A combined statistical model for multiple motifs search

Transcription factor binding sites (TFBS) play key roles in genebior 6.8 wavelet expression and regulation. They are short sequence segments with de¯nite structure and can be recognized by the corresponding transcription factors correctly. From the viewpoint of statistics, the candidates of TFBS should be quite di®erent from the segments that are randomly combined together by nucleotide. This paper proposes a combined statistical model for ¯nding over- represented short sequence segments in di®erent kinds of data set. While the over-represented short sequence segment is described by position weight matrix, the nucleotide distribution at most sites of the segment should be far from the background nucleotide distribution. The central idea of this approach is to search for such kind of signals. This algorithm is tested on 3 data sets, including binding sites data set of cyclic AMP receptor protein in E.coli, PlantProm DB which is a non-redundant collection of proximal promoter sequences from di®erent species, collection of the intergenic sequences of the whole genome of E.Coli. Even though the complexity of these three data sets is quite di®erent, the results show that this model is rather general and sensible.

Derivation of a vector model for a Brushless Doubly-Fed Machine with multiple loops per nest

The paper presents a vector model for a Brushless Doubly-Fed Machine (BDFM). The BDFM has 4 and 8 pole stator windings and a nested-loop rotor cage. The rotor cage has six nests equally spaced around the circumference and each nest comprises three loops. All the rotor loops are short circuited via a common end-ring at one end. The vector model is derived based on the electrical equations of the machine and appropriate vector transformations. In contrast to the stator, there is no three phase circuit in the rotor. Therefore, the vector transformations suitable for three phase circuits can not be utilised for the rotor circuit. A new vector transformation is employed for the rotor circuit quantities. The approach presented in this paper can be extended for a BDFM with any stator poles combination and any number of loops per nest. Simulation results from the model implemented in Simulink are presented. © 2008 IEEE.

A nonlinear model for assessing multiple probabilistic risks: A case study in South five-island of Changdao National Nature Reserve in China

Several methods for estimating the potential impacts caused by multiple probabilistic risks have been suggested. These existing methods mostly rely on the weight sum algorithm to address the need for integrated risk assessment. This paper develops a nonlinear model to perform such an assessment. The joint probability algorithm has been applied to the model development. An application of the developed model in South five-island of Changdao National Nature Reserve, China, combining remote sensing data and a GIS technique, provides a reasonable risk assessment. Based on the case study, we discuss the feasibility of the model. We propose that the model has the potential for use in identifying the regional primary stressor, investigating the most vulnerable habitat, and assessing the integrated impact of multiple stressors. (C) 2006 Elsevier Ltd. All rights reserved.

Generalizing on Multiple Grounds: Performance Learning in Model-Based Technology

This thesis explores ways to augment a model-based diagnostic program with a learning component, so that it speeds up as it solves problems. Several learning components are proposed, each exploiting a different kind of similarity between diagnostic examples. Through analysis and experiments, we explore the effect each learning component has on the performance of a model-based diagnostic program. We also analyze more abstractly the performance effects of Explanation-Based Generalization, a technology that is used in several of the proposed learning components.

A trait specific model of competition in a spatially structured plant community

John Warren and Chris Topping (2004). A trait specific model of competition in a spatially structured plant community. Ecological Modelling, 180 pp.477-485 RAE2008

A Neural Model of 3D Shape-From-Texture: Multiple-Scale Filtering, Boundary Grouping, and Surface Filling-In

A neural model is presented of how cortical areas V1, V2, and V4 interact to convert a textured 2D image into a representation of curved 3D shape. Two basic problems are solved to achieve this: (1) Patterns of spatially discrete 2D texture elements are transformed into a spatially smooth surface representation of 3D shape. (2) Changes in the statistical properties of texture elements across space induce the perceived 3D shape of this surface representation. This is achieved in the model through multiple-scale filtering of a 2D image, followed by a cooperative-competitive grouping network that coherently binds texture elements into boundary webs at the appropriate depths using a scale-to-depth map and a subsequent depth competition stage. These boundary webs then gate filling-in of surface lightness signals in order to form a smooth 3D surface percept. The model quantitatively simulates challenging psychophysical data about perception of prolate ellipsoids (Todd and Akerstrom, 1987, J. Exp. Psych., 13, 242). In particular, the model represents a high degree of 3D curvature for a certain class of images, all of whose texture elements have the same degree of optical compression, in accordance with percepts of human observers. Simulations of 3D percepts of an elliptical cylinder, a slanted plane, and a photo of a golf ball are also presented.

Trait-based representation of diatom functional diversity in a plankton functional type model of the eutrophied southern North Sea

We introduce a trait-based description of diatom functional diversity to an existing plankton functional type (PFT) model, implemented for the eutrophied coastal ecosystem in the Southern Bight of the North Sea. The trait-based description represents a continuum of diatom species, each characterized by a distinct cell volume, and includes size dependence of four diatom traits: the maximum growth rate, the half-saturation constants for nutrient uptake, the photosynthetic efficiency, and the relative affinity of copepods for diatoms. Through competition under seasonally varying forcing, the fitness of each diatom varies throughout time, and the outcome of competition results in a changing community structure. The predicted seasonal change in mean cell volume of the community is supported by field observations: smaller diatoms, which are more competitive in terms of resource acquisition, prevail during the first spring bloom, whereas the summer bloom is dominated by larger species which better resist grazing. The size-based model is used to determine the ecological niche of diatoms in the area and identifies a range of viable sizes that matches observations. The general trade-off between small, competitive diatoms and large, grazing-resistant species is a convenient framework to study patterns in diatom functional diversity. PFT models and trait-based approaches constitute promising complementary tools to study community structure in marine ecosystems.