Directional cell growth requires that cells read and interpret shallow chemical gradients, but how the gradient directional information is identified remains elusive. We use single-cell analysis and mathematical modeling to define the cellular gradient decoding network in yeast. Our results demonstrate that the spatial information of the gradient signal is read locally within the polarity site ...

We derive spectral line shapes of the expected signal for a haloscope experiment searching axionlike dark matter. The knowledge these is needed to optimize an experimental design and data analysis procedure. extend previously known results axion-photon axion-gluon couplings case gradient (axion-fermion) coupling. A unique feature interaction its dependence not only on magnitudes but also direct...

One of the related problems of OCR systems is discrimination of fonts in machine printed document images. This task improves performance of general OCR systems. Proposed methods in this paper are based on various fractal dimensions for font discrimination. First, some predefined fractal dimensions were combined with directional methods to enhance font differentiation. Then, a novel fractal dime...

Conventional features are robust for recognizing either deformed or degraded characters. This paper proposes a feature extraction method that is robust for both of them. Run-length compensation is introduced for extracting approximate directional run-lengths of strokes from degraded handwritten characters. This technique is applied to the conventional feature vector based on directional runleng...

While genetically inspired approaches to multi-objective optimization have many advantages over conventional approaches, they do not explicitly exploit directional/gradient information. This paper describes how steepestdescent, multi-objective optimization theory can be combined with EC concepts to produce improved algorithms. It shows how approximate directional information can be efficiently ...

This work is intended to provide some ideas on the use of a Gaussian-derivative model for visual perception, called the Hermite transform, to extract motion information from an image sequence. Gaussian-derivative operators have long been used in computer vision for feature extraction and are relevant in visual system modeling. A directional energy is defined in terms of the 1-D Hermite transfor...

In this paper, we present a novel image interpolation method based on variational models with both smoothing and orientation constraints. By introducing the orientation constraint, we simplify the nonlinear PDE problem into a series of problems with explicit solutions. In our model, the gradient directions for the interpolated pixels are first estimated using a modified orientation diffusion me...

The selection gradient is of central importance in evolutionary biology because it quantifies the forces of directional selection acting on a trait. Lande has shown that the selection gradient can be computed as the vector gradient of the log mean fitness when the trait is normally distributed. Using the framework of Gaussian processes and reproducing kernel Hilbert spaces, a rigorous definitio...

Iris recognition a new biometric technology has great advantages such as variability, stability and security. In this paper we propose a new feature extraction method for iris recognition based on contourlet transform. Contourlet transform captures the intrinsic geometrical structures of iris image. It decomposes the iris image into a set of directional subbands with texture details captured in...

Iris recognition a new biometric technology has great advantages such as variability, stability and security. In this paper we propose a feature extraction method for iris recognition based on contourlet transform. Contourlet transform captures the intrinsic geometrical structures of iris image. It decomposes the iris image into a set of directional subbands with texture details captured in dif...