977 resultados para Time-variable gravity


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In biostatistical applications, interest often focuses on the estimation of the distribution of time T between two consecutive events. If the initial event time is observed and the subsequent event time is only known to be larger or smaller than an observed monitoring time, then the data is described by the well known singly-censored current status model, also known as interval censored data, case I. We extend this current status model by allowing the presence of a time-dependent process, which is partly observed and allowing C to depend on T through the observed part of this time-dependent process. Because of the high dimension of the covariate process, no globally efficient estimators exist with a good practical performance at moderate sample sizes. We follow the approach of Robins and Rotnitzky (1992) by modeling the censoring variable, given the time-variable and the covariate-process, i.e., the missingness process, under the restriction that it satisfied coarsening at random. We propose a generalization of the simple current status estimator of the distribution of T and of smooth functionals of the distribution of T, which is based on an estimate of the missingness. In this estimator the covariates enter only through the estimate of the missingness process. Due to the coarsening at random assumption, the estimator has the interesting property that if we estimate the missingness process more nonparametrically, then we improve its efficiency. We show that by local estimation of an optimal model or optimal function of the covariates for the missingness process, the generalized current status estimator for smooth functionals become locally efficient; meaning it is efficient if the right model or covariate is consistently estimated and it is consistent and asymptotically normal in general. Estimation of the optimal model requires estimation of the conditional distribution of T, given the covariates. Any (prior) knowledge of this conditional distribution can be used at this stage without any risk of losing root-n consistency. We also propose locally efficient one step estimators. Finally, we show some simulation results.

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Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

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In dem vorliegenden Beitrag wird ein Ansatz zur Integration von Energiekosten in bestehende Fertigungssteuerungsverfahren vorgestellt. Das entwickelte Verfahren basiert auf dem Ansatz der Belastungsorientierten Auftragsfreigabe (BOA) und berücksichtigt schwankende Strompreise aufgrund der zunehmenden Einspeisung regenerativer Energien in das Stromnetz. Die Weiterentwicklung ermöglicht besonders kleinen und mittleren Unternehmen (KMU) die Einsparung von Energiekosten durch organisatorische Maßnahmen der Fertigungssteuerung ohne kapitalintensive Investitionen.

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The analytic continuation needed for the extraction of transport coefficients necessitates in principle a continuous function of the Euclidean time variable. We report on progress towards achieving the continuum limit for 2-point correlator measurements in thermal SU(3) gauge theory, with specific attention paid to scale setting. In particular, we improve upon the determination of the critical lattice coupling and the critical temperature of pure SU(3) gauge theory, estimating r0Tc ≃ 0.7470(7) after a continuum extrapolation. As an application the determination of the heavy quark momentum diffusion coefficient from a correlator of colour-electric fields attached to a Polyakov loop is discussed.

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The intensity of long-range correlations observed with the classical HMBC pulse sequence using static optimization of the long-range coupling delay is directly related to the size of the coupling constant and is often set as a compromise. As such, some long-range correlations might appear with a reduced intensity or might even be completely absent from the spectra. After a short introduction, this third manuscript will give a detailed review of some selected HMBC variants dedicated to improve the detection of long-range correlations, such as the ACCORD-HMBC, CIGAR-HMBC, and Broadband HMBC experiments. Practical details about the accordion optimization, which affords a substantial improvement in both the number and intensity of the long-range correlations observed, but introduces a modulation in F1, will be discussed. The incorporation of the so-called constant time variable delay in the CIGAR-HMBC experiment, which can trigger or even completely suppress 1H–1H coupling modulation inherent to the utilization of the accordion principle, will be also discussed. The broadband HMBC scheme, which consists of recording a series of HMBC spectra with different delays set as a function of the long-range heteronuclear coupling constant ranges and transverse relaxation times T2, is also examined.

