Entropy and Hausdorff Dimension in Random Growing Trees

We investigate the limiting behavior of random tree growth in preferential attachment models. The tree stems from a root, and we add vertices to the system one-by-one at random, according to a rule which depends on the degree distribution of the already existing tree. The so-called weight function, in terms of which the rule of attachment is formulated, is such that each vertex in the tree can have at most K children. We define the concept of a certain random measure mu on the leaves of the limiting tree, which captures a global property of the tree growth in a natural way. We prove that the Hausdorff and the packing dimension of this limiting measure is equal and constant with probability one. Moreover, the local dimension of mu equals the Hausdorff dimension at mu-almost every point. We give an explicit formula for the dimension, given the rule of attachment

Improving the power of hypothesis tests in sparse contingency tables

When analyzing data in contingency tables it is frequent to deal with sparse data, particularly when the sample size is small relative to the number of cells. Most analyses of this kind are interpreted in an exploratory manner and even if tests are performed, little attention is paid to statistical power. This paper proposes a method we call redundant procedure, which is based on the union–intersection principle and increases test power by focusing on specific components of the hypothesis. This method is particularly helpful when the hypothesis to be tested can be expressed as the intersections of simpler models, such that at least some of them pertain to smaller table marginals. This situation leads to working on tables that are naturally denser. One advantage of this method is its direct application to (chain) graphical models. We illustrate the proposal through simulations and suggest strategies to increase the power of tests in sparse tables. Finally, we demonstrate an application to the EU-SILC dataset

Psychological Distress in Elite Sambo and Recreational Athletes

Background: Previous studies suggest that engagement in any type of physical activity can be protective against mental health issues, whereas elite-level athletes can endure various mental health challenges. The aim of this study was to determine variations in the prevalence of psychological distress among elite sambo athletes and their recreational counterparts. Methods: A sample consisting of 245 athletes (127 males and 118 females) was chosen. Out of the total sample, 105 were elite-level athletes while 140 were recreational athletes. Participants were accessed via the Depression Anxiety Stress Scales-21 to determine their stress in various domains at a given time. Results: Data indicated that all tested differences between elite sambo athletes and recreational athletes were statistically significant; recreational athletes had a higher score on the depression scale, anxiety and stress, and a general distress score than sambo athletes. Although there are no gender differences in psychological distress in the total sample of athletes, elite sambo athletes achieve significantly lower scores in all tested variants than recreational ones. Women who engage in recreational activities have stood out as a vulnerable subsample in psychological stress. Conclusion: Future epidemiological and interventional studies should explore optimal strategies to identify mental health needs based on specific sport activity, especially in terms of gender. There is a need to place special emphasis on psychological distress in the context of combat sports

An international network to monitor the structure, composition and dynamics of Amazonian forests (RAINFOR)

The Amazon basin is likely to be increasingly affected by environmental changes: higher temperatures, changes in precipitation, CO2 fertilization and habitat fragmentation. To examine the important ecological and biogeochemical consequences of these changes, we are developing an international network, RAINFOR, which aims to monitor forest biomass and dynamics across Amazonia in a co-ordinated fashion in order to understand their relationship to soil and climate. The network will focus on sample plots established by independent researchers, some providing data extending back several decades. We will also conduct rapid transect studies of poorly monitored regions. Field expeditions analysed local soil and plant properties in the first phase (2001–2002). Initial results suggest that the network has the potential to reveal much information on the continental-scale relations between forest and environment. The network will also serve as a forum for discussion between researchers, with the aim of standardising sampling techniques and methodologies that will enable Amazonian forests to be monitored in a coherent manner in the coming decades

Observation-Based Data Driven Adaptive Control of an Electromechanical Device

The model-based approach in control engineering works well when a reliable plant model is available. However, in practice, reliable models seldom exist: instead, typical “levels” of limited reliability occur. For instance, Computed Torque Control (CTC) in robotics assumes almost perfect models. The Adaptive Inverse Dynamics Controller (AIDC) and the Slotine Li Adaptive Robot Controller (SLARC) assume absolutely correct analytical model form, and only allows imprecise knowledge regarding the actual values of the model parameters. Neglecting the effects of dynamically coupled subsystems, and allowing the action of unknown external disturbances means a higher level of corrupted model reliability. Friction-related problems are typical examples of this case. In the traditional control literature, such problems are tackled by either drastic “robust” or rather intricate “adaptive” solutions, both designed by the use of Lyapunov’s 2 nd method that is a complicated technique requiring advanced mathematical skills from the designer. As an alternative design methodology, the use of Robust Fixed Point Transformations (RFPT) was suggested, which concentrates on guaranteeing the prescribed details of tracking error relaxation via generation of iterative control signal sequences that converge on the basis of Banach’s Fixed Point Theorem . This approach is essentially based on the fresh data collected by observing the behavior of the controlled systems, rather than in the case of the traditional ones. For the first time, this technique is applied for order reduction in the adaptive control of a strongly nonlinear plant with significant model imprecisions: the control of a DC motor driven arm in dynamic interaction with a nonlinear environment is demonstrated via numerical simulations

Effect of axillary brachial plexus blockade on baroreflex-induced skin vasomotor responses: Assessing the effectiveness of sympathetic blockade

Background: The combination of laser Doppler flowmetry and non-invasive blood pressure monitoring allows the continuous observation of cutaneous vascular resistance (CVR). Continuous recording of unmodulated skin blood flow (SBF) is very sensitive to artefacts, rendering the method unreliable. In contrast, intermittent short lasting challenges of the CVR by cardiovascular autonomic reflexes may provide information about the responsiveness of the sympathetic nervous system in the skin. Methods: Eleven patients with below-wrist hand surgery (six males and five females; aged 35.2 ± 7.1 years) performed Valsalva maneuver following axillary blockade. Skin blood flow was continuously monitored on the forearm of the side axillary blockade, as well as on the contra-lateral forearm, which was used as the control. The responses were expressed as changes compared with the baseline level derived from a resting period of 30s. The maxima