990 resultados para Fat source


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Sediment samples were taken from six sampling sites in Bramble Bay, Queensland, Australia between February and November in 2012. They were analysed for a range of heavy metals including Al, Fe, Mn, Ti, Ce, Th, U, V, Cr, Co, Ni, Cu, Zn, As, Cd, Sb, Te, Hg, Tl and Pb. Fraction analysis, enrichment factors and Principal Component Analysis –Absolute Principal Component Scores (PCA-APCS) were carried out in order to assess metal pollution, potential bioavailability and source apportionment. Cr and Ni exceeded the Australian Interim Sediment Quality Guidelines at some sampling sites, while Hg was found to be the most enriched metal. Fraction analysis identified increased weak acid soluble Hg and Cd during the sampling period. Source apportionment via PCA-APCS found four sources of metals pollution, namely, marine sediments, shipping, antifouling coatings and a mixed source. These sources need to be considered in any metal pollution control measure within Bramble Bay.

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Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

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This study developed a comprehensive research methodology for identification and quantification of sources responsible for pollutant build-up and wash-off from urban road surfaces. The study identified soil and asphalt wear, and non-combusted diesel fuel as the most influential sources for metal and hydrocarbon pollution respectively. The study also developed mathematical models to relate contributions from identified sources to underlying site specific factors such as land use and traffic. Developed mathematical model will play a key role in urban planning practices, enabling the implementation of effective water pollution control strategies.

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Objectives Shift workers are prone to obesity and associated co-morbidities such as diabetes and cardiovascular disease. Sleep restriction associated with shift work results in dramatic endocrine and metabolic effects that predispose shift workers to these adverse health consequences. While sleep restriction has been associated with increased caloric intake, food preference may also play a key role in weight gain associated with shift work. This study examined the impact of an overnight simulated night shift on food preference. Methods Sixteen participants [mean 20.1, standard deviation (SD) 1.4 years; 8 women] underwent a simulated night shift and control condition in a counterbalanced order. On the following morning, participants were provided an opportunity for breakfast that included high- and low-fat food options (mean 64.8% and 6.4% fat, respectively). Results Participants ate significantly more high-fat breakfast items after the simulated night shift than after the control condition [167.3, standard error of the mean (SEM 28.7) g versus 211.4 (SEM 35.6) g; P=0.012]. The preference for high-fat food was apparent among the majority of individuals following the simulated night shift (81%), but not for the control condition (31%). Shift work and control conditions did not differ, however, in the total amount of food or calories consumed. Conclusions A simulated night shift leads to preference for high-fat food during a subsequent breakfast opportunity. These results suggest that food choice may contribute to weight-related chronic health problems commonly seen among night shift workers.

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Background Depression is a common psychiatric disorder in older people. The study aimed to examine the screening accuracy of the Geriatric Depression Scale (GDS) and the Collateral Source version of the Geriatric Depression Scale (CS-GDS) in the nursing home setting. Methods Eighty-eight residents from 14 nursing homes were assessed for depression using the GDS and the CS-GDS, and validated against clinician diagnosed depression using the Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders (SCID) for residents without dementia and the Provisional Diagnostic Criteria for Depression in Alzheimer Disease (PDCdAD) for those with dementia. The screening performances of five versions of the GDS (30-, 15-, 10-, 8-, and 4-item) and two versions of the CS-GDS (30- and 15-item) were analyzed using receiver operating characteristic (ROC) curves. Results Among residents without dementia, both the self-rated (AUC = 0.75–0.79) and proxy-rated (AUC = 0.67) GDS variations performed significantly better than chance in screening for depression. However, neither instrument adequately identified depression among residents with dementia (AUC between 0.57 and 0.70). Among the GDS variations, the 4- and 8-item scales had the highest AUC and the optimal cut-offs were >0 and >3, respectively. Conclusions The validity of the GDS in detecting depression requires a certain level of cognitive functioning. While the CS-GDS is designed to remedy this issue by using an informant, it did not have adequate validity in detecting depression among residents with dementia. Further research is needed on informant selection and other factors that can potentially influence the validity of proxy-based measures in the nursing home setting.

