Consumer confidence indices and stock markets’ meltdowns

Consumer confidence indices (CCIs) are a closely monitored barometer of countries’ economic health and an informative forecasting tool. Using European and US data, we provide a case study of the two recent stock market meltdowns (the post-dotcom bubble correction of 2000–2002 and the 2007–2009 decline at the beginning of the financial crisis) to contribute to the discussion on their appropriateness as proxies for stock markets’ investor sentiment. Investor sentiment should positively covary with stock market movements (DeLong, Shleifer, Summers, and Waldmann 1990); however, we find that the CCI–stock market relationship is not universally positive.We also do not find support for the information effect documented in the previous literature, but identify a more subtle relationship between consumer expectations about future household finances and stock market fluctuations.

Wind resource mapping using landscape roughness and spatial interpolation methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders.

Uncertainty assessment approach for composite structures based on global sensitivity indices

The problem of uncertainty propagation in composite laminate structures is studied. An approach based on the optimal design of composite structures to achieve a target reliability level is proposed. Using the Uniform Design Method (UDM), a set of design points is generated over a design domain centred at mean values of random variables, aimed at studying the space variability. The most critical Tsai number, the structural reliability index and the sensitivities are obtained for each UDM design point, using the maximum load obtained from optimal design search. Using the UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on supervised evolutionary learning. Finally, using the developed ANN a Monte Carlo simulation procedure is implemented and the variability of the structural response based on global sensitivity analysis (GSA) is studied. The GSA is based on the first order Sobol indices and relative sensitivities. An appropriate GSA algorithm aiming to obtain Sobol indices is proposed. The most important sources of uncertainty are identified.

Complex dynamics of financial indices

This paper presents a novel method for the analysis of nonlinear financial and economic systems. The modeling approach integrates the classical concepts of state space representation and time series regression. The analytical and numerical scheme leads to a parameter space representation that constitutes a valid alternative to represent the dynamical behavior. The results reveal that business cycles can be clearly revealed, while the noise effects common in financial indices can elegantly be filtered out of the results.

Analysis of financial indices by means of the windowed Fourier transform

The goal of this study is to analyze the dynamical properties of financial data series from nineteen worldwide stock market indices (SMI) during the period 1995–2009. SMI reveal a complex behavior that can be explored since it is available a considerable volume of data. In this paper is applied the window Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional order systems.

Analysis of stock market indices through multidimensional scaling

We propose a graphical method to visualize possible time-varying correlations between fifteen stock market values. The method is useful for observing stable or emerging clusters of stock markets with similar behaviour. The graphs, originated from applying multidimensional scaling techniques (MDS), may also guide the construction of multivariate econometric models.

Paired indices for clustering evaluation correction for agreement by chance

In the present paper we focus on the performance of clustering algorithms using indices of paired agreement to measure the accordance between clusters and an a priori known structure. We specifically propose a method to correct all indices considered for agreement by chance - the adjusted indices are meant to provide a realistic measure of clustering performance. The proposed method enables the correction of virtually any index - overcoming previous limitations known in the literature - and provides very precise results. We use simulated datasets under diverse scenarios and discuss the pertinence of our proposal which is particularly relevant when poorly separated clusters are considered. Finally we compare the performance of EM and KMeans algorithms, within each of the simulated scenarios and generally conclude that EM generally yields best results.

Comparing clustering solutions: the use of adjusted paired indices

In the present paper we compare clustering solutions using indices of paired agreement. We propose a new method - IADJUST - to correct indices of paired agreement, excluding agreement by chance. This new method overcomes previous limitations known in the literature as it permits the correction of any index. We illustrate its use in external clustering validation, to measure the accordance between clusters and an a priori known structure. The adjusted indices are intended to provide a realistic measure of clustering performance that excludes agreement by chance with ground truth. We use simulated data sets, under a range of scenarios - considering diverse numbers of clusters, clusters overlaps and balances - to discuss the pertinence and the precision of our proposal. Precision is established based on comparisons with the analytical approach for correction specific indices that can be corrected in this way are used for this purpose. The pertinence of the proposed correction is discussed when making a detailed comparison between the performance of two classical clustering approaches, namely Expectation-Maximization (EM) and K-Means (KM) algorithms. Eight indices of paired agreement are studied and new corrected indices are obtained.

Two new power indices based on winning coalitions

Deegan and Packel (1979) and Holler (1982) proposed two power indices for simple games: the Deegan–Packel index and the Public Good Index. In the definition of these indices, only minimal winning coalitions are taken into account. Using similar arguments, we define two new power indices. These new indices are defined taking into account only those winning coalitions that do not contain null players. The results obtained with the different power indices are compared by means of two real-world examples taken from the political field.

