Study of the muscular activation in obese and non-obese subjects during lifting loads

The obesity prevalence is increasing among the workforce of the developed countries. However, obesity seems to negatively affect the individuals’ work performance. In occupational contexts, manual lifting tasks are frequent and can produce significant muscle loading. With the aim of analysing the possible effect of obesity on workers’ muscular activation, surface electromyography data were collected from six muscles recruited during these tasks. In the current study, 6 different tasks of manual lifting (3 loads × 2 lifting styles) were performed by 14 participants with different obesity levels. Electromyography data normalization was based on the percentage of maximum contraction during each task. The muscles’ activation times before each task were also calculated. The current study suggests that obesity can increase the maximum contraction during each task and the delays on muscles’ activation time. This study suggests that obese individuals can present some changes on their muscle activation during lifting, when comparing with non-obese individuals, and reinforces the need to develop further studies focused on obesity as a risk factor for musculoskeletal disorders development.

Aplicação de metodologias Lean na secção de tecelagem de uma empresa têxtil

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Integrating data from heterogeneous DNA microarray platforms

DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.

Georeferencing historical documents: the case of the Dume Boundary

Much of the information of historical documents about the territory and property are defined on textual form. This information is mostly geographic and defines territorial areas, its limits and boundaries. For the treatment of this data, we have defined one information system where the treatment of the documental references for the study of the settlement and landscape implies a systematization of the information, normalization, integration and graphic and cartographic representation. This methodology was applied to the case study of the boundary of the monastery-diocese of Dume, in Braga - Portugal, for which there are countless documents and references to this site, but where the urban pressure has mischaracterized very significantly the landscape, making the identification of territorial limits quite difficult. The work carried out to give spatial and cartographic expression to the data, by defining viewing criteria according to the recorded information, proved to be a central working tool in the boundary study and in understanding the dynamics of the sites in the various cultural periods.

Differences in muscular activity between obese and non-obese workers during manual lifting

The prevalence of obesity is increasing throughout the workforce. Manual lifting tasks are common and can produce significant muscle loading. This study compared muscular activity between obese and non-obese subjects, using surface Electromyography (EMG), during manual lifting. Six different lifting tasks (with 5, 10 and 15 kg loads in free and constrained styles) were performed by 14 participants with different obesity levels. EMG data normalization was based on the percentage of Maximum Contraction during each Task (MCT). Muscle Activation Times (AT) before each task were also evaluated. The study suggests that obesity can increase MCT and delay muscle AT. These findings reinforce the need to develop further studies focused on obesity as a risk factor for the development of musculoskeletal disorders.