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A major concern with Bayesian decision making under uncertainty is the use of a single probability measure to quantify all relevant uncertainty. This paper studies prior robustness as a form of continuity of the value of a decision problem. I show that this notion of robustness is characterized by a form of stable choice over a sequence of perturbed decision problems, in which the available acts are perturbed in a precise fashion. I then introduce a choice-based measure of prior robustness and apply it to models of climate mitigation and portfolio choice. • Belief Robustness and Continuity: Beliefs are "robust" if minor changes in beliefs lead to minor changes in choices. This notion can be tested by evaluating perturbations of feasible bets. • Measure of Robustness: A comparative measure of belief robustness can quantify the sensitivity of optimal choices to parametric assumptions. • Impact on Key Economic Models: The measure shows that heavy-tailed distributions yield more robust choices in portfolio and economy-climate models, highlighting its practical importance. [ABSTRACT FROM AUTHOR]

Complexity of the problem of choosing among uncertain acts is a salient feature of many of the environments in which departures from expected utility theory are observed. I study a class of Generalized Simple Bounds preferences in which acts that are complex from the perspective of the decision maker are bracketed by "simple" acts to which they are related by statewise dominance. I then study a refinement of the model in which the size of the partition with respect to which an act is measurable arises endogenously as a measure of subjective complexity. Finally, I consider choice behavior characterized by a "cautious completion" of Simple Bounds preferences, and discuss the relationship between this model and models of ambiguity aversion. I develop general comparative statics results, and explore applications to portfolio choice and insurance choice. • Problems of choice problems under uncertainty are complex. • From behavioral axioms, I characterize the set of acts that are well-understood. • Decision makers use acts they understand well to bracket those they do not. • The model is tractable, and admits rich comparative statics. • The model helps explain observed choice patterns in applications. [ABSTRACT FROM AUTHOR]

The uncertainty in Facial expression recognition (FER) data is caused by factors such as ambiguous facial expressions, low-resolution facial images, the subjectivity of the annotator or subject of expression, and compound expression. FER has been steadily evolving with the advent of deep learning, but the label inconsistency problem due to the uncertainty in large FER datasets is one of the challenges in FER. Noisy labels in the label inconsistency problem adversely affect emotion recognition results. In this paper, we propose a Face-Specific Label Distribution Learning (FSLDL) method, which encourages deep networks to predict the actual emotion distribution of the input itself, rather than the noisy single label. Under the assumption that the emotion distribution of a specific sample is similar to the emotion distribution of the augmented sample from a different viewpoint, we generate a new target label distribution using facial expression-specific augmented samples. In order to generate a sophisticated target label distribution, the importance weights of the augmented samples are extracted and multiplied by each predicted emotion distribution. In addition, we compensate for the lack of information in the target label distribution by calculating the uncertainty of the provided label, and use it for model training. Finally, we make a more robust model by adding a rank regularization loss function for the importance weights and a discriminative loss function for the feature vectors. Representative experiments demonstrated that FSLDL outperforms the state-of-the-art on FER datasets such as RAF-DB, AffectNet, and SFEW. In addition, we demonstrated the effectiveness of the proposed method through various noisy label injection experiments. [Display omitted] • Noisy labels in the FER dataset affect facial expression recognition performance. • It is helpful to use distributions for facial expressions rather than single labels. • New target distribution created with faces from multi-perspectives using augmentation. • New target distribution reflecting original labels with uncertainty for each sample. • Proving the effectiveness of our method through noisy label injection experiments. [ABSTRACT FROM AUTHOR]

To interact with humans in collaborative environments, machines need to be able to predict (i.e., anticipate) future events, and execute actions in a timely manner. However, the observation of the human limb movements may not be sufficient to anticipate their actions unambiguously. In this work, we consider two additional sources of information (i.e., context) over time, gaze, movement and object information, and study how these additional contextual cues improve the action anticipation performance. We address action anticipation as a classification task, where the model takes the available information as the input and predicts the most likely action. We propose to use the uncertainty about each prediction as an online decision-making criterion for action anticipation. Uncertainty is modeled as a stochastic process applied to a time-based neural network architecture, which improves the conventional class-likelihood (i.e., deterministic) criterion. The main contributions of this paper are fourfold: (i) We propose a novel and effective decision-making criterion that can be used to anticipate actions even in situations of high ambiguity; (ii) we propose a deep architecture that outperforms previous results in the action anticipation task when using the Acticipate collaborative dataset; (iii) we show that contextual information is important to disambiguate the interpretation of similar actions; and (iv) we also provide a formal description of three existing performance metrics that can be easily used to evaluate action anticipation models. Our results on the Acticipate dataset showed the importance of contextual information and the uncertainty criterion for action anticipation. We achieve an average accuracy of 98.75 % in the anticipation task using only an average of 25 % of observations. Also, considering that a good anticipation model should perform well in the action recognition task, we achieve an average accuracy of 100 % in action recognition on the Acticipate dataset, when the entire observation set is used. [ABSTRACT FROM AUTHOR]

