999 resultados para compound-leaved groups
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p.153-169
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p.71-81
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This paper extends the standard network centrality measures of degree, closeness and betweenness to apply to groups and classes as well as individuals. The group centrality measures will enable researchers to answer such questions as ‘how central is the engineering department in the informal influence network of this company?’ or ‘among middle managers in a given organization, which are more central, the men or the women?’ With these measures we can also solve the inverse problem: given the network of ties among organization members, how can we form a team that is maximally central? The measures are illustrated using two classic network data sets. We also formalize a measure of group centrality efficiency, which indicates the extent to which a group's centrality is principally due to a small subset of its members.
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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.
Mesoscale distribution of dominant bacterioplankton groups in the northern North Sea in early summer
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Past years have seen the development of different approaches to detect phytoplankton groups from space. One of these methods, the PHYSAT one, is empirically based on reflectance anomalies. Despite observations in good agreement with in situ measurements, the underlying theoretical explanation of the method is still missing and needed by the ocean color community as it prevents improvements of the methods and characterization of uncertainties on the inversed products. In this study, radiative transfer simulations are used in addition to in situ measurements to understand the organization of the signals used in PHYSAT. Sensitivity analyses are performed to assess the impact of the variability of the following three parameters on the reflectance anomalies: specific phytoplankton absorption, colored dissolved organic matter absorption, and particles backscattering. While the later parameter explains the largest part of the anomalies variability, results show that each group is generally associated with a specific bio-optical environment which should be considered to improve methods of phytoplankton groups detection.