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Travellers are spoilt by holiday choice, and yet will usually only seriously consider a few destinations during the decision process. With thousands of destination marketing organisations (DMOs) competing for attention, places are becoming increasingly substitutable. The study of destination competitiveness is an emerging field, and thesis contributes to an enhanced understanding by addressing three topics that have received relatively little attention in the tourism literature: destination positioning, the context of short break holidays, and domestic travel in New Zealand. A descriptive model of positioning as a source of competitive advantage is developed, and tested through 12 propositions. The destination of interest is Rotorua, which was arguably New Zealand’s first tourist destination. The market of interest is Auckland, which is Rotorua’s largest visitor market. Rotorua’s history is explored to identify factors that may have contributed to the destination’s current image in the Auckland market. A mix of qualitative and quantitative procedures is then utilised to determine Rotorua’s position, relative to a competing set of destinations. Based on an applied research problem, the thesis attempts to bridge the gap between academia and industry by providing useable results and benchmarks for five regional tourism organisations (RTOs). It is proposed that, in New Zealand, the domestic short break market represents a valuable opportunity not explicitly targeted by the competitive set of destinations. Conceptually, the thesis demonstrates the importance of analysing a destination’s competitive position, from the demand perspective, in a travel context; and then the value of comparing this ‘ideal’ position with that projected by the RTO. The thesis concludes Rotorua’s market position in the Auckland short break segment represents a source of comparative advantage, but is not congruent with the current promotional theme, which is being used in all markets. The findings also have implications for destinations beyond the context of the thesis. In particular, a new definition for ‘destination attractiveness’ is proposed, which warrants consideration in the design of future destination positioning analyses.

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The Source Monitoring Framework is a promising model of constructive memory, yet fails because it is connectionist and does not allow content tagging. The Dual-Process Signal Detection Model is an improvement because it reduces mnemic qualia to a single memory signal (or degree of belief), but still commits itself to non-discrete representation. By supposing that ‘tagging’ means the assignment of propositional attitudes to aggregates of anemic characteristics informed inductively, then a discrete model becomes plausible. A Bayesian model of source monitoring accounts for the continuous variation of inputs and assignment of prior probabilities to memory content. A modified version of the High-Threshold Dual-Process model is recommended to further source monitoring research.

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On the 12th June 2014, Elon Musk, the chief executive officer of the electric car manufacturer, Tesla Motors, announced in a blog that ‘all our patents belong to you.’ He explained that the company would adopt an open source philosophy in respect of its intellectual property in order to encourage the development of the industry of electric cars, and address the carbon crisis. Elon Musk made the dramatic, landmark announcement: Yesterday, there was a wall of Tesla patents in the lobby of our Palo Alto headquarters. That is no longer the case. They have been removed, in the spirit of the open source movement, for the advancement of electric vehicle technology.

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Frequency Domain Spectroscopy (FDS) is one of the major techniques used for determining the condition of the cellulose based paper and pressboard components in large oil/paper insulated power transformers. This technique typically makes use of a sinusoidal voltage source swept from 0.1 mHz to 1 kHz. The excitation test voltage source used must meet certain characteristics, such as high output voltage, high fidelity, low noise and low harmonic content. The amplifier used; in the test voltage source; must be able to drive highly capacitive loads. This paper proposes that a switch-mode assisted linear amplifier (SMALA) can be used in the test voltage source to meet these criteria. A three level SMALA prototype amplifier was built to experimentally demonstrate the effectiveness of this proposal. The developed SMALA prototype shows no discernable harmonic distortion in the output voltage waveform, or the need for output filters, and is therefore seen as a preferable option to pulse width modulated digital amplifiers. The lack of harmonic distortion and high frequency switching noise in the output voltage of this SMALA prototype demonstrates its feasibility for applications in FDS, particularly on highly capacitive test objects such as transformer insulation systems.

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This study compared fat oxidation rate from a graded exercise test (GXT) with a moderate-intensity interval training session (MIIT) in obese men. Twelve sedentary obese males (age 29 ± 4.1 years; BMI 29.1 ± 2.4 kg·m-2; fat mass 31.7 ± 4.4 %body mass) completed two exercise sessions: GXT to determine maximal fat oxidation (MFO) and maximal aerobic power (VO2max), and an interval cycling session during which respiratory gases were measured. The 30-min MIIT involved 5-min repetitions of workloads 20% below and 20% above the MFO intensity. VO2max was 31.8 ± 5.5 ml·kg-1·min-1 and all participants achieved ≥ 3 of the designated VO2max test criteria. The MFO identified during the GXT was not significantly different compared with the average fat oxidation rate in the MIIT session. During the MIIT session, fat oxidation rate increased with time; the highest rate (0.18 ± 0.11 g·min- 1) in minute 25 was significantly higher than the rate at minute 5 and 15 (p ≤ 0.01 and 0.05 respectively). In this cohort with low aerobic fitness, fat oxidation during the MIIT session was comparable with the MFO determined during a GXT. Future research may consider if the varying workload in moderate-intensity interval training helps adherence to exercise without compromising fat oxidation.

