21 resultados para retention efficiency


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A measurement of the top-quark pair-production cross section in ppbar collisions at sqrt{s}=1.96 TeV using data corresponding to an integrated luminosity of 1.12/fb collected with the Collider Detector at Fermilab is presented. Decays of top-quark pairs into the final states e nu + jets and mu nu + jets are selected, and the cross section and the b-jet identification efficiency are determined using a new measurement technique which requires that the measured cross sections with exactly one and multiple identified b-quarks from the top-quark decays agree. Assuming a top-quark mass of 175 GeV/c^2, a cross section of 8.5+/-0.6(stat.)+/-0.7(syst.) pb is measured.

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Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.

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The use of buffer areas in forested catchments has been actively researched during the last 15 years; but until now, the research has mainly concentrated on the reduction of sediment and phosphorus loads, instead of nitrogen (N). The aim of this thesis was to examine the use of wetland buffer areas to reduce the nitrogen transport in forested catchments and to investigate the environmental impacts involved in their use. Besides the retention capacity, particular attention was paid to the main factors contributing to the N retention, the potential for increased N2O emissions after large N loading, the effects of peatland restoration for use as buffer areas on CH4 emissions, as well as the vegetation composition dynamics induced by the use of peatlands as buffer areas. To study the capacity of buffer areas to reduce N transport in forested catchments, we first used large artificial loadings of N, and then studied the capacity of buffer areas to reduce ammonium (NH4-N) export originating from ditch network maintenance areas in forested catchments. The potential for increased N2O emissions were studied using the closed chamber technique and a large artificial N loading at five buffer areas. Sampling for CH4 emissions and methane-cycling microbial populations were done on three restored buffer areas and on three buffers constructed on natural peatlands. Vegetation composition dynamics was studied at three buffer areas between 1996 and 2009. Wetland buffer areas were efficient in retaining inorganic N from inflow. The key factors contributing to the retention were the size and the length of the buffer, the hydrological loading and the rate of nutrient loading. Our results show that although the N2O emissions may increase temporarily to very high levels after a large N loading into the buffer area, the buffer areas in forested catchments should be viewed as insignificant sources of N2O. CH4 fluxes were substantially higher from buffers constructed on natural peatlands than from the restored buffer areas, probably because of the slow recovery of methanogens after restoration. The use of peatlands as buffer areas was followed by clear changes in plant species composition and the largest changes occurred in the upstream parts of the buffer areas and the wet lawn-level surfaces, where the contact between the vegetation and the through-flow waters was closer than for the downstream parts and dry hummock sites. The changes in the plant species composition may be an undesired phenomenon especially in the case of the mires representing endangered mire site types, and therefore the construction of new buffer areas should be primarily directed into drained peatland areas.

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The objectives of this study were to make a detailed and systematic empirical analysis of microfinance borrowers and non-borrowers in Bangladesh and also examine how efficiency measures are influenced by the access to agricultural microfinance. In the empirical analysis, this study used both parametric and non-parametric frontier approaches to investigate differences in efficiency estimates between microfinance borrowers and non-borrowers. This thesis, based on five articles, applied data obtained from a survey of 360 farm households from north-central and north-western regions in Bangladesh. The methods used in this investigation involve stochastic frontier (SFA) and data envelopment analysis (DEA) in addition to sample selectivity and limited dependent variable models. In article I, technical efficiency (TE) estimation and identification of its determinants were performed by applying an extended Cobb-Douglas stochastic frontier production function. The results show that farm households had a mean TE of 83% with lower TE scores for the non-borrowers of agricultural microfinance. Addressing institutional policies regarding the consolidation of individual plots into farm units, ensuring access to microfinance, extension education for the farmers with longer farming experience are suggested to improve the TE of the farmers. In article II, the objective was to assess the effects of access to microfinance on household production and cost efficiency (CE) and to determine the efficiency differences between the microfinance participating and non-participating farms. In addition, a non-discretionary DEA model was applied to capture directly the influence of microfinance on farm households production and CE. The results suggested that under both pooled DEA models and non-discretionary DEA models, farmers with access to microfinance were significantly more efficient than their non-borrowing counterparts. Results also revealed that land fragmentation, family size, household wealth, on farm-training and off farm income share are the main determinants of inefficiency after effectively correcting for sample selection bias. In article III, the TE of traditional variety (TV) and high-yielding-variety (HYV) rice producers were estimated in addition to investigating the determinants of adoption rate of HYV rice. Furthermore, the role of TE as a potential determinant to explain the differences of adoption rate of HYV rice among the farmers was assessed. The results indicated that in spite of its much higher yield potential, HYV rice production was associated with lower TE and had a greater variability in yield. It was also found that TE had a significant positive influence on the adoption rates of HYV rice. In article IV, we estimated profit efficiency (PE) and profit-loss between microfinance borrowers and non-borrowers by a sample selection framework, which provided a general framework for testing and taking into account the sample selection in the stochastic (profit) frontier function analysis. After effectively correcting for selectivity bias, the mean PE of the microfinance borrowers and non-borrowers were estimated at 68% and 52% respectively. This suggested that a considerable share of profits were lost due to profit inefficiencies in rice production. The results also demonstrated that access to microfinance contributes significantly to increasing PE and reducing profit-loss per hectare land. In article V, the effects of credit constraints on TE, allocative efficiency (AE) and CE were assessed while adequately controlling for sample selection bias. The confidence intervals were determined by the bootstrap method for both samples. The results indicated that differences in average efficiency scores of credit constrained and unconstrained farms were not statistically significant although the average efficiencies tended to be higher in the group of unconstrained farms. After effectively correcting for selectivity bias, household experience, number of dependents, off-farm income, farm size, access to on farm training and yearly savings were found to be the main determinants of inefficiencies. In general, the results of the study revealed the existence substantial technical, allocative, economic inefficiencies and also considerable profit inefficiencies. The results of the study suggested the need to streamline agricultural microfinance by the microfinance institutions (MFIs), donor agencies and government at all tiers. Moreover, formulating policies that ensure greater access to agricultural microfinance to the smallholder farmers on a sustainable basis in the study areas to enhance productivity and efficiency has been recommended. Key Words: Technical, allocative, economic efficiency, DEA, Non-discretionary DEA, selection bias, bootstrapping, microfinance, Bangladesh.