909 resultados para Interval graphs


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Essential arterial hypertension is the most common risk factor for cardiovascular morbidity and mortality. Regular exercise is a well-established intervention for the prevention and treatment of hypertension. Continuous moderate-intensity exercise training (CMT) that can be sustained for 30 min or more has been traditionally recommended for hypertension prevention and treatment. On the other hand, several studies have shown that high-intensity interval training (HIT), which consists of several bouts of high-intensity exercise (~85% to 95% of HRMAX and/or VO2MAX lasting 1 to 4 min interspersed with intervals of rest or active recovery, is superior to CMT for improving cardiorespiratory fitness, endothelial function and its markers, insulin sensitivity, markers of sympathetic activity and arterial stiffness in hypertensive and normotensive at high familial risk for hypertension subjects. This compelling evidence suggesting larger beneficial effects of HIT for several factors involved in the pathophysiology of hypertension raises the hypothesis that HIT may be more effective for preventing and controlling hypertension.

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Purpose The aim of the present study was to evaluate the effects of intensity and interval of recovery on performance in the bench press exercise, and the response of salivary lactate and alpha amylase levels. Methods Ten sportsman (aged 29 ± 4 years; body mass index 26 ± 2 kg/cm2 ) were divided in two groups: G70 (performing a bench press exercise at 70 % one repetition maximum—1RM), and G90 (performing a bench press exercise at 90 %—1RM). All groups were engaged in three intervals of recovery (30, 60 and 90 s). The maximum number of repetitions (MNR) and total weight lifted were computed, and saliva samples were collected 15 min before and after different intervals of recovery. For the comparison of the performance and biochemistry parameters, ANOVA tests for repeated measurements were conducted, with a significance level set at 5 %. Results In G70, the 30 s MNR was lower than the 60 and 90 s intervals of recovery (p\0.05) and the MNR with the 60 s interval of recovery was lower than the 90 s interval of recovery (p\0.041). Similarly, in G90 with the 30 s of interval of recovery, the sets were lower than observed with the 60 and 90 s (p\0.05), and MNR with the 60 s interval of recovery was lower than the 90 s interval of recovery (p\0.05). The salivary lactate showed an increase after exercise (p\0.05) when compared with the rest period for all groups, and no effects were observed for salivary alpha amylase. Conclusions Based on this result, the sets and reps can be modified to change the recovery time. This effect is very useful to improve the performance in relationship to different fitness levels.

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The conditioned rewarding effects of novelty compete with those of cocaine for control over choice behavior using a place conditioning task. The purpose of the present study was to use multiple doses of cocaine to determine the extent of this competition and to determine whether novelty’s impact on cocaine reward was maintained over an abstinence period. In Experiment 1, rats were conditioned with cocaine (7.5, 20, or 30 mg/kg ip) to prefer one side of an unbiased place conditioning apparatus relative to the other. In a subsequent phase, all rats received alternating daily confinements to the previously cocaine paired and unpaired sides of the apparatus. During this phase, half the rats had access to a novel object on their initially unpaired side; the remaining rats did not receive objects. The ability of novelty to compete with cocaine in a drug free and cocaine challenge test was sensitive to cocaine dose. In Experiment 2, a place preference was established with 10 mg/kg cocaine and testing occurred after 1, 14, or 28 day retention intervals. Findings indicate that choice behaviors mediated by cocaine conditioning are reduced with the passing of time. Taken together, competition between cocaine and novelty conditioned rewards are sensitive to drug dose and retention interval.

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A demographic model is developed based on interbirth intervals and is applied to estimate the population growth rate of humpback whales (Megaptera novaeangliae) in the Gulf of Maine. Fecundity rates in this model are based on the probabilities of giving birth at time t after a previous birth and on the probabilities of giving birth first at age x. Maximum likelihood methods are used to estimate these probabilities using sighting data collected for individually identified whales. Female survival rates are estimated from these same sighting data using a modified Jolly–Seber method. The youngest age at first parturition is 5 yr, the estimated mean birth interval is 2.38 yr (SE = 0.10 yr), the estimated noncalf survival rate is 0.960 (SE = 0.008), and the estimated calf survival rate is 0.875 (SE = 0.047). The population growth rate (l) is estimated to be 1.065; its standard error is estimated as 0.012 using a Monte Carlo approach, which simulated sampling from a hypothetical population of whales. The simulation is also used to investigate the bias in estimating birth intervals by previous methods. The approach developed here is applicable to studies of other populations for which individual interbirth intervals can be measured.

