330 resultados para optimism bias


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Self-organized Bi lines that are only 1.5 nm wide can be grown without kinks or breaks on Si(0 0 1) surfaces to lengths of up to 500 nm. Constant-current topographical images of the lines, obtained with the scanning tunneling microscope, have a striking bias dependence. Although the lines appear darker than the Si terraces at biases below ≈∣1.2∣ V, the contrast reverses at biases above ≈∣1.5∣ V. Between these two ranges the lines and terraces are of comparable brightness. It has been suggested that this bias dependence may be due to the presence of a semiconductor-like energy gap within the line. Using ab initio calculations it is demonstrated that the energy gap is too small to explain the experimentally observed bias dependence. Consequently, at this time, there is no compelling explanation for this phenomenon. An alternative explanation is proposed that arises naturally from calculations of the tunneling current, using the Tersoff–Hamann approximation, and an examination of the electronic structure of the line.

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Robust methods are useful in making reliable statistical inferences when there are small deviations from the model assumptions. The widely used method of the generalized estimating equations can be "robustified" by replacing the standardized residuals with the M-residuals. If the Pearson residuals are assumed to be unbiased from zero, parameter estimators from the robust approach are asymptotically biased when error distributions are not symmetric. We propose a distribution-free method for correcting this bias. Our extensive numerical studies show that the proposed method can reduce the bias substantially. Examples are given for illustration.

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The paper studies stochastic approximation as a technique for bias reduction. The proposed method does not require approximating the bias explicitly, nor does it rely on having independent identically distributed (i.i.d.) data. The method always removes the leading bias term, under very mild conditions, as long as auxiliary samples from distributions with given parameters are available. Expectation and variance of the bias-corrected estimate are given. Examples in sequential clinical trials (non-i.i.d. case), curved exponential models (i.i.d. case) and length-biased sampling (where the estimates are inconsistent) are used to illustrate the applications of the proposed method and its small sample properties.

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This study addresses the question whether a specific, work-related form of optimistic thinking has motivational consequences in terms of work engagement above and beyond general optimism over time. A specific form of optimistic thinking is focus on opportunities. Focus on opportunities is a future-oriented belief that describes how many plans, goals, and possibilities people expect to have in their future at work. Based on a cross-lagged panel design with a two-year time lag and data from a sample of 124 German business owners, results of structural equation modeling showed that focus on opportunities positively predicted changes in work engagement over time, even when controlling for general optimism. This finding supports propositions of social cognition and self-regulation theories that emphasize the importance of a specific form of optimism that has motivating potential by referring to future work goals and opportunities

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Based on socio-emotional selectivity and self-categorization theories, we developed and tested a model on how the interplay between employee age and opportunities for generativity and development predicts age bias and turnover intentions via intergenerational contact quality in the workplace. We hypothesized indirect effects of opportunities for generativity on outcomes through intergenerational contact quality among older workers only, whereas we expected that the indirect effects of opportunities for development are stronger for young compared with older workers. Data came from 321 employees in Belgium who responded to an online questionnaire. Results showed that age moderated the relationships of opportunities for generativity and development with intergenerational contact quality consistent with the expected patterns. Furthermore, age moderated the indirect effects of opportunities for generativity and development on age bias through intergenerational contact quality, but not on turnover intentions. Implications for future research and practical suggestions for managing intergenerational contact at work are discussed.

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BACKGROUND: There is growing evidence that regular physical activity (PA) reduces the risk of poor mental health. Less research has focused on the relationship between PA and positive wellbeing. The study aims were to assess the prospective associations between PA and optimism, in both young and mid-aged women. METHODS: 9688 young women (born 1973-1978) completed self-report surveys in 2000 (age 22 to 27), 2003, 2006, and 2009; and 11,226 mid-aged women (born 1946-1951) completed surveys in 2001 (age 50-55) 2004, 2007, and 2010, as part of the Australian Longitudinal Study on Women's Health. Generalized estimating equation models (with 3-year time lag) were used to examine the relationship between PA and optimism in both cohorts. RESULTS: In both cohorts, women reporting higher levels of PA had greater odds of reporting higher optimism over the 9-year period, (young, OR = 5.04, 95% CI: 3.85-6.59; mid-age, OR = 5.77, 95% CI: 4.76-7.00) than women who reported no PA. Odds were attenuated in adjusted models, with depression accounting for a large amount of this attenuation (young, OR = 2.00, 95% CI: 1.57-2.55; mid-age, OR = 1.64 95% CI: 1.38-1.94). CONCLUSIONS: Physical activity can promote optimism in young and mid-aged women over time, even after accounting for the negative effects of other psychosocial indicators such as depression.

