103 resultados para Stocking Rates


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Simulations of ozone loss rates using a three-dimensional chemical transport model and a box model during recent Antarctic and Arctic winters are compared with experimental loss rates. The study focused on the Antarctic winter 2003, during which the first Antarctic Match campaign was organized, and on Arctic winters 1999/2000, 2002/2003. The maximum ozone loss rates retrieved by the Match technique for the winters and levels studied reached 6 ppbv/sunlit hour and both types of simulations could generally reproduce the observations at 2-sigma error bar level. In some cases, for example, for the Arctic winter 2002/2003 at 475 K level, an excellent agreement within 1-sigma standard deviation level was obtained. An overestimation was also found with the box model simulation at some isentropic levels for the Antarctic winter and the Arctic winter 1999/2000, indicating an overestimation of chlorine activation in the model. Loss rates in the Antarctic show signs of saturation in September, which have to be considered in the comparison. Sensitivity tests were performed with the box model in order to assess the impact of kinetic parameters of the ClO-Cl2O2 catalytic cycle and total bromine content on the ozone loss rate. These tests resulted in a maximum change in ozone loss rates of 1.2 ppbv/sunlit hour, generally in high solar zenith angle conditions. In some cases, a better agreement was achieved with fastest photolysis of Cl2O2 and additional source of total inorganic bromine but at the expense of overestimation of smaller ozone loss rates derived later in the winter.

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Zinc (Zn)-deficient soils constrain rice (Oryza sativa) production and cause Zn malnutrition. The identification of Zn-deficiency-tolerant rice lines indicates that breeding might overcome these constraints. Here, we seek to identify processes underlying Zn-deficiency tolerance in rice at the physiological and transcriptional levels. A Zn-deficiency-tolerant line RIL46 acquires Zn more efficiently and produces more biomass than its nontolerant maternal line (IR74) at low Zn(ext) under field conditions. We tested if this was the result of increased expression of Zn(2+) transporters; increased root exudation of deoxymugineic acid (DMA) or low-molecular-weight organic acids (LMWOAs); and/or increased root production. Experiments were performed in field and controlled environment conditions. There was little genotypic variation in transcript abundance of Zn-responsive root Zn(2+)-transporters between the RIL46 and IR74. However, root exudation of DMA and LMWOA was greater in RIL46, coinciding with increased root expression of putative ligand-efflux genes. Adventitious root production was maintained in RIL46 at low Zn(ext), correlating with altered expression of root-specific auxin-responsive genes. Zinc-deficiency tolerance in RIL46 is most likely the result of maintenance of root growth, increased efflux of Zn ligands, and increased uptake of Zn-ligand complexes at low Zn(ext); these traits are potential breeding targets.

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Recent studies have indicated that research practices in psychology may be susceptible to factors that increase false-positive rates, raising concerns about the possible prevalence of false-positive findings. The present article discusses several practices that may run counter to the inflation of false-positive rates. Taking these practices into account would lead to a more balanced view on the false-positive issue. Specifically, we argue that an inflation of false-positive rates would diminish, sometimes to a substantial degree, when researchers (a) have explicit a priori theoretical hypotheses, (b) include multiple replication studies in a single paper, and (c) collect additional data based on observed results. We report findings from simulation studies and statistical evidence that support these arguments. Being aware of these preventive factors allows researchers not to overestimate the pervasiveness of false-positives in psychology and to gauge the susceptibility of a paper to possible false-positives in practical and fair ways.

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We consider the forecasting performance of two SETAR exchange rate models proposed by Kräger and Kugler [J. Int. Money Fin. 12 (1993) 195]. Assuming that the models are good approximations to the data generating process, we show that whether the non-linearities inherent in the data can be exploited to forecast better than a random walk depends on both how forecast accuracy is assessed and on the ‘state of nature’. Evaluation based on traditional measures, such as (root) mean squared forecast errors, may mask the superiority of the non-linear models. Generalized impulse response functions are also calculated as a means of portraying the asymmetric response to shocks implied by such models.

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We test whether there are nonlinearities in the response of short- and long-term interest rates to the spread in interest rates, and assess the out-of-sample predictability of interest rates using linear and nonlinear models. We find strong evidence of nonlinearities in the response of interest rates to the spread. Nonlinearities are shown to result in more accurate short-horizon forecasts, especially of the spread.

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This paper proposes two new tests for linear and nonlinear lead/lag relationships between time series based on the concepts of cross-correlations and cross-bicorrelations, respectively. The tests are then applied to a set of Sterling-denominated exchange rates. Our analysis indicates that there existed periods during the post-Bretton Woods era where the temporal relationship between different exchange rates was strong, although these periods have become less frequent over the past 20 years. In particular, our results demonstrate the episodic nature of the nonlinearity, and have implications for the speed of flow of information between financial series. The method generalises recently proposed tests for nonlinearity to the multivariate context.

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This paper considers the effect of short- and long-term interest rates, and interest rate spreads upon real estate index returns in the UK. Using Johansen's vector autoregressive framework, it is found that the real estate index cointegrates with the term spread, but not with the short or long rates themselves. Granger causality tests indicate that movements in short term interest rates and the spread cause movements in the returns series. However, decomposition of the forecast error variances from VAR models indicate that changes in these variables can only explain a small proportion of the overall variability of the returns, and that the effect has fully worked through after two months. The results suggest that these financial variables could potentially be used as leading indicators for real estate markets, with corresponding implications for return predictability.

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We examine a method recently proposed by Hinich and Patterson (mimeo, University of Texas at Austin, 1995) for testing the validity of specifying a GARCH error structure for financial time series data in the context of a set of ten daily Sterling exchange rates. The results demonstrate that there are statistical structures present in the data that cannot be captured by a GARCH model, or any of its variants. This result has important implications for the interpretation of the recent voluminous literature which attempts to model financial asset returns using this family of models.

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This paper forecasts Daily Sterling exchange rate returns using various naive, linear and non-linear univariate time-series models. The accuracy of the forecasts is evaluated using mean squared error and sign prediction criteria. These show only a very modest improvement over forecasts generated by a random walk model. The Pesaran–Timmerman test and a comparison with forecasts generated artificially shows that even the best models have no evidence of market timing ability.

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A number of tests for non-linear dependence in time series are presented and implemented on a set of 10 daily sterling exchange rates covering the entire post Bretton-Woods era until the present day. Irrefutable evidence of non-linearity is shown in many of the series, but most of this dependence can apparently be explained by reference to the GARCH family of models. It is suggested that the literature in this area has reached an impasse, with the presence of ARCH effects clearly demonstrated in a large number of papers, but with the tests for non-linearity which are currently available being unable to classify any additional non-linear structure.

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An alternative procedure to that of Lo is proposed for assessing whether there is significant evidence of persistence in time series. The technique estimates the Hurst exponent itself, and significance testing is based on an application of bootstrapping using surrogate data. The method is applied to a set of 10 daily pound exchange rates. A general lack of long-term memory is found to characterize all the series tested, in sympathy with the findings of a number of other recent papers which have used Lo's techniques.

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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.

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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.