Preschool children and excess weight: the impact of a low complexity intervention in public day care centers

Introduction: childhood obesity is a major public health problem, affecting children even at early ages. Objective: to assess the impact of dietary intervention and relatively simple physical activity on the nutritional state of preschoolers. Method: this was an intervention study in public daycare centers targeting children from 2 to 4 years of age, in the State of São Paulo. The sample consisted of 9 daycare centers covering 578 children, with 264 children in the intervention group (IG) and 314 in the comparison group (CG). Intervention was focused on modifications in diet and physical activity, avoiding overloading the routine of daycare centers, for duration of one year. A zBMI score > 1 (zBMI) and < 2 was considered risk of being overweight, and > 2 zBMI was considered excess weight (overweight and obese). Analysis was done by frequency calculations, comparisons of proportions by χ2, mean comparisons by t-student and calculations according to Pearson’s correlation coefficient. Results: IG showed an inverse correlation between the initial zBMI of the children and the difference with the zBMI at the end of the intervention (rP = -0.39, p <0.0001). The mean difference of zBMI of the overweight children in IG between the beginning and the end of the study period was negative (-0.46 z score), indicating weight reduction, while the children in the CG was positive (+0. 17 z score) (p = 0.0037). Conclusion: intervention in diet and physical activity in overweight preschool children in daycare centers could have a favorable impact on the evolution of their nutritional state.

Cogeneration design problem Computational complexity analysis and solution through an expert system

Purpose - The purpose of this paper is twofold: to analyze the computational complexity of the cogeneration design problem; to present an expert system to solve the proposed problem, comparing such an approach with the traditional searching methods available.Design/methodology/approach - The complexity of the cogeneration problem is analyzed through the transformation of the well-known knapsack problem. Both problems are formulated as decision problems and it is proven that the cogeneration problem is np-complete. Thus, several searching approaches, such as population heuristics and dynamic programming, could be used to solve the problem. Alternatively, a knowledge-based approach is proposed by presenting an expert system and its knowledge representation scheme.Findings - The expert system is executed considering two case-studies. First, a cogeneration plant should meet power, steam, chilled water and hot water demands. The expert system presented two different solutions based on high complexity thermodynamic cycles. In the second case-study the plant should meet just power and steam demands. The system presents three different solutions, and one of them was never considered before by our consultant expert.Originality/value - The expert system approach is not a "blind" method, i.e. it generates solutions based on actual engineering knowledge instead of the searching strategies from traditional methods. It means that the system is able to explain its choices, making available the design rationale for each solution. This is the main advantage of the expert system approach over the traditional search methods. On the other hand, the expert system quite likely does not provide an actual optimal solution. All it can provide is one or more acceptable solutions.

The effects of habitat complexity and hydraulic conditions on the establishment of benthic stream macroalgae

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An Efficient Parallel Algorithm for Multiple Sequence Similarities Calculation Using a Low Complexity Method

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Complexity and information technologies: an ethical inquiry into human autonomous action

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The relationship between macroalgal morphological complexity and hydraulic conditions in stream habitats

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Task complexity reveals expertise of table tennis players

AIM: The purpose of this study was to examine the effect of intensive practice in table-­tennis on perceptual, decision-­making and motor-­systems. Groups of elite (HL=11), intermediate (LL=6) and control (CC=11) performed tasks of different levels. METHODS: All subjects underwent to reaction-­time-­test and response-­time-­test consisting of a pointing task to targets placed at distinct distances (15 and 25-­cm) on the right and left sides. The ball speed test in forehand and backhand condition just for HL and LL group. RESULTS: In CC group reaction time was higher compared to HL (P< 0.05) group. In the response-­time-­test, there was a significant main effect of distance (P< 0.0001) and the tennis-­table expertise (P= 0.011). In the ball speed test the HL were constantly faster compared to the LL in both forehand stroke (P< 0.0001) and backhand stroke (P< 0.0001). Overall, the forehand stroke was significantly faster than the backhand stroke. CONCLUSION: We can conclude that table-­tennis-­players have shorter response-­times than non-­athletes and the tasks of reaction-­time and response-­time are incapable to distinguish the performance of well-­trained table tennis players of the intermediate player, but the ball speed test seems be able to do it.

