132 resultados para Weakly LindelÖf Determined Space
Resumo:
The origin of magnetic coupling in KNiF3 and K2 NiF4 is studied by means of an ab initio cluster model approach. By a detailed study of the mapping between eigenstates of the exact nonrelativistic and spin model Hamiltonians it is possible to obtain the magnetic coupling constant J and to compare ab initio cluster-model values with those resulting from ab initio periodic Hartree-Fock calculations. This comparison shows that J is strongly determined by two-body interactions; this is a surprising and unexpected result. The importance of the ligands surrounding the basic metal-ligand-metal interacting unit is reexamined by using two different partitions and the constrained space orbital variation method of analysis. This decomposition enables us to show that this effect is basically environmental. Finally, dynamical electronic correlation effects have found to be critical in determining the final value of the magnetic coupling constant.
Resumo:
The Hartman effect is analyzed in both the position and momentum representations of the problem. The importance of Wigner tunneling and deep tunneling is singled out. It is shown quantitatively how the barrier acts as a filter for low momenta (quantum speed up) as the width increases, and a detailed mechanism is proposed. Superluminal transmission is also discussed.
Resumo:
Thermal analysis, powder diffraction, and Raman scattering as a function of the temperature were carried out on K2BeF4. Moreover, the crystal structure was determined at 293 K from powder diffraction. The compound shows a transition from Pna21 to Pnam space group at 921 K with a transition enthalpy of 5 kJ/mol. The transition is assumed to be first order because the compound shows metastability. Structurally and spectroscopically the transition is similar to those observed in (NH4)2SO4, which suggests that the low-temperature phase is ferroelectric. In order to confirm it, the spontaneous polarization has been computed using an ionic model.
Resumo:
We prove a characterization of the support of the law of the solution for a stochastic wave equation with two-dimensional space variable, driven by a noise white in time and correlated in space. The result is a consequence of an approximation theorem, in the convergence of probability, for equations obtained by smoothing the random noise. For some particular classes of coefficients, approximation in the Lp-norm for p¿1 is also proved.
Space Competition and Time Delays in Human Range Expansions. Application to the Neolithic Transition
Resumo:
Space competition effects are well-known in many microbiological and ecological systems. Here we analyze such an effectin human populations. The Neolithic transition (change from foraging to farming) was mainly the outcome of a demographic process that spread gradually throughout Europe from the Near East. In Northern Europe, archaeological data show a slowdown on the Neolithic rate of spread that can be related to a high indigenous (Mesolithic) population density hindering the advance as a result of the space competition between the two populations. We measure this slowdown from a database of 902 Early Neolithic sites and develop a time-delayed reaction-diffusion model with space competition between Neolithic and Mesolithic populations, to predict the observed speeds. The comparison of the predicted speed with the observations and with a previous non-delayed model show that both effects, the time delay effect due to the generation lag and the space competition between populations, are crucial in order to understand the observations
Resumo:
The number of existing protein sequences spans a very small fraction of sequence space. Natural proteins have overcome a strong negative selective pressure to avoid the formation of insoluble aggregates. Stably folded globular proteins and intrinsically disordered proteins (IDP) use alternative solutions to the aggregation problem. While in globular proteins folding minimizes the access to aggregation prone regions IDPs on average display large exposed contact areas. Here, we introduce the concept of average meta-structure correlation map to analyze sequence space. Using this novel conceptual view we show that representative ensembles of folded and ID proteins show distinct characteristics and responds differently to sequence randomization. By studying the way evolutionary constraints act on IDPs to disable a negative function (aggregation) we might gain insight into the mechanisms by which function - enabling information is encoded in IDPs.