Potential genotoxicity is one of the essential considerations in the safety assessment of chemicals to which humans may be exposed. Several endpoints are used to evaluate genotoxicity, but, in each case, a binary assessment (negative/positive) is demanded by regulators. The use of binary assessment has rarely been questioned, although we have pointed out some questions and difficulties with regard to the statistical methods used and the evaluation of biological significance, both of which inform the calls of negative/ positive. Here, we discuss these issues further, focusing on ambiguity and uncertainty in the binary paradigm, and we seek a new direction for genotoxicity assessment. To this end, we need to understand, acknowledge, and accept these ambiguities and study-related uncertainties and then to consider new strategies for safety assessment. We also discuss the communication of ambiguity and uncertainty in risk communication. • Genotoxicity study results have usually been evaluated on a binary basis. • Statistical/biological evaluation cannot classify all results in binary terms. • Because many evaluations leave room for ambiguity/uncertainty. • We believe that it is time to retire the binary paradigm. • Ambiguity/uncertainty of test results must be communicated clearly. [ABSTRACT FROM AUTHOR]

We report the results of an experiment eliciting individuals' attitudes toward risk and model uncertainty. Using a joint elicitation procedure, we then precisely quantify the strength of individuals' attitude toward ambiguity in the context of the smooth model and characterize its main properties. Our results provide empirical evidence of decreasing absolute ambiguity aversion (DAAA) and constant relative ambiguity aversion (CRAA). These results shed new light on the way ambiguity attitudes may affect important decisions, such as the choice of health insurance policies or the optimal investment strategy in the face of climate change. [ABSTRACT FROM AUTHOR]

• Subjects respond in a pessimistic/averse manner to the uncertainty surrounding climate change and climate change catastrophes, with 67% of subjects successfully purchasing the climate change insurance in the base treatment. • When subjects have more information about the growing frequency of such events, 79% successfully ensure themselves. • A lemons problem may arise with only high-risk individuals/regions subscribing towards climate change insurance and suggests that government intervention may be required to ensure market failures do not arise. • When the strategic uncertainty of coordination with another person is removed, 81% of subjects are successful in buying the insurance. • An indirect intervention in the form of a nudge was unsuccessful, with only 58% of subjects successfully buying the insurance. This paper attempts to study how individuals respond to the availability of an insurance that would safeguard their interests if a climate change catastrophe occurred. If such an insurance is available to them, do individuals insure themselves sufficiently? Further, the study investigates if information regarding the past occurrence of the catastrophic event leads to an increase in insurance subscriptions and/or the emergence of a lemons market. Finally, policy implications are investigated - Can an indirect intervention in the form of a "nudge" ensure a better outcome? [ABSTRACT FROM AUTHOR]

Background: Uncertainty tolerance (UT) is thought to be a characteristic of individuals that influences various outcomes related to health, healthcare, and healthcare education. We undertook a systematic literature review to evaluate the state of the evidence on UT and its relationship to these outcomes.Methods: We conducted electronic and bibliographic searches to identify relevant studies examining associations between UT and health, healthcare, or healthcare education outcomes. We used standardized tools to assess methodological quality and analyzed the major findings of existing studies, which we organized and classified by theme.Results: Searches yielded 542 potentially relevant articles, of which 67 met inclusion criteria. Existing studies were heterogeneous in focus, setting, and measurement approach, were largely cross-sectional in design, and overall methodological quality was low. UT was associated with various trainee-centered, provider-centered, and patient-centered outcomes which were cognitive, emotional, and behavioral in nature. UT was most consistently associated with emotional well-being.Conclusions: Uncertainty tolerance is associated with several important trainee-, provider-, and patient-centered outcomes in healthcare and healthcare education. However, low methodological quality, study design limitations, and heterogeneity in the measurement of UT limit strong inferences about its effects, and addressing these problems is a critical need for future research. [ABSTRACT FROM AUTHOR]

