600 resultados para ENVIRONMENTAL APPLICATIONS


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While it is commonly accepted that computability on a Turing machine in polynomial time represents a correct formalization of the notion of a feasibly computable function, there is no similar agreement on how to extend this notion on functionals, that is, what functionals should be considered feasible. One possible paradigm was introduced by Mehlhorn, who extended Cobham's definition of feasible functions to type 2 functionals. Subsequently, this class of functionals (with inessential changes of the definition) was studied by Townsend who calls this class POLY, and by Kapron and Cook who call the same class basic feasible functionals. Kapron and Cook gave an oracle Turing machine model characterisation of this class. In this article, we demonstrate that the class of basic feasible functionals has recursion theoretic properties which naturally generalise the corresponding properties of the class of feasible functions, thus giving further evidence that the notion of feasibility of functionals mentioned above is correctly chosen. We also improve the Kapron and Cook result on machine representation.Our proofs are based on essential applications of logic. We introduce a weak fragment of second order arithmetic with second order variables ranging over functions from NN which suitably characterises basic feasible functionals, and show that it is a useful tool for investigating the properties of basic feasible functionals. In particular, we provide an example how one can extract feasible programs from mathematical proofs that use nonfeasible functions.

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Keyword Spotting is the task of detecting keywords of interest within continu- ous speech. The applications of this technology range from call centre dialogue systems to covert speech surveillance devices. Keyword spotting is particularly well suited to data mining tasks such as real-time keyword monitoring and unre- stricted vocabulary audio document indexing. However, to date, many keyword spotting approaches have su®ered from poor detection rates, high false alarm rates, or slow execution times, thus reducing their commercial viability. This work investigates the application of keyword spotting to data mining tasks. The thesis makes a number of major contributions to the ¯eld of keyword spotting. The ¯rst major contribution is the development of a novel keyword veri¯cation method named Cohort Word Veri¯cation. This method combines high level lin- guistic information with cohort-based veri¯cation techniques to obtain dramatic improvements in veri¯cation performance, in particular for the problematic short duration target word class. The second major contribution is the development of a novel audio document indexing technique named Dynamic Match Lattice Spotting. This technique aug- ments lattice-based audio indexing principles with dynamic sequence matching techniques to provide robustness to erroneous lattice realisations. The resulting algorithm obtains signi¯cant improvement in detection rate over lattice-based audio document indexing while still maintaining extremely fast search speeds. The third major contribution is the study of multiple veri¯er fusion for the task of keyword veri¯cation. The reported experiments demonstrate that substantial improvements in veri¯cation performance can be obtained through the fusion of multiple keyword veri¯ers. The research focuses on combinations of speech background model based veri¯ers and cohort word veri¯ers. The ¯nal major contribution is a comprehensive study of the e®ects of limited training data for keyword spotting. This study is performed with consideration as to how these e®ects impact the immediate development and deployment of speech technologies for non-English languages.

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Geographic information is increasingly being touted for use in research and industrial projects. While the technology is now available and affordable, there is a lack of easy to use software that takes advantage of geographic information. This is an important problem because users are often researchers or scientists who have insufficient software skills, and by providing applications that are easier to use, time and financial resources can be taken from training and be better applied to the actual research and development work. A solution for this problem must cater for the user and research needs. In particular it must allow for mobile operation for fieldwork, flexibility or customisability of data input, sharing of data with other tools and collaborative capabilities for the usual teamwork environment. This thesis has developed a new architecture and data model to achieve the solution. The result is the Mobile Collaborative Annotation framework providing an implementation of the new architecture and data model. Mobile Collaborative Mapping implements the framework as a Web 2.0 mashup rich internet application and has proven to be an effective solution through its positive application to a case study with fieldwork scientists. This thesis has contributed to research into mobile computing, collaborative computing and geospatial systems by creating a simpler entry point to mobile geospatial applications, enabling simplified collaboration and providing tangible time savings.

