981 resultados para Weight Scales.
Resumo:
Rhizoremediation is a bioremediation technique whereby enhanced microbial degradation of organic contaminants occurs within the plant root zone (rhizosphere). It is considered an effective and affordable ‘green technology’ for remediating soils contaminated with petroleum hydrocarbons (PHCs). This paper critically reviews the potential role of root exuded compounds in rhizoremediation, with emphasis on commonly exuded low molecular weight aliphatic organic acid anions (carboxylates). The extent to which remediation is achieved shows wide disparity among plant species. Therefore, plant selection is crucial for the advancement and widespread adoption of this technology. Root exudation is speculated to be one of the predominant factors leading to microbial changes in the rhizosphere and thus the potential driver behind enhanced petroleum biodegradation. Carboxylates can form a significant component of the root exudate mixture and are hypothesised to enhance petroleum biodegradation by: i) providing an easily degradable energy source; ii) increasing phosphorus supply; and/or iii) enhancing the contaminant bioavailability. These differing hypotheses, which are not mutually exclusive, require further investigation to progress our understanding of plant–microbe interactions with the aim to improve plant species selection and the efficacy of rhizoremediation.
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We present the first multi-event study of the spatial and temporal structuring of the aurora to provide statistical evidence of the near-Earth plasma instability which causes the substorm onset arc. Using data from ground-based auroral imagers, we study repeatable signatures of along-arc auroral beads, which are thought to represent the ionospheric projection of magnetospheric instability in the near-Earth plasma sheet. We show that the growth and spatial scales of these wave-like fluctuations are similar across multiple events, indicating that each sudden auroral brightening has a common explanation. We find statistically that growth rates for auroral beads peak at low wavenumber with the most unstable spatial scales mapping to an azimuthal wavelength λ≈1700 − 2500 km in the equatorial magnetosphere at around 9-12 RE. We compare growth rates and spatial scales with a range of theoretical predictions of magnetotail instabilities, including the cross-field current instability and the shear-flow ballooning instability. We conclude that, although the cross-field current instability can generate similar magnitude of growth rates, the range of unstable wavenumbers indicates that the shear-flow ballooning instability is the most likely explanation for our observations.
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Weeds tend to aggregate in patches within fields and there is evidence that this is partly owing to variation in soil properties. Because the processes driving soil heterogeneity operate at different scales, the strength of the relationships between soil properties and weed density would also be expected to be scale-dependent. Quantifying these effects of scale on weed patch dynamics is essential to guide the design of discrete sampling protocols for mapping weed distribution. We have developed a general method that uses novel within-field nested sampling and residual maximum likelihood (REML) estimation to explore scale-dependent relationships between weeds and soil properties. We have validated the method using a case study of Alopecurus myosuroides in winter wheat. Using REML, we partitioned the variance and covariance into scale-specific components and estimated the correlations between the weed counts and soil properties at each scale. We used variograms to quantify the spatial structure in the data and to map variables by kriging. Our methodology successfully captured the effect of scale on a number of edaphic drivers of weed patchiness. The overall Pearson correlations between A. myosuroides and soil organic matter and clay content were weak and masked the stronger correlations at >50 m. Knowing how the variance was partitioned across the spatial scales we optimized the sampling design to focus sampling effort at those scales that contributed most to the total variance. The methods have the potential to guide patch spraying of weeds by identifying areas of the field that are vulnerable to weed establishment.
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Obesity prevalence is increasing. The management of this condition requires a detailed analysis of the global risk factors in order to develop personalised advice. This study is aimed to identify current dietary patterns and habits in Spanish population interested in personalised nutrition and investigate associations with weight status. Self-reported dietary and anthropometrical data from the Spanish participants in the Food4Me study, were used in a multidimensional exploratory analysis to define specific dietary profiles. Two opposing factors were obtained according to food groups’ intake: Factor 1 characterised by a more frequent consumption of traditionally considered unhealthy foods; and Factor 2, where the consumption of “Mediterranean diet” foods was prevalent. Factor 1 showed a direct relationship with BMI (β = 0.226; r2 = 0.259; p < 0.001), while the association with Factor 2 was inverse (β = −0.037; r2 = 0.230; p = 0.348). A total of four categories were defined (Prudent, Healthy, Western, and Compensatory) through classification of the sample in higher or lower adherence to each factor and combining the possibilities. Western and Compensatory dietary patterns, which were characterized by high-density foods consumption, showed positive associations with overweight prevalence. Further analysis showed that prevention of overweight must focus on limiting the intake of known deleterious foods rather than exclusively enhance healthy products.
