237 research outputs found
An intelligent self-configurable mechanism for distributed energy storage systems
Next generation of smart grid technologies demand intel-
ligent capabilities for communication, interaction, monitoring, storage,
and energy transmission. Multiagent systems are envisioned to provide
autonomic and adaptability features to these systems in order to gain
advantage in their current environments. In this paper we present a
mechanism for providing distributed energy storage systems (DESSs)
with intelligent capabilities. In more detail, we propose a self-con gurable
mechanism which allows a DESS to adapt itself according to the future
environmental requirements. This mechanism is aimed at reducing the
costs at which energy is purchased from the market.This work has been partially supported by projects TIN2012-36586-C03-01 and TIN2011-27652-C03-01.Alberola Oltra, JM.; Julian Inglada, VJ.; GarcĂa-Fornes, A. (2014). An intelligent self-configurable mechanism for distributed energy storage systems. Cybernetics and Systems. 45(3):292-305. https://doi.org/10.1080/01969722.2014.894859S292305453Abbey , C. and G. Joos . âCoordination of Distributed Storage with Wind Energy in a Rural Distribution System.â Paper presented at Industry Applications Conference, 42nd IAS Annual Meeting, September 23â27, 2007, New Orleans, USA .Alberola , J. M. , V. Julian , and A. Garcia-Fornes . âMulti-Dimensional Transition Deliberation for Organization Adaptation in Multiagent Systems.â Paper presented at the 11th International Conference on Aut. Agents and MAS (AAMAS12), June 4â8, 2012, Valencia, Spain .Chouhan , N. S. and M. Ferdowsi . âReview of Energy Storage Systems.â Paper presented at North American Power Symposium (NAPS), October 4â6, 2009, Mississippi, USA.Conejo, A. J., Plazas, M. A., Espinola, R., & Molina, A. B. (2005). Day-Ahead Electricity Price Forecasting Using the Wavelet Transform and ARIMA Models. IEEE Transactions on Power Systems, 20(2), 1035-1042. doi:10.1109/tpwrs.2005.846054Costa , L. , F. Bourry , J. Juban , and G. Kariniotakis . âManagement of Energy Storage Coordinated with Wind Power under Electricity Market Conditions.â Paper presented at 10th International Conference on Probabilistic Methods Applied to Power Systems, May 25â29, 2008, RincĂłn, Puerto Rico .Eyer , J. and G. Corey . âEnergy Storage for the Electricity Grid: Benefits and Market Potential Assessment Guide.â Sandia National Laboratories, 2010. Technical Report .Jiang , Z. âAgent-Based Control Framework for Distributed Energy Resources Microgrids.â Paper presented at International Conference on Intelligent Agent Technology, December 18â22, 2006, Hong Kong .Karnouskos , S. and T. N. De Holanda . âSimulation of a Smart Grid City with Software Agents.â Paper presented at Third UKSim European Symposium on Computer Modeling and Simulation, November 25â27, 2009, Athens, Greece .Ketter, W., Collins, J., & Reddy, P. (2013). Power TAC: A competitive economic simulation of the smart grid. Energy Economics, 39, 262-270. doi:10.1016/j.eneco.2013.04.015Lakshman, A., & Malik, P. (2010). Cassandra. ACM SIGOPS Operating Systems Review, 44(2), 35. doi:10.1145/1773912.1773922Logenthiran, T., Srinivasan, D., Khambadkone, A. M., & Aung, H. N. (2012). Multiagent System for Real-Time Operation of a Microgrid in Real-Time Digital Simulator. IEEE Transactions on Smart Grid, 3(2), 925-933. doi:10.1109/tsg.2012.2189028Maly, D. K., & Kwan, K. S. (1995). Optimal battery energy storage system (BESS) charge scheduling with dynamic programming. IEE Proceedings - Science, Measurement and Technology, 142(6), 453-458. doi:10.1049/ip-smt:19951929Mihailescu , R. C. , M. Vasirani , and S. Ossowski . âDynamic Coalition Formation and Adaptation for Virtual Power Stations in Smart Grids.â Paper presented at 2nd International Workshop on Agent Technologies for Energy Systems, May 2, 2011, Taipei, Taiwan .Mohd , A. , E. Ortjohann , A. Schmelter , N. Hamsic , and D. Morton . âChallenges in Integrating Distributed Energy Storage Systems into Future Smart Grid.â Paper presented at IEEE International Symposium on Industrial Electronics, June 30âJuly 2, 2008, Cambridge, UK .Mohsenian-Rad, A.-H., & Leon-Garcia, A. (2010). Optimal Residential Load Control With Price Prediction in Real-Time Electricity Pricing Environments. IEEE Transactions on Smart Grid, 1(2), 120-133. doi:10.1109/tsg.2010.2055903Momoh , J. A. âSmart Grid Design for Efficient and Flexible Power Networks Operation and Control.â Paper presented at IEEE PES Power Systems Conference and Exposition, March 15â18, 2009, Seattle, USA .Nguyen, C. P., & Flueck, A. J. (2012). Agent Based Restoration With Distributed Energy Storage Support in Smart Grids. IEEE Transactions on Smart Grid, 3(2), 1029-1038. doi:10.1109/tsg.2012.2186833Nourai , A. âInstallation of the First Distributed Energy Storage System (DESS) At American Electric Power.â Sandia National Laboratories, 2007. Technical Report.Oyarzabal , J. , J. Jimeno , J. Ruela , A. Engler , and C. Hardt . âAgent Based Micro Grid Management System.â Paper presented at International Conference on Future Power Systems, November 16â18, 2005, Amsterdam, Netherlands .Pinson, P., Chevallier, C., & Kariniotakis, G. N. (2007). Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power. IEEE Transactions on Power Systems, 22(3), 1148-1156. doi:10.1109/tpwrs.2007.901117Pipattanasomporn , M. , H. Feroze , and S. Rahman . âMulti-agent Systems in a Distributed Smart Grid: Design and Implementation.â Paper presented at IEEE/PES Power Systems Conference and Exposition, March 15â18, 2009, Seattle, USA .Reddy , P. P. and M. M. Veloso . âFactored Models for Multiscale Decision Making in Smart Grid Customers.