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Effective environmental governance is hampered by the continuing presumption of the state as central actor in the domestic and international political contexts. Over the last 20 years, the traditional 'Westphalian' conception of the sovereign state has come under increasing pressure not only in theory, but also in practice, as evidenced by the increasing importance attributed to the participation of quasi-government and non-government actors in decision-making in domestic and international political issues. This paper is a contribution to the on-going debate about the meaning of effective environmental governance by mapping out a post-Westphalian conception of governance. In particular, it defines governance in relation to the protection of biodiversity; highlights obstacles to effective governance in this area, and discusses forming environmental management plans and environmental governance regimes to implement them. The final section of the paper suggests seven directions for ensuring the realisation of effective environmental governance.

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Hexachlorobenzene (HCB) is a persistent environmental contaminant that has the potential to interfere with steroid hormone regulation. The prostate requires precise control by androgens to regulate its growth and function. To determine if HCB impacts androgen action in the prostate, we used a number of methods. Our in vitro cell-culture-based assay used a firefly luciferase reporter gene driven by an androgen-responsive promoter. In the presence of dihydrotestosterone, low concentrations (0.5-5 nM) of HCB increased the androgen-responsive production of firefly luciferase and high concentrations of HCB (> 10 microM) suppressed this transcriptional activity. Results from a binding assay showed no evidence of affinity between HCB and the androgen receptor. We also tested HCB for in vivo effects using transgenic mice in which the transgene was a prostate-specific, androgen-responsive promoter upstream of a chloramphenicol acetyl transferase (CAT) reporter gene. In 4-week-old mice, the proportion of dilated prostate acini, a marker of sexual maturity, increased in the low HCB dose group and decreased in the high HCB dose mice. In the 8-week-old mice, there was a significant decrease in both CAT activity and prostate weight upon exposure to 20 mg/kg/day HCB. Therefore, in vitro and in vivo data suggest that HCB weakly agonizes androgen action, and consequently, low levels of HCB enhanced androgen action but high levels of HCB interfered. Environmental contaminants have been implicated in the rising incidence of prostate cancer, and insight into the mechanisms of endocrine disruption will help to clarify their role.

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Nitrous oxide (N2O) is a potent agricultural greenhouse gas (GHG). More than 50% of the global anthropogenic N2O flux is attributable to emissions from soil, primarily due to large fertilizer nitrogen (N) applications to corn and other non-leguminous crops. Quantification of the trade–offs between N2O emissions, fertilizer N rate, and crop yield is an essential requirement for informing management strategies aiming to reduce the agricultural sector GHG burden, without compromising productivity and producer livelihood. There is currently great interest in developing and implementing agricultural GHG reduction offset projects for inclusion within carbon offset markets. Nitrous oxide, with a global warming potential (GWP) of 298, is a major target for these endeavours due to the high payback associated with its emission prevention. In this paper we use robust quantitative relationships between fertilizer N rate and N2O emissions, along with a recently developed approach for determining economically profitable N rates for optimized crop yield, to propose a simple, transparent, and robust N2O emission reduction protocol (NERP) for generating agricultural GHG emission reduction credits. This NERP has the advantage of providing an economic and environmental incentive for producers and other stakeholders, necessary requirements in the implementation of agricultural offset projects.

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Australian climate, soils and agricultural management practices are significantly different from those of the northern hemisphere nations. Consequently, experimental data on greenhouse gas production from European and North American agricultural soils and its interpretation are unlikely to be directly applicable to Australian systems.

