67 resultados para Temporal locality of reference
Resumo:
The optimal temporal window of intravenous (IV) computed tomography (CT) cholangiography was prospectively determined. Fifteen volunteers (eight women, seven men; mean age, 38 years) underwent dynamic CT cholangiography. Two unenhanced images were acquired at the porta hepatis. Starting 5 min after initiation of IV contrast infusion (20 ml iodipamide meglumine 52%), 15 pairs of images at 5-min intervals were obtained. Attenuation of the extrahepatic bile duct (EBD) and the liver parenchyma was measured. Two readers graded visualization of the higher-order biliary branches. The first biliary opacification in the EBD occurred between 15 and 25 min (mean, 22.3 min +/- 3.2) after initiation of the contrast agent. Biliary attenuation plateaued between the 35- and the 75-min time points. Maximum hepatic parenchymal enhancement was 18.5 HU +/- 2.7. Twelve subjects demonstrated poor or non-visualization of higher-order biliary branches; three showed good or excellent visualization. Body weight and both biliary attenuation and visualization of the higher-order biliary branches correlated significantly (P<0.05). For peak enhancement of the biliary tree, CT cholangiography should be performed no earlier than 35 min after initiation of IV infusion. For a fixed contrast dose, superior visualization of the biliary system is achieved in subjects with lower body weight.
Resumo:
Middle atmospheric water vapour can be used as a tracer for dynamical processes. It is mainly measured by satellite instruments and ground-based microwave radiometers. Ground-based instruments capable of measuring middle-atmospheric water vapour are sparse but valuable as they complement satellite measurements, are relatively easy to maintain and have a long lifetime. MIAWARA-C is a ground-based microwave radiometer for middle-atmospheric water vapour designed for use on measurement campaigns for both atmospheric case studies and instrument intercomparisons. MIAWARA-C's retrieval version 1.1 (v1.1) is set up in a such way as to provide a consistent data set even if the instrument is operated from different locations on a campaign basis. The sensitive altitude range for v1.1 extends from 4 hPa (37 km) to 0.017 hPa (75 km). For v1.1 the estimated systematic error is approximately 10% for all altitudes. At lower altitudes it is dominated by uncertainties in the calibration, with altitude the influence of spectroscopic and temperature uncertainties increases. The estimated random error increases with altitude from 5 to 25%. MIAWARA-C measures two polarisations of the incident radiation in separate receiver channels, and can therefore provide two measurements of the same air mass with independent instrumental noise. The standard deviation of the difference between the profiles obtained from the two polarisations is in excellent agreement with the estimated random measurement error of v1.1. In this paper, the quality of v1.1 data is assessed for measurements obtained at two different locations: (1) a total of 25 months of measurements in the Arctic (Sodankylä, 67.37° N, 26.63° E) and (2) nine months of measurements at mid-latitudes (Zimmerwald, 46.88° N, 7.46° E). For both locations MIAWARA-C's profiles are compared to measurements from the satellite experiments Aura MLS and MIPAS. In addition, comparisons to ACE-FTS and SOFIE are presented for the Arctic and to the ground-based radiometer MIAWARA for the mid-latitude campaigns. In general, all intercomparisons show high correlation coefficients, confirming the ability of MIAWARA-C to monitor temporal variations of the order of days. The biases are generally below 13% and within the estimated systematic uncertainty of MIAWARA-C. No consistent wet or dry bias is identified for MIAWARA-C. In addition, comparisons to the reference instruments indicate the estimated random error of v1.1 to be a realistic measure of the random variation on the retrieved profile between 45 and 70 km.
Resumo:
The ground-based radiometer GROMOS, stationed in Bern (47.95° N, 7.44° E), Switzerland, has a unique dataset: it obtains ozone profiles from November 1994 to present with a time resolution of 30 min and equal quality during night- and daytime. Here, we derive a monthly climatology of the daily ozone cycle from 17 yr of GROMOS observation. We present the diurnal ozone variation of the stratosphere and mesosphere. Characterizing the diurnal cycle of stratospheric ozone is important for correct trend estimates of the ozone layer derived from satellite observations. The diurnal ozone cycle from GROMOS is compared to two models: The Whole Atmosphere Community Climate Model (WACCM) and the Hamburg Model of Neutral and Ionized Atmosphere (HAMMONIA). Aura Microwave Limb Sounder (Aura/MLS) ozone data, from night- and daytime overpasses over Bern, have also been included in the comparison. Generally, observation and models show good qualitative agreement: in the lower mesosphere, daytime ozone is for both GROMOS and models around 25% less than nighttime ozone (reference is 22:30–01:30). In the stratosphere, ozone reaches its maximum in the afternoon showing values several percent larger than the midnight value. It is important that diurnal ozone variations of this order are taken into account when merging different data sets for the derivation of long-term ozone trends in the stratosphere. Further, GROMOS and models indicate a seasonal behavior of daily ozone variations in the stratosphere with a larger afternoon maximum during daytime in summer than in winter. At 0.35 hPa, observations from GROMOS and Aura/MLS show a seasonal pattern in diurnal ozone variations with larger relative amplitudes during daytime in winter (−25 ± 5%) than in summer (−18 ± 4%) (compared to mean values around midnight). For the first time, a time series of the diurnal variations in ozone is presented: 17 yr of GROMOS data show strong interannual variations in the diurnal ozone cycle for both the stratosphere and the mesosphere. There are some indications that strong temperature tides can suppress the diurnal variation of stratospheric ozone via the anticorrelation of temperature and ozone. That means the spatio-temporal variability of solar thermal tides seems to affect the diurnal cycle of stratospheric ozone.
Resumo:
Objective: Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. Method: TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. Results: TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. Conclusions: TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy.