[Display omitted] • A data-driven TSDRO model is developed for refinery planning under uncertainty. • The uncertainty set is constructed by the Wasserstein metric and RKDE approach. • The robust counterpart of the proposed model is reformulated by duality theory. • A real-world case study of an industrial refinery is presented. • The out-of-sample performance of different methods are analyzed. This work investigates the refinery planning problem under uncertainty in product prices. A novel data-driven Wasserstein distributionally robust optimization framework is proposed for handling uncertainties in the refinery-wide planning operations. A data-driven ambiguity set is constructed based on the Wasserstein metric to model the distributional uncertainty. The robust kernel density estimation technique is adopted to establish the support set to reduce the effect of the potential outliers. Based on the derived support set and ambiguity set, a data-driven two-stage distributionally robust optimization model for refinery planning is developed. Then, the robust counterpart of the proposed model is formulated to make the problem computationally tractable. Finally, a real-world case study on a petroleum refinery is presented to illustrate the effectiveness and applicability of the proposed framework. [ABSTRACT FROM AUTHOR]

Rationale Uncertainty tolerance (UT) is an important, well-studied phenomenon in health care and many other important domains of life, yet its conceptualization and measurement by researchers in various disciplines have varied substantially and its essential nature remains unclear. Objective The objectives of this study were to: 1) analyze the meaning and logical coherence of UT as conceptualized by developers of UT measures, and 2) develop an integrative conceptual model to guide future empirical research regarding the nature, causes, and effects of UT. Methods A narrative review and conceptual analysis of 18 existing measures of Uncertainty and Ambiguity Tolerance was conducted, focusing on how measure developers in various fields have defined both the “uncertainty” and “tolerance” components of UT—both explicitly through their writings and implicitly through the items constituting their measures. Results Both explicit and implicit conceptual definitions of uncertainty and tolerance vary substantially and are often poorly and inconsistently specified. A logically coherent, unified understanding or theoretical model of UT is lacking. To address these gaps, we propose a new integrative definition and multidimensional conceptual model that construes UT as the set of negative and positive psychological responses—cognitive, emotional, and behavioral—provoked by the conscious awareness of ignorance about particular aspects of the world . This model synthesizes insights from various disciplines and provides an organizing framework for future research. We discuss how this model can facilitate further empirical and theoretical research to better measure and understand the nature, determinants, and outcomes of UT in health care and other domains of life. Conclusion Uncertainty tolerance is an important and complex phenomenon requiring more precise and consistent definition. An integrative definition and conceptual model, intended as a tentative and flexible point of departure for future research, adds needed breadth, specificity, and precision to efforts to conceptualize and measure UT. [ABSTRACT FROM AUTHOR]

Previous research has shown that individual decision making is often characterized by inertia—that is, a tendency for decision makers to choose options that maintain the status quo. In this study, I conduct a laboratory experiment to investigate two potential determinants of inertia in uncertain environments: (i) regret aversion and (ii) ambiguity-driven indecisiveness. I use a between-subjects design with varying conditions to identify the effects of these two mechanisms on choice behavior. In each condition, participants choose between two simple real gambles, one of which is the status quo option. The findings indicate that regret aversion and ambiguity-driven indecisiveness are equally important determinants of inertia, which in turn plays a major role in individual decision making. [ABSTRACT FROM AUTHOR]

Evaluation of uncertainties due to rotational ambiguities and noise propagation is essential to ascertain the reliability of Multivariate Curve Resolution estimations. When ambiguity is present, every resolved profile can be represented by a band of feasible solutions instead of by a unique profile. In the presence of experimental noise the estimation of this band of feasible solutions is more difficult and uncertain. The aim of this work is to show how experimental noise and profiles overlapping affect the reliability of feasible solutions. For this purpose, feasible solutions of several two and three components data systems with different profiles overlapping and noise levels have been systematically investigated. Results obtained using simulated and experimental data showed that increasing noise levels and profiles overlapping in one mode (e.g. concentration profiles) make more uncertain the estimation of feasible solutions in the other mode (e.g. spectral profiles), and this uncertainty is propagated in a non-uniform and complex way. [ABSTRACT FROM AUTHOR]

We analyze the policy implications of aversion to Knightian uncertainty (ambiguity) about the possibility of tipping points. We demonstrate two channels through which uncertainty aversion affects optimal policy in the general setting. The first channel relates to the policy's effect on the probability of tipping, and the second channel to its differential impact in the pre- and post-tipping regimes. We then extend a recursive dynamic model of climate policy and tipping points to include uncertainty aversion. Numerically, aversion to Knightian uncertainty in the face of an ambiguous tipping point increases the optimal tax on carbon dioxide emissions, but only by a small amount. [ABSTRACT FROM AUTHOR]