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Past research has suggested that social networking sites are the most common source for social engineering-based attacks. Persuasion research shows that people are more likely to obey and accept a message when the source’s presentation appears to be credible. However, many factors can impact the perceived credibility of a source, depending on its type and the characteristics of the environment. Our previous research showed that there are four dimensions of source credibility in terms of social engineering on Facebook: perceived sincerity, perceived competence, perceived attraction, and perceived worthiness. Because the dimensionalities of source credibility as well as their measurement scales can fluctuate from one type of source to another and from one type of context to another, our aim in this study includes validating the existence of those four dimensions toward the credibility of social engineering attackers on Facebook and developing a valid measurement scale for every dimension of them.

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Context: in the ESR1 gene encoding estrogen receptor (ER)-α may be associated with fat mass in adults. Objectives: The objective of the study was to establish whether ESR1 polymorphisms influence fat mass in childhood. Design: This was a cross-sectional analysis after genotyping of rs9340799, rs2234693, and rs7757956 ESR1 polymorphisms. Setting: The Avon Longitudinal Study of Parents and Children (ALSPAC) was a population-based prospective study. Participants: Participants included 3097 11-yr-old children with results for ESR1 genotyping, puberty measures, and dual-energy x-ray absorptiometry results. Outcomes: Relationships between ESR1 polymorphisms and indices of body composition were measured. Results: The rs7757956 polymorphism was associated with fat mass (P = 0.002). Total body fat mass (adjusted for height) was reduced by 6% in children with TA/AA genotypes, and risk of being overweight (≥85th centile of fat mass) was decreased by 20%. This genetic effect appeared to interact with puberty in girls (P = 0.05 for interaction): in those with the TT genotype, total body fat mass (adjusted for height) was 18% higher in Tanner stages 3-5 vs. stages 1-2; the equivalent difference was 7% in those with TA/AA genotypes. Furthermore, the risk of being overweight was 36% lower in girls with TA/AA genotypes in Tanner stages 3-5, but no reduction was seen in those in stages 1-2. Neither rs9340799 nor rs2234693 polymorphisms were associated with body composition measures. Conclusions: Fat mass in 11-yr-old children was related to the rs7757956 ESR1 polymorphism. This association was strongest in girls in more advanced puberty, in whom the risk of being overweight was reduced by 36% in those with the TA/AA genotype.

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We report here on a series of laboratory experiments on plumes, undertaken with the object of simulating the effect of the heat release that occurs in clouds on condensation of water vapor. The experimental technique used for this purpose relies on ohmic heating generated in an electrically conducting plume fluid subjected to a suitable alternating voltage across specified axial stations in the plume flow [Bhat et al., 1989]. The present series of experiments achieves a value of the Richardson number that is toward the lower end of the range that characteristics cumulus clouds. It is found that the buoyancy enhancement due to heating disrupts the eddy structures in the flow and reduces the dilution owing to entrainment of ambient fluid that would otherwise have occurred in the central region of the plume. Heating also reduces the spread rate of the plume, but as it accelerates the flow as well, the overall specific mass flux in the plume does not show a very significant change at the heat input employed in the experiment. However, there is some indication that the entrainment rate (proportional to the streamwise derivative of the mass flux) is slightly higher immediately after heat injection and slightly lower farther downstream. The measurements support a previous proposal for a cloud scenario [Bhat and Narasimha, 1996] and demonstrate how fresh insights into certain aspects of the fluid dynamics of clouds may be derived from the experimental techniques employed here.

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Airborne organic pollutants have significant impacts on health; however their sources, atmospheric characteristics and resulting human exposures are poorly understood. This research characterized chemical composition of atmospheric volatile organic compounds, polycyclic aromatic hydrocarbons and carbonyls in representative number of primary schools in Brisbane Metropolitan Area, quantified their concentrations, assessed their toxicity and apportioned them to their sources. The findings expand scientific knowledge of these pollutants, and will contribute towards science based management of risks associated with pollution emissions and air quality in schools and other urban and indoor environments.