Resumo:
The ground-based radiometer GROMOS, stationed in Bern (47.95° N, 7.44° E), Switzerland, has a unique dataset: it obtains ozone profiles from November 1994 to present with a time resolution of 30 min and equal quality during night- and daytime. Here, we derive a monthly climatology of the daily ozone cycle from 17 yr of GROMOS observation. We present the diurnal ozone variation of the stratosphere and mesosphere. Characterizing the diurnal cycle of stratospheric ozone is important for correct trend estimates of the ozone layer derived from satellite observations. The diurnal ozone cycle from GROMOS is compared to two models: The Whole Atmosphere Community Climate Model (WACCM) and the Hamburg Model of Neutral and Ionized Atmosphere (HAMMONIA). Aura Microwave Limb Sounder (Aura/MLS) ozone data, from night- and daytime overpasses over Bern, have also been included in the comparison. Generally, observation and models show good qualitative agreement: in the lower mesosphere, daytime ozone is for both GROMOS and models around 25% less than nighttime ozone (reference is 22:30–01:30). In the stratosphere, ozone reaches its maximum in the afternoon showing values several percent larger than the midnight value. It is important that diurnal ozone variations of this order are taken into account when merging different data sets for the derivation of long-term ozone trends in the stratosphere. Further, GROMOS and models indicate a seasonal behavior of daily ozone variations in the stratosphere with a larger afternoon maximum during daytime in summer than in winter. At 0.35 hPa, observations from GROMOS and Aura/MLS show a seasonal pattern in diurnal ozone variations with larger relative amplitudes during daytime in winter (−25 ± 5%) than in summer (−18 ± 4%) (compared to mean values around midnight). For the first time, a time series of the diurnal variations in ozone is presented: 17 yr of GROMOS data show strong interannual variations in the diurnal ozone cycle for both the stratosphere and the mesosphere. There are some indications that strong temperature tides can suppress the diurnal variation of stratospheric ozone via the anticorrelation of temperature and ozone. That means the spatio-temporal variability of solar thermal tides seems to affect the diurnal cycle of stratospheric ozone.
Resumo:
* Hundreds of experiments have now manipulated species richness (SR) of various groups of organisms and examined how this aspect of biological diversity influences ecosystem functioning. Ecologists have recently expanded this field to look at whether phylogenetic diversity (PD) among species, often quantified as the sum of branch lengths on a molecular phylogeny leading to all species in a community, also predicts ecological function. Some have hypothesized that phylogenetic divergence should be a superior predictor of ecological function than SR because evolutionary relatedness represents the degree of ecological and functional differentiation among species. But studies to date have provided mixed support for this hypothesis. * Here, we reanalyse data from 16 experiments that have manipulated plant SR in grassland ecosystems and examined the impact on above-ground biomass production over multiple time points. Using a new molecular phylogeny of the plant species used in these experiments, we quantified how the PD of plants impacts average community biomass production as well as the stability of community biomass production through time. * Using four complementary analyses, we show that, after statistically controlling for variation in SR, PD (the sum of branches in a molecular phylogenetic tree connecting all species in a community) is neither related to mean community biomass nor to the temporal stability of biomass. These results run counter to past claims. However, after controlling for SR, PD was positively related to variation in community biomass over time due to an increase in the variances of individual species, but this relationship was not strong enough to influence community stability. * In contrast to the non-significant relationships between PD, biomass and stability, our analyses show that SR per se tends to increase the mean biomass production of plant communities, after controlling for PD. The relationship between SR and temporal variation in community biomass was either positive, non-significant or negative depending on which analysis was used. However, the increases in community biomass with SR, independently of PD, always led to increased stability. These results suggest that PD is no better as a predictor of ecosystem functioning than SR. * Synthesis. Our study on grasslands offers a cautionary tale when trying to relate PD to ecosystem functioning suggesting that there may be ecologically important trait and functional variation among species that is not explained by phylogenetic relatedness. Our results fail to support the hypothesis that the conservation of evolutionarily distinct species would be more effective than the conservation of SR as a way to maintain productive and stable communities under changing environmental conditions.
Resumo:
1. Recent theoretical studies suggest that the stability of ecosystem processes is not governed by diversity per se, but by multitrophic interactions in complex communities. However, experimental evidence supporting this assumption is scarce.2. We investigated the impact of plant diversity and the presence of above- and below-ground invertebrates on the stability of plant community productivity in space and time, as well as the interrelationship between both stability measures in experimental grassland communities.3. We sampled above-ground plant biomass on subplots with manipulated above- and below-ground invertebrate densities of a grassland biodiversity experiment (Jena Experiment) 1, 4 and 6 years after the establishment of the treatments to investigate temporal stability. Moreover, we harvested spatial replicates at the last sampling date to explore spatial stability.4. The coefficient of variation of spatial and temporal replicates served as a proxy for ecosystem stability. Both spatial and temporal stability increased to a similar extent with plant diversity. Moreover, there was a positive correlation between spatial and temporal stability, and elevated plant density might be a crucial factor governing the stability of diverse plant communities.5. Above-ground insects generally increased temporal stability, whereas impacts of both earthworms and above-ground insects depended on plant species richness and the presence of grasses. These results suggest that inconsistent results of previous studies on the diversity–stability relationship have in part been due to neglecting higher trophic-level interactions governing ecosystem stability.6. Changes in plant species diversity in one trophic level are thus unlikely to mirror changes in multitrophic interrelationships. Our results suggest that both above- and below-ground invertebrates decouple the relationship between spatial and temporal stability of plant community productivity by differently affecting the homogenizing mechanisms of plants in diverse plant communities.7.Synthesis. Species extinctions and accompanying changes in multitrophic interactions are likely to result not only in alterations in the magnitude of ecosystem functions but also in its variability complicating the assessment and prediction of consequences of current biodiversity loss.