944 resultados para Model-based bootstrap


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A continuum model based on the critical state theory of soil mechanics is used to generate stress and density profiles, and to compute discharge velocities for the plane flow of cohesionless materials. Two types of yield loci are employed, namely, a yield locus with a corner, and a smooth yield locus. The yield locus with a corner leads to computational difficulties. For the smooth yield locus, results are found to be relatively insensitive to the shape of the yield locus, the location of the upper traction-free surface and the density specified on this surface. This insensitivity arises from the existence of asymptotic stress and density fields, to which the solution tends to converge on moving down the hopper. Numerical and approximate analytical solutions are obtained for these fields and the latter is used to derive an expression for the discharge velocity. This relation predicts discharge velocities to within 13% of the exact (numerical) values. While the assumption of incompressibility has been frequently used in the literature, it is shown here that in some cases, this leads to discharge velocities which are significantly higher than those obtained by the incorporation of density variation.

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Nanomaterials with a hexagonally ordered atomic structure, e.g., graphene, carbon and boron nitride nanotubes, and white graphene (a monolayer of hexagonal boron nitride) possess many impressive properties. For example, the mechanical stiffness and strength of these materials are unprecedented. Also, the extraordinary electronic properties of graphene and carbon nanotubes suggest that these materials may serve as building blocks of next generation electronics. However, the properties of pristine materials are not always what is needed in applications, but careful manipulation of their atomic structure, e.g., via particle irradiation can be used to tailor the properties. On the other hand, inadvertently introduced defects can deteriorate the useful properties of these materials in radiation hostile environments, such as outer space. In this thesis, defect production via energetic particle bombardment in the aforementioned materials is investigated. The effects of ion irradiation on multi-walled carbon and boron nitride nanotubes are studied experimentally by first conducting controlled irradiation treatments of the samples using an ion accelerator and subsequently characterizing the induced changes by transmission electron microscopy and Raman spectroscopy. The usefulness of the characterization methods is critically evaluated and a damage grading scale is proposed, based on transmission electron microscopy images. Theoretical predictions are made on defect production in graphene and white graphene under particle bombardment. A stochastic model based on first-principles molecular dynamics simulations is used together with electron irradiation experiments for understanding the formation of peculiar triangular defect structures in white graphene. An extensive set of classical molecular dynamics simulations is conducted, in order to study defect production under ion irradiation in graphene and white graphene. In the experimental studies the response of carbon and boron nitride multi-walled nanotubes to irradiation with a wide range of ion types, energies and fluences is explored. The stabilities of these structures under ion irradiation are investigated, as well as the issue of how the mechanism of energy transfer affects the irradiation-induced damage. An irradiation fluence of 5.5x10^15 ions/cm^2 with 40 keV Ar+ ions is established to be sufficient to amorphize a multi-walled nanotube. In the case of 350 keV He+ ion irradiation, where most of the energy transfer happens through inelastic collisions between the ion and the target electrons, an irradiation fluence of 1.4x10^17 ions/cm^2 heavily damages carbon nanotubes, whereas a larger irradiation fluence of 1.2x10^18 ions/cm^2 leaves a boron nitride nanotube in much better condition, indicating that carbon nanotubes might be more susceptible to damage via electronic excitations than their boron nitride counterparts. An elevated temperature was discovered to considerably reduce the accumulated damage created by energetic ions in both carbon and boron nitride nanotubes, attributed to enhanced defect mobility and efficient recombination at high temperatures. Additionally, cobalt nanorods encapsulated inside multi-walled carbon nanotubes were observed to transform into spherical nanoparticles after ion irradiation at an elevated temperature, which can be explained by the inverse Ostwald ripening effect. The simulation studies on ion irradiation of the hexagonal monolayers yielded quantitative estimates on types and abundances of defects produced within a large range of irradiation parameters. He, Ne, Ar, Kr, Xe, and Ga ions were considered in the simulations with kinetic energies ranging from 35 eV to 10 MeV, and the role of the angle of incidence of the ions was studied in detail. A stochastic model was developed for utilizing the large amount of data produced by the molecular dynamics simulations. It was discovered that a high degree of selectivity over the types and abundances of defects can be achieved by carefully selecting the irradiation parameters, which can be of great use when precise pattering of graphene or white graphene using focused ion beams is planned.

