Numerical 3D modeling of heat transfer in human tissues for microwave radiometry monitoring of Brown fat metabolismo

Background: Brown adipose tissue (BAT) plays an important role in whole body metabolism and could potentially mediate weight gain and insulin sensitivity. Although some imaging techniques allow BAT detection, there are currently no viable methods for continuous acquisition of BAT energy expenditure. We present a non-invasive technique for long term monitoring of BAT metabolism using microwave radiometry. Methods: A multilayer 3D computational model was created in HFSS™ with 1.5 mm skin, 3-10 mm subcutaneous fat, 200 mm muscle and a BAT region (2-6 cm3) located between fat and muscle. Based on this model, a log-spiral antenna was designed and optimized to maximize reception of thermal emissions from the target (BAT). The power absorption patterns calculated in HFSS™ were combined with simulated thermal distributions computed in COMSOL® to predict radiometric signal measured from an ultra-low-noise microwave radiometer. The power received by the antenna was characterized as a function of different levels of BAT metabolism under cold and noradrenergic stimulation. Results: The optimized frequency band was 1.5-2.2 GHz, with averaged antenna efficiency of 19%. The simulated power received by the radiometric antenna increased 2-9 mdBm (noradrenergic stimulus) and 4-15 mdBm (cold stimulus) corresponding to increased 15-fold BAT metabolism. Conclusions: Results demonstrated the ability to detect thermal radiation from small volumes (2-6 cm3) of BAT located up to 12 mm deep and to monitor small changes (0.5°C) in BAT metabolism. As such, the developed miniature radiometric antenna sensor appears suitable for non-invasive long term monitoring of BAT metabolism.

Exposure to microbial volatile organic compounds in a waste-handling unit

The production of MVOC by fungi has been taken into account especially from the viewpoint of indoor pollution with microorganisms but the relevance of fungal metabolites in working environments has not been sufficiently studied. The purpose of this study was to assess exposure to MVOCs in a waste-handling unit. It was used Multirae equipment (RAE Systems) to measured MVOCs concentration with a 10.6 eV lamps. The measurements were done near workers nose and during the normal activities. All measurements were done continuously and had the duration of 5 minutes at least. It was consider the higher value obtained in each measurement. In addition, for knowing fungi contamination, five air samples of 50 litres were collected through impaction method at 140 L/minute, at one meter tall, on to malt extract agar with the antibiotic chloramphenicol (MEA). MVOCs results range between 4.7 ppm and 8.9 ppm in the 6 locations consider. These results are eight times higher than normally obtained in indoor settings. Considering fungi results, two species were identified in air, being the genera Penicillium found in all the samples in uncountable colonies and Rhizopus only in one sample (40 UFC/m3). These fungi are known as MVOCs producers, namely terpenoids, ketones, alcohols and others. Until now, there has been no evidence that MVOCs are toxicologically relevant, but further epidemiological research is necessary to elucidate their role on human’s health, particularly in occupational settings where microbiological contamination is common. Additionally, further research should concentrate on quantitative analyses of specific MVOCs.

Integration of biomonitoring and instrumental techniques to assess the air quality in an industrial area located in the coastal of Central Asturias, Spain

Throughout the world, epidemiological studies were established to examine the relationship between air pollution and mortality rates and adverse respiratory health effects. However, despite the years of discussion the correlation between adverse health effects and atmospheric pollution remains controversial, partly because these studies are frequently restricted to small and well-monitored areas. Monitoring air pollution is complex due to the large spatial and temporal variations of pollution phenomena, the high costs of recording instruments, and the low sampling density of a purely instrumental approach. Therefore, together with the traditional instrumental monitoring, bioindication techniques allow for the mapping of pollution effects over wide areas with a high sampling density. In this study, instrumental and biomonitoring techniques were integrated to support an epidemiological study that will be developed in an industrial area located in Gijon in the coastal of central Asturias, Spain. Three main objectives were proposed to (i) analyze temporal patterns of PM10 concentrations in order to apportion emissions sources, (ii) investigate spatial patterns of lichen conductivity to identify the impact of the studied industrial area in air quality, and (iii) establish relationships amongst lichen conductivity with some site-specific characteristics. Samples of the epiphytic lichen Parmelia sulcata were transplanted in a grid of 18 by 20 km with an industrial area in the center. Lichens were exposed for a 5-mo period starting in April 2010. After exposure, lichen samples were soaked in 18-MΩ water aimed at determination of water electrical conductivity and, consequently, lichen vitality and cell damage. A marked decreasing gradient of lichens conductivity relative to distance from the emitting sources was observed. Transplants from a sampling site proximal to the industrial area reached values 10-fold higher than levels far from it. This finding showed that lichens reacted physiologically in the polluted industrial area as evidenced by increased conductivity correlated to contamination level. The integration of temporal PM10 measurements and analysis of wind direction corroborated the importance of this industrialized region for air quality measurements and identified the relevance of traffic for the urban area.

Occupational exposure to particulate matter and fungi in a composting plant: case study in Portugal

The handling of waste can be responsible for occupational exposure to particles and fungi. The aim of this study was to characterize exposure to particles and fungi in a composting plant. Measurements of particulate matter were performed using portable direct-reading equipment. Air samples of 50L were collected through an impaction method with a flow rate of 140L/min onto malt extract agar supplemented with chloramphenicol (0.05%). Surfaces samples were also collected. All the samples were incubated at 27ºC for 5 to 7 days. Particulate matter data showed higher contamination for PM, and PM10 sizes. Aspergillus genus presents the highest air prevalence (90.6%). Aspergillus niger (32.6%), A. fumigatus (26.5%) and A. flavus (16.3%) were the most prevalent fungi in air sampling, and Mucor sp. (39.2%), Aspergillus niger (30.9%) and A. fumigatus (28.7%) were the most found in surfaces. the results obtained claim the attention to the need of further research.

Fuzzy clustering applied to a demand response model in a smart grid contingency scenario

This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.

Fuzzy clustering applied to a demand response model in a smatr grid contingency scenario

This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.