978 resultados para Infection dynamics


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This paper presents a novel method for the analysis of nonlinear financial and economic systems. The modeling approach integrates the classical concepts of state space representation and time series regression. The analytical and numerical scheme leads to a parameter space representation that constitutes a valid alternative to represent the dynamical behavior. The results reveal that business cycles can be clearly revealed, while the noise effects common in financial indices can elegantly be filtered out of the results.

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This paper studies the dynamical properties of a system with distributed backlash and impact phenomena. This means that it is considered a chain of masses that interact with each other solely by means of backlash and impact phenomena. It is observed the emergence of non-linear phenomena resembling those encountered in the Fermi-Pasta-Ulam problem.

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This paper reports on the analysis of tidal breathing patterns measured during noninvasive forced oscillation lung function tests in six individual groups. The three adult groups were healthy, with prediagnosed chronic obstructive pulmonary disease, and with prediagnosed kyphoscoliosis, respectively. The three children groups were healthy, with prediagnosed asthma, and with prediagnosed cystic fibrosis, respectively. The analysis is applied to the pressure–volume curves and the pseudophaseplane loop by means of the box-counting method, which gives a measure of the area within each loop. The objective was to verify if there exists a link between the area of the loops, power-law patterns, and alterations in the respiratory structure with disease. We obtained statistically significant variations between the data sets corresponding to the six groups of patients, showing also the existence of power-law patterns. Our findings support the idea that the respiratory system changes with disease in terms of airway geometry and tissue parameters, leading, in turn, to variations in the fractal dimension of the respiratory tree and its dynamics.

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OBJECTIVE : To analyze studies that evaluated the role of infections as well as indirect measures of exposure to infection in the risk of childhood leukemia, particularly acute lymphoblastic leukemia. METHODS : A search in Medline, Lilacs, and SciELO scientific publication databases initially using the descriptors “childhood leukemia” and “infection” and later searching for the words “childhood leukemia” and “maternal infection or disease” or “breastfeeding” or “daycare attendance” or “vaccination” resulted in 62 publications that met the following inclusion criteria: subject aged ≤ 15 years; specific analysis of cases diagnosed with acute lymphoblastic leukemia or total leukemia; exposure assessment of mothers’ or infants’ to infections (or proxy of infection), and risk of leukemia. RESULTS : Overall, 23 studies that assessed infections in children support the hypothesis that occurrence of infection during early childhood reduces the risk of leukemia, but there are disagreements within and between studies. The evaluation of exposure to infection by indirect measures showed evidence of reduced risk of leukemia associated mainly with daycare attendance. More than 50.0% of the 16 studies that assessed maternal exposure to infection observed increased risk of leukemia associated with episodes of influenza, pneumonia, chickenpox, herpes zoster, lower genital tract infection, skin disease, sexually transmitted diseases, Epstein-Barr virus, and Helicobacter pylori . CONCLUSIONS : Although no specific infectious agent has been identified, scientific evidence suggests that exposure to infections has some effect on childhood leukemia etiology.

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Dynamical systems theory is used as a theoretical language and tool to design a distributed control architecture for teams of mobile robots, that must transport a large object and simultaneously avoid collisions with (either static or dynamic) obstacles. Here we demonstrate in simulations and implementations in real robots that it is possible to simplify the architectures presented in previous work and to extend the approach to teams of n robots. The robots have no prior knowledge of the environment. The motion of each robot is controlled by a time series of asymptotical stable states. The attractor dynamics permits the integration of information from various sources in a graded manner. As a result, the robots show a strikingly smooth an stable team behaviour.

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Dynamical systems theory is used here as a theoretical language and tool to design a distributed control architecture for a team of two mobile robots that must transport a long object and simultaneously avoid obstacles. In this approach the level of modeling is at the level of behaviors. A “dynamics” of behavior is defined over a state space of behavioral variables (heading direction and path velocity). The environment is also modeled in these terms by representing task constraints as attractors (i.e. asymptotically stable states) or reppelers (i.e. unstable states) of behavioral dynamics. For each robot attractors and repellers are combined into a vector field that governs the behavior. The resulting dynamical systems that generate the behavior of the robots may be nonlinear. By design the systems are tuned so that the behavioral variables are always very close to one attractor. Thus the behavior of each robot is controled by a time series of asymptotically stable states. Computer simulations support the validity of our dynamic model architectures.

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We address the problem of coordinating two non-holonomic mobile robots that move in formation while transporting a long payload. A competitive dynamics is introduced that gradually controls the activation and deactivation of individual behaviors. This process introduces (asymmetrical) hysteresis during behavioral switching. As a result behavioral oscillations, due to noisy information, are eliminated. Results in indoor environments show that if parameter values are chosen within reasonable ranges then, in spite of noise in the robots communi- cation and sensors, the overall robotic system works quite well even in cluttered environments. The robots overt behavior is stable and smooth.