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In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

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Nowadays any analysis of Russian economy is incomplete without taking into account the phenomenon of oligarchy. Russian oligarchs appeared after the fall of the Soviet Union and are represented by wealthy businessmen who control a huge part of natural resources enterprises and have a big political influence. Oligarchs’ shares in some natural resources industries reach even 70-80%. Their role in Russian economy is big without any doubts, however there has been very little economic analysis done. The aim of this work is to examine Russian oligarchy on micro and macro levels, its role in Russia’s transition and the possible positive and negative outcomes from this phenomenon. For this purpose the work presents two theoretical models. The first part of this thesis work examines the role of oligarchs on micro level, concentrating on the question whether the oligarchs can be more productive owners than other types of owners. To answer the question this part presents a model based on the article “Are oligarchs productive? Theory and evidence” by Y. Gorodnichenko and Y. Grygorenko. It is followed by empirical test based on the works of S. Guriev and A. Rachinsky. The model predicts oligarchs to invest more in the productivity of their enterprises and have higher returns on capital, therefore be more productive owners. According to the empirical test, oligarchs were found to outperform other types of owners, however it is not defined whether the productivity gains offset losses in tax revenue. The second part of the work concentrates on the role of oligarchy on macro level. More precisely, it examines the assumption that the depression after 1998 crises in Russia was caused by the oligarchs’ behavior. This part presents a theoretical model based on the article “A macroeconomic model of Russian transition: The role of oligarchic property rights” by S. Braguinsky and R. Myerson, where the special type of property rights is introduced. After the 1998 crises oligarchs started to invest all their resources abroad to protect themselves from political risks, which resulted in the long depression phase. The macroeconomic model shows, that better protection of property rights (smaller political risk) or/and higher outside investing could reduce the depression. Taking into account this result, the government policy can change the oligarchs’ behavior to be more beneficial for the Russian economy and make the transition faster.

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Paraserianthes falcataria is a very fast growing, light wood tree species, that has recently gained wide interest in Indonesia for industrial wood processing. At the moment the P. falcataria plantations managed by smallholders are lacking predefined management programmes for commercial wood production. The general objective of this study was to model the growth and yield of Paraserianthes falcataria stands managed by smallholders in Ciamis, West Java, Indonesia and to develop management scenarios for different production objectives. In total 106 circular sample plots with over 2300 P. falcataria trees were assessed on smallholder plantation inventory. In addition, information on market prices of P. falcataria wood was collected through rapid appraisals among industries. A tree growth model based on Chapman-Richards function was developed on three different site qualities and the stand management scenarios were developed under three management objectives: (1) low initial stand density with low intensity stand management, (2) high initial stand density with medium intensity of intervention, (3) high initial stand density and strong intensity of silvicultural interventions, repeated more than once. In general, the 9 recommended scenarios have rotation ages varying from 4 to 12 years, planting densities from 4x4 meters (625 trees ha-1) to 3x2 meters (1666 trees ha-1) and thinnings at intensities of removing 30 to 60 % of the standing trees. The highest annual income would be generated on high-quality with a scenario with initial planting density 3x2 m (1666 trees ha-1) one thinning at intensity of removing 55 % of the standing trees at the age of 2 years and clear cut at the age of 4 years.

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Thermal, spectroscopic and electrical properties of lead pyrophosphate glass prepared by melt quenching have been examined. A model based on the structural disproportionation of the P2O 7 4− ions has been proposed and is shown to consistently explain all the observations. The equilibrium of various anionic species has been discussed on the basis of their electronegativities which are in turn related to their basicities.

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An energy method is used in order to derive the non-linear equations of motion of a smart flapping wing. Flapping wing is actuated from the root by a PZT unimorph in the piezofan configuration. Dynamic characteristics of the wing, having the same size as dragonfly Aeshna Multicolor, are analyzed using numerical simulations. It is shown that flapping angle variations of the smart flapping wing are similar to the actual dragonfly wing for a specific feasible voltage. An unsteady aerodynamic model based on modified strip theory is used to obtain the aerodynamic forces. It is found that the smart wing generates sufficient lift to support its own weight and carry a small payload. It is therefore a potential candidate for flapping wing of micro air vehicles.

