995 resultados para Vegetable processing
Resumo:
Objective: To evaluate responses to self-administered brief questions regarding consumption of vegetables and fruit by comparison with blood levels of serum carotenoids and red-cell folate. Design: A cross-sectional study in which participants reported their usual intake of fruit and vegetables in servings per day, and serum levels of five carotenoids (α-carotene, β-carotene, β-cryptoxanthin, lutein/zeaxanthin and lycopene) and red-cell folate were measured. Serum carotenoid levels were determined by high-performance liquid chromatography, and red-cell folate by an automated immunoassay system. Settings and subjects: Between October and December 2000, a sample of 1598 adults aged 25 years and over, from six randomly selected urban centres in Queensland, Australia, were examined as part of a national study conducted to determine the prevalence of diabetes and associated cardiovascular risk factors. Results: Statistically significant (P<0.01) associations with vegetable and fruit intake (categorised into groups: ≤1 serving, 2–3 servings and ≥4 servings per day) were observed for α-carotene, β-carotene, β-cryptoxanthin, lutein/zeaxanthin and red-cell folate. The mean level of these carotenoids and of red-cell folate increased with increasing frequency of reported servings of vegetables and fruit, both before and after adjusting for potential confounding factors. A significant association with lycopene was observed only for vegetable intake before adjusting for confounders. Conclusions: These data indicate that brief questions may be a simple and valuable tool for monitoring vegetable and fruit intake in this population.
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Recent research has revealed the existence of an elegant defence mechanism in plants and lower eukaryotes. The mechanism, known in plants as post-transcriptional gene silencing, works through sequence-specific degradation of RNA. It appears to be directed by double-stranded RNA, associated with the production of short 21-25 nt RNAs, and spread through the plant by a diffusible signal. The short RNAs are implicated as the guides for both a nuclease complex that degrades the mRNA and a methyltransferase complex that methylates the DNA of silenced genes. It has also been suggested that these short RNAs might be the mobile silencing signal, a suggestion that has been challenged recently.
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The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.
Resumo:
The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.
Resumo:
The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.
Resumo:
Incorporating a learner’s level of cognitive processing into Learning Analytics presents opportunities for obtaining rich data on the learning process. We propose a framework called COPA that provides a basis for mapping levels of cognitive operation into a learning analytics system. We utilise Bloom’s taxonomy, a theoretically respected conceptualisation of cognitive processing, and apply it in a flexible structure that can be implemented incrementally and with varying degree of complexity within an educational organisation. We outline how the framework is applied, and its key benefits and limitations. Finally, we apply COPA to a University undergraduate unit, and demonstrate its utility in identifying key missing elements in the structure of the course.
Resumo:
Sugar cane processing sites are characterised by high sugar/hemicellulose levels, available moisture and warm conditions, and are relatively unexplored unique microbial environments. The PhyloChip microarray was used to investigate bacterial diversity and community composition in three Australian sugar cane processing plants. These ecosystems were highly complex and dominated by four main Phyla, Firmicutes (the most dominant), followed by Proteobacteria, Bacteroidetes, and Chloroflexi. Significant variation (p , 0.05) in community structure occurred between samples collected from ‘floor dump sediment’, ‘cooling tower water’, and ‘bagasse leachate’. Many bacterial Classes contributed to these differences, however most were of low numerical abundance. Separation in community composition was also linked to Classes of Firmicutes, particularly Bacillales, Lactobacillales and Clostridiales, whose dominance is likely to be linked to their physiology as ‘lactic acid bacteria’, capable of fermenting the sugars present. This process may help displace other bacterial taxa, providing a competitive advantage for Firmicutes bacteria.
Resumo:
Using Gray and McNaughton’s revised RST, this study investigated the extent to which the Behavioural Approach System (BAS) and the Fight-Flight-Freeze System (FFFS) influence the processing of gain-framed and loss-framed road safety messages and subsequent message acceptance. It was predicted that stronger BAS sensitivity and FFFS sensitivity would be associated with greater processing and acceptance of the gain-framed messages and loss-framed messages, respectively. Young drivers (N = 80, aged 17–25 years) viewed one of four road safety messages and completed a lexical decision task to assess message processing. Both self-report (e.g., Corr-Cooper RST-PQ) and behavioural measures (i.e., CARROT and Q-Task) were used to assess BAS and FFFS traits. Message acceptance was measured via self-report ratings of message effectiveness, behavioural intentions, attitudes and subsequent driving behaviour. The results are discussed in the context of the effect that differences in reward and punishment sensitivities may have on message processing and message acceptance.
