Academic Research. ACI may provide Tau-Active Antibody material existing prior the Effective Date to Katholieke Universiteit Leuven (“K.U. Leuven”) solely for use in the academic research performed under the agreement entered into between ACI and K.U. Leuven effective as of July 1, 2008 (the “K.U. Leuven Agreement”) provided, however, that (i) use of such Tau-Active Antibodies shall not conflict with Genentech’s exclusive rights under this Agreement; and (ii) all intellectual property rights (including but not limited to Patents and Know-How) made pursuant to the K.U. Leuven Agreement shall be included within the ACI IP Rights to the extent necessary or useful to Genentech in exercising its rights under the licenses granted in this Agreement.
Academic Research. The Research and any or all related work and activity performed by the Postdoctoral Fellow during the term of this Agreement is intended to be in support of the Postdoctoral Fellow and is training in benefit of the Postdoctoral Fellow’s academic advancement.
Academic Research. The user may only use the database for academic research.
Academic Research. ACI may provide [*****] material to Ecole Polytechnique Federale de Lausanne (“EPFL”) solely for use in the academic research contemplated under the agreement entered into between ACI and EPFL effective as of June 1, 2006 (the “EPFL Agreement”) provided, however, that (i) use of such [*****] shall not conflict with Genentech’s exclusive rights under this Agreement; (ii) all intellectual property rights (including but not limited to Patents and Know-How) made pursuant to the EPFL Agreement shall be included within the ACI IP Rights to the extent necessary or useful to Genentech in exercising its rights under the licenses granted in this Agreement; and (iii) publication of any research results shall be subject to Section 12.5 of this Agreement.
Academic Research. In addition to the evaluation research projects discussed above, WPREU is working with academic staff across the university who have a research interest in this area to deliver a range of institution-specific projects. We intend that outcomes of these projects will be disseminated across the sector. Current examples include: Sheffield Student 2013 - using qualitative methods to track the lowest income students through three years of study to inform future development of financial and other student support packages; A qualitative project exploring the impact of our intensive WP programmes on students and alumni, focusing on our intensive programmes in Medicine and Law; A qualitative project exploring the decision-making process of the most able students who decide not to progress onto University at Key Stages 4 and 5; Detailed research into the impact and perception of our financial support packages, pre- and post-arrival. WPREU are also co-ordinating a researcher network that brings together researchers and practitioners with an interest in this area to encourage cross-fertilisation.
Academic Research. Educational research done in the usual course in the pursuit of a degree, instructional (i.e., educational and training) use in a classroom setting; or research by faculty and students which is funded by the government or non-profit research foundations and intended for publication in the publicly available literature; provided, however, that to qualify as Academic Research, the research must not involve patentability searching.
Academic Research. LICENSEE may release the Stock or progeny thereof to academic researchers at nonprofit institutions and to scientific researchers employed by the U.S. government, in each case for research purposes only, provided that such release is made under substantially the same terms as those set forth in Exhibit A attached hereto. Any such agreement and terms shall be strictly subject to approval by MAYO, which shall have sole discretion for such approval.
Academic Research. ACI may provide [*****] material existing prior the Effective Date to Katholieke Universiteit Leuven (“K.U. Leuven”) solely for use in the academic research performed under the agreement entered into between ACI and K.U. Leuven effective as of July 1, 2008 (the “K.U. Leuven Agreement”) provided, however, that (i) use of such [*****] shall not conflict with Genentech’s exclusive rights under this Agreement; and (ii) all intellectual property rights (including but not limited to Patents and Know-How) made pursuant to the K.U. Leuven Agreement shall be included within the ACI IP Rights to the extent necessary or useful to Genentech in exercising its rights under the licenses granted in this Agreement.
Academic Research. The design of orchestration mechanisms for data centres and clouds is a topic with considerable current momentum within the research community. While a number of efforts consider orchestration of resources in cases of several DCs (geo-dispersed, distributed, federated, etc.) [2][3][4][5][6][7] most of the works focus on orchestration resources within a single DC. Within these, there are some interesting papers [8][9] establishing the similarity of operation of DCs, from the point of view of consumption of resources, with the operation over databases (DBs). They present the need for characterising DC orchestration operations with similar “ACIDity” properties as in DBs: atomicity, consistency, isolation and durability. The need to model and abstract DC resources as structured data, to be queried from consuming applications, as described in Section 3.2, is also grounded by these characteristics. Several papers analyse inter DC resources orchestration, without specific differentiation between computing, storage or networking resources and in a generic way [10][11][12][13][14], while others focus on efficiency optimisation with cost functions, based on energy consumption as optimisation target, as, for example, in [15]. From the point of view of this document, and in the context of COSIGN, a set of work with specific focus on orchestration of network resources within a DC is especially relevant. Within this category the work at [16] presents Stratos as an SDN-based composition and provisioning mechanism to orchestrate services based on virtual middleboxes within a DC. Based on Floodlight as SDN controller, an implementation uses tagging and per flow rules for traffic management. Based on metrics of end to end performance as decision indicator, Stratos achieves traffic load balancing within the DC by means of flow distribution, proposes horizontal scaling mechanisms to face network bottleneck issues within the DC and proposes migration of VM instances to complement these operations.
Academic Research. TAPAS We discuss one academic project we have been involved in since it contributes some interesting technologies to agreement-driven service management [14,38,39,55]. The project is called TAPAS, which stands for Trusted and QoS– Aware Provision of Application Services, which has as one aim to develop QoS enabled middleware capable of meeting SLAs between pairs of interacting par- ties. It is representative for a range of adaptive middlewares, such as those sur- veyed in [51], but is of particular interest because of its focus on the service provider model. In a typical TAPAS scenario a service provider provides its services to sev- eral consumers whose access to the service might overlap. The services required by each client are not necessarily the same and neither are the SLAs that they Contract Service description: The service provider (SP) will provide 1 GByte of storage to the service con- sumer (SC) for 6 months … service owner
