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This is a conference paper. ; Consortia are becoming an increasingly common model for implementing WASH programmes. The DRC WASH Consortium led by Concern Worldwide is a consortium of five international NGOs in the Democratic Republic of the Congo. This paper presents the lessons learned since the Consortium's creation in 2013. Strengths of the consortium model include: increased scale; capacity for research and learning; an innovative joint strategy to improve sustainability; a credible image in the WASH sector and a positive influence on external stakeholders; and risk-sharing. Challenges include: the continuing logistical difficulties of implementation in rural DRC; previous experience of the member NGOs more focused on emergency WASH rather than development; and the time needed to build relationships and communicate the Consortium approach. Key lessons for success are the importance of strong leadership by the Consortium Coordination Unit, and spotting 'gaps' in WASH sector coordination and learning to help position the Consortium at national level.

The Center for Middle Eastern Studies at the University of Arizona hosted the first multi-language conference in April 1998, which brought together innovative teachers of Arabic, Hebrew, Persian, and Turkish to share new technologies, instructional strategies, and materials. The organizers, Karen Galindo and Amy Newhall, assumed that teachers of these less commonly taught languages faced similar challenges and that exchange among them could be mutually beneficial. This report summarizes selected presentations.

Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world's oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits. ; European Union

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in GigaScience 4 (2015): 27, doi:10.1186/s13742-015-0066-5. ; Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world's oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits. ; This work was supported by the Micro B3 project, which is funded from the European Union's Seventh Framework Programme (FP7; Joint Call OCEAN.2011‐2: Marine microbial diversity – new insights into marine ecosystems functioning and its biotechnological potential) under the grant agreement no 287589.

Some problems cannot be solved optimally and compromises become necessary. In some cases obtaining an optimal solution may require combining algorithms and iterations. This often occurs when the problem is complex and a single procedure does not reach optimality. This paper shows a conglomerate of algorithms iterated in tasks to form an optimal consortium using cluster analysis. Hierarchical methods and distance measures lead the process. Few companies are desirable in optimal consortium formation. However, this study shows that optimization cannot be predetermined based on a specific fixed number of companies. The experiential exercise forms an optimal consortium of four companies from six shortlisted competitors