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We have studied the microstructure, surface states, valence fluctuations, magnetic properties, and exchange bias effect in MnO2 nanowires. High purity α-MnO 2 rectangular nanowires were synthesized by a facile hydrothermal method with microwave-assisted procedures. The microstructure analysis indicates that the nanowires grow in the [0 0 1] direction with the (2 1 0) plane as the surface. Mn3+ and Mn2+ ions are not found in the system by X-ray photoelectron spectroscopy. The effective magnetic moment of the manganese ions fits in with the theoretical and experimental values of Mn4+ very well. The uncoupled spins in 3d3 orbitals of the Mn 4+ ions in MnO 6 octahedra on the rough surface are responsible for the net magnetic moment. Spin glass behavior is observed through magnetic measurements. Furthermore, the exchange bias effect is observed for the first time in pure α-MnO2 phase due to the coupling of the surface spin glass with the antiferromagnetic α-MnO2 matrix. These α-MnO2 nanowires, with a spin-glass-like behavior and with an exchange bias effect excited by the uncoupled surface spins, should therefore inspire further study concerning the origin, theory, and applicability of surface structure induced magnetism in nanostructures.

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Carrier phase ambiguity resolution over long baselines is challenging in BDS data processing. This is partially due to the variations of the hardware biases in BDS code signals and its dependence on elevation angles. We present an assessment of satellite-induced code bias variations in BDS triple-frequency signals and the ambiguity resolutions procedures involving both geometry-free and geometry-based models. First, since the elevation of a GEO satellite remains unchanged, we propose to model the single-differenced fractional cycle bias with widespread ground stations. Second, the effects of code bias variations induced by GEO, IGSO and MEO satellites on ambiguity resolution of extra-wide-lane, wide-lane and narrow-lane combinations are analyzed. Third, together with the IGSO and MEO code bias variations models, the effects of code bias variations on ambiguity resolution are examined using 30-day data collected over the baselines ranging from 500 to 2600 km in 2014. The results suggest that although the effect of code bias variations on the extra-wide-lane integer solution is almost ignorable due to its long wavelength, the wide-lane integer solutions are rather sensitive to the code bias variations. Wide-lane ambiguity resolution success rates are evidently improved when code bias variations are corrected. However, the improvement of narrow-lane ambiguity resolution is not obvious since it is based on geometry-based model and there is only an indirect impact on the narrow-lane ambiguity solutions.

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Previous research has shown that action tendencies to approach alcohol may be modified using computerized ApproacheAvoidance Task (AAT), and that this impacted on subsequent consumption. A recent paper in this journal (Becker, Jostman, Wiers, & Holland, 2015) failed to show significant training effects for food in three studies: Nor did it find effects on subsequent consumption. However, avoidance training to high calorie foods was tested against a control rather than Approach training. The present study used a more comparable paradigm to the alcohol studies. It randomly assigned 90 participants to ‘approach’ or ‘avoid’ chocolate images on the AAT, and then asked them to taste and rate chocolates. A significant interaction of condition and time showed that training to avoid chocolate resulted in faster avoidance responses to chocolate images, compared with training to approach it. Consistent with Becker et al.'s Study 3, no effect was found on amounts of chocolate consumed, although a newly published study in this journal (Schumacher, Kemps, & Tiggemann, 2016) did do so. The collective evidence does not as yet provide solid basis for the application of AAT training to reduction of problematic food consumption, although clinical trials have yet to be conducted.

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Background Traffic offences have been considered an important predictor of crash involvement, and have often been used as a proxy safety variable for crashes. However the association between crashes and offences has never been meta-analysed and the population effect size never established. Research is yet to determine the extent to which this relationship may be spuriously inflated through systematic measurement error, with obvious implications for researchers endeavouring to accurately identify salient factors predictive of crashes. Methodology and Principal Findings Studies yielding a correlation between crashes and traffic offences were collated and a meta-analysis of 144 effects drawn from 99 road safety studies conducted. Potential impact of factors such as age, time period, crash and offence rates, crash severity and data type, sourced from either self-report surveys or archival records, were considered and discussed. After weighting for sample size, an average correlation of r = .18 was observed over the mean time period of 3.2 years. Evidence emerged suggesting the strength of this correlation is decreasing over time. Stronger correlations between crashes and offences were generally found in studies involving younger drivers. Consistent with common method variance effects, a within country analysis found stronger effect sizes in self-reported data even controlling for crash mean. Significance The effectiveness of traffic offences as a proxy for crashes may be limited. Inclusion of elements such as independently validated crash and offence histories or accurate measures of exposure to the road would facilitate a better understanding of the factors that influence crash involvement.