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In this paper, the teleconnections from the tropical Atlantic to the Indo-Pacific region from inter-annual to centennial time scales will be reviewed. Identified teleconnections and hypotheses on mechanisms at work are reviewed and further explored in a century-long pacemaker coupled ocean-atmosphere simulation ensemble. There is a substantial impact of the tropical Atlantic on the Pacific region at inter-annual time scales. An Atlantic Niño (Niña) event leads to rising (sinking) motion in the Atlantic region, which is compensated by sinking (rising) motion in the central-western Pacific. The sinking (rising) motion in the central-western Pacific induces easterly (westerly) surface wind anomalies just to the west, which alter the thermocline. These perturbations propagate eastward as upwelling (downwelling) Kelvin-waves, where they increase the probability for a La Niña (El Niño) event. Moreover, tropical North Atlantic sea surface temperature anomalies are also able to lead La Niña/El Niño development. At multidecadal time scales, a positive (negative) Atlantic Multidecadal Oscillation leads to a cooling (warming) of the eastern Pacific and a warming (cooling) of the western Pacific and Indian Ocean regions. The physical mechanism for this impact is similar to that at inter-annual time scales. At centennial time scales, the Atlantic warming induces a substantial reduction of the eastern Pacific warming even under CO2 increase and to a strong subsurface cooling.
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Ecological and biogeochemical processes in lakes are strongly dependent upon water temperature. Long-term surface warming of many lakes is unequivocal, but little is known about the comparative magnitude of temperature variation at diel timescales, due to a lack of appropriately resolved data. Here we quantify the pattern and magnitude of diel temperature variability of surface waters using high-frequency data from 100 lakes. We show that the near-surface diel temperature range can be substantial in summer relative to long-term change and, for lakes smaller than 3 km2, increases sharply and predictably with decreasing lake area. Most small lakes included in this study experience average summer diel ranges in their near-surface temperatures of between 4 and 7°C. Large diel temperature fluctuations in the majority of lakes undoubtedly influence their structure, function and role in biogeochemical cycles, but the full implications remain largely unexplored.
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It is argued that existing polar prediction systems do not yet meet users’ needs; and possible ways forward in advancing prediction capacity in polar regions and beyond are outlined. The polar regions have been attracting more and more attention in recent years, fuelled by the perceptible impacts of anthropogenic climate change. Polar climate change provides new opportunities, such as shorter shipping routes between Europe and East Asia, but also new risks such as the potential for industrial accidents or emergencies in ice-covered seas. Here, it is argued that environmental prediction systems for the polar regions are less developed than elsewhere. There are many reasons for this situation, including the polar regions being (historically) lower priority, with less in situ observations, and with numerous local physical processes that are less well-represented by models. By contrasting the relative importance of different physical processes in polar and lower latitudes, the need for a dedicated polar prediction effort is illustrated. Research priorities are identified that will help to advance environmental polar prediction capabilities. Examples include an improvement of the polar observing system; the use of coupled atmosphere-sea ice-ocean models, even for short-term prediction; and insight into polar-lower latitude linkages and their role for forecasting. Given the enormity of some of the challenges ahead, in a harsh and remote environment such as the polar regions, it is argued that rapid progress will only be possible with a coordinated international effort. More specifically, it is proposed to hold a Year of Polar Prediction (YOPP) from mid-2017 to mid-2019 in which the international research and operational forecasting community will work together with stakeholders in a period of intensive observing, modelling, prediction, verification, user-engagement and educational activities.
