Interactions of age and leg muscle fatigue on unobstructed walking and obstacle crossing

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Monitoring muscle damage markers during a four-week downhill walking exercise program

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Kin-bias, breeding site selection and female fitness in a cannibalistic Neotropical frog

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

Eletroestimulação em pacientes portadores de doença pulmonar obstrutiva crônica

Patients with Chronic Obstructive Pulmonary Disease may have muscle dysfunction, which ultimately reduce the functional capacity. Neuromuscular electrical stimulation (NMES) is a technique that can be effective in these patients, and implies low overload to the cardiorespiratory system. The aim of this study was to investigate the effects of NMES on muscle strength and cardiorespiratory fitness in COPD patients. Five patients (2 men, 3 women) were evaluated, with a mean age of 70.40 ± 6.61 years, and underwent anamnesis, anthropometric measurements, spirometry, pulmonary function, cardiopulmonary functional capacity and muscle strength in the lower limbs. After the evaluations, the patients were enrolled in a program of electrical stimulation of the quadriceps muscles, performed 3 times per week for 5 weeks. Each session lasted for 30 minutes, being reassessed at the end of the 15 sessions. Statistically significant response is observed to gain strength in lower limb (p = 0.005), but no significant responses were observed for the distance in six minute walking test before and after the test protocol for electrical stimulation. Showing that with NMES was located just gain muscle strength without effects on functional capacity, and there are few studies that investigate these effects, so further studies are needed to investigate this relationship.

Combined active and semi-supervised learning using particle walking temporal dynamicscombined active and semi-supervised learning using particle walking temporal dynamics

Both Semi-Supervised Leaning and Active Learning are techniques used when unlabeled data is abundant, but the process of labeling them is expensive and/or time consuming. In this paper, those two machine learning techniques are combined into a single nature-inspired method. It features particles walking on a network built from the data set, using a unique random-greedy rule to select neighbors to visit. The particles, which have both competitive and cooperative behavior, are created on the network as the result of label queries. They may be created as the algorithm executes and only nodes affected by the new particles have to be updated. Therefore, it saves execution time compared to traditional active learning frameworks, in which the learning algorithm has to be executed several times. The data items to be queried are select based on information extracted from the nodes and particles temporal dynamics. Two different rules for queries are explored in this paper, one of them is based on querying by uncertainty approaches and the other is based on data and labeled nodes distribution. Each of them may perform better than the other according to some data sets peculiarities. Experimental results on some real-world data sets are provided, and the proposed method outperforms the semi-supervised learning method, from which it is derived, in all of them.

Optimizing urban traffic flow using genetic algorithm with petri net analysis as fitness function

This paper describes a new methodology adopted for urban traffic stream optimization. By using Petri net analysis as fitness function of a Genetic Algorithm, an entire urban road network is controlled in real time. With the advent of new technologies that have been published, particularly focusing on communications among vehicles and roads infrastructures, we consider that vehicles can provide their positions and their destinations to a central server so that it is able to calculate the best route for one of them. Our tests concentrate on comparisons between the proposed approach and other algorithms that are currently used for the same purpose, being possible to conclude that our algorithm optimizes traffic in a relevant manner.

Influence of Cardiorespiratory Fitness on PPARG mRNA Expression Using Monozygotic Twin Case Control

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Excess body weight and gait influence energy cost of walking in older adults

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