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OBJECTIVE: To compare, in patients with cancer and in healthy subjects, measured resting energy expenditure (REE) from traditional indirect calorimetry to a new portable device (MedGem) and predicted REE. DESIGN: Cross-sectional clinical validation study. SETTING: Private radiation oncology centre, Brisbane, Australia. SUBJECTS: Cancer patients (n = 18) and healthy subjects (n = 17) aged 37-86 y, with body mass indices ranging from 18 to 42 kg/m(2). INTERVENTIONS: Oxygen consumption (VO(2)) and REE were measured by VMax229 (VM) and MedGem (MG) indirect calorimeters in random order after a 12-h fast and 30-min rest. REE was also calculated from the MG without adjustment for nitrogen excretion (MGN) and estimated from Harris-Benedict prediction equations. Data were analysed using the Bland and Altman approach, based on a clinically acceptable difference between methods of 5%. RESULTS: The mean bias (MGN-VM) was 10% and limits of agreement were -42 to 21% for cancer patients; mean bias -5% with limits of -45 to 35% for healthy subjects. Less than half of the cancer patients (n = 7, 46.7%) and only a third (n = 5, 33.3%) of healthy subjects had measured REE by MGN within clinically acceptable limits of VM. Predicted REE showed a mean bias (HB-VM) of -5% for cancer patients and 4% for healthy subjects, with limits of agreement of -30 to 20% and -27 to 34%, respectively. CONCLUSIONS: Limits of agreement for the MG and Harris Benedict equations compared to traditional indirect calorimetry were similar but wide, indicating poor clinical accuracy for determining the REE of individual cancer patients and healthy subjects.

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The high degree of variability and inconsistency in cash flow study usage by property professionals demands improvement in knowledge and processes. Until recently limited research was being undertaken on the use of cash flow studies in property valuations but the growing acceptance of this approach for major investment valuations has resulted in renewed interest in this topic. Studies on valuation variations identify data accuracy, model consistency and bias as major concerns. In cash flow studies there are practical problems with the input data and the consistency of the models. This study will refer to the recent literature and identify the major factors in model inconsistency and data selection. A detailed case study will be used to examine the effects of changes in structure and inputs. The key variable inputs will be identified and proposals developed to improve the selection process for these key variables. The variables will be selected with the aid of sensitivity studies and alternative ways of quantifying the key variables explained. The paper recommends, with reservations, the use of probability profiles of the variables and the incorporation of this data in simulation exercises. The use of Monte Carlo simulation is demonstrated and the factors influencing the structure of the probability distributions of the key variables are outline. This study relates to ongoing research into functional performance of commercial property within an Australian Cooperative Research Centre.

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Search engines have forever changed the way people access and discover knowledge, allowing information about almost any subject to be quickly and easily retrieved within seconds. As increasingly more material becomes available electronically the influence of search engines on our lives will continue to grow. This presents the problem of how to find what information is contained in each search engine, what bias a search engine may have, and how to select the best search engine for a particular information need. This research introduces a new method, search engine content analysis, in order to solve the above problem. Search engine content analysis is a new development of traditional information retrieval field called collection selection, which deals with general information repositories. Current research in collection selection relies on full access to the collection or estimations of the size of the collections. Also collection descriptions are often represented as term occurrence statistics. An automatic ontology learning method is developed for the search engine content analysis, which trains an ontology with world knowledge of hundreds of different subjects in a multilevel taxonomy. This ontology is then mined to find important classification rules, and these rules are used to perform an extensive analysis of the content of the largest general purpose Internet search engines in use today. Instead of representing collections as a set of terms, which commonly occurs in collection selection, they are represented as a set of subjects, leading to a more robust representation of information and a decrease of synonymy. The ontology based method was compared with ReDDE (Relevant Document Distribution Estimation method for resource selection) using the standard R-value metric, with encouraging results. ReDDE is the current state of the art collection selection method which relies on collection size estimation. The method was also used to analyse the content of the most popular search engines in use today, including Google and Yahoo. In addition several specialist search engines such as Pubmed and the U.S. Department of Agriculture were analysed. In conclusion, this research shows that the ontology based method mitigates the need for collection size estimation.