Medidas e análise estatística em sinais bioelétricos sobre pontos de acupuntura

In the 20th century, the acupuncture has spread on occident as a complementary practice of heath care. This fact has motivated the international scientific community to invest in research that seek to understand why acupuncture works. In this work we compare statistically volt age fluctuation of bioelectric signals caught on the skin at an acupuncture point (IG 4) another nearby on acupuncture point. The acquisition of these signals was performed utilizing an electronic interface with a computer, which was based on an instrumentation amplifier designed with adequate specifications to this end. On the collected signals from a sample of 30 volunteers we have calculated major statistics and submitted them to pairing t-test with significance leveI a = O, 05. We have estimated to bioelectric signals the following parameters: standard deviation, asymmetry and curtose. Moreover, we have calculated the self-correlation function matched by on exponential curve we have observed that the signal decays more rapidly from a non-acupoint then from an acupoint. This fact is an indicative of the existence of information in the acupoint

Caracterização do processo de gelificação de soluções quitosana utilizando reometria e espalhamento dinâmico da luz

Gels consist of soft materials with vast use in several activities, such as in pharmaceutical industry, food science, and coatings/textile applications. In order to obtain these materials, the process of gelification, that can be physical (based on physical interactions) and/or chemical (based on covalent crosslinking), has to be carried out. In this work we used dynamic light scattering (DLS) and rheometry to monitor the covalent gelification of chitosan solutions by glutaraldehyde. Intensity correlation function (ICF) data was obtained from DLS and the exponential stretched Kohrausch-William-Watts function (KWW) was fitted to them. The parameters of the KWW equation, β, Γ and C were evaluated. These methods were effective in clarifying the process of sol-gel transition, with the emergence of non-ergodicity, and determining the range of gelation observed in about 10-20 minutes. The dependence between apparent viscosity on reaction time was used to support the discussion proposed.

Caracterização de soluções de quitosana por espalhamento dinâmico de luz

Dynamic light scattering was used to monitor relaxation processes in chitosan solutions at concentrations within the semi-dilute and concentrated regimes, Kowhlrausch-Williams-Watts (KWW) equation being successfully fitted to intensity correlation function data. The dependence of KWW equation parameters on chitosan concentration indicated that an increase in concentration from semi-dilute to concentrated regimes resulted in narrowing the distribution of relaxation rates; temperature dependence indicated the relaxation process as described as an energy activated process, whose parameters were function of the interaction between chitosan chains (enthalpy of activation) and rigidity of chitosan conformations (pre-exponential factor)

O efeito da autocorrelação no desempenho do gráfico T2 de hotelling: caso bivariado

The chart of control of Hotelling T2 has been the main statistical device used in monitoring multivariate processes. Currently the technological development of control systems and automation enabled a high rate of collection of information of the production systems in very short time intervals, causing a dependency between the results of observations. This phenomenon known as auto correlation causes in the statistical control of the multivariate processes a high rate of false alarms, prejudicing in the chart performance. This entails the violation of the assumption of independence and normality of the distribution. In this thesis we considered not only the correlation between two variables, but also the dependence between observations of the same variable, that is, auto correlation. It was studied by simulation, the bi variate case and the effect of auto correlation on the performance of the T2 chart of Hotelling.

Processo de difusão com agregação e reorganização espontânea em uma rede 2D

Difusive processes are extremely common in Nature. Many complex systems, such as microbial colonies, colloidal aggregates, difusion of fluids, and migration of populations, involve a large number of similar units that form fractal structures. A new model of difusive agregation was proposed recently by Filoche and Sapoval [68]. Based on their work, we develop a model called Difusion with Aggregation and Spontaneous Reorganization . This model consists of a set of particles with excluded volume interactions, which perform random walks on a square lattice. Initially, the lattice is occupied with a density p = N/L2 of particles occupying distinct, randomly chosen positions. One of the particles is selected at random as the active particle. This particle executes a random walk until it visits a site occupied by another particle, j. When this happens, the active particle is rejected back to its previous position (neighboring particle j), and a new active particle is selected at random from the set of N particles. Following an initial transient, the system attains a stationary regime. In this work we study the stationary regime, focusing on scaling properties of the particle distribution, as characterized by the pair correlation function ø(r). The latter is calculated by averaging over a long sequence of configurations generated in the stationary regime, using systems of size 50, 75, 100, 150, . . . , 700. The pair correlation function exhibits distinct behaviors in three diferent density ranges, which we term subcritical, critical, and supercritical. We show that in the subcritical regime, the particle distribution is characterized by a fractal dimension. We also analyze the decay of temporal correlations

