Finite groups and geometries: a view on the present state and on the future

The model: groups of Lie-Chevalley type and buildingsThis paper is not the presentation of a completed theory but rather a report on a search progressing as in the natural sciences in order to better understand the relationship between groups and incidence geometry, in some future sought-after theory Τ. The search is based on assumptions and on wishes some of which are time-dependent, variations being forced, in particular, by the search itself.A major historical reference for this subject is, needless to say, Klein's Erlangen Programme. Klein's views were raised to a powerful theory thanks to the geometric interpretation of the simple Lie groups due to Tits (see for instance), particularly his theory of buildings and of groups with a BN-pair (or Tits systems). Let us briefly recall some striking features of this.Let G be a group of Lie-Chevalley type of rank r, denned over GF(q), q = pn, p prime. Let Xr denote the Dynkin diagram of G. To these data corresponds a unique thick building B(G) of rank r over the Coxeter diagram Xr (assuming we forget arrows provided by the Dynkin diagram). It turns out that B(G) can be constructed in a uniform way for all G, from a fixed p-Sylow subgroup U of G, its normalizer NG(U) and the r maximal subgroups of G containing NG(U).

When the key is integrate : introduction to development of dormancy behavior groups weeds in agricultural crops

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Effect of agricultural management and weeds on feeding groups of nematode in Soybean

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The centrality of groups and classes

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.

Intrinsic measure of diversity gains in generalised distributed antenna systems with cooperative users

The diversity gains achievable in the generalised distributed antenna system with cooperative users (GDAS-CU) are considered. A GDAS-CU is comprised of M largely separated access points (APs) at one side of the link, and N geographically closed user terminals (UTs) at the other side. The UTs are collaborating together to enhance the system performance, where an idealised message sharing among the UTs is assumed. First, geometry-based network models are proposed to describe the topology of a GDAS-CU. The mean cross-correlation coefficients of signals received from non-collocated APs and UTs are calculated based on the network topology and the correlation models derived from the empirical data. The analysis is also extendable to more general scenarios where the APs are placed in a clustered form due to the constraints of street layout or building structure. Subsequently, a generalised signal attenuation model derived from several stochastic ray-tracing-based pathloss models is applied to describe the power-decaying pattern in urban built-up areas, where the GDAS-CU may be deployed. Armed with the cross-correlation and pathloss model preliminaries, an intrinsic measure of cooperative diversity obtainable from a GDAS-CU is then derived, which is the number of independent fading channels that can be averaged over to detect symbols. The proposed analytical framework would provide critical insight into the degree of possible performance improvement when combining multiple copies of the received signal in such systems.

What’s in a name: Dimensions of social learning in teacher groups

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.

Theoretical analysis of ocean color radiances anomalies and implications for phytoplankton groups detection in case 1 waters

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.

A new procedure to optimize the selection of groups in a classification tree

Agglomerative cluster analyses encompass many techniques, which have been widely used in various fields of science. In biology, and specifically ecology, datasets are generally highly variable and may contain outliers, which increase the difficulty to identify the number of clusters. Here we present a new criterion to determine statistically the optimal level of partition in a classification tree. The criterion robustness is tested against perturbated data (outliers) using an observation or variable with values randomly generated. The technique, called Random Simulation Test (RST), is tested on (1) the well-known Iris dataset [Fisher, R.A., 1936. The use of multiple measurements in taxonomic problems. Ann. Eugenic. 7, 179–188], (2) simulated data with predetermined numbers of clusters following Milligan and Cooper [Milligan, G.W., Cooper, M.C., 1985. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159–179] and finally (3) is applied on real copepod communities data previously analyzed in Beaugrand et al. [Beaugrand, G., Ibanez, F., Lindley, J.A., Reid, P.C., 2002. Diversity of calanoid copepods in the North Atlantic and adjacent seas: species associations and biogeography. Mar. Ecol. Prog. Ser. 232, 179–195]. The technique is compared to several standard techniques. RST performed generally better than existing algorithms on simulated data and proved to be especially efficient with highly variable datasets.