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OBJECTIVE This study investigated the serological status of dogs living in a visceral leishmaniasis-endemic area and its correlation with the parasitological condition of the animals.METHODS Canine humoral response was evaluated using the sera of 134 dogs by enzyme-linked immunosorbent assay and immunohistochemistry to detect parasites in the skin, lymph node, and spleen of the animals. The specific antibodies investigated were IgG, IgG1, IgG2, and IgE.RESULTS According to the parasitological, laboratory, and clinical findings, the dogs were placed into one of four groups: asymptomatic with (AP+, n = 21) or without (AP-, n = 36) Leishmania tissue parasitism and symptomatic with (SP+, n = 52) or without (SP-, n = 25) parasitism. Higher IgG and IgE levels were positively correlated with the infection condition and parasite load, but not with the clinical status. In all groups, total IgG was the predominant antibody, which occurred at the expense of IgG2 instead of IgG1. Most of the infected dogs tested positive for IgG (SP+, 98.1%; AP+, 95.2%), whereas this was not observed with IgE (SP+, 80.8%; AP+, 71.2%). The most relevant finding was the high positivity of the uninfected dogs for Leishmania-specific IgG (SP-, 60.0%; AP-, 44.4%), IgE (SP-, 44.0%; AP-, 27.8%), IgG1 (SP-, 28.0%; AP-, 22.2%), and IgG2 antibodies (SP-, 56.0%; AP-, 41.7%).CONCLUSIONS The serological status of dogs, as determined by any class or subclass of antibodies, did not accurately distinguish dogs infected with L. (L.) infantum chagasifrom uninfected animals. The inaccuracy of the serological result may impair not only the diagnosis, but also epidemiological investigations and strategies for visceral leishmaniasis control. This complex serological scenario occurring in a visceral leishmaniasis-endemic area highlights the challenges associated with canine diagnosis and points out the difficulties experienced by veterinary clinicians and coordinators of control programs.

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This paper presents a fractional calculus perspective in the study of signals captured during the movement of a mechanical manipulator carrying a liquid container. In order to study the signals an experimental setup is implemented. The system acquires data from the sensors, in real time, and, in a second phase, processes them through an analysis package. The analysis package runs off-line and handles the recorded data. The results show that the Fourier spectrum of several signals presents a fractional behavior. The experimental study provides useful information that can assist in the design of a control system and the trajectory planning to be used in reducing or eliminating the effect of vibrations.

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The goal of this study is the analysis of the dynamical properties of financial data series from 32 worldwide stock market indices during the period 2000–2009 at a daily time horizon. Stock market indices are examples of complex interacting systems for which a huge amount of data exists. The methods and algorithms that have been explored for the description of physical phenomena become an effective background in the analysis of economical data. In this perspective are applied the classical concepts of signal analysis, Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional dynamical systems.

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This paper studies the dynamics of a system composed of a collection of particles that exhibit collisions between them. Several entropy measures and different impact conditions of the particles are tested. The results reveal a Power Law evolution both of the system energy and the entropy measures, typical in systems having fractional dynamics.

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This paper presents a new predictive digital control method applied to Matrix Converters (MC) operating as Unified Power Flow Controllers (UPFC). This control method, based on the inverse dynamics model equations of the MC operating as UPFC, just needs to compute the optimal control vector once in each control cycle, in contrast to direct dynamics predictive methods that needs 27 vector calculations. The theoretical principles of the inverse dynamics power flow predictive control of the MC based UPFC with input filter are established. The proposed inverse dynamics predictive power control method is tested using Matlab/Simulink Power Systems toolbox and the obtained results show that the designed power controllers guarantees decoupled active and reactive power control, zero error tracking, fast response times and an overall good dynamic and steady-state response.

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OBJECTIVE To evaluate if temperature and humidity influenced the etiology of bloodstream infections in a hospital from 2005 to 2010.METHODS The study had a case-referent design. Individual cases of bloodstream infections caused by specific groups or pathogens were compared with several references. In the first analysis, average temperature and humidity values for the seven days preceding collection of blood cultures were compared with an overall “seven-days moving average” for the study period. The second analysis included only patients with bloodstream infections. Several logistic regression models were used to compare different pathogens and groups with respect to the immediate weather parameters, adjusting for demographics, time, and unit of admission.RESULTS Higher temperatures and humidity were related to the recovery of bacteria as a whole (versus fungi) and of gram-negative bacilli. In the multivariable models, temperature was positively associated with the recovery of gram-negative bacilli (OR = 1.14; 95%CI 1.10;1.19) or Acinetobacter baumannii (OR = 1.26; 95%CI 1.16;1.37), even after adjustment for demographic and admission data. An inverse association was identified for humidity.CONCLUSIONS The study documented the impact of temperature and humidity on the incidence and etiology of bloodstream infections. The results correspond with those from ecological studies, indicating a higher incidence of gram-negative bacilli during warm seasons. These findings should guide policies directed at preventing and controlling healthcare-associated infections.

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Thesis submitted to the Universidade Nova de Lisboa,Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Engineering

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This contribution presents novel concepts for analysis of pressure–volume curves, which offer information about the time domain dynamics of the respiratory system. The aim is to verify whether a mapping of the respiratory diseases can be obtained, allowing analysis of (dis)similarities between the dynamical pattern in the breathing in children. The groups investigated here are children, diagnosed as healthy, asthmatic, and cystic fibrosis. The pressure–volume curves have been measured by means of the noninvasive forced oscillation technique during breathing at rest. The geometrical fractal dimension is extracted from the pressure–volume curves and a power-law behavior is observed in the data. The power-law model coefficients are identified from the three sets and the results show that significant differences are present between the groups. This conclusion supports the idea that the respiratory system changes with disease in terms of airway geometry, tissue parameters, leading in turn to variations in the fractal dimension of the respiratory tree and its dynamics.