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An Optimal control Approach to HIV Immunology

Applied Mathematics 2015年第6期6卷 1115-1130页

作者： Edilson F. Arruda claudia M. Dias camila V. de Magalhã es Dayse H. Pastore Roberto c. A. Thomé Hyun Mo Yang Instituto Alberto Luiz coimbra de P&oacute s Gradua&ccedil ã o e Pesquisa de Engenharia Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Instituto Multidisciplinar Universidade Federal Rural do Rio de Janeiro Nova Igua&ccedil u Brazil Departamento de Matem&aacute tica Centro Federal de Educa&ccedil ã o Tecnol&oacute gica celso Suckow da Fonseca Rio de Janeiro Brazil Departamento de Matem&aacute tica Aplicada Universidade Estadual de Campinas Campinas Brazil

This paper introduces a mathematical model which describes the dynamics of the spread of HIV in the human body. This model is comprised of a system of ordinary differential equations that involve susceptible cells, infected cells, HIV, immune cells and immune active cells. The distinguishing feature in the proposed model with respect to other models in the literature is that it takes into account cells that represent two distinct mechanisms of the immune system in the defense against HIV: the non-HIV-activated cells and the HIV-activated cells. With a view at minimizing the side effects of a treatment that employs a drug combination designed to attack the HIV at various stages of its life cycle, we introduce control variables that represent the infected patient’s medication. The optimal control rule that prescribes the medication for a given time period is obtained by means of Pontryagin’s Maximum Principle.

关键词： HIV Mathematical Modelling Optimal control Pontryagin’s Maximum Principle

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Analytical Model of Landslide Risk Using GIS

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Open Journal of Geology（地质学期刊） 2012年第3期

作者： claudio F. Mahler Erika Varanda Luiz c. D. de Oliveira Department of civil Engineering cOPPE Federal University of Rio de Janeiro Transpetro S/A Rio de Janeiro centro Federal de Educação Tecnológica celso Suckow da Fonseca/UnED-Petrópolis

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引用

Health 2020年第10期12卷 1360-1370页

作者： Lucas Lima de carvalho Lucas Rodrigues claro Amanda dos Santos cabral Marcela Pereira da Silva Mello Bruna Liane Passos Lucas Marcelly Valadares Souza Simone Fonseca Lucas Alexandre Oliveira Tellles Ravini Fernandez dos Santos Vieira dos Santos Marcia Augusta Pereira dos Santos claudia Lima campos Alzuguir Maria cristina Dias da Silva Antonio Eduardo Vieira dos Santos Maria Antonieta Rubio Tyrrell Eduardo Alexander Júlio césar Fonseca Lucas Anna Nery School of Nursing Federal University of Rio de Janeiro Rio de Janeiro Brazil celso Lisboa University center Rio de Janeiro Brazil State Secretariat of Education of Rio de Janeiro Rio de Janeiro Brazil Department of Medicine in Primary Health care Faculty of Medicine Federal University of Rio de Janeiro Rio de Janeiro Brazil Department of Maternal and child Nursing Faculty of Nursing State University of Rio de Janeiro Rio de Janeiro Brazil Department of Maternal-child Nursing Faculty of Nursing Fernandez Figueira Institute of the Oswaldo Cruz Foundation State University of Rio de Janeiro Rio de Janeiro Brazil

This documentary research aimed to describe the results of an epidemiological survey that sought to determine the prevalence of Infections Related to Health care (IRHc) in newborns admitted to a Neonatal Intensive care Unit (NIcU) at the city of Rio de Janeiro. For methodology, the existing data in the original research database were used as the primary source. The method used was the case study in a quantitative approach. The data have been statistically arranged by odds ratio, which measured the possibility of IRHc development at the 102 newborns, by exposition at the risk factors. Results: IRHc prevalence with pneumonias, sepsis, navel’s infection and ocular infections predominance rises. Prematures are 4.10 more susceptible. Twelve hours after amniotic rupture there are 1.77 more chances of infections. Babies with more than 10 days of hospitalization are 4.70 more susceptible than those with 10 days. The registers examined were incipient at the IRHc’s characterization, beginning and duration, which make the IRHc’s diagnostic/notification difficult.

关键词： Neonatal Nursing cross Infection Data Interpretation Statistical

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