Medium change monitoring using ambient seismic noise and coda wave interferometry: examples from intraplate NE Brazil and the Mid-Atlantic Ridge

This thesis presents and discusses the results of ambient seismic noise correlation for two different environments: intraplate and Mid-Atlantic Ridge. The coda wave interferometry method has also been tested for the intraplate data. Ambient noise correlation is a method that allows to retrieve the structural response between two receivers from ambient noise records, as if one of the station was a virtual source. It has been largely used in seismology to image the subsurface and to monitor structural changes associated mostly with volcanic eruptions and large earthquakes. In the intraplate study, we were able to detect localized structural changes related to a small earthquake swarm, which main event is mR 3.7, North-East of Brazil. We also showed that the 1-bit normalization and spectral whitening result on the loss of waveform details and that the phase auto-correlation, which is amplitude unbiased, seems to be more sensitive and robust for our analysis of a small earthquake swarm. The analysis of 6 months of data using cross-correlations detect clear medium changes soon after the main event while the auto-correlations detect changes essentially after 1 month. It could be explained by fluid pressure redistribution which can be initiated by hydromechanical changes and opened path ways to shallower depth levels due to later occurring earthquakes. In the Mid-Atlantic Ridge study, we investigate structural changes associated with a mb 4.9 earthquake in the region of the Saint Paul transform fault. The data have been recorded by a single broadband seismic station located at less than 200 km from the Mid-Atlantic ridge. The results of the phase auto-correlation for a 5-month period, show a strong co-seismic medium change followed by a relatively fast post-seismic recovery. This medium change is likely related to the damages caused by the earthquake’s ground shaking. The healing process (filling of the new cracks) that lasted 60 days can be decomposed in two phases, a fast recovery (70% in ~30 days) in the early post-seismic stage and a relatively slow recovery later (30% in ~30 days). In the coda wave interferometry study, we monitor temporal changes of the subsurface caused by the small intraplate earthquake swarm mentioned previously. The method was first validated with synthetics data. We were able to detect a change of 2.5% in the source position and a 15% decrease of the scatterers’ amount. Then, from the real data, we observed a rapid decorrelation of the seismic coda after the mR 3.7 seismic event. This indicates a rapid change of the subsurface in the fault’s region induced by the earthquake.

Medium change monitoring using ambient seismic noise and coda wave interferometry: examples from intraplate NE Brazil and the Mid-Atlantic Ridge

This thesis presents and discusses the results of ambient seismic noise correlation for two different environments: intraplate and Mid-Atlantic Ridge. The coda wave interferometry method has also been tested for the intraplate data. Ambient noise correlation is a method that allows to retrieve the structural response between two receivers from ambient noise records, as if one of the station was a virtual source. It has been largely used in seismology to image the subsurface and to monitor structural changes associated mostly with volcanic eruptions and large earthquakes. In the intraplate study, we were able to detect localized structural changes related to a small earthquake swarm, which main event is mR 3.7, North-East of Brazil. We also showed that the 1-bit normalization and spectral whitening result on the loss of waveform details and that the phase auto-correlation, which is amplitude unbiased, seems to be more sensitive and robust for our analysis of a small earthquake swarm. The analysis of 6 months of data using cross-correlations detect clear medium changes soon after the main event while the auto-correlations detect changes essentially after 1 month. It could be explained by fluid pressure redistribution which can be initiated by hydromechanical changes and opened path ways to shallower depth levels due to later occurring earthquakes. In the Mid-Atlantic Ridge study, we investigate structural changes associated with a mb 4.9 earthquake in the region of the Saint Paul transform fault. The data have been recorded by a single broadband seismic station located at less than 200 km from the Mid-Atlantic ridge. The results of the phase auto-correlation for a 5-month period, show a strong co-seismic medium change followed by a relatively fast post-seismic recovery. This medium change is likely related to the damages caused by the earthquake’s ground shaking. The healing process (filling of the new cracks) that lasted 60 days can be decomposed in two phases, a fast recovery (70% in ~30 days) in the early post-seismic stage and a relatively slow recovery later (30% in ~30 days). In the coda wave interferometry study, we monitor temporal changes of the subsurface caused by the small intraplate earthquake swarm mentioned previously. The method was first validated with synthetics data. We were able to detect a change of 2.5% in the source position and a 15% decrease of the scatterers’ amount. Then, from the real data, we observed a rapid decorrelation of the seismic coda after the mR 3.7 seismic event. This indicates a rapid change of the subsurface in the fault’s region induced by the earthquake.

