Current in coherent quantum systems connected to mesoscopic Fermi reservoirs

We study particle current in a recently proposed model for coherent quantum transport. In this model, a system connected to mesoscopic Fermi reservoirs (meso-reservoir) is driven out of equilibrium by the action of super-reservoirs thermalized to prescribed temperatures and chemical potentials by a simple dissipative mechanism described by the Lindblad equation. We compare exact (numerical) results with theoretical expectations based on the Landauer formula.

Particle and energy transport in quantum disordered and quasi-periodic chains connected to mesoscopic Fermi reservoirs

We study a model of nonequilibrium quantum transport of particles and energy in a many-body system connected to mesoscopic Fermi reservoirs (the so-called meso-reservoirs). We discuss the conservation laws of particles and energy within our setup as well as the transport properties of quasi-periodic and disordered chains.

An autonomic framework for enhancing the quality of data grid services

Data grid services have been used to deal with the increasing needs of applications in terms of data volume and throughput. The large scale, heterogeneity and dynamism of grid environments often make management and tuning of these data services very complex. Furthermore, current high-performance I/O approaches are characterized by their high complexity and specific features that usually require specialized administrator skills. Autonomic computing can help manage this complexity. The present paper describes an autonomic subsystem intended to provide self-management features aimed at efficiently reducing the I/O problem in a grid environment, thereby enhancing the quality of service (QoS) of data access and storage services in the grid. Our proposal takes into account that data produced in an I/O system is not usually immediately required. Therefore, performance improvements are related not only to current but also to any future I/O access, as the actual data access usually occurs later on. Nevertheless, the exact time of the next I/O operations is unknown. Thus, our approach proposes a long-term prediction designed to forecast the future workload of grid components. This enables the autonomic subsystem to determine the optimal data placement to improve both current and future I/O operations.

Riding out of the storm: How to deal with the complexity of grid and cloud management

Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management.

Changes in resting-state functionally connected parieto-frontal networks after videogame practice

Neuroimaging studies provide evidence for organized intrinsic activity under task-free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting-state functional connectivity after videogame practice applying a test–retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test–retest resting-state fMRI, jointly with a dual-regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions.

Practical Characterization of Input-Parallel-Connected Converters with a Common Input Filter

The paper presents a method to analyze robust stability and transient performance of a distributed power system consisting of commercial converter modules interconnected through a common input filter. The method is based on the use of four transfer functions, which are measurable from the converter input and output terminals. It is shown that these parameters provide important information on the power module sensitivity to the interactions caused by the external impedances. Practical characterization for the described system structure is performed introducing special transfer functions utilized for the interactions assessment. Experimental results are provided to support the presented analysis procedure.

Assigning diameter distribution typologies to an ALS data grid map

distribuciones diamétricas con ALS

Middleware architectures for the Smart Grid : survey and challenges in the foreseeable future

The traditional power grid is just a one-way supplier that gets no feedback data about the energy delivered, what tariffs could be the most suitable ones for customers, the shifting daily needs of electricity in a facility, etc. Therefore, it is only natural that efforts are being invested in improving power grid behavior and turning it into a Smart Grid. However, to this end, several components have to be either upgraded or created from scratch. Among the new components required, middleware appears as a critical one, for it will abstract all the diversity of the used devices for power transmission (smart meters, embedded systems, etc.) and will provide the application layer with a homogeneous interface involving power production and consumption management data that were not able to be provided before. Additionally, middleware is expected to guarantee that updates to the current metering infrastructure (changes in service or hardware availability) or any added legacy measuring appliance will get acknowledged for any future request. Finally, semantic features are of major importance to tackle scalability and interoperability issues. A survey on the most prominent middleware architectures for Smart Grids is presented in this paper, along with an evaluation of their features and their strong points and weaknesses.

A theory of electron collection by a grid sphere

Use of a spherical grid as electron collector at the anodic end of a tether, as recently proposed, is considered. The standard analysis of space-charge limited current to a solid sphere (with neither magnetic nor plasma-motion effects), which has been shown to best fit TSS1R in-orbit results at very high bias, is used to determine effects from grid transparency on current collected; the analysis is first reformulated in the formalism recently introduced in the two-dimensional analysis of bare-tethers. A discussion of the electric potential created by a spherical grid in vacuum is then carried out; it is shown that each grid-wire collects current well below its maximum OML current, the effective grid transparency being close to its optical value. Formulae for the current to a spherical grid, showing the effects of grid transparency, is determined. A fully consistent analysis of electric potential and electron density, outside and inside the grid, is completed.

