919 resultados para one-boson-exchange models


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The international perspectives on these issues are especially valuable in an increasingly connected, but still institutionally and administratively diverse world. The research addressed in several chapters in this volume includes issues around technical standards bodies like EpiDoc and the TEI, engaging with ways these standards are implemented, documented, taught, used in the process of transcribing and annotating texts, and used to generate publications and as the basis for advanced textual or corpus research. Other chapters focus on various aspects of philological research and content creation, including collaborative or community driven efforts, and the issues surrounding editorial oversight, curation, maintenance and sustainability of these resources. Research into the ancient languages and linguistics, in particular Greek, and the language teaching that is a staple of our discipline, are also discussed in several chapters, in particular for ways in which advanced research methods can lead into language technologies and vice versa and ways in which the skills around teaching can be used for public engagement, and vice versa. A common thread through much of the volume is the importance of open access publication or open source development and distribution of texts, materials, tools and standards, both because of the public good provided by such models (circulating materials often already paid for out of the public purse), and the ability to reach non-standard audiences, those who cannot access rich university libraries or afford expensive print volumes. Linked Open Data is another technology that results in wide and free distribution of structured information both within and outside academic circles, and several chapters present academic work that includes ontologies and RDF, either as a direct research output or as essential part of the communication and knowledge representation. Several chapters focus not on the literary and philological side of classics, but on the study of cultural heritage, archaeology, and the material supports on which original textual and artistic material are engraved or otherwise inscribed, addressing both the capture and analysis of artefacts in both 2D and 3D, the representation of data through archaeological standards, and the importance of sharing information and expertise between the several domains both within and without academia that study, record and conserve ancient objects. Almost without exception, the authors reflect on the issues of interdisciplinarity and collaboration, the relationship between their research practice and teaching and/or communication with a wider public, and the importance of the role of the academic researcher in contemporary society and in the context of cutting edge technologies. How research is communicated in a world of instant- access blogging and 140-character micromessaging, and how our expectations of the media affect not only how we publish but how we conduct our research, are questions about which all scholars need to be aware and self-critical.

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We give a theoretical treatment of the interaction of electronic excitations (excitions) in biomolecules and quantum dots with the surrounding polar solvent. Significant quantum decoherence occurs due to the interaction of the electric dipole moment of the solute with the fluctuating electric dipole moments of the individual molecules in the solvent. We introduce spin boson models which could be used to describe the effects. of decoherence on the quantum dynamics of biomolecules which undergo light-induced conformational change and on biomolecules or quantum dots which are coupled by Forster resonant energy transfer.

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In this paper, the exchange rate forecasting performance of neural network models are evaluated against the random walk, autoregressive moving average and generalised autoregressive conditional heteroskedasticity models. There are no guidelines available that can be used to choose the parameters of neural network models and therefore, the parameters are chosen according to what the researcher considers to be the best. Such an approach, however,implies that the risk of making bad decisions is extremely high, which could explain why in many studies, neural network models do not consistently perform better than their time series counterparts. In this paper, through extensive experimentation, the level of subjectivity in building neural network models is considerably reduced and therefore giving them a better chance of Forecasting exchange rates with linear and nonlinear models 415 performing well. The results show that in general, neural network models perform better than the traditionally used time series models in forecasting exchange rates.

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Numerous studies find that monetary models of exchange rates cannot beat a random walk model. Such a finding, however, is not surprising given that such models are built upon money demand functions and traditional money demand functions appear to have broken down in many developed countries. In this article, we investigate whether using a more stable underlying money demand function results in improvements in forecasts of monetary models of exchange rates. More specifically, we use a sweep-adjusted measure of US monetary aggregate M1 which has been shown to have a more stable money demand function than the official M1 measure. The results suggest that the monetary models of exchange rates contain information about future movements of exchange rates, but the success of such models depends on the stability of money demand functions and the specifications of the models.

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In this paper the exchange rate forecasting performance of neural network models are evaluated against random walk and a range of time series models. There are no guidelines available that can be used to choose the parameters of neural network models and therefore the parameters are chosen according to what the researcher considers to be the best. Such an approach, however, implies that the risk of making bad decisions is extremely high which could explain why in many studies neural network models do not consistently perform better than their time series counterparts. In this paper through extensive experimentation the level of subjectivity in building neural network models is considerably reduced and therefore giving them a better chance of performing well. Our results show that in general neural network models perform better than traditionally used time series models in forecasting exchange rates.

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The aim of our paper is to examine whether Exchange Traded Funds (ETFs) diversify away the private information of informed traders. We apply the spread decomposition models of Glosten and Harris (1998) and Madhavan, Richardson and Roomans (1997) to a sample of ETFs and their control securities. Our results indicate that ETFs have significantly lower adverse selection costs than their control securities. This suggests that private information is diversified away for these securities. Our results therefore offer one explanation for the rapid growth in the ETF market.