Resumo:
The introduction of chalcone synthase A transgenes into petunia plants can result in degradation of chalcone synthase A RNAs and loss of chalcone synthase, a process called cosuppression or post-transcriptional gene silencing. Here we show that the RNA degradation is associated with changes in premRNA processing, i.e. loss of tissue specificity in transcript cleavage patterns, accumulation of unspliced molecules, and use of template-specific secondary poly(A) sites. These changes can also be observed at a lower level in leaves but not flowers of nontransgenic petunias. Based on this, a model is presented of how transgenes may disturb the carefully evolved, developmentally controlled post-transcriptional regulation of chalcone synthase gene expression by influencing the survival rate of the endogenous and their own mRNA.
Resumo:
We have previously reported that concanavalin A (ConA)-induced MMP-2 activation involves both transcriptional and non-transcriptional mechanisms. Here we examined the effects of calcium influx on MT1-MMP expression and MMP-2 activation in MDA-MB-231 cells. The calcium ionophore ionomycin caused a dose-dependent inhibition of ConA-induced MMP-2 activation, but had no effect on MT1-MMP mRNA levels. However, Western analysis revealed an accumulation of pro-MT1-MMP (63 kDa), indicating that ionomycin blocked the conversion of pro-MT1-MMP protein to the active 60 kDa form. This suggests that increased calcium levels inhibit the processing of MT1-MMP. This finding may help to elucidate the mechanism(s) which regulates MT1-MMP activation.
Resumo:
Adequate consumption of fruits and vegetables (FV) is a characteristic of a healthy diet but remains a challenge in nutrition interventions. This cross-sectional study explored the multi-directional relationships between maternal feeding self-efficacy, parenting confidence, child feeding behaviour, exposure to new food and FV intake in a cohort of 277 infants. Mothers with healthy infants weighing ≥2500 g and ≥37 weeks gestation were recruited post-natally from 11 South Australian hospitals. Socio-demographic datawere collected at recruitment. At 6 months postnatal, infantswereweighed and measured, andmothers completed a questionnaire exploring their perceptions of child feeding behaviour and child exposure to newfoods. The questionnaire also included the Short Temperament Scale for Infants, Kessler 10 to measure maternal psychological distress and 5 items measuring maternal feeding self-efficacy. The number of occasions and variety of FV (number of subgroups within food groups) consumed by infants were estimated from a 24-hour dietary recall and 2 days food record. Structural equation modellingwas performed using Mplus version 6.11. Median (IQR) variety scores were 2 (1–3) for fruit and 3 (2–5) for vegetable intake. The most popular FV consumed were apple (n = 108, 45.0%) and pumpkin (n = 143, 56.3%). None of the variables studied predicted the variety of child fruit intake. Parenting confidence, exposure to new foods and child feeding behaviourwere indirectly related to child vegetable intake through maternal feeding self-efficacy while total number of children negatively predicted child vegetable variety (p < 0.05). This highlights the need for addressing antecedents of maternal feeding self-efficacy and the family eating environment as key strategies towards development of healthy eating in children.
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There has been a recent rapid expansion of the range of applications of low-temperature plasma processing in Si-based photovoltaic (PV) technologies. The desire to produce Si-based PV materials at an acceptable cost with consistent performance and reproducibility has stimulated a large number of major research and research infrastructure programs, and a rapidly increasing number of publications in the field of low-temperature plasma processing for Si photovoltaics. In this article, we introduce the low-temperature plasma sources for Si photovoltaic applications and discuss the effects of low-temperature plasma dissociation and deposition on the synthesis of Si-based thin films. We also examine the relevant growth mechanisms and plasma diagnostics, Si thin-film solar cells, Si heterojunction solar cells and silicon nitride materials for antireflection and surface passivation. Special attention is paid to the low-temperature plasma interactions with Si materials including hydrogen interaction, wafer cleaning, masked or mask-free surface texturization, the direct formation of p-n junction, and removal of phosphorus silicate glass or parasitic emitters. The chemical and physical interactions in such plasmas with Si surfaces are analyzed. Several examples of the plasma processes and techniques are selected to represent a variety of applications aimed at the improvement of Si-based solar cell performance. © 2014 Elsevier B.V.
Resumo:
An effective technique to improve the precision and throughput of energetic ion condensation through dielectric nanoporous templates and reduce nanopore clogging by using finely tuned pulsed bias is proposed. Multiscale numerical simulations of ion deposition show the possibility of controlling the dynamic charge balance on the upper template's surface to minimize ion deposition on nanopore sidewalls and to deposit ions selectively on the substrate surface in contact with the pore opening. In this way, the shapes of nanodots in template-assisted nanoarray fabrication can be effectively controlled. The results are applicable to various processes involving porous dielectric nanomaterials and dense nanoarrays.