured at an average of 1 year follow up. These findings demonstrate the presence and long-term endurance of positively biased social learning about the self among healthy adults, a bias that is absent or reversed among socially anxious adults. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Strong mechanically induced effects in DC current-biased suspended Josephson junctions
McDermott, Thomas; Deng, Hai-Yao; Isacsson, Andreas; Mariani, Eros
2018-01-01
Superconductivity is a result of quantum coherence at macroscopic scales. Two superconductors separated by a metallic or insulating weak link exhibit the AC Josephson effect: the conversion of a DC voltage bias into an AC supercurrent. This current may be used to activate mechanical oscillations in a suspended weak link. As the DC-voltage bias condition is remarkably difficult to achieve in experiments, here we analyze theoretically how the Josephson effect can be exploited to activate and detect mechanical oscillations in the experimentally relevant condition with purely DC current bias. We unveil how changing the strength of the electromechanical coupling results in two qualitatively different regimes showing dramatic effects of the oscillations on the DC-voltage characteristic of the device. These include the appearance of Shapiro-type plateaus for weak coupling and a sudden mechanically induced retrapping for strong coupling. Our predictions, measurable in state-of-the-art experimental setups, allow the determination of the frequency and quality factor of the resonator using DC only techniques.
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Using Machine Learning to Predict MCNP Bias
Energy Technology Data Exchange (ETDEWEB)
Grechanuk, Pavel Aleksandrovi [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2018-01-09
For many real-world applications in radiation transport where simulations are compared to experimental measurements, like in nuclear criticality safety, the bias (simulated - experimental keff) in the calculation is an extremely important quantity used for code validation. The objective of this project is to accurately predict the bias of MCNP6 [1] criticality calculations using machine learning (ML) algorithms, with the intention of creating a tool that can complement the current nuclear criticality safety methods. In the latest release of MCNP6, the Whisper tool is available for criticality safety analysts and includes a large catalogue of experimental benchmarks, sensitivity profiles, and nuclear data covariance matrices. This data, coming from 1100+ benchmark cases, is used in this study of ML algorithms for criticality safety bias predictions.
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Disorders of compulsivity: a common bias towards learning habits.
Voon, V; Derbyshire, K; Rück, C; Irvine, M A; Worbe, Y; Enander, J; Schreiber, L R N; Gillan, C; Fineberg, N A; Sahakian, B J; Robbins, T W; Harrison, N A; Wood, J; Daw, N D; Dayan, P; Grant, J E; Bullmore, E T
2015-03-01
Why do we repeat choices that we know are bad for us? Decision making is characterized by the parallel engagement of two distinct systems, goal-directed and habitual, thought to arise from two computational learning mechanisms, model-based and model-free. The habitual system is a candidate source of pathological fixedness. Using a decision task that measures the contribution to learning of either mechanism, we show a bias towards model-free (habit) acquisition in disorders involving both natural (binge eating) and artificial (methamphetamine) rewards, and obsessive-compulsive disorder. This favoring of model-free learning may underlie the repetitive behaviors that ultimately dominate in these disorders. Further, we show that the habit formation bias is associated with lower gray matter volumes in caudate and medial orbitofrontal cortex. Our findings suggest that the dysfunction in a common neurocomputational mechanism may underlie diverse disorders involving compulsion.
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Greek Physical Education Teachers' Gender Biases in Learning and Teaching
Mouratidou, Katerina; Barkoukis, Vassilis
2018-01-01
Gender biases have often been observed in physical education (PE) classes, as many teachers adopt a male-biased perspective in teaching and learning. This might affect their evaluation of students' behavior and may lead students to accept and reproduce gender biases in other social contexts. The aim of this study was to examine whether PE teachers…
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Adult learners in a novel environment use prestige-biased social learning.
Atkisson, Curtis; O'Brien, Michael J; Mesoudi, Alex
2012-08-13
Social learning (learning from others) is evolutionarily adaptive under a wide range of conditions and is a long-standing area of interest across the social and biological sciences. One social-learning mechanism derived from cultural evolutionary theory is prestige bias, which allows a learner in a novel environment to quickly and inexpensively gather information as to the potentially best teachers, thus maximizing his or her chances of acquiring adaptive behavior. Learners provide deference to high-status individuals in order to ingratiate themselves with, and gain extended exposure to, that individual. We examined prestige-biased social transmission in a laboratory experiment in which participants designed arrowheads and attempted to maximize hunting success, measured in caloric return. Our main findings are that (1) participants preferentially learned from prestigious models (defined as those models at whom others spent longer times looking), and (2) prestige information and success-related information were used to the same degree, even though the former was less useful in this experiment than the latter. We also found that (3) participants were most likely to use social learning over individual (asocial) learning when they were performing poorly, in line with previous experiments, and (4) prestige information was not used more often following environmental shifts, contrary to predictions. These results support previous discussions of the key role that prestige-biased transmission plays in social learning.
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Semi-supervised Eigenvectors for Locally-biased Learning
DEFF Research Database (Denmark)
Hansen, Toke Jansen; Mahoney, Michael W.
2012-01-01
In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to perform machine learning and data analysis tasks "nearby" that pre-specified target region. Locally-biased problems of t...
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Step Sizes for Strong Stability Preservation with Downwind-Biased Operators
Ketcheson, David I.
2011-08-04
Strong stability preserving (SSP) integrators for initial value ODEs preserve temporal monotonicity solution properties in arbitrary norms. All existing SSP methods, including implicit methods, either require small step sizes or achieve only first order accuracy. It is possible to achieve more relaxed step size restrictions in the discretization of hyperbolic PDEs through the use of both upwind- and downwind-biased semidiscretizations. We investigate bounds on the maximum SSP step size for methods that include negative coefficients and downwind-biased semi-discretizations. We prove that the downwind SSP coefficient for linear multistep methods of order greater than one is at most equal to two, while the downwind SSP coefficient for explicit Runge–Kutta methods is at most equal to the number of stages of the method. In contrast, the maximal downwind SSP coefficient for second order Runge–Kutta methods is shown to be unbounded. We present a class of such methods with arbitrarily large SSP coefficient and demonstrate that they achieve second order accuracy for large CFL number.
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Energy Technology Data Exchange (ETDEWEB)
Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J. [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States); Brink, Henrik [Dark Cosmology Centre, Juliane Maries Vej 30, 2100 Copenhagen O (Denmark); Long, James P.; Rice, John, E-mail: jwrichar@stat.berkeley.edu [Statistics Department, University of California, Berkeley, CA 94720-7450 (United States)
2012-01-10
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL-where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up-is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
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International Nuclear Information System (INIS)
Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J.; Brink, Henrik; Long, James P.; Rice, John
2012-01-01
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
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Richards, Joseph W.; Starr, Dan L.; Brink, Henrik; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; James, J. Berian; Long, James P.; Rice, John
2012-01-01
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
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Radar Rainfall Bias Correction based on Deep Learning Approach
Song, Yang; Han, Dawei; Rico-Ramirez, Miguel A.
2017-04-01
Radar rainfall measurement errors can be considerably attributed to various sources including intricate synoptic regimes. Temperature, humidity and wind are typically acknowledged as critical meteorological factors in inducing the precipitation discrepancies aloft and on the ground. The conventional practices mainly use the radar-gauge or geostatistical techniques by direct weighted interpolation algorithms as bias correction schemes whereas rarely consider the atmospheric effects. This study aims to comprehensively quantify those meteorological elements' impacts on radar-gauge rainfall bias correction based on a deep learning approach. The deep learning approach employs deep convolutional neural networks to automatically extract three-dimensional meteorological features for target recognition based on high range resolution profiles. The complex nonlinear relationships between input and target variables can be implicitly detected by such a scheme, which is validated on the test dataset. The proposed bias correction scheme is expected to be a promising improvement in systematically minimizing the synthesized atmospheric effects on rainfall discrepancies between radar and rain gauges, which can be useful in many meteorological and hydrological applications (e.g., real-time flood forecasting) especially for regions with complex atmospheric conditions.
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Ariel, Robert; Hines, Jarrod C.; Hertzog, Christopher
2014-01-01
People estimate minimal changes in learning when making predictions of learning (POLs) for future study opportunities despite later showing increased performance and an awareness of that increase (Kornell & Bjork, 2009). This phenomenon is conceptualized as a stability bias in judgments about learning. We investigated the malleability of this effect, and whether it reflected people’s underlying beliefs about learning. We manipulated prediction framing to emphasize the role of testing vs. studying on memory and directly measured beliefs about multi-trial study effects on learning by having participants construct predicted learning curves before and after the experiment. Mean POLs were more sensitive to the number of study-test opportunities when performance was framed in terms of study benefits rather than testing benefits and POLs reflected pre-existing beliefs about learning. The stability bias is partially due to framing and reflects discounted beliefs about learning benefits rather than inherent belief in the stability of performance. PMID:25067885
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Nakahashi, Wataru; Wakano, Joe Yuichiro; Henrich, Joseph
2012-12-01
Long before the origins of agriculture human ancestors had expanded across the globe into an immense variety of environments, from Australian deserts to Siberian tundra. Survival in these environments did not principally depend on genetic adaptations, but instead on evolved learning strategies that permitted the assembly of locally adaptive behavioral repertoires. To develop hypotheses about these learning strategies, we have modeled the evolution of learning strategies to assess what conditions and constraints favor which kinds of strategies. To build on prior work, we focus on clarifying how spatial variability, temporal variability, and the number of cultural traits influence the evolution of four types of strategies: (1) individual learning, (2) unbiased social learning, (3) payoff-biased social learning, and (4) conformist transmission. Using a combination of analytic and simulation methods, we show that spatial-but not temporal-variation strongly favors the emergence of conformist transmission. This effect intensifies when migration rates are relatively high and individual learning is costly. We also show that increasing the number of cultural traits above two favors the evolution of conformist transmission, which suggests that the assumption of only two traits in many models has been conservative. We close by discussing how (1) spatial variability represents only one way of introducing the low-level, nonadaptive phenotypic trait variation that so favors conformist transmission, the other obvious way being learning errors, and (2) our findings apply to the evolution of conformist transmission in social interactions. Throughout we emphasize how our models generate empirical predictions suitable for laboratory testing.
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Lam, Kathy N; Charles, Trevor C
2015-01-01
Clone libraries provide researchers with a powerful resource to study nucleic acid from diverse sources. Metagenomic clone libraries in particular have aided in studies of microbial biodiversity and function, and allowed the mining of novel enzymes. Libraries are often constructed by cloning large inserts into cosmid or fosmid vectors. Recently, there have been reports of GC bias in fosmid metagenomic libraries, and it was speculated to be a result of fragmentation and loss of AT-rich sequences during cloning. However, evidence in the literature suggests that transcriptional activity or gene product toxicity may play a role. To explore possible mechanisms responsible for sequence bias in clone libraries, we constructed a cosmid library from a human microbiome sample and sequenced DNA from different steps during library construction: crude extract DNA, size-selected DNA, and cosmid library DNA. We confirmed a GC bias in the final cosmid library, and we provide evidence that the bias is not due to fragmentation and loss of AT-rich sequences but is likely occurring after DNA is introduced into Escherichia coli. To investigate the influence of strong constitutive transcription, we searched the sequence data for promoters and found that rpoD/σ(70) promoter sequences were underrepresented in the cosmid library. Furthermore, when we examined the genomes of taxa that were differentially abundant in the cosmid library relative to the original sample, we found the bias to be more correlated with the number of rpoD/σ(70) consensus sequences in the genome than with simple GC content. The GC bias of metagenomic libraries does not appear to be due to DNA fragmentation. Rather, analysis of promoter sequences provides support for the hypothesis that strong constitutive transcription from sequences recognized as rpoD/σ(70) consensus-like in E. coli may lead to instability, causing loss of the plasmid or loss of the insert DNA that gives rise to the transcription. Despite
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Reynolds, Gemma; Field, Andy P; Askew, Chris
2014-10-01
Research with children has shown that vicarious learning can result in changes to 2 of Lang's (1968) 3 anxiety response systems: subjective report and behavioral avoidance. The current study extended this research by exploring the effect of vicarious learning on physiological responses (Lang's final response system) and attentional bias. The study used Askew and Field's (2007) vicarious learning procedure and demonstrated fear-related increases in children's cognitive, behavioral, and physiological responses. Cognitive and behavioral changes were retested 1 week and 1 month later, and remained elevated. In addition, a visual search task demonstrated that fear-related vicarious learning creates an attentional bias for novel animals, which is moderated by increases in fear beliefs during learning. The findings demonstrate that vicarious learning leads to lasting changes in all 3 of Lang's anxiety response systems and is sufficient to create attentional bias to threat in children. PsycINFO Database Record (c) 2014 APA, all rights reserved.
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2018-04-01
Luque, D., Vadillo, M, A., Gutiérrez-Cobo, M, J., Le Pelley, M, E. (2018). The blocking effect in associative learning involves learned biases in rapid attentional capture. Quarterly Journal of Experimental Psychology, 71, 522-544. doi: 10.1080/17470218.2016.1262435. The above article is part of the Special Issue on Associative Learning (in honour of Nick Mackintosh) and was inadvertently published in the February 2018 issue of Quarterly Journal of Experimental Psychology. After publication of the Special Issue, an online collection on Associative Learning will be created on SAGE Journals and this paper will be included in that collection. The Publisher apologises for this error.
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2014-01-01
Research with children has shown that vicarious learning can result in changes to 2 of Lang’s (1968) 3 anxiety response systems: subjective report and behavioral avoidance. The current study extended this research by exploring the effect of vicarious learning on physiological responses (Lang’s final response system) and attentional bias. The study used Askew and Field’s (2007) vicarious learning procedure and demonstrated fear-related increases in children’s cognitive, behavioral, and physiological responses. Cognitive and behavioral changes were retested 1 week and 1 month later, and remained elevated. In addition, a visual search task demonstrated that fear-related vicarious learning creates an attentional bias for novel animals, which is moderated by increases in fear beliefs during learning. The findings demonstrate that vicarious learning leads to lasting changes in all 3 of Lang’s anxiety response systems and is sufficient to create attentional bias to threat in children. PMID:25151521
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Semi-supervised eigenvectors for large-scale locally-biased learning
DEFF Research Database (Denmark)
Hansen, Toke Jansen; Mahoney, Michael W.
2014-01-01
improved scaling properties. We provide several empirical examples demonstrating how these semi-supervised eigenvectors can be used to perform locally-biased learning; and we discuss the relationship between our results and recent machine learning algorithms that use global eigenvectors of the graph......In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to perform machine learning and data analysis tasks nearby that prespecified target region. For example, one might......-based machine learning and data analysis tools. At root, the reason is that eigenvectors are inherently global quantities, thus limiting the applicability of eigenvector-based methods in situations where one is interested in very local properties of the data. In this paper, we address this issue by providing...
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Tagore, Amitpal S.; Barnes, David J.; Jackson, Neal; Kay, Scott T.; Schaller, Matthieu; Schaye, Joop; Theuns, Tom
2018-03-01
Cosmological parameter constraints from observations of time-delay lenses are becoming increasingly precise. However, there may be significant bias and scatter in these measurements due to, among other things, the so-called mass-sheet degeneracy. To estimate these uncertainties, we analyse strong lenses from the largest EAGLE hydrodynamical simulation. We apply a mass-sheet transformation to the radial density profiles of lenses, and by selecting lenses near isothermality, we find that the bias on H0 can be reduced to 5 per cent with an intrinsic scatter of 10 per cent, confirming previous results performed on a different simulation data set. We further investigate whether combining lensing observables with kinematic constraints helps to minimize this bias. We do not detect any significant dependence of the bias on lens model parameters or observational properties of the galaxy, but depending on the source-lens configuration, a bias may still exist. Cross lenses provide an accurate estimate of the Hubble constant, while fold (double) lenses tend to be biased low (high). With kinematic constraints, double lenses show bias and intrinsic scatter of 6 per cent and 10 per cent, respectively, while quad lenses show bias and intrinsic scatter of 0.5 per cent and 10 per cent, respectively. For lenses with a reduced χ2 > 1, a power-law dependence of the χ2 on the lens environment (number of nearby galaxies) is seen. Lastly, we model, in greater detail, the cases of two double lenses that are significantly biased. We are able to remove the bias, suggesting that the remaining biases could also be reduced by carefully taking into account additional sources of systematic uncertainty.
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Reinforcement function design and bias for efficient learning in mobile robots
International Nuclear Information System (INIS)
Touzet, C.; Santos, J.M.
1998-01-01
The main paradigm in sub-symbolic learning robot domain is the reinforcement learning method. Various techniques have been developed to deal with the memorization/generalization problem, demonstrating the superior ability of artificial neural network implementations. In this paper, the authors address the issue of designing the reinforcement so as to optimize the exploration part of the learning. They also present and summarize works relative to the use of bias intended to achieve the effective synthesis of the desired behavior. Demonstrative experiments involving a self-organizing map implementation of the Q-learning and real mobile robots (Nomad 200 and Khepera) in a task of obstacle avoidance behavior synthesis are described. 3 figs., 5 tabs
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2017-01-01
The type and variety of learning strategies used by individuals to acquire behaviours in the wild are poorly understood, despite the presence of behavioural traditions in diverse taxa. Social learning strategies such as conformity can be broadly adaptive, but may also retard the spread of adaptive innovations. Strategies like pay-off-biased learning, by contrast, are effective at diffusing new behaviour but may perform poorly when adaptive behaviour is common. We present a field experiment in a wild primate, Cebus capucinus, that introduced a novel food item and documented the innovation and diffusion of successful extraction techniques. We develop a multilevel, Bayesian statistical analysis that allows us to quantify individual-level evidence for different social and individual learning strategies. We find that pay-off-biased and age-biased social learning are primarily responsible for the diffusion of new techniques. We find no evidence of conformity; instead rare techniques receive slightly increased attention. We also find substantial and important variation in individual learning strategies that is patterned by age, with younger individuals being more influenced by both social information and their own individual experience. The aggregate cultural dynamics in turn depend upon the variation in learning strategies and the age structure of the wild population. PMID:28592681
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Adaptable history biases in human perceptual decisions.
Abrahamyan, Arman; Silva, Laura Luz; Dakin, Steven C; Carandini, Matteo; Gardner, Justin L
2016-06-21
When making choices under conditions of perceptual uncertainty, past experience can play a vital role. However, it can also lead to biases that worsen decisions. Consistent with previous observations, we found that human choices are influenced by the success or failure of past choices even in a standard two-alternative detection task, where choice history is irrelevant. The typical bias was one that made the subject switch choices after a failure. These choice history biases led to poorer performance and were similar for observers in different countries. They were well captured by a simple logistic regression model that had been previously applied to describe psychophysical performance in mice. Such irrational biases seem at odds with the principles of reinforcement learning, which would predict exquisite adaptability to choice history. We therefore asked whether subjects could adapt their irrational biases following changes in trial order statistics. Adaptability was strong in the direction that confirmed a subject's default biases, but weaker in the opposite direction, so that existing biases could not be eradicated. We conclude that humans can adapt choice history biases, but cannot easily overcome existing biases even if irrational in the current context: adaptation is more sensitive to confirmatory than contradictory statistics.
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Machine Learning Phases of Strongly Correlated Fermions
Directory of Open Access Journals (Sweden)
Kelvin Ch’ng
2017-08-01
Full Text Available Machine learning offers an unprecedented perspective for the problem of classifying phases in condensed matter physics. We employ neural-network machine learning techniques to distinguish finite-temperature phases of the strongly correlated fermions on cubic lattices. We show that a three-dimensional convolutional network trained on auxiliary field configurations produced by quantum Monte Carlo simulations of the Hubbard model can correctly predict the magnetic phase diagram of the model at the average density of one (half filling. We then use the network, trained at half filling, to explore the trend in the transition temperature as the system is doped away from half filling. This transfer learning approach predicts that the instability to the magnetic phase extends to at least 5% doping in this region. Our results pave the way for other machine learning applications in correlated quantum many-body systems.
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A self-learning algorithm for biased molecular dynamics
Tribello, Gareth A.; Ceriotti, Michele; Parrinello, Michele
2010-01-01
A new self-learning algorithm for accelerated dynamics, reconnaissance metadynamics, is proposed that is able to work with a very large number of collective coordinates. Acceleration of the dynamics is achieved by constructing a bias potential in terms of a patchwork of one-dimensional, locally valid collective coordinates. These collective coordinates are obtained from trajectory analyses so that they adapt to any new features encountered during the simulation. We show how this methodology can be used to enhance sampling in real chemical systems citing examples both from the physics of clusters and from the biological sciences. PMID:20876135
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Language learning, language use and the evolution of linguistic variation
Perfors, Amy; Fehér, Olga; Samara, Anna; Swoboda, Kate; Wonnacott, Elizabeth
2017-01-01
Linguistic universals arise from the interaction between the processes of language learning and language use. A test case for the relationship between these factors is linguistic variation, which tends to be conditioned on linguistic or sociolinguistic criteria. How can we explain the scarcity of unpredictable variation in natural language, and to what extent is this property of language a straightforward reflection of biases in statistical learning? We review three strands of experimental work exploring these questions, and introduce a Bayesian model of the learning and transmission of linguistic variation along with a closely matched artificial language learning experiment with adult participants. Our results show that while the biases of language learners can potentially play a role in shaping linguistic systems, the relationship between biases of learners and the structure of languages is not straightforward. Weak biases can have strong effects on language structure as they accumulate over repeated transmission. But the opposite can also be true: strong biases can have weak or no effects. Furthermore, the use of language during interaction can reshape linguistic systems. Combining data and insights from studies of learning, transmission and use is therefore essential if we are to understand how biases in statistical learning interact with language transmission and language use to shape the structural properties of language. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872370
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Language learning, language use and the evolution of linguistic variation.
Smith, Kenny; Perfors, Amy; Fehér, Olga; Samara, Anna; Swoboda, Kate; Wonnacott, Elizabeth
2017-01-05
Linguistic universals arise from the interaction between the processes of language learning and language use. A test case for the relationship between these factors is linguistic variation, which tends to be conditioned on linguistic or sociolinguistic criteria. How can we explain the scarcity of unpredictable variation in natural language, and to what extent is this property of language a straightforward reflection of biases in statistical learning? We review three strands of experimental work exploring these questions, and introduce a Bayesian model of the learning and transmission of linguistic variation along with a closely matched artificial language learning experiment with adult participants. Our results show that while the biases of language learners can potentially play a role in shaping linguistic systems, the relationship between biases of learners and the structure of languages is not straightforward. Weak biases can have strong effects on language structure as they accumulate over repeated transmission. But the opposite can also be true: strong biases can have weak or no effects. Furthermore, the use of language during interaction can reshape linguistic systems. Combining data and insights from studies of learning, transmission and use is therefore essential if we are to understand how biases in statistical learning interact with language transmission and language use to shape the structural properties of language.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Authors.
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Bias correction for selecting the minimal-error classifier from many machine learning models.
Ding, Ying; Tang, Shaowu; Liao, Serena G; Jia, Jia; Oesterreich, Steffi; Lin, Yan; Tseng, George C
2014-11-15
Supervised machine learning is commonly applied in genomic research to construct a classifier from the training data that is generalizable to predict independent testing data. When test datasets are not available, cross-validation is commonly used to estimate the error rate. Many machine learning methods are available, and it is well known that no universally best method exists in general. It has been a common practice to apply many machine learning methods and report the method that produces the smallest cross-validation error rate. Theoretically, such a procedure produces a selection bias. Consequently, many clinical studies with moderate sample sizes (e.g. n = 30-60) risk reporting a falsely small cross-validation error rate that could not be validated later in independent cohorts. In this article, we illustrated the probabilistic framework of the problem and explored the statistical and asymptotic properties. We proposed a new bias correction method based on learning curve fitting by inverse power law (IPL) and compared it with three existing methods: nested cross-validation, weighted mean correction and Tibshirani-Tibshirani procedure. All methods were compared in simulation datasets, five moderate size real datasets and two large breast cancer datasets. The result showed that IPL outperforms the other methods in bias correction with smaller variance, and it has an additional advantage to extrapolate error estimates for larger sample sizes, a practical feature to recommend whether more samples should be recruited to improve the classifier and accuracy. An R package 'MLbias' and all source files are publicly available. tsenglab.biostat.pitt.edu/software.htm. ctseng@pitt.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Mertens, G.; De Houwer, J.
2017-01-01
Whereas it is widely recognized that both verbal threat information and stimulus pairings can install strong and persistent fear, few studies have addressed the interaction between these two pathways of fear. According to the expectancy bias theory of Davey (1992, 1997), verbal information can
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Reynolds, G; Field, AP; Askew, C
2014-01-01
Research with children has shown that vicarious learning can result in changes to 2 of Lang's (1968) 3 anxiety response systems: subjective report and behavioral avoidance. The current study extended this research by exploring the effect of vicarious learning on physiological responses (Lang's final response system) and attentional bias. The study used Askew and Field's (2007) vicarious learning procedure and demonstrated fear-related increases in children's cognitive, behavioral, and physiol...
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When being narrow minded is a good thing: locally biased people show stronger contextual cueing.
Bellaera, Lauren; von Mühlenen, Adrian; Watson, Derrick G
2014-01-01
Repeated contexts allow us to find relevant information more easily. Learning such contexts has been proposed to depend upon either global processing of the repeated contexts, or alternatively processing of the local region surrounding the target information. In this study, we measured the extent to which observers were by default biased to process towards a more global or local level. The findings showed that the ability to use context to help guide their search was strongly related to an observer's local/global processing bias. Locally biased people could use context to help improve their search better than globally biased people. The results suggest that the extent to which context can be used depends crucially on the observer's attentional bias and thus also to factors and influences that can change this bias.
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Field, Zoë C; Field, Andy P
2013-06-01
Cognitive models of vulnerability to anxiety propose that information processing biases such as interpretation bias play a part in the etiology and maintenance of anxiety disorders. However, at present little is known about the role of memory in information processing accounts of child anxiety. The current study investigates the relationships between interpretation biases, memory and fear responses when learning about new stimuli. Children (aged 8-11 years) were presented with ambiguous information regarding a novel animal, and their fear, interpretation bias, and memory for the information was measured. The main findings were: (1) trait anxiety and interpretation bias significantly predicted acquired fear; (2) interpretation bias did not significantly mediate the relationship between trait anxiety and acquired fear; (3) interpretation bias appeared to be a more important predictor of acquired fear than trait anxiety per se; and (4) the relationship between interpretation bias and acquired fear was not mediated by the number of negative memories but was mediated by the number of positive and false-positive memories. The findings suggest that information processing models of child anxiety need to explain the role of positive memory in the formation of fear responses.
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Fear acquisition and liking of out-group and in-group members: Learning bias or attention?
Koenig, Stephan; Nauroth, Peter; Lucke, Sara; Lachnit, Harald; Gollwitzer, Mario; Uengoer, Metin
2017-10-01
The present study explores the notion of an out-group fear learning bias that is characterized by facilitated fear acquisition toward harm-doing out-group members. Participants were conditioned with two in-group and two out-group faces as conditioned stimuli. During acquisition, one in-group and one out-group face was paired with an aversive shock whereas the other in-group and out-group face was presented without shock. Psychophysiological measures of fear conditioning (skin conductance and pupil size) and explicit and implicit liking exhibited increased differential responding to out-group faces compared to in-group faces. However, the results did not clearly indicate that harm-doing out-group members were more readily associated with fear than harm-doing in-group members. In contrast, the out-group face not paired with shock decreased conditioned fear and disliking at least to the same extent that the shock-associated out-group face increased these measures. Based on these results, we suggest an account of the out-group fear learning bias that relates to an attentional bias to process in-group information. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
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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.
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Reali, Florencia; Griffiths, Thomas L.
2009-01-01
The regularization of linguistic structures by learners has played a key role in arguments for strong innate constraints on language acquisition, and has important implications for language evolution. However, relating the inductive biases of learners to regularization behavior in laboratory tasks can be challenging without a formal model. In this…
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Growth hormone biases amygdala network activation after fear learning.
Gisabella, B; Farah, S; Peng, X; Burgos-Robles, A; Lim, S H; Goosens, K A
2016-11-29
Prolonged stress exposure is a risk factor for developing posttraumatic stress disorder, a disorder characterized by the 'over-encoding' of a traumatic experience. A potential mechanism by which this occurs is through upregulation of growth hormone (GH) in the amygdala. Here we test the hypotheses that GH promotes the over-encoding of fearful memories by increasing the number of neurons activated during memory encoding and biasing the allocation of neuronal activation, one aspect of the process by which neurons compete to encode memories, to favor neurons that have stronger inputs. Viral overexpression of GH in the amygdala increased the number of amygdala cells activated by fear memory formation. GH-overexpressing cells were especially biased to express the immediate early gene c-Fos after fear conditioning, revealing strong autocrine actions of GH in the amygdala. In addition, we observed dramatically enhanced dendritic spine density in GH-overexpressing neurons. These data elucidate a previously unrecognized autocrine role for GH in the regulation of amygdala neuron function and identify specific mechanisms by which chronic stress, by enhancing GH in the amygdala, may predispose an individual to excessive fear memory formation.
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An Investigation of the Learning Strategies as Bias Factors in Second Language Cloze Tests
Ajideh, Parviz; Yaghoubi-Notash, Massoud; Khalili, Abdolreza
2017-01-01
The present study investigated the contribution of the EFL students' learning strategies to the explanation of the variance in their results on language tests. More specifically, it examined the role of these strategies as bias factors in the results of English cloze tests. Based on this aim, first, 158 intermediate EFL learners were selected from…
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Directory of Open Access Journals (Sweden)
Masayuki Hayashi
Full Text Available For maternally transmitted microbes, a female-biased host sex ratio is of reproductive advantage. Here we found a strong female bias in a field population of the green lacewing, Mallada desjardinsi (Insecta; Neuroptera. This bias was attributed to the predominance of individuals harboring a maternally inherited male-killing bacterium that was phylogenetically closely related to the plant-pathogenic Spiroplasma phoeniceum and Spiroplasma kunkelii. Among 35 laboratory-reared broods produced by wild-caught females, 21 broods (60%-all infected with Spiroplasma-consisted of only females (940 individuals. Among 14 broods consisting of both males and females (516 and 635 individuals, respectively, 4 broods were doubly infected with Spiroplasma and Rickettsia, 6 broods were singly infected with Rickettsia, and 3 broods were uninfected (remaining one brood was unknown. Mortality during embryonic and larval development was prominent in all-female broods but not in normal sex ratio broods. Following antibiotic treatment on all-female broods, mortality was significantly reduced and the sex ratio was restored to 1:1. Strong expression and high prevalence of this male-killer is remarkable considering its low density (~10-5-10-4 cells per host mitochondrial gene copy based on quantitative PCR. In addition, a bacterium closely related to Rickettsia bellii was present in 25 of 34 broods (73.5%, irrespective of the sex ratio, with the infection density comparable to other cases of endosymbiosis (~10-2-10-1 cells per mitochondrial gene copy. Higher density of Rickettsia than Spiroplasma was also demonstrated by electron microscopy which visualized both Spiroplasma-like cells and Rickettsia-like cells inside and outside the ovarian cells.
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Eden, Annuschka S; Dehmelt, Vera; Bischoff, Matthias; Zwitserlood, Pienie; Kugel, Harald; Keuper, Kati; Zwanzger, Peter; Dobel, Christian
2015-01-01
Persons suffering from anxiety disorders display facilitated processing of arousing and negative stimuli, such as negative words. This memory bias is reflected in better recall and increased amygdala activity in response to such stimuli. However, individual learning histories were not considered in most studies, a concern that we meet here. Thirty-four female persons (half with high-, half with low trait anxiety) participated in a criterion-based associative word-learning paradigm, in which neutral pseudowords were paired with aversive or neutral pictures, which should lead to a valence change for the negatively paired pseudowords. After learning, pseudowords were tested with fMRI to investigate differential brain activation of the amygdala evoked by the newly acquired valence. Explicit and implicit memory was assessed directly after training and in three follow-ups at 4-day intervals. The behavioral results demonstrate that associative word-learning leads to an explicit (but no implicit) memory bias for negatively linked pseudowords, relative to neutral ones, which confirms earlier studies. Bilateral amygdala activation underlines the behavioral effect: Higher trait anxiety is correlated with stronger amygdala activation for negatively linked pseudowords than for neutrally linked ones. Most interestingly, this effect is also present for negatively paired pseudowords that participants could not remember well. Moreover, neutrally paired pseudowords evoked higher amygdala reactivity than completely novel ones in highly anxious persons, which can be taken as evidence for generalization. These findings demonstrate that few word-learning trials generate a memory bias for emotional stimuli, indexed both behaviorally and neurophysiologically. Importantly, the typical memory bias for emotional stimuli and the generalization to neutral ones is larger in high anxious persons.
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Directory of Open Access Journals (Sweden)
Annuschka Salima Eden
2015-08-01
Full Text Available Persons suffering from anxiety disorders display facilitated processing of arousing and negative stimuli, such as negative words. This memory bias is reflected in better recall and increased amygdala activity in response to such stimuli. However, individual learning histories were not considered in most studies, a concern that we meet here. Thirty-four female persons (half with high-, half with low trait anxiety participated in a criterion-based associative word-learning paradigm, in which neutral pseudowords were paired with aversive or neutral pictures, which should lead to a valence change for the negatively paired pseudowords. After learning, pseudowords were tested with fMRI to investigate differential brain activation of the amygdala evoked by the newly acquired valence. Explicit and implicit memory was assessed directly after training and in three follow-ups at four-day intervals. The behavioral results demonstrate that associative word-learning leads to an explicit (but no implicit memory bias for negatively linked pseudowords, relative to neutral ones, which confirms earlier studies. Bilateral amygdala activation underlines the behavioral effect: Higher trait anxiety is correlated with stronger amygdala activation for negatively linked pseudowords than for neutrally linked ones. Most interestingly, this effect is also present for negatively paired pseudowords that participants could not remember well. Moreover, neutrally paired pseudowords evoked higher amygdala reactivity than completely novel ones in highly anxious persons, which can be taken as evidence for generalization. These findings demonstrate that few word-learning trials generate a memory bias for emotional stimuli, indexed both behaviorally and neurophysiologically. Importantly, the typical memory bias for emotional stimuli and the generalization to neutral ones is larger in high anxious persons.
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Step Sizes for Strong Stability Preservation with Downwind-Biased Operators
Ketcheson, David I.
2011-01-01
order accuracy. It is possible to achieve more relaxed step size restrictions in the discretization of hyperbolic PDEs through the use of both upwind- and downwind-biased semidiscretizations. We investigate bounds on the maximum SSP step size for methods
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Directory of Open Access Journals (Sweden)
Ali eKHATIBI
2014-09-01
Full Text Available Individuals with pain-related concerns are likely to interpret ambiguous pain-related information in a threatening manner. It is unknown whether this interpretation bias also occurs for ambiguous pain-related facial expressions. This study examined whether individuals who habitually attach a catastrophic meaning to pain are characterized by negative interpretation bias for ambiguous pain-related facial expressions. Sixty-four female undergraduates completed an incidental learning task during which pictures of faces were presented, each followed by a visual target at one of two locations. Participants indicated target location by pressing one of two response keys. During the learning phase, happy and painful facial expressions predicted target location. During two test phases, morphed facial expressions of pain and happiness were added, equally often followed by a target at either location. Faster responses following morphs to targets at the location predicted by painful expressions compared to targets at the location predicted by happy expressions were taken to reflect pain-related interpretation bias. During one test phase, faces were preceded by either a safe or threatening context cue. High, but not low, pain-catastrophizers responded faster following morphs to targets at the location predicted by painful expressions than to targets at the other location (when participants were aware of the contingency between expression type and target location. When context cues were presented, there was no indication of interpretation bias. Participants were also asked to directly classify the facial expressions that were presented during the incidental learning task. Participants classified morphs more often as happy than as painful, independent of their level of pain catastrophizing. This observation is discussed in terms of differences between indirect and direct measures of interpretation bias.
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<strong>Shop stewards' learning and union strategiesstrong>
DEFF Research Database (Denmark)
Warring, Niels
2007-01-01
In Denmark the trade unions have well established educational systems providing the shop stewards with a variety of competencies. Union courses have been analysed focusing on shop stewards' satisfaction with the content and the practical impact of the courses. However, little attention has been...... different theoretical traditions: Shop steward's learning is situational, relational and cross-contextual. Shop stewards' learning is lifelong and life wide. And shop stewards' learning is closely connected to the development of the labour market and not least the unions' priorities, interpretation...
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Directory of Open Access Journals (Sweden)
Alexander Komarov
2016-02-01
Full Text Available The article is devoted to the contribution of foreign language learning to stimulating students’ life skills at non-linguistic higher institutions. In the article, the author considers the possibilities of motivating students to exercise life skills in the process of foreign language instruction. The author analyses the cooperative learning technology as a means that enables students to be involved into interaction with one another as well as it develops their team-building skills to successfully cooperate and communicate with each other. The author describes different forms of cooperative leaning, which give students an opportunity to mutually enrich and complement each other’s skills in foreign language learning. The author argues that cooperative learning technology stimulates the students’ existent life skills and makes them work in the process of professionally-biased instruction of a foreign language.
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Bounding the bias of contrastive divergence learning
DEFF Research Database (Denmark)
Fischer, Anja; Igel, Christian
2011-01-01
Optimization based on k-step contrastive divergence (CD) has become a common way to train restricted Boltzmann machines (RBMs). The k-step CD is a biased estimator of the log-likelihood gradient relying on Gibbs sampling. We derive a new upper bound for this bias. Its magnitude depends on k...
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Harmonic biases in child learners: In support of language universals
Culbertson, Jennifer; Newport, Elissa L.
2015-01-01
A fundamental question for cognitive science concerns the ways in which languages are shaped by the biases of language learners. Recent research using laboratory language learning paradigms, primarily with adults, has shown that structures or rules that are common in the languages of the world are learned or processed more easily than patterns that are rare or unattested. Here we target child learners, investigating a set of biases for word order learning in the noun phrase studied by Culbertson, Smolensky & Legendre (2012) in college-age adults. We provide the first evidence that child learners exhibit a preference for typologically common harmonic word order patterns—those which preserve the order of the head with respect to its complements—validating the psychological reality of a principle formalized in many different linguistic theories. We also discuss important differences between child and adult learners in terms of both the strength and content of the biases at play during language learning. In particular, the bias favoring harmonic patterns is markedly stronger in children than adults, and children (unlike adults) acquire adjective ordering more readily than numeral ordering. The results point to the importance of investigating learning biases across development in order to understand how these biases may shape the history and structure of natural languages. PMID:25800352
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Do horses with poor welfare show `pessimistic' cognitive biases?
Henry, S.; Fureix, C.; Rowberry, R.; Bateson, M.; Hausberger, M.
2017-02-01
This field study tested the hypothesis that domestic horses living under putatively challenging-to-welfare conditions (for example involving social, spatial, feeding constraints) would present signs of poor welfare and co-occurring pessimistic judgement biases. Our subjects were 34 horses who had been housed for over 3 years in either restricted riding school situations ( e.g. kept in single boxes, with limited roughage, ridden by inexperienced riders; N = 25) or under more naturalistic conditions ( e.g. access to free-range, kept in stable social groups, leisure riding; N = 9). The horses' welfare was assessed by recording health-related, behavioural and postural indicators. Additionally, after learning a location task to discriminate a bucket containing either edible food (`positive' location) or unpalatable food (`negative' location), the horses were presented with a bucket located near the positive position, near the negative position and halfway between the positive and negative positions to assess their judgement biases. The riding school horses displayed the highest levels of behavioural and health-related problems and a pessimistic judgment bias, whereas the horses living under more naturalistic conditions displayed indications of good welfare and an optimistic bias. Moreover, pessimistic bias data strongly correlated with poor welfare data. This suggests that a lowered mood impacts a non-human species' perception of its environment and highlights cognitive biases as an appropriate tool to assess the impact of chronic living conditions on horse welfare.
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Do horses with poor welfare show 'pessimistic' cognitive biases?
Henry, S; Fureix, C; Rowberry, R; Bateson, M; Hausberger, M
2017-02-01
This field study tested the hypothesis that domestic horses living under putatively challenging-to-welfare conditions (for example involving social, spatial, feeding constraints) would present signs of poor welfare and co-occurring pessimistic judgement biases. Our subjects were 34 horses who had been housed for over 3 years in either restricted riding school situations (e.g. kept in single boxes, with limited roughage, ridden by inexperienced riders; N = 25) or under more naturalistic conditions (e.g. access to free-range, kept in stable social groups, leisure riding; N = 9). The horses' welfare was assessed by recording health-related, behavioural and postural indicators. Additionally, after learning a location task to discriminate a bucket containing either edible food ('positive' location) or unpalatable food ('negative' location), the horses were presented with a bucket located near the positive position, near the negative position and halfway between the positive and negative positions to assess their judgement biases. The riding school horses displayed the highest levels of behavioural and health-related problems and a pessimistic judgment bias, whereas the horses living under more naturalistic conditions displayed indications of good welfare and an optimistic bias. Moreover, pessimistic bias data strongly correlated with poor welfare data. This suggests that a lowered mood impacts a non-human species' perception of its environment and highlights cognitive biases as an appropriate tool to assess the impact of chronic living conditions on horse welfare.
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Neel, Rebecca; Shapiro, Jenessa R
2012-07-01
How do Whites approach interracial interactions? We argue that a previously unexamined factor-beliefs about the malleability of racial bias-guides Whites' strategies for difficult interracial interactions. We predicted and found that those who believe racial bias is malleable favor learning-oriented strategies such as taking the other person's perspective and trying to learn why an interaction is challenging, whereas those who believe racial bias is fixed favor performance-oriented strategies such as overcompensating in the interaction and trying to end the interaction as quickly as possible. Four studies support these predictions. Whether measured (Studies 1, 3, and 4) or manipulated (Study 2), beliefs that racial bias is fixed versus malleable yielded these divergent strategies for difficult interracial interactions. Furthermore, beliefs about the malleability of racial bias are distinct from related constructs (e.g., prejudice and motivations to respond without prejudice; Studies 1, 3, and 4) and influence self-reported (Studies 1-3) and actual (Study 4) strategies in imagined (Studies 1-2) and real (Studies 3-4) interracial interactions. Together, these findings demonstrate that beliefs about the malleability of racial bias influence Whites' approaches to and strategies within interracial interactions. PsycINFO Database Record (c) 2012 APA, all rights reserved
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Mixotrophic phytoflagellate bacterivory field measurements strongly biased by standard approaches
DEFF Research Database (Denmark)
Anderson, Ruth; Jürgens, Klaus; Hansen, Per Juel
2017-01-01
Bacterivory among small (≤ 20 μm) phytoflagellates (SP) is increasingly recognized as a globally relevant phenomenon, impacting a wide range of aspects from primary production levels to marine fisheries. However, to correctly parametrize mixotrophic SP in biogeochemical and food web models, a bet...... mixotrophic SP. Overall, this case study indicates that applying the two commonly used premises outlined above can introduce significant biases and considerably alter our perception of mixotrophy in a given system......., a better understanding of the magnitude and regulation of in situ SP feeding is urgently needed. Current methods to determine SP bacterivory in the field may introduce biases by treating these organisms as equivalent to heterotrophic nanoflagellates (HNF). In the present case study we experimentally tested...... two generally employed assumptions of such studies: (A) bacterivory rates of the whole SP community and of distinct SP groups remain constant over `short´ time scales (hours to a day) and (B) SP community ingestion rates approximate the average ingestion rate of all feeding individuals. Food vacuole...
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Harmonic biases in child learners: in support of language universals.
Culbertson, Jennifer; Newport, Elissa L
2015-06-01
A fundamental question for cognitive science concerns the ways in which languages are shaped by the biases of language learners. Recent research using laboratory language learning paradigms, primarily with adults, has shown that structures or rules that are common in the languages of the world are learned or processed more easily than patterns that are rare or unattested. Here we target child learners, investigating a set of biases for word order learning in the noun phrase studied by Culbertson, Smolensky, and Legendre (2012) in college-age adults. We provide the first evidence that child learners exhibit a preference for typologically common harmonic word order patterns-those which preserve the order of the head with respect to its complements-validating the psychological reality of a principle formalized in many different linguistic theories. We also discuss important differences between child and adult learners in terms of both the strength and content of the biases at play during language learning. In particular, the bias favoring harmonic patterns is markedly stronger in children than adults, and children (unlike adults) acquire adjective ordering more readily than numeral ordering. The results point to the importance of investigating learning biases across development in order to understand how these biases may shape the history and structure of natural languages. Copyright © 2015 Elsevier B.V. All rights reserved.
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Gender bias in Islamic textbooks for Muslim children in Indonesia
Directory of Open Access Journals (Sweden)
Suwardi Suwardi
2018-01-01
Full Text Available Textbook has a strong influence on the formation of children’s attitudes and value system. Therefore, Islamic textbooks as the main learning source for Muslim children in Indonesia need to consider the gender equality. This is very important to note, because feminists often view that Islam contains teachings of gender inequality. Islam places men in the higher position, while women are placed in the lower position. For example, men can be imam for women in prayer, but women cannot be imam for men. It is easier for children to learn textbook material presented in pictures. Therefore, the pictures presented in Islamic textbooks ideally do not contain gender bias. So, a research is needed to know if there is gender bias in the pictures presented in Islamic textbooks taught to Muslim children in Indonesia. To prove it, a literary research is conducted on the Islamic textbooks taught to the first grade Muslim student of Islamic Elementary School/ Madrasah Ibtidaiyah (MI in Indonesia which includes pictures in their teaching materials. Islamic textbooks studied in the research include Fikih, Akidah Akhlak, and Arabic textbooks. The results of this study conclude that the pictures presented in Islamic textbooks taught in Muslim children in Indonesia contain gender bias. The man favor pictures are more than those of woman favor. Based on the conclusion, this study recommends an improvement of pictures presented in Islamic textbooks taught to Muslim children in Indonesia.
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Perceptual Biases in Relation to Paranormal and Conspiracy Beliefs.
van Elk, Michiel
2015-01-01
Previous studies have shown that one's prior beliefs have a strong effect on perceptual decision-making and attentional processing. The present study extends these findings by investigating how individual differences in paranormal and conspiracy beliefs are related to perceptual and attentional biases. Two field studies were conducted in which visitors of a paranormal conducted a perceptual decision making task (i.e. the face/house categorization task; Experiment 1) or a visual attention task (i.e. the global/local processing task; Experiment 2). In the first experiment it was found that skeptics compared to believers more often incorrectly categorized ambiguous face stimuli as representing a house, indicating that disbelief rather than belief in the paranormal is driving the bias observed for the categorization of ambiguous stimuli. In the second experiment, it was found that skeptics showed a classical 'global-to-local' interference effect, whereas believers in conspiracy theories were characterized by a stronger 'local-to-global interference effect'. The present study shows that individual differences in paranormal and conspiracy beliefs are associated with perceptual and attentional biases, thereby extending the growing body of work in this field indicating effects of cultural learning on basic perceptual processes.
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Perceptual Biases in Relation to Paranormal and Conspiracy Beliefs.
Directory of Open Access Journals (Sweden)
Michiel van Elk
Full Text Available Previous studies have shown that one's prior beliefs have a strong effect on perceptual decision-making and attentional processing. The present study extends these findings by investigating how individual differences in paranormal and conspiracy beliefs are related to perceptual and attentional biases. Two field studies were conducted in which visitors of a paranormal conducted a perceptual decision making task (i.e. the face/house categorization task; Experiment 1 or a visual attention task (i.e. the global/local processing task; Experiment 2. In the first experiment it was found that skeptics compared to believers more often incorrectly categorized ambiguous face stimuli as representing a house, indicating that disbelief rather than belief in the paranormal is driving the bias observed for the categorization of ambiguous stimuli. In the second experiment, it was found that skeptics showed a classical 'global-to-local' interference effect, whereas believers in conspiracy theories were characterized by a stronger 'local-to-global interference effect'. The present study shows that individual differences in paranormal and conspiracy beliefs are associated with perceptual and attentional biases, thereby extending the growing body of work in this field indicating effects of cultural learning on basic perceptual processes.
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Causal Learning in Gambling Disorder: Beyond the Illusion of Control.
Perales, José C; Navas, Juan F; Ruiz de Lara, Cristian M; Maldonado, Antonio; Catena, Andrés
2017-06-01
Causal learning is the ability to progressively incorporate raw information about dependencies between events, or between one's behavior and its outcomes, into beliefs of the causal structure of the world. In spite of the fact that some cognitive biases in gambling disorder can be described as alterations of causal learning involving gambling-relevant cues, behaviors, and outcomes, general causal learning mechanisms in gamblers have not been systematically investigated. In the present study, we compared gambling disorder patients against controls in an instrumental causal learning task. Evidence of illusion of control, namely, overestimation of the relationship between one's behavior and an uncorrelated outcome, showed up only in gamblers with strong current symptoms. Interestingly, this effect was part of a more complex pattern, in which gambling disorder patients manifested a poorer ability to discriminate between null and positive contingencies. Additionally, anomalies were related to gambling severity and current gambling disorder symptoms. Gambling-related biases, as measured by a standard psychometric tool, correlated with performance in the causal learning task, but not in the expected direction. Indeed, performance of gamblers with stronger biases tended to resemble the one of controls, which could imply that anomalies of causal learning processes play a role in gambling disorder, but do not seem to underlie gambling-specific biases, at least in a simple, direct way.
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Koenig, Stephan; Uengoer, Metin; Lachnit, Harald
2017-01-01
We conducted a human fear conditioning experiment in which three different color cues were followed by an aversive electric shock on 0, 50, and 100% of the trials, and thus induced low (L), partial (P), and high (H) shock expectancy, respectively. The cues differed with respect to the strength of their shock association (L H). During conditioning we measured pupil dilation and ocular fixations to index differences in the attentional processing of the cues. After conditioning, the shock-associated colors were introduced as irrelevant distracters during visual search for a shape target while shocks were no longer administered and we analyzed the cues’ potential to capture and hold overt attention automatically. Our findings suggest that fear conditioning creates an automatic attention bias for the conditioned cues that depends on their correlation with the aversive outcome. This bias was exclusively linked to the strength of the cues’ shock association for the early attentional processing of cues in the visual periphery, but additionally was influenced by the uncertainty of the shock prediction after participants fixated on the cues. These findings are in accord with attentional learning theories that formalize how associative learning shapes automatic attention. PMID:28588466
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Social inference and social anxiety: evidence of a fear-congruent self-referential learning bias.
Button, Katherine S; Browning, Michael; Munafò, Marcus R; Lewis, Glyn
2012-12-01
Fears of negative evaluation characterise social anxiety, and preferential processing of fear-relevant information is implicated in maintaining symptoms. Little is known, however, about the relationship between social anxiety and the process of inferring negative evaluation. The ability to use social information to learn what others think about one, referred to here as self-referential learning, is fundamental for effective social interaction. The aim of this research was to examine whether social anxiety is associated with self-referential learning. 102 Females with either high (n = 52) or low (n = 50) self-reported social anxiety completed a novel probabilistic social learning task. Using trial and error, the task required participants to learn two self-referential rules, 'I am liked' and 'I am disliked'. Participants across the sample were better at learning the positive rule 'I am liked' than the negative rule 'I am disliked', β = -6.4, 95% CI [-8.0, -4.7], p learning positive self-referential information was strongest in the lowest socially anxious and was abolished in the most symptomatic participants. Relative to the low group, the high anxiety group were better at learning they were disliked and worse at learning they were liked, social anxiety by rule interaction β = 3.6; 95% CI [+0.3, +7.0], p = 0.03. The specificity of the results to self-referential processing requires further research. Healthy individuals show a robust preference for learning that they are liked relative to disliked. This positive self-referential bias is reduced in social anxiety in a way that would be expected to exacerbate anxiety symptoms. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Palmer, John; Mohr, Christine; Krummenacher, Peter; Brugger, Peter
2007-06-01
Previous research suggests that implicit sequence learning (ISL) is superior for believers in the paranormal and individuals with increased cerebral dopamine. Thirty-five healthy participants performed feedback-guided anticipations of four arrow directions. A 100-trial random sequence preceded two 100-trial biased sequences in which visual targets (arrows) on trial t tended to be displaced 90 degrees clockwise (CW) or counter-clockwise (CCW) from those on t - 1. ISL was defined as a positive change during the course of the biased run in the difference between pro-bias and counter-bias responses. It was hypothesized that this difference would be greater for believers in the paranormal than for skeptics, for those who received dopamine than for those who received placebo, and for believers who received dopamine than for the other groups. None of the hypotheses were supported by the data. It is suggested that a simple binary guessing task with a focus on prediction accuracy during early trials should be considered for future explorations.