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This paper compares the UK/US exchange rate forecasting performance of linear and nonlinear models based on monetary fundamentals, to a random walk (RW) model. Structural breaks are identified and taken into account. The exchange rate forecasting framework is also used for assessing the relative merits of the official Simple Sum and the weighted Divisia measures of money. Overall, there are four main findings. First, the majority of the models with fundamentals are able to beat the RW model in forecasting the UK/US exchange rate. Second, the most accurate forecasts of the UK/US exchange rate are obtained with a nonlinear model. Third, taking into account structural breaks reveals that the Divisia aggregate performs better than its Simple Sum counterpart. Finally, Divisia-based models provide more accurate forecasts than Simple Sum-based models provided they are constructed within a nonlinear framework.

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Numerous studies find that monetary models of exchange rates cannot beat a random walk model. Such a finding, however, is not surprising given that such models are built upon money demand functions and traditional money demand functions appear to have broken down in many developed countries. In this paper we investigate whether using a more stable underlying money demand function results in improvements in forecasts of monetary models of exchange rates. More specifically, we use a sweepadjusted measure of US monetary aggregate M1 which has been shown to have a more stable money demand function than the official M1 measure. The results suggest that the monetary models of exchange rates contain information about future movements of exchange rates but the success of such models depends on the stability of money demand functions and the specifications of the models.

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This thesis presents a two-dimensional water model investigation and development of a multiscale method for the modelling of large systems, such as virus in water or peptide immersed in the solvent. We have implemented a two-dimensional ‘Mercedes Benz’ (MB) or BN2D water model using Molecular Dynamics. We have studied its dynamical and structural properties dependence on the model’s parameters. For the first time we derived formulas to calculate thermodynamic properties of the MB model in the microcanonical (NVE) ensemble. We also derived equations of motion in the isothermal–isobaric (NPT) ensemble. We have analysed the rotational degree of freedom of the model in both ensembles. We have developed and implemented a self-consistent multiscale method, which is able to communicate micro- and macro- scales. This multiscale method assumes, that matter consists of the two phases. One phase is related to micro- and the other to macroscale. We simulate the macro scale using Landau Lifshitz-Fluctuating Hydrodynamics, while we describe the microscale using Molecular Dynamics. We have demonstrated that the communication between the disparate scales is possible without introduction of fictitious interface or approximations which reduce the accuracy of the information exchange between the scales. We have investigated control parameters, which were introduced to control the contribution of each phases to the matter behaviour. We have shown, that microscales inherit dynamical properties of the macroscales and vice versa, depending on the concentration of each phase. We have shown, that Radial Distribution Function is not altered and velocity autocorrelation functions are gradually transformed, from Molecular Dynamics to Fluctuating Hydrodynamics description, when phase balance is changed. In this work we test our multiscale method for the liquid argon, BN2D and SPC/E water models. For the SPC/E water model we investigate microscale fluctuations which are computed using advanced mapping technique of the small scales to the large scales, which was developed by Voulgarakisand et. al.

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A sávosan rögzített devizaárfolyamok elméleti és gyakorlati vizsgálatai a nemzetközi közgazdaságtan egyik legnépszerűbb témaköre volt a kilencvenes évek elején. A gyakorlati módszerek közül az alkalmazások és hivatkozások száma tekintetében az úgynevezett eltolódással igazítás módszere emelkedett ki. A módszert alkalmazó szerzők szerint amíg a lebegő árfolyamú devizák előrejelzése céltalan feladatnak tűnik, addig sávos árfolyam esetén az árfolyam sávon belüli helyzetének előrejelzése sikeresen végezhető. E tanulmány bemutatja, hogy az Európai Monetáris Rendszer és az északeurópai államok sávos árfolyamrendszereinél e módszer alkalmazásával adódott eredmények például a lebegő árfolyamú amerikai dollárra és az egységgyökfolyamatok többségére is érvényesek. A tanulmány feltárja e látszólagos ellentmondás okait, és bemutat egy olyan, a sávos árfolyamrendszerek főbb megfigyelt jellemzőire épülő modellt, amelynek keretei között a sávon belüli árfolyam előrejelzése nem feltétlenül lehetséges, mert a leértékelés előtti időszakban a sávon belüli árfolyam alakulása kaotikus lehet. / === / Following the development of the first exchange rate target zone model at the end of the eighties dozens of papers analyzed theoretical and empirical topics of currency bands. This paper reviews different empirical methods to analyze the credibility of the band and lays special emphasis on the most widely used method, the so-called drift-adjustment method. Papers applying that method claim that while forecasting a freely floating currency is hopeless, predicting an exchange rate within the future band is successful. This paper shows that the results achieved by applications to EMS and Nordic currencies are not specific to data of target zone currencies. For example, application to US dollar and even to most unit root processes leads qualitatively to the same. This paper explores the solutions of this puzzle and shows a model of target zones in which the exchange rate within the band is not necessarily predictable since the process might follow chaotic dynamics before devaluation.