The Pair-Bond Formation and Its Role in the Stimulation of Reproductive Function in Female Common Marmosets (Callithrix jacchus)

SILVA, H.P.A.; SOUSA, M.B.C. The pair-bond formation and its role in the stimulation of reproductive function in female common marmosets (collithrix Jacchus). International Journal of Primatology, v, 18, n.3, p.387-400, 1997.

Imagem corporal e fatores de risco em praticantes de caminhada da cidade do Natal-RN

Body image is the figure of our bodies built in our minds and the degree of dissatisfaction is often associated with risk factors identified by anthropometric measures. The purpose of this descriptive study was to evaluate the risk factors associated to morphological and functional variables associate to the perception of auto-image in middle-aged walkers of the south zone of the city of Natal. A hundred and thirty volunteers had been evaluated in four groups in function of the gender and age group. As measurement evaluations were used an auto-image perception questionnaire proposed by Stunkart of nine silhouettes numbered for both gender was applied; a weighing machine equipped with stadiometer for the body mass (kg) and stature (m) and the body mass index (kg/m2) that was calculated with base in measures of the body weight and stature and classified according to norms of the National Institute of Health (2000) as well as the systolic and diastolic blood pressure by a electronic digital device (DIGITRONIC). A metal anthropometric tape was used for the waist to hip ratio (WHR). It was used Analyses of variance (ANOVA) one-way, post hoc of Tukey and correlation of Spearman for the nonparametric data adopting the level of ρ≤ 0,05 for rejection of the null hypothesis. The body mass index indicated high factors of risk in the consisting groups. In all the groups were registered the desire to reduce their silhouettes. The body weight shows reduced when compared with the younger group in the male group of superior age group, while in the female group the inverse one occurs. The autoimage perception is associated with the classification of the waist to hip ratio in the female gender in the age group of the 50 to the 59 years and in the classification of the body mass index of all constituted groups. Significant associations had not been found for classification of the systolic and diastolic blood pressure in relation to the auto-image 41 perception. This thesis presents relation of interdisciplinarity and its contents have application in the fields of Physical Education, Medicine, Physiotherapy and Nursing

Avaliação do desempenho funcional de crianças com paralisia cerebral de acordo com níveis de comprometimento motor

Contextualization: Several studies have examined the mobility of this group of children, however little is known about the impact of motor function in activities of daily living, considering the seriousness of their neuromotor damage. Objective: Identify the functional differences of children with Cerebral Palsy with different levels of motor dysfunction and correlate these differences with the areas of mobility, self-care and social function in functional ability and caregiver´s assistance of these children. Methods: An l analytical cross-section search was developed, which were part 70 children / families aged from 4 to 7.5 years, in the Rehabilitation Center for Children. As tools were used the Pediatric Evaluation Disability Inventory (PEDI) and the Gross Motor Function Classification System (GMFCS). Data analysis was performed by ANOVA and Pearson's correlation tests. Results: The results show the functional variability of children CP in different severity levels of motor disfunction This variation was observed in the areas of mobility, self-care and social function. The results also showed a strong correlation between the domains mobility and self-care, mobility and social function. Conclusions: The variability shown by the children with CP, suggests the use of PEDI and GMFCS as this association appears to increase the understanding of how the gross motor functions are related to activities of daily living, describing the best commitments and their degree of impact on functional activities. This correlation demonstrates how mobility is crucial to evaluate the performance and guide the therapeutic practice, to develop the children´s potencial, and guide the caregiver in stimulation

Algoritmos inteligentes para auto-correção, auto-verificação e auto-validação de medidas em sensores

This work presents a set of intelligent algorithms with the purpose of correcting calibration errors in sensors and reducting the periodicity of their calibrations. Such algorithms were designed using Artificial Neural Networks due to its great capacity of learning, adaptation and function approximation. Two approaches willbe shown, the firstone uses Multilayer Perceptron Networks to approximate the many shapes of the calibration curve of a sensor which discalibrates in different time points. This approach requires the knowledge of the sensor s functioning time, but this information is not always available. To overcome this need, another approach using Recurrent Neural Networks was proposed. The Recurrent Neural Networks have a great capacity of learning the dynamics of a system to which it was trained, so they can learn the dynamics of a sensor s discalibration. Knowingthe sensor s functioning time or its discalibration dynamics, it is possible to determine how much a sensor is discalibrated and correct its measured value, providing then, a more exact measurement. The algorithms proposed in this work can be implemented in a Foundation Fieldbus industrial network environment, which has a good capacity of device programming through its function blocks, making it possible to have them applied to the measurement process

