Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of root s = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K-s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5 % for central isolated hadrons and 1-3 % for the final calorimeter jet energy scale.

Fast parallel kriging-based stepwise uncertainty reduction with application to the identification of an excursion set

Stepwise uncertainty reduction (SUR) strategies aim at constructing a sequence of points for evaluating a function  f in such a way that the residual uncertainty about a quantity of interest progressively decreases to zero. Using such strategies in the framework of Gaussian process modeling has been shown to be efficient for estimating the volume of excursion of f above a fixed threshold. However, SUR strategies remain cumbersome to use in practice because of their high computational complexity, and the fact that they deliver a single point at each iteration. In this article we introduce several multipoint sampling criteria, allowing the selection of batches of points at which f can be evaluated in parallel. Such criteria are of particular interest when f is costly to evaluate and several CPUs are simultaneously available. We also manage to drastically reduce the computational cost of these strategies through the use of closed form formulas. We illustrate their performances in various numerical experiments, including a nuclear safety test case. Basic notions about kriging, auxiliary problems, complexity calculations, R code, and data are available online as supplementary materials.

Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations

Multi-objective optimization algorithms aim at finding Pareto-optimal solutions. Recovering Pareto fronts or Pareto sets from a limited number of function evaluations are challenging problems. A popular approach in the case of expensive-to-evaluate functions is to appeal to metamodels. Kriging has been shown efficient as a base for sequential multi-objective optimization, notably through infill sampling criteria balancing exploitation and exploration such as the Expected Hypervolume Improvement. Here we consider Kriging metamodels not only for selecting new points, but as a tool for estimating the whole Pareto front and quantifying how much uncertainty remains on it at any stage of Kriging-based multi-objective optimization algorithms. Our approach relies on the Gaussian process interpretation of Kriging, and bases upon conditional simulations. Using concepts from random set theory, we propose to adapt the Vorob’ev expectation and deviation to capture the variability of the set of non-dominated points. Numerical experiments illustrate the potential of the proposed workflow, and it is shown on examples how Gaussian process simulations and the estimated Vorob’ev deviation can be used to monitor the ability of Kriging-based multi-objective optimization algorithms to accurately learn the Pareto front.

Networks of Information Exchange Under Uncertainty: The Case of Unconventional Gas Development in the United Kingdom

Modern policy-making is increasingly influenced by different types of uncertainty. Political actors are supposed to behave differently under the context of uncertainty then in “usual” decision-making processes. Actors exchange information in order to convince other actors and decision-makers, to coordinate their lobbying activities and form coalitions, and to get information and learn on the substantive issue. The literature suggests that preference similarity, social trust, perceived power and functional interdependence are particularly important drivers of information exchange. We assume that social trust as well as being connected to scientific actors is more important under uncertainty than in a setting with less uncertainty. To investigate information exchange under uncertainty analyze the case of unconventional shale gas development in the UK from 2008 till 2014. Our study will rely on statistical analyses of survey data on a diverse set of actors dealing with shale gas development and regulation in the UK.

Policy Instrument Selection under Uncertainty: The Case of Micropollution Regulation

The paper addresses the question of which factors drive the formation of policy preferences when there are remaining uncertainties about the causes and effects of the problem at stake. To answer this question we examine policy preferences reducing aquatic micropollutants, a specific case of water protection policy and different actor groups (e.g. state, science, target groups). Here, we contrast two types of policy preferences: a) preventive or source-directed policies, which mitigate pollution in order to avoid contact with water; and b) reactive or end-of-pipe policies, which filter water already contaminated by pollutants. In a second step, we analyze the drivers for actors’ policy preferences by focusing on three sets of explanations, i.e. participation, affectedness and international collaborations. The analysis of our survey data, qualitative interviews and regression analysis of the Swiss political elite show that participation in the policy-making process leads to knowledge exchange and reduces uncertainties about the policy problem, which promotes preferences for preventive policies. Likewise, actors who are affected by the consequences of micropollutants, such as consumer or environmental associations, opt for anticipatory policies. Interestingly, we find that uncertainties about the effectiveness of preventive policies can promote preferences for end-of-pipe policies. While preventive measures often rely on (uncertain) behavioral changes of target groups, reactive policies are more reliable when it comes to fulfilling defined policy goals. Finally, we find that in a transboundary water management context, actors with international collaborations prefer policies that produce immediate and reliable outcomes.