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Button, Katherine S; Kounali, Daphne; Stapinski, Lexine; Rapee, Ronald M; Lewis, Glyn; Munafò, Marcus R
2015-01-01
Fear of negative evaluation (FNE) defines social anxiety yet the process of inferring social evaluation, and its potential role in maintaining social anxiety, is poorly understood. We developed an instrumental learning task to model social evaluation learning, predicting that FNE would specifically bias learning about the self but not others. During six test blocks (3 self-referential, 3 other-referential), participants (n = 100) met six personas and selected a word from a positive/negative pair to finish their social evaluation sentences "I think [you are / George is]…". Feedback contingencies corresponded to 3 rules, liked, neutral and disliked, with P[positive word correct] = 0.8, 0.5 and 0.2, respectively. As FNE increased participants selected fewer positive words (β = -0.4, 95% CI -0.7, -0.2, p = 0.001), which was strongest in the self-referential condition (FNE × condition 0.28, 95% CI 0.01, 0.54, p = 0.04), and the neutral and dislike rules (FNE × condition × rule, p = 0.07). At low FNE the proportion of positive words selected for self-neutral and self-disliked greatly exceeded the feedback contingency, indicating poor learning, which improved as FNE increased. FNE is associated with differences in processing social-evaluative information specifically about the self. At low FNE this manifests as insensitivity to learning negative self-referential evaluation. High FNE individuals are equally sensitive to learning positive or negative evaluation, which although objectively more accurate, may have detrimental effects on mental health.
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Negative learning bias is associated with risk aversion in a genetic animal model of depression.
Shabel, Steven J; Murphy, Ryan T; Malinow, Roberto
2014-01-01
The lateral habenula (LHb) is activated by aversive stimuli and the omission of reward, inhibited by rewarding stimuli and is hyperactive in helpless rats-an animal model of depression. Here we test the hypothesis that congenital learned helpless (cLH) rats are more sensitive to decreases in reward size and/or less sensitive to increases in reward than wild-type (WT) control rats. Consistent with the hypothesis, we found that cLH rats were slower to switch preference between two responses after a small upshift in reward size on one of the responses but faster to switch their preference after a small downshift in reward size. cLH rats were also more risk-averse than WT rats-they chose a response delivering a constant amount of reward ("safe" response) more often than a response delivering a variable amount of reward ("risky" response) compared to WT rats. Interestingly, the level of bias toward negative events was associated with the rat's level of risk aversion when compared across individual rats. cLH rats also showed impaired appetitive Pavlovian conditioning but more accurate responding in a two-choice sensory discrimination task. These results are consistent with a negative learning bias and risk aversion in cLH rats, suggesting abnormal processing of rewarding and aversive events in the LHb of cLH rats.
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Directory of Open Access Journals (Sweden)
Stephan Koenig
2017-05-01
Full Text Available We conducted a human fear conditioning experiment in which three different color cues were followed by an aversive electric shock on 0, 50, and 100% of the trials, and thus induced low (L, partial (P, and high (H shock expectancy, respectively. The cues differed with respect to the strength of their shock association (L < P < H and the uncertainty of their prediction (L < P > H. During conditioning we measured pupil dilation and ocular fixations to index differences in the attentional processing of the cues. After conditioning, the shock-associated colors were introduced as irrelevant distracters during visual search for a shape target while shocks were no longer administered and we analyzed the cues’ potential to capture and hold overt attention automatically. Our findings suggest that fear conditioning creates an automatic attention bias for the conditioned cues that depends on their correlation with the aversive outcome. This bias was exclusively linked to the strength of the cues’ shock association for the early attentional processing of cues in the visual periphery, but additionally was influenced by the uncertainty of the shock prediction after participants fixated on the cues. These findings are in accord with attentional learning theories that formalize how associative learning shapes automatic attention.
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Developmental Changes in the Whole Number Bias
Braithwaite, David W.; Siegler, Robert S.
2018-01-01
Many students' knowledge of fractions is adversely affected by whole number bias, the tendency to focus on the separate whole number components (numerator and denominator) of a fraction rather than on the fraction's magnitude (ratio of numerator to denominator). Although whole number bias appears early in the fraction learning process and under…
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CMU DeepLens: deep learning for automatic image-based galaxy-galaxy strong lens finding
Lanusse, François; Ma, Quanbin; Li, Nan; Collett, Thomas E.; Li, Chun-Liang; Ravanbakhsh, Siamak; Mandelbaum, Rachel; Póczos, Barnabás
2018-01-01
Galaxy-scale strong gravitational lensing can not only provide a valuable probe of the dark matter distribution of massive galaxies, but also provide valuable cosmological constraints, either by studying the population of strong lenses or by measuring time delays in lensed quasars. Due to the rarity of galaxy-scale strongly lensed systems, fast and reliable automated lens finding methods will be essential in the era of large surveys such as Large Synoptic Survey Telescope, Euclid and Wide-Field Infrared Survey Telescope. To tackle this challenge, we introduce CMU DeepLens, a new fully automated galaxy-galaxy lens finding method based on deep learning. This supervised machine learning approach does not require any tuning after the training step which only requires realistic image simulations of strongly lensed systems. We train and validate our model on a set of 20 000 LSST-like mock observations including a range of lensed systems of various sizes and signal-to-noise ratios (S/N). We find on our simulated data set that for a rejection rate of non-lenses of 99 per cent, a completeness of 90 per cent can be achieved for lenses with Einstein radii larger than 1.4 arcsec and S/N larger than 20 on individual g-band LSST exposures. Finally, we emphasize the importance of realistically complex simulations for training such machine learning methods by demonstrating that the performance of models of significantly different complexities cannot be distinguished on simpler simulations. We make our code publicly available at https://github.com/McWilliamsCenter/CMUDeepLens.
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Gender bias and discrimination in nursing education: can we change it?
Anthony, Ann Strong
2004-01-01
Gender bias in nursing education impedes recruitment and retention of males into the profession. Nurse educators who are unaware of men's historical contributions to the profession may unknowingly perpetuate gender bias. The author describes how traditional stereotypes can be challenged and teaching/learning strategies can be customized to gender-driven learning styles.
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Li, S.; Rupp, D. E.; Hawkins, L.; Mote, P.; McNeall, D. J.; Sarah, S.; Wallom, D.; Betts, R. A.
2017-12-01
This study investigates the potential to reduce known summer hot/dry biases over Pacific Northwest in the UK Met Office's atmospheric model (HadAM3P) by simultaneously varying multiple model parameters. The bias-reduction process is done through a series of steps: 1) Generation of perturbed physics ensemble (PPE) through the volunteer computing network weather@home; 2) Using machine learning to train "cheap" and fast statistical emulators of climate model, to rule out regions of parameter spaces that lead to model variants that do not satisfy observational constraints, where the observational constraints (e.g., top-of-atmosphere energy flux, magnitude of annual temperature cycle, summer/winter temperature and precipitation) are introduced sequentially; 3) Designing a new PPE by "pre-filtering" using the emulator results. Steps 1) through 3) are repeated until results are considered to be satisfactory (3 times in our case). The process includes a sensitivity analysis to find dominant parameters for various model output metrics, which reduces the number of parameters to be perturbed with each new PPE. Relative to observational uncertainty, we achieve regional improvements without introducing large biases in other parts of the globe. Our results illustrate the potential of using machine learning to train cheap and fast statistical emulators of climate model, in combination with PPEs in systematic model improvement.
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Button, Katherine S.; Kounali, Daphne; Stapinski, Lexine; Rapee, Ronald M.; Lewis, Glyn; Munafò, Marcus R.
2015-01-01
Background Fear of negative evaluation (FNE) defines social anxiety yet the process of inferring social evaluation, and its potential role in maintaining social anxiety, is poorly understood. We developed an instrumental learning task to model social evaluation learning, predicting that FNE would specifically bias learning about the self but not others. Methods During six test blocks (3 self-referential, 3 other-referential), participants (n = 100) met six personas and selected a word from a positive/negative pair to finish their social evaluation sentences “I think [you are / George is]…”. Feedback contingencies corresponded to 3 rules, liked, neutral and disliked, with P[positive word correct] = 0.8, 0.5 and 0.2, respectively. Results As FNE increased participants selected fewer positive words (β = −0.4, 95% CI −0.7, −0.2, p = 0.001), which was strongest in the self-referential condition (FNE × condition 0.28, 95% CI 0.01, 0.54, p = 0.04), and the neutral and dislike rules (FNE × condition × rule, p = 0.07). At low FNE the proportion of positive words selected for self-neutral and self-disliked greatly exceeded the feedback contingency, indicating poor learning, which improved as FNE increased. Conclusions FNE is associated with differences in processing social-evaluative information specifically about the self. At low FNE this manifests as insensitivity to learning negative self-referential evaluation. High FNE individuals are equally sensitive to learning positive or negative evaluation, which although objectively more accurate, may have detrimental effects on mental health. PMID:25853835
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Minimum bias measurement at 13 TeV
Orlando, Nicola; The ATLAS collaboration
2017-01-01
The modelling of Minimum Bias (MB) is a crucial ingredient to learn about the description of soft QCD processes and to simulate the environment at the LHC with many concurrent pp interactions (pile-up). We summarise the ATLAS minimum bias measurements with proton-proton collision at 13 TeV center-of-mass-energy at the Large Hadron Collider.
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Conventional vs. e-learning in nursing education: A systematic review and meta-analysis.
Voutilainen, Ari; Saaranen, Terhi; Sormunen, Marjorita
2017-03-01
By and large, in health professions training, the direction of the effect of e-learning, positive or negative, strongly depends on the learning outcome in question as well as on learning methods which e-learning is compared to. In nursing education, meta-analytically generated knowledge regarding the comparisons between conventional and e-learning is scarce. The aim of this review is to discover the size of the effect of e-learning on learning outcomes in nursing education and to assess the quality of studies in which e-learning has been compared to conventional learning. A systematic search of six electronic databases, PubMed, Ovid MEDLINE®, CINAHL (EBSCOhost), Cochrane Library, PsycINFO, and ERIC, was conducted in order to identify relevant peer-reviewed English language articles published between 2011 and 2015. The quality of the studies included as well as the risk of bias in each study was assessed. A random-effects meta-analysis was performed to generate a pooled mean difference in the learning outcome. Altogether, 10 studies were eligible for the quality assessment and meta-analysis. Nine studies were evaluated as good quality studies, but not without a risk of bias. Performance bias caused a high risk in nearly all the studies. In the meta-analysis, an e-learning method resulted in test scores that were, on average, five points higher than a conventional method on a 0-100 scale. Heterogeneity between the studies was very large. The size and direction of the effect of a learning method on learning outcomes appeared to be strongly situational. We suggest that meta-regressions should be performed instead of basic meta-analyses in order to reveal factors that cause variation in the learning outcomes of nursing education. It might be necessary to perform separate meta-analyses between e-learning interventions aimed at improving nursing knowledge and those aimed at improving nursing skills. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Symmetry as Bias: Rediscovering Special Relativity
Lowry, Michael R.
1992-01-01
This paper describes a rational reconstruction of Einstein's discovery of special relativity, validated through an implementation: the Erlanger program. Einstein's discovery of special relativity revolutionized both the content of physics and the research strategy used by theoretical physicists. This research strategy entails a mutual bootstrapping process between a hypothesis space for biases, defined through different postulated symmetries of the universe, and a hypothesis space for physical theories. The invariance principle mutually constrains these two spaces. The invariance principle enables detecting when an evolving physical theory becomes inconsistent with its bias, and also when the biases for theories describing different phenomena are inconsistent. Structural properties of the invariance principle facilitate generating a new bias when an inconsistency is detected. After a new bias is generated. this principle facilitates reformulating the old, inconsistent theory by treating the latter as a limiting approximation. The structural properties of the invariance principle can be suitably generalized to other types of biases to enable primal-dual learning.
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Annuschka Salima Eden; Annuschka Salima Eden; Vera eDehmelt; Vera eDehmelt; Matthias eBischoff; Pienie eZwitserlood; Harald eKugel; Kati eKeuper; Peter eZwanzger; Christian eDobel; Christian eDobel; Christian eDobel
2015-01-01
Persons suffering from anxiety disorders display facilitated processing of arousing and negative stimuli, such as negative words. This memory bias is reflected in better recall and increased amygdala activity in response to such stimuli. However, individual learning histories were not considered in most studies, a concern that we meet here. Thirty-four female persons (half with high-, half with low trait anxiety) participated in a criterion-based associative word-learning paradigm, in which n...
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Eden, Annuschka S.; Dehmelt, Vera; Bischoff, Matthias; Zwitserlood, Pienie; Kugel, Harald; Keuper, Kati; Zwanzger, Peter; Dobel, Christian
2015-01-01
Persons suffering from anxiety disorders display facilitated processing of arousing and negative stimuli, such as negative words. This memory bias is reflected in better recall and increased amygdala activity in response to such stimuli. However, individual learning histories were not considered in most studies, a concern that we meet here. Thirty-four female persons (half with high-, half with low trait anxiety) participated in a criterion-based associative word-learning paradigm, in which n...
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Revealing the Cosmic Web-dependent Halo Bias
Yang, Xiaohu; Zhang, Youcai; Lu, Tianhuan; Wang, Huiyuan; Shi, Feng; Tweed, Dylan; Li, Shijie; Luo, Wentao; Lu, Yi; Yang, Lei
2017-10-01
Halo bias is the one of the key ingredients of the halo models. It was shown at a given redshift to be only dependent, to the first order, on the halo mass. In this study, four types of cosmic web environments—clusters, filaments, sheets, and voids—are defined within a state-of-the-art high-resolution N-body simulation. Within these environments, we use both halo-dark matter cross correlation and halo-halo autocorrelation functions to probe the clustering properties of halos. The nature of the halo bias differs strongly between the four different cosmic web environments described here. With respect to the overall population, halos in clusters have significantly lower biases in the {10}11.0˜ {10}13.5 {h}-1 {M}⊙ mass range. In other environments, however, halos show extremely enhanced biases up to a factor 10 in voids for halos of mass ˜ {10}12.0 {h}-1 {M}⊙ . Such a strong cosmic web environment dependence in the halo bias may play an important role in future cosmological and galaxy formation studies. Within this cosmic web framework, the age dependency of halo bias is found to be only significant in clusters and filaments for relatively small halos ≲ {10}12.5 {h}-1 {M}⊙ .
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Affective bias as a rational response to the statistics of rewards and punishments.
Pulcu, Erdem; Browning, Michael
2017-10-04
Affective bias, the tendency to differentially prioritise the processing of negative relative to positive events, is commonly observed in clinical and non-clinical populations. However, why such biases develop is not known. Using a computational framework, we investigated whether affective biases may reflect individuals' estimates of the information content of negative relative to positive events. During a reinforcement learning task, the information content of positive and negative outcomes was manipulated independently by varying the volatility of their occurrence. Human participants altered the learning rates used for the outcomes selectively, preferentially learning from the most informative. This behaviour was associated with activity of the central norepinephrine system, estimated using pupilometry, for loss outcomes. Humans maintain independent estimates of the information content of distinct positive and negative outcomes which may bias their processing of affective events. Normalising affective biases using computationally inspired interventions may represent a novel approach to treatment development.
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Bias-Free Chemically Diverse Test Sets from Machine Learning.
Swann, Ellen T; Fernandez, Michael; Coote, Michelle L; Barnard, Amanda S
2017-08-14
Current benchmarking methods in quantum chemistry rely on databases that are built using a chemist's intuition. It is not fully understood how diverse or representative these databases truly are. Multivariate statistical techniques like archetypal analysis and K-means clustering have previously been used to summarize large sets of nanoparticles however molecules are more diverse and not as easily characterized by descriptors. In this work, we compare three sets of descriptors based on the one-, two-, and three-dimensional structure of a molecule. Using data from the NIST Computational Chemistry Comparison and Benchmark Database and machine learning techniques, we demonstrate the functional relationship between these structural descriptors and the electronic energy of molecules. Archetypes and prototypes found with topological or Coulomb matrix descriptors can be used to identify smaller, statistically significant test sets that better capture the diversity of chemical space. We apply this same method to find a diverse subset of organic molecules to demonstrate how the methods can easily be reapplied to individual research projects. Finally, we use our bias-free test sets to assess the performance of density functional theory and quantum Monte Carlo methods.
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Individuals With OCD Lack Unrealistic Optimism Bias in Threat Estimation.
Zetsche, Ulrike; Rief, Winfried; Exner, Cornelia
2015-07-01
Overestimating the occurrence of threatening events has been highlighted as a central cognitive factor in the maintenance of obsessive-compulsive disorder (OCD). The present study examined the different facets of this cognitive bias, its underlying mechanisms, and its specificity to OCD. For this purpose, threat estimation, probabilistic classification learning (PCL) and psychopathological measures were assessed in 23 participants with OCD, 30 participants with social phobia, and 31 healthy controls. Whereas healthy participants showed an optimistic expectation bias regarding positive and negative future events, OCD participants lacked such a bias. This lack of an optimistic expectation bias was not specific to OCD. Compared to healthy controls, OCD participants overestimated their personal risk for experiencing negative events, but did not differ from controls in their risk estimation regarding other people. Finally, OCD participants' biases in the prediction of checking-related events were associated with their impairments in learning probabilistic cue-outcome associations in a disorder-relevant context. In sum, the present results add to a growing body of research demonstrating that cognitive biases in OCD are context-dependent. Copyright © 2015. Published by Elsevier Ltd.
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Biased Competition in Visual Processing Hierarchies: A Learning Approach Using Multiple Cues.
Gepperth, Alexander R T; Rebhan, Sven; Hasler, Stephan; Fritsch, Jannik
2011-03-01
In this contribution, we present a large-scale hierarchical system for object detection fusing bottom-up (signal-driven) processing results with top-down (model or task-driven) attentional modulation. Specifically, we focus on the question of how the autonomous learning of invariant models can be embedded into a performing system and how such models can be used to define object-specific attentional modulation signals. Our system implements bi-directional data flow in a processing hierarchy. The bottom-up data flow proceeds from a preprocessing level to the hypothesis level where object hypotheses created by exhaustive object detection algorithms are represented in a roughly retinotopic way. A competitive selection mechanism is used to determine the most confident hypotheses, which are used on the system level to train multimodal models that link object identity to invariant hypothesis properties. The top-down data flow originates at the system level, where the trained multimodal models are used to obtain space- and feature-based attentional modulation signals, providing biases for the competitive selection process at the hypothesis level. This results in object-specific hypothesis facilitation/suppression in certain image regions which we show to be applicable to different object detection mechanisms. In order to demonstrate the benefits of this approach, we apply the system to the detection of cars in a variety of challenging traffic videos. Evaluating our approach on a publicly available dataset containing approximately 3,500 annotated video images from more than 1 h of driving, we can show strong increases in performance and generalization when compared to object detection in isolation. Furthermore, we compare our results to a late hypothesis rejection approach, showing that early coupling of top-down and bottom-up information is a favorable approach especially when processing resources are constrained.
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Sequence-specific bias correction for RNA-seq data using recurrent neural networks.
Zhang, Yao-Zhong; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru
2017-01-25
The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures. The sequence-specific bias of a read is then calculated based on the sequence probabilities estimated by RNNs, and used in the estimation of gene abundance. We explore the application of two popular RNN recurrent units for this task and demonstrate that RNN-based approaches provide a flexible way to model nucleotide sequences without knowledge of predetermined sequence structures. Our experiments show that training a RNN-based nucleotide sequence model is efficient and RNN-based bias correction methods compare well with the-state-of-the-art sequence-specific bias correction method on the commonly used MAQC-III data set. RNNs provides an alternative and flexible way to calculate sequence-specific bias without explicitly pre-determining sequence structures.
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Study of the Dependency on Magnetic Field and Bias Voltage of an AC-Biased TES Microcalorimeter
Gottardi, L.; Bruijn, M.; denHartog, R.; Hoevers, H.; deKorte, P.; vanderKuur, J.; Linderman, M.; Adams, J.; Bailey, C.; Bandler, S.;
2012-01-01
At SRON we are studying the performance of a Goddard Space Flight Center single pixel TES microcalorimeter operated in an AC bias configuration. For x-ray photons at 6 keV the pixel shows an x-ray energy resolution Delta E(sub FWHM) = 3.7 eV, which is about a factor 2 worse than the energy resolution observed in an identical DC-biased pixel. In order to better understand the reasons for this discrepancy we characterized the detector as a function of temperature, bias working point and applied perpendicular magnetic field. A strong periodic dependency of the detector noise on the TES AC bias voltage is measured. We discuss the results in the framework of the recently observed weak-link behaviour of a TES microcalorimeter.
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Noise Induces Biased Estimation of the Correction Gain.
Directory of Open Access Journals (Sweden)
Jooeun Ahn
Full Text Available The detection of an error in the motor output and the correction in the next movement are critical components of any form of motor learning. Accordingly, a variety of iterative learning models have assumed that a fraction of the error is adjusted in the next trial. This critical fraction, the correction gain, learning rate, or feedback gain, has been frequently estimated via least-square regression of the obtained data set. Such data contain not only the inevitable noise from motor execution, but also noise from measurement. It is generally assumed that this noise averages out with large data sets and does not affect the parameter estimation. This study demonstrates that this is not the case and that in the presence of noise the conventional estimate of the correction gain has a significant bias, even with the simplest model. Furthermore, this bias does not decrease with increasing length of the data set. This study reveals this limitation of current system identification methods and proposes a new method that overcomes this limitation. We derive an analytical form of the bias from a simple regression method (Yule-Walker and develop an improved identification method. This bias is discussed as one of other examples for how the dynamics of noise can introduce significant distortions in data analysis.
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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
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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.
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Consider the category: The effect of spacing depends on individual learning histories.
Slone, Lauren K; Sandhofer, Catherine M
2017-07-01
The spacing effect refers to increased retention following learning instances that are spaced out in time compared with massed together in time. By one account, the advantages of spaced learning should be independent of task particulars and previous learning experiences given that spacing effects have been demonstrated in a variety of tasks across the lifespan. However, by another account, spaced learning should be affected by previous learning because past learning affects the memory and attention processes that form the crux of the spacing effect. The current study investigated whether individuals' learning histories affect the role of spacing in category learning. We examined the effect of spacing on 24 2- to 3.5-year-old children's learning of categories organized by properties to which children's previous learning experiences have biased them to attend (i.e., shape) and properties to which children are less biased to attend (i.e., texture and color). Spaced presentations led to significantly better learning of shape categories, but not of texture or color categories, compared with massed presentations. In addition, generalized estimating equations analyses revealed positive relations between the size of children's "shape-side" productive vocabularies and their shape category learning and between the size of children's "against-the-system" productive vocabularies and their texture category learning. These results suggest that children's attention to and memory for novel object categories are strongly related to their individual word-learning histories. Moreover, children's learned attentional biases affected the types of categories for which spacing facilitated learning. These findings highlight the importance of considering how learners' previous experiences may influence future learning. Copyright © 2017 Elsevier Inc. All rights reserved.
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Moral empiricism and the bias for act-based rules.
Ayars, Alisabeth; Nichols, Shaun
2017-10-01
Previous studies on rule learning show a bias in favor of act-based rules, which prohibit intentionally producing an outcome but not merely allowing the outcome. Nichols, Kumar, Lopez, Ayars, and Chan (2016) found that exposure to a single sample violation in which an agent intentionally causes the outcome was sufficient for participants to infer that the rule was act-based. One explanation is that people have an innate bias to think rules are act-based. We suggest an alternative empiricist account: since most rules that people learn are act-based, people form an overhypothesis (Goodman, 1955) that rules are typically act-based. We report three studies that indicate that people can use information about violations to form overhypotheses about rules. In study 1, participants learned either three "consequence-based" rules that prohibited allowing an outcome or three "act-based" rules that prohibiting producing the outcome; in a subsequent learning task, we found that participants who had learned three consequence-based rules were more likely to think that the new rule prohibited allowing an outcome. In study 2, we presented participants with either 1 consequence-based rule or 3 consequence-based rules, and we found that those exposed to 3 such rules were more likely to think that a new rule was also consequence based. Thus, in both studies, it seems that learning 3 consequence-based rules generates an overhypothesis to expect new rules to be consequence-based. In a final study, we used a more subtle manipulation. We exposed participants to examples act-based or accident-based (strict liability) laws and then had them learn a novel rule. We found that participants who were exposed to the accident-based laws were more likely to think a new rule was accident-based. The fact that participants' bias for act-based rules can be shaped by evidence from other rules supports the idea that the bias for act-based rules might be acquired as an overhypothesis from the
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Health risk perception, optimistic bias, and personal satisfaction.
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.
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Social biases modulate the loss of redundant forms in the cultural evolution of language.
Roberts, Gareth; Fedzechkina, Maryia
2018-02-01
According to the competitive exclusion principle (Gause, 1934), competition for the same niche must eventually lead one competitor to extinction or the occupation of a new niche. This principle applies in both biology and the cultural evolution of language, where different words and structures compete for the same function or meaning (Aronoff, 2016). Across languages, for example, word order trades off with case marking as a means of indicating who did what to whom in a sentence. Previous experimental work has shed light on how such trade-offs come about as languages adapt to human biases through learning and production, with biases becoming amplified through iterated learning over generations. At the same time, a large body of work has documented the impact of social biases on language change. However, little work has investigated how social biases interact with learning and production biases. In particular, the social dimension of language may provide alternative niches for otherwise redundant forms, preventing or slowing their extinction. We tested this hypothesis in an iterated-learning experiment in which participants were exposed to a language with two dialects, both of which had fixed word order, but differed in whether they employed case markers. In one condition, we biased participants socially towards speakers of the dialect that employed case; in other conditions we provided no bias, or biased participants for or against the dialect without case. As expected under our hypothesis, the use of case markers declined over time in all conditions, but the social bias in favor of case-dialect speakers slowed the decline. Copyright © 2017 Elsevier B.V. All rights reserved.
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A pupillary index of susceptibility to decision biases
Eldar, Eran; Felso, Valkyrie; Cohen, Jonathan; Niv, Yael
2018-01-01
Under what conditions do humans systematically deviate from rational decision making? Here we show that pupillary indices of low neural gain are associated with strong and consistent biases across six different extensively-studied decision making tasks, whereas indices of high gain are associated with weak or absent biases. Lower susceptibility to biases, however, comes at the cost of indecisiveness, or alternatively, prolonged deliberation time. We explain the association between low gain an...
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An Investigation of Human Inductive Biases in Causality and Probability Judgments
Yeung, Sai Wing
2011-01-01
People often makes inductive inferences that go beyond the data that are given. In order to generate these inferences, people must rely on inductive biases - constraints on learning that guide conclusion from limited data. This thesis presents a survey of three topics concerning people's inductive biases.The first part of this thesis examines people's expectations about the strengths of causes in elemental causal induction - learning about the relationship between a single cause and effect. T...
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Reducing status quo bias in choice experiments
DEFF Research Database (Denmark)
Bonnichsen, Ole; Ladenburg, Jacob
In stated preference literature, the tendency to choose the alternative representing the status quo situation seems to exceed real life status quo effects. Accordingly, status quo bias can be a problem. In Choice Experiments, status quo bias is found to be strongly correlated with protest attitudes...... toward the cost attribute. If economic values are to be elicited, this problem is difficult to remedy. In a split sample framework we test a novel ex-ante entreaty aimed specifically at the cost attribute and find that it effectively reduces status quo bias and improves the internal validity...
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Understanding and Overcoming Implicit Gender Bias in Plastic Surgery.
Phillips, Nicole A; Tannan, Shruti C; Kalliainen, Loree K
2016-11-01
Although explicit sex-based discrimination has largely been deemed unacceptable in professional settings, implicit gender bias persists and results in a significant lack of parity in plastic surgery and beyond. Implicit gender bias is the result of a complex interplay of cultural and societal expectations, learned behaviors, and standardized associations. As such, both male and female surgeons are subject to its influence. A review of the literature was conducted, examining theories of gender bias, current manifestations of gender bias in plastic surgery and other fields, and interventions designed to address gender bias. Multiple studies demonstrate persistent gender bias that impacts female physicians at all levels of training. Several institutions have enacted successful interventions to identify and address gender bias. Explicit gender bias has largely disappeared, yet unconscious or implicit gender bias persists. A wide-scale commitment to addressing implicit gender bias in plastic surgery is necessary and overdue. Recommendations include immediate actions that can be undertaken on an individual basis, and changes that should be implemented at a national and international level by leaders in the field.
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Testing strong factorial invariance using three-level structural equation modeling
Jak, Suzanne
Within structural equation modeling, the most prevalent model to investigate measurement bias is the multigroup model. Equal factor loadings and intercepts across groups in a multigroup model represent strong factorial invariance (absence of measurement bias) across groups. Although this approach is
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Rodríguez-Quiñonez, J. C.; Sergiyenko, O.; Hernandez-Balbuena, D.; Rivas-Lopez, M.; Flores-Fuentes, W.; Basaca-Preciado, L. C.
2014-12-01
Many laser scanners depend on their mechanical construction to guarantee their measurements accuracy, however, the current computational technologies allow us to improve these measurements by mathematical methods implemented in neural networks. In this article we are going to introduce the current laser scanner technologies, give a description of our 3D laser scanner and adjust their measurement error by a previously trained feed forward back propagation (FFBP) neural network with a Widrow-Hoff weight/bias learning function. A comparative analysis with other learning functions such as the Kohonen algorithm and gradient descendent with momentum algorithm is presented. Finally, computational simulations are conducted to verify the performance and method uncertainty in the proposed system.
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Vicarious learning of children's social-anxiety-related fear beliefs and emotional Stroop bias.
Askew, Chris; Hagel, Anna; Morgan, Julie
2015-08-01
Models of social anxiety suggest that negative social experiences contribute to the development of social anxiety, and this is supported by self-report research. However, there is relatively little experimental evidence for the effects of learning experiences on social cognitions. The current study examined the effect of observing a social performance situation with a negative outcome on children's (8 to 11 years old) fear-related beliefs and cognitive processing. Two groups of children were each shown 1 of 2 animated films of a person trying to score in basketball while being observed by others; in 1 film, the outcome was negative, and in the other, it was neutral. Children's fear-related beliefs about performing in front of others were measured before and after the film and children were asked to complete an emotional Stroop task. Results showed that social fear beliefs increased for children who saw the negative social performance film. In addition, these children showed an emotional Stroop bias for social-anxiety-related words compared to children who saw the neutral film. The findings have implications for our understanding of social anxiety disorder and suggest that vicarious learning experiences in childhood may contribute to the development of social anxiety. (c) 2015 APA, all rights reserved).
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Lender, A.; Meule, A.; Rinck, M.; Brockmeyer, T.; Blechert, J.
2018-01-01
Strong implicit responses to food have evolved to avoid energy depletion but contribute to overeating in today's affluent environments. The Approach-Avoidance Task (AAT) supposedly assesses implicit biases in response to food stimuli: Participants push pictures on a monitor "away" or pull them
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An SIS model for cultural trait transmission with conformity bias.
Walters, Caroline E; Kendal, Jeremy R
2013-12-01
Epidemiological models have been applied to human health-related behaviors that are affected by social interaction. Typically these models have not considered conformity bias, that is, the exaggerated propensity to adopt commonly observed behaviors or opinions, or content biases, where the content of the learned trait affects the probability of adoption. Here we consider an interaction of these two effects, presenting an SIS-type model for the spread and persistence of a behavior which is transmitted via social learning. Uptake is controlled by a nonlinear dependence on the proportion of individuals demonstrating the behavior in a population. Three equilibrium solutions are found, their linear stability is analyzed and the results are compared with a model for unbiased social learning. Our analysis focuses on the effects of the strength of conformity bias and the effects of content biases which alter a conformity threshold frequency of the behavior, above which there is an exaggerated propensity for adoption. The strength of the conformity bias is found to qualitatively alter the predictions regarding whether the trait becomes endemic within the population and the proportion of individuals who display the trait when it is endemic. As the conformity strength increases, the number of feasible equilibrium solutions increases from two to three, leading to a situation where the stable equilibrium attained is dependent upon the initial state. Varying the conformity threshold frequency directionally alters the behavior invasion threshold. Finally we discuss the possible application of this model to binge drinking behavior. Copyright © 2013 Elsevier Inc. All rights reserved.
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Thygesen, Uffe Høgsbro
2016-03-01
We consider organisms which use a renewal strategy such as run-tumble when moving in space, for example to perform chemotaxis in chemical gradients. We derive a diffusion approximation for the motion, applying a central limit theorem due to Anscombe for renewal-reward processes; this theorem has not previously been applied in this context. Our results extend previous work, which has established the mean drift but not the diffusivity. For a classical model of tumble rates applied to chemotaxis, we find that the resulting chemotactic drift saturates to the swimming velocity of the organism when the chemical gradients grow increasingly steep. The dispersal becomes anisotropic in steep gradients, with larger dispersal across the gradient than along the gradient. In contrast to one-dimensional settings, strong bias increases dispersal. We next include Brownian rotation in the model and find that, in limit of high chemotactic sensitivity, the chemotactic drift is 64% of the swimming velocity, independent of the magnitude of the Brownian rotation. We finally derive characteristic timescales of the motion that can be used to assess whether the diffusion limit is justified in a given situation. The proposed technique for obtaining diffusion approximations is conceptually and computationally simple, and applicable also when statistics of the motion is obtained empirically or through Monte Carlo simulation of the motion.
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Bias against research on gender bias.
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.
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Huffman, Michael A; Spiezio, Caterina; Sgaravatti, Andrea; Leca, Jean-Baptiste
2010-11-01
Demonstrating the ability to 'copy' the behavior of others is an important aspect in determining whether social learning occurs and whether group level differences in a given behavior represent cultural differences or not. Understanding the occurrence of this process in its natural context is essential, but can be a daunting task in the wild. In order to test the social learning hypothesis for the acquisition of leaf swallowing (LS), a self-medicative behavior associated with the expulsion of parasites, we conducted semi-naturalistic experiments on two captive groups of parasite-free, naïve chimpanzees (Pan troglodytes). Individuals in the group were systematically provided appropriate stimuli (rough hispid leaves) identical to those used by chimpanzees in the wild. Individuals initially responded in a variety of ways, ranging from total aversion to normal chewing and swallowing. Over time, however, the two groups adopted different variants for inserting and folding the leaves in the mouth prior to swallowing them (complete and partial LS), following the specific method spontaneously displayed by the first and primary LS models in their respective groups. These variants were similar to LS displayed by chimpanzees in the wild. Using the option-bias method, we found evidence for social learning leading to group-level biased transmission and group-level stabilization of these two variants. This is the first report on two distinct cultural variants innovated in response to the introduction of natural stimuli that emerged and spread spontaneously and concurrently within two adjacent groups of socially housed primates. These observations support the assertion that LS may reflect a generalized propensity for ingesting rough hispid leaves, which can be socially induced and transmitted within a group. Ingesting an adequate number of these leaves induces increased gut motility, which is responsible for the subsequent expulsion of particular parasite species in the wild
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Zaman, Jonas; Madden, Victoria J; Iven, Julie; Wiech, Katja; Weltens, Nathalie; Ly, Huynh Giao; Vlaeyen, Johan W S; Van Oudenhove, Lukas; Van Diest, Ilse
2017-10-01
A growing body of research has identified fear of visceral sensations as a potential mechanism in the development and maintenance of visceral pain disorders. However, the extent to which such learned fear affects visceroception remains unclear. To address this question, we used a differential fear conditioning paradigm with nonpainful esophageal balloon distensions of 2 different intensities as conditioning stimuli (CSs). The experiment comprised of preacquisition, acquisition, and postacquisition phases during which participants categorized the CSs with respect to their intensity. The CS+ was always followed by a painful electrical stimulus (unconditioned stimulus) during the acquisition phase and in 60% of the trials during postacquisition. The second stimulus (CS-) was never associated with pain. Analyses of galvanic skin and startle eyeblink responses as physiological markers of successful conditioning showed increased fear responses to the CS+ compared with the CS-, but only in the group with the low-intensity stimulus as CS+. Computational modeling of response times and response accuracies revealed that differential fear learning affected perceptual decision-making about the intensities of visceral sensations such that sensations were more likely to be categorized as more intense. These results suggest that associative learning might indeed contribute to visceral hypersensitivity in functional gastrointestinal disorders. This study shows that associative fear learning biases intensity judgements of visceral sensations toward perceiving such sensations as more intense. Learning-induced alterations in visceroception might therefore contribute to the development or maintenance of visceral pain. Copyright © 2017 American Pain Society. Published by Elsevier Inc. All rights reserved.
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Lazarov, Amit; Abend, Rany; Seidner, Shiran; Pine, Daniel S; Bar-Haim, Yair
2017-09-01
Current attention bias modification (ABM) procedures are designed to implicitly train attention away from threatening stimuli with the hope of reducing stress reactivity and anxiety symptoms. However, the mechanisms underlying effective ABM delivery are not well understood, with awareness of the training contingency suggested as one possible factor contributing to ABM efficacy. Here, 45 high-anxious participants were trained to divert attention away from threat in two ABM sessions. They were randomly assigned to one of three training protocols: an implicit protocol, comprising two standard implicit ABM training sessions; an explicit protocol, comprising two sessions with explicit instruction as to the attention training contingency; and an implicit-explicit protocol, in which participants were not informed of the training contingency in the first ABM session and informed of it at the start of the second session. We examined learning processes and stress reactivity following a stress-induction task. Results indicate that relative to implicit instructions, explicit instructions led to stronger learning during the first training session. Following rest, the explicit and implicit groups exhibited consolidation-related improvement in performance, whereas no such improvement was noted for the implicit-explicit group. Finally, although stress reactivity was reduced after training, contingency awareness did not yield a differential effect on stress reactivity measured using both self-reports and skin conductance, within and across sessions. These results suggest that explicit ABM administration leads to greater initial learning during the training protocol while not differing from standard implicit administration in terms of off-line learning and stress reactivity. Copyright © 2017. Published by Elsevier Ltd.
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Declining Bias and Gender Wage Discrimination? A Meta-Regression Analysis
Jarrell, Stephen B.; Stanley, T. D.
2004-01-01
The meta-regression analysis reveals that there is a strong tendency for discrimination estimates to fall and wage discrimination exist against the woman. The biasing effect of researchers' gender of not correcting for selection bias has weakened and changes in labor market have made it less important.
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Mismeasurement and the resonance of strong confounders: uncorrelated errors.
Marshall, J R; Hastrup, J L
1996-05-15
Greenland first documented (Am J Epidemiol 1980; 112:564-9) that error in the measurement of a confounder could resonate--that it could bias estimates of other study variables, and that the bias could persist even with statistical adjustment for the confounder as measured. An important question is raised by this finding: can such bias be more than trivial within the bounds of realistic data configurations? The authors examine several situations involving dichotomous and continuous data in which a confounder and a null variable are measured with error, and they assess the extent of resultant bias in estimates of the effect of the null variable. They show that, with continuous variables, measurement error amounting to 40% of observed variance in the confounder could cause the observed impact of the null study variable to appear to alter risk by as much as 30%. Similarly, they show, with dichotomous independent variables, that 15% measurement error in the form of misclassification could lead the null study variable to appear to alter risk by as much as 50%. Such bias would result only from strong confounding. Measurement error would obscure the evidence that strong confounding is a likely problem. These results support the need for every epidemiologic inquiry to include evaluations of measurement error in each variable considered.
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Non-Gaussian halo assembly bias
International Nuclear Information System (INIS)
Reid, Beth A.; Verde, Licia; Dolag, Klaus; Matarrese, Sabino; Moscardini, Lauro
2010-01-01
The strong dependence of the large-scale dark matter halo bias on the (local) non-Gaussianity parameter, f NL , offers a promising avenue towards constraining primordial non-Gaussianity with large-scale structure surveys. In this paper, we present the first detection of the dependence of the non-Gaussian halo bias on halo formation history using N-body simulations. We also present an analytic derivation of the expected signal based on the extended Press-Schechter formalism. In excellent agreement with our analytic prediction, we find that the halo formation history-dependent contribution to the non-Gaussian halo bias (which we call non-Gaussian halo assembly bias) can be factorized in a form approximately independent of redshift and halo mass. The correction to the non-Gaussian halo bias due to the halo formation history can be as large as 100%, with a suppression of the signal for recently formed halos and enhancement for old halos. This could in principle be a problem for realistic galaxy surveys if observational selection effects were to pick galaxies occupying only recently formed halos. Current semi-analytic galaxy formation models, for example, imply an enhancement in the expected signal of ∼ 23% and ∼ 48% for galaxies at z = 1 selected by stellar mass and star formation rate, respectively
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Cognitive bias in symptomatic and recovered agoraphobics.
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.
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Tan, Amanda W Y; Hemelrijk, Charlotte K; Malaivijitnond, Suchinda; Gumert, Michael D
2018-05-12
Examining how animals direct social learning during skill acquisition under natural conditions, generates data for examining hypotheses regarding how transmission biases influence cultural change in animal populations. We studied a population of macaques on Koram Island, Thailand, and examined model-based biases during interactions by unskilled individuals with tool-using group members. We first compared the prevalence of interactions (watching, obtaining food, object exploration) and proximity to tool users during interactions, in developing individuals (infants, juveniles) versus mature non-learners (adolescents, adults), to provide evidence that developing individuals are actively seeking information about tool use from social partners. All infants and juveniles, but only 49% of mature individuals carried out interacted with tool users. Macaques predominantly obtained food by scrounging or stealing, suggesting maximizing scrounging opportunities motivates interactions with tool users. However, while interactions by adults was limited to obtaining food, young macaques and particularly infants also watched tool users and explored objects, indicating additional interest in tool use itself. We then ran matrix correlations to identify interaction biases, and what attributes of tool users influenced these. Biases correlated with social affiliation, but macaques also preferentially targeted tool users that potentially increase scrounging and learning opportunities. Results suggest that social structure may constrain social learning, but the motivation to bias interactions towards tool users to maximize feeding opportunities may also socially modulate learning by facilitating close proximity to better tool users, and further interest in tool-use actions and materials, especially during development.
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Harrison, Sarah J; Backus, Benjamin T; Jain, Anshul
2011-05-11
The apparent direction of rotation of perceptually bistable wire-frame (Necker) cubes can be conditioned to depend on retinal location by interleaving their presentation with cubes that are disambiguated by depth cues (Haijiang, Saunders, Stone, & Backus, 2006; Harrison & Backus, 2010a). The long-term nature of the learned bias is demonstrated by resistance to counter-conditioning on a consecutive day. In previous work, either binocular disparity and occlusion, or a combination of monocular depth cues that included occlusion, internal occlusion, haze, and depth-from-shading, were used to control the rotation direction of disambiguated cubes. Here, we test the relative effectiveness of these two sets of depth cues in establishing the retinal location bias. Both cue sets were highly effective in establishing a perceptual bias on Day 1 as measured by the perceived rotation direction of ambiguous cubes. The effect of counter-conditioning on Day 2, on perceptual outcome for ambiguous cubes, was independent of whether the cue set was the same or different as Day 1. This invariance suggests that a common neural population instantiates the bias for rotation direction, regardless of the cue set used. However, in a further experiment where only disambiguated cubes were presented on Day 1, perceptual outcome of ambiguous cubes during Day 2 counter-conditioning showed that the monocular-only cue set was in fact more effective than disparity-plus-occlusion for causing long-term learning of the bias. These results can be reconciled if the conditioning effect of Day 1 ambiguous trials in the first experiment is taken into account (Harrison & Backus, 2010b). We suggest that monocular disambiguation leads to stronger bias either because it more strongly activates a single neural population that is necessary for perceiving rotation, or because ambiguous stimuli engage cortical areas that are also engaged by monocularly disambiguated stimuli but not by disparity-disambiguated stimuli
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Evaluation of color preference in zebrafish for learning and memory.
Avdesh, Avdesh; Martin-Iverson, Mathew T; Mondal, Alinda; Chen, Mengqi; Askraba, Sreten; Morgan, Newman; Lardelli, Michael; Groth, David M; Verdile, Giuseppe; Martins, Ralph N
2012-01-01
There is growing interest in using zebrafish (Danio rerio) as a model of neurodegenerative disorders such as Alzheimer's disease. A zebrafish model of tauopathies has recently been developed and characterized in terms of presence of the pathological hallmarks (i.e., neurofibrillary tangles and cell death). However, it is also necessary to validate these models for function by assessing learning and memory. The majority of tools to assess memory and learning in animal models involve visual stimuli, including color preference. The color preference of zebrafish has received little attention. To validate zebrafish as a model for color-associated-learning and memory, it is necessary to evaluate its natural preferences or any pre-existing biases towards specific colors. In the present study, we have used four different colors (red, yellow, green, and blue) to test natural color preferences of the zebrafish using two procedures: Place preference and T-maze. Results from both experiments indicate a strong aversion toward blue color relative to all other colors (red, yellow, and green) when tested in combinations. No preferences or biases were found among reds, yellows, and greens in the place preference procedure. However, red and green were equally preferred and both were preferred over yellow by zebrafish in the T-maze procedure. The results from the present study show a strong aversion towards blue color compared to red, green, and yellow, with yellow being less preferred relative to red and green. The findings from this study may underpin any further designing of color-based learning and memory paradigms or experiments involving aversion, anxiety, or fear in the zebrafish.
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Liu, Chuanjun; Xiao, Chengli
2018-01-01
The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one.
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Directory of Open Access Journals (Sweden)
Chuanjun Liu
2018-02-01
Full Text Available The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one.
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Genesis and Maintenance of Attentional Biases: The Role of the Locus Coeruleus-Noradrenaline System
Directory of Open Access Journals (Sweden)
Mana R. Ehlers
2017-01-01
Full Text Available Emotionally arousing events are typically better remembered than mundane ones, in part because emotionally relevant aspects of our environment are prioritized in attention. Such biased attentional tuning is itself the result of associative processes through which we learn affective and motivational relevance of cues. We propose that the locus coeruleus-noradrenaline (LC-NA system plays an important role in the genesis of attentional biases through associative learning processes as well as their maintenance. We further propose that individual differences in and disruptions of the LC-NA system underlie the development of maladaptive biases linked to psychopathology. We provide support for the proposed role of the LC-NA system by first reviewing work on attentional biases in development and its link to psychopathology in relation to alterations and individual differences in NA availability. We focus on pharmacological manipulations to demonstrate the effect of a disrupted system as well as the ADRA2b polymorphism as a tool to investigate naturally occurring differences in NA availability. We next review associative learning processes that—modulated by the LC-NA system—result in such implicit attentional biases. Further, we demonstrate how NA may influence aversive and appetitive conditioning linked to anxiety disorders as well as addiction and depression.
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de Haas, Elske N; Lee, Caroline; Hernandez, Carlos E; Naguib, Marc; Rodenburg, T Bas
2017-01-01
Personality can influence how animals perceive and learn cues. The behaviour and physiological responses animals show during stressful events is indicative of their personality. Acute induced stress prior to a cognitive test are known to affect the judgement of a stimulus, but personality of an individual could also affect learning of a specific cognitive paradigm. Here, we assessed if adult laying hens' behaviour and physiological responses, as indicators of their personality, were related to their cognitive performance. We assessed their behavioural responses to a tonic immobility test, an open field test, and a manual restraint test, and measured plasma corticosterone levels after manual restraint. After that, hens (n=20) were trained in a pre-set training schedule to associate a colour-cue with a reward. In a two-choice go-go test, hens needed to choose between a baited or non-baited food container displayed randomly on the left or right side of an arena. Success in learning was related to personality, with better performance of hens which showed a reactive personality type by a long latency to walk, struggle or vocalize during the tests. Only eight out of 20 hens reached the training criteria. The non-learners showed a strong side preference during all training days. Side preferences were strong in hens with high levels of plasma corticosterone and with a long duration of tonic immobility, indicating that fearful, stress-sensitive hens are more prone to develop side biases. Our results show that learning can be hindered by side biases, and fearful animals with a more proactive personality type are more sensitive to develop such biases. Copyright © 2016 Elsevier B.V. All rights reserved.
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Is perception of gender biased by a context prime?
DEFF Research Database (Denmark)
Skewes, Lea; Mørch Zederkof, Julie; Skewes, Joshua Charles
2016-01-01
It is well-documented on both explicit and implicit measures that men are associated with agential traits, while women are associated with communal traits, and that these explicit and implicit attitudes and cognitions lead to biases in behaviour. However, little is known about whether information...... about gender is already biased when it enters the cognitive system. We explored whether the same kinds of biases, which pervade implicit attitudes and cognition also pervade peoples’ perception of gender. Using a Bayesian signal detection model, we provide strong evidence that gender stereotypical...
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Learning what to see in a changing world
Directory of Open Access Journals (Sweden)
Katharina eSchmack
2016-05-01
Full Text Available Visual perception is strongly shaped by expectations, but it is poorly understood how such perceptual expectations are learned in our dynamic sensory environment. Here, we applied a Bayesian framework to investigate whether perceptual expectations are continuously updated from different aspects of ongoing experience. In two experiments, human observers performed an associative learning task in which rapidly changing expectations about the appearance of ambiguous stimuli were induced. We found that perception of ambiguous stimuli was biased by both learned associations and previous perceptual outcomes. Computational modelling revealed that perception was best explained by amodel that continuously updated priors from associative learning and perceptual history and combined these priors with the current sensory information in a probabilistic manner. Our findings suggest that the construction of visual perception is a highly dynamic process that incorporates rapidly changing expectations from different sources in a manner consistent with Bayesian learning and inference.
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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.
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QUANTIFYING THE BIASES OF SPECTROSCOPICALLY SELECTED GRAVITATIONAL LENSES
International Nuclear Information System (INIS)
Arneson, Ryan A.; Brownstein, Joel R.; Bolton, Adam S.
2012-01-01
Spectroscopic selection has been the most productive technique for the selection of galaxy-scale strong gravitational lens systems with known redshifts. Statistically significant samples of strong lenses provide a powerful method for measuring the mass-density parameters of the lensing population, but results can only be generalized to the parent population if the lensing selection biases are sufficiently understood. We perform controlled Monte Carlo simulations of spectroscopic lens surveys in order to quantify the bias of lenses relative to parent galaxies in velocity dispersion, mass axis ratio, and mass-density profile. For parameters typical of the SLACS and BELLS surveys, we find (1) no significant mass axis ratio detection bias of lenses relative to parent galaxies; (2) a very small detection bias toward shallow mass-density profiles, which is likely negligible compared to other sources of uncertainty in this parameter; (3) a detection bias toward smaller Einstein radius for systems drawn from parent populations with group- and cluster-scale lensing masses; and (4) a lens-modeling bias toward larger velocity dispersions for systems drawn from parent samples with sub-arcsecond mean Einstein radii. This last finding indicates that the incorporation of velocity-dispersion upper limits of non-lenses is an important ingredient for unbiased analyses of spectroscopically selected lens samples. In general, we find that the completeness of spectroscopic lens surveys in the plane of Einstein radius and mass-density profile power-law index is quite uniform, up to a sharp drop in the region of large Einstein radius and steep mass-density profile, and hence that such surveys are ideally suited to the study of massive field galaxies.
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Opportunity to Learn, Test Bias, and School Effects.
Anderson, Lorin W.
The purpose of the study was to examine test bias and the "non-effects" of schooling. Teachers were given a list of words selected from standardized vocabulary tests and asked to indicate the words they had taught. The words were classified by the grade level at which they were first introduced. Ninety-five third-grade students in four schools…
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The immitigable nature of assembly bias: the impact of halo definition on assembly bias
Villarreal, Antonio S.; Zentner, Andrew R.; Mao, Yao-Yuan; Purcell, Chris W.; van den Bosch, Frank C.; Diemer, Benedikt; Lange, Johannes U.; Wang, Kuan; Campbell, Duncan
2017-11-01
Dark matter halo clustering depends not only on halo mass, but also on other properties such as concentration and shape. This phenomenon is known broadly as assembly bias. We explore the dependence of assembly bias on halo definition, parametrized by spherical overdensity parameter, Δ. We summarize the strength of concentration-, shape-, and spin-dependent halo clustering as a function of halo mass and halo definition. Concentration-dependent clustering depends strongly on mass at all Δ. For conventional halo definitions (Δ ∼ 200 - 600 m), concentration-dependent clustering at low mass is driven by a population of haloes that is altered through interactions with neighbouring haloes. Concentration-dependent clustering can be greatly reduced through a mass-dependent halo definition with Δ ∼ 20 - 40 m for haloes with M200 m ≲ 1012 h-1M⊙. Smaller Δ implies larger radii and mitigates assembly bias at low mass by subsuming altered, so-called backsplash haloes into now larger host haloes. At higher masses (M200 m ≳ 1013 h-1M⊙) larger overdensities, Δ ≳ 600 m, are necessary. Shape- and spin-dependent clustering are significant for all halo definitions that we explore and exhibit a relatively weaker mass dependence. Generally, both the strength and the sense of assembly bias depend on halo definition, varying significantly even among common definitions. We identify no halo definition that mitigates all manifestations of assembly bias. A halo definition that mitigates assembly bias based on one halo property (e.g. concentration) must be mass dependent. The halo definitions that best mitigate concentration-dependent halo clustering do not coincide with the expected average splashback radii at fixed halo mass.