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

Comparação e mobilidade, equilíbrio corporal e desempenho muscular segundo a auto-eficácia para quedas em idosas

The aging process modifies various systems in the body, leading to changes in mobility, balance and muscle strength. This can cause a drop in the elderly, or not changing the perceived self-efficacy in preventing falls. Objective: To compare the mobility, body balance and muscle performance according to self-efficacy for falls in community-dwelling elderly. Methods: A cross-sectional comparative study with 63 older (65-80 years) community. Were evaluated for identification data and sociodemographic, cognitive screening using the Mini Mental State Examination (MMSE), effective for the fall of Falls Efficacy Scale International Brazil (FES-I-BRAZIL), Mobility through the Timed Up and Go Test , the balance Berg Balance Scale (BBS) and the Modified Clinical Test tests of Sensory Interaction on Balance (mCTSIB), tandem walk (TW) and Sit to Stand (STS) of the Balance Master® System. Finally, muscle performance by using isokinetic dynamometry. Statistical analysis was performed Student t test for comparison between groups, with p value ≤ 0.05. Results: Comparing the elderly with low-efficacy for falls with high-efficacy for falls, we found significant differences only for the variable Timed Up and Go Test (p = 0.04). With regard to data on balance tests were significant differences in the speed of oscillation firm surface eyes open modified Clinical Test of Sensory Interaction on Test of Balance (p = 0.01). Variables to isokinetic dynamometry were no significant differences in movement knee extension, as regards the variables peak torque (p = 0.04) and power (p = 0.03). Conclusion: The results suggest that, compared to older community with low-and high-efficacy for falls, we observed differences in variables related to mobility, balance and muscle function

Detecção e diagnóstico de falhas não-supervisionados baseados em estimativa de densidade recursiva e classificador fuzzy auto-evolutivo

In this work, we propose a two-stage algorithm for real-time fault detection and identification of industrial plants. Our proposal is based on the analysis of selected features using recursive density estimation and a new evolving classifier algorithm. More specifically, the proposed approach for the detection stage is based on the concept of density in the data space, which is not the same as probability density function, but is a very useful measure for abnormality/outliers detection. This density can be expressed by a Cauchy function and can be calculated recursively, which makes it memory and computational power efficient and, therefore, suitable for on-line applications. The identification/diagnosis stage is based on a self-developing (evolving) fuzzy rule-based classifier system proposed in this work, called AutoClass. An important property of AutoClass is that it can start learning from scratch". Not only do the fuzzy rules not need to be prespecified, but neither do the number of classes for AutoClass (the number may grow, with new class labels being added by the on-line learning process), in a fully unsupervised manner. In the event that an initial rule base exists, AutoClass can evolve/develop it further based on the newly arrived faulty state data. In order to validate our proposal, we present experimental results from a level control didactic process, where control and error signals are used as features for the fault detection and identification systems, but the approach is generic and the number of features can be significant due to the computationally lean methodology, since covariance or more complex calculations, as well as storage of old data, are not required. The obtained results are significantly better than the traditional approaches used for comparison

O figurino na narrativa dos filmes de Guel Arraes: O Auto da Compadecida (2000) e O Bem Amado (2010)

This research focuses on the course of Guel Arraes, moviemaker, and picks two movies for analysis: O Auto da Compadecida (2000) and O Bem Amado (2010), as well as their costumes. The focus on the costume is based on Semiology and aims to decode the meanings that stem out of the clothes. Three of the movies characters will have their costumes analyzed based on Roland Barthes’ theory, mainly considering semiology elements (language and speech), (significant and meaning) and (system and syntagma). The influence of the Armorial movement into the movie O Auto da Compadecida and the Kitsch aesthetic in O Bem Amado deserve consideration, aside from the study on costumes function within narrative, supported by Roland Barthes’ structural analysis of the narrative. We sought to highlight the balance between characters’ lines and the image of the costumes in the movies. Adding to the study on how costumes strongly accounts to narrative, we observed characteristic traits of director and scriptwriter Guel Arraes present in his works, which are the northeastern man identity, a presentation of the Northeast and popular comedy. We believe that his choices when creating and his life influences are not separate from one another. Our research was movie-appraisal centered and had a thorough investigation all over language. The main considerations are supported by the following theories: Barthes (2007), Figueirôa and Fechine (2008), Moles (2001), Stuart Hall (2005) and Mikhail Bakhtin (2013).