Seed conservation in ex situ genebanks - genetic studies on longevity in barley

Recognizing the danger due to a permanent risk of loss of the genetic variability of cultivated plants and their wild relatives in response to changing environmental conditions and cultural practices, plant ex situ genebank collections were created since the beginning of the last century. World-wide more than 6 million accessions have been accumulated of which more than 90% are stored as seeds. Research on seed longevity was performed in barley maintained for up to 34 years in the seed store of the German ex situ genebank of the Leibniz-Institute of Plant Genetics and Crop Plant Research in Gatersleben. A high intraspecific variation was detected in those natural aged accessions. In addition three doubled haploid barley mapping populations being artificial aged were investigated to study the inheritance of seed longevity. Quantitative trait locus (QTL) mapping was based on a transcript map. Major QTLs were identified on chromosomes 2H, 5H (two) and 7H explaining a phenotypic variation of up to 54%. A sequence homology search was performed to derive the putative function of the genes linked to the QTLs

Implementing Zn²⁺ ion and pH-value control into artificial mussel glue proteins by abstracting a His-rich domain from preCollagen

A His-rich domain of preCollagen-D found in byssal threads is derivatized with Cys and Dopa flanks to allow for mussel-inspired polymerization. Artificial mussel glue proteins are accessed that combine cysteinyldopa for adhesion with sequences for pH or Zn2+ induced β-sheet formation. The artificial constructs show strong adsorption to Al2O3, the resulting coatings tolerate hypersaline conditions and cohesion is improved by activating the β-sheet formation, that enhances E-modulus up to 60%

Social inertia in collaboration networks

This work is a study of the properties of collaboration networks employing the formalism of weighted graphs to represent their one-mode projection. The weight of the edges is directly the number of times that a partnership has been repeated. This representation allows us to define the concept of "social inertia" that measures the tendency of authors to keep on collaborating with previous partners. We use a collection of empirical datasets to analyze several aspects of the social inertia: 1) its probability distribution, 2) its correlation with other properties, and 3) the correlations of the inertia between neighbors in the network. We also contrast these empirical results with the predictions of a recently proposed theoretical model for the growth of collaboration networks.Comment: 7 pages, 5 figure

Conformally invariant wave-equations and massless fields in de Sitter spacetime

Conformally invariant wave equations in de Sitter space, for scalar and vector fields, are introduced in the present paper. Solutions of their wave equations and the related two-point functions, in the ambient space notation, have been calculated. The ``Hilbert'' space structure and the field operator, in terms of coordinate independent de Sitter plane waves, have been defined. The construction of the paper is based on the analyticity in the complexified pseudo-Riemanian manifold, presented first by Bros et al.. Minkowskian limits of these functions are analyzed. The relation between the ambient space notation and the intrinsic coordinates is then studied in the final stage.Comment: 21 pages, LaTeX, some details adde

Enhanced retinal image registration accuracy using expectation maximisation and variable bin-sized mutual information

While retinal images (RI) assist in the diagnosis of various eye conditions and diseases such as glaucoma and diabetic retinopathy, their innate features including low contrast homogeneous and nonuniformly illuminated regions, present a particular challenge for retinal image registration (RIR). Recently, the hybrid similarity measure, Expectation Maximization for Principal Component Analysis with Mutual Information (EMPCA-MI) has been proposed for RIR. This paper investigates incorporating various fixed and adaptive bin size selection strategies to estimate the probability distribution in the mutual information (MI) stage of EMPCA-MI, and analyses their corresponding effect upon RIR performance. Experimental results using a clinical mono-modal RI dataset confirms that adaptive bin size selection consistently provides both lower RIR errors and superior robustness compared to the empirically determined fixed bin sizes

Physically interacting humans regulate muscle coactivation to improve visuo-haptic perception.

