991 resultados para Duprat, Antoine, Cardinal, 1463-1535.


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Solid state IR and Raman as well as aqueous solution state Raman spectra are reported for the linear di-amino acid peptide L-aspartyl-L-glutamic acid (L-Asp-L-Glu); the solution state Raman spectrum has also been obtained for the N,O-deuterated derivative. SCF-DFT calculations at the B3-LYP/cc-pVDZ level established that the structure and vibrational spectra of L-Asp-L-Glu can be interpreted using a model of the peptide with ten hydrogen-bonded water molecules, in conjunction with the conductor-like polarizable continuum solvation method. The DFT calculations resulted in the computation of a stable zwitterionic structure, which displays trans-amide conformation. The vibrational spectra were computed at the optimised molecular geometry, enabling normal coordinate analysis, which yielded satisfactory agreement with the experimental IR and Raman data. Computed potential energy distributions of the normal modes provided detailed vibrational assignments.

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Purpose: The purpose of this paper is to describe the problems encountered and the solutions developed when using benchmarking and key performance indicators (KPIs) to monitor a major UK social house building innovation (change) programme. The innovation programme sought improvements to both the quality of the house product and the procurement process. Design/methodology/approach: Benchmarking and KPIs were used to quantify performance and in-depth case studies to identify underlying cause and effect relationships within the innovation programme. Findings: The inherent competition between consortium members; the complexity of the relationship between the consortium and its strategic partner; the lack of an authoritative management control structure; and the rapidly changing nature of the UK social housing market all proved problematic to the development of a reliable and robust monitoring system. These problems were overcome by the development of multi-dimensional benchmarking model that balanced the needs and aspirations of the individual organisations with the broader objectives of the consortium. Research limitations/implications: Whilst the research methodology provides insight into the factors that affected the performance of a major innovation programme its findings may not be representative of all projects. Practical implications: The lessons learnt should assist those developing benchmarking models for multi-client consortia. Originality/value: The work reported in this paper describes an inclusive approach to benchmarking in which a multiple client group and their strategic partner sought to work together for shared gain. Very few papers have addressed this issue.

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Induced by a literature review, this paper presents a framework of dimensions and indicators highlighting the underpinning aspects and values of social learning within teacher groups. Notions of social networks, communities of practice and learning teams were taken as the main perspectives to influence this social learning framework. The review exercise resulted in four dimensions: (1) practice, (2) domain and value creation, (3) collective identity and (4) organization. The indicators corresponding to these dimensions serve as the foundation for understanding social learning in practice. The framework of dimensions and indicators can be of assistance for researchers as well as teacher groups that aim to assess their views on social learning and analyse whether these views fit the learning goals of the group, or that adjustments are required. In this way, learning processes within groups of teachers can be improved.

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De laatste decennia is er in onderwijspraktijk en onderwijsonderzoek veel aandacht voor sociaal leren van (aanstaande) leraren als een stimulans voor hun professionele ontwikkeling. Bij het nastreven van innovatie in dergelijke lerarengroepen, blijkt faciliteren van belang. In deze studie is onderzocht op welke wijze lerarengroepen gefaciliteerd kunnen worden ter optimalisatie van de professionele ontwikkeling van de groepsleden. Hiervoor is gebruik gemaakt van een eerder ontwikkeld theoretisch kader met 4 dimensies en 11 indicatoren van sociaal leren. Het onderzoek is uitgevoerd in een lerarenopleiding primair onderwijs (pabo) waar groepen van pabodocenten, pabostudenten en leerkrachten primair onderwijs zijn gevolgd gedurende twee jaren in een enkelvoudige en meervoudige casestudie. Data zijn verzameld in de vorm van video/audio-opnames van de werkbijeenkomsten, het beantwoorden van reflectieve vragen, het volgen van de digitale leeromgeving en het uitvoeren van retrospectieve interviews. Op basis van kwalitatieve analyses is op diverse momenten samen met de groepsleden bekeken hoe de sociale configuratie eruit zag, of dit passend was bij de groepsdoelen en welke vervolgstappen wenselijk waren. De in deze studie ontwikkelde interviewleidraad blijkt een bruikbaar kwalitatief instrument in dit faciliteringsproces.

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Ocean color measured from satellites provides daily, global estimates of marine inherent optical properties (IOPs). Semi-analytical algorithms (SAAs) provide one mechanism for inverting the color of the water observed by the satellite into IOPs. While numerous SAAs exist, most are similarly constructed and few are appropriately parameterized for all water masses for all seasons. To initiate community-wide discussion of these limitations, NASA organized two workshops that deconstructed SAAs to identify similarities and uniqueness and to progress toward consensus on a unified SAA. This effort resulted in the development of the generalized IOP (GIOP) model software that allows for the construction of different SAAs at runtime by selection from an assortment of model parameterizations. As such, GIOP permits isolation and evaluation of specific modeling assumptions, construction of SAAs, development of regionally tuned SAAs, and execution of ensemble inversion modeling. Working groups associated with the workshops proposed a preliminary default configuration for GIOP (GIOP-DC), with alternative model parameterizations and features defined for subsequent evaluation. In this paper, we: (1) describe the theoretical basis of GIOP; (2) present GIOP-DC and verify its comparable performance to other popular SAAs using both in situ and synthetic data sets; and, (3) quantify the sensitivities of their output to their parameterization. We use the latter to develop a hierarchical sensitivity of SAAs to various model parameterizations, to identify components of SAAs that merit focus in future research, and to provide material for discussion on algorithm uncertainties and future emsemble applications.