Estratégia de avaliação do risco de lesões músculo-esqueléticas de membros superiores ligadas ao trabalho aplicada na indústria de abate e desmancha de carne em P

RESUMO - Objectivo: As lesões músculo-esqueléticas ligadas ao trabalho (LMELT) são doenças profissionais frequentes. Neste estudo ensaiou-se uma estratégia de diagnóstico do risco e de vigilância da saúde dos trabalhadores numa empresa de abate e desmancha de carne. Métodos: Utilizou-se uma estratégia de obtenção de informação em todos os postos de trabalho e trabalhadores da empresa. Utilizaram-se: (i) adaptação do Questionário Nórdico Músculo-Esquelético, incluindo caracterização da exposição biomecânica; (ii) protocolo de avaliação clínica de LMELT; (iii) filtro RSI e método Strain Index; (iv) instrumentação, como electrogoniometria e sensores de força em postos de risco elevado. Resultados: Identificou-se a presença de sintomas e sinais de LMELT principalmente nos punhos/mãos (n=27) e região lombo-sagrada (n=32), uma importante prevalência de casos relacionados com a actividade de trabalho (30%) e níveis de risco elevados com base nas classificações do Strain Index (n=26 MSDto e n=7 MSEsq). A utilização da instrumentação permitiu obter detalhes da repetitividade, das posturas e dos momentos de aplicação de força, úteis para a intervenção. Conclusões: A prevenção só é possível através da aplicação de programas/estratégias integradas de diagnóstico e gestão do risco de LMELT que sejam eficazes no sentido da intervenção sobre a actividade e as condições de trabalho.--------------------------ABSTRACT – Background: Work-related Musculoskeletal Disorders (WRMSD) are common occupational diseases. The present study aims at examining an integrated perspective of risk assessment and health surveillance at a meatpacking plant. Methods: The strategy adopted was of obtaining information about WRMSDs awareness at all workstations and from all their workers. This was based on: (i) questionnaire application - an adaptation of the Nordic musculoskeletal questionnaire, including a biomechanical item, (ii) WRMSDs clinical protocol (iii) RSI risk filter and Strain Index application, (iv) instrumentation with electrogoniometry and force sensors at previously classified as high risk workstations. Results: WRMSDs signs and symptoms mainly in wrist/hands (n=27) and in lumbar region (n=32) were identified. Results revealed an important prevalence of WRULMSDs associated to meatpacking industry activities (30%) and high risk scores based on Strain Index (n=26 Right UL; n=7 Left UL). Instrumentation showed details of recurrency, of postures and of force, which can be used for intervention. Conclusions: It’s necessary to develop ergonomic strategies and approaches on WRMSDs prevention (risk assessment and manage