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Bovine rumen protein with two levels of residual lipids (1.9% or 3.8%) was subjected to thermoplastic extrusion under different temperatures and moisture contents. Protein Solubility in different buffers, disulphide cross-linking and molecular weight distribution were determined on the extrudates. After extrusion, samples with 1.9% residual lipids content had a higher concentration of protein insoluble by undetermined forces, irrespective of feed moisture and processing temperature used. Lipid content of 3.8% in the feed material resulted in more protein participating in the extrudate network through non-covalent interactions (hydrophobic and electrostatic) and disulphide bonds. A small dependency of the extrusion process on moisture and temperature and a marked dependency on lipid content, especially phospholipid, was observed, Electrophoresis under non-reducing conditions showed that protein extrusion with low feed moisture promoted high molecular breakdown inside the barrel, probably due to intense shear force, and further protein aggregation at the die end. (C) 2009 Elsevier Ltd. All rights reserved.
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A randomized, placebo-controlled trial was conducted in overweight calcium stone-forming (CSF) patients, to evaluate the effect of calcium supplementation associated with a calorie-restricted diet on body weight (BW) and fat reduction and its potential changes upon serum and urinary parameters. Fifteen patients were placed on a hypocaloric diet for 3 months, supplemented with either calcium carbonate (CaCO(3), n = 8) or placebo (n = 7), 500 mg bid. Blood and 24-h urine samples were collected and body composition was assessed at baseline and after the intervention. At the end of the study, final BW was significantly lower vs baseline in both CaCO(3) (74 +/- A 14 vs. 80 +/- A 14 kg, P = 0.01) and placebo groups (80 +/- A 10 vs. 87 +/- A 9 kg, P = 0.02) but the mean percentage of loss of body weight and body fat did not differ between CaCO(3) and placebo (7.0 +/- A 2.0 vs. 8.0 +/- A 3.0%, P = 0.40 and 13.0 +/- A 7.0 vs. 13.0 +/- A 10.0%; P = 0.81, respectively). After CaCO(3) or placebo, no significant differences versus baseline were observed for urinary parameters in both CaCO(3) and placebo, except for a higher mean urinary citrate in placebo group. These data suggest that increasing calcium intake by calcium carbonate supplementation did not contribute to a further reduction of BW and fat in overweight CSF patients submitted to a hypocaloric diet nor altered urinary lithogenic parameters.
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To determine whether changes in dietary intakes predict weight loss, we studied 80 overweight adults who attended a nutritional counseling program during 6 months of follow-up at a primary health care center in Brazil. Habitual diet was assessed using a validated food frequency questionnaire at baseline and after 6 months. The mean age (+/-SD) of the participants was 46.5 +/- 9.5 years, and their mean body mass index was 29 +/- 3 kg/m(2) at baseline. After 6 months, the differences in body weight and fruit/vegetable intake were -1.4 +/- 3 kg and 109 +/- 320 g daily, respectively. Using multiple linear regression models adjusted for age, sex, changes in walking time, and total energy intake, the increased intake of dietary fiber from fruits/vegetables was associated with a greater weight loss (beta 1 [95% confidence interval (CI)] = -0.180 [-0.269, -0.0911) after 6 months of follow-up. Similar results were observed for increased intake of vegetables (beta 1 [95% CI] = -0.00497 [-0.008, -0.0021) and fruits (beta 1 [95% CI] = -0.00290 [-0.005, -0.001]) as predictors of weight loss. The increase of 100 g/d of vegetables and fruits represented a body weight loss of 500 and 300 g after 6 months, respectively (P <.05). Our findings support the relevance of increased intakes of fruits and vegetables that may help avoid weight gain in overweight adults. (C) 2008 Elsevier Inc. All rights reserved.
Resumo:
The degree to which habitat fragmentation affects bird incidence is species specific and may depend on varying spatial scales. Selecting the correct scale of measurement is essential to appropriately assess the effects of habitat fragmentation on bird occurrence. Our objective was to determine which spatial scale of landscape measurement best describes the incidence of three bird species (Pyriglena leucoptera, Xiphorhynchus fuscus and Chiroxiphia caudata) in the fragmented Brazilian Atlantic forest and test if multi-scalar models perform better than single-scalar ones. Bird incidence was assessed in 80 forest fragments. The surrounding landscape structure was described with four indices measured at four spatial scales (400-, 600-, 800- and 1,000-m buffers around the sample points). The explanatory power of each scale in predicting bird incidence was assessed using logistic regression, bootstrapped with 1,000 repetitions. The best results varied between species (1,000-m radius for P. leucoptera; 800-m for X. fuscus and 600-m for C. caudata), probably due to their distinct feeding habits and foraging strategies. Multi-scale models always resulted in better predictions than single-scale models, suggesting that different aspects of the landscape structure are related to different ecological processes influencing bird incidence. In particular, our results suggest that local extinction and (re)colonisation processes might simultaneously act at different scales. Thus, single-scale models may not be good enough to properly describe complex pattern-process relationships. Selecting variables at multiple ecologically relevant scales is a reasonable procedure to optimise the accuracy of species incidence models.
