2 resultados para Positive influence
em AMS Tesi di Laurea - Alm@DL - Università di Bologna
Resumo:
With the development of the economy and society, air pollution has posed a huge threat to public health around the world, especially to people who live in urban areas. Typically, urban development patterns can be roughly divided into compact cities and urban sprawl. In recent years, the relationship between urban form and air quality (especially PM2.5) is gaining more and more attention from urban planners, environmentalists, and governments. This study is focusing on The New York metropolitan area and Shanghai city, which are both megacities but with different urban spatial forms. For both study areas,there are five main variables to measure the urban form metrics, naming Population Density, Artificial Land Area Per Ten Thousand People, Road Density, Green Land Area Ratio and Artificial Land Area Ratio. In addition, considering the impact of economic activities and public transportation, GDP per capita, Number of bus stop and Number of subway station are used as control variables. Based on the results of regression, a megacity like the New York metropolitan area with urban sprawl shows a low spatial correlation on PM2.5 concentration. Meanwhile, almost all the spatial form indicators effect on PM2.5 concentration is not significant. However, a compact megacity like Shanghai shows a diametrically opposite result. Urban form, especially population density, has a strong relationship with PM2.5 concentration. It can be predicted that a reduction in population density would lead to significant improvements on decrease the PM2.5 concentration in Shanghai. Meanwhile, increasing the ratio of green land and construction area per capita will get a positive influence on reducing PM2.5 concentration as well. Road density is not a significant factor for a megacity in both two urban forms. The way and type of energy used by vehicles on megacities maybe more critical.
Resumo:
The aim of the present thesis was to investigate the influence of lower-limb joint models on musculoskeletal model predictions during gait. We started our analysis by using a baseline model, i.e., the state-of-the-art lower-limb model (spherical joint at the hip and hinge joints at the knee and ankle) created from MRI of a healthy subject in the Medical Technology Laboratory of the Rizzoli Orthopaedic Institute. We varied the models of knee and ankle joints, including: knee- and ankle joints with mean instantaneous axis of rotation, universal joint at the ankle, scaled-generic-derived planar knee, subject-specific planar knee model, subject-specific planar ankle model, spherical knee, spherical ankle. The joint model combinations corresponding to 10 musculoskeletal models were implemented into a typical inverse dynamics problem, including inverse kinematics, inverse dynamics, static optimization and joint reaction analysis algorithms solved using the OpenSim software to calculate joint angles, joint moments, muscle forces and activations, joint reaction forces during 5 walking trials. The predicted muscle activations were qualitatively compared to experimental EMG, to evaluate the accuracy of model predictions. Planar joint at the knee, universal joint at the ankle and spherical joints at the knee and at the ankle produced appreciable variations in model predictions during gait trials. The planar knee joint model reduced the discrepancy between the predicted activation of the Rectus Femoris and the EMG (with respect to the baseline model), and the reduced peak knee reaction force was considered more accurate. The use of the universal joint, with the introduction of the subtalar joint, worsened the muscle activation agreement with the EMG, and increased ankle and knee reaction forces were predicted. The spherical joints, in particular at the knee, worsened the muscle activation agreement with the EMG. A substantial increase of joint reaction forces at all joints was predicted despite of the good agreement in joint kinematics with those of the baseline model. The introduction of the universal joint had a negative effect on the model predictions. The cause of this discrepancy is likely to be found in the definition of the subtalar joint and thus, in the particular subject’s anthropometry, used to create the model and define the joint pose. We concluded that the implementation of complex joint models do not have marked effects on the joint reaction forces during gait. Computed results were similar in magnitude and in pattern to those reported in literature. Nonetheless, the introduction of planar joint model at the knee had positive effect upon the predictions, while the use of spherical joint at the knee and/or at the ankle is absolutely unadvisable, because it predicted unrealistic joint reaction forces.