KINSHIP AND HISTORY: TRIBES, GENEALOGIES, AND SOCIAL CHANGE AMONG THE BEDOUIN OF THE EASTERN ARAB WORLD

Most scholars of tribal organization among the Bedouin of the eastern Arab world utilize a two-dimensional, hierarchical model of Bedouin kinship that represents only relations of descent and affinity. This model resembles a genealogy and shows how small descent units are enclosed by larger ones. It implies that tribes grow in size only through biological reproduction. Such a representation of the Bedouin tribe fails to distinguish politically central lineages from politically peripheral lineages and also ignores the processes through which foreign lineages become “attached” as clients to politically powerful, central lineages. To correct and supplement this genealogical model, the author presents a concentric model of Bedouin tribes that adds a “central/peripheral” distinction. This model also includes relations of political “attachment” that can affect the internal morphology and growth of Bedouin tribes in ways that are comparable to the effects of affinal and suckling kinship relations on internal organization. The proposed concentric model thus allows us to represent historical change more accurately and also brings us closer to Bedouin concepts of tribal organization

q-Deformed Supersymmetry and Dynamic Magnon Representations

It was recently noted that the dispersion relation for the magnons of planar N=4 SYM can be identified with the Casimir of a certain deformation of the Poincare algebra, in which the energy and momentum operators are supplemented by a boost generator J. By considering the relationship between J and su(2|2) x R^2, we derive a q-deformed super-Poincare symmetry algebra of the kinematics. Using this, we show that the dynamic magnon representations may be obtained by boosting from a fixed rest-frame representation. We comment on aspects of the coalgebra structure and some implications for the question of boost-covariance of the S-matrix.Comment: 15 pages, LaTeX; (v2) references adde

Data-based mechanistic modelling, forecasting, and control.

This article briefly reviews the main aspects of the generic data based mechanistic (DBM) approach to modeling stochastic dynamic systems and shown how it is being applied to the analysis, forecasting, and control of environmental and agricultural systems. The advantages of this inductive approach to modeling lie in its wide range of applicability. It can be used to model linear, nonstationary, and nonlinear stochastic systems, and its exploitation of recursive estimation means that the modeling results are useful for both online and offline applications. To demonstrate the practical utility of the various methodological tools that underpin the DBM approach, the article also outlines several typical, practical examples in the area of environmental and agricultural systems analysis, where DBM models have formed the basis for simulation model reduction, control system design, and forecastin

HEALTH CARE REFORM: THE IMPLICATIONS FOR HEALTH DATA SYSTEMS

Health Economics and Policy,