Strain and slackness of achilles tendon during passive joint mobilization via imaging ultrasonography

Background: In vivo study of the mechanical behavior of tendons may bring advances in evaluating the impact of intervention programs for flexibility and strength, in clinical practice and sports. Objective: The aim of this study was to quantify the relative strain and slackness of achilles tendons during passive mobilization, for four ankle joint angles and two knee angles. Methods: The displacement of the muscle-tendon junction was quantified by means of ultrasound images acquired during passive ankle mobilization, with the aid of an electrogoniometer and an electromyograph to ensure the achievement of the required angles and muscle inactivity, respectively. Results: The strain values ranged from 4.28%±2.37 to -0.94%±1.58 for the fully extended knee, and from 2.38%±1.63 to -2.32%±2.16% for the flexed knee. Conclusions: The values found in this study confirm those in the literature and demonstrate how the Achilles tendon participates in length changes in the muscle-tendon unit during passive movement. These results suggest that the mechanical properties of tendinous tissues affect the relationship between the length of muscle fibers and the joint angle, even during this type of movement

Assessment of a low-cost solar water heating systems in farrowing facilities

ArticleThe objective of this study was to develop a prototype solar heater using alternative materials and then to compare its thermal efficiency against that of two other commercial solar heating systems when heating the floor of piglet housing. To evaluate the thermal heaters, temperature sensors were installed in the inlet and outlet of each floor and the thermal reservoir. The results showed good performance, however the thermal efficiency of the alternative heater was lower than the conventional systems. However, due to the construction of this solar collector with alternative materials its cost was relatively low and its operation is easier than the other conventional heater, therefore this heater is a good alternative to use for small livestock producer

A new staggered algorithm for thermomechanical coupled problems

This study presents a new staggered coupled strategy to deal with thermomechanical problems. The proposed strategy is based on the isothermal split methodology, i.e. the mechanical problem is solved at constant temperature and the thermal problem is solved for a fixed configuration. Nevertheless, the procedure for this strategy is divided into two phases within each increment: the prediction and the correction phases, while the interchange of information is performed on both. This allows taking advantage of automatic time-step control techniques, previously implemented for the mechanical problem, which is the main feature that distinguishes it from the classical strategies. The aim of the proposed strategy is to reduce the computational cost without compromising the accuracy of the results. The new coupling strategy is validated using three numerical examples, comparing its accuracy and performance with the ones obtained with the classical (commonly employed) strategies for solving thermomechanical problems. Moreover, the influence of the time-step size on the accuracy is analysed. The results indicate that the proposed strategy presents accuracy close to the one obtained with the implicit coupling algorithm, while the computational cost is only slightly higher than the one required by the explicit strategy. (C) 2017 Elsevier Ltd. All rights reserved.The authors gratefully acknowledge the financial support of the Portuguese Foundation for Science and Technology (FCT) under projects P2020-PTDC/EMS-TEC/0702/2014 (POCI-01-0145-FEDER-016779) and P2020-PTDC/EMS-TEC/6400/2014 (POCI-01-0145-FEDER-016876) by UE/FEDER through the program COMPETE 2020. The second author is also grateful to the FCT for the Postdoctoral grant SFRH/BPD/101334/2014.info:eu-repo/semantics/publishedVersio

Economic and climatic models for estimating coffee supply

O objetivo deste trabalho foi estimar a oferta cafeeira por meio da calibração de modelos estatísticos, com variáveis econômicas e climáticas, das principais regiões produtoras do Estado de São Paulo. As regiões estudadas foram Batatais, Caconde, Cássia dos Coqueiros, Cristais Paulista, Espírito Santo do Pinhal, Marília, Mococa e Osvaldo Cruz. Foram utilizados dados de oferta cafeeira, variáveis econômicas (crédito rural, crédito rural na agricultura e valor da produção) e variáveis climáticas (temperatura do ar, precipitação pluvial, evapotranspiração potencial, deficiência e excedente hídrico) de cada região, para o período de 2000–2014. Os modelos foram calibrados com uso de técnicas de regressão linear múltipla, e todas as combinações possíveis foram testadas para a seleção das variáveis. A oferta cafeeira foi a variável dependente, e as demais, as independentes. A acurácia e a precisão dos modelos foram analisadas pelo erro percentual médio e pelo coeficiente de determinação ajustado, respectivamente. As variáveis que mais influenciam a oferta cafeeira são o valor de produção e a temperatura do ar. É possível estimar a oferta cafeeira com regressões lineares múltiplas por meio de variáveis econômicas e elementos climáticos. Os modelos mais acurados são os calibrados para estimar a oferta cafeeira das regiões de Cássia dos Coqueiros e Osvaldo Cruz.The objective of this work was to estimate the coffee supply by calibrating statistical models with economic and climatic variables for the main producing regions of the state of São Paulo, Brazil. The regions were Batatais, Caconde, Cássia dos Coqueiros, Cristais Paulista, Espírito Santo do Pinhal, Marília, Mococa, and Osvaldo Cruz. Data on coffee supply, economic variables (rural credit, rural agricultural credit, and production value), and climatic variables (air temperature, rainfall, potential evapotranspiration, water deficit, and water surplus) for each region, during the period from 2000–2014, were used. The models were calibrated using multiple linear regression, and all possible combinations were tested for selecting the variables. Coffee supply was the dependent variable, and the other ones were considered independent. The accuracy and precision of the models were assessed by the mean absolute percentage error and the adjusted coefficient of determination, respectively. The variables that most affect coffee supply are production value and air temperature. Coffee supply can be estimated with multiple linear regressions using economic and climatic variables. The most accurate models are those calibrated to estimate coffee supply for the regions of Cássia dos Coqueiros and Osvaldo Cruz