Subharmonic gap structure in short ballistic graphene junctions

We present a theoretical analysis of the current-voltage characteristics of a ballistic superconductor-normal-superconductor (SNS) junction, in which a strip of graphene is coupled to two superconducting electrodes. We focus in the short-junction regime, where the length of the strip is much smaller than superconducting coherence length. We show that the differential conductance exhibits a very rich subharmonic gap structure which can be modulated by means of a gate voltage. On approaching the Dirac point the conductance normalized by the normal-state conductance is identical to that of a short diffusive SNS junction.Comment: revtex4, 4 pages, 4 figure

Analysis of the feasibility of an experiment to measure carbon monoxide in the atmosphere

The feasibility of measuring atmospheric carbon monoxide from a remote platform using the correlation interferometry technique was considered. It has been determined that CO data can be obtained with an accuracy of 10 percent using this technique on the first overtone band of CO at 2.3 mu. That band has been found to be much more suitable than the stronger fundamental band at 4.6 mu. Calculations for both wavelengths are presented which illustrate the effects of atmospheric temperature profiles, inversion layers, ground temperature and emissivity, CO profile, reflectivity, and atmospheric pressure. The applicable radiative transfer theory on which these calculations are based is described together with the principles of the technique

Sensitivity of primary production to different eddy parameterizations: A case study of the spring bloom development in the northwestern Mediterranean Sea

The abilities of the Gent and McWilliams (1990) (GM) and Horizontal Diffusion (HD) eddy-parameterizations to represent the mesoscale effects relevant for primary production are compared and analyzed. Following Levy et al. (1999a), this is done in the case study of the spring bloom that follows the formation of a dense water patch in the northwestern Mediterranean Sea. It is shown that, unlike HD, the use of the GM parameterization can capture many aspects of the primary production enhancement associated with the restratifying action of mesoscale eddies. However, predicted primary production, when using the GM parameterization, is sensitive to the GM's parameter set, and particularly to the maximum value of the lateral mixing coefficient, k(max)

Hysteresis Switching Loops in Ag-manganite memristive interfaces

Multilevel resistance states in silver-manganite interfaces are studied both experimentally and through a realistic model that includes as a main ingredient the oxygen vacancies diffusion under applied electric fields. The switching threshold and amplitude studied through Hysteresis Switching Loops are found to depend critically on the initial state. The associated vacancy profiles further unveil the prominent role of the effective electric field acting at the interfaces. While experimental results validate main assumptions of the model, the simulations allow to disentangle the microscopic mechanisms behind the resistive switching in metal-transition metal oxide interfaces.Comment: 14 pages, 3 figures, to be published in Jour. of Appl. Phy

Development of a breadboard model correlation interferometer for the carbon monoxide pollution experiment

The breadboard model of the correlation interferometer for the Carbon Monoxide Pollution Experiment has been designed, fabricated, and tested. Laboratory, long-path, and atmospheric tests which were performed show the technique to be a feasible method for obtaining a global carbon monoxide map and a vertical carbon monoxide profile and similar information is readily obtainable for methane as well. In addition, the technique is readily applicable to other trace gases by minor instrumental changes. As shown by the results and the conclusions, it has been determined that CO and CH4 data can be obtained with an accuracy of 10% using this technique on the spectral region around 2.3 microns

Volatility clustering and scaling for financial time series due to attractor bubbling

A microscopic model of financial markets is considered, consisting of many interacting agents (spins) with global coupling and discrete-time thermal bath dynamics, similar to random Ising systems. The interactions between agents change randomly in time. In the thermodynamic limit the obtained time series of price returns show chaotic bursts resulting from the emergence of attractor bubbling or on-off intermittency, resembling the empirical financial time series with volatility clustering. For a proper choice of the model parameters the probability distributions of returns exhibit power-law tails with scaling exponents close to the empirical ones.Comment: For related publications see http://www.helbing.or

Thermodynamics as an alternative foundation for zero-temperature density functional theory and spin density functional theory

Thermodynamics provides a transparent definition of the free energy of density functional theory (DFT), and of its derivatives - the potentials, at finite temperatures T. By taking the T to 0 limit, it is shown here that both DFT and spin-dependent DFT (for ground states) suffer from precisely the same benign ambiguities: (a) charge and spin quantization lead to "up to a constant" indeterminacies in the potential and the magnetic field respectively, and (b) the potential in empty subspaces is undetermined but irrelevant. Surprisingly, these simple facts were inaccessible within the standard formulation, leading to recent discussions of apparent difficulties within spin-DFT.Comment: RevTeX, to appear in Phys. Rev.

Core-periphery or decentralized? Topological shifts of specialized information on Twitter

In this paper we investigate shifts in Twitter network topology resulting from the type of information being shared. We identified communities matching areas of agricultural expertise and measured the core-periphery centralization of network formations resulting from users sharing generic versus specialized information. We found that centralization increases when specialized information is shared and that the network adopts decentralized formations as conversations become more generic. The results are consistent with classical diffusion models positing that specialized information comes with greater centralization, but they also show that users favor decentralized formations, which can foster community cohesion, when spreading specialized information is secondary

AIML and sequence-to-sequence models to build artificial intelligence chatbots: insights from a comparative analysis

A chatbot is a software that is able to autonomously communicate with a human being through text and due to its usefulness, an increasing number of businesses are implementing such tools in order to provide timely communication to their clients. In the past, whilst literature has focused on implementing innovative chatbots and the evaluation of such tools, limited studies have been done to critically comparing such conversational systems. In order to address this gap, this study critically compares the Artificial Intelligence Mark-up Language (AIML), and Sequence-to-Sequence models for building chatbots. In this endeavor, two chatbots were developed to implement each model and were evaluated using a mixture of glass box and black box evaluation, based on 3 metrics, namely, user’s satisfaction, the information retrieval rate, and the task completion rate of each chatbot. Results showed that the AIML chatbot ensured better user satisfaction, and task completion rate, while the Sequence-to-Sequence model had better information retrieval rate