â Paper presented at the Twenty-sixth AAAI Conference on Artificial Intelligence, July 22â26, 2012, Toronto, Canada .Ribeiro, P. F., Johnson, B. K., Crow, M. L., Arsoy, A., & Liu, Y. (2001). Energy storage systems for advanced power applications. Proceedings of the IEEE, 89(12), 1744-1756. doi:10.1109/5.975900Schutte , S. and M. Sonnenschein . âMosaik-Scalable Smart Grid Scenario Specification.â Paper presented at Proceedings of the 2012 Winter Simulation Conference (WSC), December 9â12, 2012, Berlin, Germany .Sioshansi, R., Denholm, P., Jenkin, T., & Weiss, J. (2009). Estimating the value of electricity storage in PJM: Arbitrage and some welfare effects. Energy Economics, 31(2), 269-277. doi:10.1016/j.eneco.2008.10.005Szkuta, B. R., Sanabria, L. A., & Dillon, T. S. (1999). Electricity price short-term forecasting using artificial neural networks. IEEE Transactions on Power Systems, 14(3), 851-857. doi:10.1109/59.780895Van Dam, K. H., Houwing, M., Lukszo, Z., & Bouwmans, I. (2008). Agent-based control of distributed electricity generation with micro combined heat and powerâCross-sectoral learning for process and infrastructure engineers. Computers & Chemical Engineering, 32(1-2), 205-217. doi:10.1016/j.compchemeng.2007.07.012Vosen, S. (1999). Hybrid energy storage systems for stand-alone electric power systems: optimization of system performance and cost through control strategies. International Journal of Hydrogen Energy, 24(12), 1139-1156. doi:10.1016/s0360-3199(98)00175-xVytelingum , P. , T. D. Voice , S. Ramchurn , A. Rogers , and N. R. Jennings . âAgent-Based Micro-Storage Management for the Smart Grid.â Paper presented at Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems, May 10â14, 2010a, Toronto, Canada .Vytelingum , P. , T. D. Voice , S. Ramchurn , A. Rogers , and N. R. Jennings . âIntelligent Agents for the Smart Grid.â Paper presented at the 9th International Conference on Autonomous Agents and Multiagent Systems, May 10â14, 2010b, Toronto, Canada
Clinical and Organizational Factors Related to the Reduction of Mechanical Restraint Application in an Acute Ward: An 8-Year Retrospective Analysis
Background:
The purpose of this study was to describe the frequency of mechanical restraint use in an acute psychiatric ward and to analyze which variables may have significantly influenced the use of this procedure. Methods: This retrospective study was conducted in the Servizio Psichiatrico di Diagnosi e Cura (SPDC) of Modena Centro. The following variables of our sample, represented by all restrained patients admitted from 1-1-2005 to 31-12-2012, were analyzed: age, gender, nationality, psychiatric diagnoses, organic comorbidity, state and duration of admission, motivation and duration of restraints, nursing shift and hospitalization day of restraint, number of patients admitted at the time of restraint and institutional changes during the observation period. The above variables were statistically compared with those of all other non-restrained patients admitted to our ward in the same period. Results: Mechanical restraints were primarily used as a safety procedure to manage aggressive behavior of male patients, during the first days of hospitalization and night shifts. Neurocognitive disorders, organic comorbidity, compulsory state and long duration of admission were statistically significantly related to the increase of restraint use (p<.001, multivariate logistic regression). Institutional changes, especially more restricted guidelines concerning restraint application, were statistically significantly related to restraint use reduction (p<.001, chi2 test, multivariate logistic regression). Conclusion: The data obtained highlight that mechanical restraint use was influenced not only by clinical factors, but mainly by staff and policy factors, which have permitted a gradual but significant reduction in the use of this procedure through a multidimensional approach
Human germline heterozygous gain-of-function STAT6 variants cause severe allergic disease
sharma et al. define a new primary atopic disorder caused by heterozygous gain-of-function variants in STAT6. this results in severe, early-onset allergies, and is seen in 16 patients from 10 families. Anti-IL-4R & alpha; antibody and JAK inhibitor treatment were highly effective.STAT6 (signal transducer and activator of transcription 6) is a transcription factor that plays a central role in the pathophysiology of allergic inflammation. we have identified 16 patients from 10 families spanning three continents with a profound phenotype of early-life onset allergic immune dysregulation, widespread treatment-resistant atopic dermatitis, hypereosinophilia with esosinophilic gastrointestinal disease, asthma, elevated serum IgE, IgE-mediated food allergies, and anaphylaxis. the cases were either sporadic (seven kindreds) or followed an autosomal dominant inheritance pattern (three kindreds). all patients carried monoallelic rare variants in STAT6 and functional studies established their gain-of-function (GOF) phenotype with sustained STAT6 phosphorylation, increased STAT6 target gene expression, and T(H)2 skewing. Precision treatment with the anti-IL-4R & alpha; antibody, dupilumab, was highly effective improving both clinical manifestations and immunological biomarkers. this study identifies heterozygous GOF variants in STAT6 as a novel autosomal dominant allergic disorder. We anticipate that our discovery of multiple kindreds with germline STAT6 GOF variants will facilitate the recognition of more affected individuals and the full definition of this new primary atopic disorder
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