980 resultados para note-taking


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Numerous factors are associated with poverty and underdevelopment in Africa, including climate variability. Rainfall, and climate more generally, are implicated directly in the United Nations “Millennium Development Goals” to eradicate extreme poverty and hunger, and reduce child mortality and incidence of diseases such as malaria by the target date of 2015. But, Africa is not currently on target to meet these goals. We pose a number of questions from a climate science perspective aimed at understanding this background: Is there a common origin to factors that currently constrain climate science? Why is it that in a continent where human activity is so closely linked to interannual rainfall variability has climate science received little of the benefit that saw commercialization driving meteorology in the developed world? What might be suggested as an effective way for the continent to approach future climate variability and change? We make the case that a route to addressing the challenges of climate change in Africa rests with the improved management of climate variability. We start by discussing the constraints on climate science and how they might be overcome. We explain why the optimal management of activities directly influenced by interannual climate variability (which include the development of scientific capacity) has the potential to serve as a forerunner to engagement in the wider issue of climate change. We show this both from the perspective of the climate system and the institutions that engage with climate issues. We end with a thought experiment that tests the benefits of linking climate variability and climate change in the setting of smallholder farmers in Limpopo Province, South Africa.

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This Note outlines the further development of a system of models for the estimation of the costs of livestock diseases first presented by Bennett (2003). The models have been developed to provide updated and improved estimates of the costs associated with 34 endemic diseases of livestock in Great Britain, using border prices and including assessments of the impact of diseases on human health and animal welfare. Results show that, of the diseases studied, mastitis has the highest costs for cattle diseases, enzootic abortion for sheep diseases, swine influenza for pig diseases and salmonellosis for poultry diseases.

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This note reports on the results of a choice experiment survey of 400 people in England and Wales, conducted to estimate the value that society places on changes to the size of the badger population. The study was undertaken in the context of the possible need to reduce the badger population by culling to help control bovine tuberculosis in cattle. The study found that people were concerned about the problem of bovine tuberculosis in cattle, which was reflected in their willingness to pay to control the disease, and gave a relatively low value to changes in the size of the badger population (within limits). However, people did not like the idea of a policy that intentionally killed large numbers of badgers and had a relatively very high willingness to pay not to have such a policy.

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A method is proposed to determine the extent of degradation in the rumen involving a two-stage mathematical modeling process. In the first stage, a statistical model shifts (or maps) the gas accumulation profile obtained using a fecal inoculum to a ruminal gas profile. Then, a kinetic model determines the extent of degradation in the rumen from the shifted profile. The kinetic model is presented as a generalized mathematical function, allowing any one of a number of alternative equation forms to be selected. This method might allow the gas production technique to become an approach for determining extent of degradation in the rumen, decreasing the need for surgically modified animals while still maintaining the link with the animal. Further research is needed before the proposed methodology can be used as a standard method across a range of feeds.

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This note presents a robust method for estimating response surfaces that consist of linear response regimes and a linear plateau. The linear response-and-plateau model has fascinated production scientists since von Liebig (1855) and, as Upton and Dalton indicated, some years ago in this Journal, the response-and-plateau model seems to fit the data in many empirical studies. The estimation algorithm evolves from Bayesian implementation of a switching-regression (finite mixtures) model and demonstrates routine application of Gibbs sampling and data augmentation-techniques that are now in widespread application in other disciplines.

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A model was published by Lewis et al. (2002) to predict the mean age at first egg (AFE) for pullets of laying strains reared under non-limiting environmental conditions and exposed to a single change in photoperiod during the rearing stage. Subsequently, Lewis et al. (2003) reported the effects of two opposing changes in photoperiod, which showed that the first change appears to alter the pullet's physiological age so that it responds to the second change as though it had been given at an earlier age (if photoperiod was decreased), or later age (if photoperiod was increased) than the true chronological age. During the construction of a computer model based on these two publications, it became apparent that some of the components of the models needed adjustment. The amendments relate to (1) the standard deviation (S.D.) used for calculating the proportion of a young flock that has attained photosensitivity, (2) the equation for calculating the slope of the line relating AFE to age at transfer from one photoperiod to another, (3) the equation used for estimating the distribution of AFE as a function of the mean value, (4) the point of no return when pullets which have started spontaneous maturation in response to the current photoperiod can no longer respond to a late change in photoperiod and (5) the equations used for calculating the distribution of AFE when the trait is bimodal.

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Tropospheric ozone is an air pollutant thought to reduce crop yields across Europe. Much experimental scientific work has been completed or is currently underway to quantify yield effects at ambient ozone levels. In this research, we seek to directly evaluate whether such effects are observed at the farm level. This is done by intersecting a farm level panel dataset for winter wheat farms in England & Wales with information on ambient ozone, and estimating a production function with ozone as a fixed input. Panel data methods, Generalised Method of Moments (GMM) techniques and nested exogeneity tests are employed in the estimation. The results confirm a small, but nevertheless statistically significant negative effect of ambient ozone levels on wheat yields.

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Diebold and Lamb (1997) argue that since the long-run elasticity of supply derived from the Nerlovian model entails a ratio of random variables, it is without moments. They propose minimum expected loss estimation to correct this problem but in so-doing ignore the fact that a non white-noise-error is implicit in the model. We show that, as a consequence the estimator is biased and demonstrate that Bayesian estimation which fully accounts for the error structure is preferable.