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Specificity and overlap of attention and memory biases in depression.
Marchetti, Igor; Everaert, Jonas; Dainer-Best, Justin; Loeys, Tom; Beevers, Christopher G; Koster, Ernst H W
2018-01-01
Attentional and memory biases are viewed as crucial cognitive processes underlying symptoms of depression. However, it is still unclear whether these two biases are uniquely related to depression or whether they show substantial overlap. We investigated the degree of specificity and overlap of attentional and memory biases for depressotypic stimuli in relation to depression and anxiety by means of meta-analytic commonality analysis. By including four published studies, we considered a pool of 463 healthy and subclinically depressed individuals, different experimental paradigms, and different psychological measures. Memory bias is reliably and strongly related to depression and, specifically, to symptoms of negative mood, worthlessness, feelings of failure, and pessimism. Memory bias for negative information was minimally related to anxiety. Moreover, neither attentional bias nor the overlap between attentional and memory biases were significantly related to depression. Limitations include cross-sectional nature of the study. Our study showed that, across different paradigms and psychological measures, memory bias (and not attentional bias) represents a primary mechanism in depression. Copyright © 2017 Elsevier B.V. All rights reserved.
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Associations among negative parenting, attention bias to anger, and social anxiety among youth.
Gulley, Lauren D; Oppenheimer, Caroline W; Hankin, Benjamin L
2014-02-01
Theories of affective learning suggest that early experiences contribute to emotional disorders by influencing the development of processing biases for negative emotional stimuli. Although studies have shown that physically abused children preferentially attend to angry faces, it is unclear whether youth exposed to more typical aspects of negative parenting exhibit the same type of bias. The current studies extend previous research by linking observed negative parenting styles (e.g., authoritarian) and behaviors (e.g., criticism and negative affect) to attention bias for angry faces in both a psychiatrically enriched (ages 11-17 years; N = 60) and a general community (ages 9-15 years; N = 75) sample of youth. In addition, the association between observed negative parenting (e.g., authoritarian style and negative affect) and youth social anxiety was mediated by attention bias for angry faces in the general community sample. Overall, findings provide preliminary support for theories of affective learning and risk for psychopathology among youth.
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Dopaminergic medication affects choice bias in Parkinson's disease
Nuland, A.J.M. van; Helmich, R.C.G.; Dirkx, M.F.M.; Zach, H.; Bloem, B.R.; Toni, I.; Cools, R.; Ouden, H.E.M. den
2016-01-01
Objective: Assess dopaminergic effects on choice bias in Parkinson's disease (PD). Background: Bradykinesia, rigidity and resting tremor are the core symptoms of PD, but many patients also suffer from cognitive dysfunction. For instance, PD patients have an increased tendency to learn from aversive
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Self-learning Monte Carlo (dynamical biasing)
International Nuclear Information System (INIS)
Matthes, W.
1981-01-01
In many applications the histories of a normal Monte Carlo game rarely reach the target region. An approximate knowledge of the importance (with respect to the target) may be used to guide the particles more frequently into the target region. A Monte Carlo method is presented in which each history contributes to update the importance field such that eventually most target histories are sampled. It is a self-learning method in the sense that the procedure itself: (a) learns which histories are important (reach the target) and increases their probability; (b) reduces the probabilities of unimportant histories; (c) concentrates gradually on the more important target histories. (U.K.)
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Poernomo, Alvin; Kang, Dae-Ki
2018-08-01
Training a deep neural network with a large number of parameters often leads to overfitting problem. Recently, Dropout has been introduced as a simple, yet effective regularization approach to combat overfitting in such models. Although Dropout has shown remarkable results on many deep neural network cases, its actual effect on CNN has not been thoroughly explored. Moreover, training a Dropout model will significantly increase the training time as it takes longer time to converge than a non-Dropout model with the same architecture. To deal with these issues, we address Biased Dropout and Crossmap Dropout, two novel approaches of Dropout extension based on the behavior of hidden units in CNN model. Biased Dropout divides the hidden units in a certain layer into two groups based on their magnitude and applies different Dropout rate to each group appropriately. Hidden units with higher activation value, which give more contributions to the network final performance, will be retained by a lower Dropout rate, while units with lower activation value will be exposed to a higher Dropout rate to compensate the previous part. The second approach is Crossmap Dropout, which is an extension of the regular Dropout in convolution layer. Each feature map in a convolution layer has a strong correlation between each other, particularly in every identical pixel location in each feature map. Crossmap Dropout tries to maintain this important correlation yet at the same time break the correlation between each adjacent pixel with respect to all feature maps by applying the same Dropout mask to all feature maps, so that all pixels or units in equivalent positions in each feature map will be either dropped or active during training. Our experiment with various benchmark datasets shows that our approaches provide better generalization than the regular Dropout. Moreover, our Biased Dropout takes faster time to converge during training phase, suggesting that assigning noise appropriately in
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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
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Overcoming Learning Aversion in Evaluating and Managing Uncertain Risks.
Cox, Louis Anthony Tony
2015-10-01
Decision biases can distort cost-benefit evaluations of uncertain risks, leading to risk management policy decisions with predictably high retrospective regret. We argue that well-documented decision biases encourage learning aversion, or predictably suboptimal learning and premature decision making in the face of high uncertainty about the costs, risks, and benefits of proposed changes. Biases such as narrow framing, overconfidence, confirmation bias, optimism bias, ambiguity aversion, and hyperbolic discounting of the immediate costs and delayed benefits of learning, contribute to deficient individual and group learning, avoidance of information seeking, underestimation of the value of further information, and hence needlessly inaccurate risk-cost-benefit estimates and suboptimal risk management decisions. In practice, such biases can create predictable regret in selection of potential risk-reducing regulations. Low-regret learning strategies based on computational reinforcement learning models can potentially overcome some of these suboptimal decision processes by replacing aversion to uncertain probabilities with actions calculated to balance exploration (deliberate experimentation and uncertainty reduction) and exploitation (taking actions to maximize the sum of expected immediate reward, expected discounted future reward, and value of information). We discuss the proposed framework for understanding and overcoming learning aversion and for implementing low-regret learning strategies using regulation of air pollutants with uncertain health effects as an example. © 2015 Society for Risk Analysis.
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Long-Term Memory Biases Auditory Spatial Attention
Zimmermann, Jacqueline F.; Moscovitch, Morris; Alain, Claude
2017-01-01
Long-term memory (LTM) has been shown to bias attention to a previously learned visual target location. Here, we examined whether memory-predicted spatial location can facilitate the detection of a faint pure tone target embedded in real world audio clips (e.g., soundtrack of a restaurant). During an initial familiarization task, participants…
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International Nuclear Information System (INIS)
Colbeck, Roger; Kent, Adrian
2006-01-01
Alice is a charismatic quantum cryptographer who believes her parties are unmissable; Bob is a (relatively) glamorous string theorist who believes he is an indispensable guest. To prevent possibly traumatic collisions of self-perception and reality, their social code requires that decisions about invitation or acceptance be made via a cryptographically secure variable-bias coin toss (VBCT). This generates a shared random bit by the toss of a coin whose bias is secretly chosen, within a stipulated range, by one of the parties; the other party learns only the random bit. Thus one party can secretly influence the outcome, while both can save face by blaming any negative decisions on bad luck. We describe here some cryptographic VBCT protocols whose security is guaranteed by quantum theory and the impossibility of superluminal signaling, setting our results in the context of a general discussion of secure two-party computation. We also briefly discuss other cryptographic applications of VBCT
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Colbeck, Roger; Kent, Adrian
2006-03-01
Alice is a charismatic quantum cryptographer who believes her parties are unmissable; Bob is a (relatively) glamorous string theorist who believes he is an indispensable guest. To prevent possibly traumatic collisions of self-perception and reality, their social code requires that decisions about invitation or acceptance be made via a cryptographically secure variable-bias coin toss (VBCT). This generates a shared random bit by the toss of a coin whose bias is secretly chosen, within a stipulated range, by one of the parties; the other party learns only the random bit. Thus one party can secretly influence the outcome, while both can save face by blaming any negative decisions on bad luck. We describe here some cryptographic VBCT protocols whose security is guaranteed by quantum theory and the impossibility of superluminal signaling, setting our results in the context of a general discussion of secure two-party computation. We also briefly discuss other cryptographic applications of VBCT.
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Malakar, Nabin K.; Lary, D. L.; Moore, A.; Gencaga, D.; Roscoe, B.; Albayrak, Arif; Petrenko, Maksym; Wei, Jennifer
2012-01-01
Air quality information is increasingly becoming a public health concern, since some of the aerosol particles pose harmful effects to peoples health. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. The comparison between the AOD measured from the ground-based Aerosol Robotic Network (AERONET) system and the satellite MODIS instruments at 550 nm shows that there is a bias between the two data products. We performed a comprehensive analysis exploring possible factors which may be contributing to the inter-instrumental bias between MODIS and AERONET. The analysis used several measured variables, including the MODIS AOD, as input in order to train a neural network in regression mode to predict the AERONET AOD values. This not only allowed us to obtain an estimate, but also allowed us to infer the optimal sets of variables that played an important role in the prediction. In addition, we applied machine learning to infer the global abundance of ground level PM2.5 from the AOD data and other ancillary satellite and meteorology products. This research is part of our goal to provide air quality information, which can also be useful for global epidemiology studies.
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Srinivas, G.; Chowdary, Jasti S.; Gnanaseelan, C.; Prasad, K. V. S. R.; Karmakar, Ananya; Parekh, Anant
2018-03-01
In the present study the association between mean and interannual subsurface temperature bias over the equatorial Indian Ocean (EIO) is investigated during boreal summer (June through September; JJAS) in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. Anomalously high subsurface warm bias (greater than 3 °C) over the eastern EIO (EEIO) region is noted in CFSv2 during summer, which is higher compared to other parts of the tropical Indian Ocean. Prominent eastward current bias in the upper 100 m over the EIO region induced by anomalous westerly winds is primarily responsible for subsurface temperature bias. The eastward currents transport warm water to the EEIO and is pushed down to subsurface due to downwelling. Thus biases in both horizontal and vertical currents over the EIO region support subsurface warm bias. The evolution of systematic subsurface warm bias in the model shows strong interannual variability. These maximum subsurface warming episodes over the EEIO are mainly associated with La Niña like forcing. Strong convergence of low level winds over the EEIO and Maritime continent enhanced the westerly wind bias over the EIO during maximum warming years. This low level convergence of wind is induced by the bias in the gradient in the mean sea level pressure with positive bias over western EIO and negative bias over EEIO and parts of western Pacific. Consequently, changes in the atmospheric circulation associated with La Niña like conditions affected the ocean dynamics by modulating the current bias thereby enhancing the subsurface warm bias over the EEIO. It is identified that EEIO subsurface warming is stronger when La Niña co-occurred with negative Indian Ocean Dipole events as compared to La Niña only years in the model. Ocean general circulation model (OGCM) experiments forced with CFSv2 winds clearly support our hypothesis that ocean dynamics influenced by westerly winds bias is primarily
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Toward a clarification of the taxonomy of "bias" in epidemiology textbooks.
Schwartz, Sharon; Campbell, Ulka B; Gatto, Nicolle M; Gordon, Kirsha
2015-03-01
Epidemiology textbooks typically divide biases into 3 general categories-confounding, selection bias, and information bias. Despite the ubiquity of this categorization, authors often use these terms to mean different things. This hinders communication among epidemiologists and confuses students who are just learning about the field. To understand the sources of this problem, we reviewed current general epidemiology textbooks to examine how the authors defined and categorized biases. We found that much of the confusion arises from different definitions of "validity" and from a mixing of 3 overlapping organizational features in defining and differentiating among confounding, selection bias, and information bias: consequence, the result of the problem; cause, the processes that give rise to the problem; and cure, how these biases can be addressed once they occur. By contrast, a consistent taxonomy would provide (1) a clear and consistent definition of what unites confounding, selection bias, and information bias and (2) a clear articulation and consistent application of the feature that distinguishes these categories. Based on a distillation of these textbook discussions, we provide an example of a taxonomy that we think meets these criteria.
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Determinants of Colour Constancy and the Blue Bias
Gegenfurtner, Karl
2017-01-01
We investigated several sensory and cognitive determinants of colour constancy across 40 illumination hues. In the first experiment, we measured colour naming for the illumination and for the colour induced by the illumination on the colorimetric grey. Results confirmed that the induced colours are approximately complementary to the colour of the illumination. In the second experiment, we measured colour constancy using achromatic adjustments. Average colour constancy was perfect under the blue daylight illumination and decreased in colour directions away from the blue daylight illumination due to undershooting and a strong blue bias. Apart from this blue bias, colour constancy was not related to illumination discrimination and to chromatic detection measured previously with the same setup and stimuli. We also observed a strong negative relationship between the degree of colour constancy and the consensus of naming the illumination colour. Constancy coincided with a low naming consensus, in particular because bluish illumination colours were sometimes seen as achromatic. Blue bias and category consensus alone explained >68%, and all determinants together explained >94% of the variance of achromatic adjustments. These findings suggest that colour constancy is optimised for blue daylight. PMID:29348910
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No arousal-biased competition in focused visuospatial attention.
Ásgeirsson, Árni Gunnar; Nieuwenhuis, Sander
2017-11-01
Arousal sometimes enhances and sometimes impairs perception and memory. A recent theory attempts to reconcile these findings by proposing that arousal amplifies the competition between stimulus representations, strengthening already strong representations and weakening already weak representations. Here, we report a stringent test of this arousal-biased competition theory in the context of focused visuospatial attention. Participants were required to identify a briefly presented target in the context of multiple distractors, which varied in the degree to which they competed for representation with the target, as revealed by psychophysics. We manipulated arousal using emotionally arousing pictures (Experiment 1), alerting tones (Experiment 2) and white-noise stimulation (Experiment 3), and validated these manipulations with electroencephalography and pupillometry. In none of the experiments did we find evidence that arousal modulated the effect of distractor competition on the accuracy of target identification. Bayesian statistics revealed moderate to strong evidence against arousal-biased competition. Modeling of the psychophysical data based on Bundesen's (1990) theory of visual attention corroborated the conclusion that arousal does not bias competition in focused visuospatial attention. Copyright © 2017 Elsevier B.V. All rights reserved.
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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.
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Le Mens, Gael; Denrell, Jerker
2011-01-01
Recent research has argued that several well-known judgment biases may be due to biases in the available information sample rather than to biased information processing. Most of these sample-based explanations assume that decision makers are "naive": They are not aware of the biases in the available information sample and do not correct for them.…
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<strong>Pervasive strong>technology
DEFF Research Database (Denmark)
Larsen, Lasse Juel; Majgaard, Gunver
2010-01-01
This paper discusses learning potentials of pervasive technology when used in the classroom setting. Explicitly this paper uses the research and development project “Octopus” as its point of departure and as the foundation for reflections on how learning takes place in intelligent contexts. We...... propose that pervasive and tangible media like the Octopus reshapes learning not only by utilizing the body as the epicenter for experiences, but also by changing the traditional temporal and vertical learning design (vertical refers to temporal gab between learned knowledge and applied knowledge......) normally associated with the traditional school system. Initial analyses on the research project “Octopus” indicate that the temporal and vertical learning patterns are replaced by spatial and simultaneous learning design. We suggest that this change signals a fundamental approach and at the same time...
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The impact of the biasing radial electric field on the SOL in a divertor tokamak
International Nuclear Information System (INIS)
Rozhansky, V.; Tendler, M.
1993-01-01
Strong radial electric field can be induced within the SOL in a divertor tokamak by applying a voltage to divertor plates with respect to the first wall. This biasing scheme results in the strong radial electric field which is much larger than the natural electric field, usually of the order T e /e. Experiments employing this biasing scheme were carried out on the tokamak TdeV. Many interesting effects such as - modifications of the density profile and radial transport of impurities as a function of the polarity and the magnitude of the biasing voltage, the generation of the flux surface average toroidal rotation proportional to the applied voltage, redistribution of the plasma outflow onto divertor plates and so on - were demonstrated to result from the biasing. Furthermore, in contrast to studies carried out employing a different biasing scheme which primarily results in a poloidal electric field, the strong radial electric field impacts more significantly within SOL than the poloidal electric field. Here, we aim to show that the main effects observed experimentally follow from the analysis, provided continuity and momentum balances are employed invoking anomalous viscosity and inertia. (author) 4 refs
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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
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<strong>New learning arenas for shop stewards - a new political agenda for unions strong>
DEFF Research Database (Denmark)
Warring, Niels
. In the paper I will discuss results from a project involving shop stewards from four different unions, all members of LO (the confederation of trade unions for skilled and unskilled workers). We worked with different methods in the project ending with ‘future-creating workshops' where shop stewards...... in daily practices can be analysed us a combination of perspectives from different theoretical traditions. Shop steward's learning is situational, relational and cross-contextual. Shop stewards' learning is lifelong and life wide. And shop stewards' learning is closely connected to the development...... of the labour market and not least the unions' priorities, interpretation and reaction to this development....
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Body image related negative interpretation bias in anorexia nervosa.
Brockmeyer, Timo; Anderle, Alisa; Schmidt, Hagen; Febry, Stephanie; Wünsch-Leiteritz, Wally; Leiteritz, Andreas; Friederich, Hans-Christoph
2018-05-01
A distorted body image and pronounced body dissatisfaction are hallmarks of anorexia nervosa (AN) that typically result in dietary restraint and compensatory behaviours. Cognitive biases such as negative interpretation bias are considered key maintaining factors of these maladaptive cognitions and behaviours. However, little attention has been paid to empirical tests whether negative interpretation bias exists in AN and to what degree it is associated with symptom severity. Participants in the present study were 40 women with AN and 40 healthy women with no history of an eating disorder. Body-related negative interpretation bias (i.e., a tendency to interpret ambiguous information about the own body in a negative way) was measured by a Scrambled Sentences Task. Patients with AN showed a stronger body-related negative interpretation bias than healthy controls. Within both groups, negative interpretation bias correlated strongly and positively with AN symptom severity and these effects were not moderated by levels of depressive symptoms. The findings support the idea that biased interpretation of body-related information is associated with the specific psychopathology of AN. Targeted, computerised interventions (e.g. interpretation bias modification) may help to alter these dysfunctional cognitive schemas that lie at the heart of AN. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Eden, Annuschka Salima; Zwitserlood, Pienie; Keuper, Katharina; Junghöfer, Markus; Laeger, Inga; Zwanzger, Peter; Dobel, Christian
2014-01-01
The well-established memory bias for arousing-negative stimuli seems to be enhanced in high trait-anxious persons and persons suffering from anxiety disorders. We monitored the emergence and development of such a bias during and after learning, in high and low trait anxious participants. A word-learning paradigm was applied, consisting of spoken pseudowords paired either with arousing-negative or neutral pictures. Learning performance during training evidenced a short-lived advantage for arousing-negative associated words, which was not present at the end of training. Cued recall and valence ratings revealed a memory bias for pseudowords that had been paired with arousing-negative pictures, immediately after learning and two weeks later. This held even for items that were not explicitly remembered. High anxious individuals evidenced a stronger memory bias in the cued-recall test, and their ratings were also more negative overall compared to low anxious persons. Both effects were evident, even when explicit recall was controlled for. Regarding the memory bias in anxiety prone persons, explicit memory seems to play a more crucial role than implicit memory. The study stresses the need for several time points of bias measurement during the course of learning and retrieval, as well as the employment of different measures for learning success.
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Directory of Open Access Journals (Sweden)
Annuschka Salima Eden
Full Text Available The well-established memory bias for arousing-negative stimuli seems to be enhanced in high trait-anxious persons and persons suffering from anxiety disorders. We monitored the emergence and development of such a bias during and after learning, in high and low trait anxious participants. A word-learning paradigm was applied, consisting of spoken pseudowords paired either with arousing-negative or neutral pictures. Learning performance during training evidenced a short-lived advantage for arousing-negative associated words, which was not present at the end of training. Cued recall and valence ratings revealed a memory bias for pseudowords that had been paired with arousing-negative pictures, immediately after learning and two weeks later. This held even for items that were not explicitly remembered. High anxious individuals evidenced a stronger memory bias in the cued-recall test, and their ratings were also more negative overall compared to low anxious persons. Both effects were evident, even when explicit recall was controlled for. Regarding the memory bias in anxiety prone persons, explicit memory seems to play a more crucial role than implicit memory. The study stresses the need for several time points of bias measurement during the course of learning and retrieval, as well as the employment of different measures for learning success.
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McElreath, Richard; Bell, Adrian V; Efferson, Charles; Lubell, Mark; Richerson, Peter J; Waring, Timothy
2008-11-12
The existence of social learning has been confirmed in diverse taxa, from apes to guppies. In order to advance our understanding of the consequences of social transmission and evolution of behaviour, however, we require statistical tools that can distinguish among diverse social learning strategies. In this paper, we advance two main ideas. First, social learning is diverse, in the sense that individuals can take advantage of different kinds of information and combine them in different ways. Examining learning strategies for different information conditions illuminates the more detailed design of social learning. We construct and analyse an evolutionary model of diverse social learning heuristics, in order to generate predictions and illustrate the impact of design differences on an organism's fitness. Second, in order to eventually escape the laboratory and apply social learning models to natural behaviour, we require statistical methods that do not depend upon tight experimental control. Therefore, we examine strategic social learning in an experimental setting in which the social information itself is endogenous to the experimental group, as it is in natural settings. We develop statistical models for distinguishing among different strategic uses of social information. The experimental data strongly suggest that most participants employ a hierarchical strategy that uses both average observed pay-offs of options as well as frequency information, the same model predicted by our evolutionary analysis to dominate a wide range of conditions.
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Diversity Matters in Academic Radiology: Acknowledging and Addressing Unconscious Bias.
Allen, Brenda J; Garg, Kavita
2016-12-01
To meet challenges related to changing demographics, and to optimize the promise of diversity, radiologists must bridge the gap between numbers of women and historically underrepresented minorities in radiology and radiation oncology as contrasted with other medical specialties. Research reveals multiple ways that women and underrepresented minorities can benefit radiology education, research, and practice. To achieve those benefits, promising practices promote developing and implementing strategies that support diversity as an institutional priority and cultivate shared responsibility among all members to create inclusive learning and workplace environments. Strategies also include providing professional development to empower and equip members to accomplish diversity-related goals. Among topics for professional development about diversity, unconscious bias has shown positive results. Unconscious bias refers to ways humans unknowingly draw upon assumptions about individuals and groups to make decisions about them. Researchers have documented unconscious bias in a variety of contexts and professions, including health care, in which they have studied differential treatment, diagnosis, prescribed care, patient well-being and compliance, physician-patient interactions, clinical decision making, and medical school education. These studies demonstrate unfavorable impacts on members of underrepresented groups and women. Learning about and striving to counteract unconscious bias points to promising practices for increasing the numbers of women and underrepresented minorities in the radiology and radiation oncology workforce. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.
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Testing strong factorial invariance using three-level structural equation modeling
Directory of Open Access Journals (Sweden)
Suzanne eJak
2014-07-01
Full Text Available Within structural equation modeling, the most prevalent model to investigate measurement bias is the multigroup model. Equal factor loadings and intercepts across groups in a multigroup model represent strong factorial invariance (absence of measurement bias across groups. Although this approach is possible in principle, it is hardly practical when the number of groups is large or when the group size is relatively small. Jak, Oort and Dolan (2013 showed how strong factorial invariance across large numbers of groups can be tested in a multilevel structural equation modeling framework, by treating group as a random instead of a fixed variable. In the present study, this model is extended for use with three-level data. The proposed method is illustrated with an investigation of strong factorial invariance across 156 school classes and 50 schools in a Dutch dyscalculia test, using three-level structural equation modeling.
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Positivity effect in healthy aging in observational but not active feedback-learning.
Bellebaum, Christian; Rustemeier, Martina; Daum, Irene
2012-01-01
The present study investigated the impact of healthy aging on the bias to learn from positive or negative performance feedback in observational and active feedback learning. In active learning, a previous study had already shown a negative learning bias in healthy seniors older than 75 years, while no bias was found for younger seniors. However, healthy aging is accompanied by a 'positivity effect', a tendency to primarily attend to stimuli with positive valence. Based on recent findings of dissociable neural mechanisms in active and observational feedback learning, the positivity effect was hypothesized to influence older participants' observational feedback learning in particular. In two separate experiments, groups of young (mean age 27) and older participants (mean age 60 years) completed an observational or active learning task designed to differentially assess positive and negative learning. Older but not younger observational learners showed a significant bias to learn better from positive than negative feedback. In accordance with previous findings, no bias was found for active learning. This pattern of results is discussed in terms of differences in the neural underpinnings of active and observational learning from performance feedback.
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Ion extraction from positively biased laser-ablation plasma
International Nuclear Information System (INIS)
Isono, Fumika; Nakajima, Mitsuo; Hasegawa, Jun; Horioka, Kazuhiko
2016-01-01
Ions were extracted through a grounded grid from a positively biased laser-ablation plasma and the behaviors were investigated. Since the plasma was positively biased against the grounded wall, we could extract the ions without insulated gap. We confirmed formation of a virtual anode when we increased the distance between the grid and the ion collector. Results also indicated that when the ion flux from the ablation plasma exceeded a critical value, the current was strongly suppressed to the space charge limited level due to the formation of virtual anode.
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Toddlers' bias to look at average versus obese figures relates to maternal anti-fat prejudice.
Ruffman, Ted; O'Brien, Kerry S; Taumoepeau, Mele; Latner, Janet D; Hunter, John A
2016-02-01
Anti-fat prejudice (weight bias, obesity stigma) is strong, prevalent, and increasing in adults and is associated with negative outcomes for those with obesity. However, it is unknown how early in life this prejudice forms and the reasons for its development. We examined whether infants and toddlers might display an anti-fat bias and, if so, whether it was influenced by maternal anti-fat attitudes through a process of social learning. Mother-child dyads (N=70) split into four age groups participated in a preferential looking paradigm whereby children were presented with 10 pairs of average and obese human figures in random order, and their viewing times (preferential looking) for the figures were measured. Mothers' anti-fat prejudice and education were measured along with mothers' and fathers' body mass index (BMI) and children's television viewing time. We found that older infants (M=11months) had a bias for looking at the obese figures, whereas older toddlers (M=32months) instead preferred looking at the average-sized figures. Furthermore, older toddlers' preferential looking was correlated significantly with maternal anti-fat attitudes. Parental BMI, education, and children's television viewing time were unrelated to preferential looking. Looking times might signal a precursor to explicit fat prejudice socialized via maternal anti-fat attitudes. Copyright © 2015 Elsevier Inc. All rights reserved.
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Assessing the extent of non-stationary biases in GCMs
Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish
2017-06-01
General circulation models (GCMs) are the main tools for estimating changes in the climate for the future. The imperfect representation of climate models introduces biases in the simulations that need to be corrected prior to their use for impact assessments. Bias correction methods generally assume that the bias calculated over the historical period does not change and can be applied to the future. This study investigates this assumption by considering the extent and nature of bias non-stationarity using 20th century precipitation and temperature simulations from six CMIP5 GCMs across Australia. Four statistics (mean, standard deviation, 10th and 90th quantiles) in monthly and seasonal biases are obtained for three different time window lengths (10, 25 and 33 years) to examine the properties of bias over time. This approach is repeated for two different phases of the Interdecadal Pacific Oscillation (IPO), which is known to have strong influences on the Australian climate. It is found that bias non-stationarity at decadal timescales is indeed an issue over some of Australia for some GCMs. When considering interdecadal variability there are significant difference in the bias between positive and negative phases of the IPO. Regional analyses confirmed these findings with the largest differences seen on the east coast of Australia, where IPO impacts tend to be the strongest. The nature of the bias non-stationarity found in this study suggests that it will be difficult to modify existing bias correction approaches to account for non-stationary biases. A more practical approach for impact assessments that use bias correction maybe to use a selection of GCMs where the assumption of bias non-stationarity holds.
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A Framework for Integrating Implicit Bias Recognition Into Health Professions Education.
Sukhera, Javeed; Watling, Chris
2018-01-01
Existing literature on implicit bias is fragmented and comes from a variety of fields like cognitive psychology, business ethics, and higher education, but implicit-bias-informed educational approaches have been underexplored in health professions education and are difficult to evaluate using existing tools. Despite increasing attention to implicit bias recognition and management in health professions education, many programs struggle to meaningfully integrate these topics into curricula. The authors propose a six-point actionable framework for integrating implicit bias recognition and management into health professions education that draws on the work of previous researchers and includes practical tools to guide curriculum developers. The six key features of this framework are creating a safe and nonthreatening learning context, increasing knowledge about the science of implicit bias, emphasizing how implicit bias influences behaviors and patient outcomes, increasing self-awareness of existing implicit biases, improving conscious efforts to overcome implicit bias, and enhancing awareness of how implicit bias influences others. Important considerations for designing implicit-bias-informed curricula-such as individual and contextual variables, as well as formal and informal cultural influences-are discussed. The authors also outline assessment and evaluation approaches that consider outcomes at individual, organizational, community, and societal levels. The proposed framework may facilitate future research and exploration regarding the use of implicit bias in health professions education.
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Family matters: Directionality of turning bias while kissing is modulated by context.
Sedgewick, Jennifer R; Elias, Lorin J
2016-01-28
When leaning forward to kiss to a romantic partner, individuals tend to direct their kiss to the right more often than the left. Studies have consistently demonstrated this kissing asymmetry, although other factors known to influence lateral biases, such as sex or situational context, had yet to be explored. The primary purpose of our study was to investigate if turning direction was consistent between a romantic (parent-parent) and parental (parent-child) kissing context, and secondly, to examine if sex differences influenced turning bias between parent-child kissing partners. An archival analysis coded the direction of turning bias for 161 images of romantic kissing (mothers kissing fathers) and 529 images of parental kissing (mothers or fathers kissing sons or daughters). The results indicated that the direction of turning bias differed between kissing contexts. As expected, a right-turn bias was observed for romantic kissing; however, a left-turn bias was exhibited for parental kissing. There was no significant difference of turning bias between any parent-child kissing partners. Interpretations for the left-turn bias discuss parental kissing as a learned lateral behaviour.
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Ostrofsky, Justin; Kozbelt, Aaron; Cohen, Dale J
2015-01-01
We tested the misperception hypothesis of drawing errors, which states that drawing accuracy is strongly influenced by the perceptual encoding of a to-be-drawn stimulus. We used a highly controlled experimental paradigm in which nonartist participants made perceptual judgements and drawings of angles under identical stimulus exposure conditions. Experiment 1 examined the isosceles/scalene triangle angle illusion; congruent patterns of bias in the perception and drawing tasks were found for 40 and 60° angles, but not for 20 or 80° angles, providing mixed support for the misperception hypothesis. Experiment 2 examined shape constancy effects with respect to reproductions of single acute or obtuse angles; congruent patterns of bias in the perception and drawing tasks were found across a range of angles from 29 to 151°, providing strong support for the misperception hypothesis. In both experiments, perceptual and drawing biases were positively correlated. These results are largely consistent with the misperception hypothesis, suggesting that inaccurate perceptual encoding of angles is an important reason that nonartists err in drawing angles from observation.
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Strong paramagnon scattering in single atom Pd contacts
DEFF Research Database (Denmark)
Schendel, V.; Barreteau, Cyrille; Brandbyge, Mads
2017-01-01
Pd contacts shows a reduction with increasing bias, which gives rise to a peculiar Lambda-shaped spectrum. Supported by theoretical calculations, we correlate this finding with the lifetime of hot quasiparticles in Pd, which is strongly influenced by paramagnon scattering. In contrast to this, Co...
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Le Mens, Gaël; Denrell, Jerker
2011-04-01
Recent research has argued that several well-known judgment biases may be due to biases in the available information sample rather than to biased information processing. Most of these sample-based explanations assume that decision makers are "naive": They are not aware of the biases in the available information sample and do not correct for them. Here, we show that this "naivety" assumption is not necessary. Systematically biased judgments can emerge even when decision makers process available information perfectly and are also aware of how the information sample has been generated. Specifically, we develop a rational analysis of Denrell's (2005) experience sampling model, and we prove that when information search is interested rather than disinterested, even rational information sampling and processing can give rise to systematic patterns of errors in judgments. Our results illustrate that a tendency to favor alternatives for which outcome information is more accessible can be consistent with rational behavior. The model offers a rational explanation for behaviors that had previously been attributed to cognitive and motivational biases, such as the in-group bias or the tendency to prefer popular alternatives. 2011 APA, all rights reserved
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Adaptive enhanced sampling by force-biasing using neural networks
Guo, Ashley Z.; Sevgen, Emre; Sidky, Hythem; Whitmer, Jonathan K.; Hubbell, Jeffrey A.; de Pablo, Juan J.
2018-04-01
A machine learning assisted method is presented for molecular simulation of systems with rugged free energy landscapes. The method is general and can be combined with other advanced sampling techniques. In the particular implementation proposed here, it is illustrated in the context of an adaptive biasing force approach where, rather than relying on discrete force estimates, one can resort to a self-regularizing artificial neural network to generate continuous, estimated generalized forces. By doing so, the proposed approach addresses several shortcomings common to adaptive biasing force and other algorithms. Specifically, the neural network enables (1) smooth estimates of generalized forces in sparsely sampled regions, (2) force estimates in previously unexplored regions, and (3) continuous force estimates with which to bias the simulation, as opposed to biases generated at specific points of a discrete grid. The usefulness of the method is illustrated with three different examples, chosen to highlight the wide range of applicability of the underlying concepts. In all three cases, the new method is found to enhance considerably the underlying traditional adaptive biasing force approach. The method is also found to provide improvements over previous implementations of neural network assisted algorithms.
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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)
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Drought Duration Biases in Current Global Climate Models
Moon, Heewon; Gudmundsson, Lukas; Seneviratne, Sonia
2016-04-01
Several droughts in the recent past are characterized by their increased duration and intensity. In particular, substantially prolonged droughts have brought major societal and economic losses in certain regions, yet climate change projections of such droughts in terms of duration is subject to large uncertainties. This study analyzes the biases of drought duration in state-of-the-art global climate model (GCM) simulations from the 5th phase of Coupled Model Intercomparison Project (CMIP5). Drought durations are defined as negative precipitation anomalies and evaluated with three observation-based datasets in the period of 1901-2010. Large spread in biases of GCMs is commonly found in all regions, with particular strong biases in North East Brazil, Africa, Northern Australia, Central America, Central and Northern Europe, Sahel and Asia. Also in most regions, the interquartile range of bias lies below 0, meaning that the GCMs tend to underestimate drought durations. Meanwhile in some regions such as Western South America, the Amazon, Sahel, West and South Africa, and Asia, considerable inconsistency among the three observation-based datasets were found. These results indicate substantial uncertainties and errors in current GCMs for simulating drought durations as well as a large spread in observation-based datasets, both of which are found to be particularly strong in those regions that are often considered to be hot spots of projected future drying. The underlying sources of these uncertainties need to be identified in further study and will be applied to constrain GCM-based drought projections under climate change.
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International Nuclear Information System (INIS)
Dorosz, P.; Baszczyk, M.; Glab, S.; Kucewicz, W.; Mik, L.; Sapor, M.
2013-01-01
Gain of the silicon photomultiplier is strongly dependent on the value of bias voltage and temperature. This paper proposes a method for gain stabilization just by compensation of temperature fluctuations by bias correction. It has been confirmed that this approach gives good results and the gain can be kept very stable
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Back-dropout Transfer Learning for Action Recognition
DEFF Research Database (Denmark)
Ren, Huamin; Kanhabua, Nattiya; Møgelmose, Andreas
2018-01-01
transfer learning being a promising approach, it is still an open question how to adapt the model learned from the source dataset to the target dataset. One big challenge is to prevent the impact of category bias on classification performance. Dataset bias exists when two images from the same category...
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Content specificity of attention bias to threat in anxiety disorders: a meta-analysis.
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.
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Directory of Open Access Journals (Sweden)
Marissa A Gorlick
Full Text Available Arousal Biased Competition theory suggests that arousal enhances competitive attentional processes, but makes no strong claims about valence effects. Research suggests that the scope of enhanced attention depends on valence with negative arousal narrowing and positive arousal broadening attention. Attentional scope likely affects declarative-memory-mediated and perceptual-representation-mediated learning systems differently, with declarative-memory-mediated learning depending on narrow attention to develop targeted verbalizable rules, and perceptual-representation-mediated learning depending on broad attention to develop a perceptual representation. We hypothesize that negative arousal accentuates declarative-memory-mediated learning and attenuates perceptual-representation-mediated learning, while positive arousal reverses this pattern. Prototype learning provides an ideal test bed as dissociable declarative-memory and perceptual-representation systems mediate two-prototype (AB and one-prototype (AN prototype learning, respectively, and computational models are available that provide powerful insights on cognitive processing. As predicted, we found that negative arousal narrows attentional focus facilitating AB learning and impairing AN learning, while positive arousal broadens attentional focus facilitating AN learning and impairing AB learning.
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Gorlick, Marissa A; Maddox, W Todd
2013-01-01
Arousal Biased Competition theory suggests that arousal enhances competitive attentional processes, but makes no strong claims about valence effects. Research suggests that the scope of enhanced attention depends on valence with negative arousal narrowing and positive arousal broadening attention. Attentional scope likely affects declarative-memory-mediated and perceptual-representation-mediated learning systems differently, with declarative-memory-mediated learning depending on narrow attention to develop targeted verbalizable rules, and perceptual-representation-mediated learning depending on broad attention to develop a perceptual representation. We hypothesize that negative arousal accentuates declarative-memory-mediated learning and attenuates perceptual-representation-mediated learning, while positive arousal reverses this pattern. Prototype learning provides an ideal test bed as dissociable declarative-memory and perceptual-representation systems mediate two-prototype (AB) and one-prototype (AN) prototype learning, respectively, and computational models are available that provide powerful insights on cognitive processing. As predicted, we found that negative arousal narrows attentional focus facilitating AB learning and impairing AN learning, while positive arousal broadens attentional focus facilitating AN learning and impairing AB learning.
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Strategi Mengatasi Common Measures Bias dalam Balanced Scorecard
Directory of Open Access Journals (Sweden)
Sekar Akrom Faradiza
2016-06-01
Balanced Scorecard (BSC is a comprehensive performance measurement. BSC is not only used financial indicators but also non financial indicators there are customer, internal process business and learning and growth perspective. By using BSC, evaluators have common and unique measures. When evaluate manager performance, evaluator tends to only use common measures and ignore unique measures. This is called common measures bias. This study aims to investigate whether dissaggregated and aggregated BSC and management communication can overcome common measures bias and intent to BSC approach. This study also will evaluate whether these approach will affect evaluator decision when allocated compensation. We conduct 2x2x2 experiment of undergraduate accounting students. Participant act as a senior manager and evaluate the performance of two divisions and then allocated the bonus. ANOVA repeated measurement are used to conduct hypothesis test. The results showed that dissaggregated BSC and management communication could not overcome common measures bias but effected management decision when allocated compensation.
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Who Learns More? Cultural Differences in Implicit Sequence Learning
Fu, Qiufang; Dienes, Zoltan; Shang, Junchen; Fu, Xiaolan
2013-01-01
Background It is well documented that East Asians differ from Westerners in conscious perception and attention. However, few studies have explored cultural differences in unconscious processes such as implicit learning. Methodology/Principal Findings The global-local Navon letters were adopted in the serial reaction time (SRT) task, during which Chinese and British participants were instructed to respond to global or local letters, to investigate whether culture influences what people acquire in implicit sequence learning. Our results showed that from the beginning British expressed a greater local bias in perception than Chinese, confirming a cultural difference in perception. Further, over extended exposure, the Chinese learned the target regularity better than the British when the targets were global, indicating a global advantage for Chinese in implicit learning. Moreover, Chinese participants acquired greater unconscious knowledge of an irrelevant regularity than British participants, indicating that the Chinese were more sensitive to contextual regularities than the British. Conclusions/Significance The results suggest that cultural biases can profoundly influence both what people consciously perceive and unconsciously learn. PMID:23940773
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Household chaos moderates the link between maternal attribution bias and parenting
Wang, Z.; Deater-Deckard, K.; Bell, M.A.
2013-01-01
Objective Parents who attribute child misbehavior to children's intentions and dismiss situational factors tend to show more hostility and less warmth in their parenting behavior, and are at greater risk for maltreatment. We extended this literature by investigating the role of household chaos as a moderator of the link between maternal attribution biases and parenting behaviors. Design The current sample included 160 mothers of 3- to7-year-old children. Mothers provided reports on their attribution biases and household chaos levels. Maternal negativity and positivity were measured using self-reports and observers’ ratings. Results The links between attribution bias and parenting behavior were stronger in more chaotic environments, with the moderating effect of chaos being particularly strong for internal attribution bias. Conclusions The findings point to the importance of social cognitive biases in the etiology of maternal behavior in family contexts that lack order and predictability. PMID:24358017
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A new method for mapping perceptual biases across visual space.
Finlayson, Nonie J; Papageorgiou, Andriani; Schwarzkopf, D Samuel
2017-08-01
How we perceive the environment is not stable and seamless. Recent studies found that how a person qualitatively experiences even simple visual stimuli varies dramatically across different locations in the visual field. Here we use a method we developed recently that we call multiple alternatives perceptual search (MAPS) for efficiently mapping such perceptual biases across several locations. This procedure reliably quantifies the spatial pattern of perceptual biases and also of uncertainty and choice. We show that these measurements are strongly correlated with those from traditional psychophysical methods and that exogenous attention can skew biases without affecting overall task performance. Taken together, MAPS is an efficient method to measure how an individual's perceptual experience varies across space.
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A Developmental Neuroscience Perspective on Affect-Biased Attention
Morales, Santiago; Fu, Xiaoxue; Pérez-Edgar, Koraly E.
2016-01-01
There is growing interest regarding the impact of affect-biased attention on psychopathology. However, most of the research to date lacks a developmental approach. In the present review, we examine the role affect-biased attention plays in shaping socioemotional trajectories within a developmental neuroscience framework. We propose that affect-biased attention, particularly if stable and entrenched, acts as a developmental tether that helps sustain early socioemotional and behavioral profiles over time, placing some individuals on maladaptive developmental trajectories. Although most of the evidence is found in the anxiety literature, we suggest that these relations may operate across multiple domains of interest, including positive affect, externalizing behaviors, drug use, and eating behaviors. We also review the general mechanisms and neural correlates of affect-biased attention, as well as the current evidence for the co-development of attention and affect. Based on the reviewed literature, we propose a model that may help us better understand the nuances of affect-biased attention across development. The model may serve as a strong foundation for ongoing attempts to identify neurocognitive mechanisms and intervene with individuals at risk. Finally, we discuss open issues for future research that may help bridge existing gaps in the literature. PMID:27606972
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International Nuclear Information System (INIS)
Coninck, Heleen de; Stephens, Jennie C.; Metz, Bert
2009-01-01
Closing the gap between carbon dioxide capture and storage (CCS) rhetoric and technical progress is critically important to global climate mitigation efforts. Developing strong international cooperation on CCS demonstration with global coordination, transparency, cost-sharing and communication as guiding principles would facilitate efficient and cost-effective collaborative global learning on CCS, would allow for improved understanding of the global capacity and applicability of CCS, and would strengthen global trust, awareness and public confidence in the technology.
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Directory of Open Access Journals (Sweden)
Jingyi Lu
2018-05-01
Full Text Available People frequently judge how they are viewed by others during social interactions. These judgments are called metaperceptions. This study investigates the relationship between eagerness to determine the evaluation of others and metaperceptions. We propose that eagerness, which reflects approach motivation, induces positive emotions. We apply feelings-as-information theory and hypothesize that positive emotions cause optimistic self-evaluations and metaperceptions. Participants in three studies interact with judges during a singing contest (Study 1, a speech (Study 2, and an interview (Study 3. Results corroborate that eagerness to learn the evaluation of others is overall related to optimistically biased metaperceptions. This effect is mediated sequentially by positive emotions, optimistic self-evaluations, and increased metaperceptions.
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Nakhaeizadeh, Sherry; Dror, Itiel E; Morgan, Ruth M
2014-05-01
An experimental study was designed to examine cognitive biases within forensic anthropological non-metric methods in assessing sex, ancestry and age at death. To investigate examiner interpretation, forty-one non-novice participants were semi randomly divided into three groups. Prior to conducting the assessment of the skeletal remains, two of the groups were given different extraneous contextual information regarding the sex, ancestry and age at death of the individual. The third group acted as a control group with no extraneous contextual information. The experiment was designed to investigate if the interpretation and conclusions of the skeletal remains would differ amongst participants within the three groups, and to assess whether the examiners would confirm or disagree with the given extraneous context when establishing a biological profile. The results revealed a significant biasing effect within the three groups, demonstrating a strong confirmation bias in the assessment of sex, ancestry and age at death. In assessment of sex, 31% of the participants in the control group concluded that the skeleton remains were male. In contrast, in the group that received contextual information that the remains were male, 72% concluded that the remains were male, and in the participant group where the context was that the remains were of a female, 0% of the participants concluded that the remains were male. Comparable results showing bias were found in assessing ancestry and age at death. These data demonstrate that cognitive bias can impact forensic anthropological non-metric methods on skeletal remains and affects the interpretation and conclusions of the forensic scientists. This empirical study is a step in establishing an evidence base approach for dealing with cognitive issues in forensic anthropological assessments, so as to enhance this valuable forensic science discipline. Copyright © 2013 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights
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Feldmann-Wüstefeld, Tobias; Uengoer, Metin; Schubö, Anna
2015-11-01
Besides visual salience and observers' current intention, prior learning experience may influence deployment of visual attention. Associative learning models postulate that observers pay more attention to stimuli previously experienced as reliable predictors of specific outcomes. To investigate the impact of learning experience on deployment of attention, we combined an associative learning task with a visual search task and measured event-related potentials of the EEG as neural markers of attention deployment. In the learning task, participants categorized stimuli varying in color/shape with only one dimension being predictive of category membership. In the search task, participants searched a shape target while disregarding irrelevant color distractors. Behavioral results showed that color distractors impaired performance to a greater degree when color rather than shape was predictive in the learning task. Neurophysiological results show that the amplified distraction was due to differential attention deployment (N2pc). Experiment 2 showed that when color was predictive for learning, color distractors captured more attention in the search task (ND component) and more suppression of color distractor was required (PD component). The present results thus demonstrate that priority in visual attention is biased toward predictive stimuli, which allows learning experience to shape selection. We also show that learning experience can overrule strong top-down control (blocked tasks, Experiment 3) and that learning experience has a longer-term effect on attention deployment (tasks on two successive days, Experiment 4). © 2015 Society for Psychophysiological Research.
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Language experience changes subsequent learning
Onnis, Luca; Thiessen, Erik
2013-01-01
What are the effects of experience on subsequent learning? We explored the effects of language-specific word order knowledge on the acquisition of sequential conditional information. Korean and English adults were engaged in a sequence learning task involving three different sets of stimuli: auditory linguistic (nonsense syllables), visual non-linguistic (nonsense shapes), and auditory non-linguistic (pure tones). The forward and backward probabilities between adjacent elements generated two equally probable and orthogonal perceptual parses of the elements, such that any significant preference at test must be due to either general cognitive biases, or prior language-induced biases. We found that language modulated parsing preferences with the linguistic stimuli only. Intriguingly, these preferences are congruent with the dominant word order patterns of each language, as corroborated by corpus analyses, and are driven by probabilistic preferences. Furthermore, although the Korean individuals had received extensive formal explicit training in English and lived in an English-speaking environment, they exhibited statistical learning biases congruent with their native language. Our findings suggest that mechanisms of statistical sequential learning are implicated in language across the lifespan, and experience with language may affect cognitive processes and later learning. PMID:23200510
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The basis of shooter biases: beyond cultural stereotypes.
Miller, Saul L; Zielaskowski, Kate; Plant, E Ashby
2012-10-01
White police officers and undergraduate students mistakenly shoot unarmed Black suspects more than White suspects on computerized shoot/don't shoot tasks. This bias is typically attributed to cultural stereotypes of Black men. Yet, previous research has not examined whether such biases emerge even in the absence of cultural stereotypes. The current research investigates whether individual differences in chronic beliefs about interpersonal threat interact with target group membership to elicit shooter biases, even when group membership is unrelated to race or cultural stereotypes about danger. Across two studies, participants with strong beliefs about interpersonal threats were more likely to mistakenly shoot outgroup members than ingroup members; this was observed for unfamiliar, arbitrarily formed groups using a minimal group paradigm (Study 1) and racial groups not culturally stereotyped as dangerous (Asians; Study 2). Implications for the roles of both group membership and cultural stereotypes in shaping decisions to shoot are discussed.
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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
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Mechanisms of value-learning in the guidance of spatial attention.
Anderson, Brian A; Kim, Haena
2018-05-11
The role of associative reward learning in the guidance of feature-based attention is well established. The extent to which reward learning can modulate spatial attention has been much more controversial. At least one demonstration of a persistent spatial attention bias following space-based associative reward learning has been reported. At the same time, multiple other experiments have been published failing to demonstrate enduring attentional biases towards locations at which a target, if found, yields high reward. This is in spite of evidence that participants use reward structures to inform their decisions where to search, leading some to suggest that, unlike feature-based attention, spatial attention may be impervious to the influence of learning from reward structures. Here, we demonstrate a robust bias towards regions of a scene that participants were previously rewarded for selecting. This spatial bias relies on representations that are anchored to the configuration of objects within a scene. The observed bias appears to be driven specifically by reinforcement learning, and can be observed with equal strength following non-reward corrective feedback. The time course of the bias is consistent with a transient shift of attention, rather than a strategic search pattern, and is evident in eye movement patterns during free viewing. Taken together, our findings reconcile previously conflicting reports and offer an integrative account of how learning from feedback shapes the spatial attention system. Copyright © 2018 Elsevier B.V. All rights reserved.
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Evolutionary thinking in microeconomic models: prestige bias and market bubbles.
Directory of Open Access Journals (Sweden)
Adrian Viliami Bell
Full Text Available Evolutionary models broadly support a number of social learning strategies likely important in economic behavior. Using a simple model of price dynamics, I show how prestige bias, or copying of famed (and likely successful individuals, influences price equilibria and investor disposition in a way that exacerbates or creates market bubbles. I discuss how integrating the social learning and demographic forces important in cultural evolution with economic models provides a fruitful line of inquiry into real-world behavior.
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Social biases determine spatiotemporal sparseness of ciliate mating heuristics.
Clark, Kevin B
2012-01-01
Ciliates become highly social, even displaying animal-like qualities, in the joint presence of aroused conspecifics and nonself mating pheromones. Pheromone detection putatively helps trigger instinctual and learned courtship and dominance displays from which social judgments are made about the availability, compatibility, and fitness representativeness or likelihood of prospective mates and rivals. In earlier studies, I demonstrated the heterotrich Spirostomum ambiguum improves mating competence by effecting preconjugal strategies and inferences in mock social trials via behavioral heuristics built from Hebbian-like associative learning. Heuristics embody serial patterns of socially relevant action that evolve into ordered, topologically invariant computational networks supporting intra- and intermate selection. S. ambiguum employs heuristics to acquire, store, plan, compare, modify, select, and execute sets of mating propaganda. One major adaptive constraint over formation and use of heuristics involves a ciliate's initial subjective bias, responsiveness, or preparedness, as defined by Stevens' Law of subjective stimulus intensity, for perceiving the meaningfulness of mechanical pressures accompanying cell-cell contacts and additional perimating events. This bias controls durations and valences of nonassociative learning, search rates for appropriate mating strategies, potential net reproductive payoffs, levels of social honesty and deception, successful error diagnosis and correction of mating signals, use of insight or analysis to solve mating dilemmas, bioenergetics expenditures, and governance of mating decisions by classical or quantum statistical mechanics. I now report this same social bias also differentially affects the spatiotemporal sparseness, as measured with metric entropy, of ciliate heuristics. Sparseness plays an important role in neural systems through optimizing the specificity, efficiency, and capacity of memory representations. The present
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Social biases determine spatiotemporal sparseness of ciliate mating heuristics
2012-01-01
Ciliates become highly social, even displaying animal-like qualities, in the joint presence of aroused conspecifics and nonself mating pheromones. Pheromone detection putatively helps trigger instinctual and learned courtship and dominance displays from which social judgments are made about the availability, compatibility, and fitness representativeness or likelihood of prospective mates and rivals. In earlier studies, I demonstrated the heterotrich Spirostomum ambiguum improves mating competence by effecting preconjugal strategies and inferences in mock social trials via behavioral heuristics built from Hebbian-like associative learning. Heuristics embody serial patterns of socially relevant action that evolve into ordered, topologically invariant computational networks supporting intra- and intermate selection. S. ambiguum employs heuristics to acquire, store, plan, compare, modify, select, and execute sets of mating propaganda. One major adaptive constraint over formation and use of heuristics involves a ciliate’s initial subjective bias, responsiveness, or preparedness, as defined by Stevens’ Law of subjective stimulus intensity, for perceiving the meaningfulness of mechanical pressures accompanying cell-cell contacts and additional perimating events. This bias controls durations and valences of nonassociative learning, search rates for appropriate mating strategies, potential net reproductive payoffs, levels of social honesty and deception, successful error diagnosis and correction of mating signals, use of insight or analysis to solve mating dilemmas, bioenergetics expenditures, and governance of mating decisions by classical or quantum statistical mechanics. I now report this same social bias also differentially affects the spatiotemporal sparseness, as measured with metric entropy, of ciliate heuristics. Sparseness plays an important role in neural systems through optimizing the specificity, efficiency, and capacity of memory representations. The
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Carpenter, Gail A; Gaddam, Sai Chaitanya
2010-04-01
Memories in Adaptive Resonance Theory (ART) networks are based on matched patterns that focus attention on those portions of bottom-up inputs that match active top-down expectations. While this learning strategy has proved successful for both brain models and applications, computational examples show that attention to early critical features may later distort memory representations during online fast learning. For supervised learning, biased ARTMAP (bARTMAP) solves the problem of over-emphasis on early critical features by directing attention away from previously attended features after the system makes a predictive error. Small-scale, hand-computed analog and binary examples illustrate key model dynamics. Two-dimensional simulation examples demonstrate the evolution of bARTMAP memories as they are learned online. Benchmark simulations show that featural biasing also improves performance on large-scale examples. One example, which predicts movie genres and is based, in part, on the Netflix Prize database, was developed for this project. Both first principles and consistent performance improvements on all simulation studies suggest that featural biasing should be incorporated by default in all ARTMAP systems. Benchmark datasets and bARTMAP code are available from the CNS Technology Lab Website: http://techlab.bu.edu/bART/. Copyright 2009 Elsevier Ltd. All rights reserved.