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Major and trace element (including REE) geochemistry of basalts and chilled basaltic glasses from the MAR axial zone in the vicinity of the Sierra Leone FZ (5-7°10'N) has been studied. Associations of basalts of various compositions with particular ocean-floor geological structural features have been analyzed as well. Three basaltic varieties have been discriminated. Almost ubiquitous are high-Mg basalts (Variety 1) that are derivatives of N-MORB tholeiitic melts and that are produced in the axial zone of spreading. Variety 2 is alkaline basalts widespread on the southwestern flank of the MAR crest zone in the Sierra Leone region, likely generated through deep mantle melting under plume impact. Variety 3 is basalts derivative from T- and P-MORB-like tholeiitic melts and originating through addition of deeper mantle material to depleted upper mantle melts. Magma generation parameters, as calculated from chilled glass compositions, are different for depleted tholeiites (44-55 km, 1320-1370°C) and enriched tholeiites (45-78 km, 1330-1450°C). Mantle plume impact is shown to affect not only tholeiitic basalt compositions but also magma generation conditions in the axial spreading zone, resulting in higher Ti and Na concentrations in melts parental to rift-related basalts occurring near the plume. T- and P-MORBs are also developed near areas where mantle plumes are localized. High-Mg basalts are shown to come in several types with distinctive Ti and Na contents. Nearly every single MAR segment (bounded by sinistral strike slips and the Bogdanov Fracture Zone) is featured by its own basalt type suggesting that it has formed above an asthenospheric diapir with its unique magma generation conditions. These conditions are time variable. Likely causes of temporal and spatial instability of the mantle upwelling beneath this portion of the MAR are singular tectonic processes and plume activity. In sulfide-bearing rift morphostructures (so-called "Ore area'' and the Markov Basin), basalts make up highly evolved suites generated through olivine and plagioclase fractionation, which is suggestive of relatively long-lived magma chambers beneath the sulfide-bearing rift morphostructures. Functioning of these chambers is a combined effect of singular geodynamic regime and plume activity. In these chambers melts undergo deep differentiation leading to progressively increasing concentration of sulfide phase, eventually to be supplied to the hydrothermal plumbing system.

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Radiocarbon dating series, bulk sediment, and organic carbon flux from various Atlantic deep-sea regions reveal that the thickness of the bioturbated zone increases by 2 cm if food supply increases by 1 gC/m**2/yr (r = 0.8). Bulk sediment accumulation rates do not influence the depth of bioturbational mixing under normal pelagic sedimentary conditions. We believe that this relationship between nutrient supply and benthic mixing can be used for a quantitative and time-variable unmixing procedure to improve high-resolution stratigraphic correlations and paleoclimatic interpretations of deep-sea records.

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During the cruises No 17 and 22 of the German research vessel "Meteor", 45 water samples were taken at 4 stations in the central part of the Mediterranean Sea. Mass spectrometrical analyses showed that systematic, but time variable changes of the oxygen isotope ratios occur. Deep water samples (T> 500 m) have a ± constant isotopic composition of d18O = +1.79? (SMOW) and a Chlorinity of 21.399?. These data are discussed with respect to paleotemperature determinations.

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Abstract This paper describes a two-part methodology for managing the risk posed by water supply variability to irrigated agriculture. First, an econometric model is used to explain the variation in the production value of irrigated agriculture. The explanatory variables include an index of irrigation water availability (surface storage levels), a price index representative of the crops grown in each geographical unit, and a time variable. The model corrects for autocorrelation and it is applied to 16 representative Spanish provinces in terms of irrigated agriculture. In the second part, the fitted models are used for the economic evaluation of drought risk. In flow variability in the hydrological system servicing each province is used to perform ex-ante evaluations of economic output for the upcoming irrigation season. The model?s error and the probability distribution functions (PDFs) of the reservoirs? storage variations are used to generate Monte Carlo (Latin Hypercube) simulations of agricultural output 7 and 3 months prior to the irrigation season. The results of these simulations illustrate the different risk profiles of each management unit, which depend on farm productivity and on the probability distribution function of water in flow to reservoirs. The potential for ex-ante drought impact assessments is demonstrated. By complementing hydrological models, this method can assist water managers and decisionmakers in managing reservoirs.

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The Free Core Nutation (FCN) is a free mode of the Earth's rotation caused by the different material characteristics of the Earth's core and mantle. This causes the rotational axes of those layers to slightly diverge from each other, resulting in a wobble of the Earth's rotation axis comparable to nutations. In this paper we focus on estimating empirical FCN models using the observed nutations derived from the VLBI sessions between 1993 and 2013. Assuming a fixed value for the oscillation period, the time-variable amplitudes and phases are estimated by means of multiple sliding window analyses. The effects of using different a priori Earth Rotation Parameters (ERP) in the derivation of models are also addressed. The optimal choice of the fundamental parameters of the model, namely the window width and step-size of its shift, is searched by performing a thorough experimental analysis using real data. The former analyses lead to the derivation of a model with a temporal resolution higher than the one used in the models currently available, with a sliding window reduced to 400 days and a day-by-day shift. It is shown that this new model increases the accuracy of the modeling of the observed Earth's rotation. Besides, empirical models determined from USNO Finals as a priori ERP present a slightly lower Weighted Root Mean Square (WRMS) of residuals than IERS 08 C04 along the whole period of VLBI observations, according to our computations. The model is also validated through comparisons with other recognized models. The level of agreement among them is satisfactory. Let us remark that our estimates give rise to the lowest residuals and seem to reproduce the FCN signal in more detail.