When making decisions in everyday life, we often have to choose between uncertain outcomes. Economic studies have demonstrated that healthy people tend to prefer options with known probabilities (risk) than those with unknown probabilities (ambiguity), which is referred to as "ambiguity aversion." However, it remains unclear how patients with schizophrenia behave under ambiguity, despite growing evidence of their altered decision-making under uncertainty. In this study, combining economic tools and functional magnetic resonance imaging (fMRI), we assessed the attitudes toward risk/ambiguity and investigated the neural correlates during decision-making under risk/ambiguity in schizophrenia. Although no significant difference in attitudes under risk was observed, patients with schizophrenia chose ambiguity significantly more often than the healthy controls. Attitudes under risk and ambiguity did not correlate across patients with schizophrenia. Furthermore, unlike in the healthy controls, activation of the left lateral orbitofrontal cortex was not increased during decision-making under ambiguity compared to under risk in schizophrenia. These results suggest that ambiguity aversion, a well-established subjective bias, is attenuated in patients with schizophrenia, highlighting the need to distinguish between risk and ambiguity when assessing decision-making under these situations. Our findings, comprising important clinical implications, contribute to improved understanding of the mechanisms underlying altered decision-making in patients with schizophrenia. [ABSTRACT FROM AUTHOR]

Ambiguity in language derives, in part, from the multiple motivations that underlie the choice to use any particular expression. The use of some lexical items, such as probability expressions and scalar terms, can be motivated by a desire to communicate uncertainty as well as a desire to be polite (i.e., manage face). Research has demonstrated that the interpretation of these items can be influenced by the existence of a potential politeness motive. In general, communications about negative events, relative to positive events, result in higher likelihood estimates whenever politeness can be discerned as a potential motive. With few exceptions, however, this research has focused only on the hearer. In the present research we focused on the dyad and examined whether speakers vary their messages as a function of politeness, and the effect that this has on subsequent judgments made by a recipient. In two experiments we presented participants with situations that varied in terms of face-threat and asked them how they would communicate potentially threatening information. Both experiments included a second set of participants who read these utterances and provided judgments as to the degree of uncertainty conveyed by the utterance. In both experiments, messages in the face-threatening condition conveyed greater uncertainty than messages in the non-face-threatening condition, and the probability estimates made by the second set of participants varied as a function of conveyed uncertainty. This research demonstrates that when examining speakers and hearers together, severe events may be judged less likely (rather than more likely), because speakers tend to hedge the certainty with which they communicate the information. [ABSTRACT FROM AUTHOR]

By definition, risk taking involves uncertainty surrounding potential outcomes. However, risky decisions can vary in the amount of ambiguity about the likelihood of each outcome occurring. The current study tested the hypothesis that the amount of ambiguity in risky-decisions would moderate the relationship between risk taking and anxiety. In this study, participants completed individual difference measures and then a version of the Balloon Analogue Risk Task (BART) with either high or low ambiguity about the likelihood of a negative outcome. As hypothesized, higher levels of anxiety predicted less risk taking in the high ambiguity version of the BART, but anxiety and risk taking were unrelated to one another in the low ambiguity version. This study demonstrates that in order to understand the relationship between anxiety and risk taking, ambiguity level must be taken into account. Furthermore, this finding provides support for cognitive models of anxiety suggesting that anxious individuals interpret negative outcomes as more likely to occur than less anxious individuals. [ABSTRACT FROM AUTHOR]

Background: Although some studies reported specifically self-face processing deficits in patients with schizophrenia disorder (SZ), it remains unclear whether these deficits rather reflect a more global face processing deficit. Contradictory results are probably due to the different methodologies employed and the lack of control of other confounding factors. Moreover, no study has so far evaluated possible daily life self-face recognition difficulties in SZ. Therefore, our primary objective was to investigate self-face recognition in patients suffering from SZ compared to healthy controls (HC) using an "objective measure" (reaction time and accuracy) and a "subjective measure" (self-report of daily self-face recognition difficulties).Method: Twenty-four patients with SZ and 23 HC performed a self-face recognition task and completed a questionnaire evaluating daily difficulties in self-face recognition. Recognition task material consisted in three different faces (the own, a famous and an unknown) being morphed in steps of 20%.Results: Results showed that SZ were overall slower than HC regardless of the face identity, but less accurate only for the faces containing 60%-40% morphing. Moreover, SZ and HC reported a similar amount of daily problems with self/other face recognition. No significant correlations were found between objective and subjective measures (p > 0.05).Limitations: The small sample size and relatively mild severity of psychopathology does not allow us to generalize our results.Conclusions: These results suggest that: (1) patients with SZ are as capable of recognizing their own face as HC, although they are susceptible to ambiguity; (2) there are far less self recognition deficits in schizophrenia patients than previously postulated. [ABSTRACT FROM AUTHOR]

