Evidence Propagation and Consensus Formation in Noisy Environments

We study the effectiveness of consensus formation in multi-agent systems where there is both belief updating based on direct evidence and also belief combination between agents. In particular, we consider the scenario in which a population of agents collaborate on the best-of-n problem where the aim is to reach a consensus about which is the best (alternatively, true) state from amongst a set of states, each with a different quality value (or level of evidence). Agents' beliefs are represented within Dempster-Shafer theory by mass functions and we investigate the macro-level properties of four well-known belief combination operators for this multi-agent consensus formation problem: Dempster's rule, Yager's rule, Dubois & Prade's operator and the averaging operator. The convergence properties of the operators are considered and simulation experiments are conducted for different evidence rates and noise levels. Results show that a combination of updating on direct evidence and belief combination between agents results in better consensus to the best state than does evidence updating alone. We also find that in this framework the operators are robust to noise. Broadly, Yager's rule is shown to be the better operator under various parameter values, i.e. convergence to the best state, robustness to noise, and scalability.Comment: 13th international conference on Scalable Uncertainty Managemen

Rational Design of Sustainable Liquid Microcapsules for Spontaneous Fragrance Encapsulation

The high volatility, water-immiscibility, and light/oxygen-sensitivity of most aroma compounds represent a challenge to their incorporation in liquid consumer products. Current encapsulation methods entail the use of petroleum-based materials, initiators, and crosslinkers as well as mixing, heating, and purification steps. Hence, more efficient and eco-friendly approaches to encapsulation must be sought. Herein, we propose a simple method by making use of a pre-formed amphiphilic polymer and employing the Hansen Solubility Parameters approach to determine which fragrances could be encapsulated by spontaneous coacervation in water. The coacervates do not precipitate as solids but they remain suspended as colloidally stable liquid microcapsules, as demonstrated by fluorescence correlation spectroscopy. The effective encapsulation of fragrance is proven through confocal Raman spectroscopy, while the structure of the capsules is investigated by means of cryo FIB/SEM, confocal laser scanning microscopy, and small-angle X-ray scattering

Information Content of DSGE Forecasts

This paper examines the question whether information is contained in forecasts from DSGE models beyond that contained in lagged values, which are extensively used in the models. Four sets of forecasts are examined. The results are encouraging for DSGE forecasts of real GDP. The results suggest that there is information in the DSGE forecasts not contained in forecasts based only on lagged values and that there is no information in the lagged-value forecasts not contained in the DSGE forecasts. The opposite is true for forecasts of the GDP deflator

Evaluation of a DSGE Model of Energy in the United Kingdom Using Stationary Data

I examine the impact of energy price shock (oil prices shock and gas prices shock) on the economic activities in the United Kingdom using a dynamic stochastic general equilibrium model with a New Keynesian Philips Curve. I decomposed the changes in output caused by all of the stationary structural shocks. I found that the fall in output during the financial crisis period is driven by domestic demand shock, energy prices shock and world demand shock. I found the energy prices shock’s contribution to fall in output is temporary. Such that, the UK can borrow against such a temporary fall. This estimated model can create additional input to the policymaker’s choice of models

Is personality a determinant of patient satisfaction with hospital care?

Objective. We investigated to what extent personality is associated with patient satisfaction with hospital care. A sizeable association with personality would render patient satisfaction invalid as an indicator of hospital care quality. Design. Overall satisfaction and satisfaction with aspects of care were regressed on the Big Five dimensions of personality, controlled for patient characteristics as possible explanatory variables of observed associations. Participants. A total of 237 recently discharged inpatients aged 18-84 years (M = 50, SD = 17 years), 57% female, who were hospitalized for an average of 8 days. Instruments. The Satisfaction with Hospital Care Questionnaire addressing 12 aspects of care ranging from admission procedures to discharge and aftercare and the Five-Factor Personality Inventory assessing a person's standing on Extraversion, Agreeableness, Conscientiousness, Emotional stability, and Autonomy. Results. Agreeableness significantly predicted patient satisfaction in about half of the scales. After controlling for shared variance with age and educational level, the unique contribution of Agreeableness shrank to a maximum of 3-5% explained variance. When one outlier was dropped from the analysis, the contribution of Agreeableness was no longer statistically significant. Conclusion. Patient satisfaction seems only marginally associated with personality, at least at the level of the broad Big Five dimension

Fatigue and radiotherapy: (B) experience in patients 9 months following treatment.

Little is known regarding the prevalence and course of fatigue in cancer patients after treatment has ended and no recurrence found. The present study examines fatigue in disease-free cancer patients after being treated with radiotherapy (n = 154). The following questions are addressed. First, how do patients describe their fatigue 9 months after radiotherapy and is this different from fatigue in a nonselective sample from the general population (n = 139)? Secondly, to what degree is fatigue in patients associated with sociodemographic, medical, physical and psychological factors? Finally, is it possible to predict which patients will suffer from fatigue 9 months after radiotherapy? Results indicated that fatigue in disease-free cancer patients did not differ significantly from fatigue in the general population. However, for 34% of the patients, fatigue following treatment was worse than anticipated, 39% listed fatigue as one of the three symptoms causing them most distress, 26% of patients worried about their fatigue and patients' overall quality of life was negatively related to fatigue (r = -0.46). Fatigue in disease-free patients was significantly associated with: gender, physical distress, pain rating, sleep quality, functional disability, psychological distress and depression, but not with medical (diagnosis, prognosis, co-morbidity) or treatment-related (target area, total radiation dose, fractionation) variables. The degree of fatigue, functional disability and pain before radiotherapy were the best predictors of fatigue at 9-month follow-up, explaining 30%, 3% and 4% of the variance respectively. These findings are in line with the associations found with fatigue during treatment as reported in the preceding paper in this issue. The significant associations between fatigue and both psychological and physical variables demonstrate the complex aetiology of this symptom in patients and point out the necessity of a multidisciplinary approach for its treatment

A reliability-based approach for influence maximization using the evidence theory

The influence maximization is the problem of finding a set of social network users, called influencers, that can trigger a large cascade of propagation. Influencers are very beneficial to make a marketing campaign goes viral through social networks for example. In this paper, we propose an influence measure that combines many influence indicators. Besides, we consider the reliability of each influence indicator and we present a distance-based process that allows to estimate the reliability of each indicator. The proposed measure is defined under the framework of the theory of belief functions. Furthermore, the reliability-based influence measure is used with an influence maximization model to select a set of users that are able to maximize the influence in the network. Finally, we present a set of experiments on a dataset collected from Twitter. These experiments show the performance of the proposed solution in detecting social influencers with good quality.Comment: 14 pages, 8 figures, DaWak 2017 conferenc