108 resultados para Compression rates
Resumo:
The extraterrestrial solar spectrum (ESS) is an important component in near infrared (near-IR) radiative transfer calculations. However, the impact of a particular choice of the ESS in these regions has been given very little attention. A line-by-line (LBL) transfer model has been used to calculate the absorbed solar irradiance and solar heating rates in the near-IR from 2000-10000 cm−1(1-5 μm) using different ESS. For overhead sun conditions in a mid-latitude summer atmosphere, the absorbed irradiances could differ by up to about 11 Wm−2 (8.2%) while the tropospheric and stratospheric heating rates could differ by up to about 0.13 K day−1 (8.1%) and 0.19 K day−1 (7.6%). The spectral shape of the ESS also has a small but non-negligible impact on these factors in the near-IR.
Resumo:
BACKGROUND: The English Improving Access to Psychological Therapies (IAPT) initiative aims to make evidence-based psychological therapies for depression and anxiety disorder more widely available in the National Health Service (NHS). 32 IAPT services based on a stepped care model were established in the first year of the programme. We report on the reliable recovery rates achieved by patients treated in the services and identify predictors of recovery at patient level, service level, and as a function of compliance with National Institute of Health and Care Excellence (NICE) Treatment Guidelines. METHOD: Data from 19,395 patients who were clinical cases at intake, attended at least two sessions, had at least two outcomes scores and had completed their treatment during the period were analysed. Outcome was assessed with the patient health questionnaire depression scale (PHQ-9) and the anxiety scale (GAD-7). RESULTS: Data completeness was high for a routine cohort study. Over 91% of treated patients had paired (pre-post) outcome scores. Overall, 40.3% of patients were reliably recovered at post-treatment, 63.7% showed reliable improvement and 6.6% showed reliable deterioration. Most patients received treatments that were recommended by NICE. When a treatment not recommended by NICE was provided, recovery rates were reduced. Service characteristics that predicted higher reliable recovery rates were: high average number of therapy sessions; higher step-up rates among individuals who started with low intensity treatment; larger services; and a larger proportion of experienced staff. CONCLUSIONS: Compliance with the IAPT clinical model is associated with enhanced rates of reliable recovery.
Resumo:
Body size affects nearly all aspects of organismal biology, so it is important to understand the constraints and dynamics of body size evolution. Despite empirical work on the macroevolution and macroecology of minimum and maximum size, there is little general quantitative theory on rates and limits of body size evolution. We present a general theory that integrates individual productivity, the lifestyle component of the slow–fast life-history continuum, and the allometric scaling of generation time to predict a clade's evolutionary rate and asymptotic maximum body size, and the shape of macroevolutionary trajectories during diversifying phases of size evolution. We evaluate this theory using data on the evolution of clade maximum body sizes in mammals during the Cenozoic. As predicted, clade evolutionary rates and asymptotic maximum sizes are larger in more productive clades (e.g. baleen whales), which represent the fast end of the slow–fast lifestyle continuum, and smaller in less productive clades (e.g. primates). The allometric scaling exponent for generation time fundamentally alters the shape of evolutionary trajectories, so allometric effects should be accounted for in models of phenotypic evolution and interpretations of macroevolutionary body size patterns. This work highlights the intimate interplay between the macroecological and macroevolutionary dynamics underlying the generation and maintenance of morphological diversity.
Resumo:
BACKGROUND: Accelerated gastric emptying (GE) may lead to reduced satiation, increased food intake and is associated with obesity and type 2 diabetes. Domperidone is a dopamine 2 (D(2)) receptor antagonist with claims of gastrointestinal tract pro-kinetic activity. In humans, domperidone is used as an anti-emetic and treatment for gastrointestinal bloating and discomfort. AIM: To determine the effect of acute domperidone administration on GE rate and appetite sensations in healthy adults. METHODS: A single-blind block randomised placebo-controlled crossover study assessed 13 healthy adults. Subjects ingested 10 mg domperidone or placebo 30 min before a high-fat (HF) test meal. GE rate was determined using the (13)CO(2) octanoic acid breath test. Breath samples and subjective appetite ratings were collected in the fasted and during the 360 min postprandial period. RESULTS:Gastric emptying half-time was similar following placebo (254 ± 54 min) and 10 mg domperidone (236 ± 65 min). Domperidone did not change appetite sensations during the 360 min postprandial period (P > 0.05). CONCLUSIONS: In healthy adults, acute administration of 10 mg domperidone did not change GE or appetite sensations following a HF test meal.