Background and Objectives: Intolerance of uncertainty (IU) has been linked to Generalized Anxiety Disorder (GAD), but studies experimentally manipulating uncertainty have mostly failed to find differences between GAD patients and controls, possible due to a lack of distinction between uncertainty and ambiguity. This study therefore investigated reactivity to ambiguity in addition to uncertainty in high worriers (HW) and low worriers (LW). We hypothesized an interpretation bias between the groups during ambiguity tasks, while uncertainty would facilitate threat processing of subsequent aversive stimuli.Methods: HW (N = 23) and LW (N = 23) completed a paradigm comprising the anticipation and perception of pictures with dangerous, safe, or ambiguous content. Anticipatory cues were certain (always correct information about the following picture) or uncertain (no information). Subjective ratings, reaction times and skin conductance responses (SCRs) were recorded.Results: HW rated particularly ambiguous pictures as more aversive and showed longer reaction times to all picture conditions compared to LW. SCRs were also larger in HW compared to LW, particularly during uncertain but also safe anticipation. No group differences were observed during perception of stimuli.Limitations: All participants were female. HW was used as subclinical phenotype of GAD.Conclusions: Intolerance of ambiguity seems to be related to individual differences in worry and possibly to the development of GAD. Threat-related interpretations differentiating HW and LW occurred particularly for ambiguous pictures but were not accompanied by increased autonomic arousal during the picture viewing. This disparity between subjective rating and arousal may be the result of worrying in response to intolerance of uncertainty, restraining physiological responses. [ABSTRACT FROM AUTHOR]

Intolerance of Uncertainty (IU) has gained increasing interest as a vulnerability factor for worry in Generalized Anxiety Disorder and other emotional disorders. We extended the procedure of Grupe and Nitschke (2011) to compare threat processing in High IU (n=29) and Low IU (n=26) participants. Participants viewed four cues: two reference cues that preceded aversive pictures on 100% or 0% of trials, and a target cue that preceded aversive pictures on 50% of trials (Uncertain condition). Participants were instructed about these probabilities in advance. In addition, we surprised participants with a second target cue that also preceded aversive pictures on 50% of trials but that had not been mentioned in the instructions (Ambiguous condition). Results provided preliminary evidence that High IU participants showed greater online threat expectancy, postexperimental covariation estimates and negative mood for the target cues compared to the reference cues. The results also suggest that among high IU individuals, ambiguity, rather than uncertainty per se, may be a particularly powerful trigger for biased threat appraisal and negative affect. Clinically, the results suggest that patients with high IU may benefit from interventions to help them calibrate the degree of risk in situations involving ambiguous threat. [ABSTRACT FROM AUTHOR]

The current study aims to present a parsimonious measure of five factors of distress intolerance as proposed by Zvolensky et al. (2010). Exploratory ( n = 511) and confirmatory ( n = 157) factor analytic studies of items from five established measures of distress intolerance suggest a 20-item measure representing five dimensions of distress intolerance (uncertainty, ambiguity, physical discomfort, frustration, and negative emotion). A comparison of latent factor models suggests that a bifactor model may present the best fit to the data, reflecting the identification of a general factor of distress intolerance while also recognizing the multidimensionality of the five group factors. The current findings suggest a parsimonious measure of five factors of distress intolerance, though further research may consider method and measurement biases and the convergent and discriminant validity of the subscales. [ABSTRACT FROM AUTHOR]

Although a number of theoretical studies explain empirical puzzles in finance with ambiguity aversion, it is not a given that individual ambiguity attitudes survive in markets. In fact, despite ample evidence of ambiguity aversion in individual decision making, most studies find no or only limited ambiguity aversion in experimental financial markets, even when they exclude arbitrage. We argue that ambiguity effects in markets depend on market feedback and on a sufficiently strong bias toward ambiguity among the participants. Accordingly, we find significant ambiguity effects in low-feedback call markets for assets that provoke high ambiguity aversion, but no ambiguity effects in high-feedback double auctions. [ABSTRACT FROM AUTHOR]