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

Synchronous and Time-Lagged Effects between Occupational Self-Efficacy and Objective and Subjective Career Success: Findings from a Four-Wave and 9-Year Longitudinal Study

We integrated research on the dimensionality of career success into social-cognitive career theory and explored the positive feedback loop between occupational self-efficacy and objective and subjective career success over time (self-efficacy → objective success → subjective success → self-efficacy). Furthermore, we theoretically accounted for synchronous and time-lagged effects, as well as indirect reciprocity between the variables. We tested the proposed model by means of longitudinal structural equation modeling in a 9-year four-wave panel design, by applying a model comparison approach and indirect effect analyses (N = 608 professionals). The findings supported the proposed positive feedback loop between occupational self-efficacy and career success. Supporting our time-based reasoning, the findings showed that unfolding effects between occupational self-efficacy and objective career success take more time (i.e., time-lagged or over time) than unfolding effects between objective and subjective career success, as well as between subjective career success and occupational self-efficacy (i.e., synchronous or concurrently). Indirect effects of past on future occupational self-efficacy via objective and subjective career success were significant, providing support for an indirect reciprocity model. Results are discussed with respect to extensions of social-cognitive career theory and occupational self-efficacy development over time.

Fostering networking behavior, career planning and optimism, and subjective career success: An intervention study

The present study evaluated personal resource-oriented interventions supporting the career development of young academics, working at German universities within the STEM fields. The study sought to foster subjective career success by improving networking behavior, career planning, and career optimism. The study involved a quasi-experimental pre-post intervention with two intervention and two control groups (N = 81 research associates). Participants of the first intervention group received networking training; participants of the second intervention group received the same networking training plus individual career coaching. Participants of both intervention groups were female. Participants of the control groups (i.e., male vs. female group) did not participate in any intervention. As expected, path analyses, based on mean differences frompre-test to post-test, revealed an increase in career planning and career optimism within the networking plus career coaching intervention group, that was indirectly positively related to changes in subjective career success. Contrary to our expectations, the networking group training alone and in combination with the career coaching showed no effectiveness in fostering networking behavior. Results are discussed in the context of career counseling and intervention effectiveness studies.

Gender, Professional Networks, and Subjective Career Success within Early Academic Science Careers: The Role of Gender Composition in Inside and Outside Departmental Support Networks

The present study analyzed (a) gender differences in the gender composition (i.e., the proportion of male to female contacts) of professional support networks inside and outside an individual’s academic department and (b) how these differences in gender composition relate to subjective career success (i.e., perceived career success and perceived external marketability). Results showed that the networks’ gender composition is associated with subjective career success. Men’s networks consist of a higher proportion of male to female supporters, which, in turn, was positively related to subjective career success. Additional analyses revealed that the findings could not be accounted for by alternative factors, such as network size, networking behaviors, and career ambition.

Protean and boundaryless career attitudes: relationships with subjective and objective career success

The protean and boundaryless career attitudes have gained special attention during the past years. Aprotean career attitude implies that aperson strives towards adevelopmental progression and self-fulfillment; aboundaryless career attitude is characterized by ahigh physical and/or psychological mobility. The aim of the present paper is twofold: First, we want to empirically investigate the relationship between protean and boundaryless career attitudes and subjective (i.e., career satisfaction and success in comparison with colleagues) and objective (i.e., promotions and salary) career success. Second, we want to integrate research on protean and boundaryless career attitudes with research on predictors of career success. We analyze the career attitudes-career success relationship with asample of 116 professionals. Our findings suggest that components of the protean career attitude are rather more related with subjective career success and that components of the boundaryless career attitude are more related with objective career success. Conclusions regarding the relevance of career attitudes for career success are drawn.

How do objective and subjective career success interrelate over time?

The present research is concerned with the direction of influence between objective and subjective career success. We conducted a prospective longitudinal study with five waves of measurement that covered a time span of 10 years. Participants were professionals working in different occupational fields (N=1,336). We modelled the changes in objective success (income, hierarchical position), in other-referent subjective success (subjective success as compared to a reference group), and in self-referent subjective success (job satisfaction) by means of latent growth curve analysis. Objective success influenced both the initial level and the growth of other-referent subjective success, but it had no influence on job satisfaction. Most importantly, both measures of subjective success and both their initial levels and their changes had strong influences on the growth of objective success. We conclude that the ‘objective success influences subjective success’ relationship is smaller than might be expected, whereas the ‘subjective success influences objective success’ relationship is larger than might be expected.