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Design of a compact broadband filter using tightly coupled line sections in defected (A slot is cut in the ground) microstrip medium operating from 3 1-6 8 GHz has been repotted in this article Filter has been designed and analyzed using an equivalent circuit model based on even and odd mock parameters of coupled line sections The proposed filter has attenuation poles on either side of the pass band resulting in improved selectivity This filter features spurious free response up to third harmonic frequency Experimental results of the filter have been validated against the analytical and full wave simulations (C) 2010 Wiley Periodicals Inc Microwave Opt Technol Lett 53 184-187 2011 View this article online at wileyonlinelibrary com DOI 10.1002/mop.25676

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Species identification forms the basis for understanding the diversity of the living world, but it is also a prerequisite for understanding many evolutionary patterns and processes. The most promising approach for correctly delimiting and identifying species is to integrate many types of information in the same study. Our aim was to test how cuticular hydro- carbons, traditional morphometrics, genetic polymorphisms in nuclear markers (allozymes and DNA microsatellites) and DNA barcoding (partial mitochondrial COI gene) perform in delimiting species. As an example, we used two closely related Formica ants, F. fusca and F. lemani, sampled from a sympatric population in the northern part of their distribu- tion. Morphological characters vary and overlap in different parts of their distribution areas, but cuticular hydrocarbons include a strong taxonomic signal and our aim is to test the degree to which morphological and genetic data correspond to the chemical data. In the morphological analysis, species were best separated by the combined number of hairs on pro- notum and mesonotum, but individual workers overlapped in hair numbers, as previously noted by several authors. Nests of the two species were separated but not clustered according to species in a Principal Component Analysis made on nuclear genetic data. However, model-based Bayesian clustering resulted in perfect separation of the species and gave no indication of hybridization. Furthermore, F. lemani and F. fusca did not share any mitochondrial haplotypes, and the species were perfectly separated in a phylogenetic tree. We conclude that F. fusca and F. lemani are valid species that can be separated in our study area relatively well with all methods employed. However, the unusually small genetic differen- tiation in nuclear markers (FST = 0.12) shows that they are closely related, and occasional hybridization between F. fusca and F. lemani cannot be ruled out.

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We report in this paper the aggregation properties of amphotericin-B (amp-B) in solution using CD and 1H-NMR techniques. Our results indicate that the preferred structure of amp-B in dimethylsulfoxide is a monomer at low concentrations (10−4M and below) and a stable dimer at higher concentrations (range 5 · 103 M to 10−2M). In a DMSO/ethanol mixture (1:1 (v/v)), the antibiotic is monomeric, irrespective of the concentration within the range studied. We propose a head-to-tail model based on NMR data. An understanding of the head-to-tail dimer, is, we believe important, particularly in view of the recent report wherein it is proposed that the drug inserts into bilayers as head-to-tail oligomers.

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The presence of cell agglomerates has been found to influence significantly the rates of liquid drainage from static foams. The process of drainage has been modelled by considering the foam to be made of pentagonal dodecahedral bubbles yielding films, nearly horizontal and nearly vertical Plateau borders. The films are assumed to drain into both kinds of Plateau borders equally. The horizontal Plateau borders are assumed to receive liquid from the films and drain into the vertical Plateau borders, which, in turn, form the main flow paths for gravity drainage. The drainage process is assumed to be similar to that for pure liquid until a stage is reached where the size of the cell agglomerates become equivalent to those of films and Plateau borders. Thereafter, a squeezing flow mechanism has been formulated where the aggromerates deform and flow. The model based on the above assumptions has been verified against experimental results and has been found to predict not only drainage data but also the separation of cell agglomerates from broths.

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An energy method is used in order to derive the non-linear equations of motion of a smart flapping wing. Flapping wing is actuated from the root by a PZT unimorph in the piezofan configuration. Dynamic characteristics of the wing, having the same size as dragonfly Aeshna Multicolor, are analyzed using numerical simulations. It is shown that flapping angle variations of the smart flapping wing are similar to the actual dragonfly wing for a specific feasible voltage. An unsteady aerodynamic model based on modified strip theory is used to obtain the aerodynamic forces. It is found that the smart wing generates sufficient lift to support its own weight and carry a small payload. It is therefore a potential candidate for flapping wing of micro air vehicles.