Cognitive models of social anxiety propose that socially anxious individuals engage in excessive self-focusing attention when entering a social situation. In the present study, speech anxiety was induced to socially anxious and control participants. Event-related potentials were recorded while participants performed a perceptual judgement task using distinct or ambiguous stimuli, before and after social feedback. Disputed feedback led to more revisions and decreased levels of confidence, especially among socially anxious individuals. Prior feedback, greater occipital P1 amplitudes in both groups for ambiguous probes indicated heightened sensory facilitation to ambiguous information, and greater anterior N1 amplitudes for ambiguous stimuli in highly anxious participants suggested anticipation of negative feedback in this group. Post-feedback, P1, N1 and LPP amplitudes were reduced overall among socially anxious individuals indicating a reduction in sensory facilitation of visual information. These results suggest excessive self-focusing among socially anxious individuals, possibly linked to anticipation of an anxiety-provoking social situation. • Uncertainty enhances P1 response to non-face stimuli in social contexts. • Anticipation of negative feedback in the socially anxious group was found. • Excessive self-focusing is associated with less attention to external stimuli. • Reduction of sensory facilitation is manifested by the P1, N1 and LPP amplitudes. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an integrative framework to evaluate ecommerce website efficiency from the user viewpoint using Data Envelopment Analysis (DEA). This framework is inspired by concepts driven from theories of information processing and cognition and considers the website efficiency as a measure of its quality and performance. When the users interact with the website interfaces to perform a task, they are involved in a cognitive effort, sustaining a cognitive cost to search, interpret and process information, and experiencing either a sense of satisfaction or dissatisfaction for that. The amount of ambiguity and uncertainty, and the search (over-)time during navigation that they perceive determine the effort size – and, as a consequence, the cognitive cost amount – they have to bear to perform their task. On the contrary, task performing and result achievement provide the users with cognitive benefits, making interaction with the website potentially attractive, satisfying, and useful. In total, 9 variables are measured, classified in a set of 3 website macro-dimensions (user experience, site navigability and structure). The framework is implemented to compare 52 ecommerce websites that sell products in the information technology and media market. A stepwise regression is performed to assess the influence of cognitive costs and benefits that mostly affect website efficiency. [Copyright &y& Elsevier]

This study mainly deals with the consequences of inadequate data coverage on the interpretation of geophysical information. The results of the joint gravity and geomagnetic survey of the Ciomadul Volcano are discussed in connection with conclusions of previously performed magneto-telluric (MT) investigations.In the first step, inversion of both the potential fields and MT data apparently suggested the existence of a shallow (i.e., <5 km) magma chamber containing residual melt, or alternatively, highly hydrothermally altered rocks. However, strong arguments exist against both of these hypotheses such as lack of strong geothermal manifestations at the surface, or the too young age of the volcano, inconsistent with the assumed advanced alteration stage. During the next step, a brief study on the limitations of the inversion approach revealed significant shortcomings generated by uneven data distribution. Based on these conclusions, the gravity inversion results were reconsidered by substituting the initially assumed single magma chamber with a hypothetical swarm of narrow volcano conduits, each with size below the Nyquist threshold of the gravity survey as determined by an observations coverage density of less than one station/km2. The new 3D density-based model was obtained by forward modelling, unveiling the structure of the shallow part of the volcanic feeder system that gradually developed and branched bottom-to-top.Given the shortcomings of the inversion due to inappropriate data coverage, it was speculated that a former solution of MT inversion might have been biased also by data scarcity. That leads to the integration of local effects (caused by narrow, but highly conductive fluid-filled conduits) into a single electrical resistivity anomaly that is improperly interpreted. [Display omitted] • New gravity and geomagnetic data for Ciomadul volcano were obtained. • New density and magnetic properties of the rocks within Ciomadul area. • Impact of data coverage on the uncertainty of their interpretation is studied. • New paradigm for interpretation of geophysical data is offered. • Gravity-based 3D structural model for shallow Ciomadul volcano plumbing system. [ABSTRACT FROM AUTHOR]