Model complexity affects transient population dynamics following a dispersal event: A case study with pea aphids

Stage-structured population models predict transient population dynamics if the population deviates from the stable stage distribution. Ecologists’ interest in transient dynamics is growing because populations regularly deviate from the stable stage distribution, which can lead to transient dynamics that differ significantly from the stable stage dynamics. Because the structure of a population matrix (i.e., the number of life-history stages) can influence the predicted scale of the deviation, we explored the effect of matrix size on predicted transient dynamics and the resulting amplification of population size. First, we experimentally measured the transition rates between the different life-history stages and the adult fecundity and survival of the aphid, Acythosiphon pisum. Second, we used these data to parameterize models with different numbers of stages. Third, we compared model predictions with empirically measured transient population growth following the introduction of a single adult aphid. We find that the models with the largest number of life-history stages predicted the largest transient population growth rates, but in all models there was a considerable discrepancy between predicted and empirically measured transient peaks and a dramatic underestimation of final population sizes. For instance, the mean population size after 20 days was 2394 aphids compared to the highest predicted population size of 531 aphids; the predicted asymptotic growth rate (λmax) was consistent with the experiments. Possible explanations for this discrepancy are discussed. Includes 4 supplemental files.

Analyzing the Complexity and Reliability of Switch-Frequency-Reconfigurable Antennas Using Graph Models

This paper addresses the functional reliability and the complexity of reconfigurable antennas using graph models. The correlation between complexity and reliability for any given reconfigurable antenna is defined. Two methods are proposed to reduce failures and improve the reliability of reconfigurable antennas. The failures are caused by the reconfiguration technique or by the surrounding environment. These failure reduction methods proposed are tested and examples are given which verify these methods.

Complex networks analysis of language complexity

Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability. Copyright (c) EPLA, 2012

The complexity of motion in the Aristotelian Physics

The intention of this paper is to present some Aristotelian arguments regarding the motion on local terrestrial region. Because it is a highly sophisticated and complex explanation dealt with, briefly, the principles and causes that based theoretic sciences in general and in particular physics. Subdivided into eight topics this article in order to facilitate the understanding of these concepts for the reader not familiar with the Aristotelian texts. With intent to avoid an innocent view, anachronistic and linear the citations are of primary sources or commentators of Aristotle's works.

Evaluation of physiologic complexity in time series using generalized sample entropy and surrogate data analysis

Complexity in time series is an intriguing feature of living dynamical systems, with potential use for identification of system state. Although various methods have been proposed for measuring physiologic complexity, uncorrelated time series are often assigned high values of complexity, errouneously classifying them as a complex physiological signals. Here, we propose and discuss a method for complex system analysis based on generalized statistical formalism and surrogate time series. Sample entropy (SampEn) was rewritten inspired in Tsallis generalized entropy, as function of q parameter (qSampEn). qSDiff curves were calculated, which consist of differences between original and surrogate series qSampEn. We evaluated qSDiff for 125 real heart rate variability (HRV) dynamics, divided into groups of 70 healthy, 44 congestive heart failure (CHF), and 11 atrial fibrillation (AF) subjects, and for simulated series of stochastic and chaotic process. The evaluations showed that, for nonperiodic signals, qSDiff curves have a maximum point (qSDiff(max)) for q not equal 1. Values of q where the maximum point occurs and where qSDiff is zero were also evaluated. Only qSDiff(max) values were capable of distinguish HRV groups (p-values 5.10 x 10(-3); 1.11 x 10(-7), and 5.50 x 10(-7) for healthy vs. CHF, healthy vs. AF, and CHF vs. AF, respectively), consistently with the concept of physiologic complexity, and suggests a potential use for chaotic system analysis. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4758815]

COMPLEXITY MEASURE: A QUANTUM INFORMATION APPROACH

In the past decades, all of the efforts at quantifying systems complexity with a general tool has usually relied on using Shannon's classical information framework to address the disorder of the system through the Boltzmann-Gibbs-Shannon entropy, or one of its extensions. However, in recent years, there were some attempts to tackle the quantification of algorithmic complexities in quantum systems based on the Kolmogorov algorithmic complexity, obtaining some discrepant results against the classical approach. Therefore, an approach to the complexity measure is proposed here, using the quantum information formalism, taking advantage of the generality of the classical-based complexities, and being capable of expressing these systems' complexity on other framework than its algorithmic counterparts. To do so, the Shiner-Davison-Landsberg (SDL) complexity framework is considered jointly with linear entropy for the density operators representing the analyzed systems formalism along with the tangle for the entanglement measure. The proposed measure is then applied in a family of maximally entangled mixed state.

Brazilian exchange rate complexity: Financial crisis effects

With the financial market globalization, foreign investments became vital for the economies, mainly in emerging countries. In the last decades, Brazilian exchange rates appeared as a good indicator to measure either investors' confidence or risk aversion. Here, some events of global or national financial crisis are analyzed, trying to understand how they influenced the "dollar-real" rate evolution. The theoretical tool to be used is the Lopez-Mancini-Calbet (LMC) complexity measure that, applied to real exchange rate data, has shown good fitness between critical events and measured patterns. (C) 2011 Elsevier B.V. All rights reserved.