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Mavrotas G.,National Technical University of Athens | Skoulaxinou S.,EPEM S.A. | Gakis N.,FACETS S.A. | Katsouros V.,Athena Research and Innovation Center | Georgopoulou E.,National Observatory of Athens
Waste Management

In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty years they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH4 generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the application of the model in a Greek region. © 2013 Elsevier Ltd. Source

Mavrotas G.,National Technical University of Athens | Gakis N.,FACETS S.A. | Skoulaxinou S.,EPEM S.A. | Katsouros V.,Athena Research and Innovation Center | Georgopoulou E.,National Observatory of Athens
Renewable and Sustainable Energy Reviews

Energy production from Municipal Solid Waste (MSW) has become one of the most prominent strategies in MSW management. In this study a multi-objective mathematical programming model is developed in order to provide the candidate (Pareto optimal) solutions for a MSW management system performing structural, design and operational optimization. Besides the economic criterion the Green House Gas (GHG) emissions are taken into account as a second optimization criterion. Therefore, we do not obtain just an optimal solution (i.e. least cost), but a set of Pareto optimal solutions that spread from minimum cost to minimum GHG emissions. Each Pareto optimal solution provides the corresponding technologies and the capacities that are associated with it. An innovative issue is that we incorporate the external costs/benefits associated with (a) atmospheric pollution impacts (b) impacts on soil and groundwater (c) impacts on quality of life (d) electricity use/displacement (e) fertilizer use reduction from compost. Using the external costs/benefits as an additional term in the cost objective significantly affects the results especially regarding the Waste-to-Energy options. This is clearly illustrated in the case study for the MSW management of the Athens region in Greece. © 2015 Elsevier Ltd. All rights reserved. Source

Vlachos I.S.,University of Thessaly | Vlachos I.S.,National and Kapodistrian University of Athens | Paraskevopoulou M.D.,University of Thessaly | Karagkouni D.,University of Thessaly | And 11 more authors.
Nucleic Acids Research

MicroRNAs (miRNAs) are short non-coding RNA species, which act as potent gene expression regulators. Accurate identification of miRNA targets is crucial to understanding their function. Currently, hundreds of thousands of miRNA:gene interactions have been experimentally identified. However, this wealth of information is fragmented and hidden in thousands of manuscripts and raw nextgeneration sequencing data sets. DIANA-TarBase was initially released in 2006 and it was the first database aiming to catalog published experimentally validated miRNA:gene interactions. DIANA-TarBase v7.0 (http://www.microrna.gr/tarbase) aims to provide for the first time hundreds of thousands of high-quality manually curated experimentally validated miRNA:gene interactions, enhanced with detailed meta-data. DIANA-TarBase v7.0 enables users to easily identify positive or negative experimental results, the utilized experimental methodology, experimental conditions including cell/tissue type and treatment. The new interface provides also advanced information ranging from the binding site location, as identified experimentally as well as in silico, to the primer sequences used for cloning experiments. More than half a million miRNA:gene interactions have been curated from published experiments on 356 different cell types from 24 species, corresponding to 9- to 250-fold more entries than any other relevant database. DIANA-TarBase v7.0 is freely available. © The Author(s) 2014. Source

Paraskevopoulou M.D.,University of Thessaly | Paraskevopoulou M.D.,Hellenic Pasteur Institute | Vlachos I.S.,University of Thessaly | Vlachos I.S.,Hellenic Pasteur Institute | And 17 more authors.
Nucleic Acids Research

MicroRNAs (miRNAs) are short non-coding RNAs (ncRNAs) that act as post-transcriptional regulators of coding gene expression. Long non-coding RNAs (lncRNAs) have been recently reported to interact with miRNAs. The sponge-like function of lncRNAs introduces an extra layer of complexity in the miRNA interactome. DIANA-LncBase v1 provided a database of experimentally supported and in silico predicted miRNA Recognition Elements (MREs) on lncRNAs. The second version of LncBase (www.microrna.gr/LncBase) presents an extensive collection of miRNA:lncRNA interactions. The significantly enhanced database includes more than 70 000 low and high-throughput, (in)direct miRNA:lncRNA experimentally supported interactions, derived from manually curated publications and the analysis of 153 AGO CLIP-Seq libraries. The new experimental module presents a 14-fold increase compared to the previous release. LncBase v2 hosts in silico predicted miRNA targets on lncRNAs, identified with the DIANA-microT algorithm. The relevant module provides millions of predicted miRNA binding sites, accompanied with detailed metadata and MRE conservation metrics. LncBase v2 caters information regarding cell type specific miRNA:lncRNA regulation and enables users to easily identify interactions in 66 different cell types, spanning 36 tissues for human and mouse. Database entries are also supported by accurate lncRNA expression information, derived from the analysis of more than 6 billion RNA-Seq reads. © The Author(s) 2015. Source

Liakos P.,Athena Research and Innovation Center | Koltsida P.,Athena Research and Innovation Center | Kakaletris G.,Athena Research and Innovation Center | Baumann P.,Jacobs University Bremen
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

The ever growing amount of information collected by scientific instruments and the presence of descriptive metadata accompanying them calls for a unified way of querying over array and semi-structured data. We present xWCPS, a novel query language that bridges the path between these two different worlds, enhancing the expressiveness and user-friendliness of previous approaches. © Springer International Publishing Switzerland 2015. Source

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