648 resultados para Kyoto


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Chronic kidney disease (CKD) in ageing is a burden on health systems worldwide. Rat models of age-related CKD linked with obesity and hypertension were used to investigate alterations in oxidant handling and energy metabolism to identify gene targets or markers for age-related CKD. Young adult (3 months) and old (21–24 months) spontaneously-hypertensive (SHR), normotensive Wistar-Kyoto (WKY) and Wistar rats (normotensive, obese in ageing) were compared for renal functional and physiological parameters, renal fibrosis and inflammation, oxidative stress (hemeoxygenase-1/HO-1), apoptosis and cell injury (including Bax:Bcl-2), phosphorylated and non-phosphorylated forms of oxidant and energy sensing proteins (p66Shc, AMPK), signal transduction proteins (ERK1/2, PKB), and transcription factors (NF-κB, FoxO1). All old rats were normoglycemic. Renal fibrosis, tubular epithelial apoptosis, interstitial macrophages and myofibroblasts (all p < 0.05), p66Shc/phospho-p66 (p < 0.05), Bax/Bcl-2 ratio (p < 0.05) and NF-κB expression (p < 0.01) were highest in old obese Wistars. Expression of phospho-FoxO/FoxO was elevated in old Wistars (p < 0.001) and WKYs (p < 0.01). SHRs had high levels in young and old rats. Expression of PKB, phospho-PKB, ERK1/2 and phospho-ERK1/2 were significantly elevated in all aged animals. These results suggest that obesity and hypertension have differing oxidant handling and signalling pathways that act in the pathogenesis of age-related CKD

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Language contact is a significant external social factor that impacts on the change in natural languages over time. In some circumstances this corresponds to language competition, in which individuals in a population choose one language over another based on their social interactions. We investigated the dynamics of language change in two initially separate populations of agents that were then mixed with levels of influence determined by the social classes of the two populations, with 16 different combinations tested. As expected, the study found that how the communities interact with each other impacts on the communal language developed. However, it was also found that the acquisition of new words was substantial even with limited interaction between populations and low levels of influence, and that comprehension could be well established across language groups even when production of words from the other language group was low.

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Selection of features that will permit accurate pattern classification is a difficult task. However, if a particular data set is represented by discrete valued features, it becomes possible to determine empirically the contribution that each feature makes to the discrimination between classes. This paper extends the discrimination bound method so that both the maximum and average discrimination expected on unseen test data can be estimated. These estimation techniques are the basis of a backwards elimination algorithm that can be use to rank features in order of their discriminative power. Two problems are used to demonstrate this feature selection process: classification of the Mushroom Database, and a real-world, pregnancy related medical risk prediction task - assessment of risk of perinatal death.

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The Kyoto Protocol is remarkable among global multilateral environmental agreements for its efforts to depoliticize compliance. However, attempts to create autonomous, arm’s length and rule-based compliance processes with extensive reliance on putatively neutral experts were only partially realized in practice in the first commitment period from 2008 to 2012. In particular, the procedurally constrained facilitative powers vested in the Facilitative Branch were circumvented, and expert review teams (ERTs) assumed pivotal roles in compliance facilitation. The ad hoc diplomatic and facilitative practices engaged in by these small teams of technical experts raise questions about the reliability and consistency of the compliance process. For the future operation of the Kyoto compliance system, it is suggested that ERTs should be confined to more technical and procedural roles, in line with their expertise. There would then be greater scope for the Facilitative Branch to assume a more comprehensive facilitative role, safeguarded by due process guarantees, in accordance with its mandate. However, if – as appears likely – the future compliance trajectories under the United Nations Framework Convention on Climate Change will include a significant role for ERTs without oversight by the Compliance Committee, it is important to develop appropriate procedural safeguards that reflect and shape the various technical and political roles these teams currently play.

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Several algorithms and techniques widely used in Computer Science have been adapted from, or inspired by, known biological phenomena. This is a consequence of the multidisciplinary background of most early computer scientists. The field has now matured, and permits development of tools and collaborative frameworks which play a vital role in advancing current biomedical research. In this paper, we briefly present examples of the former, and elaborate upon two of the latter, applied to immunological modelling and as a new paradigm in gene expression.