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One dimensional models of reflective practice do not incorporate spirituality and social responsibility. Theological reflection, a form of reflective practice, is contextualized by a vision of social responsibility and the use of spirituality. An alternative model of reflective practice is proposed for spirituality and socially responsive learning at work.

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It is shown that a bosonic formulation of the double-exchange model, one of the classical models for magnetism, generates dynamically a gauge-invariant phase in a finite region of the phase diagram. We use analytical methods, Monte Carlo simulations and finite-size scaling analysis. We study the transition line between that region and the paramagnetic phase. The numerical results show that this transition line belongs to the universality class of the antiferromagnetic RP^(2) model. The fact that one can define a universality class for the antiferromagnetic RP^(2) model, different from the one of the O(N) models, is puzzling and somehow contradicts naive expectations about universality.

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Fibronectin (FN) is a large extracellular matrix (ECM) protein that is made up of

type I (FNI), type II (FNII), & type III (FNIII) domains. It assembles into an insoluble

supra-­‐‑molecular structure: the fibrillar FN matrix. FN fibrillogenesis is a cell‐‑mediated process, which is initiated when FN binds to integrins on the cell surface. The FN matrix plays an important role in cell migration, proliferation, signaling & adhesion. Despite decades of research, the FN matrix is one of the least understood supra-­‐‑molecular protein assemblies. There have been several attempts to elucidate the exact mechanism of matrix assembly resulting in significant progress in the field but it is still unclear as to what are FN-­‐‑FN interactions, the nature of these interactions and the domains of FN that

are in contact with each other. FN matrix fibrils are elastic in nature. Two models have been proposed to explain the elasticity of the fibrils. The first model: the ‘domain unfolding’ model postulates that the unraveling of FNIII domains under tension explains fibril elasticity.

The second model relies on the conformational change of FN from compact to extended to explain fibril elasticity. FN contain 15 FNIII domains, each a 7-­‐‑strand beta sandwich. Earlier work from our lab used the technique of labeling a buried Cys to study the ‘domain unfolding’ model. They used mutant FNs containing a buried Cys in a single FNIII domain and found that 6 of the 15 FNIII domains label in matrix fibrils. Domain unfolding due to tension, matrix associated conformational changes or spontaneous folding and unfolding are all possible explanation for labeling of the buried Cys. The present study also uses the technique of labeling a buried Cys to address whether it is spontaneous folding and unfolding that labels FNIII domains in cell culture. We used thiol reactive DTNB to measure the kinetics of labeling of buried Cys in eleven FN III domains over a wide range of urea concentrations (0-­‐‑9M). The kinetics data were globally fit using Mathematica. The results are equivalent to those of H-­‐‑D exchange, and

provide a comprehensive analysis of stability and unfolding/folding kinetics of each

domain. For two of the six domains spontaneous folding and unfolding is possibly the reason for labeling in cell culture. For the rest of the four domains it is probably matrix associated conformational changes or tension induced unfolding.

A long-­‐‑standing debate in the protein-­‐‑folding field is whether unfolding rate

constants or folding rate constants correlate to the stability of a protein. FNIII domains all have the same ß sandwich structure but very different stabilities and amino acid sequences. Our study analyzed the kinetics of unfolding and folding and stabilities of eleven FNIII domains and our results show that folding rate constants for FNIII domains are relatively similar and the unfolding rates vary widely and correlate to stability. FN forms a fibrillar matrix and the FN-­‐‑FN interactions during matrix fibril formation are not known. FNI 1-­‐‑9 or the N-­‐‑ terminal region is indispensible for matrix formation and its major binding partner has been shown to be FNIII 2. Earlier work from our lab, using FRET analysis showed that the interaction of FNI 1-­‐‑9 with a destabilized FNIII 2 (missing the G strand, FNIII 2ΔG) reduces the FRET efficiency. This efficiency is restored in the presence of FUD (bacterial adhesion from S. pyogenes) that has been known to interact with FNI 1-­‐‑9 via a tandem ß zipper. In the present study we

use FRET analysis and a series of deletion mutants of FNIII 2ΔG to study the shortest fragment of FNIII 2ΔG that is required to bind FNI 1-­‐‑9. Our results presented here are qualitative and show that FNIII 2ΔC’EFG is the shortest fragment required to bind FNI 1-­‐‑9. Deletion of one more strand abolishes the interaction with FNI 1-­‐‑9.