Nationwide impact and vehicle to grid application of electric vehicles mobility using an activity based model

This paper describes the impact of electric mobility on the transmission grid in Flanders region (Belgium), using a micro-simulation activity based models. These models are used to provide temporal and spatial estimation of energy and power demanded by electric vehicles (EVs) in different mobility zones. The increment in the load demand due to electric mobility is added to the background load demand in these mobility areas and the effects over the transmission substations are analyzed. From this information, the total storage capacity per zone is evaluated and some strategies for EV aggregator are proposed, allowing the aggregator to fulfill bids on the electricity markets.

Network assisted content protection architectures for a connected world

Content protection is a key component for the success of a multimedia services platform, as proven by the plethora of solutions currently on the market. In this paper we analyze a new network scenario where permanent bidirectional connectivity and video-aware encryption technologies allow a trustful operation of ubiquitous end devices. We propose new scalable models for a content protection architecture that may achieve dramatic improvement in robustness, reliability, and scalability. Selective ciphering and countermeasures are included in those models, together with several examples of their application.

Construction of a Pendentive Grid Crossing Vault

Nuts & bolts of construction history : culture, technology and society :[proceedings of the Fourth International Congress on Construction History, Paris, 3-7 July 2012. ISBN: 978-2-7084-0929-3 . Vol 1 págs 81 a 88

A semantic middleware architecture focused on data and heterogeneity management within the Smart Grid

There is an increasing tendency of turning the current power grid, essentially unaware of variations in electricity demand and scattered energy sources, into something capable of bringing a degree of intelligence by using tools strongly related to information and communication technologies, thus turning into the so-called Smart Grid. In fact, it could be considered that the Smart Grid is an extensive smart system that spreads throughout any area where power is required, providing a significant optimization in energy generation, storage and consumption. However, the information that must be treated to accomplish these tasks is challenging both in terms of complexity (semantic features, distributed systems, suitable hardware) and quantity (consumption data, generation data, forecasting functionalities, service reporting), since the different energy beneficiaries are prone to be heterogeneous, as the nature of their own activities is. This paper presents a proposal on how to deal with these issues by using a semantic middleware architecture that integrates different components focused on specific tasks, and how it is used to handle information at every level and satisfy end user requests.

Experiences and methodology in a multidisciplinary energy and architecture competition: Solar Decathlon Europe 2012

Solar Decathlon Europe is an international competition among universities which promotes interdisciplinary learning in engineering and architecture. Students from different disciplines participate in teams guided by several professors during a 29 month preparation period plus five weeks of on-site contest. The educational project involves designing, building and testing a solar energy house connected to the electrical grid with the strategy of maximizing self-consumption, supported by bioclimatic technologies and maintaining a low environmental footprint. It culminates in a on-site contest in which teams must assembly the house themselves, test it with ordinary real life tasks and finally disassembly it. The event has also a divulgative aim, trying to make students and visitors get interested in discovering the problems presented by real engineering and architecture applications. In addition, SDE covers R&D aspects in different fields such as energy efficiency, solar energy and bioclimatic architecture. This article presents the methodology followed during the SDE 2012 edition, in which more than 850 students participated. The obtained results show that the educational competition was a success according to the technical and professional ambitions of the students, most of them considering that their knowledge had increased in areas related to technical and multidisciplinary aspects.

Improving photovoltaics grid integration through short time forecasting and self-consumption

The uncertainty associated to the forecast of photovoltaic generation is a major drawback for the widespread introduction of this technology into electricity grids. This uncertainty is a challenge in the design and operation of electrical systems that include photovoltaic generation. Demand-Side Management (DSM) techniques are widely used to modify energy consumption. If local photovoltaic generation is available, DSM techniques can use generation forecast to schedule the local consumption. On the other hand, local storage systems can be used to separate electricity availability from instantaneous generation; therefore, the effects of forecast error in the electrical system are reduced. The effects of uncertainty associated to the forecast of photovoltaic generation in a residential electrical system equipped with DSM techniques and a local storage system are analyzed in this paper. The study has been performed in a solar house that is able to displace a residential user?s load pattern, manage local storage and estimate forecasts of electricity generation. A series of real experiments and simulations have carried out on the house. The results of this experiments show that the use of Demand Side Management (DSM) and local storage reduces to 2% the uncertainty on the energy exchanged with the grid. In the case that the photovoltaic system would operate as a pure electricity generator feeding all generated electricity into grid, the uncertainty would raise to around 40%.