Influência de fatores biopsicossociais sobre a mortalidade de idosos no município de Santa Cruz/RN: um estudo prospectivo

The aging process if characterizes for a complex events network, from multidimensional nature, that encloses biological, social, psychic and functional aspects. The alteration of one or more aspects can speed up the aging process, anticipating limitations and until the death in the aged. For an adjusted confrontation of this question is necessary an interdisciplinary vision, in which the some areas of the knowledge can interact and with this to intervenes of the best possible form. Then, information derived from studies of aspects related to incidence, morbidity-mortality and transition patterns, involved in the health-illness process can more accurately identify risk groups thereby establishing links between social factors, illness, incapacity and death. Thus, this study aimed to identify, by a multidimensional vision, the risk factors of mortality in a coorth of elderly in a city in the interior of the state of Rio Grande do Norte (RN), Brazil. A prospective study carried out in Santa Cruz RN, where 310 elderly were randomly selected to form a baseline. The follow-up was 53 months. The predictive variables were divided into sociodemographic, physical health, neuropsychiatric and functional capacity. The statistical analysis carried out by bivariate analysis, survival analysis, followed by binary logistic regression and Cox regression, in the multivariate analysis, considering significant levels p < 0.05 and confidence interval (CI) of 95%. A total of 60 (19.3%) elderly died during the follow-up, where cardiovascular disease was the main cause. The survival was approximately 24.8 months. The study of general survival showed, at 12, 24, 36, and 48 months of observation, a survival rate of 97%, 54%, 31%, and 5% respectively, with a statistical difference in survival only observed for the variables of cognitive function and Basic Activities of Daily Living. In the logistic regression analysis, the risk factors identified were cognitive deficits (OR = 8.74), poor perception of health (OR = 3.89) and dependence for Basic Activities of Daily Living (OR = 3.96). In the Cox analysis, as well as dependence for Basic Activities of Daily Living (HR = 3.17), cognitive deficit (HR = 4.30) and stroke (CVA) (HR = 3.49) continued as independent risk factors for death. The risk factors found in the study can be interpreted as the primary predictors for death among elderly members of the community. Therefore, improvements in health conditions, with actions towards sustaining an autonomous life with special attention for elderly with cognitive impairment, could mean additional healthy quality of life, resulting in the reduction of premature mortality in this population

Morbimortalidade perinatal associada à infecção clamidiana: uma revisão sistemática

Universidade Federal do Rio Grande do Norte

Otimização do controle do diagrama de radiação de radares de varredura para rastreio de foguetes usando o método GAMMC para o Caso Planar (GAMMC-P)

Launching centers are designed for scientific and commercial activities with aerospace vehicles. Rockets Tracking Systems (RTS) are part of the infrastructure of these centers and they are responsible for collecting and processing the data trajectory of vehicles. Generally, Parabolic Reflector Radars (PRRs) are used in RTS. However, it is possible to use radars with antenna arrays, or Phased Arrays (PAs), so called Phased Arrays Radars (PARs). Thus, the excitation signal of each radiating element of the array can be adjusted to perform electronic control of the radiation pattern in order to improve functionality and maintenance of the system. Therefore, in the implementation and reuse projects of PARs, modeling is subject to various combinations of excitation signals, producing a complex optimization problem due to the large number of available solutions. In this case, it is possible to use offline optimization methods, such as Genetic Algorithms (GAs), to calculate the problem solutions, which are stored for online applications. Hence, the Genetic Algorithm with Maximum-Minimum Crossover (GAMMC) optimization method was used to develop the GAMMC-P algorithm that optimizes the modeling step of radiation pattern control from planar PAs. Compared with a conventional crossover GA, the GAMMC has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, the GAMMC prevents premature convergence, increases population fitness and reduces the processing time. Therefore, the GAMMC-P uses a reconfigurable algorithm with multiple objectives, different coding and genetic operator MMC. The test results show that GAMMC-P reached the proposed requirements for different operating conditions of a planar RAV.