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Institution

Universidade de Pernambuco

EducationRecife, Brazil
About: Universidade de Pernambuco is a education organization based out in Recife, Brazil. It is known for research contribution in the topics: Population & Artificial neural network. The organization has 6147 authors who have published 6948 publications receiving 73648 citations.


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Journal ArticleDOI
TL;DR: The Robustness Indicator is proposed to reveal that the major oil-exporting countries choose their partners more wisely and the trade relations are steadier, and the optimal network structure, which has the minimal total trade cost is obtained by Simulated Annealing Algorithm.

36 citations

Journal ArticleDOI
TL;DR: All cases of deaths of 10 to 49-years-old women which occurred in Recife, Pernambuco, Brazil, during 1992 and 1993 were evaluated and the main basic causes of maternal deaths identified were arterial hypertension and infections.
Abstract: Este estudo avaliou os casos de obitos de mulheres com idade de 10 a 49 anos, ocorridos em Recife, Pernambuco, nos anos 1992 e 1993, com a finalidade de identificar as causas de obitos maternos. As informacoes foram obtidas a partir de 1.013 declaracoes de obito, sendo complementadas com consultas aos prontuarios medicos, fichas de anestesia, relatorios de enfermagem, necropsias e por meio de entrevistas com os medicos que assistiram estes obitos ou com familiares das mulheres. As principais causas basicas de obito materno identificadas foram hipertensao arterial (23,8%), infeccoes (19,0%), aborto (11,9%), hemorragias (9,5%), embolia pulmonar (4,8%) e acidentes anestesicos (2,4%). Cerca de 70% das mortes maternas ocorridas em Recife neste periodo foram por causas obstetricas diretas.

36 citations

Journal ArticleDOI
TL;DR: In this article, the effect of ultrasound and osmotic dehydration pretreatments on papaya drying kinetics was investigated, and the diffusional model was used to describe the moisture transfer and the effective water diffusivity was identified in the order of 10−9 m2 s−1.
Abstract: The effect of ultrasound and osmotic dehydration pretreatments on papaya drying kinetics was investigated. The ultrasound pretreatment was carried out in an ultrasonic bath at 30 °C. The osmotic pretreatment in sucrose solution was carried out in an incubator at 34 °C and agitation of 80 rpm for 210 min. The drying process was conducted in a fixed bed dryer at 70 °C. Experimental data were fitted successfully using the Page model for dried fresh and pretreated fruits, with coefficient of determination greater than 0.9992 and average relative error lower that 14.4 %. The diffusional model was used to describe the moisture transfer, and the effective water diffusivity was identified in the order of 10−9 m2 s−1. It was found that drying rates of osmosed fruits were the lowest due to the presence of infused solutes, while the ultrasound pretreatment contributed to faster drying rates. Evaluation of the dried fruit was performed by means of total carotenoids retention. Ultrasound treatments in distilled water prior to air-drying gave rise to dried papayas with retention of carotenoids in the range 30.4–39.8 % and the ultrasonic-assisted osmotic dehydration of papayas showed carotenoids retention values up to 64.9 %, whereas the dried fruit without pretreatment showed carotenoids retention lower than 24 %.

36 citations

Journal ArticleDOI
TL;DR: Experimental results show that the proposed GSRM method can produce models that approximate the shape of an object, including its concave regions, boundaries, and holes, if any.
Abstract: In this paper, we propose a new method for surface reconstruction based on growing self-organizing maps (SOMs), called growing self-reconstruction maps (GSRMs). GSRM is an extension of growing neural gas (GNG) that includes the concept of triangular faces in the learning algorithm and additional conditions in order to include and remove connections, so that it can produce a triangular two-manifold mesh representation of a target object given an unstructured point cloud of its surface. The main modifications concern competitive Hebbian learning (CHL), the vertex insertion operation, and the edge removal mechanism. The method proposed is able to learn the geometry and topology of the surface represented in the point cloud and to generate meshes with different resolutions. Experimental results show that the proposed method can produce models that approximate the shape of an object, including its concave regions, boundaries, and holes, if any.

36 citations

Journal ArticleDOI
TL;DR: The proportion of individuals with diabetic foot treated at family health units in the city of Recife, Pernambuco State, Brazil was identified and a positive and statistically significant association with the variables alcoholism and amputation was found.
Abstract: One of the most important chronic complications of diabetes mellitus is diabetic foot. Severe progression of diabetes can lead to lower limb amputations. However, since evolution of the disease is slow, it is possible to implement prevention and control measures. The scope of the Family Health Program (in terms of the possibility of early diagnosis of diabetes mellitus and diabetic foot) favors epidemiological studies to determine the problem's magnitude. This article aimed to identify the proportion of individuals with diabetic foot treated at family health units in the city of Recife, Pernambuco State, Brazil. An epidemiological survey was conducted with a probabilistic sample of medical charts of diabetic patients (N = 1,374) enrolled in six health districts in the city, analyzing relations between socioeconomic variables, health conditions, and the occurrence of amputation. Diabetic foot was observed in 9% of the sample. There was a positive and statistically significant association with the variables alcoholism and amputation (p < 0.001). The prevalence of lower limb amputations was 25.6% among individuals with complications and 2.3% of the total sample.

36 citations


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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202314
202261
2021840
2020823
2019571
2018547