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Nitrous oxide (N2O) is a major greenhouse gas (GHG) product of intensive agriculture. Fertilizer nitrogen (N) rate is the best single predictor of N2O emissions in row-crop agriculture in the US Midwest. We use this relationship to propose a transparent, scientifically robust protocol that can be utilized by developers of agricultural offset projects for generating fungible GHG emission reduction credits for the emerging US carbon cap and trade market. By coupling predicted N2O flux with the recently developed maximum return to N (MRTN) approach for determining economically profitable N input rates for optimized crop yield, we provide the basis for incentivizing N2O reductions without affecting yields. The protocol, if widely adopted, could reduce N2O from fertilized row-crop agriculture by more than 50%. Although other management and environmental factors can influence N2O emissions, fertilizer N rate can be viewed as a single unambiguous proxy—a transparent, tangible, and readily manageable commodity. Our protocol addresses baseline establishment, additionality, permanence, variability, and leakage, and provides for producers and other stakeholders the economic and environmental incentives necessary for adoption of agricultural N2O reduction offset projects.

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Estimates of potential and actual C sequestration require areal information about various types of management activities. Forest surveys, land use data, and agricultural statistics contribute information enabling calculation of the impacts of current and historical land management on C sequestration in biomass (in forests) or in soil (in agricultural systems). Unfortunately little information exists on the distribution of various management activities that can impact soil C content in grassland systems. Limited information of this type restricts our ability to carry out bottom-up estimates of the current C balance of grasslands or to assess the potential for grasslands to act as C sinks with changes in management. Here we review currently available information about grassland management, how that information could be related to information about the impacts of management on soil C stocks, information that may be available in the future, and needs that remain to be filled before in-depth assessments may be carried out. We also evaluate constraints induced by variability in information sources within and between countries. It is readily apparent that activity data for grassland management is collected less frequently and on a coarser scale than data for forest or agricultural inventories and that grassland activity data cannot be directly translated into IPCC-type factors as is done for IPCC inventories of agricultural soils. However, those management data that are available can serve to delineate broad-scale differences in management activities within regions in which soil C is likely to change in response to changes in management. This, coupled with the distinct possibility of more intensive surveys planned in the future, may enable more accurate assessments of grassland C dynamics with higher resolution both spatially and in the number management activities.

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Previous research suggests that soil organic C pools may be a feature of semiarid regions that are particularly sensitive to climatic changes. We instituted an 18-mo experiment along an elevation gradient in northern Arizona to evaluate the influence of temperature, moisture, and soil C pool size on soil respiration. Soils, from underneath different free canopy types and interspaces of three semiarid ecosystems, were moved upslope and/or downslope to modify soil climate. Soils moved downslope experienced increased temperature and decreased precipitation, resulting in decreased soil moisture and soil respiration las much as 23 acid 20%, respectively). Soils moved upslope to more mesic, cooler sites had greater soil water content and increased rates of soil respiration las much as 40%), despite decreased temperature. Soil respiration rates normalized for total C were not significantly different within any of the three incubation sites, indicating that under identical climatic conditions, soil respiration is directly related to soil C pool size for the incubated soils. Normalized soil respiration rates between sites differed significantly for all soil types and were always greater for soils incubated under more mesic, but cooler, conditions. Total soil C did not change significantly during the experiment, but estimates suggest that significant portions of the rapidly cycling C pool were lost. While long-term decreases in aboveground and belowground detrital inputs may ultimately be greater than decreased soil respiration, the initial response to increased temperature and decreased precipitation in these systems is a decrease in annual soil C efflux.

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Carbon pools and fluxes were quantified along an environmental gradient in northern Arizona. Data are presented on vegetation, litter, and soil C pools and soil CO2 fluxes from ecosystems ranging from shrub-steppe through woodlands to coniferous forest and the ecotones in between. Carbon pool sizes and fluxes in these semiarid ecosystems vary with temperature and precipitation and are strongly influenced by canopy cover. Ecosystem respiration is approximately 50 percent greater in the more mesic, forest environment than in the dry shrub-steppe environment. Soil respiration rates within a site vary seasonally with temperature but appear to be constrained by low soil moisture during dry summer months, when approximately 75% of total annual soil respiration occurs. Total annual amount of CO2 respired across all sites is positively correlated with annual precipitation and negatively correlated with temperature. Results suggest that changes in the amount and periodicity of precipitation will have a greater effect on C pools and fluxes than will changes in temperature :in the semiarid Southwestern United States.