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As computational models in fields such as medicine and engineering get more refined, resource requirements are increased. In a first instance, these needs have been satisfied using parallel computing and HPC clusters. However, such systems are often costly and lack flexibility. HPC users are therefore tempted to move to elastic HPC using cloud services. One difficulty in making this transition is that HPC and cloud systems are different, and performance may vary. The purpose of this study is to evaluate cloud services as a means to minimise both cost and computation time for large-scale simulations, and to identify which system properties have the most significant impact on performance. Our simulation results show that, while the performance of Virtual CPU (VCPU) is satisfactory, network throughput may lead to difficulties.

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Most real-life data analysis problems are difficult to solve using exact methods, due to the size of the datasets and the nature of the underlying mechanisms of the system under investigation. As datasets grow even larger, finding the balance between the quality of the approximation and the computing time of the heuristic becomes non-trivial. One solution is to consider parallel methods, and to use the increased computational power to perform a deeper exploration of the solution space in a similar time. It is, however, difficult to estimate a priori whether parallelisation will provide the expected improvement. In this paper we consider a well-known method, genetic algorithms, and evaluate on two distinct problem types the behaviour of the classic and parallel implementations.

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Cost-effective mitigation of climate change is essential for both climate and environmental policy. Forest rotation age is one of the silvicultural measures by which the forest carbon stocks can be influenced with in accordance with the Kyoto Protocol, Article 3.4. The purpose of this study is to evaluate how forest rotation age affects carbon sequestration and the profitability of forestry. The relation between the forest rotation period optimizing forest owners’ discounted net returns over time and rotations which are 10, 20 and 30 years longer than the optimal rotation is examined. In addition, the cost of lengthening the rotation period is studied as well as whether carbon sequestration revenues can improve the profitability of forestry. The data used in the study consist of 16 stands located in Southern Finland. The main tree species in these stands were Norway spruce and Scots pine. Forest simulation tool MOTTI was used in the analysis. The results indicate that by lengthening the rotation period forest carbon stocks increase. However, as the rotation period is lengthened by more than 10 years, as a result of the diminishing growth curve, the rate of carbon sequestration slows down. The average discounted cost of carbon sequestration varied between 2.4 – 14.1 €/tCO2. Carbon sequestration rates in spruce stands were higher and the costs lower than those obtained from pine stands. The absence of carbon trading schemes is an obstacle for the commercialization of forest carbon sinks. In the future, research should concentrate on analysing what kind of operational models of carbon trading could be feasible in Finland.

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Climate change is the single biggest environmental problem in the world at the moment. Although the effects are still not fully understood and there is considerable amount of uncertainty, many na-tions have decided to mitigate the change. On the societal level, a planner who tries to find an eco-nomically optimal solution to an environmental pollution problem seeks to reduce pollution from the sources where reductions are most cost-effective. This study aims to find out how effective the instruments of the agricultural policy are in the case of climate change mitigation in Finland. The theoretical base of this study is the neoclassical economic theory that is based on the assumption of a rational economic agent who maximizes his own utility. This theoretical base has been widened towards the direction clearly essential to the matter: the theory of environmental eco-nomics. Deeply relevant to this problem and central in the theory of environmental economics are the concepts of externalities and public goods. What are also relevant are the problems of global pollution and non-point-source pollution. Econometric modelling was the method that was applied to this study. The Finnish part of the AGMEMOD-model, covering the whole EU, was used for the estimation of the development of pollution. This model is a seemingly recursive, partially dynamic partial-equilibrium model that was constructed to predict the development of Finnish agricultural production of the most important products. For the study, I personally updated the model and also widened its scope in some relevant matters. Also, I devised a table that can calculate the emissions of greenhouse gases according to the rules set by the IPCC. With the model I investigated five alternative scenarios in comparison to the base-line scenario of Agenda 2000 agricultural policy. The alternative scenarios were: 1) the CAP reform of 2003, 2) free trade on agricultural commodities, 3) technological change, 4) banning the cultivation of organic soils and 5) the combination of the last three scenarios as the maximal achievement in reduction. The maximal achievement in the alternative scenario 5 was 1/3 of the level achieved on the base-line scenario. CAP reform caused only a minor reduction when com-pared to the base-line scenario. Instead, the free trade scenario and the scenario of technological change alone caused a significant reduction. The biggest single reduction was achieved by banning the cultivation of organic land. However, this was also the most questionable scenario to be real-ized, the reasons for this are further elaborated in the paper. The maximal reduction that can be achieved in the Finnish agricultural sector is about 11 % of the emission reduction that is needed to comply with the Kyoto protocol.

