University of Luxembourg

About: University of Luxembourg is a education organization based out in Luxembourg, Luxembourg. It is known for research contribution in the topics: Context (language use) & Computer science. The organization has 4744 authors who have published 22175 publications receiving 381824 citations.

Social media use of older adults: a mini-review.

Abstract: Background: Maintaining social relationships has been defined as a core element of aging well. With a considerable amount of older adults living alone, social media provides the possibility to engage in meaningful social contact, e.g. by joining online social networks and online discussion forums. Objective: The review encompasses current knowledge of prerequisites in social media use of older adults such as functional capacity, information and communications technology-related knowledge, and favorable attitudes towards social media. Then, the potential of social media use for clinical practice and possible negative consequences are outlined. Method: Literature on social media use from a gerontological perspective was reviewed in July and August 2012. Results: Online communities are suitable for providing and receiving social support when confronted with a difficult life situation, regardless of geographical location or time. From a practitioner’s perspective, social media can be used to advance health-related knowledge such as informa

PRODORIC: prokaryotic database of gene regulation

Abstract: The database PRODORIC aims to systematically organize information on prokaryotic gene expression, and to integrate this information into regulatory networks. The present version focuses on pathogenic bacteria such as Pseudomonas aeruginosa. PRODORIC links data on environmental stimuli with trans-acting transcription factors, cis-acting promoter elements and regulon definition. Interactive graphical representations of operon, gene and promoter structures including regulator-binding sites, transcriptional and translational start sites, supplemented with information on regulatory proteins are available at varying levels of detail. The data collection provided is based on exhaustive analyses of scientific literature and computational sequence prediction. Included within PRODORIC are tools to define and predict regulator binding sites. It is accessible at http://prodoric.tu-bs.de.

Consistent estimation of Gibbs energy using component contributions

Abstract: Standard Gibbs energies of reactions are increasingly being used in metabolic modeling for applying thermodynamic constraints on reaction rates, metabolite concentrations and kinetic parameters. The increasing scope and diversity of metabolic models has led scientists to look for genome-scale solutions that can estimate the standard Gibbs energy of all the reactions in metabolism. Group contribution methods greatly increase coverage, albeit at the price of decreased precision. We present here a way to combine the estimations of group contribution with the more accurate reactant contributions by decomposing each reaction into two parts and applying one of the methods on each of them. This method gives priority to the reactant contributions over group contributions while guaranteeing that all estimations will be consistent, i.e. will not violate the first law of thermodynamics. We show that there is a significant increase in the accuracy of our estimations compared to standard group contribution. Specifically, our cross-validation results show an 80% reduction in the median absolute residual for reactions that can be derived by reactant contributions only. We provide the full framework and source code for deriving estimates of standard reaction Gibbs energy, as well as confidence intervals, and believe this will facilitate the wide use of thermodynamic data for a better understanding of metabolism.

Contingency Ranking With Respect to Overloads in Very Large Power Systems Taking Into Account Uncertainty, Preventive, and Corrective Actions

Abstract: This paper deals with day-ahead security management with respect to a postulated set of contingencies, while taking into account uncertainties about the next day generation/load scenario In order to help the system operator in decision making under uncertainty, we aim at ranking these contingencies into four clusters according to the type of control actions needed to cover the worst uncertainty pattern of each contingency with respect to branch overload To this end we use a fixed point algorithm that loops over two main modules: a discrete bi-level program (BLV) that computes the worst-case scenario, and a special kind of security constrained optimal power flow (SCOPF) which computes optimal preventive/corrective actions to cover the worst-case We rely on a DC grid model, as the large number of binary variables, the large size of the problem, and the stringent computational requirements preclude the use of existing mixed integer nonlinear programming (MINLP) solvers Consequently we solve the SCOPF using a mixed integer linear programming (MILP) solver while the BLV is decomposed into a series of MILPs We provide numerical results with our approach on a very large European system model with 9241 buses and 5126 contingencies