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The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e. g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.

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Let G be a graph on n vertices with maximum degree ?. We use the Lovasz local lemma to show the following two results about colourings ? of the edges of the complete graph Kn. If for each vertex v of Kn the colouring ? assigns each colour to at most (n - 2)/(22.4?2) edges emanating from v, then there is a copy of G in Kn which is properly edge-coloured by ?. This improves on a result of Alon, Jiang, Miller, and Pritikin [Random Struct. Algorithms 23(4), 409433, 2003]. On the other hand, if ? assigns each colour to at most n/(51?2) edges of Kn, then there is a copy of G in Kn such that each edge of G receives a different colour from ?. This proves a conjecture of Frieze and Krivelevich [Electron. J. Comb. 15(1), R59, 2008]. Our proofs rely on a framework developed by Lu and Szekely [Electron. J. Comb. 14(1), R63, 2007] for applying the local lemma to random injections. In order to improve the constants in our results we use a version of the local lemma due to Bissacot, Fernandez, Procacci, and Scoppola [preprint, arXiv:0910.1824]. (c) 2011 Wiley Periodicals, Inc. Random Struct. Alg., 40, 425436, 2012

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Electrical impedance tomography (EIT) is an imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed on the object surface. The EIT reconstruction problem can be approached as a nonlinear nonconvex optimization problem in which one tries to maximize the matching between a simulated impedance problem and the observed data. This nonlinear optimization problem is often ill-posed, and not very suited to methods that evaluate derivatives of the objective function. It may be approached by simulated annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function, which involves a full simulation of the impedance problem at each iteration. A variation of SA is proposed in which the objective function is evaluated only partially, while ensuring boundaries on the behavior of the modified algorithm.

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Purpose: To compare two modalities of exercise training (i.e., Endurance Training [ET] and High-Intensity Interval Training [HIT]) on health-related parameters in obese children aged between 8 and 12 years. Methods: Thirty obese children were randomly allocated into either the ET or HIT group. The ET group performed a 30 to 60-minute continuous exercise at 80% of the peak heart rate (HR). The HIT group training performed 3 to 6 sets of 60-s sprint at 100% of the peak velocity interspersed by a 3-min active recovery period at 50% of the exercise velocity. HIT sessions last similar to 70% less than ET sessions. At baseline and after 12 weeks of intervention, aerobic fitness, body composition and metabolic parameters were assessed. Results: Both the absolute (ET: 26.0%; HIT: 19.0%) and the relative VO2 peak (ET: 13.1%; HIT: 14.6%) were significantly increased in both groups after the intervention. Additionally, the total time of exercise (ET: 19.5%; HIT: 16.4%) and the peak velocity during the maximal graded cardiorespiratory test (ET: 16.9%; HIT: 13.4%) were significantly improved across interventions. Insulinemia (ET: 29.4%; HIT: 30.5%) and HOMA-index (ET: 42.8%; HIT: 37.0%) were significantly lower for both groups at POST when compared to PRE. Body mass was significantly reduced in the HIT (2.6%), but not in the ET group (1.2%). A significant reduction in BMI was observed for both groups after the intervention (ET: 3.0%; HIT: 5.0%). The responsiveness analysis revealed a very similar pattern of the most responsive variables among groups. Conclusion: HIT and ET were equally effective in improving important health related parameters in obese youth.

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Let k and l be positive integers. With a graph G, we associate the quantity c(k,l)(G), the number of k-colourings of the edge set of G with no monochromatic matching of size l. Consider the function c(k,l) : N --> N given by c(k,l)(n) = max {c(k,l)(G): vertical bar V(G)vertical bar = n}, the maximum of c(k,l)(G) over all graphs G on n vertices. In this paper, we determine c(k,l)(n) and the corresponding extremal graphs for all large n and all fixed values of k and l.