Resumo:
As new buildings are constructed in response to changes in technology or user requirements, the value of the existing stock will decline in relative terms. This is termed economic depreciation and it may be influenced by the age and quality of buildings, amount and timing of expenditure, and wider market and economic conditions. This study tests why individual assets experience different depreciation rates, applying panel regression techniques to 375 UK office and industrial assets. Results suggest that rental value depreciation rates reduce as buildings get older, while a composite measure of age and quality provides more explanation of depreciation than age alone. Furthermore, economic and local real estate market conditions are significant in explaining how depreciation rates change over time.
Resumo:
This study examines the impact of foreign real estate investment on the US office market capitalization rates. The geographic unit of analysis is MSA and the time period is 2001-2013. Drawing upon a database of commercial real estate transactions provided by Real Capital Analytics, we model the determinants of market capitalization rates with a particular focus on the significance of the proportion of market transactions involving foreign investors. We have employed several econometric techniques to explore the data, potential estimation biases, and test robustness of the results. The results suggest statistically significant effects of foreign investment across 38 US metro areas. It is estimated that, all else equal, a 100 basis points increase in foreign share of total investment in a US metropolitan office market causes about an 8 basis points decrease in the market cap rate.
Resumo:
Using a variation of the Nelson-Siegel term structure model we examine the sensitivity of real estate securities in six key global markets to unexpected changes in the level, slop and curvature of the yield curve. Our results confirm the time-sensitive nature of the exposure and sensitivity to interest rates and highlight the importance of considering the entire term structure of interest rates. One issue that is of particular of interest is that despite the 2007-9 financial crisis the importance of unanticipated interest rate risk weakens post 2003. Although the analysis does examine a range of markets the empirical analysis is unable to provide definitive evidence as to whether REIT and property-company markets display heightened or reduced exposure.
Resumo:
Accurate high-resolution records of snow accumulation rates in Antarctica are crucial for estimating ice sheet mass balance and subsequent sea level change. Snowfall rates at Law Dome, East Antarctica, have been linked with regional atmospheric circulation to the mid-latitudes as well as regional Antarctic snowfall. Here, we extend the length of the Law Dome accumulation record from 750 years to 2035 years, using recent annual layer dating that extends to 22 BCE. Accumulation rates were calculated as the ratio of measured to modelled layer thicknesses, multiplied by the long-term mean accumulation rate. The modelled layer thicknesses were based on a power-law vertical strain rate profile fitted to observed annual layer thickness. The periods 380–442, 727–783 and 1970–2009 CE have above-average snow accumulation rates, while 663–704, 933–975 and 1429–1468 CE were below average, and decadal-scale snow accumulation anomalies were found to be relatively common (74 events in the 2035-year record). The calculated snow accumulation rates show good correlation with atmospheric reanalysis estimates, and significant spatial correlation over a wide expanse of East Antarctica, demonstrating that the Law Dome record captures larger-scale variability across a large region of East Antarctica well beyond the immediate vicinity of the Law Dome summit. Spectral analysis reveals periodicities in the snow accumulation record which may be related to El Niño–Southern Oscillation (ENSO) and Interdecadal Pacific Oscillation (IPO) frequencies.
