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Correlation between muscle mass, nutritional status and physical performance of elderly people
Thiago Neves,Carlos Alexandre Fett,Eduardo Ferriolli,Milene Giovana Crespilho Souza,Adilson Domingos dos Reis Filho,Marcela Bomfim Martin Lopes,Neusa Maria Carraro Martins,Waleria Christiane Rezende Fe 대한골다공증학회 2018 Osteoporosis and Sarcopenia Vol.4 No.4
Objectives: This study evaluated the relationship between the skeletal muscle mass (SMM), obtained by predictive equations, and the body composition, nutritional aspects, functionality and physical performance in elderly people. Methods: The sample consisted of adults aged 65 years or over from the cross-sectional study of the Brazilian Elderly Frailty Study Network, in Cuiaba, Mato Grosso State, Brazil. The anthropometric parameters, instrumental activities of daily living (IADL), Short Physical Performance Battery (SPPB), and handgrip strength (HGS) were evaluated. The SMM was estimated by 2 predictive anthropometric equations. Results: Both SMM equations correlated with age, anthropometric indices, SPPB, IADL, and HGS. However, only HGS and neck circumference strongly correlated in both equations, being higher in SMM II. Conclusions: It seems that both equations are sensitive to obtain the SMM, contributing to the diagnosis of sarcopenia, nutritional status, and a physical performance condition.
Intelligent control system for extractive distillation columns
Thiago Gonçalves das Neves,Wagner Brandão Ramos,Gilvan Wanderley de Farias Neto,Romildo Pereira Brito 한국화학공학회 2018 Korean Journal of Chemical Engineering Vol.35 No.4
We developed and implemented an intelligent control system to be used in an extractive distillation column that produces anhydrous ethanol using ethylene glycol as solvent. The concept of artificial neural networks (ANN) was used to predict new setpoints after disturbances, and proved to be a fast and feasible solution. The developed control system receives data from temperature, flowrate and composition measurements of the azeotrope feed, and the ANN estimates the new set-points of the controllers to maintain 99.5mol% of ethanol at the top and less than 0.1mol% at the bottom; feed composition was also estimated using an ANN. All ANN were trained to provide output data corresponding to an optimized operating condition. The results showed that the intelligent control system can predict a new operating condition for any disturbance in the column feed and presented superior performance when compared with the control system without ANN.
Heat Treatment and Lubrication Analysis Over Surface Integrity of Cold Extruded Metals
Thiago Luiz Lara Oliveira,Frederico Ozanan Neves,Thalita Cristina De Paula,Antonio Carlos Ancelotti Junior 한국정밀공학회 2020 International Journal of Precision Engineering and Vol.7 No.2
Cold forming is a process which is largely employed in industry. Thisprocess may have impacts on mechanical properties and surface integrity. This paper presents a study on Surface Integrity (SI) within the context of cold extruded billets with two different materials, steel and aluminium alloys. Different lubricant oils were used in this study, and heat treatment was employed after cold processing. Typical surface alterations such as micro-hardness and roughness were analysed, and a FEM analysis was used to predict the areas with increasing hardness. An analysis of test variance (ANOVA) was conducted, aiming to determine the influence factors of the experiments. Thus, influence factors like oil performance and extrusion load were investigated. The performance and influence of oils on cold extrusion processing for different materials were analysed. Due to the effects of lubricants on surface integrity in terms of hardness and roughness, a comparison was given with projections forsubstituting mineral oils for vegetable oils without losing functional performance.
Nicholas Rolnick,Ivo Vieira de Sousa Neto,Eduardo Fernandes da Fonseca,Rodrigo Vanerson Passos Neves,Thiago dos Santos Rosa,Dahan da Cunha Nascimento 한국운동재활학회 2022 JER Vol.18 No.2
Combining blood flow restriction (BFR) with exercise is considered a relevant, helpful method in load-compromised individuals and a viable replacement for traditional heavy-load strength training. BFR exercise may be particularly useful for those unable to withstand high mechanical stresses on joints resulting in skeletal muscle dysfunction, such as patients with chronic kidney disease (CKD). Current literature suggests that BFR training displays similar positive health benefits to exercise training alone for CKD patients, including maintenance of muscle strength, glomerular filtration rate maintenance, uremic parameters, inflammatory profile, redox status, glucose homeostasis, blood pressure adjustments, and low adverse reports. In this review of nine studies in CKD patients, we clarify the potential safety and health effects of exercise training with BFR compared to exercise training alone and recommend insights for future research and practical use. Furthermore, we introduce relevant gaps in this emerging field, providing substantial guidance, critical discussion, and valuable preliminary conclusions in this demographic of patients. However, based on the limited studies in this area, more research is necessary to determine the optimal BFR exercise programming.