When moving a piano or dancing tango with a partner, how should I control my arm muscles to sense their movements and follow or guide them smoothly? Here we observe how physically connected pairs tracking a moving target with the arm modify muscle coactivation with their visual acuity and the partner's performance. They coactivate muscles to stiffen the arm when the partner's performance is worse and relax with blurry visual feedback. Computational modeling shows that this adaptive sensing property cannot be explained by the minimization of movement error hypothesis that has previously explained adaptation in dynamic environments. Instead, individuals skillfully control the stiffness to guide the arm toward the planned motion while minimizing effort and extracting useful information from the partner's movement. The central nervous system regulates muscle activation to guide motion with accurate task information from vision and haptics while minimizing the metabolic cost. As a consequence, the partner with the most accurate target information leads the movement.NEW & NOTEWORTHY Our results reveal that interacting humans inconspicuously modulate muscle activation to extract accurate information about the common target while considering their own and the partner's sensorimotor noise. A novel computational model was developed to decipher the underlying mechanism: muscle coactivation is adapted to combine haptic information from the interaction with the partner and own visual information in a stochastically optimal manner. This improves the prediction of the target position with minimal metabolic cost in each partner, resulting in the lead of the partner with the most accurate visual information

Multimodal retinal image registration using a fast principal component analysis hybrid-based similarity measure

Multimodal retinal images (RI) are extensively used for analysing various eye diseases and conditions such as myopia and diabetic retinopathy. The incorporation of either two or more RI modalities provides complementary structure information in the presence of non-uniform illumination and low-contrast homogeneous regions. It also presents significant challenges for retinal image registration (RIR). This paper investigates how the Expectation Maximization for Principal Component Analysis with Mutual Information (EMPCA-MI) algorithm can effectively achieve multimodal RIR. This iterative hybrid-based similarity measure combines spatial features with mutual information to provide enhanced registration without recourse to either segmentation or feature extraction. Experimental results for clinical multimodal RI datasets comprising colour fundus and scanning laser ophthalmoscope images confirm EMPCA-MI is able to consistently afford superior numerical and qualitative registration performance compared with existing RIR techniques, such as the bifurcation structures method

Scattering of Low-Frequency Radiation by a Gyrating Electron

The scattering of electromagnetic radiation by the particle gyrating in an external magnetic field is considered. Particular attention is paid to the low-frequency case, when the frequencies of incident radiation are much less than the electron gyrofrequency. The spectral and polarization features of the scattering cross-section are analyzed in detail. It is found that the scattering transfers the low-frequency photons to high harmonics of the gyrofrequency, into the range of the synchrotron emission of the electron. The total scattering cross-section appears much larger than that for the particle at rest. The problem studied is directly applicable to the radio wave scattering in the magnetosphere of a pulsar. The particles acquire relativistic rotational energies as a result of resonant absorption of the high-frequency radio waves and concurrently scatter the low-frequency radio waves, which are still below the resonance. It is shown that the scattering can affect the radio intensity and polarization at the lowest frequencies and can compete with the resonant absorption in contributing to the low-frequency turnover in the pulsar spectrum. Moreover, the scattering can be an efficient mechanism of the pulsar high-energy emission, in addition to the synchrotron re-emission of the particles. Other astrophysical applications of the scattering by gyrating particles are pointed out as well.Comment: 13 pages, no figures. Accepted for publication in MNRA

Why finance professors should be teaching Nietzsche

<p><strong>Abstract:</strong> Retinal images (RI) are widely used to diagnose a variety of eye conditions and diseases such as myopia and diabetic retinopathy. They are inherently characterised by having nonuniform illumination and low-contrast homogeneous regions which represent a unique set of challenges for retinal image registration (RIR). This paper investigates using the expectation maximization for principal component analysis based mutual information (EMPCA-MI) algorithm in RIR. It combines spatial features with mutual information to efficiently achieve improved registration performance. Experimental results for mono-modal RI datasets verify that EMPCA-MI<br>together with Powell-Brent optimization affords superior robustness in comparison with existing RIR methods, including the geometrical features method.</p> <p><br><strong>Index Terms</strong>— Image registration, principal component analysis, mutual information, expectation-maximization algorithms, retinopathy.</p> <p> </p> <p><strong>Poster presented at</strong>: 38th International Conference on Acoustics, Speech, and Signal Processing<br>(ICASSP), 26th to 31st May 2013, Vancouver, Canada.<br>doi: 10.1109/ICASSP.2013.6637824</p