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In recent years, concern has arisen over the effects of increasing carbon dioxide (CO2) in the earth's atmosphere due to the burning of fossil fuels. One way to mitigate increase in atmospheric CO2 concentration and climate change is carbon sequestration to forest vegeta-tion through photosynthesis. Comparable regional scale estimates for the carbon balance of forests are therefore needed for scientific and political purposes. The aim of the present dissertation was to improve methods for quantifying and verifying inventory-based carbon pool estimates of the boreal forests in the mineral soils. Ongoing forest inventories provide a data based on statistically sounded sampling for estimating the level of carbon stocks and stock changes, but improved modelling tools and comparison of methods are still needed. In this dissertation, the entire inventory-based large-scale forest carbon stock assessment method was presented together with some separate methods for enhancing and comparing it. The enhancement methods presented here include ways to quantify the biomass of understorey vegetation as well as to estimate the litter production of needles and branches. In addition, the optical remote sensing method illustrated in this dis-sertation can be used to compare with independent data. The forest inventory-based large-scale carbon stock assessment method demonstrated here provided reliable carbon estimates when compared with independent data. Future ac-tivity to improve the accuracy of this method could consist of reducing the uncertainties regarding belowground biomass and litter production as well as the soil compartment. The methods developed will serve the needs for UNFCCC reporting and the reporting under the Kyoto Protocol. This method is principally intended for analysts or planners interested in quantifying carbon over extensive forest areas.

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The increase in global temperature has been attributed to increased atmospheric concentrations of greenhouse gases (GHG), mainly that of CO2. The threat of severe and complex socio-economic and ecological implications of climate change have initiated an international process that aims to reduce emissions, to increase C sinks, and to protect existing C reservoirs. The famous Kyoto protocol is an offspring of this process. The Kyoto protocol and its accords state that signatory countries need to monitor their forest C pools, and to follow the guidelines set by the IPCC in the preparation, reporting and quality assessment of the C pool change estimates. The aims of this thesis were i) to estimate the changes in carbon stocks vegetation and soil in the forests in Finnish forests from 1922 to 2004, ii) to evaluate the applied methodology by using empirical data, iii) to assess the reliability of the estimates by means of uncertainty analysis, iv) to assess the effect of forest C sinks on the reliability of the entire national GHG inventory, and finally, v) to present an application of model-based stratification to a large-scale sampling design of soil C stock changes. The applied methodology builds on the forest inventory measured data (or modelled stand data), and uses statistical modelling to predict biomasses and litter productions, as well as a dynamic soil C model to predict the decomposition of litter. The mean vegetation C sink of Finnish forests from 1922 to 2004 was 3.3 Tg C a-1, and in soil was 0.7 Tg C a-1. Soil is slowly accumulating C as a consequence of increased growing stock and unsaturated soil C stocks in relation to current detritus input to soil that is higher than in the beginning of the period. Annual estimates of vegetation and soil C stock changes fluctuated considerably during the period, were frequently opposite (e.g. vegetation was a sink but soil was a source). The inclusion of vegetation sinks into the national GHG inventory of 2003 increased its uncertainty from between -4% and 9% to ± 19% (95% CI), and further inclusion of upland mineral soils increased it to ± 24%. The uncertainties of annual sinks can be reduced most efficiently by concentrating on the quality of the model input data. Despite the decreased precision of the national GHG inventory, the inclusion of uncertain sinks improves its accuracy due to the larger sectoral coverage of the inventory. If the national soil sink estimates were prepared by repeated soil sampling of model-stratified sample plots, the uncertainties would be accounted for in the stratum formation and sample allocation. Otherwise, the increases of sampling efficiency by stratification remain smaller. The highly variable and frequently opposite annual changes in ecosystem C pools imply the importance of full ecosystem C accounting. If forest C sink estimates will be used in practice average sink estimates seem a more reasonable basis than the annual estimates. This is due to the fact that annual forest sinks vary considerably and annual estimates are uncertain, and they have severe consequences for the reliability of the total national GHG balance. The estimation of average sinks should still be based on annual or even more frequent data due to the non-linear decomposition process that is influenced by the annual climate. The methodology used in this study to predict forest C sinks can be transferred to other countries with some modifications. The ultimate verification of sink estimates should be based on comparison to empirical data, in which case the model-based stratification presented in this study can serve to improve the efficiency of the sampling design.