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Human language reveals a universal positivity bias.
Dodds, Peter Sheridan; Clark, Eric M; Desu, Suma; Frank, Morgan R; Reagan, Andrew J; Williams, Jake Ryland; Mitchell, Lewis; Harris, Kameron Decker; Kloumann, Isabel M; Bagrow, James P; Megerdoomian, Karine; McMahon, Matthew T; Tivnan, Brian F; Danforth, Christopher M
2015-02-24
Using human evaluation of 100,000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language, observing that (i) the words of natural human language possess a universal positivity bias, (ii) the estimated emotional content of words is consistent between languages under translation, and (iii) this positivity bias is strongly independent of frequency of word use. Alongside these general regularities, we describe interlanguage variations in the emotional spectrum of languages that allow us to rank corpora. We also show how our word evaluations can be used to construct physical-like instruments for both real-time and offline measurement of the emotional content of large-scale texts.
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Empirical Comparison of Publication Bias Tests in Meta-Analysis.
Lin, Lifeng; Chu, Haitao; Murad, Mohammad Hassan; Hong, Chuan; Qu, Zhiyong; Cole, Stephen R; Chen, Yong
2018-04-16
Decision makers rely on meta-analytic estimates to trade off benefits and harms. Publication bias impairs the validity and generalizability of such estimates. The performance of various statistical tests for publication bias has been largely compared using simulation studies and has not been systematically evaluated in empirical data. This study compares seven commonly used publication bias tests (i.e., Begg's rank test, trim-and-fill, Egger's, Tang's, Macaskill's, Deeks', and Peters' regression tests) based on 28,655 meta-analyses available in the Cochrane Library. Egger's regression test detected publication bias more frequently than other tests (15.7% in meta-analyses of binary outcomes and 13.5% in meta-analyses of non-binary outcomes). The proportion of statistically significant publication bias tests was greater for larger meta-analyses, especially for Begg's rank test and the trim-and-fill method. The agreement among Tang's, Macaskill's, Deeks', and Peters' regression tests for binary outcomes was moderately strong (most κ's were around 0.6). Tang's and Deeks' tests had fairly similar performance (κ > 0.9). The agreement among Begg's rank test, the trim-and-fill method, and Egger's regression test was weak or moderate (κ < 0.5). Given the relatively low agreement between many publication bias tests, meta-analysts should not rely on a single test and may apply multiple tests with various assumptions. Non-statistical approaches to evaluating publication bias (e.g., searching clinical trials registries, records of drug approving agencies, and scientific conference proceedings) remain essential.
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Expanding Possibilities through Metaphor: Breaking Biases to Improve Crisis Management
Cirka, Carol C.; Corrigall, Elizabeth A.
2010-01-01
In this article, we demonstrate that an exercise using metaphors to overcome cognitive biases helped students to proactively imagine and prepare for an expanded set of potential crises. The exercise complements traditional textbook approaches to crisis management and incorporates creativity skill building in a realistic context. Learning outcomes…
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Computer-Mediated Counter-Arguments and Individual Learning
Hsu, Jack Shih-Chieh; Huang, Hsieh-Hong; Linden, Lars P.
2011-01-01
This study explores a de-bias function for a decision support systems (DSS) that is designed to help a user avoid confirmation bias by increasing the user's learning opportunities. Grounded upon the theory of mental models, the use of DSS is viewed as involving a learning process, whereby a user is directed to build mental models so as to reduce…
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Learning from Failed Decisions
Nutt, Paul C.
2010-01-01
The consequences and dilemmas posed by learning issues for decision making are discussed. Learning requires both awareness of barriers and a coping strategy. The motives to hold back information essential for learning stem from perverse incentives, obscure outcomes, and the hindsight bias. There is little awareness of perverse incentives that…
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Growth hormone biases amygdala network activation after fear learning
Gisabella, Barbara; Farah, Shadia; Peng, Xiaoyu; Burgos-Robles, Anthony Noel; Lim, Seh Hong; Goosens, Ki Ann
2016-01-01
Prolonged stress exposure is a risk factor for developing posttraumatic stress disorder, a disorder characterized by the ?over-encoding' of a traumatic experience. A potential mechanism by which this occurs is through upregulation of growth hormone (GH) in the amygdala. Here we test the hypotheses that GH promotes the over-encoding of fearful memories by increasing the number of neurons activated during memory encoding and biasing the allocation of neuronal activation, one aspect of the proce...
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Diagnostics for the Biased Electrode Experiment on NSTX
International Nuclear Information System (INIS)
Roquemore, A.L.; Zweben, S.J.; Bush, C.E.; Kaita, R.; Marsalsa, R.J.; Maqueda, R.J.
2009-01-01
A linear array of four small biased electrodes was installed in NSTX in an attempt to control the width of the scrape-off layer (SOL) by creating a strong local poloidal electric field. The set of electrodes were separated poloidally by a 1 cm gap between electrodes and were located slightly below the midplane of NSTX, 1 cm behind the RF antenna and oriented so that each electrode is facing approximately normal to the magnetic field. Each electrode can be independently biased to ± 100 volts. Present power supplies limit the current on two electrodes to 30 amps the other two to 10 amps each. The effect of local biasing was measured with a set of Langmuir probes placed between the electrodes and another set extending radially outward from the electrodes, and also by the gas puff imaging diagnostic (GPI) located 1 m away along the magnetic field lines intersecting the electrodes. Two fast cameras were also aimed directly at the electrode array. The hardware and controls of the biasing experiment will be presented and the initial effects on local plasma parameters will be discussed
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A comparator-hypothesis account of biased contingency detection.
Vadillo, Miguel A; Barberia, Itxaso
2018-02-12
Our ability to detect statistical dependencies between different events in the environment is strongly biased by the number of coincidences between them. Even when there is no true covariation between a cue and an outcome, if the marginal probability of either of them is high, people tend to perceive some degree of statistical contingency between both events. The present paper explores the ability of the Comparator Hypothesis to explain the general pattern of results observed in this literature. Our simulations show that this model can account for the biasing effects of the marginal probabilities of cues and outcomes. Furthermore, the overall fit of the Comparator Hypothesis to a sample of experimental conditions from previous studies is comparable to that of the popular Rescorla-Wagner model. These results should encourage researchers to further explore and put to the test the predictions of the Comparator Hypothesis in the domain of biased contingency detection. Copyright © 2018 Elsevier B.V. All rights reserved.
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Gender bias in leader evaluations: merging implicit theories and role congruity perspectives.
Hoyt, Crystal L; Burnette, Jeni L
2013-10-01
This research extends our understanding of gender bias in leader evaluations by merging role congruity and implicit theory perspectives. We tested and found support for the prediction that the link between people's attitudes regarding women in authority and their subsequent gender-biased leader evaluations is significantly stronger for entity theorists (those who believe attributes are fixed) relative to incremental theorists (those who believe attributes are malleable). In Study 1, 147 participants evaluated male and female gubernatorial candidates. Results supported predictions, demonstrating that traditional attitudes toward women in authority significantly predicted a pro-male gender bias in leader evaluations (and progressive attitudes predicted a pro-female gender bias) with an especially strong effect for those with more entity-oriented, relative to incrementally oriented person theories. Study 2 (119 participants) replicated these findings and demonstrated the mediating role of these attitudes in linking gender stereotypes and leader role expectations to biased evaluations.
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DEFF Research Database (Denmark)
Kutchinsky, Jonatan; Wildt, Morten; Taboryski, Rafael Jozef
1999-01-01
A biased superconductor-normal metal-superconductor junction is known to be a strong nonequilibrium system, where Andreev scattering at the interfaces creates a quasiparticle distribution function far from equilibrium, a manifestation of this is the well-known subgap structure in the I...
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Energy Technology Data Exchange (ETDEWEB)
Dorosz, P., E-mail: pdorosz@agh.edu.pl [AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Electronics, 30-059 Krakow (Poland); Baszczyk, M.; Glab, S. [AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Electronics, 30-059 Krakow (Poland); Kucewicz, W., E-mail: kucewicz@agh.edu.pl [AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Electronics, 30-059 Krakow (Poland); Mik, L.; Sapor, M. [AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Electronics, 30-059 Krakow (Poland)
2013-08-01
Gain of the silicon photomultiplier is strongly dependent on the value of bias voltage and temperature. This paper proposes a method for gain stabilization just by compensation of temperature fluctuations by bias correction. It has been confirmed that this approach gives good results and the gain can be kept very stable.
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Impact of chlorophyll bias on the tropical Pacific mean climate in an earth system model
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.
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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.
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Bias modification training can alter approach bias and chocolate consumption.
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.
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Kobza, Stefan; Ferrea, Stefano; Schnitzler, Alfons; Pollok, Bettina; Südmeyer, Martin; Bellebaum, Christian
2012-01-01
Feedback to both actively performed and observed behaviour allows adaptation of future actions. Positive feedback leads to increased activity of dopamine neurons in the substantia nigra, whereas dopamine neuron activity is decreased following negative feedback. Dopamine level reduction in unmedicated Parkinson's Disease patients has been shown to lead to a negative learning bias, i.e. enhanced learning from negative feedback. Recent findings suggest that the neural mechanisms of active and observational learning from feedback might differ, with the striatum playing a less prominent role in observational learning. Therefore, it was hypothesized that unmedicated Parkinson's Disease patients would show a negative learning bias only in active but not in observational learning. In a between-group design, 19 Parkinson's Disease patients and 40 healthy controls engaged in either an active or an observational probabilistic feedback-learning task. For both tasks, transfer phases aimed to assess the bias to learn better from positive or negative feedback. As expected, actively learning patients showed a negative learning bias, whereas controls learned better from positive feedback. In contrast, no difference between patients and controls emerged for observational learning, with both groups showing better learning from positive feedback. These findings add to neural models of reinforcement-learning by suggesting that dopamine-modulated input to the striatum plays a minor role in observational learning from feedback. Future research will have to elucidate the specific neural underpinnings of observational learning.
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Sensorimotor learning biases choice behavior: a learning neural field model for decision making.
Directory of Open Access Journals (Sweden)
Christian Klaes
Full Text Available According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action
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International Nuclear Information System (INIS)
Woo, C.H.; Garner, F.A.
1991-11-01
A new concept of point-defect production as the main driving force for void swelling under cascade damage conditions is proposed. This concept takes into account the recombination and formation of immobile clusters and loops of vacancies and interstitials in the cascade region. The life times of the clusters and loops due to desolution are strong functions of the temperature, as well as their vacancy and interstitial nature. The resulting biased production of free point defects from the internal sources is shown to be a strong driving force for void swelling. The characteristics of void swelling due to production bias are described and compared with experimental results. We conclude that the production bias concept provides a good description of void swelling under cascade damage conditions
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International Nuclear Information System (INIS)
Woo, C.H.; Singh, B.N.; Garner, F.A.
1992-01-01
A new concept of point defect production as the main driving force for void swelling under cascade damage conditions is proposed. This concept takes into account the recombination and formation of immobile clusters and loops of vacancies and interstitials in the cascade region. The lifetimes of the clusters and loops due to desolution are strong functions of the temperature, as well as their vacancy and interstitial nature. The resulting biased production of free point defects from the internal sources is shown to be a strong driving force for void swelling. The characteristics of void swelling due to production bias are described and compared with experimental results. We conclude that the production bias concept provides a good description of void swelling under cascade damage conditions. (orig.)
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Contingency bias in probability judgement may arise from ambiguity regarding additional causes.
Mitchell, Chris J; Griffiths, Oren; More, Pranjal; Lovibond, Peter F
2013-09-01
In laboratory contingency learning tasks, people usually give accurate estimates of the degree of contingency between a cue and an outcome. However, if they are asked to estimate the probability of the outcome in the presence of the cue, they tend to be biased by the probability of the outcome in the absence of the cue. This bias is often attributed to an automatic contingency detection mechanism, which is said to act via an excitatory associative link to activate the outcome representation at the time of testing. We conducted 3 experiments to test alternative accounts of contingency bias. Participants were exposed to the same outcome probability in the presence of the cue, but different outcome probabilities in the absence of the cue. Phrasing the test question in terms of frequency rather than probability and clarifying the test instructions reduced but did not eliminate contingency bias. However, removal of ambiguity regarding the presence of additional causes during the test phase did eliminate contingency bias. We conclude that contingency bias may be due to ambiguity in the test question, and therefore it does not require postulation of a separate associative link-based mechanism.
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Methodological flaws introduce strong bias into molecular analysis of microbial populations.
Krakat, N; Anjum, R; Demirel, B; Schröder, P
2017-02-01
In this study, we report how different cell disruption methods, PCR primers and in silico analyses can seriously bias results from microbial population studies, with consequences for the credibility and reproducibility of the findings. Our results emphasize the pitfalls of commonly used experimental methods that can seriously weaken the interpretation of results. Four different cell lysis methods, three commonly used primer pairs and various computer-based analyses were applied to investigate the microbial diversity of a fermentation sample composed of chicken dung. The fault-prone, but still frequently used, amplified rRNA gene restriction analysis was chosen to identify common weaknesses. In contrast to other studies, we focused on the complete analytical process, from cell disruption to in silico analysis, and identified potential error rates. This identified a wide disagreement of results between applied experimental approaches leading to very different community structures depending on the chosen approach. The interpretation of microbial diversity data remains a challenge. In order to accurately investigate the taxonomic diversity and structure of prokaryotic communities, we suggest a multi-level approach combining DNA-based and DNA-independent techniques. The identified weaknesses of commonly used methods to study microbial diversity can be overcome by a multi-level approach, which produces more reliable data about the fate and behaviour of microbial communities of engineered habitats such as biogas plants, so that the best performance can be ensured. © 2016 The Society for Applied Microbiology.
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Combination of biased forecasts: Bias correction or bias based weights?
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.
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A Variational Approach to Simultaneous Image Segmentation and Bias Correction.
Zhang, Kaihua; Liu, Qingshan; Song, Huihui; Li, Xuelong
2015-08-01
This paper presents a novel variational approach for simultaneous estimation of bias field and segmentation of images with intensity inhomogeneity. We model intensity of inhomogeneous objects to be Gaussian distributed with different means and variances, and then introduce a sliding window to map the original image intensity onto another domain, where the intensity distribution of each object is still Gaussian but can be better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying the bias field with a piecewise constant signal within the sliding window. A maximum likelihood energy functional is then defined on each local region, which combines the bias field, the membership function of the object region, and the constant approximating the true signal from its corresponding object. The energy functional is then extended to the whole image domain by the Bayesian learning approach. An efficient iterative algorithm is proposed for energy minimization, via which the image segmentation and bias field correction are simultaneously achieved. Furthermore, the smoothness of the obtained optimal bias field is ensured by the normalized convolutions without extra cost. Experiments on real images demonstrated the superiority of the proposed algorithm to other state-of-the-art representative methods.
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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...
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Intervention strength does not differentially affect memory reconsolidation of strong memories.
van Schie, Kevin; van Veen, Suzanne C; Hendriks, Yanniek R; van den Hout, Marcel A; Engelhard, Iris M
2017-10-01
Recently, it has become clear that retrieval (i.e., reactivation) of consolidated memories may return these memories into a labile state before they are restored into long-term memory ('reconsolidation'). Using behavioral manipulations, reactivated memories can be disrupted via the mechanism of novel learning. In the present study, we investigated whether changing a strong memory during reconsolidation depends on the strength of novel learning. To test this, participants (N=144) in six groups acquired a relatively strong memory on Day 1 by viewing and recalling a series of pictures three times. On Day 8, these pictures were reactivated in three groups, and they were not reactivated in the other three groups. Then, participants viewed and recalled new pictures once (weak new learning) or three times (strong new learning), or they did not learn any new pictures. On Day 9, participants performed a recognition test in which their memory for Day 1 pictures was assessed. Two main results are noted. First, the groups that reactivated pictures from Day 1 and received weak or strong new learning did not differ in memory performance. Second, these two groups consistently performed similar to groups that controlled for new learning without reactivation. Because these results contradict what was expected based on the reconsolidation hypothesis, we discuss possible explanations and implications. Copyright © 2017 Elsevier Inc. All rights reserved.
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Richardson, John T E
2010-12-01
The attainment of White students at UK institutions of higher education tends to be higher than that of students from other ethnic groups, but the causes of this are unclear. This study compared White students and students from other ethnic groups in their conceptions of learning, their approaches to studying, and their academic attainment. A stratified sample of 1,146 White students and 1,146 students from other ethnic groups taking courses by distance learning with the UK Open University. The Mental Models section of the Inventory of Learning Styles and the Revised Approaches to Studying Inventory were administered in a postal survey. The students' questionnaire scores were contaminated by response bias, which varied across different ethnic groups. When adjusted to control for response bias, the scores on the two questionnaires shared 37.2% of their variance and made a significant contribution to predicting the students' attainment. White students were more likely to exhibit a meaning-directed learning pattern, whereas Asian and Black students were more likely to exhibit a reproduction-directed learning pattern. However, the variation in attainment across different ethnic groups remained significant when their questionnaire scores and prior qualifications were taken into account. There is a strong relationship between students' conceptions of learning and their approaches to studying, and variations in conceptions of learning in different ethnic groups give rise to variations in approaches to studying. However, factors other than prior qualifications and conceptions of learning are responsible for variation in attainment across different ethnic groups.
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Eden, Annuschka Salima; Zwitserlood, Pienie; Keuper, Katharina; Junghöfer, Markus; Laeger, Inga; Zwanzger, Peter; Dobel, Christian
2014-01-01
The well-established memory bias for arousing-negative stimuli seems to be enhanced in high trait-anxious persons and persons suffering from anxiety disorders. We monitored the emergence and development of such a bias during and after learning, in high and low trait anxious participants. A word-learning paradigm was applied, consisting of spoken pseudowords paired either with arousing-negative or neutral pictures. Learning performance during training evidenced a short-lived advantage for arou...
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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.
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Artificial neuron-glia networks learning approach based on cooperative coevolution.
Mesejo, Pablo; Ibáñez, Oscar; Fernández-Blanco, Enrique; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana B
2015-06-01
Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated method, their performance against the traditional approach, i.e. without artificial astrocytes, was already demonstrated on classification problems. However, the corresponding learning algorithms developed so far strongly depends on a set of glial parameters which are manually tuned for each specific problem. As a consequence, previous experimental tests have to be done in order to determine an adequate set of values, making such manual parameter configuration time-consuming, error-prone, biased and problem dependent. Thus, in this paper, we propose a novel learning approach for ANGNs that fully automates the learning process, and gives the possibility of testing any kind of reasonable parameter configuration for each specific problem. This new learning algorithm, based on coevolutionary genetic algorithms, is able to properly learn all the ANGNs parameters. Its performance is tested on five classification problems achieving significantly better results than ANGN and competitive results with ANN approaches.
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Who Benefits from Mastery Learning?
Lai, Patrick; Biggs, John
1994-01-01
Data from 95 educationally disadvantaged Hong Kong students placed in mastery-learning classes were compared with 64 control students in expository-learning classes. Results indicate that under mastery learning, deep- and surface-biased learners increasingly diverge in performance and attitude, with surface learners doing better unit to unit, and…
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Parenting Practices, Interpretive Biases, and Anxiety in Latino Children
Varela, R. Enrique; Niditch, Laura A.; Hensley-Maloney, Lauren; Moore, Kathryn W.; Creveling, C. Christiane
2013-01-01
A number of factors are believed to confer risk for anxiety development in children; however, cultural variation of purported risk factors remains unclear. We examined relations between controlling and rejecting parenting styles, parental modeling of anxious behaviors, child interpretive biases, and child anxiety in a mixed clinically anxious (n = 27) and non-clinical (n = 20) sample of Latino children and at least one of their parents. Families completed discussion-based tasks and questionnaires in a lab setting. Results indicated that child anxiety was: linked with parental control and child interpretative biases; associated with parental modeling of anxious behaviors at a trend level; and not associated with low parental acceptance. Findings that controlling parenting and child interpretive biases were associated with anxiety extend current theories of anxiety development to the Latino population. We speculate that strong family ties may buffer Latino children from detrimental effects of perceived low parental acceptance. PMID:23434545
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Can YouTube enhance student nurse learning?
Clifton, Andrew; Mann, Claire
2011-05-01
The delivery of nurse education has changed radically in the past two decades. Increasingly, nurse educators are using new technology in the classroom to enhance their teaching and learning. One recent technological development to emerge is the user-generated content website YouTube. Originally YouTube was used as a repository for sharing home-made videos, more recently online content is being generated by political parties, businesses and educationalists. We recently delivered a module to undergraduate student nurses in which the teaching and learning were highly populated with YouTube resources. We found that the use of YouTube videos increased student engagement, critical awareness and facilitated deep learning. Furthermore, these videos could be accessed at any time of the day and from a place to suit the student. We acknowledge that there are some constraints to using YouTube for teaching and learning particularly around the issue of unregulated content which is often misleading, inaccurate or biased. However, we strongly urge nurse educators to consider using YouTube for teaching and learning, in and outside the classroom, to a generation of students who are native of a rapidly changing digital world. Copyright © 2010 Elsevier Ltd. All rights reserved.
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Directory of Open Access Journals (Sweden)
Janice A Sabin
Full Text Available Overweight patients report weight discrimination in health care settings and subsequent avoidance of routine preventive health care. The purpose of this study was to examine implicit and explicit attitudes about weight among a large group of medical doctors (MDs to determine the pervasiveness of negative attitudes about weight among MDs. Test-takers voluntarily accessed a public Web site, known as Project Implicit®, and opted to complete the Weight Implicit Association Test (IAT (N = 359,261. A sub-sample identified their highest level of education as MD (N = 2,284. Among the MDs, 55% were female, 78% reported their race as white, and 62% had a normal range BMI. This large sample of test-takers showed strong implicit anti-fat bias (Cohen's d = 1.0. MDs, on average, also showed strong implicit anti-fat bias (Cohen's d = 0.93. All test-takers and the MD sub-sample reported a strong preference for thin people rather than fat people or a strong explicit anti-fat bias. We conclude that strong implicit and explicit anti-fat bias is as pervasive among MDs as it is among the general public. An important area for future research is to investigate the association between providers' implicit and explicit attitudes about weight, patient reports of weight discrimination in health care, and quality of care delivered to overweight patients.
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Sampling bias in climate-conflict research
Adams, Courtland; Ide, Tobias; Barnett, Jon; Detges, Adrien
2018-03-01
Critics have argued that the evidence of an association between climate change and conflict is flawed because the research relies on a dependent variable sampling strategy1-4. Similarly, it has been hypothesized that convenience of access biases the sample of cases studied (the `streetlight effect'5). This also gives rise to claims that the climate-conflict literature stigmatizes some places as being more `naturally' violent6-8. Yet there has been no proof of such sampling patterns. Here we test whether climate-conflict research is based on such a biased sample through a systematic review of the literature. We demonstrate that research on climate change and violent conflict suffers from a streetlight effect. Further, studies which focus on a small number of cases in particular are strongly informed by cases where there has been conflict, do not sample on the independent variables (climate impact or risk), and hence tend to find some association between these two variables. These biases mean that research on climate change and conflict primarily focuses on a few accessible regions, overstates the links between both phenomena and cannot explain peaceful outcomes from climate change. This could result in maladaptive responses in those places that are stigmatized as being inherently more prone to climate-induced violence.
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Visual search attentional bias modification reduced social phobia in adolescents.
De Voogd, E L; Wiers, R W; Prins, P J M; Salemink, E
2014-06-01
An attentional bias for negative information plays an important role in the development and maintenance of (social) anxiety and depression, which are highly prevalent in adolescence. Attention Bias Modification (ABM) might be an interesting tool in the prevention of emotional disorders. The current study investigated whether visual search ABM might affect attentional bias and emotional functioning in adolescents. A visual search task was used as a training paradigm; participants (n = 16 adolescents, aged 13-16) had to repeatedly identify the only smiling face in a 4 × 4 matrix of negative emotional faces, while participants in the control condition (n = 16) were randomly allocated to one of three placebo training versions. An assessment version of the task was developed to directly test whether attentional bias changed due to the training. Self-reported anxiety and depressive symptoms and self-esteem were measured pre- and post-training. After two sessions of training, the ABM group showed a significant decrease in attentional bias for negative information and self-reported social phobia, while the control group did not. There were no effects of training on depressive mood or self-esteem. No correlation between attentional bias and social phobia was found, which raises questions about the validity of the attentional bias assessment task. Also, the small sample size precludes strong conclusions. Visual search ABM might be beneficial in changing attentional bias and social phobia in adolescents, but further research with larger sample sizes and longer follow-up is needed. Copyright © 2013 Elsevier Ltd. All rights reserved.
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International Nuclear Information System (INIS)
Duan Linglong
2008-01-01
Pure Ti films were fabricated by bias sputtering. The deposition rate, the density and the surface topography of the Ti films at different negative bias were studied. The results show that the deposition rate is weakly affected when the bias power is low. As the bias voltage increases, the deposition rate decreases strongly due to the increase of the layer density and the resputtering phenomena. The film density increased and saturated to nearly bulk value at a bias voltage of -119.1 V. SEM view indicates that the columnar-type structure of Ti films can be destroyed by applying negative bias. The experiments demonstrated that a dense Ti film with more smooth surface can be produced by applying negative bias. (authors)
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Auditory hindsight bias: Fluency misattribution versus memory reconstruction.
Higham, Philip A; Neil, Greg J; Bernstein, Daniel M
2017-06-01
We report 4 experiments investigating auditory hindsight bias-the tendency to overestimate the intelligibility of distorted auditory stimuli after learning their identity. An associative priming manipulation was used to vary the amount of processing fluency independently of prior target knowledge. For hypothetical designs, in which hindsight judgments are made for peers in foresight, we predicted that judgments would be based on processing fluency and that hindsight bias would be greater in the unrelated- compared to related-prime context (differential-fluency hypothesis). Conversely, for memory designs, in which foresight judgments are remembered in hindsight, we predicted that judgments would be based on memory reconstruction and that there would be independent effects of prime relatedness and prior target knowledge (recollection hypothesis). These predictions were confirmed. Specifically, we found support for the differential-fluency hypothesis when a hypothetical design was used in Experiments 1 and 2 (hypothetical group). Conversely, when a memory design was used in Experiments 2 (memory group), 3A, and 3B, we found support for the recollection hypothesis. Together, the results suggest that qualitatively different mechanisms create hindsight bias in the 2 designs. The results are discussed in terms of fluency misattributions, memory reconstruction, anchoring-and-adjustment, sense making, and a multicomponent model of hindsight bias. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Enhanced exchange bias in MnN/CoFe bilayers after high-temperature annealing
Dunz, M.; Schmalhorst, J.; Meinert, M.
2018-05-01
We report an exchange bias of more than 2700 Oe at room temperature in MnN/CoFe bilayers after high-temperature annealing. We studied the dependence of exchange bias on the annealing temperature for different MnN thicknesses in detail and found that samples with tMnN > 32nm show an increase of exchange bias for annealing temperatures higher than TA = 400 °C. Maximum exchange bias values exceeding 2000 Oe with reasonably small coercive fields around 600 Oe are achieved for tMnN = 42, 48 nm. The median blocking temperature of those systems is determined to be 180 °C after initial annealing at TA = 525 °C. X-ray diffraction measurements and Auger depth profiling show that the large increase of exchange bias after high-temperature annealing is accompanied by strong nitrogen diffusion into the Ta buffer layer of the stacks.
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Attentional Bias Associated with Habitual Self-Stigma in People with Mental Illness.
Chan, Kevin K S; Mak, Winnie W S
2015-01-01
As habitual self-stigma can have a tremendous negative impact on people with mental illness, it is of paramount importance to identify its risk factors. The present study aims to examine the potential contributory role of attentional bias in habitual self-stigma. People with mental illness having strong (n = 47) and weak (n = 47) habitual self-stigma completed a computerized emotional Stroop task which included stigma-related, positive, and non-affective words as stimuli. The strong habit group was found to exhibit faster color-naming of stigma-related words (compared to non-affective words), whereas the weak habit group showed no difference in the speed of response to different stimuli. These findings suggest that people with stronger habitual self-stigma may be more able to ignore the semantic meaning of stigma-related words and focus on the color-naming task. Moreover, people with stronger habitual self-stigma may have greater attentional avoidance of stigma-related material. The present study is the first to demonstrate a specific relationship between habitual self-stigma and biased processing of stigma-related information. In order to further determine the role and the nature of attentional bias in habitual self-stigma, future research should employ a broader range of experimental paradigms and measurement techniques to examine stigma-related attentional bias in people with mental illness.
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Directional bias of illusory stream caused by relative motion adaptation.
Tomimatsu, Erika; Ito, Hiroyuki
2016-07-01
Enigma is an op-art painting that elicits an illusion of rotational streaming motion. In the present study, we tested whether adaptation to various motion configurations that included relative motion components could be reflected in the directional bias of the illusory stream. First, participants viewed the center of a rotating Enigma stimulus for adaptation. There was no physical motion on the ring area. During the adaptation period, the illusory stream on the ring was mainly seen in the direction opposite to that of the physical rotation. After the physical rotation stopped, the illusory stream on the ring was mainly seen in the same direction as that of the preceding physical rotation. Moreover, adapting to strong relative motion induced a strong bias in the illusory motion direction in the subsequently presented static Enigma stimulus. The results suggest that relative motion detectors corresponding to the ring area may produce the illusory stream of Enigma. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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A Classroom Demonstration of Potential Biases in the Subjective Interpretation of Projective Tests.
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)
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Forward-biased nanophotonic detector for ultralow-energy dissipation receiver
Nozaki, Kengo; Matsuo, Shinji; Fujii, Takuro; Takeda, Koji; Shinya, Akihiko; Kuramochi, Eiichi; Notomi, Masaya
2018-04-01
Generally, reverse-biased photodetectors (PDs) are used for high-speed optical receivers. The forward voltage region is only utilized in solar-cells, and this photovoltaic operation would not be concurrently obtained with high efficiency and high speed operation. Here we report that photonic-crystal waveguide PDs enable forward-biased high-speed operation at 40 Gbit/s with keeping high responsivity (0.88 A/W). Within our knowledge, this is the first demonstration of the forward-biased PDs with high responsivity. This achievement is attributed to the ultracompactness of our PD and the strong light confinement within the absorber and depleted regions, thereby enabling efficient photo-carrier generation and fast extraction. This result indicates that it is possible to construct a high-speed and ultracompact photo-receiver without an electrical amplifier nor an external bias circuit. Since there is no electrical energy required, our estimation shows that the consumption energy is just the optical energy of the injected signal pulse which is about 1 fJ/bit. Hence, it will lead to an ultimately efficient and highly integrable optical-to-electrical converter in a chip, which will be a key ingredient for dense nanophotonic communication and processors.
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Forward-biased nanophotonic detector for ultralow-energy dissipation receiver
Directory of Open Access Journals (Sweden)
Kengo Nozaki
2018-04-01
Full Text Available Generally, reverse-biased photodetectors (PDs are used for high-speed optical receivers. The forward voltage region is only utilized in solar-cells, and this photovoltaic operation would not be concurrently obtained with high efficiency and high speed operation. Here we report that photonic-crystal waveguide PDs enable forward-biased high-speed operation at 40 Gbit/s with keeping high responsivity (0.88 A/W. Within our knowledge, this is the first demonstration of the forward-biased PDs with high responsivity. This achievement is attributed to the ultracompactness of our PD and the strong light confinement within the absorber and depleted regions, thereby enabling efficient photo-carrier generation and fast extraction. This result indicates that it is possible to construct a high-speed and ultracompact photo-receiver without an electrical amplifier nor an external bias circuit. Since there is no electrical energy required, our estimation shows that the consumption energy is just the optical energy of the injected signal pulse which is about 1 fJ/bit. Hence, it will lead to an ultimately efficient and highly integrable optical-to-electrical converter in a chip, which will be a key ingredient for dense nanophotonic communication and processors.
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Energy Technology Data Exchange (ETDEWEB)
Lu Jianduo, E-mail: l_j316@163.co [Hubei Province Key Laboratory of Systems Science in Metallurgical Process, Wuhan University of Science and Technology, Wuhan 430081 (China); Li Yunbao; Yun Meijuan [Hubei Province Key Laboratory of Systems Science in Metallurgical Process, Wuhan University of Science and Technology, Wuhan 430081 (China); Zheng Wei [Key Laboratory of Dynamic Geodesy, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077 (China)
2011-03-28
We investigate the effect of the bias in an electron-spin filter based on a two-dimensional electron gas modulated by ferromagnetic-Schottky metal stripes. The numerical results show that the electron transmission and the conductance as well as the spin polarization are strongly dependent on the bias applied to the device. - Research highlights: We propose a bias-tunable electron-spin filter. The transmission and the conductance depend on the bias and the electron energy. The spin polarization depends on the bias and the electron energy. The results are helpful for making new types of bias-tunable spin filters.
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A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.
Ben Taieb, Souhaib; Atiya, Amir F
2016-01-01
Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.
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Collisson, Beverly Anne; Grela, Bernard; Spaulding, Tammie; Rueckl, Jay G; Magnuson, James S
2015-05-01
We investigated whether preschool children with specific language impairment (SLI) exhibit the shape bias in word learning: the bias to generalize based on shape rather than size, color, or texture in an object naming context ('This is a wek; find another wek') but not in a non-naming similarity classification context ('See this? Which one goes with this one?'). Fifty-four preschool children (16 with SLI, 16 children with typical language [TL] in an equated control group, and 22 additional children with TL included in individual differences analyses but not group comparisons) completed a battery of linguistic and cognitive assessments and two experiments. In Experiment 1, children made generalization choices in object naming and similarity classification contexts on separate days, from options similar to a target object in shape, color, or texture. On average, TL children exhibited the shape bias in an object naming context, but children with SLI did not. In Experiment 2, we tested whether the failure to exhibit the shape bias might be linked to ability to detect systematicities in the visual domain. Experiment 2 supported this hypothesis, in that children with SLI failed to learn simple paired visual associations that were readily learned by children with TL. Analyses of individual differences in the two studies revealed that visual paired-associate learning predicted degree of shape bias in children with SLI and TL better than any other measure of nonverbal intelligence or standard assessments of language ability. We discuss theoretical and clinical implications. © 2014 John Wiley & Sons Ltd.
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Age-differences in cognitive flexibility when overcoming a preexisting bias through feedback.
Wilson, Cristina G; Nusbaum, Amy T; Whitney, Paul; Hinson, John M
2018-08-01
Older adults are often worse than younger adults at adapting to changing situational demands, and this difference is commonly attributed to an age-related decline in acquiring and updating information. Previous research on aging and cognitive flexibility has used measures that require adapting to novel associations learned during a laboratory task (e.g., choice X led to positive outcomes but now leads to negative outcomes). However, in everyday life people must frequently overcome associations based on preexisting beliefs and biases (e.g., you like to eat cake, but your doctor said to limit your sugar intake). The goal of the present study was to examine possible age-differences in overcoming a preexisting bias and determine whether age-related changes in the acquisition and updating of information influence this form of flexibility. Older (n = 20) and younger (n = 20) adults completed a novel task in which repeated choices were made between a sure option (gain or loss) and one of two risky options that were initially ambiguous. Optimal performance required overcoming a framing bias toward being risk seeking to avoid a sure loss and risk averse when offered a sure gain. Probe questions assessed knowledge of choice outcomes, while skin conductance assessed physiological reactions to choices and choice outcomes. Both older and younger adults demonstrated flexibility by reducing the impact of bias over trials, but younger adults had better performance overall. Age-differences were associated with distinct aspects of processing. Young adults had more precise knowledge of choice outcomes and developed skin conductance responses in anticipation of bad choices that were not apparent in older adults. Older adults showed significant improvement over trials in their ability to decrease bias-driven choices, but younger showed greater flexibility. Age-differences in task performance were based on differences in learning and corresponding representations of task
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Parenting practices, interpretive biases, and anxiety in Latino children.
Varela, R Enrique; Niditch, Laura A; Hensley-Maloney, Lauren; Moore, Kathryn W; Creveling, C Christiane
2013-03-01
A number of factors are believed to confer risk for anxiety development in children; however, cultural variation of purported risk factors remains unclear. We examined relations between controlling and rejecting parenting styles, parental modeling of anxious behaviors, child interpretive biases, and child anxiety in a mixed clinically anxious (n=27) and non-clinical (n=20) sample of Latino children and at least one of their parents. Families completed discussion-based tasks and questionnaires in a lab setting. Results indicated that child anxiety was: linked with parental control and child interpretative biases, associated with parental modeling of anxious behaviors at a trend level, and not associated with low parental acceptance. Findings that controlling parenting and child interpretive biases were associated with anxiety extend current theories of anxiety development to the Latino population. We speculate that strong family ties may buffer Latino children from detrimental effects of perceived low parental acceptance. Copyright © 2013 Elsevier Ltd. All rights reserved.
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New Trends in Magnetic Exchange Bias
Mougin, Alexandra; Mangin, Stéphane; Bobo, Jean-Francois; Loidl, Alois
2005-05-01
The study of layered magnetic structures is one of the hottest topics in magnetism due to the growing attraction of applications in magnetic sensors and magnetic storage media, such as random access memory. For almost half a century, new discoveries have driven researchers to re-investigate magnetism in thin film structures. Phenomena such as giant magnetoresistance, tunneling magnetoresistance, exchange bias and interlayer exchange coupling led to new ideas to construct devices, based not only on semiconductors but on a variety of magnetic materials Upon cooling fine cobalt particles in a magnetic field through the Néel temperature of their outer antiferromagnetic oxide layer, Meiklejohn and Bean discovered exchange bias in 1956. The exchange bias effect through which an antiferromagnetic AF layer can cause an adjacent ferromagnetic F layer to develop a preferred direction of magnetization, is widely used in magnetoelectronics technology to pin the magnetization of a device reference layer in a desired direction. However, the origin and effects due to exchange interaction across the interface between antiferromagneic and ferromagnetic layers are still debated after about fifty years of research, due to the extreme difficulty associated with the determination of the magnetic interfacial structure in F/AF bilayers. Indeed, in an AF/F bilayer system, the AF layer acts as “the invisible man” during conventional magnetic measurements and the presence of the exchange coupling is evidenced indirectly through the unusual behavior of the adjacent F layer. Basically, the coercive field of the F layer increases in contact with the AF and, in some cases, its hysteresis loop is shifted by an amount called exchange bias field. Thus, AF/F exchange coupling generates a new source of anisotropy in the F layer. This induced anisotropy strongly depends on basic features such as the magnetocrystalline anisotropy, crystallographic and spin structures, defects, domain patterns etc
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Gong, Tao; Lam, Yau W; Shuai, Lan
2016-01-01
Psychological experiments have revealed that in normal visual perception of humans, color cues are more salient than shape cues, which are more salient than textural patterns. We carried out an artificial language learning experiment to study whether such perceptual saliency hierarchy (color > shape > texture) influences the learning of orders regulating adjectives of involved visual features in a manner either congruent (expressing a salient feature in a salient part of the form) or incongruent (expressing a salient feature in a less salient part of the form) with that hierarchy. Results showed that within a few rounds of learning participants could learn the compositional segments encoding the visual features and the order between them, generalize the learned knowledge to unseen instances with the same or different orders, and show learning biases for orders that are congruent with the perceptual saliency hierarchy. Although the learning performances for both the biased and unbiased orders became similar given more learning trials, our study confirms that this type of individual perceptual constraint could contribute to the structural configuration of language, and points out that such constraint, as well as other factors, could collectively affect the structural diversity in languages.
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Gong, Tao; Lam, Yau W.; Shuai, Lan
2016-01-01
Psychological experiments have revealed that in normal visual perception of humans, color cues are more salient than shape cues, which are more salient than textural patterns. We carried out an artificial language learning experiment to study whether such perceptual saliency hierarchy (color > shape > texture) influences the learning of orders regulating adjectives of involved visual features in a manner either congruent (expressing a salient feature in a salient part of the form) or incongruent (expressing a salient feature in a less salient part of the form) with that hierarchy. Results showed that within a few rounds of learning participants could learn the compositional segments encoding the visual features and the order between them, generalize the learned knowledge to unseen instances with the same or different orders, and show learning biases for orders that are congruent with the perceptual saliency hierarchy. Although the learning performances for both the biased and unbiased orders became similar given more learning trials, our study confirms that this type of individual perceptual constraint could contribute to the structural configuration of language, and points out that such constraint, as well as other factors, could collectively affect the structural diversity in languages. PMID:28066281
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The central tendency bias in color perception: effects of internal and external noise.
Olkkonen, Maria; McCarthy, Patrice F; Allred, Sarah R
2014-09-05
Perceptual estimates can be biased by previously seen stimuli in delayed estimation tasks. These biases are often toward the mean of the whole stimulus set. Recently, we demonstrated such a central tendency bias in delayed color estimation. In the Bayesian framework of perceptual inference, perceptual biases arise when noisy sensory measurements are combined with prior information about the world. Here, we investigate this idea in color perception by manipulating stimulus range and stimulus noise while characterizing delayed color estimates. First, we manipulated the experimental prior for stimulus color by embedding stimuli in collections with different hue ranges. Stimulus range affected hue bias: Hue estimates were always biased toward the mean of the current set. Next, we studied the effect of internal and external noise on the amount of hue bias. Internal noise was manipulated by increasing the delay between the reference and test from 0.4 to 4 s. External noise was manipulated by increasing the amount of chromatic noise in the reference stimulus, while keeping the delay between the reference and test constant at 2 s. Both noise manipulations had a reliable effect on the strength of the central tendency bias. Furthermore, there was a tendency for a positive relationship between variability of the estimates and bias in both noise conditions. In conclusion, observers are able to learn an experimental hue prior, and the weight on the prior can be manipulated by introducing noise in the estimation process. © 2014 ARVO.
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Biased signaling of G protein-coupled receptors - From a chemokine receptor CCR7 perspective
DEFF Research Database (Denmark)
Jørgensen, Astrid Sissel; Rosenkilde, Mette M; Hjortø, Gertrud M
2018-01-01
of CCL21 displays an extraordinarily strong glycosaminoglycan (GAG) binding, CCR7 plays a central role in coordinating the meeting between mature antigen presenting DCs and naïve T-cells which normally takes place in the lymph nodes (LNs). This process is a prerequisite for the initiation of an antigen...... the cell-based immune system is controlled. Bias comes in three forms; ligand-, receptor- and tissue-bias. Biased signaling is increasingly being recognized as playing an important role in contributing to the fine-tuned coordination of immune cell chemotaxis. In the current review we discuss the recent...
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Scale-dependent bias from the reconstruction of non-Gaussian distributions
International Nuclear Information System (INIS)
Chongchitnan, Sirichai; Silk, Joseph
2011-01-01
Primordial non-Gaussianity introduces a scale-dependent variation in the clustering of density peaks corresponding to rare objects. This variation, parametrized by the bias, is investigated on scales where a linear perturbation theory is sufficiently accurate. The bias is obtained directly in real space by comparing the one- and two-point probability distributions of density fluctuations. We show that these distributions can be reconstructed using a bivariate Edgeworth series, presented here up to an arbitrarily high order. The Edgeworth formalism is shown to be well-suited for ''local'' cubic-order non-Gaussianity parametrized by g NL . We show that a strong scale dependence in the bias can be produced by g NL of order 10 5 , consistent with cosmic microwave background constraints. On a separation length of ∼100 Mpc, current constraints on g NL still allow the bias for the most massive clusters to be enhanced by 20-30% of the Gaussian value. We further examine the bias as a function of mass scale, and also explore the relationship between the clustering and the abundance of massive clusters in the presence of g NL . We explain why the Edgeworth formalism, though technically challenging, is a very powerful technique for constraining high-order non-Gaussianity with large-scale structures.
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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.
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Electronic transport in Thue-Morse gapped graphene superlattice under applied bias
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.
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Modulation of low-frequency oscillations in GaAs MESFETs' channel current by sidegating bias
Institute of Scientific and Technical Information of China (English)
DING Yong; LU Shengli; ZHAO Fuchuan
2005-01-01
Low-frequency oscillations in channel current are usually observed when measuring the GaAs MESFET's output characteristics. This paper studies the oscillations by testing the MESFET's output characteristics under different sidegate bias conditions. It is shown that the low-frequency oscillations of channel current are directly related to the sidegate bias. In other words, the sidegate bias can modulate the oscillations. Whether the sidegate bias varies positively or negatively, there will inevitably be a threshold voltage after which the low-frequency oscillations disappear. The observation is strongly dependent upon the peculiarities of channel-substrate (C-S) junction and impact ionization of traps-EL2 under high field. This conclusion is of particular pertinence to the design of low-noise GaAs IC's.
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E-learning for health professionals.
Vaona, Alberto; Banzi, Rita; Kwag, Koren H; Rigon, Giulio; Cereda, Danilo; Pecoraro, Valentina; Tramacere, Irene; Moja, Lorenzo
2018-01-21
The use of e-learning, defined as any educational intervention mediated electronically via the Internet, has steadily increased among health professionals worldwide. Several studies have attempted to measure the effects of e-learning in medical practice, which has often been associated with large positive effects when compared to no intervention and with small positive effects when compared with traditional learning (without access to e-learning). However, results are not conclusive. To assess the effects of e-learning programmes versus traditional learning in licensed health professionals for improving patient outcomes or health professionals' behaviours, skills and knowledge. We searched CENTRAL, MEDLINE, Embase, five other databases and three trial registers up to July 2016, without any restrictions based on language or status of publication. We examined the reference lists of the included studies and other relevant reviews. If necessary, we contacted the study authors to collect additional information on studies. Randomised trials assessing the effectiveness of e-learning versus traditional learning for health professionals. We excluded non-randomised trials and trials involving undergraduate health professionals. Two authors independently selected studies, extracted data and assessed risk of bias. We graded the certainty of evidence for each outcome using the GRADE approach and standardised the outcome effects using relative risks (risk ratio (RR) or odds ratio (OR)) or standardised mean difference (SMD) when possible. We included 16 randomised trials involving 5679 licensed health professionals (4759 mixed health professionals, 587 nurses, 300 doctors and 33 childcare health consultants).When compared with traditional learning at 12-month follow-up, low-certainty evidence suggests that e-learning may make little or no difference for the following patient outcomes: the proportion of patients with low-density lipoprotein (LDL) cholesterol of less than 100 mg
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Petukhov, A M; Yu Soldatov, E
2017-01-01
Separation of electroweak component from strong component of associated Zγ production on hadron colliders is a very challenging task due to identical final states of such processes. The only difference is the origin of two leading jets in these two processes. Rectangular cuts on jet kinematic variables from ATLAS/CMS 8 TeV Zγ experimental analyses were improved using machine learning techniques. New selection variables were also tested. The expected significance of separation for LHC experime...
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Use of bias sputtering to enhance decoupling in oxide composite perpendicular recording media
International Nuclear Information System (INIS)
Lee, Hwan-Soo; Bain, James A.; Laughlin, David E.
2007-01-01
The effects of substrate bias on two types of oxide composite perpendicular recording media CoCrPt-SiO 2 and FePt-MgO were investigated. The use of substrate bias greatly modified the thin film microstructure and resulted in the enhanced grain decoupling in the films. The growth characteristics due to preferential resputtering were interpreted to arise mainly from weak surface bonding to the growing films for nontextured growth, combined with strong cohesion for the textured growth
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Woud, Marcella L.; Maas, Joyce; Wiers, Reinout W.; Becker, Eni S.; Rinck, Mike
2016-01-01
According to theories of addictive behaviors, approach and attentional biases toward smoking-related cues play a crucial role in tobacco dependence. Several studies have investigated these biases by using various paradigms in different sample types. However, this heterogeneity makes it difficult to compare and evaluate the results. The present study aimed to address this problem, via (i) a structural comparison of different measures of approach-avoidance and a measure of smoking-related attentional biases, and (ii) using within one study different representative samples in the context of tobacco dependence. Three measures of approach-avoidance were employed: an Approach Avoidance Task (AAT), a Stimulus Response Compatibility Task (SRC), and a Single Target Implicit Association Test (ST-IAT). To assess attentional biases, a modified Stroop task including smoking-related words was administered. The study included four groups: n = 58 smokers, n = 57 non-smokers, n = 52 cravers, and n = 54 ex-smokers. We expected to find strong tobacco-related approach biases and attentional biases in smokers and cravers. However, the general pattern of results did not confirm these expectations. Approach responses assessed during the AAT and SRC did not differ between groups. Moreover, the Stroop did not show the expected interference effect. For the ST-IAT, cravers had stronger approach associations toward smoking-related cues, whereas non-smokers showed stronger avoidance associations. However, no such differences in approach-avoidance associations were found in smokers and ex-smokers. To conclude, these data do not provide evidence for a strong role of implicit approach and attentional biases toward smoking-related cues in tobacco dependency. PMID:26955359
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Directory of Open Access Journals (Sweden)
Adrian Meule
2016-05-01
Full Text Available Strong bottom-up impulses and weak top-down control may interactively lead to overeating and, consequently, weight gain. In the present study, female university freshmen were tested at the start of the first semester and again at the start of the second semester. Attentional bias toward high- or low-calorie food-cues was assessed using a dot-probe paradigm and participants completed the Barratt Impulsiveness Scale . Attentional bias and motor impulsivity interactively predicted change in body mass index: motor impulsivity positively predicted weight gain only when participants showed an attentional bias toward high-calorie food-cues. Attentional and non-planning impulsivity were unrelated to weight change. Results support findings showing that weight gain is prospectively predicted by a combination of weak top-down control (i.e. high impulsivity and strong bottom-up impulses (i.e. high automatic motivational drive toward high-calorie food stimuli. They also highlight the fact that only specific aspects of impulsivity are relevant in eating and weight regulation.
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Analysis of bias effects on the total ionizing dose response in a 180 nm technology
International Nuclear Information System (INIS)
Liu Zhangli; Hu Zhiyuan; Zhang, Zhengxuan; Shao Hua; Chen Ming; Bi Dawei; Ning Bingxu; Zou Shichang
2011-01-01
The effects of gamma ray irradiation on the shallow trench isolation (STI) leakage current in a 180 nm technology are investigated. The radiation response is strongly influenced by the bias modes, gate bias during irradiation, substrate bias during irradiation and operating substrate bias after irradiation. We found that the worst case occurs under the ON bias condition for the ON, OFF and PASS bias mode. A positive gate bias during irradiation significantly enhances the STI leakage current, indicating the electric field influence on the charge buildup process during radiation. Also, a negative substrate bias during irradiation enhances the STI leakage current. However a negative operating substrate bias effectively suppresses the STI leakage current, and can be used to eliminate the leakage current produced by the charge trapped in the deep STI oxide. Appropriate substrate bias should be introduced to alleviate the total ionizing dose (TID) response, and lead to acceptable threshold voltage shift and subthreshold hump effect. Depending on the simulation results, we believe that the electric field distribution in the STI oxide is the key parameter influencing bias effects on the radiation response of transistor. - Highlights: → ON bias is the worst bias condition for the ON, PASS and OFF bias modes. → Larger gate bias during irradiation leads to more pronounced characteristic degradation. → TID induced STI leakage can be suppressed by negative operating substrate bias voltage. → Negative substrate bias during irradiation leads to larger increase of off-state leakage. → Electric field in the STI oxide greatly influences the device's radiation effect.