This paper investigates the consequences of voter uncertainty on voter–party ideological congruence. Building on the theory of motivated reasoning, it argues that voter feelings about political parties should determine whether they will be attracted or repelled by uncertain policy positions. The empirical analysis demonstrates the following. First, voters employ a 'likability' heuristic: they perceive more (less) ideological proximity to the party they (dis)like, regardless of the actual party position. Second, the likability effect boosts as the voter's uncertainty increases. Facing a party with a vague ideological position, voters who dislike the party exaggerate the ideological distance, whereas those who like the party underestimate this distance. These findings imply that raising voter uncertainty might help the party to the extent that it is liked, but it can backfire if the party is not popular enough. More generally, the results bear important implications for the literature on voter uncertainty and party strategies. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the different psychoanalytic lectures of “Hamlet” are confronted to new findings claiming Hamlet to be guilty of his father''s murder (Bayard, Enquête sur Hamlet, 2002). Then, Shakespeare''s masterpiece is discussed as a paradigm of paradoxality and ambiguity from which stems its unbroken fascination. Instead of determining arbitrarily if Hamlet or Claudius are the villains, a new interpretation uncloses a third possibility of who might be responsable for the king''s death: what if Hamlet''s mother Gertrude has conceived the King''s murder? Finally, the author points out the heuristic value that “Hamlet” contains both as a paradigm and an enigm, for the theory and the practice of nowadays psychoanalysis. [Copyright &y& Elsevier]

The prevailing concerns on ecological and environmental issues, occurring especially at regional to global scales, have prompted significant advances on the use of remote sensing data for the estimation of land cover information at sub-pixel level. However, the quality of such classification products, as well as the performance of the classification protocol employed, are difficult to quantify. This paper had the objectives of 1) reviewing the existing alternatives, while identifying major drawbacks and desirable properties, for sub-pixel accuracy assessment based on cross-comparison matrices, and 2) developing theoretical grounds, for a more general accuracy assessment of soft classifications, that account for the sub-pixel class distribution uncertainty. It was found that, for a sub-pixel confusion matrix to exhibit a diagonalization characteristic that allows identifying a perfect matching case, the agreement measure must be constrained at pixel level, whereas a disagreement measure can take into account the sub-pixel distribution uncertainty, leading to an underspecified problem termed the sub-pixel area allocation problem. It was demonstrated that the sub-pixel area allocation problem admits a unique solution if, and only if, no more than one class is either over- or underestimated at each pixel. In this case, the sub-pixel confusion can be uniquely determined. When no unique solution exists, the space of feasible solutions can be represented by confusion intervals. A new cross-comparison matrix that reports the confusion intervals in the form of a center value plus–minus maximum error was proposed to account for the sub-pixel distribution uncertainty. The new matrix is referred to as sub-pixel confusion–uncertainty matrix (SCM). Sub-pixel accuracy measures were also derived from this matrix. The practical use of the SCM and derived indices was demonstrated in assessing an invasive species detection method and a fuzzy classification of urban land use/land cover through remote sensing procedures. [Copyright &y& Elsevier]

Abstract: Although recent findings suggest that intolerance of uncertainty is a fundamental construct involved in excessive worry, additional research is required to further establish the construct validity of intolerance of uncertainty and demonstrate its unique contribution to the understanding of worry. The present study examined the relationships among measures of worry, intolerance of uncertainty, intolerance of ambiguity, perfectionism, and perceived control in a sample of 197 university students. The findings indicated that intolerance of uncertainty moderately overlaps with earlier conceptualizations of intolerance of ambiguity; however, worry was more highly related to intolerance of uncertainty than to intolerance of ambiguity. Intolerance of uncertainty also emerged as the most salient predictor of worry compared to other cognitive processes such as perfectionism and perceived control. Worry and intolerance of uncertainty continued to be significantly related after controlling for intolerance of ambiguity, perfectionism, and perceived control, which implies that intolerance of uncertainty shares a unique association with worry that is not accounted for by these other cognitive factors. Overall, the findings provide evidence of construct validity and underscore the role of intolerance of uncertainty in the conceptualization of worry. [Copyright &y& Elsevier]

The study focuses on teachers’ perceived certainty, a concept which is understood as being made up of didactic, practical and relational certainty, and its relationship with teacher collaboration, role ambiguity and job satisfaction. Analyses draw on data from 1153 Norwegian elementary and junior high school teachers. Results indicate that there are statistically significant differences between the two subgroups of teachers concerning collaboration and job satisfaction. Furthermore, interesting differences regarding relations between collaboration and teacher certainty are found. Teachers in this study also report most collaboration on planning lessons, but little collaboration on activities one would expect to enhance self-awareness and reflection. A structural equation model involving relationships between all variables is tested and results reveal good fit indices. [Copyright &y& Elsevier]