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It is now 20 years since the United Nations Conference on Environment and Development, better known as the Earth Summit was held in Rio de Janeiro. An important achievement of the conference was an agreement on the Climate Change Convention which in turn led to the Kyoto Protocol. Another was agreement to 'not carry out any activities on the lands of indigenous peoples that would cause environmental degradation or that would be culturally inappropriate'. Recently we have seen an updated and revised conference in Rio where the same issues were again discussed. Since then ideas about sustainability have changed considerably and to some extent they have merged with ideas about corporate social responsibility and about governance, determined by the economic and political fortunes of the actors involved. It is now time therefore to re-examine the concept of sustainability in the aftermath of this conference and to consider what issues are now considered pertinent around the world. This book therefore takes different positions concerning different aspects of this vital topic.

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We are addressing a new problem of improving automatic speech recognition performance, given multiple utterances of patterns from the same class. We have formulated the problem of jointly decoding K multiple patterns given a single Hidden Markov Model. It is shown that such a solution is possible by aligning the K patterns using the proposed Multi Pattern Dynamic Time Warping algorithm followed by the Constrained Multi Pattern Viterbi Algorithm The new formulation is tested in the context of speaker independent isolated word recognition for both clean and noisy patterns. When 10 percent of speech is affected by a burst noise at -5 dB Signal to Noise Ratio (local), it is shown that joint decoding using only two noisy patterns reduces the noisy speech recognition error rate to about 51 percent, when compared to the single pattern decoding using the Viterbi Algorithm. In contrast a simple maximization of individual pattern likelihoods, provides only about 7 percent reduction in error rate.

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The Clean Development Mechanism (CDM), Article 12 of the Kyoto Protocol allows Afforestation and Reforestation (A/R) projects as mitigation activities to offset the CO2 in the atmosphere whilst simultaneously seeking to ensure sustainable development for the host country. The Kyoto Protocol was ratified by the Government of India in August 2002 and one of India's objectives in acceding to the Protocol was to fulfil the prerequisites for implementation of projects under the CDM in accordance with national sustainable priorities. The objective of this paper is to assess the effectiveness of using large-scale forestry projects under the CDM in achieving its twin goals using Karnataka State as a case study. The Generalized Comprehensive Mitigation Assessment Process (GCOMAP) Model is used to observe the effect of varying carbon prices on the land available for A/R projects. The model is coupled with outputs from the Lund-Potsdam-Jena (LPJ) Dynamic Global Vegetation Model to incorporate the impacts of temperature rise due to climate change under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2, A1B and B1. With rising temperatures and CO2, vegetation productivity is increased under A2 and A1B scenarios and reduced under B1. Results indicate that higher carbon price paths produce higher gains in carbon credits and accelerate the rate at which available land hits maximum capacity thus acting as either an incentive or disincentive for landowners to commit their lands to forestry mitigation projects. (C) 2009 Elsevier B.V. All rights reserved.

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Climate change is one of the most important global environmental challenges, with implications for food production, water supply, health, energy, etc. Addressing climate change requires a good scientific understanding as well as coordinated action at national and global level. This paper addresses these challenges. Historically, the responsibility for greenhouse gas emissions' increase lies largely with the industrialized world, though the developing countries are likely to be the source of an increasing proportion of future emissions. The projected climate change under various scenarios is likely to have implications on food production, water supply, coastal settlements, forest ecosystems, health, energy security, etc. The adaptive capacity of communities likely to be impacted by climate change is low in developing countries. The efforts made by the UNFCCC and the Kyoto Protocol provisions are clearly inadequate to address the climate change challenge. The most effective way to address climate change is to adopt a sustainable development pathway by shifting to environmentally sustainable technologies and promotion of energy efficiency, renewable energy, forest conservation, reforestation, water conservation, etc. The issue of highest importance to developing countries is reducing the vulnerability of their natural and socio-economic systems to the projected climate change. India and other developing countries will face the challenge of promoting mitigation and adaptation strategies, bearing the cost of such an effort, and its implications for economic development.