How to use content analysis in historical research

This paper illustrates the use of a content analysis in historical research. The purpose of a content analysis study is to illustrate the ways in which an individual organization participates in the processes of social change

Zooplankton ecology of Norton Sound, Alaska

Thesis (M.S.) University of Alaska Fairbanks, 1979The zooplankton distribution in Norton Sound was monitored for the Outer Continental Shelf Environmental Assessment Program. Salinity, temperature, and predation were investigated as factors controlling species composition and community structure. Sampling was concentrated along the eastern coast of Norton Sound during July and August, 1976. The copepod Acartia clausi and the cladocerans Evadne sp. and Podon sp. were numerically dominant in the samples. These species are able to tolerate the widely ranging salinities and temperatures of the coastal waters. The A. clausi population abundance was correlated with water temperature, while cladoceran and larval mollusc populations were correlated with salinity. No differences in species composition were discerned between stations along the shallow coast; however, the seaward community contained a greater diversity of organisms supporting a larger planktonic carnivore biomass. Zooplankton was a numerically dominant item in the diets of many fish species, although the epibenthic mysid community was volumetrically most important

Synchrony in networks of coupled non-smooth dynamical systems: extending the master stability function

The master stability function is a powerful tool for determining synchrony in high-dimensional networks of coupled limit cycle oscillators. In part, this approach relies on the analysis of a low-dimensional variational equation around a periodic orbit. For smooth dynamical systems, this orbit is not generically available in closed form. However, many models in physics, engineering and biology admit to non-smooth piece-wise linear caricatures, for which it is possible to construct periodic orbits without recourse to numerical evolution of trajectories. A classic example is the McKean model of an excitable system that has been extensively studied in the mathematical neuroscience community. Understandably, the master stability function cannot be immediately applied to networks of such non-smooth elements. Here, we show how to extend the master stability function to non-smooth planar piece-wise linear systems, and in the process demonstrate that considerable insight into network dynamics can be obtained. In illustration, we highlight an inverse period- doubling route to synchrony, under variation in coupling strength, in globally linearly coupled networks for which the node dynamics is poised near a homoclinic bifurcation. Moreover, for a star graph, we establish a mechanism for achieving so-called remote synchronisation (where the hub oscillator does not synchronise with the rest of the network), even when all the oscillators are identical. We contrast this with node dynamics close to a non-smooth Andronov–Hopf bifurcation and also a saddle node bifurcation of limit cycles, for which no such bifurcation of synchrony occurs

Mechanical systems subjected to generalized nonholonomic constraints

We study mechanical systems subject to constraint functions that can be dependent at some points and independent at the rest. Such systems are modelled by means of generalized codistributions. We discuss how the constraint force can transmit an impulse to the motion at the points of dependence and derive an explicit formula to obtain the ``post-impact'' momentum in terms of the ``pre-impact'' momentum.Comment: 24 pages, no figure

Counting and computing regions of DD-decomposition: algebro-geometric approach

New methods for $D$-decomposition analysis are presented. They are based on topology of real algebraic varieties and computational real algebraic geometry. The estimate of number of root invariant regions for polynomial parametric families of polynomial and matrices is given. For the case of two parametric family more sharp estimate is proven. Theoretic results are supported by various numerical simulations that show higher precision of presented methods with respect to traditional ones. The presented methods are inherently global and could be applied for studying $D$-decomposition for the space of parameters as a whole instead of some prescribed regions. For symbolic computations the Maple v.14 software and its package RegularChains are used.Comment: 16 pages, 8 figure