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Reward associations magnify memory-based biases on perception.
Doallo, Sonia; Patai, Eva Zita; Nobre, Anna Christina
2013-02-01
Long-term spatial contextual memories are a rich source of predictions about the likely locations of relevant objects in the environment and should enable tuning of neural processing of unfolding events to optimize perception and action. Of particular importance is whether and how the reward outcome of past events can impact perception. We combined behavioral measures with recordings of brain activity with high temporal resolution to test whether the previous reward outcome associated with a memory could modulate the impact of memory-based biases on perception, and if so, the level(s) at which visual neural processing is biased by reward-associated memory-guided attention. Data showed that past rewards potentiate the effects of spatial memories upon the discrimination of target objects embedded within complex scenes starting from early perceptual stages. We show that a single reward outcome of learning impacts on how we perceive events in our complex environments.
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Strategies in probabilistic feedback learning in Parkinson patients OFF medication.
Bellebaum, C; Kobza, S; Ferrea, S; Schnitzler, A; Pollok, B; Südmeyer, M
2016-04-21
Studies on classification learning suggested that altered dopamine function in Parkinson's Disease (PD) specifically affects learning from feedback. In patients OFF medication, enhanced learning from negative feedback has been described. This learning bias was not seen in observational learning from feedback, indicating different neural mechanisms for this type of learning. The present study aimed to compare the acquisition of stimulus-response-outcome associations in PD patients OFF medication and healthy control subjects in active and observational learning. 16 PD patients OFF medication and 16 controls were examined with three parallel learning tasks each, two feedback-based (active and observational) and one non-feedback-based paired associates task. No acquisition deficit was seen in the patients for any of the tasks. More detailed analyses on the learning strategies did, however, reveal that the patients showed more lose-shift responses during active feedback learning than controls, and that lose-shift and win-stay responses more strongly determined performance accuracy in patients than controls. For observational feedback learning, the performance of both groups correlated similarly with the performance in non-feedback-based paired associates learning and with the accuracy of observed performance. Also, patients and controls showed comparable evidence of feedback processing in observational learning. In active feedback learning, PD patients use alternative learning strategies than healthy controls. Analyses on observational learning did not yield differences between patients and controls, adding to recent evidence of a differential role of the human striatum in active and observational learning from feedback. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Trofimova, Ira
2014-01-01
The lexical approach is a method in differential psychology that uses people's estimations of verbal descriptors of human behavior in order to derive the structure of human individuality. The validity of the assumptions of this method about the objectivity of people's estimations is rarely questioned. Meanwhile the social nature of language and the presence of emotionality biases in cognition are well-recognized in psychology. A question remains, however, as to whether such an emotionality-capacities bias is strong enough to affect semantic perception of verbal material. For the lexical approach to be valid as a method of scientific investigations, such biases should not exist in semantic perception of the verbal material that is used by this approach. This article reports on two studies investigating differences between groups contrasted by 12 temperament traits (i.e. by energetic and other capacities, as well as emotionality) in the semantic perception of very general verbal material. Both studies contrasted the groups by a variety of capacities: endurance, lability and emotionality separately in physical, social-verbal and mental aspects of activities. Hypotheses of “background emotionality” and a “projection through capacities” were supported. Non-evaluative criteria for categorization (related to complexity, organization, stability and probability of occurrence of objects) followed the polarity of evaluative criteria, and did not show independence from this polarity. Participants with stronger physical or social endurance gave significantly more positive ratings to a variety of concepts, and participants with faster physical tempo gave more positive ratings to timing-related concepts. The results suggest that people's estimations of lexical material related to human behavior have emotionality, language- and dynamical capacities-related biases and therefore are unreliable. This questions the validity of the lexical approach as a method for the objective
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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.
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Exchange bias in finite sized NiO nanoparticles with Ni clusters
International Nuclear Information System (INIS)
Gandhi, Ashish Chhaganlal; Lin, Jauyn Grace
2017-01-01
Structural and magnetic properties of finite sized NiO nanoparticles are investigated with synchrotron X-ray diffraction (XRD), transmission electron microscopy, magnetometer and ferromagnetic resonance (FMR) spectroscopy. A minor Ni phase is detected with synchrotron XRD, attributed to the oxygen defects in the NiO core. A considerable exchange bias of ~100 Oe is observed at 50 K and it drops abruptly and vanishes above 150 K, in association with the reduction of frozen spins. FMR data indicate a strong interaction between ferromagnetic (FM) and antiferromagnetic (AFM) phases below 150 K, consistent with the picture of isolated FM clusters in AFM matrix. - Highlights: • Structural and magnetic properties of finite sized NiO nanoparticles are systematically investigated with several advanced techniques. • A strong interaction between ferromagnetic and antiferromagnetic phases is found below 150 K. • Exchange bias field in finite sized NiO nanoparticles is due to anisotropy energy of Ni clusters over riding the domain wall energy of NiO.
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Exchange bias in finite sized NiO nanoparticles with Ni clusters
Energy Technology Data Exchange (ETDEWEB)
Gandhi, Ashish Chhaganlal; Lin, Jauyn Grace, E-mail: jglin@ntu.edu.tw
2017-02-15
Structural and magnetic properties of finite sized NiO nanoparticles are investigated with synchrotron X-ray diffraction (XRD), transmission electron microscopy, magnetometer and ferromagnetic resonance (FMR) spectroscopy. A minor Ni phase is detected with synchrotron XRD, attributed to the oxygen defects in the NiO core. A considerable exchange bias of ~100 Oe is observed at 50 K and it drops abruptly and vanishes above 150 K, in association with the reduction of frozen spins. FMR data indicate a strong interaction between ferromagnetic (FM) and antiferromagnetic (AFM) phases below 150 K, consistent with the picture of isolated FM clusters in AFM matrix. - Highlights: • Structural and magnetic properties of finite sized NiO nanoparticles are systematically investigated with several advanced techniques. • A strong interaction between ferromagnetic and antiferromagnetic phases is found below 150 K. • Exchange bias field in finite sized NiO nanoparticles is due to anisotropy energy of Ni clusters over riding the domain wall energy of NiO.
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Mismeasurement and the resonance of strong confounders: correlated errors.
Marshall, J R; Hastrup, J L; Ross, J S
1999-07-01
Confounding in epidemiology, and the limits of standard methods of control for an imperfectly measured confounder, have been understood for some time. However, most treatments of this problem are based on the assumption that errors of measurement in confounding and confounded variables are independent. This paper considers the situation in which a strong risk factor (confounder) and an inconsequential but suspected risk factor (confounded) are each measured with errors that are correlated; the situation appears especially likely to occur in the field of nutritional epidemiology. Error correlation appears to add little to measurement error as a source of bias in estimating the impact of a strong risk factor: it can add to, diminish, or reverse the bias induced by measurement error in estimating the impact of the inconsequential risk factor. Correlation of measurement errors can add to the difficulty involved in evaluating structures in which confounding and measurement error are present. In its presence, observed correlations among risk factors can be greater than, less than, or even opposite to the true correlations. Interpretation of multivariate epidemiologic structures in which confounding is likely requires evaluation of measurement error structures, including correlations among measurement errors.
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Directory of Open Access Journals (Sweden)
Poppy eWatson
2012-10-01
Full Text Available Human behavior can be paradoxical, in that actions can be initiated that are seemingly incongruent with an individual’s explicit desires. This is most commonly observed in drug addiction, where maladaptive behavior (i.e. drug seeking appears to be compulsive, continuing at great personal cost. Approach biases towards addictive substances have been correlated with actual drug-use in a number of studies, suggesting that this measure can, in some cases, index everyday maladaptive tendencies. At present it is unclear whether this bias to drug cues is a Pavlovian conditioned approach response, a habitual response, the result of a Pavlovian-instrumental transfer process or a goal-directed action in the sense that expectancy of the rewarding effects of drugs controls approach. We consider this question by combining the theoretical framework of associative learning with the available evidence from approach bias research. Although research investigating the relative contributions of these mechanisms to the approach bias is to date relatively limited, we review existing studies and also outline avenues for future research.
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Watson, P; de Wit, S; Hommel, Bernhard; Wiers, R W
2012-01-01
Human behavior can be paradoxical, in that actions can be initiated that are seemingly incongruent with an individual's explicit desires. This is most commonly observed in drug addiction, where maladaptive behavior (i.e., drug seeking) appears to be compulsive, continuing at great personal cost. Approach biases toward addictive substances have been correlated with actual drug-use in a number of studies, suggesting that this measure can, in some cases, index everyday maladaptive tendencies. At present it is unclear whether this bias to drug cues is a Pavlovian conditioned approach response, a habitual response, the result of a Pavlovian-instrumental transfer process, or a goal-directed action in the sense that expectancy of the rewarding effects of drugs controls approach. We consider this question by combining the theoretical framework of associative learning with the available evidence from approach bias research. Although research investigating the relative contributions of these mechanisms to the approach bias is to date relatively limited, we review existing studies and also outline avenues for future research.
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Wang, Z; Deater-Deckard, K; Bell, M A
2013-10-01
Parents who attribute child misbehavior to children's intentions and dismiss situational factors tend to show more hostility and less warmth in their parenting behavior, and are at greater risk for maltreatment. We extended this literature by investigating the role of household chaos as a moderator of the link between maternal attribution biases and parenting behaviors. The current sample included 160 mothers of 3- to7-year-old children. Mothers provided reports on their attribution biases and household chaos levels. Maternal negativity and positivity were measured using self-reports and observers' ratings. The links between attribution bias and parenting behavior were stronger in more chaotic environments, with the moderating effect of chaos being particularly strong for internal attribution bias. The findings point to the importance of social cognitive biases in the etiology of maternal behavior in family contexts that lack order and predictability.
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International Nuclear Information System (INIS)
2008-08-01
The International Workshop on Lessons Learned from Strong Earthquake was held at Kashiwazaki civic plaza, Kashiwazaki, Niigata-prefecture, Japan, for three days in June 2008. Kashiwazaki-Kariwa NPP (KK-NPP) is located in the city of Kashiwazaki and the village of Kariwa, and owned and operated by Tokyo Electric Power Company Ltd. (TEPCO). After it experienced the Niigata-ken Chuetsu-oki earthquake in July 2007, IAEA dispatched experts' missions twice and held technical discussions with TEPCO. Through such activities, the IAEA secretariat and experts obtained up-dated information of plant integrity, geological and seismological evaluation and developments of the consultation in the regulatory framework of Japan. Some of the information has been shared with the member states through the reports on findings and lessons learned from the missions to Japan. The international workshop was held to discuss and share the information of lessons learned from strong earthquakes in member states' nuclear installations. It provided the opportunity for participants from abroad to share the information of the recent earthquake and experience in Japan and to visit KK-NPP. And for experts in Japan, the workshop provided the opportunity to share the international approach on seismic-safety-related measures and experiences. The workshop was organised by the IAEA as a part of an extra budgetary project, in cooperation with OECD/NEA, hosted by Japanese organisations including Nuclear and Industrial Safety Agency (NISA), Nuclear Safety Commission (NSC), and Japan Nuclear Energy Safety Organization (JNES). The number of the workshop participants was 70 experts from outside Japan, 27 countries and 2 international organisations, 154 Japanese experts and 81 audience and media personnel, totalling to 305 participants. The three-day workshop was open to the media including the site visit, and covered by NHK (the nation's public broadcasting corporation) and nation-wide and local television
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End effect Keff bias curve for actinide-only burnup credit casks
International Nuclear Information System (INIS)
Kang, C.H.; Lancaster, D.B.
1997-01-01
A conservative end effect k eff bias curve for actinide-only burnup credit for spent fuel casks is presented in this paper. The k eff bias values can be added to the uniform axial burnup analysis to conservatively bound the actinide-only end effect. A normalized axial burnup distribution for the standard Westinghouse 17 x 17 assembly design is used for calculating k eff . The end effect calculated is a strong function of burnup, and increases as cask size size decreases. The presence of poison plates increases the end effect. The bias curve presented is based on the most limiting cask configuration of a single PWR assembly with completely black poison plates. Therefore, axially uniform criticality calculations with application of the proposed k eff could eliminate the need for axially burnup dependent analyses. 7 refs., 1 fig
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Aging Electorates, Intergenerational Fairness and Pro-Elderly Policy Bias
DEFF Research Database (Denmark)
Vanhuysse, Pieter
2015-01-01
change provides urgent arguments for (re)activating the fiscal and human capital basis of aging welfare states and for investing in early human capital. But the institutional complexities and context-dependencies of generational politics do not justify blanket generational blame games.......This article reviews the state of the art in comparative politics and political sociology on the interplay between population aging and public policies in OECD democracies. It discusses findings from the Intergenerational Justice Index (IJI) - a simple four-dimensional indicator developed......) whereas the fourth dimension measures policy inputs in the form of welfare states’ overall pro-elderly spending bias. I argue that demography is not destiny: good policy design strongly mediates the direct influence of population aging on pro-elderly policy bias and intergenerational equity. Demographic...
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Impurity-induced anisotropic semiconductor-semimetal transition in monolayer biased black phosphorus
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.
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A Systematic Review of Attention Biases in Opioid, Cannabis, Stimulant Use Disorders.
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
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Beyond assembly bias: exploring secondary halo biases for cluster-size haloes
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.
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<strong>Neuroeconomics and Human Resource Developmentstrong>
DEFF Research Database (Denmark)
Larsen, Torben
2009-01-01
Neuroeconomics and Human Resource Development Objective Neuroeconomic game trials have detected a present-bias in human decision making which represents a serious shortcoming facing the long termed nature of complex problems in a globalized economy i.e. regional residual poverty, ecological...... threats and personal stress. So far, the evidence-based findings on human resource development (HRD) seem not to match these huge challenges. The aim of this study is to identify cost-effective means of mental training to recover sufficiently from the present bias to enable more sustainable decisions...... Pragmatic de-stressing by medical meditation adds extra years to a normal life and saves health care expenses for a moderate meditation course fee. So, medical meditation prevails as a dominant de-stressing intervention serving a wider goal of more long termed decision making. An international monitoring...
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International Nuclear Information System (INIS)
Giannantonio, Tommaso; Porciani, Cristiano
2010-01-01
We study structure formation in the presence of primordial non-Gaussianity of the local type with parameters f NL and g NL . We show that the distribution of dark-matter halos is naturally described by a multivariate bias scheme where the halo overdensity depends not only on the underlying matter density fluctuation δ but also on the Gaussian part of the primordial gravitational potential φ. This corresponds to a non-local bias scheme in terms of δ only. We derive the coefficients of the bias expansion as a function of the halo mass by applying the peak-background split to common parametrizations for the halo mass function in the non-Gaussian scenario. We then compute the halo power spectrum and halo-matter cross spectrum in the framework of Eulerian perturbation theory up to third order. Comparing our results against N-body simulations, we find that our model accurately describes the numerical data for wave numbers k≤0.1-0.3h Mpc -1 depending on redshift and halo mass. In our multivariate approach, perturbations in the halo counts trace φ on large scales, and this explains why the halo and matter power spectra show different asymptotic trends for k→0. This strongly scale-dependent bias originates from terms at leading order in our expansion. This is different from what happens using the standard univariate local bias where the scale-dependent terms come from badly behaved higher-order corrections. On the other hand, our biasing scheme reduces to the usual local bias on smaller scales, where |φ| is typically much smaller than the density perturbations. We finally discuss the halo bispectrum in the context of multivariate biasing and show that, due to its strong scale and shape dependence, it is a powerful tool for the detection of primordial non-Gaussianity from future galaxy surveys.
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The skewed weak lensing likelihood: why biases arise, despite data and theory being sound.
Sellentin, Elena; Heymans, Catherine; Harnois-Déraps, Joachim
2018-04-01
We derive the essentials of the skewed weak lensing likelihood via a simple Hierarchical Forward Model. Our likelihood passes four objective and cosmology-independent tests which a standard Gaussian likelihood fails. We demonstrate that sound weak lensing data are naturally biased low, since they are drawn from a skewed distribution. This occurs already in the framework of ΛCDM. Mathematically, the biases arise because noisy two-point functions follow skewed distributions. This form of bias is already known from CMB analyses, where the low multipoles have asymmetric error bars. Weak lensing is more strongly affected by this asymmetry as galaxies form a discrete set of shear tracer particles, in contrast to a smooth shear field. We demonstrate that the biases can be up to 30% of the standard deviation per data point, dependent on the properties of the weak lensing survey and the employed filter function. Our likelihood provides a versatile framework with which to address this bias in future weak lensing analyses.
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Aoki, Kenichi; Feldman, Marcus W
2014-02-01
The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change--coevolutionary, two-timescale, and information decay--are compared and shown to sometimes yield contradictory results. The so-called Rogers' paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers' paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. Copyright © 2013 Elsevier Inc. All rights reserved.
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Aoki, Kenichi; Feldman, Marcus W.
2013-01-01
The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change – coevolutionary, two-timescale, and information decay – are compared and shown to sometimes yield contradictory results. The so-called Rogers’ paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers’ paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. PMID:24211681
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Picard, Delphine; Zarhbouch, Benaissa
2014-01-01
A leftward spatial bias in drawing placement was demonstrated by Heller (1991) using the draw-a-person test with right-handed American children. No such bias was observed in left-handed children who are assumed to be less lateralised than their right-handed peers. According to Heller the leftward spatial bias is primarily a reflection of the right hemisphere specialisation for spatial processing. However, an alternative explanation in terms of directional trends may be put forward. In the present study we first confirm Heller's findings of a handedness effect on drawing placement using the draw-a-tree task with a large sample of right- and left-handed French children aged 5-15 years (Exp. 1). We then provide evidence that a similar leftward bias occurs in right-handed Moroccan children aged 7-11 years with opposite script directionality and opposite preferred drawing movement directions (i.e., right-to-left directional trends) to the those of right-handed French children (Exp. 2). Taken together these findings suggest that directionality trends arising from learned cultural habits and motor preferences play little role in determining spatial bias in the centring of a single object drawn on a page. Rather there may be a cerebral origin for drawing single objects slightly on the left side of the graphic space.
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Social learning in cooperative dilemmas.
Lamba, Shakti
2014-07-22
Helping is a cornerstone of social organization and commonplace in human societies. A major challenge for the evolutionary sciences is to explain how cooperation is maintained in large populations with high levels of migration, conditions under which cooperators can be exploited by selfish individuals. Cultural group selection models posit that such large-scale cooperation evolves via selection acting on populations among which behavioural variation is maintained by the cultural transmission of cooperative norms. These models assume that individuals acquire cooperative strategies via social learning. This assumption remains empirically untested. Here, I test this by investigating whether individuals employ conformist or payoff-biased learning in public goods games conducted in 14 villages of a forager-horticulturist society, the Pahari Korwa of India. Individuals did not show a clear tendency to conform or to be payoff-biased and are highly variable in their use of social learning. This variation is partly explained by both individual and village characteristics. The tendency to conform decreases and to be payoff-biased increases as the value of the modal contribution increases. These findings suggest that the use of social learning in cooperative dilemmas is contingent on individuals' circumstances and environments, and question the existence of stably transmitted cultural norms of cooperation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
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Deadly Attraction - Attentional Bias toward Preferred Cigarette Brand in Smokers.
Domaradzka, Ewa; Bielecki, Maksymilian
2017-01-01
Numerous studies have shown that biases in visual attention might be evoked by affective and personally relevant stimuli, for example addiction-related objects. Despite the fact that addiction is often linked to specific products and systematic purchase behaviors, no studies focused directly on the existence of bias evoked by brands. Smokers are characterized by high levels of brand loyalty and everyday contact with cigarette packaging. Using the incentive-salience mechanism as a theoretical framework, we hypothesized that this group might exhibit a bias toward the preferred cigarette brand. In our study, a group of smokers ( N = 40) performed a dot probe task while their eye movements were recorded. In every trial a pair of pictures was presented - each of them showed a single cigarette pack. The visual properties of stimuli were carefully controlled, so branding information was the key factor affecting subjects' reactions. For each participant, we compared gaze behavior related to the preferred vs. other brands. The analyses revealed no attentional bias in the early, orienting phase of the stimulus processing and strong differences in maintenance and disengagement. Participants spent more time looking at the preferred cigarettes and saccades starting at the preferred brand location had longer latencies. In sum, our data shows that attentional bias toward brands might be found in situations not involving choice or decision making. These results provide important insights into the mechanisms of formation and maintenance of attentional biases to stimuli of personal relevance and might serve as a first step toward developing new attitude measurement techniques.
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Query-Biased Preview over Outsourced and Encrypted Data
Directory of Open Access Journals (Sweden)
Ningduo Peng
2013-01-01
document to check if it contains the desired content. An informative query-biased preview feature, as applied in modern search engine, could help the users to learn about the content without downloading the entire document. However, when the data are encrypted, securely extracting a keyword-in-context snippet from the data as a preview becomes a challenge. Based on private information retrieval protocol and the core concept of searchable encryption, we propose a single-server and two-round solution to securely obtain a query-biased snippet over the encrypted data from the server. We achieve this novel result by making a document (plaintext previewable under any cryptosystem and constructing a secure index to support dynamic computation for a best matched snippet when queried by some keywords. For each document, the scheme has O(d storage complexity and O(log(d/s+s+d/s communication complexity, where d is the document size and s is the snippet length.
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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.
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Hernaus, Dennis; Gold, James M; Waltz, James A; Frank, Michael J
2018-04-03
While many have emphasized impaired reward prediction error signaling in schizophrenia, multiple studies suggest that some decision-making deficits may arise from overreliance on stimulus-response systems together with a compromised ability to represent expected value. Guided by computational frameworks, we formulated and tested two scenarios in which maladaptive representations of expected value should be most evident, thereby delineating conditions that may evoke decision-making impairments in schizophrenia. In a modified reinforcement learning paradigm, 42 medicated people with schizophrenia and 36 healthy volunteers learned to select the most frequently rewarded option in a 75-25 pair: once when presented with a more deterministic (90-10) pair and once when presented with a more probabilistic (60-40) pair. Novel and old combinations of choice options were presented in a subsequent transfer phase. Computational modeling was employed to elucidate contributions from stimulus-response systems (actor-critic) and expected value (Q-learning). People with schizophrenia showed robust performance impairments with increasing value difference between two competing options, which strongly correlated with decreased contributions from expected value-based learning (Q-learning). Moreover, a subtle yet consistent contextual choice bias for the probabilistic 75 option was present in people with schizophrenia, which could be accounted for by a context-dependent reward prediction error in the actor-critic. We provide evidence that decision-making impairments in schizophrenia increase monotonically with demands placed on expected value computations. A contextual choice bias is consistent with overreliance on stimulus-response learning, which may signify a deficit secondary to the maladaptive representation of expected value. These results shed new light on conditions under which decision-making impairments may arise. Copyright © 2018 Society of Biological Psychiatry. Published by
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Associations among Negative Parenting, Attention Bias to Anger, and Social Anxiety among Youth
Gulley, Lauren D.; Oppenheimer, Caroline W.; Hankin, Benjamin L.
2014-01-01
Theories of affective learning suggest that early experiences contribute to emotional disorders by influencing the development of processing biases for negative emotional stimuli. Although studies have shown that physically abused children preferentially attend to angry faces, it is unclear whether youth exposed to more typical aspects of negative…
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COEXISTENCE OF PRIVATE FIRMS AND OPEN SOURCE FIRMS UNDER SPILLOVERS AND CONSUMER BIAS
Directory of Open Access Journals (Sweden)
Murat YILMAZ
2017-12-01
Full Text Available Open source technologies have been an important divergence from the private produc- tion, and some markets have accommodated both open source firms and private firms. We explore the conditions under which such a coexistence of both type of firms can be seen. Through a simple and tractable game theoretical model, with spillovers on the open source production and positive consumer bias for the privately produced good, we analyze the conditions for which, in the equilibrium, a private firm and an open source firm share the market. We find that for large enough consumer bias, the two types cannot coexist, however when the consumer bias is relatively low and the spillover effect is not too strong, then we get a coexistence result.
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Selection bias and the Rubin-Ford effect
International Nuclear Information System (INIS)
James, P.A.; Joseph, R.D.; Collins, C.A.
1991-01-01
We have re-examined the 'Rubin-Ford effect', and more recent claims of galaxy streaming from the same galaxy sample, to investigate the impact of selection effects on these results. A 'Monte Carlo'-type analysis was applied to simulate the selection procedure used to obtain this sample, and a strong bias was identified, resulting in apparent velocity flows at 600-800 km s -1 . Thus the 'Rubin-Ford effect' and the associated galaxy streaming are spurious effects resulting from the method of sample selection. (author)
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Experimenter Confirmation Bias and the Correction of Science Misconceptions
Allen, Michael; Coole, Hilary
2012-06-01
This paper describes a randomised educational experiment ( n = 47) that examined two different teaching methods and compared their effectiveness at correcting one science misconception using a sample of trainee primary school teachers. The treatment was designed to promote engagement with the scientific concept by eliciting emotional responses from learners that were triggered by their own confirmation biases. The treatment group showed superior learning gains to control at post-test immediately after the lesson, although benefits had dissipated after 6 weeks. Findings are discussed with reference to the conceptual change paradigm and to the importance of feeling emotion during a learning experience, having implications for the teaching of pedagogies to adults that have been previously shown to be successful with children.
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Directory of Open Access Journals (Sweden)
Nicholas J Hudson
Full Text Available Codon bias in the genome of an organism influences its phenome by changing the speed and efficiency of mRNA translation and hence protein abundance. We hypothesized that differences in codon bias, either between-species differences in orthologous genes, or within-species differences between genes, may play an evolutionary role. To explore this hypothesis, we compared the genome-wide codon bias in six species that occupy vital positions in the Eukaryotic Tree of Life. We acquired the entire protein coding sequences for these organisms, computed the codon bias for all genes in each organism and explored the output for relationships between codon bias and protein function, both within- and between-lineages. We discovered five notable coordinated patterns, with extreme codon bias most pronounced in traits considered highly characteristic of a given lineage. Firstly, the Homo sapiens genome had stronger codon bias for DNA-binding transcription factors than the Saccharomyces cerevisiae genome, whereas the opposite was true for ribosomal proteins--perhaps underscoring transcriptional regulation in the origin of complexity. Secondly, both mammalian species examined possessed extreme codon bias in genes relating to hair--a tissue unique to mammals. Thirdly, Arabidopsis thaliana showed extreme codon bias in genes implicated in cell wall formation and chloroplast function--which are unique to plants. Fourthly, Gallus gallus possessed strong codon bias in a subset of genes encoding mitochondrial proteins--perhaps reflecting the enhanced bioenergetic efficiency in birds that co-evolved with flight. And lastly, the G. gallus genome had extreme codon bias for the Ciliary Neurotrophic Factor--which may help to explain their spontaneous recovery from deafness. We propose that extreme codon bias in groups of genes that encode functionally related proteins has a pathway-level energetic explanation.
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Testing human sperm chemotaxis: how to detect biased motion in population assays.
Directory of Open Access Journals (Sweden)
Leah Armon
Full Text Available Biased motion of motile cells in a concentration gradient of a chemoattractant is frequently studied on the population level. This approach has been particularly employed in human sperm chemotactic assays, where the fraction of responsive cells is low and detection of biased motion depends on subtle differences. In these assays, statistical measures such as population odds ratios of swimming directions can be employed to infer chemotactic performance. Here, we report on an improved method to assess statistical significance of experimentally determined odds ratios and discuss the strong impact of data correlations that arise from the directional persistence of sperm swimming.
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Approximate Bias Correction in Econometrics
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...
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Did Buddha turn the other cheek too? A comparison of posing biases between Jesus and Buddha.
Duerksen, Kari N; Friedrich, Trista E; Elias, Lorin J
2015-10-02
People tend to exhibit a leftward bias in posing. Various studies suggest that posing to the left portrays a stronger emotion, whereas posing to the right portrays a more neutral emotion. Religions such as Christianity emphasize the role of strong emotions in religious experience, whereas religions such as Buddhism emphasize the calming of emotions as being important. In the present study, we investigated if the emphasis on emotionality of a religion influences the depiction of their religious figures. Specifically, we coded 484 paintings of Jesus and Buddha from online art databases for whether the deity exhibited a left bias, right bias, or central face presentation. The posing biases were analysed to discover whether paintings of Jesus would more frequently depict a leftward bias than paintings of Buddha. Jesus is more commonly depicted with a leftward bias than Buddha, and Buddha is more commonly depicted with a central face presentation than Jesus. These findings support the idea that the amount of emotionality that is to be conveyed in artwork influences the whether the subject is posed with a leftward bias.
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Koseki, Shunya; Keenlyside, Noel; Demissie, Teferi; Toniazzo, Thomas; Counillon, Francois; Bethke, Ingo; Ilicak, Mehmet; Shen, Mao-Lin
2018-06-01
We have investigated the causes of the sea surface temperature (SST) bias in the Angola-Benguela Frontal Zone (ABFZ) of the southeastern Atlantic Ocean simulated by the Norwegian Earth System Model (NorESM). Similar to other coupled-models, NorESM has a warm SST bias in the ABFZ of up to 8 °C in the annual mean. Our analysis of NorESM reveals that a cyclonic surface wind bias over the ABFZ drives a locally excessively strong southward (0.05 m/s (relative to observation)) Angola Current displacing the ABFZ southward. A series of uncoupled stand-alone atmosphere and ocean model simulations are performed to investigate the cause of the coupled model bias. The stand-alone atmosphere model driven with observed SST exhibits a similar cyclonic surface circulation bias; while the stand-alone ocean model forced with the reanalysis data produces a warm SST in the ABFZ with a magnitude approximately half of that in the coupled NorESM simulation. An additional uncoupled sensitivity experiment shows that the atmospheric model's local negative surface wind curl generates anomalously strong Angola Current at the ocean surface. Consequently, this contributes to the warm SST bias in the ABFZ by 2 °C (compared to the reanalysis forced simulation). There is no evidence that local air-sea feedbacks among wind stress curl, SST, and sea level pressure (SLP) affect the ABFZ SST bias. Turbulent surface heat flux differences between coupled and uncoupled experiments explain the remaining 2 °C warm SST bias in NorESM. Ocean circulation, upwelling and turbulent heat flux errors all modulate the intensity and the seasonality of the ABFZ errors.
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Koseki, Shunya; Keenlyside, Noel; Demissie, Teferi; Toniazzo, Thomas; Counillon, Francois; Bethke, Ingo; Ilicak, Mehmet; Shen, Mao-Lin
2017-09-01
We have investigated the causes of the sea surface temperature (SST) bias in the Angola-Benguela Frontal Zone (ABFZ) of the southeastern Atlantic Ocean simulated by the Norwegian Earth System Model (NorESM). Similar to other coupled-models, NorESM has a warm SST bias in the ABFZ of up to 8 °C in the annual mean. Our analysis of NorESM reveals that a cyclonic surface wind bias over the ABFZ drives a locally excessively strong southward (0.05 m/s (relative to observation)) Angola Current displacing the ABFZ southward. A series of uncoupled stand-alone atmosphere and ocean model simulations are performed to investigate the cause of the coupled model bias. The stand-alone atmosphere model driven with observed SST exhibits a similar cyclonic surface circulation bias; while the stand-alone ocean model forced with the reanalysis data produces a warm SST in the ABFZ with a magnitude approximately half of that in the coupled NorESM simulation. An additional uncoupled sensitivity experiment shows that the atmospheric model's local negative surface wind curl generates anomalously strong Angola Current at the ocean surface. Consequently, this contributes to the warm SST bias in the ABFZ by 2 °C (compared to the reanalysis forced simulation). There is no evidence that local air-sea feedbacks among wind stress curl, SST, and sea level pressure (SLP) affect the ABFZ SST bias. Turbulent surface heat flux differences between coupled and uncoupled experiments explain the remaining 2 °C warm SST bias in NorESM. Ocean circulation, upwelling and turbulent heat flux errors all modulate the intensity and the seasonality of the ABFZ errors.
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Depression-Biased Reverse Plasticity Rule Is Required for Stable Learning at Top-Down Connections
Burbank, Kendra S.; Kreiman, Gabriel
2012-01-01
Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP) rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP) where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP) produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body. PMID:22396630
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Depression-biased reverse plasticity rule is required for stable learning at top-down connections.
Directory of Open Access Journals (Sweden)
Kendra S Burbank
Full Text Available Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body.
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The Gambler’s Fallacy Is Associated with Weak Affective Decision Making but Strong Cognitive Ability
Xue, Gui; He, Qinghua; Lei, Xuemei; Chen, Chunhui; Liu, Yuyun; Chen, Chuansheng; Lu, Zhong-Lin; Dong, Qi; Bechara, Antoine
2012-01-01
Humans demonstrate an inherent bias towards making maladaptive decisions, as shown by a phenomenon known as the gambler's fallacy (GF). The GF has been traditionally considered as a heuristic bias supported by the fast and automatic intuition system, which can be overcome by the reasoning system. The present study examined an intriguing hypothesis, based on emerging evidence from neuroscience research, that the GF might be attributed to a weak affective but strong cognitive decision making me...
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Perry, Sylvia P; Dovidio, John F; Murphy, Mary C; van Ryn, Michelle
2015-01-01
Two correlational studies investigated the joint effect of bias awareness-a new individual difference measure that assesses Whites' awareness and concern about their propensity to be biased-and prejudice on Whites' intergroup anxiety and intended intergroup contact. Using a community sample (Study 1), we found the predicted Bias Awareness × Prejudice interaction. Prejudice was more strongly related to interracial anxiety among those high (vs. low) in bias awareness. Study 2 investigated potential behavioral consequences in an important real world context: medical students' intentions for working primarily with minority patients. Study 2 replicated the Bias Awareness × Prejudice interaction and further demonstrated that interracial anxiety mediated medical students' intentions to work with minority populations. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
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Apparatus bias and place conditioning with ethanol in mice.
Cunningham, Christopher L; Ferree, Nikole K; Howard, MacKenzie A
2003-12-01
Although the distinction between "biased" and "unbiased" is generally recognized as an important methodological issue in place conditioning, previous studies have not adequately addressed the distinction between a biased/unbiased apparatus and a biased/unbiased stimulus assignment procedure. Moreover, a review of the recent literature indicates that many reports (70% of 76 papers published in 2001) fail to provide adequate information about apparatus bias. This issue is important because the mechanisms underlying a drug's effect in the place-conditioning procedure may differ depending on whether the apparatus is biased or unbiased. The present studies were designed to assess the impact of apparatus bias and stimulus assignment procedure on ethanol-induced place conditioning in mice (DBA/2 J). A secondary goal was to compare various dependent variables commonly used to index conditioned place preference. Apparatus bias was manipulated by varying the combination of tactile (floor) cues available during preference tests. Experiment 1 used an unbiased apparatus in which the stimulus alternatives were equally preferred during a pre-test as indicated by the group average. Experiment 2 used a biased apparatus in which one of the stimuli was strongly preferred by most mice (mean % time on cue = 67%) during the pre-test. In both studies, the stimulus paired with drug (CS+) was assigned randomly (i.e., an "unbiased" stimulus assignment procedure). Experimental mice received four pairings of CS+ with ethanol (2 g/kg, i.p.) and four pairings of the alternative stimulus (CS-) with saline; control mice received saline on both types of trial. Each experiment concluded with a 60-min choice test. With the unbiased apparatus (experiment 1), significant place conditioning was obtained regardless of whether drug was paired with the subject's initially preferred or non-preferred stimulus. However, with the biased apparatus (experiment 2), place conditioning was apparent only when
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Spectral Resolution-linked Bias in Transit Spectroscopy of Extrasolar Planets
Deming, Drake; Sheppard, Kyle
2017-05-01
We re-visit the principles of transmission spectroscopy for transiting extrasolar planets, focusing on the overlap between the planetary spectrum and the illuminating stellar spectrum. Virtually all current models of exoplanetary transmission spectra utilize an approximation that is inaccurate when the spectrum of the illuminating star has a complex line structure, such as molecular bands in M-dwarf spectra. In those cases, it is desirable to model the observations using a coupled stellar-planetary radiative transfer model calculated at high spectral resolving power, followed by convolution to the observed resolution. Not consistently accounting for overlap of stellar M-dwarf and planetary lines at high spectral resolution can bias the modeled amplitude of the exoplanetary transmission spectrum, producing modeled absorption that is too strong. We illustrate this bias using the exoplanet TRAPPIST-1b, as observed using Hubble Space Telescope/WFC3. The bias in this case is about 250 ppm, 12% of the modeled transit absorption. Transit spectroscopy using JWST will have access to longer wavelengths where the water bands are intrinsically stronger, and the observed signal-to-noise ratios will be higher than currently possible. We therefore expect that this resolution-linked bias will be especially important for future JWST observations of TESS-discovered super-Earths and mini-Neptunes transiting M-dwarfs.
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Spectral Resolution-linked Bias in Transit Spectroscopy of Extrasolar Planets
Energy Technology Data Exchange (ETDEWEB)
Deming, Drake; Sheppard, Kyle [Department of Astronomy, University of Maryland at College Park, College Park, MD 20742 (United States)
2017-05-20
We re-visit the principles of transmission spectroscopy for transiting extrasolar planets, focusing on the overlap between the planetary spectrum and the illuminating stellar spectrum. Virtually all current models of exoplanetary transmission spectra utilize an approximation that is inaccurate when the spectrum of the illuminating star has a complex line structure, such as molecular bands in M-dwarf spectra. In those cases, it is desirable to model the observations using a coupled stellar–planetary radiative transfer model calculated at high spectral resolving power, followed by convolution to the observed resolution. Not consistently accounting for overlap of stellar M-dwarf and planetary lines at high spectral resolution can bias the modeled amplitude of the exoplanetary transmission spectrum, producing modeled absorption that is too strong. We illustrate this bias using the exoplanet TRAPPIST-1b, as observed using Hubble Space Telescope /WFC3. The bias in this case is about 250 ppm, 12% of the modeled transit absorption. Transit spectroscopy using JWST will have access to longer wavelengths where the water bands are intrinsically stronger, and the observed signal-to-noise ratios will be higher than currently possible. We therefore expect that this resolution-linked bias will be especially important for future JWST observations of TESS-discovered super-Earths and mini-Neptunes transiting M-dwarfs.
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Landau levels in biased graphene structures with monolayer-bilayer interfaces
Mirzakhani, M.; Zarenia, M.; Vasilopoulos, P.; Ketabi, S. A.; Peeters, F. M.
2017-09-01
The electron energy spectrum in monolayer-bilayer-monolayer and in bilayer-monolayer-bilayer graphene structures is investigated and the effects of a perpendicular magnetic field and electric bias are studied. Different types of monolayer-bilayer interfaces are considered as zigzag (ZZ) or armchair (AC) junctions which modify considerably the bulk Landau levels (LLs) when the spectra are plotted as a function of the center coordinate of the cyclotron orbit. Far away from the two interfaces, one obtains the well-known LLs for extended monolayer or bilayer graphene. The LL structure changes significantly at the two interfaces or junctions where the valley degeneracy is lifted for both types of junctions, especially when the distance between them is approximately equal to the magnetic length. Varying the nonuniform bias and the width of this junction-to-junction region in either structure strongly influence the resulting spectra. Significant differences exist between ZZ and AC junctions in both structures. The densities of states (DOSs) for unbiased structures are symmetric in energy whereas those for biased structures are asymmetric. An external bias creates interface LLs in the gaps between the LLs of the unbiased system in which the DOS can be quite small. Such a pattern of LLs can be probed by scanning tunneling microscopy.
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Spectral Resolution-linked Bias in Transit Spectroscopy of Extrasolar Planets
International Nuclear Information System (INIS)
Deming, Drake; Sheppard, Kyle
2017-01-01
We re-visit the principles of transmission spectroscopy for transiting extrasolar planets, focusing on the overlap between the planetary spectrum and the illuminating stellar spectrum. Virtually all current models of exoplanetary transmission spectra utilize an approximation that is inaccurate when the spectrum of the illuminating star has a complex line structure, such as molecular bands in M-dwarf spectra. In those cases, it is desirable to model the observations using a coupled stellar–planetary radiative transfer model calculated at high spectral resolving power, followed by convolution to the observed resolution. Not consistently accounting for overlap of stellar M-dwarf and planetary lines at high spectral resolution can bias the modeled amplitude of the exoplanetary transmission spectrum, producing modeled absorption that is too strong. We illustrate this bias using the exoplanet TRAPPIST-1b, as observed using Hubble Space Telescope /WFC3. The bias in this case is about 250 ppm, 12% of the modeled transit absorption. Transit spectroscopy using JWST will have access to longer wavelengths where the water bands are intrinsically stronger, and the observed signal-to-noise ratios will be higher than currently possible. We therefore expect that this resolution-linked bias will be especially important for future JWST observations of TESS-discovered super-Earths and mini-Neptunes transiting M-dwarfs.
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Multi-faceted Rasch measurement and bias patterns in EFL writing performance assessment.
He, Tung-Hsien; Gou, Wen Johnny; Chien, Ya-Chen; Chen, I-Shan Jenny; Chang, Shan-Mao
2013-04-01
This study applied multi-faceted Rasch measurement to examine rater bias in the assessment of essays written by college students learning English as a foreign language. Four raters who had received different academic training from four distinctive disciplines applied a six-category rating scale to analytically rate essays on an argumentative topic and on a descriptive topic. FACETS, a Rasch computer program, was utilized to pinpoint bias patterns by analyzing the rater-topic, rater-category, and topic-category interactions. Results showed: argumentative essays were rated more severely than were descriptive essays; the linguistics-major rater was the most lenient rater, while the literature-major rater was the severest one; and the category of language use received the severest ratings, whereas content was given the most lenient ratings. The severity hierarchies for raters, essay topics, and rating categories suggested that raters' academic training and their perceptions of the importance of categories were associated with their bias patterns. Implications for rater training are discussed.
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Reasoning, biases and dual processes: The lasting impact of Wason (1960).
Evans, Jonathan St B T
2016-10-01
Wason (1960) published a relatively short experimental paper, in which he introduced the 2-4-6 problem as a test of inductive reasoning. This paper became one of the most highly cited to be published in the Quarterly Journal of Experimental Psychology and is significant for a number of reasons. First, the 2-4-6 task itself was ingenious and yielded evidence of error and bias in the intelligent participants who attempted it. Research on the 2-4-6 problem continues to the present day. More importantly, it was Wason's first paper on reasoning and one which made strong claims for bias and irrationality in a period dominated by rationalist writers like Piaget. It set in motion the study of cognitive biases in thinking and reasoning, well before the start of Tversky and Kahneman's famous heuristics and biases research programme. I also show here something for which Wason has received insufficient credit. It was Wason's work on this task and his later studies of his four card selection task that led to the first development of the dual process theory of reasoning which is so dominant in the current literature on the topic more than half a century later.
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Beyond attentional bias: a perceptual bias in a dot-probe task.
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.
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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...
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Causes of model dry and warm bias over central U.S. and impact on climate projections.
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.
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Adaptive cultural transmission biases in children and nonhuman primates.
Price, Elizabeth E; Wood, Lara A; Whiten, Andrew
2017-08-01
Comparative and evolutionary developmental analyses seek to discover the similarities and differences between humans and non-human species that might illuminate both the evolutionary foundations of our nature that we share with other animals, and the distinctive characteristics that make human development unique. As our closest animal relatives, with whom we last shared common ancestry, non-human primates have been particularly important in this endeavour. Such studies have focused on social learning, traditions, and culture, and have discovered much about the 'how' of social learning, concerned with key underlying processes such as imitation and emulation. One of the core discoveries is that the adaptive adjustment of social learning options to different contexts is not unique to human, therefore multiple new strands of research have begun to focus on more subtle questions about when, from whom, and why such learning occurs. Here we review illustrative studies on both human infants and young children and on non-human primates to identify the similarities shared more broadly across the primate order, and the apparent specialisms that distinguish human development. Adaptive biases in social learning discussed include those modulated by task comprehension, experience, conformity to majorities, and the age, skill, proficiency and familiarity of potential alternative cultural models. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.
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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.
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Taxonomic bias in biodiversity data and societal preferences.
Troudet, Julien; Grandcolas, Philippe; Blin, Amandine; Vignes-Lebbe, Régine; Legendre, Frédéric
2017-08-22
Studying and protecting each and every living species on Earth is a major challenge of the 21 st century. Yet, most species remain unknown or unstudied, while others attract most of the public, scientific and government attention. Although known to be detrimental, this taxonomic bias continues to be pervasive in the scientific literature, but is still poorly studied and understood. Here, we used 626 million occurrences from the Global Biodiversity Information Facility (GBIF), the biggest biodiversity data portal, to characterize the taxonomic bias in biodiversity data. We also investigated how societal preferences and taxonomic research relate to biodiversity data gathering. For each species belonging to 24 taxonomic classes, we used the number of publications from Web of Science and the number of web pages from Bing searches to approximate research activity and societal preferences. Our results show that societal preferences, rather than research activity, strongly correlate with taxonomic bias, which lead us to assert that scientists should advertise less charismatic species and develop societal initiatives (e.g. citizen science) that specifically target neglected organisms. Ensuring that biodiversity is representatively sampled while this is still possible is an urgent prerequisite for achieving efficient conservation plans and a global understanding of our surrounding environment.
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Resistance and resistance fluctuations in random resistor networks under biased percolation.
Pennetta, Cecilia; Reggiani, L; Trefán, Gy; Alfinito, E
2002-06-01
We consider a two-dimensional random resistor network (RRN) in the presence of two competing biased processes consisting of the breaking and recovering of elementary resistors. These two processes are driven by the joint effects of an electrical bias and of the heat exchange with a thermal bath. The electrical bias is set up by applying a constant voltage or, alternatively, a constant current. Monte Carlo simulations are performed to analyze the network evolution in the full range of bias values. Depending on the bias strength, electrical failure or steady state are achieved. Here we investigate the steady state of the RRN focusing on the properties of the non-Ohmic regime. In constant-voltage conditions, a scaling relation is found between /(0) and V/V(0), where is the average network resistance, (0) the linear regime resistance, and V0 the threshold value for the onset of nonlinearity. A similar relation is found in constant-current conditions. The relative variance of resistance fluctuations also exhibits a strong nonlinearity whose properties are investigated. The power spectral density of resistance fluctuations presents a Lorentzian spectrum and the amplitude of fluctuations shows a significant non-Gaussian behavior in the prebreakdown region. These results compare well with electrical breakdown measurements in thin films of composites and of other conducting materials.
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Directory of Open Access Journals (Sweden)
Anita eSchick
2013-06-01
Full Text Available Affective state can influence cognition leading to biased information processing, interpretation, attention, and memory. Such bias has been reported to be essential for the onset and maintenance of different psychopathologies, particularly affective disorders. However, empirical evidence has been very heterogeneous and little is known about the neurophysiological mechanisms underlying cognitive bias and its time-course. We therefore investigated the interpretation of ambiguous stimuli as indicators of biased information processing with an ambiguous cue-conditioning paradigm. In an acquisition phase, participants learned to discriminate two tones of different frequency, which acquired emotional and motivational value due to subsequent feedback (monetary gain or avoidance of monetary loss. In the test phase, three additional tones of intermediate frequencies were presented, whose interpretation as positive (approach of reward or negative (avoidance of punishment, indicated by a button press, was used as an indicator of the bias. Twenty healthy volunteers participated in this paradigm while a 64-channel electroencephalogram was recorded. Participants also completed questionnaires assessing individual differences in depression and rumination. Overall, we found a small positive bias, which correlated negatively with reflective pondering, a type of rumination. As expected, reaction times were increased for intermediate tones. ERP amplitudes between 300 – 700 ms post-stimulus differed depending on the interpretation of the intermediate tones. A negative compared to a positive interpretation led to an amplitude increase over frontal electrodes. Our study provides evidence that in humans, as in animal research, the ambiguous cue-conditioning paradigm is a valid procedure for indirectly assessing ambiguous cue interpretation and a potential interpretation bias, which is sensitive to individual differences in affect-related traits.
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Long-term memory biases auditory spatial attention.
Zimmermann, Jacqueline F; Moscovitch, Morris; Alain, Claude
2017-10-01
Long-term memory (LTM) has been shown to bias attention to a previously learned visual target location. Here, we examined whether memory-predicted spatial location can facilitate the detection of a faint pure tone target embedded in real world audio clips (e.g., soundtrack of a restaurant). During an initial familiarization task, participants heard audio clips, some of which included a lateralized target (p = 50%). On each trial participants indicated whether the target was presented from the left, right, or was absent. Following a 1 hr retention interval, participants were presented with the same audio clips, which now all included a target. In Experiment 1, participants showed memory-based gains in response time and d'. Experiment 2 showed that temporal expectations modulate attention, with greater memory-guided attention effects on performance when temporal context was reinstated from learning (i.e., when timing of the target within audio clips was not changed from initially learned timing). Experiment 3 showed that while conscious recall of target locations was modulated by exposure to target-context associations during learning (i.e., better recall with higher number of learning blocks), the influence of LTM associations on spatial attention was not reduced (i.e., number of learning blocks did not affect memory-guided attention). Both Experiments 2 and 3 showed gains in performance related to target-context associations, even for associations that were not explicitly remembered. Together, these findings indicate that memory for audio clips is acquired quickly and is surprisingly robust; both implicit and explicit LTM for the location of a faint target tone modulated auditory spatial attention. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Lester, Kathryn J; Field, Andy P; Muris, Peter
2011-01-01
This study investigated the effects of experimentally modifying interpretation biases for children's cognitions, avoidance behavior, anxiety vulnerability, and physiological responding. Sixty-seven children (6-11 years) were randomly assigned to receive a positive or negative interpretation bias modification procedure to induce interpretation biases toward or away from threat about ambiguous situations involving Australian marsupials. Children rapidly learned to select outcomes of ambiguous situations, which were congruent with their assigned condition. Furthermore, following positive modification, children's threat biases about novel ambiguous situations significantly decreased, whereas threat biases significantly increased after negative modification. In response to a stress-evoking behavioral avoidance test, positive modification attenuated behavioral avoidance compared to negative modification. However, no significant effects of bias modification on anxiety vulnerability or physiological responses to this stress-evoking Behavioral Avoidance Task were observed.
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Halo assembly bias and the tidal anisotropy of the local halo environment
Paranjape, Aseem; Hahn, Oliver; Sheth, Ravi K.
2018-05-01
We study the role of the local tidal environment in determining the assembly bias of dark matter haloes. Previous results suggest that the anisotropy of a halo's environment (i.e. whether it lies in a filament or in a more isotropic region) can play a significant role in determining the eventual mass and age of the halo. We statistically isolate this effect, using correlations between the large-scale and small-scale environments of simulated haloes at z = 0 with masses between 1011.6 ≲ (m/h-1 M⊙) ≲ 1014.9. We probe the large-scale environment, using a novel halo-by-halo estimator of linear bias. For the small-scale environment, we identify a variable αR that captures the tidal anisotropy in a region of radius R = 4R200b around the halo and correlates strongly with halo bias at fixed mass. Segregating haloes by αR reveals two distinct populations. Haloes in highly isotropic local environments (αR ≲ 0.2) behave as expected from the simplest, spherically averaged analytical models of structure formation, showing a negative correlation between their concentration and large-scale bias at all masses. In contrast, haloes in anisotropic, filament-like environments (αR ≳ 0.5) tend to show a positive correlation between bias and concentration at any mass. Our multiscale analysis cleanly demonstrates how the overall assembly bias trend across halo mass emerges as an average over these different halo populations, and provides valuable insights towards building analytical models that correctly incorporate assembly bias. We also discuss potential implications for the nature and detectability of galaxy assembly bias.
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Deepening Learning through Learning-by-Inventing
Apiola, Mikko; Tedre, Matti
2013-01-01
It has been shown that deep approaches to learning, intrinsic motivation, and self-regulated learning have strong positive effects on learning. How those pedagogical theories can be integrated in computing curricula is, however, still lacking empirically grounded analyses. This study integrated, in a robotics-based programming class, a method of learning-by-inventing, and studied its qualitative effects on students’ learning through 144 interviews. Five findings were related with learning the...
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Media bias under direct and indirect government control: when is the bias smaller?
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.
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Development of a strong electromagnet wiggler
International Nuclear Information System (INIS)
Burns, M.J.; Deis, G.A.; Holmes, R.H.; Van Maren, R.D.; Halbach, K.
1987-01-01
The Strong Electromagnet (SEM) wiggler is a permanent magnet-assisted electromagnet under development at the Lawrence Livermore National Laboratory (LLNL) as part of the Induction Linac Free-Electron-Laser (IFEL) program. This concept uses permanent magnets within the wiggler to provide a reverse bias flux in the iron and thus delay the onset of magnetic saturation. The electromagnet coils determine the wiggler field and operate at low current densities by virtue of their placement away from the midplane. We describe here the design approach used and test data from a 7-period wiggler prototype that includes curved pole tips to provide wiggle-plane focusing. 7 refs
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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.