Resumo:
We present a study of binary mixtures of Bose-Einstein condensates confined in a double-well potential within the framework of the mean field Gross-Pitaevskii (GP) equation. We re-examine both the single component and the binary mixture cases for such a potential, and we investigate what are the situations in which a simpler two-mode approach leads to an accurate description of their dynamics. We also estimate the validity of the most usual dimensionality reductions used to solve the GP equations. To this end, we compare both the semi-analytical two-mode approaches and the numerical simulations of the one-dimensional (1D) reductions with the full 3D numerical solutions of the GP equation. Our analysis provides a guide to clarify the validity of several simplified models that describe mean-field nonlinear dynamics, using an experimentally feasible binary mixture of an F = 1 spinor condensate with two of its Zeeman manifolds populated, m = ±1.
Resumo:
We present a study of binary mixtures of Bose-Einstein condensates confined in a double-well potential within the framework of the mean field Gross-Pitaevskii (GP) equation. We re-examine both the single component and the binary mixture cases for such a potential, and we investigate what are the situations in which a simpler two-mode approach leads to an accurate description of their dynamics. We also estimate the validity of the most usual dimensionality reductions used to solve the GP equations. To this end, we compare both the semi-analytical two-mode approaches and the numerical simulations of the one-dimensional (1D) reductions with the full 3D numerical solutions of the GP equation. Our analysis provides a guide to clarify the validity of several simplified models that describe mean-field nonlinear dynamics, using an experimentally feasible binary mixture of an F = 1 spinor condensate with two of its Zeeman manifolds populated, m = ±1.
Resumo:
The incorporation of space allows the establishment of a more precise relationship between a contaminating input, a contaminating byproduct and emissions that reach the final receptor. However, the presence of asymmetric information impedes the implementation of the first-best policy. As a solution to this problem a site specific deposit refund system for the contaminating input and the contaminating byproduct are proposed. Moreover, the utilization of a successive optimization technique first over space and second over time enables definition of the optimal intertemporal site specific deposit refund system
Resumo:
En este artículo planteamos una aproximación a la idea de espacio público como articulador del conjunto de acontecimientos que intervienen en la vida de las ciudades. Entendemos este fenómeno como una red poliédrica y multidimensional, cuyo estudio pasa por el análisis de diversas problemáticas: la identificación de los límites entre espacio público y esfera pública; la conformación del espacio público construido; la aproximación teórica al fenómeno desde la contemporaneidad; la dimensión social del espacio público; y finalmente la perspectiva de la gestión de las ciudades. Todas estas dimensiones expresan una mirada crítica del objeto i ponen en valor niveles de trabajo interdisciplinar y multiescala, fundamentales para entender e intervenir en el espacio público de la ciudad contemporánea.
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This paper discusses some of the key concepts in the consideration of public art as a central element in urban regeneration processes, especially in reference to its role in the processes of citizen participation.
Resumo:
En este artículo planteamos una aproximación a la idea de espacio público como articulador del conjunto de acontecimientos que intervienen en la vida de las ciudades. Entendemos este fenómeno como una red poliédrica y multidimensional, cuyo estudio pasa por el análisis de diversas problemáticas: la identificación de los límites entre espacio público y esfera pública; la conformación del espacio público construido; la aproximación teórica al fenómeno desde la contemporaneidad; la dimensión social del espacio público; y finalmente la perspectiva de la gestión de las ciudades. Todas estas dimensiones expresan una mirada crítica del objeto i ponen en valor niveles de trabajo interdisciplinar y multiescala, fundamentales para entender e intervenir en el espacio público de la ciudad contemporánea.
Resumo:
The term Space Manifold Dynamics (SMD) has been proposed for encompassing the various applications of Dynamical Systems methods to spacecraft mission analysis and design, ranging from the exploitation of libration orbits around the collinear Lagrangian points to the design of optimal station-keeping and eclipse avoidance manoeuvres or the determination of low energy lunar and interplanetary transfers
Resumo:
The term Space Manifold Dynamics (SMD) has been proposed for encompassing the various applications of Dynamical Systems methods to spacecraft mission analysis and design, ranging from the exploitation of libration orbits around the collinear Lagrangian points to the design of optimal station-keeping and eclipse avoidance manoeuvres or the determination of low energy lunar and interplanetary transfers
Resumo:
The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.