989 resultados para Chip formation
Resumo:
Acrylamide forms during cooking and processing predominately from the reaction of free asparagine and reducing sugars in the Maillard reaction. The identification of low free asparagine and reducing sugar varieties of crops is therefore an important target. In this study, nine varieties of potato (French fry varieties Maris Piper (from two suppliers), Pentland Dell, King Edward, Daisy, and Markies; and chipping varieties Lady Claire, Lady Rosetta, Saturna, and Hermes) grown in the United Kingdom in 2009 were analyzed at monthly intervals through storage from November 2009 to July 2010. Acrylamide formation was measured in heated flour and chips fried in oil. Analysis of variance revealed significant interactions between varieties nested within type (French fry and chipping) and storage time for most free amino acids, glucose, fructose, and acrylamide formation. Acrylamide formed in chips correlated significantly with acrylamide formed in flour and with chip color. There were significant correlations between glucose or total reducing sugar concentration and acrylamide formation in both variety types, but with fructose the correlation was much stronger for chipping than for French fry varieties. Conversely, there were significant correlations with acrylamide formation for both total free amino acid and free asparagine concentration in the French fry but not chipping varieties. The study showed the potential of variety selection for preventing unacceptable levels of acrylamide formation in potato products and the variety-dependent effect of long-term storage on acrylamide risk. It also highlighted the complex relationship between precursor concentration and acrylamide risk in potatoes.
Resumo:
The purpose of this research is design considerations for environmental monitoring platforms for the detection of hazardous materials using System-on-a-Chip (SoC) design. Design considerations focus on improving key areas such as: (1) sampling methodology; (2) context awareness; and (3) sensor placement. These design considerations for environmental monitoring platforms using wireless sensor networks (WSN) is applied to the detection of methylmercury (MeHg) and environmental parameters affecting its formation (methylation) and deformation (demethylation). ^ The sampling methodology investigates a proof-of-concept for the monitoring of MeHg using three primary components: (1) chemical derivatization; (2) preconcentration using the purge-and-trap (P&T) method; and (3) sensing using Quartz Crystal Microbalance (QCM) sensors. This study focuses on the measurement of inorganic mercury (Hg) (e.g., Hg2+) and applies lessons learned to organic Hg (e.g., MeHg) detection. ^ Context awareness of a WSN and sampling strategies is enhanced by using spatial analysis techniques, namely geostatistical analysis (i.e., classical variography and ordinary point kriging), to help predict the phenomena of interest in unmonitored locations (i.e., locations without sensors). This aids in making more informed decisions on control of the WSN (e.g., communications strategy, power management, resource allocation, sampling rate and strategy, etc.). This methodology improves the precision of controllability by adding potentially significant information of unmonitored locations.^ There are two types of sensors that are investigated in this study for near-optimal placement in a WSN: (1) environmental (e.g., humidity, moisture, temperature, etc.) and (2) visual (e.g., camera) sensors. The near-optimal placement of environmental sensors is found utilizing a strategy which minimizes the variance of spatial analysis based on randomly chosen points representing the sensor locations. Spatial analysis is employed using geostatistical analysis and optimization occurs with Monte Carlo analysis. Visual sensor placement is accomplished for omnidirectional cameras operating in a WSN using an optimal placement metric (OPM) which is calculated for each grid point based on line-of-site (LOS) in a defined number of directions where known obstacles are taken into consideration. Optimal areas of camera placement are determined based on areas generating the largest OPMs. Statistical analysis is examined by using Monte Carlo analysis with varying number of obstacles and cameras in a defined space. ^
Resumo:
A month-long intensive measurement campaign was conducted in March/April 2007 at Agnes Water, a remote coastal site just south of the Great Barrier Reef on the east coast of Australia. Particle and ion size distributions were continuously measured during the campaign. Coastal nucleation events were observed in clean, marine air masses coming from the south-east on 65% of the days. The events usually began at ~10:00 local time and lasted for 1-4 hrs. They were characterised by the appearance of a nucleation mode with a peak diameter of ~10 nm. The freshly nucleated particles grew within 1-4 hrs up to sizes of 20-50 nm. The events occurred when solar intensity was high (~1000 W m-2) and RH was low (~60%). Interestingly, the events were not related to tide height. The volatile and hygroscopic properties of freshly nucleated particles (17-22.5 nm), simultaneously measured with a volatility-hygroscopicity-tandem differential mobility analyser (VH-TDMA), were used to infer chemical composition. The majority of the volume of these particles was attributed to internally mixed sulphate and organic components. After ruling out coagulation as a source of significant particle growth, we conclude that the condensation of sulphate and/or organic vapours was most likely responsible for driving particle growth during the nucleation events. We cannot make any direct conclusions regarding the chemical species that participated in the initial particle nucleation. However, we suggest that nucleation may have resulted from the photo-oxidation products of unknown sulphur or organic vapours emitted from the waters of Hervey Bay, or from the formation of DMS-derived sulphate clusters over the open ocean that were activated to observable particles by condensable vapours emitted from the nutrient rich waters around Fraser Island or Hervey Bay. Furthermore, a unique and particularly strong nucleation event was observed during northerly wind. The event began early one morning (08:00) and lasted almost the entire day resulting in the production of a large number of ~80 nm particles (average modal concentration during the event was 3200 cm-3). The Great Barrier Reef was the most likely source of precursor vapours responsible for this event.
Resumo:
The measurement of submicrometre (< 1.0 m) and ultrafine particles (diameter < 0.1 m) number concentration have attracted attention since the last decade because the potential health impacts associated with exposure to these particles can be more significant than those due to exposure to larger particles. At present, ultrafine particles are not regularly monitored and they are yet to be incorporated into air quality monitoring programs. As a result, very few studies have analysed their long-term and spatial variations in ultrafine particle concentration, and none have been in Australia. To address this gap in scientific knowledge, the aim of this research was to investigate the long-term trends and seasonal variations in particle number concentrations in Brisbane, Australia. Data collected over a five-year period were analysed using weighted regression models. Monthly mean concentrations in the morning (6:00-10:00) and the afternoon (16:00-19:00) were plotted against time in months, using the monthly variance as the weights. During the five-year period, submicrometre and ultrafine particle concentrations increased in the morning by 105.7% and 81.5% respectively whereas in the afternoon there was no significant trend. The morning concentrations were associated with fresh traffic emissions and the afternoon concentrations with the background. The statistical tests applied to the seasonal models, on the other hand, indicated that there was no seasonal component. The spatial variation in size distribution in a large urban area was investigated using particle number size distribution data collected at nine different locations during different campaigns. The size distributions were represented by the modal structures and cumulative size distributions. Particle number peaked at around 30 nm, except at an isolated site dominated by diesel trucks, where the particle number peaked at around 60 nm. It was found that ultrafine particles contributed to 82%-90% of the total particle number. At the sites dominated by petrol vehicles, nanoparticles (< 50 nm) contributed 60%-70% of the total particle number, and at the site dominated by diesel trucks they contributed 50%. Although the sampling campaigns took place during different seasons and were of varying duration these variations did not have an effect on the particle size distributions. The results suggested that the distributions were rather affected by differences in traffic composition and distance to the road. To investigate the occurrence of nucleation events, that is, secondary particle formation from gaseous precursors, particle size distribution data collected over a 13 month period during 5 different campaigns were analysed. The study area was a complex urban environment influenced by anthropogenic and natural sources. The study introduced a new application of time series differencing for the identification of nucleation events. To evaluate the conditions favourable to nucleation, the meteorological conditions and gaseous concentrations prior to and during nucleation events were recorded. Gaseous concentrations did not exhibit a clear pattern of change in concentration. It was also found that nucleation was associated with sea breeze and long-range transport. The implications of this finding are that whilst vehicles are the most important source of ultrafine particles, sea breeze and aged gaseous emissions play a more important role in secondary particle formation in the study area.