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Ultrathin Limit of Exchange Bias Coupling at Oxide Multiferroic/Ferromagnetic Interfaces
Huijben, Mark; Yu, P.; Martin, L.W.; Molegraaf, Hajo; Chu, Y.H.; Holcomb, M.B.; Balke, N.; Rijnders, Augustinus J.H.M.; Ramesh, R.
2013-01-01
Exchange bias coupling at the multiferroic- ferromagnetic interface in BiFeO3/La0.7Sr0.3MnO3 heterostructures exhibits a critical thickness for ultrathin BiFeO3 layers of 5 unit cells (2 nm). Linear dichroism measurements demonstrate the dependence on the BiFeO3 layer thickness with a strong
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Bathellier, Brice; Tee, Sui Poh; Hrovat, Christina; Rumpel, Simon
2013-01-01
Learning speed can strongly differ across individuals. This is seen in humans and animals. Here, we measured learning speed in mice performing a discrimination task and developed a theoretical model based on the reinforcement learning framework to account for differences between individual mice. We found that, when using a multiplicative learning rule, the starting connectivity values of the model strongly determine the shape of learning curves. This is in contrast to current learning models ...
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Not All Emotions Are Created Equal: The Negativity Bias in Social-Emotional Development
Vaish, Amrisha; Grossman, Tobias; Woodward, Amanda
2008-01-01
There is ample empirical evidence for an asymmetry in the way that adults use positive versus negative information to make sense of their world; specifically, across an array of psychological situations and tasks, adults display a negativity bias, or the propensity to attend to, learn from, and use negative information far more than positive…
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Deadly Attraction – Attentional Bias toward Preferred Cigarette Brand in Smokers
Directory of Open Access Journals (Sweden)
Ewa Domaradzka
2017-08-01
Full Text Available Numerous studies have shown that biases in visual attention might be evoked by affective and personally relevant stimuli, for example addiction-related objects. Despite the fact that addiction is often linked to specific products and systematic purchase behaviors, no studies focused directly on the existence of bias evoked by brands. Smokers are characterized by high levels of brand loyalty and everyday contact with cigarette packaging. Using the incentive-salience mechanism as a theoretical framework, we hypothesized that this group might exhibit a bias toward the preferred cigarette brand. In our study, a group of smokers (N = 40 performed a dot probe task while their eye movements were recorded. In every trial a pair of pictures was presented – each of them showed a single cigarette pack. The visual properties of stimuli were carefully controlled, so branding information was the key factor affecting subjects’ reactions. For each participant, we compared gaze behavior related to the preferred vs. other brands. The analyses revealed no attentional bias in the early, orienting phase of the stimulus processing and strong differences in maintenance and disengagement. Participants spent more time looking at the preferred cigarettes and saccades starting at the preferred brand location had longer latencies. In sum, our data shows that attentional bias toward brands might be found in situations not involving choice or decision making. These results provide important insights into the mechanisms of formation and maintenance of attentional biases to stimuli of personal relevance and might serve as a first step toward developing new attitude measurement techniques.
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Deadly Attraction – Attentional Bias toward Preferred Cigarette Brand in Smokers
Domaradzka, Ewa; Bielecki, Maksymilian
2017-01-01
Numerous studies have shown that biases in visual attention might be evoked by affective and personally relevant stimuli, for example addiction-related objects. Despite the fact that addiction is often linked to specific products and systematic purchase behaviors, no studies focused directly on the existence of bias evoked by brands. Smokers are characterized by high levels of brand loyalty and everyday contact with cigarette packaging. Using the incentive-salience mechanism as a theoretical framework, we hypothesized that this group might exhibit a bias toward the preferred cigarette brand. In our study, a group of smokers (N = 40) performed a dot probe task while their eye movements were recorded. In every trial a pair of pictures was presented – each of them showed a single cigarette pack. The visual properties of stimuli were carefully controlled, so branding information was the key factor affecting subjects’ reactions. For each participant, we compared gaze behavior related to the preferred vs. other brands. The analyses revealed no attentional bias in the early, orienting phase of the stimulus processing and strong differences in maintenance and disengagement. Participants spent more time looking at the preferred cigarettes and saccades starting at the preferred brand location had longer latencies. In sum, our data shows that attentional bias toward brands might be found in situations not involving choice or decision making. These results provide important insights into the mechanisms of formation and maintenance of attentional biases to stimuli of personal relevance and might serve as a first step toward developing new attitude measurement techniques. PMID:28848479
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Prada, Marília; Rodrigues, David; Garrido, Margarida V
2016-08-01
Organic claims can influence how a product is perceived in dimensions that are unrelated with the food production method (e.g., organic food is perceived as more healthful and less caloric than conventional food). Such claims can also bias how the consumers of organic food are perceived and how other people judge their behavior. Schuldt and Schwarz (2010) have shown that individuals evaluating a target with a weight-loss goal are more lenient in judging the target forgoing exercise when the target had an organic (vs. conventional) dessert. This impact of organic claims on leniency judgments has been interpreted either as a halo or a licensing effect. In the current research we aim to replicate and extend Schuldt and Schwarz's (2010) results by examining the mechanisms that are more likely to explain the observed leniency judgments. In Experiment 1, we observed that leniency towards a target that has consumed an organic meal is only observed when the target intentionally chooses such organic meal (vs. choice determined by the situation). These findings suggest that the impact of organic claims on leniency judgments is not merely based on a halo effect. Instead, a licensing account emerges as the most probable mechanism. In Experiment 2, we further found that stronger (vs. weaker) motives for forgoing exercise influenced leniency judgments to the same extent as having had an organic meal. Understanding the mechanisms that shape consumers' decisions may have important implications to prevent bias in their judgments about food and exercise. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Pabuccu, Aybuke; Erduran, Sibel
2017-01-01
There exists bias among students that learning organic chemistry topics requires rote learning. In this paper, we address such bias through an organic chemistry activity designed to promote argumentation. We investigated how pre-service science teachers engage in an argumentation about conformational analysis. Analysis of the outcomes concentrated…
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Is in-group bias culture-dependent? A meta-analysis across 18 societies.
Fischer, Ronald; Derham, Crysta
2016-01-01
We report a meta-analysis on the relationship between in-group bias and culture. Our focus is on whether broad macro-contextual variables influence the extent to which individuals favour their in-group. Data from 21,266 participants from 18 societies included in experimental and survey studies were available. Using Hofstede's (1980) and Schwartz (2006) culture-level predictors in a 3-level mixed-effects meta-analysis, we found strong support for the uncertainty-reduction hypothesis. An interaction between Autonomy and real vs artificial groups suggested that in low autonomy contexts, individuals show greater in-group bias for real groups. Implications for social identity theory and intergroup conflict are outlined.
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Novel semiconducting boron carbide/pyridine polymers for neutron detection at zero bias
Energy Technology Data Exchange (ETDEWEB)
Echeverria, Elena; Enders, A.; Dowben, P.A. [University of Nebraska-Lincoln, Department of Physics and Astronomy, Lincoln, NE (United States); James, Robinson; Chiluwal, Umesh; Gapfizi, Richard; Tae, Jae-Do; Driver, M. Sky; Kelber, Jeffry A. [University of North Texas, Department of Chemistry, Denton, TX (United States); Pasquale, Frank L. [University of North Texas, Department of Chemistry, Denton, TX (United States); Lam Research Corporation, PECVD Business Unit, Tualatin, OR (United States); Colon Santana, Juan A. [Center for Energy Sciences Research, Lincoln, NE (United States)
2014-09-19
Thin films containing aromatic pyridine moieties bonded to boron, in the partially dehydrogenated boron-rich icosahedra (B{sub 10}C{sub 2}H{sub X}), prove to be an effective material for neutron detection applications when deposited on n-doped (100) silicon substrates. The characteristic I-V curves for the heterojunction diodes exhibit strong rectification and largely unperturbed normalized reverse bias leakage currents with increasing pyridine content. The neutron capture generated pulses from these heterojunction diodes were obtained at zero bias voltage although without the signatures of complete electron-hole collection. These results suggest that modifications to boron carbide may result in better neutron voltaic materials. (orig.)
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Social science. Publication bias in the social sciences: unlocking the file drawer.
Franco, Annie; Malhotra, Neil; Simonovits, Gabor
2014-09-19
We studied publication bias in the social sciences by analyzing a known population of conducted studies--221 in total--in which there is a full accounting of what is published and unpublished. We leveraged Time-sharing Experiments in the Social Sciences (TESS), a National Science Foundation-sponsored program in which researchers propose survey-based experiments to be run on representative samples of American adults. Because TESS proposals undergo rigorous peer review, the studies in the sample all exceed a substantial quality threshold. Strong results are 40 percentage points more likely to be published than are null results and 60 percentage points more likely to be written up. We provide direct evidence of publication bias and identify the stage of research production at which publication bias occurs: Authors do not write up and submit null findings. Copyright © 2014, American Association for the Advancement of Science.
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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.
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Applications of machine learning in cancer prediction and prognosis.
Cruz, Joseph A; Wishart, David S
2007-02-11
Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on "older" technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.
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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’...
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Infants learn better from left to right: a directional bias in infants' sequence learning.
Bulf, Hermann; de Hevia, Maria Dolores; Gariboldi, Valeria; Macchi Cassia, Viola
2017-05-26
A wealth of studies show that human adults map ordered information onto a directional spatial continuum. We asked whether mapping ordinal information into a directional space constitutes an early predisposition, already functional prior to the acquisition of symbolic knowledge and language. While it is known that preverbal infants represent numerical order along a left-to-right spatial continuum, no studies have investigated yet whether infants, like adults, organize any kind of ordinal information onto a directional space. We investigated whether 7-month-olds' ability to learn high-order rule-like patterns from visual sequences of geometric shapes was affected by the spatial orientation of the sequences (left-to-right vs. right-to-left). Results showed that infants readily learn rule-like patterns when visual sequences were presented from left to right, but not when presented from right to left. This result provides evidence that spatial orientation critically determines preverbal infants' ability to perceive and learn ordered information in visual sequences, opening to the idea that a left-to-right spatially organized mental representation of ordered dimensions might be rooted in biologically-determined constraints on human brain development.
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Perry, Sylvia P.; Dovidio, John F.; Murphy, Mary C.; van Ryn, Michelle
2015-01-01
Two correlational studies investigated the joint effect of Bias Awareness—a new individual difference measure that assesses Whites’ awareness and concern about their propensity to be biased—and prejudice on Whites’ intergroup anxiety and intended intergroup contact. Using a community sample (Study 1), we found the predicted Bias Awareness × Prejudice interaction. Prejudice was more strongly related to interracial anxiety among those high (vs. low) in Bias Awareness. Study 2 investigated potential behavioral consequences in an important real world context: medical students’ intentions for working primarily with minority patients. Study 2 replicated the Bias Awareness × Prejudice interaction and further demonstrated that interracial anxiety mediated medical students’ intentions to work with minority populations. PMID:25111552
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Does gender bias influence awards given by societies?
Holmes, Mary Anne; Asher, Pranoti; Farrington, John; Fine, Rana; Leinen, Margaret S.; LeBoy, Phoebe
2011-11-01
AGU is a participant in a U.S. National Science Foundation (NSF)-funded project called Advancing Ways of Awarding Recognition in Disciplinary Societies (AWARDS), which seeks to examine whether gender bias affects selection of recipients of society awards. AGU is interested in learning why there is a higher proportion of female recipients of service and education awards over the past 2 decades. Combined with a lower rate of receipt of research awards, these results suggest that implicit (subconscious) bias in favor of male candidates still influences awardee selection. Six other professional societies (American Chemical Society, American Mathematical Society, American Society of Anesthesiologists, Mathematical Association of America, Society for Neuroscience, and Society for Industrial and Applied Mathematics) are participating in the project. Volunteers from each participant society attended an Association for Women in Science (AWIS)-sponsored workshop in May 2010 to examine data and review literature on best practices for fair selection of society awardees. A draft proposal for implementing these practices will be brought before the AGU Council and the Honors and Recognition Committee at their upcoming meetings.
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Contextual Mobile Learning Strongly Related to Industrial Activities: Principles and Case Study
David, Bertrand; Yin, Chuantao; Chalon, René
2010-01-01
M-learning (mobile learning) can take various forms. We are interested in contextualized M-learning, i.e. the training related to the situation physically or logically localized. Contextualization and pervasivity are important aspects of our approach. We propose in particular MOCOCO principles (Mobility - COntextualisation - COoperation) using IMERA platform (Mobile Interaction in the Augmented Real Environment) covering our university campus in which we prototype and test our approach. We ar...
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Blanco, Fernando; Barberia, Itxaso; Matute, Helena
2015-01-01
In the reasoning literature, paranormal beliefs have been proposed to be linked to two related phenomena: a biased perception of causality and a biased information-sampling strategy (believers tend to test fewer hypotheses and prefer confirmatory information). In parallel, recent contingency learning studies showed that, when two unrelated events coincide frequently, individuals interpret this ambiguous pattern as evidence of a causal relationship. Moreover, the latter studies indicate that sampling more cause-present cases than cause-absent cases strengthens the illusion. If paranormal believers actually exhibit a biased exposure to the available information, they should also show this bias in the contingency learning task: they would in fact expose themselves to more cause-present cases than cause-absent trials. Thus, by combining the two traditions, we predicted that believers in the paranormal would be more vulnerable to developing causal illusions in the laboratory than nonbelievers because there is a bias in the information they experience. In this study, we found that paranormal beliefs (measured using a questionnaire) correlated with causal illusions (assessed by using contingency judgments). As expected, this correlation was mediated entirely by the believers' tendency to expose themselves to more cause-present cases. The association between paranormal beliefs, biased exposure to information, and causal illusions was only observed for ambiguous materials (i.e., the noncontingent condition). In contrast, the participants' ability to detect causal relationships which did exist (i.e., the contingent condition) was unaffected by their susceptibility to believe in paranormal phenomena.
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Directory of Open Access Journals (Sweden)
Fernando Blanco
Full Text Available In the reasoning literature, paranormal beliefs have been proposed to be linked to two related phenomena: a biased perception of causality and a biased information-sampling strategy (believers tend to test fewer hypotheses and prefer confirmatory information. In parallel, recent contingency learning studies showed that, when two unrelated events coincide frequently, individuals interpret this ambiguous pattern as evidence of a causal relationship. Moreover, the latter studies indicate that sampling more cause-present cases than cause-absent cases strengthens the illusion. If paranormal believers actually exhibit a biased exposure to the available information, they should also show this bias in the contingency learning task: they would in fact expose themselves to more cause-present cases than cause-absent trials. Thus, by combining the two traditions, we predicted that believers in the paranormal would be more vulnerable to developing causal illusions in the laboratory than nonbelievers because there is a bias in the information they experience. In this study, we found that paranormal beliefs (measured using a questionnaire correlated with causal illusions (assessed by using contingency judgments. As expected, this correlation was mediated entirely by the believers' tendency to expose themselves to more cause-present cases. The association between paranormal beliefs, biased exposure to information, and causal illusions was only observed for ambiguous materials (i.e., the noncontingent condition. In contrast, the participants' ability to detect causal relationships which did exist (i.e., the contingent condition was unaffected by their susceptibility to believe in paranormal phenomena.
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Petukhov, A. M.; Soldatov, E. Yu
2017-12-01
Separation of electroweak component from strong component of associated Zγ production on hadron colliders is a very challenging task due to identical final states of such processes. The only difference is the origin of two leading jets in these two processes. Rectangular cuts on jet kinematic variables from ATLAS/CMS 8 TeV Zγ experimental analyses were improved using machine learning techniques. New selection variables were also tested. The expected significance of separation for LHC experiments conditions at the second datataking period (Run2) and 120 fb-1 amount of data reaches more than 5σ. Future experimental observation of electroweak Zγ production can also lead to the observation physics beyond Standard Model.
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A learning-style theory for understanding autistic behaviors
Directory of Open Access Journals (Sweden)
Ning eQian
2011-08-01
Full Text Available Understanding autism’s ever-expanding array of behaviors, from sensation to cognition, is a major challenge. We posit that autistic and typically-developing brains implement different algorithms that are better suited to learn, represent, and process different tasks; consequently, they develop different interests and behaviors. Computationally, a continuum of algorithms exists, from lookup-table (LUT learning, which aims to store experiences precisely, to interpolation (INT learning, which focuses on extracting underlying statistical structure (regularities from experiences. We hypothesize that autistic and typical brains, respectively, are biased toward LUT and INT learning, in low and high dimensional feature spaces, possibly because of their narrow and broad tuning functions. The LUT style is good at learning relationships that are local, precise, rigid, and contain little regularity for generalization (e.g., the name-number association in a phonebook. However, it is poor at learning relationships that are context dependent, noisy, flexible, and do contain regularities for generalization (e.g., associations between gaze direction and intention, language and meaning, sensory input and interpretation, motor-control signal and movement, and social situation and proper response. The LUT style poorly compresses information, resulting in inefficiency, sensory overload (overwhelm, restricted interests, and resistance to change. It also leads to poor prediction and anticipation, frequent surprises and over-reaction (hyper-sensitivity, impaired attentional selection and switching, concreteness, strong local focus, weak adaptation, and superior and inferior performances on simple and complex tasks. The spectrum nature of autism can be explained by different degrees of LUT learning among different individuals, and in different systems of the same individual. Our theory suggests that therapy should focus on training autistic LUT algorithm to learn
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A Learning-Style Theory for Understanding Autistic Behaviors
Qian, Ning; Lipkin, Richard M.
2011-01-01
Understanding autism's ever-expanding array of behaviors, from sensation to cognition, is a major challenge. We posit that autistic and typically developing brains implement different algorithms that are better suited to learn, represent, and process different tasks; consequently, they develop different interests and behaviors. Computationally, a continuum of algorithms exists, from lookup table (LUT) learning, which aims to store experiences precisely, to interpolation (INT) learning, which focuses on extracting underlying statistical structure (regularities) from experiences. We hypothesize that autistic and typical brains, respectively, are biased toward LUT and INT learning, in low- and high-dimensional feature spaces, possibly because of their narrow and broad tuning functions. The LUT style is good at learning relationships that are local, precise, rigid, and contain little regularity for generalization (e.g., the name–number association in a phonebook). However, it is poor at learning relationships that are context dependent, noisy, flexible, and do contain regularities for generalization (e.g., associations between gaze direction and intention, language and meaning, sensory input and interpretation, motor-control signal and movement, and social situation and proper response). The LUT style poorly compresses information, resulting in inefficiency, sensory overload (overwhelm), restricted interests, and resistance to change. It also leads to poor prediction and anticipation, frequent surprises and over-reaction (hyper-sensitivity), impaired attentional selection and switching, concreteness, strong local focus, weak adaptation, and superior and inferior performances on simple and complex tasks. The spectrum nature of autism can be explained by different degrees of LUT learning among different individuals, and in different systems of the same individual. Our theory suggests that therapy should focus on training autistic LUT algorithm to learn regularities
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DEFF Research Database (Denmark)
Lauridsen, Karen M.; Lauridsen, Ole
Ole Lauridsen, Aarhus School of Business and Social Sciences, Aarhus University, Denmark Karen M. Lauridsen, Aarhus School of Business and Social Sciences, Aarhus University, Denmark Learning Styles in Higher Education – Learning How to Learn Applying learning styles (LS) in higher education...... by Constructivist learning theory and current basic knowledge of how the brain learns. The LS concept will thus be placed in a broader learning theoretical context as a strong learning and teaching tool. Participants will be offered the opportunity to have their own LS preferences established before...... teaching leads to positive results and enhanced student learning. However, learning styles should not only be considered a didactic matter for the teacher, but also a tool for the individual students to improve their learning capabilities – not least in contexts where information is not necessarily...
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Is Bible Translation "Imperialist"? Challenging Another Anti-Christian Bias in the Academy
Adrian, William
2007-01-01
A strong anti-Christian bias exists in the modern American university. It has been documented by George Marsden in his 1994 book, "The Soul of the American University," and by a growing number of other scholars. The modern university response to the history of Bible translation movements provides another example of the anti-Christian…
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Investor’s Commitment Bias and Escalation of Firm’s Investment Decision
Directory of Open Access Journals (Sweden)
Anis JARBOUI
2012-12-01
Full Text Available This study examines the reasons of perseverance in firm’s investment decision. It shows the possible influence of three closely related features which are: firm’s financial indicators, investor’s risk profile, and investor’s commitment bias, on a firm’s investment decisions escalation. This study aims to provide evidence as to whether investor considers the financial and risk’s perception features (financial strength and risk profile to persevere his initial investment decision while he notes a high level of commitment bias. The proposed model of this paper uses GLM univariate data analyses to examine this relationship. Investor’s risk profile and his commitment bias have been measured by means of a questionnaire comprising several items. As for the selected sample, it has been composed of some 360 Tunisian individual investors. Our results have revealed that investors pay more attention to keep their psychology comfort than their financial comfort. It exposed the importance of the investor’s commitment bias and its risk perception in explaining investment decision escalation. Moreover results shows that there is strong and significant empirical relationship linking the escalatory behavior in investment decision and the interaction effects between the three independent variables. This means that, in practice, investors consider the three factors simultaneously.
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Human and organizational biases affecting the management of safety
Energy Technology Data Exchange (ETDEWEB)
Reiman, Teemu, E-mail: teemu.reiman@vtt.fi [VTT, Espoo (Finland); Rollenhagen, Carl [KTH, Stockholm (Sweden)
2011-10-15
Management of safety is always based on underlying models or theories of organization, human behavior and system safety. The aim of the article is to review and describe a set of potential biases in these models and theories. We will outline human and organizational biases that have an effect on the management of safety in four thematic areas: beliefs about human behavior, beliefs about organizations, beliefs about information and safety models. At worst, biases in these areas can lead to an approach where people are treated as isolated and independent actors who make (bad) decisions in a social vacuum and who pose a threat to safety. Such an approach aims at building barriers and constraints to human behavior and neglects the measures aiming at providing prerequisites and organizational conditions for people to work effectively. This reductionist view of safety management can also lead to too drastic a strong separation of so-called human factors from technical issues, undermining the holistic view of system safety. Human behavior needs to be understood in the context of people attempting (together) to make sense of themselves and their environment, and act based on perpetually incomplete information while relying on social conventions, affordances provided by the environment and the available cognitive heuristics. In addition, a move toward a positive view of the human contribution to safety is needed. Systemic safety management requires an increased understanding of various normal organizational phenomena - in this paper discussed from the point of view of biases - coupled with a systemic safety culture that encourages and endorses a holistic view of the workings and challenges of the socio-technical system in question. - Highlights: > Biases in safety management approaches are reviewed and described. > Four thematic areas are covered: human behavior, organizations, information, safety models. > The biases influence how safety management is defined, executed
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Human and organizational biases affecting the management of safety
International Nuclear Information System (INIS)
Reiman, Teemu; Rollenhagen, Carl
2011-01-01
Management of safety is always based on underlying models or theories of organization, human behavior and system safety. The aim of the article is to review and describe a set of potential biases in these models and theories. We will outline human and organizational biases that have an effect on the management of safety in four thematic areas: beliefs about human behavior, beliefs about organizations, beliefs about information and safety models. At worst, biases in these areas can lead to an approach where people are treated as isolated and independent actors who make (bad) decisions in a social vacuum and who pose a threat to safety. Such an approach aims at building barriers and constraints to human behavior and neglects the measures aiming at providing prerequisites and organizational conditions for people to work effectively. This reductionist view of safety management can also lead to too drastic a strong separation of so-called human factors from technical issues, undermining the holistic view of system safety. Human behavior needs to be understood in the context of people attempting (together) to make sense of themselves and their environment, and act based on perpetually incomplete information while relying on social conventions, affordances provided by the environment and the available cognitive heuristics. In addition, a move toward a positive view of the human contribution to safety is needed. Systemic safety management requires an increased understanding of various normal organizational phenomena - in this paper discussed from the point of view of biases - coupled with a systemic safety culture that encourages and endorses a holistic view of the workings and challenges of the socio-technical system in question. - Highlights: → Biases in safety management approaches are reviewed and described. → Four thematic areas are covered: human behavior, organizations, information, safety models. → The biases influence how safety management is defined
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Pauwels, V. R. N.; DeLannoy, G. J. M.; Hendricks Franssen, H.-J.; Vereecken, H.
2013-01-01
In this paper, we present a two-stage hybrid Kalman filter to estimate both observation and forecast bias in hydrologic models, in addition to state variables. The biases are estimated using the discrete Kalman filter, and the state variables using the ensemble Kalman filter. A key issue in this multi-component assimilation scheme is the exact partitioning of the difference between observation and forecasts into state, forecast bias and observation bias updates. Here, the error covariances of the forecast bias and the unbiased states are calculated as constant fractions of the biased state error covariance, and the observation bias error covariance is a function of the observation prediction error covariance. In a series of synthetic experiments, focusing on the assimilation of discharge into a rainfall-runoff model, it is shown that both static and dynamic observation and forecast biases can be successfully estimated. The results indicate a strong improvement in the estimation of the state variables and resulting discharge as opposed to the use of a bias-unaware ensemble Kalman filter. Furthermore, minimal code modification in existing data assimilation software is needed to implement the method. The results suggest that a better performance of data assimilation methods should be possible if both forecast and observation biases are taken into account.
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Directory of Open Access Journals (Sweden)
V. R. N. Pauwels
2013-09-01
Full Text Available In this paper, we present a two-stage hybrid Kalman filter to estimate both observation and forecast bias in hydrologic models, in addition to state variables. The biases are estimated using the discrete Kalman filter, and the state variables using the ensemble Kalman filter. A key issue in this multi-component assimilation scheme is the exact partitioning of the difference between observation and forecasts into state, forecast bias and observation bias updates. Here, the error covariances of the forecast bias and the unbiased states are calculated as constant fractions of the biased state error covariance, and the observation bias error covariance is a function of the observation prediction error covariance. In a series of synthetic experiments, focusing on the assimilation of discharge into a rainfall-runoff model, it is shown that both static and dynamic observation and forecast biases can be successfully estimated. The results indicate a strong improvement in the estimation of the state variables and resulting discharge as opposed to the use of a bias-unaware ensemble Kalman filter. Furthermore, minimal code modification in existing data assimilation software is needed to implement the method. The results suggest that a better performance of data assimilation methods should be possible if both forecast and observation biases are taken into account.
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Better than I thought: positive evaluation bias in hypomania.
Directory of Open Access Journals (Sweden)
Liam Mason
Full Text Available Mania is characterised by increased impulsivity and risk-taking, and psychological accounts argue that these features may be due to hypersensitivity to reward. The neurobiological mechanisms remain poorly understood. Here we examine reinforcement learning and sensitivity to both reward and punishment outcomes in hypomania-prone individuals not receiving pharmacotherapy.We recorded EEG from 45 healthy individuals split into three groups by low, intermediate and high self-reported hypomanic traits. Participants played a computerised card game in which they learned the reward contingencies of three cues. Neural responses to monetary gain and loss were measured using the feedback-related negativity (FRN, a component implicated in motivational outcome evaluation and reinforcement learning.As predicted, rewards elicited a smaller FRN in the hypomania-prone group relative to the low hypomania group, indicative of greater reward responsiveness. The hypomania-prone group also showed smaller FRN to losses, indicating diminished response to negative feedback.Our findings indicate that proneness to hypomania is associated with both reward hypersensitivity and discounting of punishment. This positive evaluation bias may be driven by aberrant reinforcement learning signals, which fail to update future expectations. This provides a possible neural mechanism explaining risk-taking and impaired reinforcement learning in BD. Further research will be needed to explore the potential value of the FRN as a biological vulnerability marker for mania and pathological risk-taking.
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Bond and Equity Home Bias and Foreign Bias: an International Study
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...
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The Ugly Truth About Ourselves and Our Robot Creations: The Problem of Bias and Social Inequity.
Howard, Ayanna; Borenstein, Jason
2017-09-21
Recently, there has been an upsurge of attention focused on bias and its impact on specialized artificial intelligence (AI) applications. Allegations of racism and sexism have permeated the conversation as stories surface about search engines delivering job postings for well-paying technical jobs to men and not women, or providing arrest mugshots when keywords such as "black teenagers" are entered. Learning algorithms are evolving; they are often created from parsing through large datasets of online information while having truth labels bestowed on them by crowd-sourced masses. These specialized AI algorithms have been liberated from the minds of researchers and startups, and released onto the public. Yet intelligent though they may be, these algorithms maintain some of the same biases that permeate society. They find patterns within datasets that reflect implicit biases and, in so doing, emphasize and reinforce these biases as global truth. This paper describes specific examples of how bias has infused itself into current AI and robotic systems, and how it may affect the future design of such systems. More specifically, we draw attention to how bias may affect the functioning of (1) a robot peacekeeper, (2) a self-driving car, and (3) a medical robot. We conclude with an overview of measures that could be taken to mitigate or halt bias from permeating robotic technology.
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Characterizing sampling and quality screening biases in infrared and microwave limb sounding
Millán, Luis F.; Livesey, Nathaniel J.; Santee, Michelle L.; von Clarmann, Thomas
2018-03-01
This study investigates orbital sampling biases and evaluates the additional impact caused by data quality screening for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Aura Microwave Limb Sounder (MLS). MIPAS acts as a proxy for typical infrared limb emission sounders, while MLS acts as a proxy for microwave limb sounders. These biases were calculated for temperature and several trace gases by interpolating model fields to real sampling patterns and, additionally, screening those locations as directed by their corresponding quality criteria. Both instruments have dense uniform sampling patterns typical of limb emission sounders, producing almost identical sampling biases. However, there is a substantial difference between the number of locations discarded. MIPAS, as a mid-infrared instrument, is very sensitive to clouds, and measurements affected by them are thus rejected from the analysis. For example, in the tropics, the MIPAS yield is strongly affected by clouds, while MLS is mostly unaffected. The results show that upper-tropospheric sampling biases in zonally averaged data, for both instruments, can be up to 10 to 30 %, depending on the species, and up to 3 K for temperature. For MIPAS, the sampling reduction due to quality screening worsens the biases, leading to values as large as 30 to 100 % for the trace gases and expanding the 3 K bias region for temperature. This type of sampling bias is largely induced by the geophysical origins of the screening (e.g. clouds). Further, analysis of long-term time series reveals that these additional quality screening biases may affect the ability to accurately detect upper-tropospheric long-term changes using such data. In contrast, MLS data quality screening removes sufficiently few points that no additional bias is introduced, although its penetration is limited to the upper troposphere, while MIPAS may cover well into the mid-troposphere in cloud-free scenarios. We emphasize that the
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Public policies: right to learn and formative assessment
Directory of Open Access Journals (Sweden)
Antonio Chizzotti
2016-09-01
Full Text Available This paper deals with the right to learn in school type education and considers the assessment as assurance of teaching and learning quality. It deals with the current evaluation processes and discriminatory misconceptions of merely summative assessments, which tend to qualify students. This text evaluates the punitive bias of meritocratic grading of learning and argues that only formative assessment can ensure the right to learn
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The role of vision, speed, and attention in overcoming directional biases during arm movements.
Dounskaia, Natalia; Goble, Jacob A
2011-03-01
Previous research has revealed directional biases (preferences to select movements in specific directions) during horizontal arm movements with the use of a free-stroke drawing task. The biases were interpreted as a result of a tendency to generate motion at either the shoulder or elbow (leading joint) and move the other (subordinate) joint predominantly passively to avoid neural effort for control of interaction torque. Here, we examined influence of vision, movement speed, and attention on the directional biases. Participants performed the free-stroke drawing task, producing center-out strokes in randomly selected directions. Movements were performed with and without vision and at comfortable and fast pace. A secondary, cognitive task was used to distract attention. Preferred directions remained the same in all conditions. Bias strength mildly increased without vision, especially during fast movements. Striking increases in bias strength were caused by the secondary task, pointing to additional cognitive load associated with selection of movements in the non-preferred directions. Further analyses demonstrated that the tendency to minimize active interference with interaction torque at the subordinate joint matched directional biases in all conditions. This match supports the explanation of directional biases as a result of a tendency to minimize neural effort for interaction torque control. The cognitive load may enhance this tendency in two ways, directly, by reducing neural capacity for interaction torque control, and indirectly, by decreasing capacity of working memory that stores visited directions. The obtained results suggest strong directional biases during daily activities because natural arm movements usually subserve cognitive tasks.
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Dynamic remodeling of in-group bias during the 2008 presidential election.
Rand, David G; Pfeiffer, Thomas; Dreber, Anna; Sheketoff, Rachel W; Wernerfelt, Nils C; Benkler, Yochai
2009-04-14
People often favor members of their own group, while discriminating against members of other groups. Such in-group favoritism has been shown to play an important role in human cooperation. However, in the face of changing conflicts and shifting alliances, it is essential for group identities to be flexible. Using the dictator game from behavioral economics, we demonstrate the remodeling of group identities among supporters of Democratic presidential candidates Barack Obama and Hillary Clinton. After Clinton's concession in June 2008, Democrats were more generous toward supporters of their own preferred candidate than to supporters of the other Democratic candidate. The bias observed in June persisted into August, and disappeared only in early September after the Democratic National Convention. We also observe a strong gender effect, with bias both appearing and subsiding among men only. This experimental study illustrates a dynamic change in bias, tracking the realignment of real world conflict lines and public efforts to reconstitute group identity. The change in salient group identity we describe here likely contributed to the victory of Barack Obama in the 2008 presidential election.
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Bolund, Elisabeth; Lummaa, Virpi; Smith, Ken R.; Hanson, Heidi A.; Maklakov, Alexei A.
2016-01-01
The causes underlying sex differences in lifespan are strongly debated. While females commonly outlive males in humans, this is generally less pronounced in societies before the demographic transition to low mortality and fertility rates. Life-history theory suggests that reduced reproduction should benefit female lifespan when females pay higher costs of reproduction than males. Using unique longitudinal demographic records on 140,600 reproducing individuals from the Utah Population Database, we demonstrate a shift from male-biased to female-biased adult lifespans in individuals born before versus during the demographic transition. Only women paid a cost of reproduction in terms of shortened post-reproductive lifespan at high parities. Therefore, as fertility decreased over time, female lifespan increased, while male lifespan remained largely stable, supporting the theory that differential costs of reproduction in the two sexes result in the shifting patterns of sex differences in lifespan across human populations. Further, our results have important implications for demographic forecasts in human populations and advance our understanding of lifespan evolution. PMID:27087670
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Czech Academy of Sciences Publication Activity Database
Fornůsková, Alena; Petit, E.J.; Bartonička, T.; Kaňuch, P.; Butet, A.; Řehák, Z.; Bryja, Josef
2014-01-01
Roč. 113, č. 4 (2014), s. 1115-1125 ISSN 0024-4066 R&D Projects: GA ČR GA206/06/0954 Institutional support: RVO:68081766 Keywords : dialects * maternal effects * sex-biased dispersal * philopatry * vocal learning Subject RIV: EG - Zoology Impact factor: 2.264, year: 2014
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In-plane and perpendicular exchange bias in [Pt/Co]/NiO multilayers
Energy Technology Data Exchange (ETDEWEB)
Lin, K.W.; Guo, J.Y.; Chang, S.C.; Ouyang, H. [Department of Materials Science and Engineering, National Chung Hsing University, Taichung 402 (China); Kahwaji, S.; Van Lierop, J. [Department of Physics and Astronomy, University of Manitoba, Winnipeg, R3T 2N2 (Canada); Phuoc, N.N.; Suzuki, T. [Information Storage Materials Laboratory, Toyota Technological Institute, Nagoya 468-8511 (Japan)
2007-12-15
Exchange bias in [Pt/Co]/NiO multilayers were studied as a function of film thickness and [Pt/Co] layer repetition. A strong temperature dependence of the coercivity, H{sub c}, and exchange bias field, H{sub ex}, was observed for the thick and thinnest [Pt/Co]/NiO multilayers. While the thinnest [Pt(3 nm)/Co(1.25 nm)]{sub 4}/NiO multilayers exhibits no in-plane exchange bias field, a perpendicular H{sub ex} {sub perpendicular} {sub to} {proportional_to} -150 Oe at 80 K was measured. By contrast, the thickest [Pt(12 nm)/Co(10 nm)]{sub 1}/NiO multilayers exhibited an in-plane H{sub ex//}{proportional_to}-600 Oe (with H{sub ex//}{proportional_to}-1300 Oe at 5 K) with no measurable perpendicular exchange bias field. The estimated interfacial exchange coupling energy implies the effective Co layer thickness contributing to the exchange bias is effective only in Co layer in contact with NiO bottom layer. AC susceptibility and the temperature dependence of H{sub ex} show that the a 1.25 nm thick Co component enables perpendicular exchange bias with a reduced blocking temperature T{sub B}{proportional_to}200 K, compared to that (T{sub B}{proportional_to}250 K) for the thick [Pt/Co]/NiO multilayers. This is attributed to disordered CoPt phases that formed due to intermixing between Co and Pt during deposition. (copyright 2008 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
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International Nuclear Information System (INIS)
Matsuyama, Shoichiro; Shinohara, Shunjiro
2001-01-01
A large density profile modification was successfully obtained by voltage biasing to electrodes inserted in a RF (radio frequency) produced, magnetized plasma, and formation of strong shear of azimuthal plasma rotation velocity in a supersonic regime was found. For the case of biasing to an electrode near the central plasma region, two types of density transitions were observed in the outer plasma region: one was an oscillatory transition between two states, and the other was a transition from high to low density states with a large reduction of density fluctuations. (author)
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Energy Technology Data Exchange (ETDEWEB)
Matsuyama, Shoichiro; Shinohara, Shunjiro [Kyushu Univ., Interdisciplinary Graduate School of Engineering Sciences, Fukuoka (Japan)
2001-07-01
A large density profile modification was successfully obtained by voltage biasing to electrodes inserted in a RF (radio frequency) produced, magnetized plasma, and formation of strong shear of azimuthal plasma rotation velocity in a supersonic regime was found. For the case of biasing to an electrode near the central plasma region, two types of density transitions were observed in the outer plasma region: one was an oscillatory transition between two states, and the other was a transition from high to low density states with a large reduction of density fluctuations. (author)
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Place learning overrides innate behaviors in Drosophila.
Baggett, Vincent; Mishra, Aditi; Kehrer, Abigail L; Robinson, Abbey O; Shaw, Paul; Zars, Troy
2018-03-01
Animals in a natural environment confront many sensory cues. Some of these cues bias behavioral decisions independent of experience, and action selection can reveal a stimulus-response (S-R) connection. However, in a changing environment it would be a benefit for an animal to update behavioral action selection based on experience, and learning might modify even strong S-R relationships. How animals use learning to modify S-R relationships is a largely open question. Three sensory stimuli, air, light, and gravity sources were presented to individual Drosophila melanogaster in both naïve and place conditioning situations. Flies were tested for a potential modification of the S-R relationships of anemotaxis, phototaxis, and negative gravitaxis by a contingency that associated place with high temperature. With two stimuli, significant S-R relationships were abandoned when the cue was in conflict with the place learning contingency. The role of the dunce ( dnc ) cAMP-phosphodiesterase and the rutabaga ( rut ) adenylyl cyclase were examined in all conditions. Both dnc 1 and rut 2080 mutant flies failed to display significant S-R relationships with two attractive cues, and have characteristically lower conditioning scores under most conditions. Thus, learning can have profound effects on separate native S-R relationships in multiple contexts, and mutation of the dnc and rut genes reveal complex effects on behavior. © 2018 Baggett et al.; Published by Cold Spring Harbor Laboratory Press.
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Prototypes and same-gender bias in perceptions of hiring discrimination.
Carlsson, Rickard; Sinclair, Samantha
2018-01-01
The present study investigated the relative importance of two explanations behind perceptions of gender discrimination in hiring: prototypes and same-gender bias. According to the prototype explanation, people perceive an event as discrimination to the extent that it fits their preconceptions of typical discrimination. In contrast, the same-gender bias explanation asserts that people more readily detect discrimination toward members of their own gender. In four experiments (n = 797), women and men made considerably stronger discrimination attributions, and were moderately more discouraged from seeking work, when the victim was female rather than male. Further, a series of regressions analyses showed beliefs in discrimination of women to be moderately correlated with discrimination attributions of female victims, but little added explanatory value of participant gender, stigma consciousness, or feminist identification. The results offer strong support for the prototype explanation.
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Cognitive Bias in Systems Verification
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.
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Length bias correction in one-day cross-sectional assessments - The nutritionDay study.
Frantal, Sophie; Pernicka, Elisabeth; Hiesmayr, Michael; Schindler, Karin; Bauer, Peter
2016-04-01
A major problem occurring in cross-sectional studies is sampling bias. Length of hospital stay (LOS) differs strongly between patients and causes a length bias as patients with longer LOS are more likely to be included and are therefore overrepresented in this type of study. To adjust for the length bias higher weights are allocated to patients with shorter LOS. We determined the effect of length-bias adjustment in two independent populations. Length-bias correction is applied to the data of the nutritionDay project, a one-day multinational cross-sectional audit capturing data on disease and nutrition of patients admitted to hospital wards with right-censoring after 30 days follow-up. We applied the weighting method for estimating the distribution function of patient baseline variables based on the method of non-parametric maximum likelihood. Results are validated using data from all patients admitted to the General Hospital of Vienna between 2005 and 2009, where the distribution of LOS can be assumed to be known. Additionally, a simplified calculation scheme for estimating the adjusted distribution function of LOS is demonstrated on a small patient example. The crude median (lower quartile; upper quartile) LOS in the cross-sectional sample was 14 (8; 24) and decreased to 7 (4; 12) when adjusted. Hence, adjustment for length bias in cross-sectional studies is essential to get appropriate estimates. Copyright © 2015 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
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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
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Ribeiro, Andre S; Eales, Brenda A; Biddle, Fred G
2013-05-15
The corpus callosum (CC) and hippocampal commissure (HC) are major interhemispheric connections whose role in brain function and behaviors is fascinating and contentious. Paw preference of laboratory mice is a genetically regulated, adaptive behavior, continuously shaped by training and learning. We studied variation with training in paw-preference in mice of the 9XCA/WahBid ('9XCA') recombinant inbred strain, selected for complete absence of the CC and severely reduced HC. We measured sequences of paw choices in 9XCA mice in two training sessions in unbiased test chambers, separated by one-week. We compared them with sequences of paw choices in model non-learner mice that have random unbiased paw choices and with those of C57BL/6JBid ('C57BL/6J') mice that have normal interhemispheric connections and learn a paw preference. Positive autocorrelation between successive paw choices during each session and change in paw-preference bias between sessions indicate that 9XCA mice have weak, but not null, learning skills. We tested the effect of the forebrain commissural defect on paw-preference learning with the independent BTBR T+ tf/J ('BTBR') mouse strain that has a genetically identical, non-complementing commissural trait. BTBR has weak short-term and long-term memory skills, identical to 9XCA. The results provide strong evidence that CC and HC contribute in memory function and formation of paw-preference biases. Copyright © 2013 Elsevier B.V. All rights reserved.
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Directory of Open Access Journals (Sweden)
David Herrera
Full Text Available In two-alternative discrimination tasks, experimenters usually randomize the location of the rewarded stimulus so that systematic behavior with respect to irrelevant stimuli can only produce chance performance on the learning curves. One way to achieve this is to use random numbers derived from a discrete binomial distribution to create a 'full random training schedule' (FRS. When using FRS, however, sporadic but long laterally-biased training sequences occur by chance and such 'input biases' are thought to promote the generation of laterally-biased choices (i.e., 'output biases'. As an alternative, a 'Gellerman-like training schedule' (GLS can be used. It removes most input biases by prohibiting the reward from appearing on the same location for more than three consecutive trials. The sequence of past rewards obtained from choosing a particular discriminative stimulus influences the probability of choosing that same stimulus on subsequent trials. Assuming that the long-term average ratio of choices matches the long-term average ratio of reinforcers, we hypothesized that a reduced amount of input biases in GLS compared to FRS should lead to a reduced production of output biases. We compared the choice patterns produced by a 'Rational Decision Maker' (RDM in response to computer-generated FRS and GLS training sequences. To create a virtual RDM, we implemented an algorithm that generated choices based on past rewards. Our simulations revealed that, although the GLS presented fewer input biases than the FRS, the virtual RDM produced more output biases with GLS than with FRS under a variety of test conditions. Our results reveal that the statistical and temporal properties of training sequences interacted with the RDM to influence the production of output biases. Thus, discrete changes in the training paradigms did not translate linearly into modifications in the pattern of choices generated by a RDM. Virtual RDMs could be further employed to guide
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Herrera, David; Treviño, Mario
2015-01-01
In two-alternative discrimination tasks, experimenters usually randomize the location of the rewarded stimulus so that systematic behavior with respect to irrelevant stimuli can only produce chance performance on the learning curves. One way to achieve this is to use random numbers derived from a discrete binomial distribution to create a 'full random training schedule' (FRS). When using FRS, however, sporadic but long laterally-biased training sequences occur by chance and such 'input biases' are thought to promote the generation of laterally-biased choices (i.e., 'output biases'). As an alternative, a 'Gellerman-like training schedule' (GLS) can be used. It removes most input biases by prohibiting the reward from appearing on the same location for more than three consecutive trials. The sequence of past rewards obtained from choosing a particular discriminative stimulus influences the probability of choosing that same stimulus on subsequent trials. Assuming that the long-term average ratio of choices matches the long-term average ratio of reinforcers, we hypothesized that a reduced amount of input biases in GLS compared to FRS should lead to a reduced production of output biases. We compared the choice patterns produced by a 'Rational Decision Maker' (RDM) in response to computer-generated FRS and GLS training sequences. To create a virtual RDM, we implemented an algorithm that generated choices based on past rewards. Our simulations revealed that, although the GLS presented fewer input biases than the FRS, the virtual RDM produced more output biases with GLS than with FRS under a variety of test conditions. Our results reveal that the statistical and temporal properties of training sequences interacted with the RDM to influence the production of output biases. Thus, discrete changes in the training paradigms did not translate linearly into modifications in the pattern of choices generated by a RDM. Virtual RDMs could be further employed to guide the selection of
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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.
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Devour, Brian M.; Bell, Eric F.
2017-06-01
Accurate measurement of galaxy structures is a prerequisite for quantitative investigation of galaxy properties or evolution. Yet, the impact of galaxy inclination and dust on commonly used metrics of galaxy structure is poorly quantified. We use infrared data sets to select inclination-independent samples of disc and flattened elliptical galaxies. These samples show strong variation in Sérsic index, concentration and half-light radii with inclination. We develop novel inclination-independent galaxy structures by collapsing the light distribution in the near-infrared on to the major axis, yielding inclination-independent 'linear' measures of size and concentration. With these new metrics we select a sample of Milky Way analogue galaxies with similar stellar masses, star formation rates, sizes and concentrations. Optical luminosities, light distributions and spectral properties are all found to vary strongly with inclination: When inclining to edge-on, r-band luminosities dim by >1 magnitude, sizes decrease by a factor of 2, 'dust-corrected' estimates of star formation rate drop threefold, metallicities decrease by 0.1 dex and edge-on galaxies are half as likely to be classified as star forming. These systematic effects should be accounted for in analyses of galaxy properties.
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Avoiding boredom: Caudate and insula activity reflects boredom-elicited purchase bias.
Dal Mas, Dennis E; Wittmann, Bianca C
2017-07-01
People show a strong tendency to avoid boring situations, but the neural systems mediating this behavioural bias are yet unknown. We used functional magnetic resonance imaging (fMRI) to investigate how the anticipation of a boring task influences decisions to purchase entertainment. Participants accepted higher prices to avoid boredom compared to control tasks, and individual differences in boredom experience predicted the increase in price. This behavioural bias was associated with higher activity in the caudate nucleus during music purchases driven by boredom avoidance. Insula activation was increased during performance of the boring task and subsequently associated with individual differences in boredom-related decision making. These results identify a mechanism that drives decisions to avoid boring situations and potentially underlies consumer decisions. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Threat bias, not negativity bias, underpins differences in political ideology.
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.
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Kaatz, Anna; Carnes, Molly; Gutierrez, Belinda; Savoy, Julia; Samuel, Clem; Filut, Amarette; Pribbenow, Christine Maidl
2017-01-01
Explicit racial bias has decreased in the United States, but racial stereotypes still exist and conspire in multiple ways to perpetuate the underparticipation of Blacks in science careers. Capitalizing on the potential effectiveness of role-playing video games to promote the type of active learning required to increase awareness of and reduce subtle racial bias, we developed the video game Fair Play, in which players take on the role of Jamal, a Black male graduate student in science, who experiences discrimination in his PhD program. We describe a mixed-methods evaluation of the experience of scientific workforce trainers who played Fair Play at the National Institutes of Health Division of Training Workforce Development and Diversity program directors’ meeting in 2013 (n = 47; 76% female, n = 34; 53% nonwhite, n = 26). The evaluation findings suggest that Fair Play can promote perspective taking and increase bias literacy, which are steps toward reducing racial bias and affording Blacks equal opportunities to excel in science. PMID:28450447
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Chevuturi, A.; Turner, A. G.; Woolnough, S. J.
2016-12-01
In this study we investigate the development of biases in the Indian Ocean region in summer hindcasts of the UK Met Office coupled initialised global seasonal forecasting system, GloSea5-GC2. Previous work has demonstrated the rapid evolution of strong monsoon circulation biases over India from seasonal forecasts initialised in early May, together with coupled strong easterly wind biases on the equator. We analyse a set of three springtime start dates for the 20-year hindcast period (1992-2011) and fifteen total ensemble members for each year. We use comparisons with a variety of observations to test the rate of evolving mean-state biases in the Arabian Sea, over India, and over the equatorial Indian Ocean. Biases are all shown to develop rapidly, particularly for the circulation bias over India that is connected to convection. These circulation biases later reach the surface and lead to responses in Arabian Sea SST in accordance with coastal and Ekman upwelling processes. We also assess the evolution of radiation and turbulent heat fluxes at the surface. Meanwhile at the equator, easterly biases in surface winds are shown to develop rapidly, consistent with an SST pattern that is consistent with positive-Indian Ocean dipole mean state conditions (warm western equatorial Indian Ocean, cold east). This bias develops consistent with coupled ocean-atmosphere exchanges and Bjerknes feedback. We hypothesize that lower tropospheric easterly wind biases developing in the equatorial region originate from the surface, and also that signals of the cold bias in the eastern equatorial Indian Ocean propagate to the Bay of Bengal via coastal Kelvin waves. Earlier work has shown the utility of wind-stress corrections in the Indian Ocean for correcting the easterly winds bias there and ultimately improving the evolution of the Indian Ocean Dipole. We identify and test this wind-stress correction technique in case study years from the hindcast period to see their impact on seasonal
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Social incentives improve deliberative but not procedural learning in older adults.
Gorlick, Marissa A; Maddox, W Todd
2015-01-01
Age-related deficits are seen across tasks where learning depends on asocial feedback processing, however plasticity has been observed in some of the same tasks in social contexts suggesting a novel way to attenuate deficits. Socioemotional selectivity theory suggests this plasticity is due to a deliberative motivational shift toward achieving well-being with age (positivity effect) that reverses when executive processes are limited (negativity effect). The present study examined the interaction of feedback valence (positive, negative) and social salience (emotional face feedback - happy; angry, asocial point feedback - gain; loss) on learning in a deliberative task that challenges executive processes and a procedural task that does not. We predict that angry face feedback will improve learning in a deliberative task when executive function is challenged. We tested two competing hypotheses regarding the interactive effects of deliberative emotional biases on automatic feedback processing: (1) If deliberative emotion regulation and automatic feedback are interactive we expect happy face feedback to improve learning and angry face feedback to impair learning in older adults because cognitive control is available. (2) If deliberative emotion regulation and automatic feedback are not interactive we predict that emotional face feedback will not improve procedural learning regardless of valence. Results demonstrate that older adults show persistent deficits relative to younger adults during procedural category learning suggesting that deliberative emotional biases do not interact with automatic feedback processing. Interestingly, a subgroup of older adults identified as potentially using deliberative strategies tended to learn as well as younger adults with angry relative to happy feedback, matching the pattern observed in the deliberative task. Results suggest that deliberative emotional biases can improve deliberative learning, but have no effect on procedural learning.
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Leveraging position bias to improve peer recommendation.
Directory of Open Access Journals (Sweden)
Kristina Lerman
Full Text Available With the advent of social media and peer production, the amount of new online content has grown dramatically. To identify interesting items in the vast stream of new content, providers must rely on peer recommendation to aggregate opinions of their many users. Due to human cognitive biases, the presentation order strongly affects how people allocate attention to the available content. Moreover, we can manipulate attention through the presentation order of items to change the way peer recommendation works. We experimentally evaluate this effect using Amazon Mechanical Turk. We find that different policies for ordering content can steer user attention so as to improve the outcomes of peer recommendation.