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A numerical method for the Dirichlet initial boundary value problem for the heat equation in the exterior and unbounded region of a smooth closed simply connected 3-dimensional domain is proposed and investigated. This method is based on a combination of a Laguerre transformation with respect to the time variable and an integral equation approach in the spatial variables. Using the Laguerre transformation in time reduces the parabolic problem to a sequence of stationary elliptic problems which are solved by a boundary layer approach giving a sequence of boundary integral equations of the first kind to solve. Under the assumption that the boundary surface of the solution domain has a one-to-one mapping onto the unit sphere, these integral equations are transformed and rewritten over this sphere. The numerical discretisation and solution are obtained by a discrete projection method involving spherical harmonic functions. Numerical results are included.

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In this work, we introduce the periodic nonlinear Fourier transform (PNFT) method as an alternative and efficacious tool for compensation of the nonlinear transmission effects in optical fiber links. In the Part I, we introduce the algorithmic platform of the technique, describing in details the direct and inverse PNFT operations, also known as the inverse scattering transform for periodic (in time variable) nonlinear Schrödinger equation (NLSE). We pay a special attention to explaining the potential advantages of the PNFT-based processing over the previously studied nonlinear Fourier transform (NFT) based methods. Further, we elucidate the issue of the numerical PNFT computation: we compare the performance of four known numerical methods applicable for the calculation of nonlinear spectral data (the direct PNFT), in particular, taking the main spectrum (utilized further in Part II for the modulation and transmission) associated with some simple example waveforms as the quality indicator for each method. We show that the Ablowitz-Ladik discretization approach for the direct PNFT provides the best performance in terms of the accuracy and computational time consumption.

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Practical application of flow boiling to ground- and space-based thermal management systems hinges on the ability to predict the system’s heat removal capabilities under expected operating conditions. Research in this field has shown that the heat transfer coefficient within two-phase heat exchangers can be largely dependent on the experienced flow regime. This finding has inspired an effort to develop mechanistic heat transfer models for each flow pattern which are likely to outperform traditional empirical correlations. As a contribution to the effort, this work aimed to identify the heat transfer mechanisms for the slug flow regime through analysis of individual Taylor bubbles. An experimental apparatus was developed to inject single vapor Taylor bubbles into co-currently flowing liquid HFE 7100. The heat transfer was measured as the bubble rose through a 6 mm inner diameter heated tube using an infrared thermography technique. High-speed flow visualization was obtained and the bubble film thickness measured in an adiabatic section. Experiments were conducted at various liquid mass fluxes (43-200 kg/m2s) and gravity levels (0.01g-1.8g) to characterize the effect of bubble drift velocity on the heat transfer mechanisms. Variable gravity testing was conducted during a NASA parabolic flight campaign. Results from the experiments showed that the drift velocity strongly affects the hydrodynamics and heat transfer of single elongated bubbles. At low gravity levels, bubbles exhibited shapes characteristic of capillary flows and the heat transfer enhancement due to the bubble was dominated by conduction through the thin film. At moderate to high gravity, traditional Taylor bubbles provided small values of enhancement within the film, but large peaks in the wake heat transfer occurred due to turbulent vortices induced by the film plunging into the trailing liquid slug. Characteristics of the wake heat transfer profiles were analyzed and related to the predicted velocity field. Results were compared and shown to agree with numerical simulations of colleagues from EPFL, Switzerland. In addition, a preliminary study was completed on the effect of a Taylor bubble passing through nucleate flow boiling, showing that the thinning thermal boundary layer within the film suppressed nucleation, thereby decreasing the heat transfer coefficient.

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In this work we perform a comparison of two different numerical schemes for the solution of the time-fractional diffusion equation with variable diffusion coefficient and a nonlinear source term. The two methods are the implicit numerical scheme presented in [M.L. Morgado, M. Rebelo, Numerical approximation of distributed order reaction- diffusion equations, Journal of Computational and Applied Mathematics 275 (2015) 216-227] that is adapted to our type of equation, and a colocation method where Chebyshev polynomials are used to reduce the fractional differential equation to a system of ordinary differential equations

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Analyzing the relationship between the baseline value and subsequent change of a continuous variable is a frequent matter of inquiry in cohort studies. These analyses are surprisingly complex, particularly if only two waves of data are available. It is unclear for non-biostatisticians where the complexity of this analysis lies and which statistical method is adequate.With the help of simulated longitudinal data of body mass index in children,we review statistical methods for the analysis of the association between the baseline value and subsequent change, assuming linear growth with time. Key issues in such analyses are mathematical coupling, measurement error, variability of change between individuals, and regression to the mean. Ideally, it is better to rely on multiple repeated measurements at different times and a linear random effects model is a standard approach if more than two waves of data are available. If only two waves of data are available, our simulations show that Blomqvist's method - which consists in adjusting for measurement error variance the estimated regression coefficient of observed change on baseline value - provides accurate estimates. The adequacy of the methods to assess the relationship between the baseline value and subsequent change depends on the number of data waves, the availability of information on measurement error, and the variability of change between individuals.