Amorphous silicon e 3D sensors applied to object detection

Nowadays, existing 3D scanning cameras and microscopes in the market use digital or discrete sensors, such as CCDs or CMOS for object detection applications. However, these combined systems are not fast enough for some application scenarios since they require large data processing resources and can be cumbersome. Thereby, there is a clear interest in exploring the possibilities and performances of analogue sensors such as arrays of position sensitive detectors with the final goal of integrating them in 3D scanning cameras or microscopes for object detection purposes. The work performed in this thesis deals with the implementation of prototype systems in order to explore the application of object detection using amorphous silicon position sensors of 32 and 128 lines which were produced in the clean room at CENIMAT-CEMOP. During the first phase of this work, the fabrication and the study of the static and dynamic specifications of the sensors as well as their conditioning in relation to the existing scientific and technological knowledge became a starting point. Subsequently, relevant data acquisition and suitable signal processing electronics were assembled. Various prototypes were developed for the 32 and 128 array PSD sensors. Appropriate optical solutions were integrated to work together with the constructed prototypes, allowing the required experiments to be carried out and allowing the achievement of the results presented in this thesis. All control, data acquisition and 3D rendering platform software was implemented for the existing systems. All these components were combined together to form several integrated systems for the 32 and 128 line PSD 3D sensors. The performance of the 32 PSD array sensor and system was evaluated for machine vision applications such as for example 3D object rendering as well as for microscopy applications such as for example micro object movement detection. Trials were also performed involving the 128 array PSD sensor systems. Sensor channel non-linearities of approximately 4 to 7% were obtained. Overall results obtained show the possibility of using a linear array of 32/128 1D line sensors based on the amorphous silicon technology to render 3D profiles of objects. The system and setup presented allows 3D rendering at high speeds and at high frame rates. The minimum detail or gap that can be detected by the sensor system is approximately 350 μm when using this current setup. It is also possible to render an object in 3D within a scanning angle range of 15º to 85º and identify its real height as a function of the scanning angle and the image displacement distance on the sensor. Simple and not so simple objects, such as a rubber and a plastic fork, can be rendered in 3D properly and accurately also at high resolution, using this sensor and system platform. The nip structure sensor system can detect primary and even derived colors of objects by a proper adjustment of the integration time of the system and by combining white, red, green and blue (RGB) light sources. A mean colorimetric error of 25.7 was obtained. It is also possible to detect the movement of micrometer objects using the 32 PSD sensor system. This kind of setup offers the possibility to detect if a micro object is moving, what are its dimensions and what is its position in two dimensions, even at high speeds. Results show a non-linearity of about 3% and a spatial resolution of < 2µm.

Genome-scale metabolic network reconstruction of Polaromonas sp. strain JS666: analysis of cDCE degradation rates and design of experiments for bioremediation improvement

Release of chloroethene compounds into the environment often results in groundwater contamination, which puts people at risk of exposure by drinking contaminated water. cDCE (cis-1,2-dichloroethene) accumulation on subsurface environments is a common environmental problem due to stagnation and partial degradation of other precursor chloroethene species. Polaromonas sp. strain JS666 apparently requires no exotic growth factors to be used as a bioaugmentation agent for aerobic cDCE degradation. Although being the only suitable microorganism found capable of such, further studies are needed for improving the intrinsic bioremediation rates and fully comprehend the metabolic processes involved. In order to do so, a metabolic model, iJS666, was reconstructed from genome annotation and available bibliographic data. FVA (Flux Variability Analysis) and FBA (Flux Balance Analysis) techniques were used to satisfactory validate the predictive capabilities of the iJS666 model. The iJS666 model was able to predict biomass growth for different previously tested conditions, allowed to design key experiments which should be done for further model improvement and, also, produced viable predictions for the use of biostimulant metabolites in the cDCE biodegradation.

Fabrication and characterization of transparent conductive oxide surface sensors for electrocorticography – TrECoG

Understanding how the brain works has been one of the greatest goals of mankind. This desire fuels the scientific community to pursue novel techniques able to acquire the complex information produced by the brain at any given moment. The Electrocorticography (ECoG) is one of those techniques. By placing conductive electrodes over the dura, or directly over the cortex, and measuring the electric potential variation, one can acquire information regarding the activation of those areas. In this work, transparent ECoGs, (TrECoGs) are fabricated through thin film deposition of the Transparent Conductive Oxides (TCOs) Indium-Zinc-Oxide (IZO) and Gallium-Zinc-Oxide (GZO). Five distinct devices have been fabricated via shadow masking and photolithography. The data acquired and presented in this work validates the TrECoGs fabricated as efficient devices for recording brain activity. The best results were obtained for the GZO- based TrECoG, which presented an average impedance of 36 kΩ at 1 kHz for 500 μm diameter electrodes, a transmittance close to 90% for the visible spectrum and a clear capability to detect brain signal variations. The IZO based devices also presented high transmittance levels (90%), but with higher impedances, which ranged from 40 kΩ to 100 kΩ.

Semantic architecture for sensors

Based on the report for the unit “Sociology of New Information Technologies” of the Master on Computer Sciences at FCT/University Nova Lisbon in 2015-16. The responsible of this curricular unit is Prof. António Moniz