The longitudinal impact of self-efficacy and career goals on objective and subjective career success

The present research reports on the impact of occupational self-efficacy and of career-advancement goals on objective (salary, status) and subjective (career satisfaction) career attainments. Seven hundred and thirty four highly educated and full-time employed professionals answered questionnaires immediately after graduation, three years later, and seven years later. Controlling for discipline, GPA at master’s level, and gender, we found that occupational self-efficacy measured at career entry had a positive impact on salary and status three years later and a positive impact on salary change and career satisfaction seven years later. Career-advancement goals at career entry had a positive impact on salary and status after three years and a positive impact on status change after seven years, but a negative impact on career satisfaction after seven years. Women earned less than men, but did not differ from men in hierarchical status and in career satisfaction. Theoretical implications for socio-cognitive theorizing and for career-success research as well as applied implications for vocational behavior are discussed.

Coaches` subjective talent criteria in top-level soccer

Introduction: In professional soccer, talent selection relies on the subjective judgment of scouts and coaches. To date, little is known about coaches´ “eye for talent” (Christensen, 2009, p. 379) and the nature of the subjective criteria they use to identify those players with the greatest potential to achieve peak performance in adulthood (Williams & Reilly, 2000). Drawing on a constructivist approach (Kelly, 1991), this study explores coaches´ subjective talent criteria. It is assumed that coaches are able to verbalise and specify their talent criteria, and that these are related to their talent selection decisions based on instinct. Methods: Participants and generation of data. Five national youth soccer coaches (Mage = 55.6; SD = 5.03) were investigated at three appointments: (1) talent selection decision based on instinct, (2) semi-structured inductive interview to elicit each coaches´ talent criteria in detail, (3) communicative validation and evaluation of the players by each coach using the repertory grid technique (Fromm, 2004). Data Analysis: Interviews were transcribed and summarized with regard to each specified talent criterion. Each talent criterion was categorized using a bottom-up-approach (meaning categorization, Kvale, 1996). The repertory grid data was analysed using descriptive statistics and correlation analysis. Results and Discussion: For each coach, six to nine talent criteria were elicited and specified. The subjective talent criteria include aspects of personality, cognitive perceptual skills, motor abilities, development, technique, social environment and physical constitution, which shows that the coaches use a multi-dimensional concept of talent. However, more than half of all criteria describe personality characteristics, in particular achievement motivation, volition and self-confidence. In contrast to Morris (2000), this result shows that coaches have a differentiated view of the personality characteristics required to achieve peak performance. As an indication of criterion validity, moderate to high correlations (.57 ≤ r ≤ .81) are found between the evaluations of the players according to the coaches´ talent criteria and their talent selection decision. The study shows that coaches are able to specify their subject talent criteria and that those criteria are strongly related to their instinctive selection decisions. References: Christensen, M. K. (2009). "An Eye for Talent": Talent Identification and the "Practical Sense" of Top-Level Soccer Coaches. Sociology of Sport Journal, 26, 365–382. Fromm, M. (2004). Introduction to the Repertory Grid Interview. Münster: Waxmann. Kelly, G. A. (1991). The Psychology of Personal Constructs: Volume One: Theory and personality. London: Routledge. Kvale, S. (1996). InterViews: An introduction to Qualitative Research Interviewing. Thousand Oaks: Sage. Morris, T. (2000). Psychological characteristics and talent identification in soccer. Journal of Sports Sciences, 18, 715–726. Williams, A. M., & Reilly, T. (2000). Talent identification and development in soccer. Journal of Sports Sciences, 18, 657–667.

Subjective perception of sleepiness in a driving simulator is different from that in the Maintenance of Wakefulness Test.

OBJECTIVE To test whether sleep-deprived, healthy subjects who do not always signal spontaneously perceived sleepiness (SPS) before falling asleep during the Maintenance of Wakefulness Test (MWT) would do so in a driving simulator. METHODS Twenty-four healthy subjects (20-26 years old) underwent a MWT for 40 min and a driving simulator test for 1 h, before and after one night of sleep deprivation. Standard electroencephalography, electrooculography, submental electromyography, and face videography were recorded simultaneously to score wakefulness and sleep. Subjects were instructed to signal SPS as soon as they subjectively felt sleepy and to try to stay awake for as long as possible in every test. They were rewarded for both "appropriate" perception of SPS and staying awake for as long as possible. RESULTS After sleep deprivation, seven subjects (29%) did not signal SPS before falling asleep in the MWT, but all subjects signalled SPS before falling asleep in the driving simulator (p <0.004). CONCLUSIONS The previous results of an "inaccurate" SPS in the MWT were confirmed, and a perfect SPS was shown in the driving simulator. It was hypothesised that SPS is more accurate for tasks involving continuous feedback of performance, such as driving, compared to the less active situation of the MWT. Spontaneously perceived sleepiness in the MWT cannot be used to judge sleepiness perception while driving. Further studies are needed to define the accuracy of SPS in working tasks or occupations with minimal or no performance feedback.