50 resultados para Prediction theory


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We report the observation of electroweak single top quark production in 3.2  fb-1 of pp̅ collision data collected by the Collider Detector at Fermilab at √s=1.96  TeV. Candidate events in the W+jets topology with a leptonically decaying W boson are classified as signal-like by four parallel analyses based on likelihood functions, matrix elements, neural networks, and boosted decision trees. These results are combined using a super discriminant analysis based on genetically evolved neural networks in order to improve the sensitivity. This combined result is further combined with that of a search for a single top quark signal in an orthogonal sample of events with missing transverse energy plus jets and no charged lepton. We observe a signal consistent with the standard model prediction but inconsistent with the background-only model by 5.0 standard deviations, with a median expected sensitivity in excess of 5.9 standard deviations. We measure a production cross section of 2.3-0.5+0.6(stat+sys)  pb, extract the value of the Cabibbo-Kobayashi-Maskawa matrix element |Vtb|=0.91-0.11+0.11(stat+sys)±0.07  (theory), and set a lower limit |Vtb|>0.71 at the 95% C.L., assuming mt=175  GeV/c2.

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We report the observation of electroweak single top quark production in 3.2 fb-1 of ppbar collision data collected by the Collider Detector at Fermilab at sqrt{s}=1.96 TeV. Candidate events in the W+jets topology with a leptonically decaying W boson are classified as signal-like by four parallel analyses based on likelihood functions, matrix elements, neural networks, and boosted decision trees. These results are combined using a super discriminant analysis based on genetically evolved neural networks in order to improve the sensitivity. This combined result is further combined with that of a search for a single top quark signal in an orthogonal sample of events with missing transverse energy plus jets and no charged lepton. We observe a signal consistent with the standard model prediction but inconsistent with the background-only model by 5.0 standard deviations, with a median expected sensitivity in excess of 5.9 standard deviations. We measure a production cross section of 2.3+0.6-0.5(stat+sys) pb, extract the CKM matrix element value |Vtb|=0.91+0.11-0.11 (stat+sys)+-0.07(theory), and set a lower limit |Vtb|>0.71 at the 95% confidence level, assuming m_t=175 GeVc^2.

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We report a measurement of the single top quark production cross section in 2.2 ~fb-1 of p-pbar collision data collected by the Collider Detector at Fermilab at sqrt{s}=1.96 TeV. Candidate events are classified as signal-like by three parallel analyses which use likelihood, matrix element, and neural network discriminants. These results are combined in order to improve the sensitivity. We observe a signal consistent with the standard model prediction, but inconsistent with the background-only model by 3.7 standard deviations with a median expected sensitivity of 4.9 standard deviations. We measure a cross section of 2.2 +0.7 -0.6(stat+sys) pb, extract the CKM matrix element value |V_{tb}|=0.88 +0.13 -0.12 (stat+sys) +- 0.07(theory), and set the limit |V_{tb}|>0.66 at the 95% C.L.

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Agriculture’s contribution to climate change is controversial as it is a significant source of greenhouse gases but also a sink of carbon. Hence its economic and technological potential to mitigate climate change have been argued to be noteworthy. However, social profitability of emission mitigation is a result from factors among emission reductions such as surface water quality impact or profit from production. Consequently, to value comprehensive results of agricultural climate emission mitigation practices, these co-effects to environment and economics should be taken into account. The objective of this thesis was to develop an integrated economic and ecological model to analyse the social welfare of crop cultivation in Finland on distinctive cultivation technologies, conventional tillage and conservation tillage (no-till). Further, we ask whether it would be privately or socially profitable to allocate some of barley cultivation for alternative land use, such as green set-aside or afforestation, when production costs, GHG’s and water quality impacts are taken into account. In the theoretical framework we depict the optimal input use and land allocation choices in terms of environmental impacts and profit from production and derive the optimal tax and payment policies for climate and water quality friendly land allocation. The empirical application of the model uses Finnish data about production cost and profit structure and environmental impacts. According to our results, given emission mitigation practices are not self-evidently beneficial for farmers or society. On the contrary, in some cases alternative land allocation could even reduce social welfare, profiting conventional crop cultivation. This is the case regarding mineral soils such as clay and silt soils. On organic agricultural soils, climate mitigation practices, in this case afforestation and green fallow give more promising results, decreasing climate emissions and nutrient runoff to water systems. No-till technology does not seem to profit climate mitigation although it does decrease other environmental impacts. Nevertheless, the data behind climate emission mitigation practices impact to production and climate is limited and partly contradictory. More specific experiment studies on interaction of emission mitigation practices and environment would be needed. Further study would be important. Particularly area specific production and environmental factors and also food security and safety and socio-economic impacts should be taken into account.

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A density-functional approach on the hexagonal graphene lattice is developed using an exact numerical solution to the Hubbard model as the reference system. Both nearest-neighbour and up to third nearest-neighbour hoppings are considered and exchange-correlation potentials within the local density approximation are parameterized for both variants. The method is used to calculate the ground-state energy and density of graphene flakes and infinite graphene sheet. The results are found to agree with exact diagonalization for small systems, also if local impurities are present. In addition, correct ground-state spin is found in the case of large triangular and bowtie flakes out of the scope of exact diagonalization methods.