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Semi-supervised learning and domain adaptation in natural language processing
Søgaard, Anders
2013-01-01
This book introduces basic supervised learning algorithms applicable to natural language processing (NLP) and shows how the performance of these algorithms can often be improved by exploiting the marginal distribution of large amounts of unlabeled data. One reason for that is data sparsity, i.e., the limited amounts of data we have available in NLP. However, in most real-world NLP applications our labeled data is also heavily biased. This book introduces extensions of supervised learning algorithms to cope with data sparsity and different kinds of sampling bias.This book is intended to be both
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Fabrication of a Cryogenic Bias Filter for Ultrasensitive Focal Plane
Chervenak, James; Wollack, Edward
2012-01-01
A fabrication process has been developed for cryogenic in-line filtering for the bias and readout of ultrasensitive cryogenic bolometers for millimeter and submillimeter wavelengths. The design is a microstripline filter that cuts out, or strongly attenuates, frequencies (10 50 GHz) that can be carried by wiring staged at cryogenic temperatures. The filter must have 100-percent transmission at DC and low frequencies where the bias and readout lines will carry signal. The fabrication requires the encapsulation of superconducting wiring in a dielectric-metal envelope with precise electrical characteristics. Sufficiently thick insulation layers with high-conductivity metal layers fully surrounding a patterned superconducting wire in arrayable formats have been demonstrated. A degenerately doped silicon wafer has been chosen to provide a metallic ground plane. A metallic seed layer is patterned to enable attachment to the ground plane. Thick silicon dioxide films are deposited at low temperatures to provide tunable dielectric isolation without degrading the metallic seed layer. Superconducting wiring is deposited and patterned using microstripline filtering techniques to cut out the relevant frequencies. A low Tc superconductor is used so that it will attenuate power strongly above the gap frequency. Thick dielectric is deposited on top of the circuit, and then vias are patterned through both dielectric layers. A thick conductive film is deposited conformally over the entire circuit, except for the contact pads for the signal and bias attachments to complete the encapsulating ground plane. Filters are high-aspect- ratio rectangles, allowing close packing in one direction, while enabling the chip to feed through the wall of a copper enclosure. The chip is secured in the copper wall using a soft metal seal to make good thermal and electrical contact to the outer shield.
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Good practices for quantitative bias analysis.
Lash, Timothy L; Fox, Matthew P; MacLehose, Richard F; Maldonado, George; McCandless, Lawrence C; Greenland, Sander
2014-12-01
Quantitative bias analysis serves several objectives in epidemiological research. First, it provides a quantitative estimate of the direction, magnitude and uncertainty arising from systematic errors. Second, the acts of identifying sources of systematic error, writing down models to quantify them, assigning values to the bias parameters and interpreting the results combat the human tendency towards overconfidence in research results, syntheses and critiques and the inferences that rest upon them. Finally, by suggesting aspects that dominate uncertainty in a particular research result or topic area, bias analysis can guide efficient allocation of sparse research resources. The fundamental methods of bias analyses have been known for decades, and there have been calls for more widespread use for nearly as long. There was a time when some believed that bias analyses were rarely undertaken because the methods were not widely known and because automated computing tools were not readily available to implement the methods. These shortcomings have been largely resolved. We must, therefore, contemplate other barriers to implementation. One possibility is that practitioners avoid the analyses because they lack confidence in the practice of bias analysis. The purpose of this paper is therefore to describe what we view as good practices for applying quantitative bias analysis to epidemiological data, directed towards those familiar with the methods. We focus on answering questions often posed to those of us who advocate incorporation of bias analysis methods into teaching and research. These include the following. When is bias analysis practical and productive? How does one select the biases that ought to be addressed? How does one select a method to model biases? How does one assign values to the parameters of a bias model? How does one present and interpret a bias analysis?. We hope that our guide to good practices for conducting and presenting bias analyses will encourage
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What Property of the Contour of a Deforming Region Biases Percepts toward Liquid?
Directory of Open Access Journals (Sweden)
Takahiro Kawabe
2017-06-01
Full Text Available Human observers can perceive the existence of a transparent surface from dynamic image deformation. They can also easily discriminate a transparent solid material such as plastic and glass from a transparent fluid one such as water and shampoo just by viewing them. However, the image information required for material discrimination of this sort is still unclear. A liquid changes its contour shape non-rigidly. We therefore examined whether additional properties of the contour of a deformation-defined region, which indicated contour non-rigidity, biased percepts of the region toward liquid materials. Our stimuli had a translating circular region wherein a natural texture image was deformed at the spatiotemporal deformation frequency that was optimal for the perception of a transparent layer. In Experiment 1, we dynamically deformed the contour of the circular region and found that large deformation of the contour biased the percept toward liquid. In Experiment 2, we manipulated the blurriness of the contour and observed that a strongly blurred contour biased percepts toward liquid. Taken together, the results suggest that a deforming region lacking a discrete contour biases percepts toward liquid.
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Low-bias flat band-stop filter based on velocity modulated gaussian graphene superlattice
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.
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Hindsight bias and outcome bias in the social construction of medical negligence: a review.
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.
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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
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Effect of biased feedback on motor imagery learning in BCI-teleoperation system
Directory of Open Access Journals (Sweden)
Maryam eAlimardani
2014-04-01
Full Text Available Feedback design is an important issue in motor imagery BCI systems. Regardless, to date it has not been reported how feedback presentation can optimize co-adaptation between a human brain and such systems. This paper assesses the effect of realistic visual feedback on users’ BC performance and motor imagery skills. We previously developed a tele-operation system for a pair of humanlike robotic hands and showed that BCI control of such hands along with first-person perspective visual feedback of movements can arouse a sense of embodiment in the operators. In the first stage of this study, we found that the intensity of this ownership illusion was associated with feedback presentation and subjects’ performance during BCI motion control. In the second stage, we probed the effect of positive and negative feedback bias on subjects’ BCI performance and motor imagery skills. Although the subject specific classifier, which was set up at the beginning of experiment, detected no significant change in the subjects’ online performance, evaluation of brain activity patterns revealed that subjects’ self-regulation of motor imagery features improved due to a positive bias of feedback and a possible occurrence of ownership illusion. Our findings suggest that in general training protocols for BCIs, manipulation of feedback can play an important role in the optimization of subjects’ motor imagery skills.
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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...
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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.
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Rouxinol, Francisco; Hao, Hugo; Lahaye, Matt
2015-03-01
Quantum electromechanical systems incorporating superconducting qubits have received extensive interest in recent years due to their promising prospects for studying fundamental topics of quantum mechanics such as quantum measurement, entanglement and decoherence in new macroscopic limits, also for their potential as elements in technological applications in quantum information network and weak force detector, to name a few. In this presentation we will discuss ours efforts toward to devise an electromechanical circuit to strongly couple a nanomechanical resonator to a superconductor qubit, where a high voltage dc-bias is required, to study quantum behavior of a mechanical resonator. Preliminary results of our latest generation of devices integrating a superconductor qubit into a high-Q voltage biased microwave cavities are presented. Developments in the circuit design to couple a mechanical resonator to a qubit in the high-Q voltage bias CPW cavity is discussed as well prospects of achieving single-phonon measurement resolution. National Science Foundation under Grant No. DMR-1056423 and Grant No. DMR-1312421.
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Vocalic and consonantal processing biases in early word-learning: Cross-language differences?
DEFF Research Database (Denmark)
Højen, Anders; Nazzi, Thierry
2010-01-01
Previous research showed that French-learning 16- or 20-month-olds could learn pairs of words that differed by a single consonantal but not vocalic feature. Danish has a richer vowel inventory than French, allowing for 31 phonological vowel contrasts, including vowel length and presence/absence o...
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Koch, Amanda J; D'Mello, Susan D; Sackett, Paul R
2015-01-01
Gender bias continues to be a concern in many work settings, leading researchers to identify factors that influence workplace decisions. In this study we examine several of these factors, using an organizing framework of sex distribution within jobs (including male- and female-dominated jobs as well as sex-balanced, or integrated, jobs). We conducted random effects meta-analyses including 136 independent effect sizes from experimental studies (N = 22,348) and examined the effects of decision-maker gender, amount and content of information available to the decision maker, type of evaluation, and motivation to make careful decisions on gender bias in organizational decisions. We also examined study characteristics such as type of participant, publication year, and study design. Our findings revealed that men were preferred for male-dominated jobs (i.e., gender-role congruity bias), whereas no strong preference for either gender was found for female-dominated or integrated jobs. Second, male raters exhibited greater gender-role congruity bias than did female raters for male-dominated jobs. Third, gender-role congruity bias did not consistently decrease when decision makers were provided with additional information about those they were rating, but gender-role congruity bias was reduced when information clearly indicated high competence of those being evaluated. Fourth, gender-role congruity bias did not differ between decisions that required comparisons among ratees and decisions made about individual ratees. Fifth, decision makers who were motivated to make careful decisions tended to exhibit less gender-role congruity bias for male-dominated jobs. Finally, for male-dominated jobs, experienced professionals showed smaller gender-role congruity bias than did undergraduates or working adults. (c) 2015 APA, all rights reserved.
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A new method to measure galaxy bias by combining the density and weak lensing fields
Energy Technology Data Exchange (ETDEWEB)
Pujol, Arnau; Chang, Chihway; Gaztañaga, Enrique; Amara, Adam; Refregier, Alexandre; Bacon, David J.; Carretero, Jorge; Castander, Francisco J.; Crocce, Martin; Fosalba, Pablo; Manera, Marc; Vikram, Vinu
2016-07-29
We present a new method to measure redshift-dependent galaxy bias by combining information from the galaxy density field and the weak lensing field. This method is based on the work of Amara et al., who use the galaxy density field to construct a bias-weighted convergence field κg. The main difference between Amara et al.'s work and our new implementation is that here we present another way to measure galaxy bias, using tomography instead of bias parametrizations. The correlation between κg and the true lensing field κ allows us to measure galaxy bias using different zero-lag correlations, such as <κgκ>/<κκ> or <κgκg>/<κgκ>. Our method measures the linear bias factor on linear scales, under the assumption of no stochasticity between galaxies and matter. We use the Marenostrum Institut de Ciències de l'Espai (MICE) simulation to measure the linear galaxy bias for a flux-limited sample (i < 22.5) in tomographic redshift bins using this method. This article is the first that studies the accuracy and systematic uncertainties associated with the implementation of the method and the regime in which it is consistent with the linear galaxy bias defined by projected two-point correlation functions (2PCF). We find that our method is consistent with a linear bias at the per cent level for scales larger than 30 arcmin, while non-linearities appear at smaller scales. This measurement is a good complement to other measurements of bias, since it does not depend strongly on σ8 as do the 2PCF measurements. We will apply this method to the Dark Energy Survey Science Verification data in a follow-up article.
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Self-Awareness and Cultural Identity as an Effort to Reduce Bias in Medicine.
White, Augustus A; Logghe, Heather J; Goodenough, Dan A; Barnes, Linda L; Hallward, Anne; Allen, Irving M; Green, David W; Krupat, Edward; Llerena-Quinn, Roxana
2018-02-01
In response to persistently documented health disparities based on race and other demographic factors, medical schools have implemented "cultural competency" coursework. While many of these courses have focused on strategies for treating patients of different cultural backgrounds, very few have addressed the impact of the physician's own cultural background and offered methods to overcome his or her own unconscious biases. In hopes of training physicians to contextualize the impact of their own cultural background on their ability to provide optimal patient care, the authors created a 14-session course on culture, self-reflection, and medicine. After completing the course, students reported an increased awareness of their blind spots and that providing equitable care and treatment would require lifelong reflection and attention to these biases. In this article, the authors describe the formation and implementation of a novel medical school course on self-awareness and cultural identity designed to reduce unconscious bias in medicine. Finally, we discuss our observations and lessons learned after more than 10 years of experience teaching the course.
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Bias and discriminability during emotional signal detection in melancholic depression.
Hyett, Matthew; Parker, Gordon; Breakspear, Michael
2014-04-27
Cognitive disturbances in depression are pernicious and so contribute strongly to the burden of the disorder. Cognitive function has been traditionally studied by challenging subjects with modality-specific psychometric tasks and analysing performance using standard analysis of variance. Whilst informative, such an approach may miss deeper perceptual and inferential mechanisms that potentially unify apparently divergent emotional and cognitive deficits. Here, we sought to elucidate basic psychophysical processes underlying the detection of emotionally salient signals across individuals with melancholic and non-melancholic depression. Sixty participants completed an Affective Go/No-Go (AGN) task across negative, positive and neutral target stimuli blocks. We employed hierarchical Bayesian signal detection theory (SDT) to model psychometric performance across three equal groups of those with melancholic depression, those with a non-melancholic depression and healthy controls. This approach estimated likely response profiles (bias) and perceptual sensitivity (discriminability). Differences in the means of these measures speak to differences in the emotional signal detection between individuals across the groups, while differences in the variance reflect the heterogeneity of the groups themselves. Melancholic participants showed significantly decreased sensitivity to positive emotional stimuli compared to those in the non-melancholic group, and also had a significantly lower discriminability than healthy controls during the detection of neutral signals. The melancholic group also showed significantly higher variability in bias to both positive and negative emotionally salient material. Disturbances of emotional signal detection in melancholic depression appear dependent on emotional context, being biased during the detection of positive stimuli, consistent with a noisier representation of neutral stimuli. The greater heterogeneity of the bias across the melancholic
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The psychological price of media bias.
Babad, Elisha
2005-12-01
Media bias was investigated through the effects of a TV interviewer's preferential behavior on the image of the interviewee in the eyes of the viewers. Judges viewed a political interview with either a friendly or a hostile interviewer then rated their impressions of the interviewed politician, whose behavior was identical in all conditions. The preferential nonverbal behavior of the interviewer (controlling for recognition and comprehension of verbal content) systematically influenced viewers' ratings of the politician. The effect consisted mainly of damage to the politician in the hostile interviewer condition. Describing the interviewee as a professor yielded a similar preferential behavior effect. A strong halo effect was identified, but it was ruled out as the mechanism accounting for the interviewer effect.
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Control of long range turbulent transport with biasing in the tokamak scrape-off-layer
International Nuclear Information System (INIS)
Figarella, C.F.; Ghendrih, Ph.; Sarazin, Y.; Attuel, G.; Benkadda, S.; Beyer, P.; Falchetto, G.; Fleurence, E.; Garbet, X.; Grandgirard, V.
2005-01-01
Cross-field transport in the SOL influences tokamak performance in particular regarding the divertor efficiency. Recent experiment evidence emphasizes non-exponential and/or flat SOL profiles that suggest a large perpendicular transport. A 2D fluid model based on the interchange instability to simulate the SOL turbulence was found to exhibits intermittent dynamics of the particle flux. We propose a control method that prevents long range transport events from reaching the far SOL: It consists in biasing the far SOL leading to a transport barrier which stops the propagation of these intermittent events. The best trade off is to localize the biased toroidal ring around the baffles. We show that such a control is achievable providing the strength of the barrier is strong enough. The investigation of the minimal biasing power required to achieve the control as well as its experimental estimate is performed
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Control of long range turbulent transport with biasing in the tokamak scrape-off-layer
International Nuclear Information System (INIS)
Figarella, C.F.; Ghendrih, Ph.; Sarazin, Y.; Attuel, G.; Falchetto, G.; Fleurence, E.; Garbet, X.; Grandgirard, V.
2004-01-01
Cross field transport in the SOL (scrape-off-layer) influences tokamak performance in particular regarding the divertor efficiency. Recent experiment evidence emphasizes non-exponential and/or flat SOL profiles that suggest a large perpendicular transport. A 2-dimensional fluid model based on the interchange instability to simulate the SOL turbulence was found to exhibits intermittent dynamics of the particle flux. We propose a control method that prevents long range transport events from reaching the far SOL: It consists in biasing the far SOL leading to a transport barrier which stops the propagation of these intermittent events. The best trade off is to localize the biased toroidal ring around the baffles. We show that such a control is achievable providing the strength of the barrier is strong enough. The investigation of the minimal biasing power required to achieve the control as well as its experimental estimate is performed. (authors)
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Applications of Machine Learning in Cancer Prediction and Prognosis
Directory of Open Access Journals (Sweden)
Joseph A. Cruz
2006-01-01
Full Text Available Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on “older” technologies such artificial neural networks (ANNs instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25% improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.
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Explicit goal-driven attention, unlike implicitly learned attention, spreads to secondary tasks.
Addleman, Douglas A; Tao, Jinyi; Remington, Roger W; Jiang, Yuhong V
2018-03-01
To what degree does spatial attention for one task spread to all stimuli in the attended region, regardless of task relevance? Most models imply that spatial attention acts through a unitary priority map in a task-general manner. We show that implicit learning, unlike endogenous spatial cuing, can bias spatial attention within one task without biasing attention to a spatially overlapping secondary task. Participants completed a visual search task superimposed on a background containing scenes, which they were told to encode for a later memory task. Experiments 1 and 2 used explicit instructions to bias spatial attention to one region for visual search; Experiment 3 used location probability cuing to implicitly bias spatial attention. In location probability cuing, a target appeared in one region more than others despite participants not being told of this. In all experiments, search performance was better in the cued region than in uncued regions. However, scene memory was better in the cued region only following endogenous guidance, not after implicit biasing of attention. These data support a dual-system view of top-down attention that dissociates goal-driven and implicitly learned attention. Goal-driven attention is task general, amplifying processing of a cued region across tasks, whereas implicit statistical learning is task-specific. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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Self-biased broadband magnet-free linear isolator based on one-way space-time coherency
Taravati, Sajjad
2017-12-01
This paper introduces a self-biased broadband magnet-free and linear isolator based on one-way space-time coherency. The incident wave and the space-time-modulated medium share the same temporal frequency and are hence temporally coherent. However, thanks to the unidirectionally of the space-time modulation, the space-time-modulated medium and the incident wave are spatially coherent only in the forward direction and not in the opposite direction. As a consequence, the energy of the medium strongly couples to the propagating wave in the forward direction, while it conflicts with the propagating wave in the opposite direction, yielding strong isolation. We first derive a closed-form solution for the wave scattering from a spatiotemporally coherent medium and then show that a perfectly coherent space-time-modulated medium provides a moderate isolation level which is also subject to one-way transmission gain. To overcome this issue, we next investigate the effect of space-coherency imperfection between the medium and the wave, while they are still perfectly temporally coherent. Leveraging the spatial-coherency imperfection, the medium exhibits a quasiarbitrary and strong nonreciprocal transmission. Finally, we present the experimental demonstration of the self-biased version of the proposed broadband isolator, exhibiting more than 122 % fractional operation bandwidth.
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Influence of prior information on pain involves biased perceptual decision-making.
Wiech, Katja; Vandekerckhove, Joachim; Zaman, Jonas; Tuerlinckx, Francis; Vlaeyen, Johan W S; Tracey, Irene
2014-08-04
Prior information about features of a stimulus is a strong modulator of perception. For instance, the prospect of more intense pain leads to an increased perception of pain, whereas the expectation of analgesia reduces pain, as shown in placebo analgesia and expectancy modulations during drug administration. This influence is commonly assumed to be rooted in altered sensory processing and expectancy-related modulations in the spinal cord, are often taken as evidence for this notion. Contemporary models of perception, however, suggest that prior information can also modulate perception by biasing perceptual decision-making - the inferential process underlying perception in which prior information is used to interpret sensory information. In this type of bias, the information is already present in the system before the stimulus is observed. Computational models can distinguish between changes in sensory processing and altered decision-making as they result in different response times for incorrect choices in a perceptual decision-making task (Figure S1A,B). Using a drift-diffusion model, we investigated the influence of both processes in two independent experiments. The results of both experiments strongly suggest that these changes in pain perception are predominantly based on altered perceptual decision-making. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
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Measurement of Minimum Bias Observables with ATLAS
Kvita, Jiri; The ATLAS collaboration
2017-01-01
The modelling of Minimum Bias (MB) is a crucial ingredient to learn about the description of soft QCD processes. It has also a significant relevance for the simulation of the environment at the LHC with many concurrent pp interactions (“pileup”). The ATLAS collaboration has provided new measurements of the inclusive charged particle multiplicity and its dependence on transverse momentum and pseudorapidity in special data sets with low LHC beam currents, recorded at center of mass energies of 8 TeV and 13 TeV. The measurements cover a wide spectrum using charged particle selections with minimum transverse momentum of both 100 MeV and 500 MeV and in various phase space regions of low and high charged particle multiplicities.
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Developing a strong safety culture - a safety management challenge
International Nuclear Information System (INIS)
Low, M.; Gipson, G. P.; Williams, M.
1995-01-01
The approach is presented adapted by Nuclear Electric to build a strong safety culture through the development of its safety management system. Two features regarded as critical to a strong safety culture are: provision of effective communications to promote an awareness and ownership of safety among craft, and commitment to continuous improvement with a genuine willingness to learn from own experiences and those from others. (N.T.) 5 refs., 4 figs., 1 tab
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Non-iterative relative bias correction for 3D reconstruction of in utero fetal brain MR imaging.
Kim, Kio; Habas, Piotr; Rajagopalan, Vidya; Scott, Julia; Corbett-Detig, James; Rousseau, Francois; Glenn, Orit; Barkovich, James; Studholme, Colin
2010-01-01
The slice intersection motion correction (SIMC) method is a powerful tool to compensate for motion that occurs during in utero acquisition of the multislice magnetic resonance (MR) images of the human fetal brain. The SIMC method makes use of the slice intersection intensity profiles of orthogonally planned slice pairs to simultaneously correct for the relative motion occurring between all the acquired slices. This approach is based on the assumption that the bias field is consistent between slices. However, for some clinical studies where there is a strong bias field combined with significant fetal motion relative to the coils, this assumption is broken and the resulting motion estimate and the reconstruction to a 3D volume can both contain errors. In this work, we propose a method to correct for the relative differences in bias field between all slice pairs. For this, we define the energy function as the mean square difference of the intersection profiles, that is then minimized with respect to the bias field parameters of the slices. A non iterative method which considers the relative bias between each slice simultaneously is used to efficiently remove inconsistencies. The method, when tested on synthetic simulations and actual clinical imaging studies where bias was an issue, brought a significant improvement to the final reconstructed image.
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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.
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Fithian, William; Elith, Jane; Hastie, Trevor; Keith, David A
2015-04-01
Presence-only records may provide data on the distributions of rare species, but commonly suffer from large, unknown biases due to their typically haphazard collection schemes. Presence-absence or count data collected in systematic, planned surveys are more reliable but typically less abundant.We proposed a probabilistic model to allow for joint analysis of presence-only and survey data to exploit their complementary strengths. Our method pools presence-only and presence-absence data for many species and maximizes a joint likelihood, simultaneously estimating and adjusting for the sampling bias affecting the presence-only data. By assuming that the sampling bias is the same for all species, we can borrow strength across species to efficiently estimate the bias and improve our inference from presence-only data.We evaluate our model's performance on data for 36 eucalypt species in south-eastern Australia. We find that presence-only records exhibit a strong sampling bias towards the coast and towards Sydney, the largest city. Our data-pooling technique substantially improves the out-of-sample predictive performance of our model when the amount of available presence-absence data for a given species is scarceIf we have only presence-only data and no presence-absence data for a given species, but both types of data for several other species that suffer from the same spatial sampling bias, then our method can obtain an unbiased estimate of the first species' geographic range.
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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.
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Social Incentives Improve Deliberative But Not Procedural Learning in Older Adults
Directory of Open Access Journals (Sweden)
Marissa A Gorlick
2015-04-01
Full Text Available Age-related deficits are seen across tasks where learning depends on asocial feedback processing, however plasticity has been observed in some of the same tasks in social contexts suggesting a novel way to attenuate deficits. Socioemotional selectivity theory suggests this plasticity is due to a deliberative motivational shift toward achieving well-being with age (positivity effect that reverses when executive processes are limited (negativity effect. The present study examined the interaction of feedback valence (positive, negative and social salience (emotional face feedback – happy; angry, asocial point feedback – gain; loss on learning in a deliberative task that challenges executive processes and a procedural task that does not. We predict that angry face feedback will improve learning in a deliberative task when executive function is challenged. We tested two competing hypotheses regarding the interactive effects of deliberative emotional biases on automatic feedback processing: 1 If deliberative emotion regulation and automatic feedback are interactive we expect happy face feedback to improve learning and angry face feedback to impair learning in older adults because cognitive control is available. 2 If deliberative emotion regulation and automatic feedback are not interactive we predict that emotional face feedback will not improve procedural learning regardless of valence. Results demonstrate that older adults show persistent deficits relative to younger adults during procedural category learning suggesting that deliberative emotional biases do not interact with automatic feedback processing. Interestingly, a subgroup of older adults identified as potentially using deliberative strategies tended to learn as well as younger adults with angry relative to happy feedback, matching the pattern observed in the deliberative task. Results suggest that deliberative emotional biases can improve deliberative learning, but have no effect on
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Reward Learning, Neurocognition, Social Cognition, and Symptomatology in Psychosis.
Lewandowski, Kathryn E; Whitton, Alexis E; Pizzagalli, Diego A; Norris, Lesley A; Ongur, Dost; Hall, Mei-Hua
2016-01-01
Patients with psychosis spectrum disorders exhibit deficits in social and neurocognition, as well as hallmark abnormalities in motivation and reward processing. Aspects of reward processing may overlap behaviorally and neurobiologically with some elements of cognitive functioning, and abnormalities in these processes may share partially overlapping etiologies in patients. However, whether reward processing and cognition are associated across the psychoses and linked to state and trait clinical symptomatology is unclear. The present study examined associations between cognitive functioning, reward learning, and clinical symptomatology in a cross-diagnostic sample. Patients with schizophrenia (SZ; n = 37), bipolar I disorder with psychosis (BD; n = 42), and healthy controls (n = 29) were assessed for clinical symptoms (patients only), neurocognitive functioning using the MATRICS Battery (MCCB) and reward learning using the probabilistic reward task (PRT). Groups were compared on neurocognition and PRT response bias, and associations between PRT response bias and neurocognition or clinical symptoms were examined controlling for demographic variables and PRT task difficulty (discriminability). Patients with SZ performed worse than controls on most measures of neurocognition; patients with BD exhibited deficits in some domains between the level of patients with SZ and controls. The SZ - but not BD - group exhibited deficits in social cognition compared to controls. Patients and controls did not differ on PRT response bias, but did differ on PRT discriminability. Better response bias across the sample was associated with poorer social cognition, but not neurocognition; conversely, discriminability was associated with neurocognition but not social cognition. Symptoms of psychosis, particularly negative symptoms, were associated with poorer response bias across patient groups. Reward learning was associated with symptoms of psychosis - in particular negative
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Income growth and gender bias in childhood mortality in developing countries:
Ueyama, Mika
2007-01-01
"With poverty studies having shifted their focus from household poverty to individual poverty, a number of studies have started to examine intrahousehold resource allocation, especially gender bias within the household as potential causes of poverty. The literature has highlighted the existence of gender inequalities in South Asia, attributed to strong preferences for male offspring stemming from cultural and traditional customs. Only a few studies focused on the regional difference in the ex...
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Adams, Daniel J.; Khanal, Shankar; Khan, Mohammad Asif; Maksymov, Artur; Spinu, Leonard
2018-05-01
The in-plane temperature dependence of exchange bias was studied through both dc magnetometry and ferromagnetic resonance spectroscopy in a series of [NiFe/IrMn]n multilayer films, where n is the number of layer repetitions. Major hysteresis loops were recorded in the temperature range of 300 K to 2 K to reveal the effect of temperature on the exchange bias in the static regime while temperature-dependent continuous-wave ferromagnetic resonance for frequencies from 3 to 16 GHz was used to determine the exchange bias dynamically. Strong divergence between the values of exchange bias determined using the two different types of measurements as well as a peak in temperature dependence of the resonance linewidth were observed. These results are explained in terms of the slow-relaxer mechanism.
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Directory of Open Access Journals (Sweden)
Marie Devaine
2017-03-01
Full Text Available Peoples' subjective attitude towards costs such as, e.g., risk, delay or effort are key determinants of inter-individual differences in goal-directed behaviour. Thus, the ability to learn about others' prudent, impatient or lazy attitudes is likely to be critical for social interactions. Conversely, how adaptive such attitudes are in a given environment is highly uncertain. Thus, the brain may be tuned to garner information about how such costs ought to be arbitrated. In particular, observing others' attitude may change one's uncertain belief about how to best behave in related difficult decision contexts. In turn, learning from others' attitudes is determined by one's ability to learn about others' attitudes. We first derive, from basic optimality principles, the computational properties of such a learning mechanism. In particular, we predict two apparent cognitive biases that would arise when individuals are learning about others' attitudes: (i people should overestimate the degree to which they resemble others (false-consensus bias, and (ii they should align their own attitudes with others' (social influence bias. We show how these two biases non-trivially interact with each other. We then validate these predictions experimentally by profiling people's attitudes both before and after guessing a series of cost-benefit arbitrages performed by calibrated artificial agents (which are impersonating human individuals.
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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...
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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.
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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
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Pharmacogenomics Bias - Systematic distortion of study results by genetic heterogeneity
Directory of Open Access Journals (Sweden)
Zietemann, Vera
2008-04-01
trial. Results: We found four studies that systematically evaluated heterogeneity bias. All of them indicated that there is a potential of heterogeneity bias. However, none of these studies explicitly investigated the effect of genetic heterogeneity. Therefore, we performed our own simulation study. Our generic simulation showed that a purely HT-related bias is negative (conservative and a purely HP-related bias is positive (liberal. For many typical scenarios, the absolute bias is smaller than 10%. In case of joint HP and HT, the overall bias is likely triggered by the HP component and reaches positive values >100% if fractions of „fast progressors" and „strong treatment responders" are low. In the clinical example with pravastatin therapy, the unadjusted model overestimated the true life-years gained (LYG by 5.5% (1.07 LYG vs. 0.99 LYG for 56-year-old men. Conclusions: We have been able to predict the pharmacogenomics bias jointly caused by heterogeneity in progression of disease and heterogeneity in treatment response as a function of characteristics of patients, chronic disease, and treatment. In the case of joint presence of both types of heterogeneity, models ignoring this heterogeneity may generate results that overestimate the treatment benefit.
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Energy Technology Data Exchange (ETDEWEB)
Zhang, G.P., E-mail: princeterry@163.com [Institute of Physics, Chinese Academy of Science, Beijing 100080 (China); Gao, G.J. [Changchun University of Science and Technology, College of Science, Changchun 130000 (China); Wang, X.Q.; Lv, G.H.; Zhou, L.; Chen, H.; Pang, H.; Yang, S.Z. [Institute of Physics, Chinese Academy of Science, Beijing 100080 (China)
2012-07-15
Ti-Al-N films were deposited by cathodic vacuum arc (CVA) technique in N{sub 2} atmosphere with different pulsed substrate bias. The influence of pulsed substrate bias (0 to -800 V) on the deposition rate, surface morphology, crystal structure, and mechanical properties of the Ti-Al-N films were systematically investigated. Increasing pulsed bias voltage resulted in the decrease of deposition rate but the increase of surface roughness. It was found that there was a strong correlation between the pulsed bias and film structure. All the films studied in this paper were composed of TiN, AlN, and Ti-Al-N ternary phases. The grains changed from equiaxial to columnar and exhibited preferred orientation when the pulsed bias increased. With the increase of pulsed bias voltage, the atomic ratio of Ti to Al element increased gradually, while the N to (Ti + Al) ratio decreased. The composite films present an enhanced nanohardness compared with binary TiN and ZrN films. The film deposited with pulsed bias of -200 V possessed the maximum scratch critical load and nanohardness. The minimum friction coefficient with pulsed bias of -300 V was obtained.
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Christopoulos, George I; King-Casas, Brooks
2015-01-01
In social environments, it is crucial that decision-makers take account of the impact of their actions not only for oneself, but also on other social agents. Previous work has identified neural signals in the striatum encoding value-based prediction errors for outcomes to oneself; also, recent work suggests that neural activity in prefrontal cortex may similarly encode value-based prediction errors related to outcomes to others. However, prior work also indicates that social valuations are not isomorphic, with social value orientations of decision-makers ranging on a cooperative to competitive continuum; this variation has not been examined within social learning environments. Here, we combine a computational model of learning with functional neuroimaging to examine how individual differences in orientation impact neural mechanisms underlying 'other-value' learning. Across four experimental conditions, reinforcement learning signals for other-value were identified in medial prefrontal cortex, and were distinct from self-value learning signals identified in striatum. Critically, the magnitude and direction of the other-value learning signal depended strongly on an individual's cooperative or competitive orientation toward others. These data indicate that social decisions are guided by a social orientation-dependent learning system that is computationally similar but anatomically distinct from self-value learning. The sensitivity of the medial prefrontal learning signal to social preferences suggests a mechanism linking such preferences to biases in social actions and highlights the importance of incorporating heterogeneous social predispositions in neurocomputational models of social behavior. Published by Elsevier Inc.
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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,.
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Biases in GNSS-Data Processing
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.
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Not so primitive: context-sensitive meta-learning about unattended sound sequences.
Todd, Juanita; Provost, Alexander; Whitson, Lisa R; Cooper, Gavin; Heathcote, Andrew
2013-01-01
Mismatch negativity (MMN), an evoked response potential elicited when a "deviant" sound violates a regularity in the auditory environment, is integral to auditory scene processing and has been used to demonstrate "primitive intelligence" in auditory short-term memory. Using a new multiple-context and -timescale protocol we show that MMN magnitude displays a context-sensitive modulation depending on changes in the probability of a deviant at multiple temporal scales. We demonstrate a primacy bias causing asymmetric evidence-based modulation of predictions about the environment, and we demonstrate that learning how to learn about deviant probability (meta-learning) induces context-sensitive variation in the accessibility of predictive long-term memory representations that underpin the MMN. The existence of the bias and meta-learning are consistent with automatic attributions of behavioral salience governing relevance-filtering processes operating outside of awareness.
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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....
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Large scale structure from biased non-equilibrium phase transitions percolation theory picture
Lalak, Z; Ovrut, B A; Ross, Graham G
1995-01-01
We give an analytical description of the spatial distribution of domain walls produced during a biased nonequilibrium phase transition in the vacuum state of a light scalar field. We discuss in detail the spectrum of the associated cosmological energy density perturbations. It is shown that the contribution coming from domain walls can enhance the standard cold dark matter spectrum in such a way as to account for the whole range of IRAS data and for the COBE measurement of the microwave background anisotropy. We also demonstrate that in case of a biased phase transition which allows a percolative description, the number of large size domain walls is strongly suppressed. This offers a way of avoiding excessive microwave background distorsions due to the gravitational field of domain walls present after decoupling.
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Unclaimed Prize Information Biases Perceptions of Winning in Scratch Card Gambling.
Walker, Alexander C; Stange, Madison; Fugelsang, Jonathan A; Koehler, Derek J; Dixon, Mike J
2018-03-29
Unclaimed prize information (i.e., the number of prizes still available to be won) is information commonly provided to scratch card gamblers. However, unless the number of tickets remaining to be purchased is also provided, this information is uninformative. Despite its lack of utility in assisting gamblers in choosing the most favourable type of scratch card to play, we hypothesized that unclaimed prize information would bias participants' judgments within a scratch card gambling context. In Experiment 1 (N = 201), we showed that participants are influenced by this information such that they felt more likely to win, were more excited to play, and preferred to hypothetically purchase more of the scratch card with the greatest number of unclaimed prizes. In Experiment 2 (N = 201), we attempted to ameliorate this bias by providing participants with the number of tickets remaining to be purchased and equating the payback percentages of all three games. The bias, although attenuated, still persisted in these conditions. Finally, in Experiment 3 (N = 200), we manipulated the hypothetical scratch cards such that games with the highest number of unclaimed prizes were the least favourable, and vice versa. As in Experiment 2, participants still favoured cards with greater numbers of unclaimed prizes. Possible mechanisms underlying this bias are discussed. In conclusion, across three experiments, we demonstrate that salient unclaimed prize information is capable of exerting a strong effect over judgments related to scratch card games.
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Tuning antiferromagnetic exchange interaction for spontaneous exchange bias in MnNiSnSi system
Jia, Liyun; Shen, Jianlei; Li, Mengmeng; Wang, Xi; Ma, Li; Zhen, Congmian; Hou, Denglu; Liu, Enke; Wang, Wenhong; Wu, Guangheng
2017-12-01
Based on almost all the data from the literature on spontaneous exchange bias (SEB), it is expected that the system will show SEB if it meets two conditions simultaneously: (i) there are the coexistence and competition of antiferromagnetic (AFM) and ferromagnetic (FM) interactions and (ii) AFM interaction should dominate but not be too strong in this competition. In order to verify this view, a systematic study on SEB has been performed in this work. Mn50Ni40Sn10 with strong FM interaction and without SEB is chosen as the mother composition, and the negative chemical pressure is introduced by the substitution of Sn by Si to enhance AFM interaction. It is found that a long-range FM ordering window is closed, and a long-range AFM ordering window is opened. As a result, SEB is triggered and a continuous tuning of the spontaneous exchange bias field (HSEB) from 0 Oe to 1300 Oe has been realized in a Mn50Ni40Sn10-xSix system by the enhanced AFM interaction.
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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...
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Zhou, Wenyu; Xie, Shang-Ping
2017-08-01
Global climate models (GCMs) have long suffered from biases of excessive tropical precipitation in the Southern Hemisphere (SH). The severity of the double-Intertropical Convergence Zone (ITCZ) bias, defined here as the interhemispheric difference in zonal mean tropical precipitation, varies strongly among models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble. Models with a more severe double-ITCZ bias feature warmer tropical sea surface temperature (SST) in the SH, coupled with weaker southeast trades. While previous studies focus on coupled ocean-atmosphere interactions, here we show that the intermodel spread in the severity of the double-ITCZ bias is closely related to land surface temperature biases, which can be further traced back to those in the Atmosphere Model Intercomparison Project (AMIP) simulations. By perturbing land temperature in models, we demonstrate that cooler land can indeed lead to a more severe double-ITCZ bias by inducing the above coupled SST-trade wind pattern in the tropics. The response to land temperature can be consistently explained from both the dynamic and energetic perspectives. Although this intermodel spread from the land temperature variation does not account for the ensemble model mean double-ITCZ bias, identifying the land temperature effect provides insights into simulating a realistic ITCZ for the right reasons.
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Forgetting feelings: Opposite biases in reports of the intensity of past emotion and mood.
Kaplan, Robin L; Levine, Linda J; Lench, Heather C; Safer, Martin A
2016-04-01
Memory for feelings is subject to fading and bias over time. In 2 studies, the authors examined whether the magnitude and direction of bias depend on the type of feeling being recalled: emotion or mood. A few days after the U.S. Presidential elections in 2008 and 2012, participants reported how they felt about the election outcome (emotion) and how they felt in general (mood). A month after the elections, participants recalled their feelings. The intensity of past emotion was recalled more accurately than the intensity of past mood. Participants underestimated the intensity of emotion but overestimated the intensity of mood. Participants' appraisals of the importance of the election, which diminished over time, contributed to underestimating the intensity of emotion. In contrast, participants' strong emotional response to the election contributed to overestimating the intensity of mood. These opposing biases have important implications for decision making and clinical assessment. (c) 2016 APA, all rights reserved).
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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.
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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.
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Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies
Theis, Fabian J.
2017-01-01
Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package sambia. PMID:29312464
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Genome-wide analysis of codon usage bias in Ebolavirus.
Cristina, Juan; Moreno, Pilar; Moratorio, Gonzalo; Musto, Héctor
2015-01-22
Ebola virus (EBOV) is a member of the family Filoviridae and its genome consists of a 19-kb, single-stranded, negative sense RNA. EBOV is subdivided into five distinct species with different pathogenicities, being Zaire ebolavirus (ZEBOV) the most lethal species. The interplay of codon usage among viruses and their hosts is expected to affect overall viral survival, fitness, evasion from host's immune system and evolution. In the present study, we performed comprehensive analyses of codon usage and composition of ZEBOV. Effective number of codons (ENC) indicates that the overall codon usage among ZEBOV strains is slightly biased. Different codon preferences in ZEBOV genes in relation to codon usage of human genes were found. Highly preferred codons are all A-ending triplets, which strongly suggests that mutational bias is a main force shaping codon usage in ZEBOV. Dinucleotide composition also plays a role in the overall pattern of ZEBOV codon usage. ZEBOV does not seem to use the most abundant tRNAs present in the human cells for most of their preferred codons. Copyright © 2014 Elsevier B.V. All rights reserved.
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Preferences, country bias, and international trade
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.
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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.
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Exchange bias and bistable magneto-resistance states in amorphous TbFeCo thin films
Energy Technology Data Exchange (ETDEWEB)
Li, Xiaopu, E-mail: xl6ba@virginia.edu; Ma, Chung T.; Poon, S. Joseph, E-mail: sjp9x@virginia.edu [Department of Physics, University of Virginia, Charlottesville, Virginia 22904 (United States); Lu, Jiwei [Department of Materials Science and Engineering, University of Virginia, Charlottesville, Virginia 22904 (United States); Devaraj, Arun [Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352 (United States); Spurgeon, Steven R.; Comes, Ryan B. [Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352 (United States)
2016-01-04
Amorphous TbFeCo thin films sputter deposited at room temperature on thermally oxidized Si substrate are found to exhibit strong perpendicular magnetic anisotropy. Atom probe tomography, scanning transmission electron microscopy, and energy dispersive X-ray spectroscopy mapping have revealed two nanoscale amorphous phases with different Tb atomic percentages distributed within the amorphous film. Exchange bias accompanied by bistable magneto-resistance states has been uncovered near room temperature by magnetization and magneto-transport measurements. The exchange anisotropy originates from the exchange interaction between the ferrimagnetic and ferromagnetic components corresponding to the two amorphous phases. This study provides a platform for exchange bias and magneto-resistance switching using single-layer amorphous ferrimagnetic thin films that require no epitaxial growth.
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Query-Biased Preview over Outsourced and Encrypted Data
Luo, Guangchun; Qin, Ke; Chen, Aiguo
2013-01-01
For both convenience and security, more and more users encrypt their sensitive data before outsourcing it to a third party such as cloud storage service. However, searching for the desired documents becomes problematic since it is costly to download and decrypt each possibly needed document to check if it contains the desired content. An informative query-biased preview feature, as applied in modern search engine, could help the users to learn about the content without downloading the entire document. However, when the data are encrypted, securely extracting a keyword-in-context snippet from the data as a preview becomes a challenge. Based on private information retrieval protocol and the core concept of searchable encryption, we propose a single-server and two-round solution to securely obtain a query-biased snippet over the encrypted data from the server. We achieve this novel result by making a document (plaintext) previewable under any cryptosystem and constructing a secure index to support dynamic computation for a best matched snippet when queried by some keywords. For each document, the scheme has O(d) storage complexity and O(log(d/s) + s + d/s) communication complexity, where d is the document size and s is the snippet length. PMID:24078798
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Query-biased preview over outsourced and encrypted data.
Peng, Ningduo; Luo, Guangchun; Qin, Ke; Chen, Aiguo
2013-01-01
For both convenience and security, more and more users encrypt their sensitive data before outsourcing it to a third party such as cloud storage service. However, searching for the desired documents becomes problematic since it is costly to download and decrypt each possibly needed document to check if it contains the desired content. An informative query-biased preview feature, as applied in modern search engine, could help the users to learn about the content without downloading the entire document. However, when the data are encrypted, securely extracting a keyword-in-context snippet from the data as a preview becomes a challenge. Based on private information retrieval protocol and the core concept of searchable encryption, we propose a single-server and two-round solution to securely obtain a query-biased snippet over the encrypted data from the server. We achieve this novel result by making a document (plaintext) previewable under any cryptosystem and constructing a secure index to support dynamic computation for a best matched snippet when queried by some keywords. For each document, the scheme has O(d) storage complexity and O(log(d/s) + s + d/s) communication complexity, where d is the document size and s is the snippet length.
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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.
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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...
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Nasie, Meytal; Bar-Tal, Daniel; Pliskin, Ruthie; Nahhas, Eman; Halperin, Eran
2014-11-01
One significant socio-psychological barrier for peaceful resolution of conflicts is each party's adherence to its own collective narrative. We hypothesized that raising awareness to the psychological bias of naïve realism and its identification in oneself would provide a path to overcoming this barrier, thus increasing openness to the adversary's narrative. We conducted three experimental studies in the context of the Israeli-Palestinian conflict. Studies 1 and 2, conducted among Jewish Israelis and Palestinian Israelis, respectively, revealed that participants with hawkish political ideology reported greater openness to the adversary's narrative when they were made aware of naïve realism bias. Study 3 revealed that hawkish participants at the baseline adhered to the ingroup narrative and resisted the adversary's narrative more than dovish participants. They were also more able to identify the bias in themselves upon learning about it. This identification may explain why the manipulation led to bias correction only among hawkish participants. © 2014 by the Society for Personality and Social Psychology, Inc.
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Sani, Susan Raouf Hadadi; Tabibi, Zahra; Fadardi, Javad Salehi; Stavrinos, Despina
2017-12-01
The present study explored whether aggression, emotional regulation, cognitive inhibition, and attentional bias towards emotional stimuli were related to risky driving behavior (driving errors, and driving violations). A total of 117 applicants for taxi driver positions (89% male, M age=36.59years, SD=9.39, age range 24-62years) participated in the study. Measures included the Ahwaz Aggression Inventory, the Difficulties in emotion regulation Questionnaire, the emotional Stroop task, the Go/No-go task, and the Driving Behavior Questionnaire. Correlation and regression analyses showed that aggression and emotional regulation predicted risky driving behavior. Difficulties in emotion regulation, the obstinacy and revengeful component of aggression, attentional bias toward emotional stimuli, and cognitive inhibition predicted driving errors. Aggression was the only significant predictive factor for driving violations. In conclusion, aggression and difficulties in regulating emotions may exacerbate risky driving behaviors. Deficits in cognitive inhibition and attentional bias toward negative emotional stimuli can increase driving errors. Predisposition to aggression has strong effect on making one vulnerable to violation of traffic rules and crashes. Copyright © 2017 Elsevier Ltd. All rights reserved.
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International Nuclear Information System (INIS)
Kim, Yonghee; Heo, Myoung-Sun; Moon, Geol; Kim, Ji-Hyoun; Jhe, Wonho; Noh, Heung-Ryoul
2010-01-01
We experimentally demonstrate resonant symmetry lifting in a parametrically modulated magneto-optical trap of cold 85 Rb atoms. This is achieved by applying a weak additional modulation at half the frequency of the strong parametric modulation, which acts as an effective static bias field to the system. We measure the system response by varying the amplitude of the additional fictitious bias as well as the relative phase between the bias and the parametric drive, and the results are in good agreement with theory. The additional modulation provides an additional degree of freedom to control the system, which is useful for investigating system properties such as susceptibility, dynamic response, and related critical phenomena. We also have measured the amplitude of the response to higher harmonics of the additional modulation frequency, which allows more precise understanding of the system dynamics.
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Directory of Open Access Journals (Sweden)
Jens Jirschitzka
Full Text Available In four studies we tested a new methodological approach to the investigation of evaluation bias. The usage of piecewise growth curve modeling allowed for investigation into the impact of people's attitudes on their persuasiveness ratings of pro- and con-arguments, measured over the whole range of the arguments' polarity from an extreme con to an extreme pro position. Moreover, this method provided the opportunity to test specific hypotheses about the course of the evaluation bias within certain polarity ranges. We conducted two field studies with users of an existing online information portal (Studies 1a and 2a as participants, and two Internet laboratory studies with mostly student participants (Studies 1b and 2b. In each of these studies we presented pro- and con-arguments, either for the topic of MOOCs (massive open online courses, Studies 1a and 1b or for the topic of M-learning (mobile learning, Studies 2a and 2b. Our results indicate that using piecewise growth curve models is more appropriate than simpler approaches. An important finding of our studies was an asymmetry of the evaluation bias toward pro- or con-arguments: the evaluation bias appeared over the whole polarity range of pro-arguments and increased with more and more extreme polarity. This clear-cut result pattern appeared only on the pro-argument side. For the con-arguments, in contrast, the evaluation bias did not feature such a systematic picture.
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Bias-field equalizer for bubble memories
Keefe, G. E.
1977-01-01
Magnetoresistive Perm-alloy sensor monitors bias field required to maintain bubble memory. Sensor provides error signal that, in turn, corrects magnitude of bias field. Error signal from sensor can be used to control magnitude of bias field in either auxiliary set of bias-field coils around permanent magnet field, or current in small coils used to remagnetize permanent magnet by infrequent, short, high-current pulse or short sequence of pulses.
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Borelli, Jessica L.; David, Daryn H.; Crowley, Michael J.; Snavely, Jonathan E.; Mayes, Linda C.
2013-01-01
The tendency to perceive caregivers in highly positive terms and to perceive the self as strong and problem-free are two facets of the positive bias characteristic of a dismissing attachment classification in adulthood. However, this link has not yet been examined in children. We evaluated the association between dismissing attachment and positive…
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Political attitudes bias the mental representation of a presidential candidate's face.
Young, Alison I; Ratner, Kyle G; Fazio, Russell H
2014-02-01
Using a technique known as reverse-correlation image classification, we demonstrated that the face of Mitt Romney as represented in people's minds varies as a function of their attitudes toward Mitt Romney. Our findings provide evidence that attitudes bias how people see something as concrete and well learned as the face of a political candidate during an election. Practically, our findings imply that citizens may not merely interpret political information about a candidate to fit their opinion, but also may construct a political world in which they literally see candidates differently.
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Katz, Anna; Carnes, Molly; Gutierrez, Belinda; Savoy, Julia; Samuel, Clem; Filut, Amarette; Pribbenow, Christine Maidl
2017-01-01
Explicit racial bias has decreased in the United States, but racial stereotypes still exist and conspire in multiple ways to perpetuate the underparticipation of Blacks in science careers. Capitalizing on the potential effectiveness of role-playing video games to promote the type of active learning required to increase awareness of and reduce…
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Introduction to Unconscious Bias
Schmelz, Joan T.
2010-05-01
We all have biases, and we are (for the most part) unaware of them. In general, men and women BOTH unconsciously devalue the contributions of women. This can have a detrimental effect on grant proposals, job applications, and performance reviews. Sociology is way ahead of astronomy in these studies. When evaluating identical application packages, male and female University psychology professors preferred 2:1 to hire "Brian” over "Karen” as an assistant professor. When evaluating a more experienced record (at the point of promotion to tenure), reservations were expressed four times more often when the name was female. This unconscious bias has a repeated negative effect on Karen's career. This talk will introduce the concept of unconscious bias and also give recommendations on how to address it using an example for a faculty search committee. The process of eliminating unconscious bias begins with awareness, then moves to policy and practice, and ends with accountability.
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Research bias in judgement bias studies : a systematic review of valuation judgement literature
Vincent Gruis; Pim Klamer; Cok Bakker
2017-01-01
Valuation judgement bias has been a research topic for several years due to its proclaimed effect on valuation accuracy. However, little is known on the emphasis of literature on judgement bias, with regard to, for instance, research methodologies, research context and robustness of research
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Research bias in judgement bias studies : A systematic review of valuation judgement literature
Klamer, Pim; Bakker, C.; Gruis, Vincent
2017-01-01
Valuation judgement bias has been a research topic for several years due to its proclaimed effect on valuation accuracy. However, little is known on the emphasis of literature on judgement bias, with regard to, for instance, research methodologies, research context and robustness of research
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Gates, Allison; Vandermeer, Ben; Hartling, Lisa
2018-04-01
To evaluate the reliability of RobotReviewer's risk of bias judgments. In this prospective cross-sectional evaluation, we used RobotReviewer to assess risk of bias among 1,180 trials. We computed reliability with human reviewers using Cohen's kappa coefficient and calculated sensitivity and specificity. We investigated differences in reliability by risk of bias domain, topic, and outcome type using the chi-square test in meta-analysis. Reliability (95% CI) was moderate for random sequence generation (0.48 [0.43, 0.53]), allocation concealment (0.45 [0.40, 0.51]), and blinding of participants and personnel (0.42 [0.36, 0.47]); fair for overall risk of bias (0.34 [0.25, 0.44]); and slight for blinding of outcome assessors (0.10 [0.06, 0.14]), incomplete outcome data (0.14 [0.08, 0.19]), and selective reporting (0.02 [-0.02, 0.05]). Reliability for blinding of participants and personnel (P < 0.001), blinding of outcome assessors (P = 0.005), selective reporting (P < 0.001), and overall risk of bias (P < 0.001) differed by topic. Sensitivity and specificity (95% CI) ranged from 0.20 (0.18, 0.23) to 0.76 (0.72, 0.80) and from 0.61 (0.56, 0.65) to 0.95 (0.93, 0.96), respectively. Risk of bias appraisal is subjective. Compared with reliability between author groups, RobotReviewer's reliability with human reviewers was similar for most domains and better for allocation concealment, blinding of participants and personnel, and overall risk of bias. Copyright © 2018 Elsevier Inc. All rights reserved.