Resumo:
Although estimation of turbulent transport parameters using inverse methods is not new, there is little evaluation of the method in the literature. Here, it is shown that extended observation of the broad scale hydrography by Argo provides a path to improved estimates of regional turbulent transport rates. Results from a 20 year ocean state estimate produced with the ECCO v4 non-linear inverse modeling framework provide supporting evidence. Turbulent transport parameter maps are estimated under the constraints of fitting the extensive collection of Argo profiles collected through 2011. The adjusted parameters dramatically reduce misfits to in situ profiles as compared with earlier ECCO solutions. They also yield a clear reduction in the model drift away from observations over multi-century long simulations, both for assimilated variables (temperature and salinity) and independent variables (bio-geochemical tracers). Despite the minimal constraints imposed specifically on the estimated parameters, their geography is physically plausible and exhibits close connections with the upper ocean ocean stratification as observed by Argo. The estimated parameter adjustments furthermore have first order impacts on upper-ocean stratification and mixed layer depths over 20 years. These results identify the constraint of fitting Argo profiles as an effective observational basis for regional turbulent transport rates. Uncertainties and further improvements of the method are discussed.
Resumo:
Ants often form mutualistic interactions with aphids, soliciting honeydew in return for protective services. Under certain circumstances, however, ants will prey upon aphids. In addition, in the presence of ants aphids may increase the quantity or quality of honeydew produced, which is costly. Through these mechanisms, ant attendance can reduce aphid colony growth rates. However, it is unknown whether demand from within the ant colony can affect the ant-aphid interaction. In a factorial experiment, we tested whether the presence of larvae in Lasius niger ant colonies affected the growth rate of Aphis fabae colonies. Other explanatory variables tested were the origin of ant colonies (two separate colonies were used) and previous diet (sugar only or sugar and protein). We found that the presence of larvae in the ant colony significantly reduced the growth rate of aphid colonies. Previous diet and colony origin did not affect aphid colony growth rates. Our results suggest that ant colonies balance the flow of two separate resources from aphid colonies- renewable sugars or a protein-rich meal, depending on demand from ant larvae within the nest. Aphid payoffs from the ant-aphid interaction may change on a seasonal basis, as the demand from larvae within the ant colony waxes and wanes.
Resumo:
Partial budgeting was used to estimate the net benefit of blending Jersey milk in Holstein-Friesian milk for Cheddar cheese production. Jersey milk increases Cheddar cheese yield. However, the cost of Jersey milk is also higher; thus, determining the balance of profitability is necessary, including consideration of seasonal effects. Input variables were based on a pilot plant experiment run from 2012 to 2013 and industry milk and cheese prices during this period. When Jersey milk was used at an increasing rate with Holstein-Friesian milk (25, 50, 75, and 100% Jersey milk), it resulted in an increase of average net profit of 3.41, 6.44, 8.57, and 11.18 pence per kilogram of milk, respectively, and this additional profit was constant throughout the year. Sensitivity analysis showed that the most influential input on additional profit was cheese yield, whereas cheese price and milk price had a small effect. The minimum increase in yield, which was necessary for the use of Jersey milk to be profitable, was 2.63, 7.28, 9.95, and 12.37% at 25, 50, 75, and 100% Jersey milk, respectively. Including Jersey milk did not affect the quantity of whey butter and powder produced. Althoug further research is needed to ascertain the amount of additional profit that would be found on a commercial scale, the results indicate that using Jersey milk for Cheddar cheese making would lead to an improvement in profit for the cheese makers, especially at higher inclusion rates.
Resumo:
Lightning flash rates, RL, are modulated by corotating interaction regions (CIRs) and the polarity of the heliospheric magnetic field (HMF) in near-Earth space. As the HMF polarity reverses at the heliospheric current sheet (HCS), typically within a CIR, these phenomena are likely related. In this study, RL is found to be significantly enhanced at the HCS and at 27 days prior/after. The strength of the enhancement depends on the polarity of the HMF reversal at the HCS. Near-Earth solar and galactic energetic particle fluxes are also ordered by HMF polarity, though the variations qualitatively differ from RL, with the main increase occurring prior to the HCS crossing. Thus, the CIR effect on lightning is either the result of compression/amplification of the HMF (and its subsequent interaction with the terrestrial system) or that energetic particle preconditioning of the Earth system prior to the HMF polarity change is central to solar wind lightning coupling mechanism.
Resumo:
Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.