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Background: We aimed to investigate the effect of rest interval, between successive contractions, on muscular fatigue. Methods: Eighteen subjects performed elbow flexion and extension (30 repetitions) on an isokinetic dynamometer with 80 degrees of range of motion. The flexion velocity was 120 degrees/s, while for elbow extension we used 5 different velocities (30, 75, 120, 240, 360 degrees/s), producing 5 different rest intervals (2.89, 1.28, 0.85, 0.57 and 0.54 s). Results: We observed that when the rest interval was 2.89 s there was a reduction in fatigue. On the other hand, when the rest interval was 0.54 s the fatigue was increased. Conclusions: When the resting time was lower (0.54 s) the decline of work in the flexor muscle group was higher compared with different rest interval duration.

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We prove that asymptotically (as n -> infinity) almost all graphs with n vertices and C(d)n(2-1/2d) log(1/d) n edges are universal with respect to the family of all graphs with maximum degree bounded by d. Moreover, we provide an efficient deterministic embedding algorithm for finding copies of bounded degree graphs in graphs satisfying certain pseudorandom properties. We also prove a counterpart result for random bipartite graphs, where the threshold number of edges is even smaller but the embedding is randomized.

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Background: Psychosis has various causes, including mania and schizophrenia. Since the differential diagnosis of psychosis is exclusively based on subjective assessments of oral interviews with patients, an objective quantification of the speech disturbances that characterize mania and schizophrenia is in order. In principle, such quantification could be achieved by the analysis of speech graphs. A graph represents a network with nodes connected by edges; in speech graphs, nodes correspond to words and edges correspond to semantic and grammatical relationships. Methodology/Principal Findings: To quantify speech differences related to psychosis, interviews with schizophrenics, manics and normal subjects were recorded and represented as graphs. Manics scored significantly higher than schizophrenics in ten graph measures. Psychopathological symptoms such as logorrhea, poor speech, and flight of thoughts were grasped by the analysis even when verbosity differences were discounted. Binary classifiers based on speech graph measures sorted schizophrenics from manics with up to 93.8% of sensitivity and 93.7% of specificity. In contrast, sorting based on the scores of two standard psychiatric scales (BPRS and PANSS) reached only 62.5% of sensitivity and specificity. Conclusions/Significance: The results demonstrate that alterations of the thought process manifested in the speech of psychotic patients can be objectively measured using graph-theoretical tools, developed to capture specific features of the normal and dysfunctional flow of thought, such as divergence and recurrence. The quantitative analysis of speech graphs is not redundant with standard psychometric scales but rather complementary, as it yields a very accurate sorting of schizophrenics and manics. Overall, the results point to automated psychiatric diagnosis based not on what is said, but on how it is said.

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OBJECTIVE: The purpose of this study was to evaluate the following: 1) the effects of continuous exercise training and interval exercise training on the end-tidal carbon dioxide pressure (PETCO2) response during a graded exercise test in patients with coronary artery disease; and 2) the effects of exercise training modalities on the association between PETCO2 at the ventilatory anaerobic threshold (VAT) and indicators of ventilatory efficiency and cardiorespiratory fitness in patients with coronary artery disease. METHODS: Thirty-seven patients (59.7 +/- 1.7 years) with coronary artery disease were randomly divided into two groups: continuous exercise training (n = 20) and interval exercise training (n = 17). All patients performed a graded exercise test with respiratory gas analysis before and after three months of the exercise training program to determine the VAT, respiratory compensation point (RCP) and peak oxygen consumption. RESULTS: After the interventions, both groups exhibited increased cardiorespiratory fitness. Indeed, the continuous exercise and interval exercise training groups demonstrated increases in both ventilatory efficiency and PETCO2 values at VAT, RCP, and peak of exercise. Significant associations were observed in both groups: 1) continuous exercise training (PETCO(2)VAT and cardiorespiratory fitness r = 0.49; PETCO(2)VAT and ventilatory efficiency r = -0.80) and 2) interval exercise training (PETCO(2)VAT and cardiorespiratory fitness r = 0.39; PETCO(2)VAT and ventilatory efficiency r = -0.45). CONCLUSIONS: Both exercise training modalities showed similar increases in PETCO2 levels during a graded exercise test in patients with coronary artery disease, which may be associated with an improvement in ventilatory efficiency and cardiorespiratory fitness.

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We show how to construct a topological Markov map of the interval whose invariant probability measure is the stationary law of a given stochastic chain of infinite order. In particular we characterize the maps corresponding to stochastic chains with memory of variable length. The problem treated here is the converse of the classical construction of the Gibbs formalism for Markov expanding maps of the interval.