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Stephens and Donnelly have introduced a simple yet powerful importance sampling scheme for computing the likelihood in population genetic models. Fundamental to the method is an approximation to the conditional probability of the allelic type of an additional gene, given those currently in the sample. As noted by Li and Stephens, the product of these conditional probabilities for a sequence of draws that gives the frequency of allelic types in a sample is an approximation to the likelihood, and can be used directly in inference. The aim of this note is to demonstrate the high level of accuracy of "product of approximate conditionals" (PAC) likelihood when used with microsatellite data. Results obtained on simulated microsatellite data show that this strategy leads to a negligible bias over a wide range of the scaled mutation parameter theta. Furthermore, the sampling variance of likelihood estimates as well as the computation time are lower than that obtained with importance sampling on the whole range of theta. It follows that this approach represents an efficient substitute to IS algorithms in computer intensive (e.g. MCMC) inference methods in population genetics. (c) 2006 Elsevier Inc. All rights reserved.

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Background Hawthorn (Crataegus laevigata) leaves, flowers and berries are used by herbal practitioners in the UK to treat hypertension in conjunction with prescribed drugs. Small-scale human studies support this approach. Aim To investigate the effects of hawthorn for hypertension in patients with type 2 diabetes taking prescribed drugs. Design of study Randomised controlled trial. Setting General practices in Reading, UK. Method Patients with type 2 diabetes (n = 79) were randomised to daily 1200 mg hawthorn extract (n = 39) or placebo (n = 40) for 16 weeks. At baseline and outcome a wellbeing questionnaire was completed and blood pressure and fasting blood samples taken. A food frequency questionnaire estimated nutrient intake. Results Hypotensive drugs were used by 71% of the study population with a mean intake of 4.4 hypoglycaemic and/or hypotensive drugs. Fat intake was lower and sugar intake higher than recommendations, and low micronutrient intake was prevalent. There was a significant group difference in mean diastolic blood pressure reductions (P = 0.035): the hawthorn group showed greater reductions (baseline: 85.6 mmHg, 95% confidence interval [Cl] = 83.3 to 87.8; outcome: 83.0 mmHg, 95% Cl = 80.5 to 85.7) than the placebo group (baseline: 84.5 mmHg, 95% Cl = 82 to 87; outcome: 85.0 mmHg, 95% Cl = 82.2 to 87.8). There was no group difference in systolic blood pressure reduction from baseline (3.6 and 0.8 mmHg for hawthorn and placebo groups, respectively; P = 0.329). Although mean fat intake met current recommendations, mean sugar intake was higher and there were indications of potential multiple micronutrient deficiencies. No herb-drug interaction was found and minor health complaints were reduced from baseline in both groups. Conclusions This is the first randomised controlled trial to demonstrate a hypotensive effect of hawthorn in patients with diabetes taking medication.

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Background: Hawthorn (Crataegus laevigata) leaves, flowers and berries are used by herbal practitioners in the UK to treat hypertension in conjunction with prescribed drugs. Small-scale human studies support this approach. Aim: To investigate the effects of hawthorn for hypertension in patients with type 2 diabetes taking prescribed drugs. Design of study: Randomised controlled trial. Setting: General practices in Reading, UK. Method: Patients with type 2 diabetes (n = 79) were randomised to daily 1200 mg hawthorn extract (n = 39) or placebo (n = 40) for 16 weeks. At baseline and outcome a wellbeing questionnaire was completed and blood pressure and fasting blood samples taken. A food frequency questionnaire estimated nutrient intake. Results: Hypotensive drugs were used by 71% of the study population with a mean intake of 4.4 hypoglycaemic and/or hypotensive drugs. Fat intake was lower and sugar intake higher than recommendations, and low micronutrient intake was prevalent. There was a significant group difference in mean diastolic blood pressure reductions (P = 0.035): the hawthorn group showed greater reductions (baseline: 85.6 mmHg, 95% confidence interval [Cl] = 83.3 to 87.8; outcome: 83.0 mmHg, 95% Cl = 80.5 to 85.7) than the placebo group (baseline: 84.5 mmHg, 95% Cl = 82 to 87; outcome: 85.0 mmHg, 95% Cl = 82.2 to 87.8). There was no group difference in systolic blood pressure reduction from baseline (3.6 and 0.8 mmHg for hawthorn and placebo groups, respectively; P = 0.329). Although mean fat intake met current recommendations, mean sugar intake was higher and there were indications of potential multiple micronutrient deficiencies. No herb-drug interaction was found and minor health complaints were reduced from baseline in both groups. Conclusions: This is the first randomised controlled trial to demonstrate a hypotensive effect of hawthorn in patients with diabetes taking medication.

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Skill and risk taking are argued to be independent and to require different remedial programs. However, it is possible to contend that skill-based training could be associated with an increase, a decrease, or no change in risk taking behavior. In 3 experiments, the authors examined the influence of a skill-based training program (hazard perception) on the risk taking behavior of car drivers (using video-based driving simulations). Experiment 1 demonstrated a decrease in risk taking for novice drivers. In Experiment 2, the authors examined the possibilities that the skills training might operate through either a nonspecific reduction in risk taking or a specific improvement in hazard perception. Evidence supported the latter. These findings were replicated in a more ecological context in Experiment 3, which compared advanced and nonadvanced police drivers.

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Although perceived health risk plays a prominent role in theories of health behavior, its empirical role in risk taking is less clear. In Study 1 (N = 129), 2 measures of drivers' risk-taking behavior were found to be unrelated to self-estimates of accident concern but to be related to self-ratings of driving skill and the perceived thrill of driving. In Study 2 (N = 405), out of a wide range of potential influences, accident concern had the weakest relationship with risk taking. The authors concluded that although health risk is a key feature in many theories of health behavior and a central focus for researchers and policy makers, it may not be such a prominent factor for those actually taking the risk.

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