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The mean squared displacement of a tracer particle in a single file of identical particles with excluded volume interactions shows the famed Harris scaling aEurox (2)(t)aEuro parts per thousand a parts per thousand integral K (1/2) t (1/2) as function of time. Here we study what happens to this law when each particle of the single file interacts with the environment such that it is transiently imm
As cell and molecular biology is becoming increasingly quantitative, there is an upsurge of interest in mechanistic modeling at different levels of resolution. Such models mostly concern kinetics and include gene and protein interactions as well as cell population dynamics. The final goal of these models is to provide experimental predictions, which is now taking on. However, even without matured
Fast directional growth is a necessity for the young seedling; after germination, it needs to quickly penetrate the soil to begin its autotrophic life. In most dicot plants, this rapid escape is due to the anisotropic elongation of the hypocotyl, the columnar organ between the root and the shoot meristems. Anisotropic growth is common in plant organs and is canonically attributed to cell wall anis
A novel modified method for obtaining approximate solutions to difficult optimization problems within the neural network paradigm is presented. We consider the graph partition and the travelling salesman problems. The key new ingredient is a reduction of solution space by one dimension by using graded neurons, thereby avoiding the destructive redundancy that has plagued these problems when using s
A general introduction to the use of feed-back artificial neural networks (ANN) for obtaining good approximate solutions to combinatorial optimization problems is given, assuming no previous knowledge in the field. In particular we emphasize a novel neural mapping technique which efficiently reduces the solution space. This approach maps the problems onto Potts glass rather than spin glass models.
A fully integrated instrument for cereal grain quality assessment is presented. Color video images of grains fed onto a belt are digitized. These images are then segmented into kernel entities, which are subject to the analysis. The number of degrees of freedom for each such object is decreased to a suitable level for Artificial Neural Network (ANN) processing. Feed- forward ANN's with one hidden
The authors describe an approach to particle tracking based on deformable templates. Hough transforms are used to give initial conditions for the templates which then converge using a deterministic annealing algorithm. This template approach is closely related to the elastic net algorithm. The authors demonstrate successful results on both simulated and real data. The authors also show how the Hou
We present a novel, versatile optoelectronic neural network architecture for implementing supervised learning algorithms in photorefractive materials. The system is based on spatial multiplexing rather than the more commonly used angular multiplexing of the interconnect gratings. This simple, single-crystal architecture implements a variety of multilayer supervised learning algorithms including me
An F77 package for feed-forward artificial neural network data processing, JETNET 3.0, is presented. It represents a substantial extension and generalization of an earlier release, JETNET 2.0. The package, which consists of a set of subroutines, is focused on multilayer perceptron architectures. As compared to earlier versions it contains a variety of minimization options, measures for monitoring
We study a small Anderson-impurity cluster using lattice density functional methods, and try todetermine the exact exchange-correlation (XC) potential via reverse engineering. In doing so we nd singlet{triplet degenerate interacting ground states which cannot be v0-represented in an ensemble-DFT sense. Wealso nd that it is possible to represent a triplet ground state as a pure state, but not the s
We discuss some aspects of the current status of event generators for small-x DIS. In particular we report on recent results using the CCFM evolution implemented in the SMALLX and CASCADE program concerning the importance of the so-called consistency constraint, and compare with the linked dipole chain model implemented in the LDC program. We point out some potential problems with the resolved vir
We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator developme
