17,164 research outputs found
A Nonstochastic Information Theory for Communication and State Estimation
In communications, unknown variables are usually modelled as random
variables, and concepts such as independence, entropy and information are
defined in terms of the underlying probability distributions. In contrast,
control theory often treats uncertainties and disturbances as bounded unknowns
having no statistical structure. The area of networked control combines both
fields, raising the question of whether it is possible to construct meaningful
analogues of stochastic concepts such as independence, Markovness, entropy and
information without assuming a probability space. This paper introduces a
framework for doing so, leading to the construction of a maximin information
functional for nonstochastic variables. It is shown that the largest maximin
information rate through a memoryless, error-prone channel in this framework
coincides with the block-coding zero-error capacity of the channel. Maximin
information is then used to derive tight conditions for uniformly estimating
the state of a linear time-invariant system over such a channel, paralleling
recent results of Matveev and Savkin
Exploring High Dimensional Free Energy Landscapes: Temperature Accelerated Sliced Sampling
Biased sampling of collective variables is widely used to accelerate rare
events in molecular simulations and to explore free energy surfaces. However,
computational efficiency of these methods decreases with increasing number of
collective variables, which severely limits the predictive power of the
enhanced sampling approaches. Here we propose a method called Temperature
Accelerated Sliced Sampling (TASS) that combines temperature accelerated
molecular dynamics with umbrella sampling and metadynamics to sample the
collective variable space in an efficient manner. The presented method can
sample a large number of collective variables and is advantageous for
controlled exploration of broad and unbound free energy basins. TASS is also
shown to achieve quick free energy convergence and is practically usable with
ab initio molecular dynamics techniques
Height-length relation of shells in the Indian backwater oyster Crassostrea madrasensis (Preston) of the Cochin harbour
Height-length relationship in Crassostrea madrasensis (Preston) showed an exponential trend and relation in the form, H=ALá´®. Deviations of actual values from the mean values consequent to the increase in size were noticed. Height and length approximated in oysters of less than 3.5cm in height resulting in orbicular shape. In oyster of shell height 3.5cm to 8cm, increase in height is faster leading to an oval shape. Above 8cm in height, the oysters become further elongated. Height-length relation is non-linear with an index (B value) of 1.1156. A linear relationship also holds good as the B value is not very much different from unity (H=-2.5424+2.0036L)
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