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So Paulo is the most developed state in Brazil and contains few fragments of native ecosystems, generally surrounded by intensive agriculture lands. Despite this, some areas still shelter large native animals. We aimed at understanding how medium and large carnivores use a mosaic landscape of forest/savanna and agroecosystems, and how the species respond to different landscape parameters (percentage of landcover and edge density), in a multi-scale perspective. The response variables were: species richness, carnivore frequency and frequency for the three most recorded species (Puma concolor, Chrysocyon brachyurus and Leopardus pardalis). We compared 11 competing models using Akaike`s information criterion (AIC) and assessed model support using weight of AIC. Concurrent models were combinations of landcover types (native vegetation, ""cerrado"" formations, ""cerrado"" and eucalypt plantation), landscape feature (percentage of landcover and edge density) and spatial scale. Herein, spatial scale refers to the radius around a sampling point defining a circular landscape. The scales analyzed were 250 (fine), 1,000 (medium) and 2,000 m (coarse). The shape of curves for response variables (linear, exponential and power) was also assessed. Our results indicate that species with high mobility, P. concolor and C. brachyurus, were best explained by edge density of the native vegetation at a coarse scale (2,000 m). The relationship between P. concolor and C. brachyurus frequency had a negative power-shaped response to explanatory variables. This general trend was also observed for species richness and carnivore frequency. Species richness and P. concolor frequency were also well explained by a second concurrent model: edge density of cerrado at the fine (250 m) scale. A different response was recorded for L. pardalis, as the frequency was best explained for the amount of cerrado at the fine (250 m) scale. The curve of response was linearly positive. The contrasting results (P. concolor and C. brachyurus vs L. pardalis) may be due to the much higher mobility of the two first species, in comparison with the third. Still, L. pardalis requires habitat with higher quality when compared with other two species. This study highlights the importance of considering multiple spatial scales when evaluating species responses to different habitats. An important and new finding was the prevalence of edge density over the habitat extension to explain overall carnivore distribution, a key information for planning and management of protected areas.
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Fifteen percent of patients with Wilms`` tumor (WT) experience relapse. It has been suggested that weight and age may affect the chances of relapse. Few studies have investigated the role, if any, between P-glycoprotein (P-gp) and relapse. The authors assessed the prognostic value of tumor weight and age at diagnosis and asked whether some other potential biological markers, specifically P-gp protein expression, had a prognostic value in favorable-histology WT. No association between age and relapse could be found. Patients with tumor weight >= a parts per thousand yen550 g were 6 times more likely to relapse, whereas P-gp expression was positive in 18/40 (45%%) of the patients, of which 10/12 (83.3%%) relapsed and 8/28 (28.6%%) did not. Further studies are necessary to elucidate whether or not P-gp is related to relapse in patients with histologically favorable Wilms`` tumor. If confirmed, the protein may be used in the future as a target for new drugs and treatments for this group of patients.
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Detecting both the majors genes that control the phenotypic mean and those controlling phenotypic variance has been raised in quantitative trait loci analysis. In order to mapping both kinds of genes, we applied the idea of the classic Haley-Knott regression to double generalized linear models. We performed both kinds of quantitative trait loci detection for a Red Jungle Fowl x White Leghorn F2 intercross using double generalized linear models. It is shown that double generalized linear model is a proper and efficient approach for localizing variance-controlling genes. We compared two models with or without fixed sex effect and prefer including the sex effect in order to reduce the residual variances. We found that different genes might take effect on the body weight at different time as the chicken grows.