Previous research has shown that uncertainty constitutes a powerful stressor (e.g. Monat, Averill, & Lazarus, 1972; Zakowski, 1995), although individual differences in reactions to uncertainty have not been investigated adequately. The Uncertainty Response-Emotional factor from the Uncertainty Response Scale (URS—Greco & Roger, 2001) measures individual differences in the extent to which uncertainty is perceived as stressful. This paper addresses the relationship between uncertainty and health by means of an experiment in which physiological arousal was measured during a period of experimentally-induced uncertainty. Results showed that Uncertainty Response-Emotional predicted increases in both systolic and diastolic blood pressure during a period of anticipation prior to the occurrence of a possible threat of unknown intensity. [Copyright &y& Elsevier]

Current theories propose that our sense of curiosity is determined by the learning progress or information gain that our cognitive system expects to make. However, few studies have explicitly tried to quantify subjective information gain and link it to measures of curiosity. Here, we asked people to report their curiosity about the intrinsically engaging perceptual 'puzzles' known as Mooney images, and to report on the strength of their aha experience upon revealing the solution image (curiosity relief). We also asked our participants (279) to make a guess concerning the solution of the image, and used the distribution of these guesses to compute the crowdsourced semantic entropy (or ambiguity) of the images, as a measure of the potential for information gain. Our results confirm that curiosity and, even more so, aha experience is substantially associated with this semantic information gain measure. These findings support the expected information gain theory of curiosity and suggest that the aha experience or intrinsic reward is driven by the actual information gain. In an unannounced memory part, we also established that the often reported influence of curiosity on memory is fully mediated by the aha experience or curiosity relief. We discuss the implications of our results for the burgeoning fields of curiosity and psychoaesthetics. [ABSTRACT FROM AUTHOR]

Rotational ambiguity is a phenomenon with the potential of generating an uncertainty in the estimation of analyte concentrations in protocols based on matrix instrumental data processed by multivariate curve resolution - alternating least-squares (MCR-ALS). This is particularly relevant when the second-order advantage is to be achieved, i.e., when selected analytes are determined in unknown samples having unexpected constituents, not considered in the calibration set of samples. It is therefore imperative that analytical chemists developing second-order multivariate calibration methods using MCR-ALS acknowledge the relevance of this issue, and more importantly, have access to the required tools to size the relative impact of this potential source of uncertainty on the estimated analyte concentrations. The purpose of this tutorial is to provide a down-to-earth view of rotational ambiguity, by studying in detail a synthetic example mimicking a typical chromatographic-spectral experiment, where a set of calibration samples is joined with an unknown sample having an uncalibrated interference. After explaining the background information needed to understand the origin of the phenomenon, the available tools for the estimation of the feasible MCR-ALS solutions and the derived uncertainty on analyte predictions will be discussed. A multi-component experimental system will also be discussed, stressing the fact that rotational ambiguity uncertainties, however small, should always be estimated and reported. [Display omitted] • Rotational ambiguity is ubiquitous in multivariate curve resolution. • The phenomenon is explained in simple terms. • Simulated and experimental data are described. • The potential impact on prediction uncertainty is underlined. [ABSTRACT FROM AUTHOR]

• The mechanisms of GAD remain poorly understood. • We compared threat appraisal under ambiguity versus uncertainty in GAD. • Four cues predicted different probabilities of an aversive picture. • Ambiguity was associated with expectancy and covariation biases relative to uncertainty. • GAD participants showed enhanced negative affect for ambiguity relative to uncertainty. Generalised anxiety disorder (GAD) is one of the most common anxiety disorders, yet its mechanisms remain poorly understood. In the current study, we assessed threat processing and negative affect under conditions of uncertainty and ambiguity in a sample of treatment-seeking individuals with GAD (n = 34) and in community controls (n = 34). Participants completed a laboratory aversive learning task based on that used by Grupe and Nitschke (2011). A bias in threat expectancy was observed in GAD participants relative to controls for an ambiguous cue that had not been mentioned in the instructions. GAD participants also overestimated the number of times this ambiguous cue had been followed by an aversive outcome, relative to an instructed uncertain cue (50 %). This covariation bias was not observed in controls. GAD participants also reported significantly stronger negative affect towards the ambiguous cue than the uncertain cue, a pattern that was not observed in controls, although the group interaction did not reach significance. These results provide preliminary evidence that ambiguity – rather than uncertainty per se – may be a particularly powerful trigger for biased threat appraisal and negative affect in GAD. [ABSTRACT FROM AUTHOR]