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The use of the shear wave velocity data as a field index for evaluating the liquefaction potential of sands is receiving increased attention because both shear wave velocity and liquefaction resistance are similarly influenced by many of the same factors such as void ratio, state of stress, stress history and geologic age. In this paper, the potential of support vector machine (SVM) based classification approach has been used to assess the liquefaction potential from actual shear wave velocity data. In this approach, an approximate implementation of a structural risk minimization (SRM) induction principle is done, which aims at minimizing a bound on the generalization error of a model rather than minimizing only the mean square error over the data set. Here SVM has been used as a classification tool to predict liquefaction potential of a soil based on shear wave velocity. The dataset consists the information of soil characteristics such as effective vertical stress (sigma'(v0)), soil type, shear wave velocity (V-s) and earthquake parameters such as peak horizontal acceleration (a(max)) and earthquake magnitude (M). Out of the available 186 datasets, 130 are considered for training and remaining 56 are used for testing the model. The study indicated that SVM can successfully model the complex relationship between seismic parameters, soil parameters and the liquefaction potential. In the model based on soil characteristics, the input parameters used are sigma'(v0), soil type. V-s, a(max) and M. In the other model based on shear wave velocity alone uses V-s, a(max) and M as input parameters. In this paper, it has been demonstrated that Vs alone can be used to predict the liquefaction potential of a soil using a support vector machine model. (C) 2010 Elsevier B.V. All rights reserved.

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Mutation and/or dysfunction of signaling proteins in the mitogen activated protein kinase (MAPK) signal transduction pathway are frequently observed in various kinds of human cancer. Consistent with this fact, in the present study, we experimentally observe that the epidermal growth factor (EGF) induced activation profile of MAP kinase signaling is not straightforward dose-dependent in the PC3 prostate cancer cells. To find out what parameters and reactions in the pathway are involved in this departure from the normal dose-dependency, a model-based pathway analysis is performed. The pathway is mathematically modeled with 28 rate equations yielding those many ordinary differential equations (ODE) with kinetic rate constants that have been reported to take random values in the existing literature. This has led to us treating the ODE model of the pathways kinetics as a random differential equations (RDE) system in which the parameters are random variables. We show that our RDE model captures the uncertainty in the kinetic rate constants as seen in the behavior of the experimental data and more importantly, upon simulation, exhibits the abnormal EGF dose-dependency of the activation profile of MAP kinase signaling in PC3 prostate cancer cells. The most likely set of values of the kinetic rate constants obtained from fitting the RDE model into the experimental data is then used in a direct transcription based dynamic optimization method for computing the changes needed in these kinetic rate constant values for the restoration of the normal EGF dose response. The last computation identifies the parameters, i.e., the kinetic rate constants in the RDE model, that are the most sensitive to the change in the EGF dose response behavior in the PC3 prostate cancer cells. The reactions in which these most sensitive parameters participate emerge as candidate drug targets on the signaling pathway. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

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The kinetics of the oxidation of electrodeposited boron powder and the boron powder produced by the reduction process were studied using thermogravimetry (TG). The oxidation was carried out by heating boron powder in a stream of oxygen. Both isothermal and non-isothermal methods were used to study the kinetics. Model-free isoconversional method was used to derive the kinetics parameters. A two step oxidation reaction (exothermic) was observed. The oxidation reaction could not be completed due to the formation of glassy layer of boric oxide on the surface of boron powder which acts as a barrier for further diffusion of oxygen into the particle. The activation energy obtained using model-free method for electrodeposited boron is 122 +/- 7 kJ mol(-1) whereas a value of 205 +/- 9 kJ mol(-1) was obtained for boron produced by the reduction process (commercially procured boron). Mechanistic interpretation of the oxidation reaction was done using model based method. The activation energy was found to depend on the size distribution of the particles and specific surface area of the powder. (C) 2010 Elsevier B.V. All rights reserved.