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Toews, Ingrid; Glenton, Claire; Lewin, Simon; Berg, Rigmor C.; Noyes, Jane; Booth, Andrew; Marusic, Ana; Malicki, Mario; Munthe-Kaas, Heather M.; Meerpohl, Joerg J.
2016-01-01
Background Qualitative research findings are increasingly used to inform decision-making. Research has indicated that not all quantitative research on the effects of interventions is disseminated or published. The extent to which qualitative researchers also systematically underreport or fail to publish certain types of research findings, and the impact this may have, has received little attention. Methods A survey was delivered online to gather data regarding non-dissemination and dissemination bias in qualitative research. We invited relevant stakeholders through our professional networks, authors of qualitative research identified through a systematic literature search, and further via snowball sampling. Results 1032 people took part in the survey of whom 859 participants identified as researchers, 133 as editors and 682 as peer reviewers. 68.1% of the researchers said that they had conducted at least one qualitative study that they had not published in a peer-reviewed journal. The main reasons for non-dissemination were that a publication was still intended (35.7%), resource constraints (35.4%), and that the authors gave up after the paper was rejected by one or more journals (32.5%). A majority of the editors and peer reviewers “(strongly) agreed” that the main reasons for rejecting a manuscript of a qualitative study were inadequate study quality (59.5%; 68.5%) and inadequate reporting quality (59.1%; 57.5%). Of 800 respondents, 83.1% “(strongly) agreed” that non-dissemination and possible resulting dissemination bias might undermine the willingness of funders to support qualitative research. 72.6% and 71.2%, respectively, “(strongly) agreed” that non-dissemination might lead to inappropriate health policy and health care. Conclusions The proportion of non-dissemination in qualitative research is substantial. Researchers, editors and peer reviewers play an important role in this. Non-dissemination and resulting dissemination bias may impact on
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Toews, Ingrid; Glenton, Claire; Lewin, Simon; Berg, Rigmor C; Noyes, Jane; Booth, Andrew; Marusic, Ana; Malicki, Mario; Munthe-Kaas, Heather M; Meerpohl, Joerg J
2016-01-01
Qualitative research findings are increasingly used to inform decision-making. Research has indicated that not all quantitative research on the effects of interventions is disseminated or published. The extent to which qualitative researchers also systematically underreport or fail to publish certain types of research findings, and the impact this may have, has received little attention. A survey was delivered online to gather data regarding non-dissemination and dissemination bias in qualitative research. We invited relevant stakeholders through our professional networks, authors of qualitative research identified through a systematic literature search, and further via snowball sampling. 1032 people took part in the survey of whom 859 participants identified as researchers, 133 as editors and 682 as peer reviewers. 68.1% of the researchers said that they had conducted at least one qualitative study that they had not published in a peer-reviewed journal. The main reasons for non-dissemination were that a publication was still intended (35.7%), resource constraints (35.4%), and that the authors gave up after the paper was rejected by one or more journals (32.5%). A majority of the editors and peer reviewers "(strongly) agreed" that the main reasons for rejecting a manuscript of a qualitative study were inadequate study quality (59.5%; 68.5%) and inadequate reporting quality (59.1%; 57.5%). Of 800 respondents, 83.1% "(strongly) agreed" that non-dissemination and possible resulting dissemination bias might undermine the willingness of funders to support qualitative research. 72.6% and 71.2%, respectively, "(strongly) agreed" that non-dissemination might lead to inappropriate health policy and health care. The proportion of non-dissemination in qualitative research is substantial. Researchers, editors and peer reviewers play an important role in this. Non-dissemination and resulting dissemination bias may impact on health care research, practice and policy. More
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Directory of Open Access Journals (Sweden)
Ingrid Toews
Full Text Available Qualitative research findings are increasingly used to inform decision-making. Research has indicated that not all quantitative research on the effects of interventions is disseminated or published. The extent to which qualitative researchers also systematically underreport or fail to publish certain types of research findings, and the impact this may have, has received little attention.A survey was delivered online to gather data regarding non-dissemination and dissemination bias in qualitative research. We invited relevant stakeholders through our professional networks, authors of qualitative research identified through a systematic literature search, and further via snowball sampling.1032 people took part in the survey of whom 859 participants identified as researchers, 133 as editors and 682 as peer reviewers. 68.1% of the researchers said that they had conducted at least one qualitative study that they had not published in a peer-reviewed journal. The main reasons for non-dissemination were that a publication was still intended (35.7%, resource constraints (35.4%, and that the authors gave up after the paper was rejected by one or more journals (32.5%. A majority of the editors and peer reviewers "(strongly agreed" that the main reasons for rejecting a manuscript of a qualitative study were inadequate study quality (59.5%; 68.5% and inadequate reporting quality (59.1%; 57.5%. Of 800 respondents, 83.1% "(strongly agreed" that non-dissemination and possible resulting dissemination bias might undermine the willingness of funders to support qualitative research. 72.6% and 71.2%, respectively, "(strongly agreed" that non-dissemination might lead to inappropriate health policy and health care.The proportion of non-dissemination in qualitative research is substantial. Researchers, editors and peer reviewers play an important role in this. Non-dissemination and resulting dissemination bias may impact on health care research, practice and policy
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Strong interactions between learned helplessness and risky decision-making in a rat gambling model.
Nobrega, José N; Hedayatmofidi, Parisa S; Lobo, Daniela S
2016-11-18
Risky decision-making is characteristic of depression and of addictive disorders, including pathological gambling. However it is not clear whether a propensity to risky choices predisposes to depressive symptoms or whether the converse is the case. Here we tested the hypothesis that rats showing risky decision-making in a rat gambling task (rGT) would be more prone to depressive-like behaviour in the learned helplessness (LH) model. Results showed that baseline rGT choice behaviour did not predict escape deficits in the LH protocol. In contrast, exposure to the LH protocol resulted in a significant increase in risky rGT choices on retest. Unexpectedly, control rats subjected only to escapable stress in the LH protocol showed a subsequent decrease in riskier rGT choices. Further analyses indicated that the LH protocol affected primarily rats with high baseline levels of risky choices and that among these it had opposite effects in rats exposed to LH-inducing stress compared to rats exposed only to the escape trials. Together these findings suggest that while baseline risky decision making may not predict LH behaviour it interacts strongly with LH conditions in modulating subsequent decision-making behaviour. The suggested possibility that stress controllability may be a key factor should be further investigated.
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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.
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Framing obesity a disease: Indirect effects of affect and controllability beliefs on weight bias.
Nutter, Sarah; Alberga, Angela S; MacInnis, Cara; Ellard, John H; Russell-Mayhew, Shelly
2018-05-24
Obesity has been declared a disease by the American and Canadian Medical Associations. Although these declarations sparked much debate as to the impact of framing obesity as a disease on weight bias, strong empirical research is needed to examine this impact. The current study examined the impact of framing obesity a disease on weight bias, focusing on moderating and mediating processes. A sample of 309 participants living in the United States or Canada was recruited from Crowdflower. Participants completed measures of demographics, ideology, general attitudes, and previous contact quality and quantity with people living with obesity. Participants then read one of three articles as part of an experimental manipulation framing obesity as a disease, obesity not as a disease, and a control article unrelated to obesity. Post-manipulation included measures of affect, disgust, empathy, blame, and weight bias. Orthogonal contrasts were used to compare the obesity-disease condition to the obesity-not-disease condition and control condition. The manipulation had a direct effect on affect (emotions), such that affect toward individuals with obesity was more positive in the obesity-disease condition than the obesity-not-disease and control condition combined. Exploration of moderating effects revealed that both the belief in a just world and weight satisfaction moderated the relationship between the obesity-disease manipulation and blame for obesity. Two models of indirect effects on weight bias were also examined, which demonstrated that the obesity-disease manipulation predicted less weight bias through more positive affect (model 1) as well as less weight bias through decreased blame among individuals high in belief in a just world (model 2). This study further highlights the complex effects of declaring obesity a disease, uncovering a new direction for future research into the role of affect as well as indirect effects of characterising obesity a disease on weight bias.
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Attribution bias and social anxiety in schizophrenia
Directory of Open Access Journals (Sweden)
Amelie M. Achim
2016-06-01
Full Text Available Studies on attribution biases in schizophrenia have produced mixed results, whereas such biases have been more consistently reported in people with anxiety disorders. Anxiety comorbidities are frequent in schizophrenia, in particular social anxiety disorder, which could influence their patterns of attribution biases. The objective of the present study was thus to determine if individuals with schizophrenia and a comorbid social anxiety disorder (SZ+ show distinct attribution biases as compared with individuals with schizophrenia without social anxiety (SZ− and healthy controls. Attribution biases were assessed with the Internal, Personal, and Situational Attributions Questionnaire in 41 individual with schizophrenia and 41 healthy controls. Results revealed the lack of the normal externalizing bias in SZ+, whereas SZ− did not significantly differ from healthy controls on this dimension. The personalizing bias was not influenced by social anxiety but was in contrast linked with delusions, with a greater personalizing bias in individuals with current delusions. Future studies on attribution biases in schizophrenia should carefully document symptom presentation, including social anxiety.
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Tamate, Tsuyoshi
2015-08-01
Evolutionary ecologists often expect that natural and sexual selection result in systematic co-occurrence patterns of sex-biased mortality and sexual size dimorphism (SSD) within animal species. However, whether such patterns actually occur in wild animals is poorly examined. The following expectation, the larger sex suffers higher mortality, was primarily tested here for apparently native sea-run masu salmon (Oncorhynchus masou) in three populations in Hokkaido, Japan. Field surveys on sex ratios, body sizes, and ages of smolts and returning adults revealed that two of the three populations exhibited an expected pattern, a female-biased marine mortality and SSD, but one population demonstrated an unexpected co-occurrence of male-biased marine mortality and female-biased SSD. These female-biased SSDs were attributed to faster marine growth of females because of no sex difference in smolt body size. It has been previously suggested that breeding selection favoring large size generally act more strongly in females than in males in Japanese anadromous masu, as there is a weak sexual selection on adult males but universally intensive natural selection on adult females. Thus, this hypothesis explains female-biased SSDs well in all study populations. Interpopulation variation in sex-biased mortality found here might result from differences in marine predation and/or fishing pressures, given that selection driving female-biased SSD makes females forage more aggressively than males during the marine phase. Taken together, these results raise the possibility that evolutionary forces have shaped adaptive sex-specific foraging strategies under relationships between growth and mortality, resulting in co-occurrence patterns of sex-biased mortality and SSD within animal species.
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Directory of Open Access Journals (Sweden)
Maartje evan de Velde
2014-10-01
Full Text Available In sentence production, grammatical advance planning scope depends on contextual factors (e.g., time pressure, linguistic factors (e.g., ease of structural processing, and cognitive factors (e.g., production speed. The present study tests the influence of the availability of multiple syntactic alternatives (i.e., syntactic flexibility on the scope of advance planning during the recall of Dutch dative phrases. We manipulated syntactic flexibility by using verbs with a strong bias or a weak bias towards one structural alternative in sentence frames accepting both verbs (e.g., strong/weak bias: De ober schotelt/serveert de klant de maaltijd [voor] 'The waiter dishes out/serves the customer the meal'. To assess lexical planning scope, we varied the frequency of the first post-verbal noun (N1, Experiment 1 or the second post-verbal noun (N2, Experiment 2. In each experiment, 36 speakers produced the verb phrases in a Rapid Serial Visual Presentation (RSVP paradigm. On each trial, they read a sentence presented one word at a time, performed a short distractor task, and then saw a sentence preamble (e.g., De ober… which they had to complete to form the presented sentence. Onset latencies were compared using linear mixed effects models. N1 frequency did not produce any effects. N2 frequency only affected sentence onsets in the weak verb bias condition and especially in slow speakers. These findings highlight the dependency of planning scope during sentence recall on the grammatical properties of the verb and the frequency of post-verbal nouns. Implications for utterance planning in everyday speech are discussed.
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Transfer of test-enhanced learning: Meta-analytic review and synthesis.
Pan, Steven C; Rickard, Timothy C
2018-05-07
Attempting recall of information from memory, as occurs when taking a practice test, is one of the most potent training techniques known to learning science. However, does testing yield learning that transfers to different contexts? In the present article, we report the findings of the first comprehensive meta-analytic review into that question. Our review encompassed 192 transfer effect sizes extracted from 122 experiments and 67 published and unpublished articles (N = 10,382) that together comprise more than 40 years of research. A random-effects model revealed that testing can yield transferrable learning as measured relative to a nontesting reexposure control condition (d = 0.40, 95% CI [0.31, 0.50]). That transfer of learning is greatest across test formats, to application and inference questions, to problems involving medical diagnoses, and to mediator and related word cues; it is weakest to rearranged stimulus-response items, to untested materials seen during initial study, and to problems involving worked examples. Moderator analyses further indicated that response congruency and elaborated retrieval practice, as well as initial test performance, strongly influence the likelihood of positive transfer. In two assessments for publication bias using PET-PEESE and various selection methods, the moderator effect sizes were minimally affected. However, the intercept predictions were substantially reduced, often indicating no positive transfer when none of the aforementioned moderators are present. Overall, our results motivate a three-factor framework for transfer of test-enhanced learning and have practical implications for the effective use of practice testing in educational and other training contexts. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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Biased Brownian dynamics for rate constant calculation.
Zou, G; Skeel, R D; Subramaniam, S
2000-01-01
An enhanced sampling method-biased Brownian dynamics-is developed for the calculation of diffusion-limited biomolecular association reaction rates with high energy or entropy barriers. Biased Brownian dynamics introduces a biasing force in addition to the electrostatic force between the reactants, and it associates a probability weight with each trajectory. A simulation loses weight when movement is along the biasing force and gains weight when movement is against the biasing force. The sampl...
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Carbone, Alessandra; Madden, Richard
2005-10-01
Codon bias is related to metabolic functions in translationally biased organisms, and two facts are argued about. First, genes with high codon bias describe in meaningful ways the metabolic characteristics of the organism; important metabolic pathways corresponding to crucial characteristics of the lifestyle of an organism, such as photosynthesis, nitrification, anaerobic versus aerobic respiration, sulfate reduction, methanogenesis, and others, happen to involve especially biased genes. Second, gene transcriptional levels of sets of experiments representing a significant variation of biological conditions strikingly confirm, in the case of Saccharomyces cerevisiae, that metabolic preferences are detectable by purely statistical analysis: the high metabolic activity of yeast during fermentation is encoded in the high bias of enzymes involved in the associated pathways, suggesting that this genome was affected by a strong evolutionary pressure that favored a predominantly fermentative metabolism of yeast in the wild. The ensemble of metabolic pathways involving enzymes with high codon bias is rather well defined and remains consistent across many species, even those that have not been considered as translationally biased, such as Helicobacter pylori, for instance, reveal some weak form of translational bias for this genome. We provide numerical evidence, supported by experimental data, of these facts and conclude that the metabolic networks of translationally biased genomes, observable today as projections of eons of evolutionary pressure, can be analyzed numerically and predictions of the role of specific pathways during evolution can be derived. The new concepts of Comparative Pathway Index, used to compare organisms with respect to their metabolic networks, and Evolutionary Pathway Index, used to detect evolutionarily meaningful bias in the genetic code from transcriptional data, are introduced.
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Directory of Open Access Journals (Sweden)
Ann McCarthy
Full Text Available Bias is a pervasive problem when characterizing microbial communities. An important source is the difference in lysis efficiencies of different populations, which vary depending on the extraction protocol used. To avoid such biases impacting comparisons between gene and transcript abundances in the environment, the use of one protocol that simultaneously extracts both types of nucleic acids from microbial community samples has gained popularity. However, knowledge regarding tradeoffs to combined nucleic acid extraction protocols is limited, particularly regarding yield and biases in the observed community composition. Here, we evaluated a commercially available protocol for simultaneous extraction of DNA and RNA, which we adapted for freshwater microbial community samples that were collected on filters. DNA and RNA yields were comparable to other commonly used, but independent DNA and RNA extraction protocols. RNA protection agents benefited RNA quality, but decreased DNA yields significantly. Choice of extraction protocol influenced the perceived bacterial community composition, with strong method-dependent biases observed for specific phyla such as the Verrucomicrobia. The combined DNA/RNA extraction protocol detected significantly higher levels of Verrucomicrobia than the other protocols, and those higher numbers were confirmed by microscopic analysis. Use of RNA protection agents as well as independent sequencing runs caused a significant shift in community composition as well, albeit smaller than the shift caused by using different extraction protocols. Despite methodological biases, sample origin was the strongest determinant of community composition. However, when the abundance of specific phylogenetic groups is of interest, researchers need to be aware of the biases their methods introduce. This is particularly relevant if different methods are used for DNA and RNA extraction, in addition to using RNA protection agents only for RNA
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Platelet-biased stem cells reside at the apex of the haematopoietic stem-cell hierarchy.
Sanjuan-Pla, Alejandra; Macaulay, Iain C; Jensen, Christina T; Woll, Petter S; Luis, Tiago C; Mead, Adam; Moore, Susan; Carella, Cintia; Matsuoka, Sahoko; Bouriez Jones, Tiphaine; Chowdhury, Onima; Stenson, Laura; Lutteropp, Michael; Green, Joanna C A; Facchini, Raffaella; Boukarabila, Hanane; Grover, Amit; Gambardella, Adriana; Thongjuea, Supat; Carrelha, Joana; Tarrant, Paul; Atkinson, Deborah; Clark, Sally-Ann; Nerlov, Claus; Jacobsen, Sten Eirik W
2013-10-10
The blood system is maintained by a small pool of haematopoietic stem cells (HSCs), which are required and sufficient for replenishing all human blood cell lineages at millions of cells per second throughout life. Megakaryocytes in the bone marrow are responsible for the continuous production of platelets in the blood, crucial for preventing bleeding--a common and life-threatening side effect of many cancer therapies--and major efforts are focused at identifying the most suitable cellular and molecular targets to enhance platelet production after bone marrow transplantation or chemotherapy. Although it has become clear that distinct HSC subsets exist that are stably biased towards the generation of lymphoid or myeloid blood cells, we are yet to learn whether other types of lineage-biased HSC exist or understand their inter-relationships and how differently lineage-biased HSCs are generated and maintained. The functional relevance of notable phenotypic and molecular similarities between megakaryocytes and bone marrow cells with an HSC cell-surface phenotype remains unclear. Here we identify and prospectively isolate a molecularly and functionally distinct mouse HSC subset primed for platelet-specific gene expression, with enhanced propensity for short- and long-term reconstitution of platelets. Maintenance of platelet-biased HSCs crucially depends on thrombopoietin, the primary extrinsic regulator of platelet development. Platelet-primed HSCs also frequently have a long-term myeloid lineage bias, can self-renew and give rise to lymphoid-biased HSCs. These findings show that HSC subtypes can be organized into a cellular hierarchy, with platelet-primed HSCs at the apex. They also demonstrate that molecular and functional priming for platelet development initiates already in a distinct HSC population. The identification of a platelet-primed HSC population should enable the rational design of therapies enhancing platelet output.
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The coalitional value theory of antigay bias
Winegard, Bo; Reynolds, Tania; Baumeister, Roy F.; Plant, E. Ashby
2016-01-01
Research indicates that antigay bias follows a specific pattern (and probably has throughout written history, at least in the West): (a) men evince more antigay bias than women; (b) men who belong to traditionally male coalitions evince more antigay bias than those who do not; (c) antigay bias is
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Steger, Doris; Berry, David; Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander
2011-01-01
The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.
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Anti-Bias Education: Reflections
Derman-Sparks, Louise
2011-01-01
It is 30 years since NAEYC published "Anti-Bias Curriculum Tools for Empowering Young Children" (Derman-Sparks & ABC Task Force, 1989). Since then, anti-bias education concepts have become part of the early childhood education (ECE) narrative in the United States and many other countries. It has brought a fresh way of thinking about…
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A Bias for the Natural? Children's Beliefs about Traits Acquired through Effort, Bribes, or Medicine
Lockhart, Kristi L.; Keil, Frank C.; Aw, Justine
2013-01-01
Three studies compared beliefs about natural and late blooming positive traits with those acquired through personal effort, extrinsic rewards or medicine. Young children (5-6 years), older children (8-13 years), and adults all showed a strong bias for natural and late blooming traits over acquired traits. All age groups, except 8- to 10-year-olds,…
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Visual attention to features by associative learning.
Gozli, Davood G; Moskowitz, Joshua B; Pratt, Jay
2014-11-01
Expecting a particular stimulus can facilitate processing of that stimulus over others, but what is the fate of other stimuli that are known to co-occur with the expected stimulus? This study examined the impact of learned association on feature-based attention. The findings show that the effectiveness of an uninformative color transient in orienting attention can change by learned associations between colors and the expected target shape. In an initial acquisition phase, participants learned two distinct sequences of stimulus-response-outcome, where stimuli were defined by shape ('S' vs. 'H'), responses were localized key-presses (left vs. right), and outcomes were colors (red vs. green). Next, in a test phase, while expecting a target shape (80% probable), participants showed reliable attentional orienting to the color transient associated with the target shape, and showed no attentional orienting with the color associated with the alternative target shape. This bias seemed to be driven by learned association between shapes and colors, and not modulated by the response. In addition, the bias seemed to depend on observing target-color conjunctions, since encountering the two features disjunctively (without spatiotemporal overlap) did not replicate the findings. We conclude that associative learning - likely mediated by mechanisms underlying visual object representation - can extend the impact of goal-driven attention to features associated with a target stimulus. Copyright © 2014 Elsevier B.V. All rights reserved.
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Evolutionary dynamics of fluctuating populations with strong mutualism
Chotibut, Thiparat; Nelson, David
2013-03-01
Evolutionary game theory with finite interacting populations is receiving increased attention, including subtle phenomena associated with number fluctuations, i.e., ``genetic drift.'' Models of cooperation and competition often utilize a simplified Moran model, with a strictly fixed total population size. We explore a more general evolutionary model with independent fluctuations in the numbers of two distinct species, in a regime characterized by ``strong mutualism.'' The model has two absorbing states, each corresponding to fixation of one of the two species, and allows exploration of the interplay between growth, competition, and mutualism. When mutualism is favored, number fluctuations eventually drive the system away from a stable fixed point, characterized by cooperation, to one of the absorbing states. Well-mixed populations will thus be taken over by a single species in a finite time, despite the bias towards cooperation. We calculate both the fixation probability and the mean fixation time as a function of the initial conditions and carrying capacities in the strong mutualism regime, using the method of matched asymptotic expansions. Our results are compared to computer simulations.
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McVey, Gail L; Walker, Kathryn S; Beyers, Joanne; Harrison, Heather L; Simkins, Sari W; Russell-Mayhew, Shelly
2013-04-04
Promoting healthy weight is a top priority in Canada. Recent federal guidelines call for sustained, multisectoral partnerships that address childhood obesity on multiple levels. Current healthy weight messaging does not fully acknowledge the influence of social determinants of health on weight. An interactive workshop was developed and implemented by a team of academic researchers and health promoters from the psychology and public health disciplines to raise awareness about 1) weight bias and its negative effect on health, 2) ways to balance healthy weight messaging to prevent the triggering of weight and shape preoccupation, and 3) the incorporation of mental health promotion into healthy weight messaging. We conducted a full-day workshop with 342 Ontario public health promoters and administered a survey at preintervention, postintervention, and follow-up. Participation in the full-day workshop led to significant decreases in antifat attitudes and the internalization of media stereotypes and to significant increases in self-efficacy to address weight bias. Participants reported that the training heightened their awareness of their own personal weight biases and the need to broaden their scope of healthy weight promotion to include mental health promotion. There was consensus that additional sessions are warranted to help translate knowledge into action. Buy-in and resource support at the organizational level was also seen as pivotal. Professional development training in the area of weight bias awareness is associated with decreases in antifat attitudes and the internalization of media stereotypes around thinness. Health promoters' healthy weight messaging was improved by learning to avoid messages that trigger weight and shape preoccupation or unhealthful eating practices among children and youth. Participants also learned ways to integrate mental health promotion and resiliency-building into daily practice.
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International Nuclear Information System (INIS)
Blanchard, R.J.
1995-01-01
This documents Phase 1 determinations on sampler induced bias for four sampler types used in tank characterization. Each sampler, grab sampler or bottle-on-a-string, auger sampler, sludge sampler and universal sampler, is briefly discussed and their physical limits noted. Phase 2 of this document will define additional testing and analysis to further define Sampler Bias
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Religious Attitudes and Home Bias
C. Reggiani; G. Rossini
2008-01-01
Home bias affects trade in goods, services and financial assets. It is mostly generated by "natural" trade barriers. Among these dividers we may list many behavioral and sociological factors, such as status quo biases and a few kind of ‘embeddedness’. Unfortunately these factors are difficult to measure. An important part of ‘embeddedness’ may be related to religious attitudes. Is there any relation between economic home bias and religious attitudes at the individual tier? Our aim is to provi...
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Nakahashi, Wataru
2007-08-01
Conformity is often observed in human social learning. Social learners preferentially imitate the majority or most common behavior in many situations, though the strength of conformity varies with the situation. Why has such a psychological tendency evolved? I investigate this problem by extending a standard model of social learning evolution with infinite environmental states (Feldman, M.W., Aoki, K., Kumm, J., 1996. Individual versus social learning: evolutionary analysis in a fluctuating environment. Anthropol. Sci. 104, 209-231) to include conformity bias. I mainly focus on the relationship between the strength of conformity bias that evolves and environmental stability, which is one of the most important factors in the evolution of social learning. Using the evolutionarily stable strategy (ESS) approach, I show that conformity always evolves when environmental stability and the cost of adopting a wrong behavior are small, though environmental stability and the cost of individual learning both negatively affect the strength of conformity.
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Directory of Open Access Journals (Sweden)
Ranjana K. Mehta
2015-12-01
Full Text Available Standing desks have proven to be effective and viable solutions to combat sedentary behavior among children during the school day in studies around the world. However, little is known regarding the potential of such interventions on cognitive outcomes in children over time. The purpose of this pilot study was to determine the neurocognitive benefits, i.e., improvements in executive functioning and working memory, of stand-biased desks and explore any associated changes in frontal brain function. 34 freshman high school students were recruited for neurocognitive testing at two time points during the school year: (1 in the fall semester and (2 in the spring semester (after 27.57 (1.63 weeks of continued exposure. Executive function and working memory was evaluated using a computerized neurocognitive test battery, and brain activation patterns of the prefrontal cortex were obtained using functional near infrared spectroscopy. Continued utilization of the stand-biased desks was associated with significant improvements in executive function and working memory capabilities. Changes in corresponding brain activation patterns were also observed. These findings provide the first preliminary evidence on the neurocognitive benefits of standing desks, which to date have focused largely on energy expenditure. Findings obtained here can drive future research with larger samples and multiple schools, with comparison groups that may in turn implicate the importance of stand-biased desks, as simple environmental changes in classrooms, on enhancing children’s cognitive functioning that drive their cognitive development and impact educational outcomes.
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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....
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A Comparison of attentional biases and memory biases in social phobia and major depression
Rinck, M.; Becker, E.S.
2005-01-01
Cognitive processes play an important role in the etiology and maintenance of anxiety and depression. Current theories differ, however, in their predictions regarding the occurrence of attentional biases and memory biases in depression and anxiety. To allow for a systematic comparison of disorders
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Biro, Peter A
2013-02-01
Sampling animals from the wild for study is something nearly every biologist has done, but despite our best efforts to obtain random samples of animals, 'hidden' trait biases may still exist. For example, consistent behavioral traits can affect trappability/catchability, independent of obvious factors such as size and gender, and these traits are often correlated with other repeatable physiological and/or life history traits. If so, systematic sampling bias may exist for any of these traits. The extent to which this is a problem, of course, depends on the magnitude of bias, which is presently unknown because the underlying trait distributions in populations are usually unknown, or unknowable. Indeed, our present knowledge about sampling bias comes from samples (not complete population censuses), which can possess bias to begin with. I had the unique opportunity to create naturalized populations of fish by seeding each of four small fishless lakes with equal densities of slow-, intermediate-, and fast-growing fish. Using sampling methods that are not size-selective, I observed that fast-growing fish were up to two-times more likely to be sampled than slower-growing fish. This indicates substantial and systematic bias with respect to an important life history trait (growth rate). If correlations between behavioral, physiological and life-history traits are as widespread as the literature suggests, then many animal samples may be systematically biased with respect to these traits (e.g., when collecting animals for laboratory use), and affect our inferences about population structure and abundance. I conclude with a discussion on ways to minimize sampling bias for particular physiological/behavioral/life-history types within animal populations.
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Collegewide Promotion of E-Learning/Active Learning and Faculty Development
Ogawa, Nobuyuki; Shimizu, Akira
2016-01-01
Japanese National Institutes of Technology have revealed a plan to strongly promote e-Learning and active learning under the common schematization of education in over 50 campuses nationwide. Our e-Learning and ICT-driven education practiced for more than fifteen years were highly evaluated, and is playing a leading role in promoting e-Learning…
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Developmental precursors of young school-age children's hostile attribution bias.
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.
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Some dynamical properties of very strong double layers in a triple plasma device
International Nuclear Information System (INIS)
Carpenter, T.; Torven, S.
1987-01-01
Experimental results on three dynamic properties of very strong double layers observed in a triple plasma device are presented. First, it is observed that when an inductance of sufficient size is inserted in series with the external bias supply used to produce the double layer, disruptions in the plasma current occur accompanied by disruptions in the double layer potential. Second, it is observed that with all external reactances reduced as much as possible, a sort of jitter-motion occurs in the position of the double layer around its equilibrium position. Third, when the external bias supply is pulsed, the initial potential distribution is observed to have an essentially uniform slope, as in the case of a vacuum capacitor. The disruption phenomenon may be explained in terms of the behavior of the potential structure as a function of the bias voltage and this explanation is discussed along with the experimental evidence for its validity. A comparable understanding of the other two phenomena has not been achieved, but in both cases there are qualitative difference between the behavior reported here and what has been observed in Q-machines and these difference are discussed. (author)
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Strongly correlated quantum transport out-of-equilibrium
Dutt, Prasenjit
The revolutionary advances in nanotechnology and nanofabrication have facilitated the precise control and manipulation of mesoscopic systems where quantum effects are pronounced. Quantum devices with tunable gates have made it possible to access regimes far beyond the purview of linear response theory. In particular, the influence of strong voltage and thermal biases has led to the observation of novel phenomena where the non-equilibrium characteristics of the system are of paramount importance. We study transport through quantum-impurity systems in the regime of strong correlations and determine the effects of large temperature and potential gradients on its many-body physics. In Part I of this thesis we focus on the steady-state dynamics of the system, a commonly encountered experimental scenario. For a system consisting of several leads composed of non-interacting electrons, each individually coupled to a quantum impurity with interactions and maintained at different chemical potentials, we reformulate the system in terms of an effective-equilibrium density matrix. This density matrix has a simple Boltzmann-like form in terms of the system's Lippmann-Schwinger (scattering) operators. We elaborate the conditions for this description to be valid based on the microscopic Hamiltonian of the system. We then prove the equivalence of physical observables computed using this formulation with corresponding expressions in the Schwinger-Keldysh approach and provide a dictionary between Green's functions in either scheme. An imaginary-time functional integral framework to compute finite temperature Green's functions is proposed and used to develop a novel perturbative expansion in the interaction strength which is exact in all other system parameters. We use these tools to study the fate of the Abrikosov-Suhl regime on the Kondo-correlated quantum dot due to the effects of bias and external magnetic fields. Next, we expand the domain of this formalism to additionally
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Domain wall engineering through exchange bias
International Nuclear Information System (INIS)
Albisetti, E.; Petti, D.
2016-01-01
The control of the structure and position of magnetic domain walls is at the basis of the development of different magnetic devices and architectures. Several nanofabrication techniques have been proposed to geometrically confine and shape domain wall structures; however, a fine tuning of the position and micromagnetic configuration is hardly achieved, especially in continuous films. This work shows that, by controlling the unidirectional anisotropy of a continuous ferromagnetic film through exchange bias, domain walls whose spin arrangement is generally not favored by dipolar and exchange interactions can be created. Micromagnetic simulations reveal that the domain wall width, position and profile can be tuned by establishing an abrupt change in the direction and magnitude of the exchange bias field set in the system. - Highlights: • Micromagnetic simulations study domain walls in exchange biased thin films. • Novel domain wall configurations can be stabilized via exchange bias. • Domain walls nucleate at the boundary of regions with different exchange bias. • Domain wall width and spin profile are controlled by tuning the exchange bias.
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E-Learning Research and Development: On Evaluation, Learning Performance, and Visual Attention
Rüth, Marco
2017-01-01
Digital learning is becoming a prevalent everyday human behavior. Effective digital learning services are integral for educational innovation and constitute competitive advantages for education businesses. Quality management in e-learning research and development is thus of utmost importance and needs both strong conceptual and empirical…
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How we categorize objects is related to how we remember them: The shape bias as a memory bias.
Vlach, Haley A
2016-12-01
The "shape bias" describes the phenomenon that, after a certain point in development, children and adults generalize object categories based on shape to a greater degree than other perceptual features. The focus of research on the shape bias has been to examine the types of information that learners attend to in one moment in time. The current work takes a different approach by examining whether learners' categorical biases are related to their retention of information across time. In three experiments, children's (N=72) and adults' (N=240) memory performance for features of objects was examined in relation to their categorical biases. The results of these experiments demonstrated that the number of shape matches chosen during the shape bias task significantly predicted shape memory. Moreover, children and adults with a shape bias were more likely to remember the shape of objects than the color and size of objects. Taken together, this work suggests that the development of a shape bias may engender better memory for shape information. Copyright © 2016 Elsevier Inc. All rights reserved.
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Zwaan, Laura; Monteiro, Sandra; Sherbino, Jonathan; Ilgen, Jonathan; Howey, Betty; Norman, Geoffrey
2017-02-01
Many authors have implicated cognitive biases as a primary cause of diagnostic error. If this is so, then physicians already familiar with common cognitive biases should consistently identify biases present in a clinical workup. The aim of this paper is to determine whether physicians agree on the presence or absence of particular biases in a clinical case workup and how case outcome knowledge affects bias identification. We conducted a web survey of 37 physicians. Each participant read eight cases and listed which biases were present from a list provided. In half the cases the outcome implied a correct diagnosis; in the other half, it implied an incorrect diagnosis. We compared the number of biases identified when the outcome implied a correct or incorrect primary diagnosis. Additionally, the agreement among participants about presence or absence of specific biases was assessed. When the case outcome implied a correct diagnosis, an average of 1.75 cognitive biases were reported; when incorrect, 3.45 biases (F=71.3, p<0.00001). Individual biases were reported from 73% to 125% more often when an incorrect diagnosis was implied. There was no agreement on presence or absence of individual biases, with κ ranging from 0.000 to 0.044. Individual physicians are unable to agree on the presence or absence of individual cognitive biases. Their judgements are heavily influenced by hindsight bias; when the outcome implies a diagnostic error, twice as many biases are identified. The results present challenges for current error reduction strategies based on identification of cognitive biases. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
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Possible Sources of Bias in Primary Care Electronic Health Record Data Use and Reuse.
Verheij, Robert A; Curcin, Vasa; Delaney, Brendan C; McGilchrist, Mark M
2018-05-29
Enormous amounts of data are recorded routinely in health care as part of the care process, primarily for managing individual patient care. There are significant opportunities to use these data for other purposes, many of which would contribute to establishing a learning health system. This is particularly true for data recorded in primary care settings, as in many countries, these are the first place patients turn to for most health problems. In this paper, we discuss whether data that are recorded routinely as part of the health care process in primary care are actually fit to use for other purposes such as research and quality of health care indicators, how the original purpose may affect the extent to which the data are fit for another purpose, and the mechanisms behind these effects. In doing so, we want to identify possible sources of bias that are relevant for the use and reuse of these type of data. This paper is based on the authors' experience as users of electronic health records data, as general practitioners, health informatics experts, and health services researchers. It is a product of the discussions they had during the Translational Research and Patient Safety in Europe (TRANSFoRm) project, which was funded by the European Commission and sought to develop, pilot, and evaluate a core information architecture for the learning health system in Europe, based on primary care electronic health records. We first describe the different stages in the processing of electronic health record data, as well as the different purposes for which these data are used. Given the different data processing steps and purposes, we then discuss the possible mechanisms for each individual data processing step that can generate biased outcomes. We identified 13 possible sources of bias. Four of them are related to the organization of a health care system, whereas some are of a more technical nature. There are a substantial number of possible sources of bias; very little is
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Learning multivariate distributions by competitive assembly of marginals.
Sánchez-Vega, Francisco; Younes, Laurent; Geman, Donald
2013-02-01
We present a new framework for learning high-dimensional multivariate probability distributions from estimated marginals. The approach is motivated by compositional models and Bayesian networks, and designed to adapt to small sample sizes. We start with a large, overlapping set of elementary statistical building blocks, or "primitives," which are low-dimensional marginal distributions learned from data. Each variable may appear in many primitives. Subsets of primitives are combined in a Lego-like fashion to construct a probabilistic graphical model; only a small fraction of the primitives will participate in any valid construction. Since primitives can be precomputed, parameter estimation and structure search are separated. Model complexity is controlled by strong biases; we adapt the primitives to the amount of training data and impose rules which restrict the merging of them into allowable compositions. The likelihood of the data decomposes into a sum of local gains, one for each primitive in the final structure. We focus on a specific subclass of networks which are binary forests. Structure optimization corresponds to an integer linear program and the maximizing composition can be computed for reasonably large numbers of variables. Performance is evaluated using both synthetic data and real datasets from natural language processing and computational biology.
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International Nuclear Information System (INIS)
Poirier, R.L.; Enegren, T.A.; Enchevich, I.B.
1991-05-01
The RF cavity for the booster synchrotron requires a frequency swing from 46 MHz at a repetition rate of 50 Hz and a maximum accelerating gap voltage of 65 kV. A DC biased prototype cavity built at LANL using perpendicular-biased yttrium-garnet ferrites, rather than the more conventional parallel-biased NiZn ferrites, has now undergone major reconstruction at TRIUMF for AC bias operation. RF signal level measurements have shown that the frequency swing at a repetition rate of 50 Hz can be accomplished and still handle the eddy current losses in the cavity structures with minimal effect on the magnetizing field. The prototype cavity is now undergoing high power RF tests with full power AC bias operation. The results of these tests and operational experience is reported. (Author) ref., 6 figs
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On the Contribution of Large-Scale Structure to Strong Gravitational Lensing
Faure, C.; Kneib, J.-P.; Hilbert, S.; Massey, R.; Covone, G.; Finoguenov, A.; Leauthaud, A.; Taylor, J. E.; Pires, S.; Scoville, N.; Koekemoer, Anton M.
2009-04-01
We study the correlation between the locations of galaxy-galaxy strong-lensing candidates and tracers of large-scale structure from both weak lensing (WL) or X-ray emission. The Cosmological Evolution Survey (COSMOS) is a unique data set, combining deep, high resolution and contiguous imaging in which strong lenses have been discovered, plus unparalleled multiwavelength coverage. To help interpret the COSMOS data, we have also produced mock COSMOS strong- and WL observations, based on ray-tracing through the Millennium Simulation. In agreement with the simulations, we find that strongly lensed images with the largest angular separations are found in the densest regions of the COSMOS field. This is explained by a prevalence among the lens population in dense environments of elliptical galaxies with high total-to-stellar mass ratios, which can deflect light through larger angles. However, we also find that the overall fraction of elliptical galaxies with strong gravitational lensing is independent of the local mass density; this observation is not true of the simulations, which predict an increasing fraction of strong lenses in dense environments. The discrepancy may be a real effect, but could also be explained by various limitations of our analysis. For example, our visual search of strong lens systems could be incomplete and suffer from selection bias; the luminosity function of elliptical galaxies may differ between our real and simulated data; or the simplifying assumptions and approximations used in our lensing simulations may be inadequate. Work is therefore ongoing. Automated searches for strong lens systems will be particularly important in better constraining the selection function.
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Directory of Open Access Journals (Sweden)
ELISABETTA eMONFARDINI
2012-09-01
Full Text Available Much theoretical attention is currently devoted to social learning. Yet, empirical studies formally comparing its effectiveness relative to individual learning are rare. Here, we focus on free choice, which is at the heart of individual reward-based learning, but absent in social learning. Choosing among two equally valued options is known to create a preference for the selected option in both humans and monkeys. We thus surmised that social learning should be more helpful when choice-induced preferences retard individual learning than when they optimize it. To test this prediction, the same task requiring to find which among two items concealed a reward was applied to rhesus macaques and humans. The initial trial was individual or social, rewarded or unrewarded. Learning was assessed on the second trial. Choice-induced preference strongly affected individual learning. Monkeys and humans performed much more poorly after an initial negative choice than after an initial positive choice. Comparison with social learning verified our prediction. For negative outcome, social learning surpassed or at least equaled individual learning in all subjects. For positive outcome, the predicted superiority of individual learning did occur in a majority of subjects (5/6 monkeys and 6/12 humans. A minority kept learning better socially though, perhaps due to a more dominant/aggressive attitude toward peers. Poor learning from errors due to over-valuation of personal choices is among the decision-making biases shared by humans and animals. The present study suggests that choice-immune social learning may help curbing this potentially harmful tendency. Learning from successes is an easier path. The present data suggest that whether one tends to walk it alone or with a peer's help might depend on the social dynamics within the actor/observer dyad.
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Grain Boundary Induced Bias Instability in Soluble Acene-Based Thin-Film Transistors
Nguyen, Ky V.; Payne, Marcia M.; Anthony, John E.; Lee, Jung Hun; Song, Eunjoo; Kang, Boseok; Cho, Kilwon; Lee, Wi Hyoung
2016-01-01
Since the grain boundaries (GBs) within the semiconductor layer of organic field-effect transistors (OFETs) have a strong influence on device performance, a substantial number of studies have been devoted to controlling the crystallization characteristics of organic semiconductors. We studied the intrinsic effects of GBs within 5,11-bis(triethylsilylethynyl) anthradithiophene (TES-ADT) thin films on the electrical properties of OFETs. The GB density was easily changed by controlling nulceation event in TES-ADT thin films. When the mixing time was increased, the number of aggregates in as-spun TES-ADT thin films were increased and subsequent exposure of the films to 1,2-dichloroethane vapor led to a significant increase in the number of nuleation sites, thereby increasing the GB density of TES-ADT spherulites. The density of GBs strongly influences the angular spread and crystallographic orientation of TES-ADT spherulites. Accordingly, the FETs with higher GB densities showed much poorer electrical characteristics than devices with lower GB density. Especially, GBs provide charge trapping sites which are responsible for bias-stress driven electrical instability. Dielectric surface treatment with a polystyrene brush layer clarified the GB-induced charge trapping by reducing charge trapping at the semiconductor-dielectric interface. Our study provides an understanding on GB induced bias instability for the development of high performance OFETs. PMID:27615358
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Babbitt, Gregory A; Alawad, Mohammed A; Schulze, Katharina V; Hudson, André O
2014-01-01
While mRNA stability has been demonstrated to control rates of translation, generating both global and local synonymous codon biases in many unicellular organisms, this explanation cannot adequately explain why codon bias strongly tracks neighboring intergene GC content; suggesting that structural dynamics of DNA might also influence codon choice. Because minor groove width is highly governed by 3-base periodicity in GC, the existence of triplet-based codons might imply a functional role for the optimization of local DNA molecular dynamics via GC content at synonymous sites (≈GC3). We confirm a strong association between GC3-related intrinsic DNA flexibility and codon bias across 24 different prokaryotic multiple whole-genome alignments. We develop a novel test of natural selection targeting synonymous sites and demonstrate that GC3-related DNA backbone dynamics have been subject to moderate selective pressure, perhaps contributing to our observation that many genes possess extreme DNA backbone dynamics for their given protein space. This dual function of codons may impose universal functional constraints affecting the evolution of synonymous and non-synonymous sites. We propose that synonymous sites may have evolved as an 'accessory' during an early expansion of a primordial genetic code, allowing for multiplexed protein coding and structural dynamic information within the same molecular context. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
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delta-biased Josephson tunnel junctions
DEFF Research Database (Denmark)
Monaco, R.; Mygind, Jesper; Koshelet, V.
2010-01-01
Abstract: The behavior of a long Josephson tunnel junction drastically depends on the distribution of the dc bias current. We investigate the case in which the bias current is fed in the central point of a one-dimensional junction. Such junction configuration has been recently used to detect...... the persistent currents circulating in a superconducting loop. Analytical and numerical results indicate that the presence of fractional vortices leads to remarkable differences from the conventional case of uniformly distributed dc bias current. The theoretical findings are supported by detailed measurements...
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Al-Neklawy, Ahmed Farid
2017-11-01
Although the traditional didactic lecture is considered to be efficient for presenting information and providing explanations, it usually does not provide adequate time for deeper learning activities. So, traditional lecture is one of the most widely criticized educational methods. Virtual learning environment (VLE) is a specially designed environment that facilitates teachers' management of educational courses for their students, using computer hardware and software, which involves distance learning. In this study, we evaluated the experiment of online teaching of General Embryology for Egyptian undergraduate medical students using WizIQ learning management system. A total of 100 students were invited to submit an online survey at the end of the course to evaluate delivery of instruction, creation of an environment that supported learning, and administrative issues. Most of the students reported that they were strongly satisfied with the efficacy of the instructional methods and were strongly satisfied with the degree of clarity of the course material. They strongly accepted the page format and design of the virtual classroom and strongly agreed that the learning environment supported the learning procedure. The item of easy logging into the virtual classroom had aberrant variable responses; it recorded the lowest mean response; this variation in responses was due to technical factors as the students used different devices with different speeds of internet connections. Ninety percent of students have strongly recommended the course attendance for their fellow students. These results demonstrate that online Anatomy teaching using learning management systems appears to be a successful additional learning tool among Egyptian medical students. Copyright © 2017 Elsevier GmbH. All rights reserved.
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Exploring the microscopic origin of exchange bias with photoelectron emission microscopy (invited)
International Nuclear Information System (INIS)
Scholl, A.; Nolting, F.; Stohr, J.; Regan, T.; Luning, J.; Seo, J. W.; Locquet, J.-P.; Fompeyrine, J.; Anders, S.; Ohldag, H.
2001-01-01
It is well known that magnetic exchange coupling across the ferromagnet - antiferromagnet interface results in an unidirectional magnetic anisotropy of the ferromagnetic layer, called exchange bias. Despite large experimental and theoretical efforts, the origin of exchange bias is still controversial, mainly because detection of the interfacial magnetic structure is difficult. We have applied photoelectron emission microscopy (PEEM) on several ferromagnet - antiferromagnet thin-film structures and microscopically imaged the ferromagnetic and the antiferromagnetic structure with high spatial resolution. Taking advantage of the surface sensitivity and elemental specificity of PEEM, the magnetic configuration and critical properties such as the Neel temperature were determined on LaFeO 3 and NiO thin films and single crystals. On samples coated with a ferromagnetic layer, we microscopically observe exchange coupling across the interface, causing a clear correspondence of the domain structures in the adjacent ferromagnet and antiferromagnet. Field dependent measurements reveal a strong uniaxial anisotropy in individual ferromagnetic domains. A local exchange bias was observed even in not explicitly field-annealed samples, caused by interfacial uncompensated magnetic spins. These experiments provide highly desired information on the relative orientation of electron spins at the interface between ferromagnets and antiferromagnets. [copyright] 2001 American Institute of Physics
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Greifeneder, Rainer; Zelt, Sarah; Seele, Tim; Bottenberg, Konstantin; Alt, Alexander
2012-09-01
Handwriting legibility systematically biases evaluations in that highly legible handwriting results in more positive evaluations than less legible handwriting. Because performance assessments in educational contexts are not only based on computerized or multiple choice tests but often include the evaluation of handwritten work samples, understanding the causes of this bias is critical. This research was designed to replicate and extend the legibility bias in two tightly controlled experiments and to explore whether gender-based inferences contribute to its occurrence. A total of 132 students from a German university participated in one pre-test and two independent experiments. Participants were asked to read and evaluate several handwritten essays varying in content quality. Each essay was presented to some participants in highly legible handwriting and to other participants in less legible handwriting. In addition, the assignment of legibility to participant group was reversed from essay to essay, resulting in a mixed-factor design. The legibility bias was replicated in both experiments. Results suggest that gender-based inferences do not account for its occurrence. Rather it appears that fluency from legibility exerts a biasing impact on evaluations of content and author abilities. The legibility bias was shown to be genuine and strong. By refuting a series of alternative explanations, this research contributes to a better understanding of what underlies the legibility bias. The present research may inform those who grade on what to focus and thus help to better allocate cognitive resources when trying to reduce this important source of error. ©2011 The British Psychological Society.
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International Nuclear Information System (INIS)
Ostapchenko, S.
2011-01-01
The model-dependence of the relation between the inelastic and various minimum-bias proton-proton cross sections is analyzed, paying a special attention to the sensitivity of minimum-bias triggers to diffractive collisions. Concentrating on the trigger selections of the ATLAS experiment, the measured cross sections are compared to predictions of a number of hadronic Monte Carlo models used in the cosmic ray field. It is demonstrated that the ATLAS results are able to discriminate between different models and between certain theoretical approaches for soft multi-particle production. On the other hand, the strong model-dependence of the selection efficiency of the minimum-bias triggers prevents one from inferring high mass diffraction rate from the discussed data. Moreover, the measured cross sections prove to be insensitive to the production of low mass diffractive states in proton-proton collisions. Consequently, a reliable determination of the total inelastic cross section requires forward proton tracking by a dedicated experiment.
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Learning and judgment can be affected by predisposed fearfulness in laying hens
Haas, de Elske N.; Lee, Caroline; Rodenburg, Bas
2017-01-01
High fearfulness could disrupt learning and likely affects judgment in animals, especially when it is part of an animals' personality, i.e., trait anxiety. Here, we tested whether high fearfulness affects discrimination learning and judgment bias (JB) in laying hens. Based on the response to an open
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Decision making biases in the communication of earthquake risk
Welsh, M. B.; Steacy, S.; Begg, S. H.; Navarro, D. J.
2015-12-01
L'Aquila, with 6 scientists convicted of manslaughter, shocked the scientific community, leading to urgent re-appraisal of communication methods for low-probability, high-impact events. Before the trial, a commission investigating the earthquake recommended risk assessment be formalised via operational earthquake forecasts and that social scientists be enlisted to assist in developing communication strategies. Psychological research has identified numerous decision biases relevant to this, including hindsight bias, where people (after the fact) overestimate an event's predictability. This affects experts as well as naïve participants as it relates to their ability to construct a plausible causal story rather than the likelihood of the event. Another problem is availability, which causes overestimation of the likelihood of observed rare events due to their greater noteworthiness. This, however, is complicated by the 'description-experience' gap, whereby people underestimate probabilities for events they have not experienced. That is, people who have experienced strong earthquakes judge them more likely while those who have not judge them less likely - relative to actual probabilities. Finally, format changes alter people's decisions. That is people treat '1 in 10,000' as different from 0.01% despite their mathematical equivalence. Such effects fall under the broad term framing, which describes how different framings of the same event alter decisions. In particular, people's attitude to risk depends significantly on how scenarios are described. We examine the effect of biases on the communication of change in risk. South Australian participants gave responses to scenarios describing familiar (bushfire) or unfamiliar (earthquake) risks. While bushfires are rare in specific locations, significant fire events occur each year and are extensively covered. By comparison, our study location (Adelaide) last had a M5 quake in 1954. Preliminary results suggest the description
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Waters, Allison M; Forrest, Kylee; Peters, Rosie-Mae; Bradley, Brendan P; Mogg, Karin
2015-03-01
Children of parents with emotional disorders have an increased risk for developing anxiety and depressive disorders. Yet the mechanisms that contribute to this increased risk are poorly understood. The present study aimed to examine attention biases in children as a function of maternal lifetime emotional disorders and maternal attention biases. There were 134 participants, including 38 high-risk children, and their mothers who had lifetime emotional disorders; and 29 low-risk children, and their mothers without lifetime emotional disorders. Mothers and children completed a visual probe task with emotional face pairs presented for 500 ms. Attention bias in children did not significantly differ solely as a function of whether or not their mothers had lifetime emotional disorders. However, attention bias in high-risk children was significantly related to their mothers' attention bias. Specifically, children of mothers with lifetime emotional disorders showed a greater negative attention bias if their mothers had a greater tendency to direct attention away from positive information. This study was cross-sectional in nature, and therefore unable to assess long-term predictive effects. Also, just one exposure duration of 500 ms was utilised. Attention bias for negative information is greater in offspring of mothers who have lifetime emotional disorders and a reduced positive bias, which could be a risk marker for the development of emotional disorders in children.