Number of adaptive steps to a local fitness peak

We consider a population of genotype sequences evolving on a rugged fitness landscape with many local fitness peaks. The population walks uphill until it encounters a local fitness maximum. We find that the statistical properties of the walk length depend on whether the underlying fitness distribution has a finite mean. If the mean is finite, all the walk length cumulants grow with the sequence length but approach a constant otherwise. Experimental implications of our analytical results are also discussed

Evolutionary dynamics on strongly correlated fitness landscapes

We study the evolutionary dynamics of a maladapted population of self-replicating sequences on strongly correlated fitness landscapes. Each sequence is assumed to be composed of blocks of equal length and its fitness is given by a linear combination of four independent block fitnesses. A mutation affects the fitness contribution of a single block leaving the other blocks unchanged and hence inducing correlations between the parent and mutant fitness. On such strongly correlated fitness landscapes, we calculate the dynamical properties like the number of jumps in the most populated sequence and the temporal distribution of the last jump which is shown to exhibit a inverse square dependence as in evolution on uncorrelated fitness landscapes. We also obtain exact results for the distribution of records and extremes for correlated random variables

A probabilistic fusion framework for 3-D reconstruction using heterogeneous sensors

This letter proposes a framework to perform 3-D reconstruction using a heterogeneous sensor network, with potential use in augmented reality, human behavior understanding, smart-room implementations, robotics, and many other applications. We fuse orientation measurements from inertial sensors, images from cameras and depth data from Time of Flight sensors within a probabilistic framework in a synergistic manner to obtain robust reconstructions. A fully probabilistic method is proposed to efficiently fuse the multi-modal data of the system

Marine fisheries of the south-east coast of India during 2008

The south-east coast of India comprising the states of Andhra Pradesh, Tamil Nadu and Pondicherry have a total coastline of 2050 km which is 34% of the total coastline of the country. This region is more diverse with respect to the number of species that are landed. In 2007, it was observed that 499 species were landed in Tamil Nadu, 294 in Andhra Pradesh and 115 in Pondicherry

Thermal and structural properties of unusual starches from developmental corn lines

Starches from exotic corn lines were screened by using differential scanning calorimetry (DSC) to find thermal properties that were significantly different from those exhibited by starches from normal Corn Belt lines. Two independent gelatinization transitions, one corresponding to the melting of a peak at ∼66 °C and the other to a peak melting at ∼69 °C, were found in some starches. The melting characteristics were traced to two separate types of granules within the endosperm. Strong correlations were found between DSC properties and proportion of large granules with equivalent diameter ≥17 μm. Starches with a lower peak onset gelatinization temperature (ToG), had a lower normalized concentration of chains with a degree of polymerization (dp) of 15–24 and/or a greater normalized concentration of chains with a dp of 6–12. These studies will aid in understanding structure–thermal property relationships of starches, and in identifying corn lines of interest for commercial breeding

The Roles of Transmembrane Domain Helix-III during Rhodopsin Photoactivation

Background: Rhodopsin, the prototypic member of G protein-coupled receptors (GPCRs), undergoes isomerization of 11- cis-retinal to all-trans-retinal upon photoactivation. Although the basic mechanism by which rhodopsin is activated is well understood, the roles of whole transmembrane (TM) helix-III during rhodopsin photoactivation in detail are not completely clear. Principal Findings: We herein use single-cysteine mutagenesis technique to investigate conformational changes in TM helices of rhodopsin upon photoactivation. Specifically, we study changes in accessibility and reactivity of cysteine residues introduced into the TM helix-III of rhodopsin. Twenty-eight single-cysteine mutants of rhodopsin (P107C-R135C) were prepared after substitution of all natural cysteine residues (C140/C167/C185/C222/C264/C316) by alanine. The cysteine mutants were expressed in COS-1 cells and rhodopsin was purified after regeneration with 11-cis-retinal. Cysteine accessibility in these mutants was monitored by reaction with 4, 49-dithiodipyridine (4-PDS) in the dark and after illumination. Most of the mutants except for T108C, G109C, E113C, I133C, and R135C showed no reaction in the dark. Wide variation in reactivity was observed among cysteines at different positions in the sequence 108–135 after photoactivation. In particular, cysteines at position 115, 119, 121, 129, 131, 132, and 135, facing 11-cis-retinal, reacted with 4-PDS faster than neighboring amino acids. The different reaction rates of mutants with 4-PDS after photoactivation suggest that the amino acids in different positions in helix-III are exposed to aqueous environment to varying degrees. Significance: Accessibility data indicate that an aqueous/hydrophobic boundary in helix-III is near G109 and I133. The lack of reactivity in the dark and the accessibility of cysteine after photoactivation indicate an increase of water/4-PDS accessibility for certain cysteine-mutants at Helix-III during formation of Meta II. We conclude that photoactivation resulted in water-accessible at the chromophore-facing residues of Helix-III.National Institutes of Health (U.S.) (grant GM28289)National Eye Institute (Grant Grant EY11716)National Science Foundation (U.S.) (grant EIA-0225609

Object Classification Techniques using Tree Based Classifiers

Object recognition is presently one of the most active research areas in computer vision, pattern recognition, artificial intelligence and human activity analysis. The area of object detection and classification, attention habitually focuses on changes in the location of anobject with respect to time, since appearance information can sensibly describe the object category. In this paper, feature set obtained from the Gray Level Co-Occurrence Matrices (GLCM), representing a different stage of statistical variations of object category. The experiments are carried out using Caltech 101 dataset, considering sevenobjects viz (airplanes, camera, chair, elephant, laptop, motorbike and bonsai tree) and the extracted GLCM feature set are modeled by tree based classifier like Naive Bayes Tree and Random Forest. In the experimental results, Random Forest classifier exhibits the accuracy and effectiveness of the proposed method with an overall accuracy rate of 89.62%, which outperforms the Naive Bayes classifier

Thermodynamic stability of metallurgical coke relative to graphite

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