Refined genome-wide comparative map of the domestic horse, donkey and human based on cross-species chromosome painting: insight into the occasional fertility of mules

We have made a complete set of painting probes for the domestic horse by degenerate oligonucleotide-primed PCR amplification of flow-sorted horse chromosomes. The horse probes, together with a full set of those available for human, were hybridized onto metaphase chromosomes of human, horse and mule. Based on the hybridization results, we have generated genome-wide comparative chromosome maps involving the domestic horse, donkey and human. These maps define the overall distribution and boundaries of evolutionarily conserved chromosomal segments in the three genomes. Our results shed further light on the karyotypic relationships among these species and, in particular, the chromosomal rearrangements that underlie hybrid sterility and the occasional fertility of mules.

Multiscale object features from clustered complex wavelet coefficients

This paper introduces a method by which intuitive feature entities can be created from ILP (InterLevel Product) coefficients. The ILP transform is a pyramid of decimated complex-valued coefficients at multiple scales, derived from dual-tree complex wavelets, whose phases indicate the presence of different feature types (edges and ridges). We use an Expectation-Maximization algorithm to cluster large ILP coefficients that are spatially adjacent and similar in phase. We then demonstrate the relationship that these clusters possess with respect to observable image content, and conclude with a look at potential applications of these clusters, such as rotation- and scale-invariant object recognition. © 2005 IEEE.

Cardioviral RNA structure logo analysis: entropy, correlations, and prediction

In recent years, there has been an increased number of sequenced RNAs leading to the development of new RNA databases. Thus, predicting RNA structure from multiple alignments is an important issue to understand its function. Since RNA secondary structures are often conserved in evolution, developing methods to identify covariate sites in an alignment can be essential for discovering structural elements. Structure Logo is a technique established on the basis of entropy and mutual information measured to analyze RNA sequences from an alignment. We proposed an efficient Structure Logo approach to analyze conservations and correlations in a set of Cardioviral RNA sequences. The entropy and mutual information content were measured to examine the conservations and correlations, respectively. The conserved secondary structure motifs were predicted on the basis of the conservation and correlation analyses. Our predictive motifs were similar to the ones observed in the viral RNA structure database, and the correlations between bases also corresponded to the secondary structure in the database.

Rapid entropy-based detection and properties measurement of concrete spalling with machine vision for post-earthquake safety assessments

The current procedures in post-earthquake safety and structural assessment are performed manually by a skilled triage team of structural engineers/certified inspectors. These procedures, and particularly the physical measurement of the damage properties, are time-consuming and qualitative in nature. This paper proposes a novel method that automatically detects spalled regions on the surface of reinforced concrete columns and measures their properties in image data. Spalling has been accepted as an important indicator of significant damage to structural elements during an earthquake. According to this method, the region of spalling is first isolated by way of a local entropy-based thresholding algorithm. Following this, the exposure of longitudinal reinforcement (depth of spalling into the column) and length of spalling along the column are measured using a novel global adaptive thresholding algorithm in conjunction with image processing methods in template matching and morphological operations. The method was tested on a database of damaged RC column images collected after the 2010 Haiti earthquake, and comparison of the results with manual measurements indicate the validity of the method.

Linear multiscale analysis and finite element validation of stretching and bending dominated lattice materials

The paper presents a multiscale procedure for the linear analysis of components made of lattice materials. The method allows the analysis of both pin-jointed and rigid-jointed microtruss materials with arbitrary topology of the unit cell. At the macroscopic level, the procedure enables to determine the lattice stiffness, while at the microscopic level the internal forces in the lattice elements are expressed in terms of the macroscopic strain applied to the lattice component. A numeric validation of the method is described. The procedure is completely automated and can be easily used within an optimization framework to find the optimal geometric parameters of a given lattice material. © 2011 Elsevier Ltd. All rights reserved.

Predictive entropy search for efficient global optimization of black-box functions

We propose a novel information-theoretic approach for Bayesian optimization called Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that maximizes the expected information gained with respect to the global maximum. PES codifies this intractable acquisition function in terms of the expected reduction in the differential entropy of the predictive distribution. This reformulation allows PES to obtain approximations that are both more accurate and efficient than other alternatives such as Entropy Search (ES). Furthermore, PES can easily perform a fully Bayesian treatment of the model hyperparameters while ES cannot. We evaluate PES in both synthetic and real-world applications, including optimization problems in machine learning, finance, biotechnology, and robotics. We show that the increased accuracy of PES leads to significant gains in optimization performance.

Boundary conditions at the solid-liquid surface over the multiscale channel size from nanometer to micron

The boundary condition at the solid surface is one of the important problems for the microfluidics. In this paper we study the effects of the channel sizes on the boundary conditions (BC), using the hybrid computation scheme adjoining the molecular dynamics (MD) simulations and the continuum fluid mechanics. We could reproduce the three types of boundary conditions (slip, no-slip and locking) over the multiscale channel sizes. The slip lengths are found to be mainly dependent on the interfacial parameters with the fixed apparent shear rate. The channel size has little effects on the slip lengths if the size is above a critical value within a couple of tens of molecular diameters. We explore the liquid particle distributions nearest the solid walls and found that the slip boundary condition always corresponds to the uniform liquid particle distributions parallel to the solid walls, while the no-slip or locking boundary conditions correspond to the ordered liquid structures close to the solid walls. The slip, no-slip and locking interfacial parameters yield the positive, zero and negative slip lengths respectively. The three types of boundary conditions existing in "microscale" still occur in "macroscale". However, the slip lengths weakly dependent on the channel sizes yield the real shear rates and the slip velocity relative to the solid wall traveling speed approaching those with the no-slip boundary condition when the channel size is larger than thousands of liquid molecular diameters for all of the three types of interfacial parameters, leading to the quasi-no-slip boundary conditions.