Autonomic and electrocortical indices of performance monitoring and source memory discrimination in older and younger adults

Reduced capacity for executive cognitive function and for the autonomic control of cardiac responsivity are both concomitants of the aging process. These may be linked through their mutual dependence on medial prefrontal function, but the specifics ofthat linkage have not been well explored. Executive functions associated with medial prefrontal cortex involve various aspects ofperformance monitoring, whereas centrally mediated autonomic functions can be observed as heart rate variability (HRV), i.e., variability in the length of intervals between heart beats. The focus for this thesis was to examine the degree to which the capacity for phasic autonomic adjustments to heart rate relates to performance monitoring in younger and older adults, using measures of electrocortical and autonomic activity. Behavioural performance and attention allocation during two age-sensitive tasks could be predicted by various aspects of autonomic control. For young adults, greater influence of the parasympathetic system on HRV was beneficial for learning unfamiliar maze paths; for older adults, greater sympathetic influence was detrimental to these functions. Further, these relationships were primarily evoked when the task required the construction and use of internalized representations of mazes rather than passive responses to feedback. When memory for source was required, older adults made three times as many source errors as young adults. However, greater parasympathetic influence on HRV in the older group was conducive to avoiding source errors and to reduced electrocortical responses to irrelevant information. Higher sympathetic predominance, in contrast, was associated with higher rates of source error and greater electrocortical responses tq non-target information in both groups. These relations were not seen for 11 errors associated with a speeded perceptual task, irrespective of its difficulty level. Overall, autonomic modulation of cardiac activity was associated with higher levels of performance monitoring, but differentially across tasks and age groups. With respect to age, those older adults who had maintained higher levels of autonomic cardiac regulation appeared to have also maintained higher levels of executive control over task performance.

The effect of elevated muscle fluid volume on indices of muscle damage following an acute bout of eccentric exercise

The primary purpose of the current investigation was to develop an elevated muscle fluid level using a human in-vivo model. The secondary purpose was to determine if an increased muscle fluid content could alter the acute muscle damage response following a bout of eccentric exercise. Eight healthy, recreationally active males participated in a cross-over design involving two randomly assigned trials. A hydration trial (HYD) consisting of a two hour infusion of a hypotonic (0.45%) saline at a rate of 20mL/minVl .73m"^ and a control trial (CON), separated by four weeks. Following the infusion (HYD) or rest period (CON), participants completed a single leg isokinetic eccentric exercise protocol of the quadriceps, consisting of 10 sets of 10 repetitions with a one minute rest between each set. Muscle biopsies were collected prior to the exercise, immediately following and at three hours post exercise. Muscle analysis included determination of wet-dry ratios and quantification of muscle damage using toluidine blue staining and light microscopy. Blood samples were collected prior to, immediately post, three and 24 hours post exercise to determine changes in creatine kinase (CK), lactate dehydrogenase (LD), interleukin-6 (IL-6) and Creactive protein (CRP) levels. Results demonstrated an increased muscle fluid volume in the HYD condition following the infusion when compared to the CON condition. Isometric peak torque was significantly reduced following the exercise in both the HYD and CON conditions. There were no significant differences in the number of areas of muscle damage at any of the time points in either condition, with no differences between conditions. CK levels were significantly greater 24hour post exercise compared to pre, immediately and three hours post similarly in both conditions. LD in the HYD condition followed a similar trend as CK with 24 hour levels higher than pre, immediately post and three hours post and LD levels were significantly greater 24 hours post compared to pre levels in the CON condition, with no differences between conditions. A significant main effect for time was observed for CRP (p<0.05) for time, such that CRP levels increased consistently at each subsequent time point. However, CRP and IL-6 levels were not different at any of the measured time points when comparing the two conditions. Although the current investigation was able to successfully increase muscle fluid volume and an increased CK, LD and CRP were observed, no muscle damage was observed following the eccentric exercise protocol in the CON or HYD conditions. Therefore, the hypotonic infusion used in the HYD condition proved to be a viable method to acutely increase muscle fluid content in in-vivo human skeletal muscle.

The landscape of work engagement in brain injury rehabilitation /

This study examined work engagement among brain injury rehabilitation professionals with specific attention to how they engage with their work (the extent to which they experience vigor, dedication, and absorption while working) and how they engage with people (the degree to which they are welcoming towards others and demonstrate integrity, responsibility, transparency). This study also tested a theoretical model of work engagement that predicted a relationship between engagement and personal, interpersonal, and organizational capacity. Eighty-one staff employed in a hospital-based brain injury program participated in the study. A quantitative self-report survey was used to measure participants' levels of capacity and engagement and a qualitative question was included to identify initiatives that could be introduced to enhance job performance. As predicted by the model, there were statistically significant positive correlations among all three capacity variables and engagement with work and statistically significant positive correlations between ethical engagement and personal and interpersonal capacity. The results of the qualitative data analysis revealed three broad categories of recommendations for improving job performance (more learning opportunities, more resources to support professional development, and the need to build greater team cohesion). These findings provide initial support for a theoretical model that emphasizes the link between capacity and engagement, which could be used to guide theory-driven interventions aimed at improving the work environment.