2,053 research outputs found
Development of interspecific hybrids between three American yam bean species (Pachyrhizus spp.).
American yam bean (Pachyrhizus Richard ex DC.), a neotropical legume, is cultivated in Latin America and Asia for its edible and crunchy storage roots. Because of their low dry matter content and 'fruity' nature, roots are usually consumed raw. In order to increase root dry matter content and promote a wider use of American yam beans for food and starch processing interspecific crosses were made between P. tuberosus (Chuin) germplasm originating from the Peruvian Amazon and two other domesticated yam bean species: P. ahipa native to the Andean highlands and P. erosus originating from Central America. While the 'Chuin' type is characterized by high storage root dry matter content, P. erosus is high yielding and drought tolerant and P. ahipa performs well in high altitudes. The breeding experiment was designed as a completely diallelic cross between three P.ahipa and three P. tuberosus accessions and between three P. erosus und three P. tuberosus accessions. Nine P. ahipa x P. tuberosus (Chuin) F1 cross populations as well as 9 P. erosus x P. tuberosus (Chuin) F1 cross populations were developed. Hybridity of interspecific progenies was confirmed by morphological and agronomical evaluation and multivariate statistical analysis. Hybrid plants were generally fertile and vigorous. The resulting 18 F1 interspecific and 12 F1 intraspecific cross populations are used to generate a large number of F2 lines that serve to select genotypes with high dry matter and high starch content as well as good adaptation to a broad range of environmental conditions
Field screening of variation for heat tolerance in a large set of sweetpotato germplasm accessions.
Structure of the membrane-bound formate hydrogenlyase complex from Escherichia coli
The prototypical hydrogen-producing enzyme, the membrane-bound formate hydrogenlyase (FHL) complex from Escherichia coli, links formate oxidation at a molybdopterin-containing formate dehydrogenase to proton reduction at a [NiFe] hydrogenase. It is of intense interest due to its ability to efficiently produce H2 during fermentation, its reversibility, allowing H2-dependent CO2 reduction, and its evolutionary link to respiratory complex I. FHL has been studied for over a century, but its atomic structure remains unknown. Here we report cryo-EM structures of FHL in its aerobically and anaerobically isolated forms at resolutions reaching 2.6âĂ
. This includes well-resolved density for conserved loops linking the soluble and membrane arms believed to be essential in coupling enzymatic turnover to ion translocation across the membrane in the complex I superfamily. We evaluate possible structural determinants of the bias toward hydrogen production over its oxidation and describe an unpredicted metal-binding site near the interface of FdhF and HycF subunits that may play a role in redox-dependent regulation of FdhF interaction with the complex
Interpol: An R package for preprocessing of protein sequences
<p>Abstract</p> <p>Background</p> <p>Most machine learning techniques currently applied in the literature need a fixed dimensionality of input data. However, this requirement is frequently violated by real input data, such as DNA and protein sequences, that often differ in length due to insertions and deletions. It is also notable that performance in classification and regression is often improved by numerical encoding of amino acids, compared to the commonly used sparse encoding.</p> <p>Results</p> <p>The software "Interpol" encodes amino acid sequences as numerical descriptor vectors using a database of currently 532 descriptors (mainly from AAindex), and normalizes sequences to uniform length with one of five linear or non-linear interpolation algorithms. Interpol is distributed with open source as platform independent R-package. It is typically used for preprocessing of amino acid sequences for classification or regression.</p> <p>Conclusions</p> <p>The functionality of Interpol widens the spectrum of machine learning methods that can be applied to biological sequences, and it will in many cases improve their performance in classification and regression.</p
Dynamics of Social Balance on Networks
We study the evolution of social networks that contain both friendly and
unfriendly pairwise links between individual nodes. The network is endowed with
dynamics in which the sense of a link in an imbalanced triad--a triangular loop
with 1 or 3 unfriendly links--is reversed to make the triad balanced. With this
dynamics, an infinite network undergoes a dynamic phase transition from a
steady state to "paradise"--all links are friendly--as the propensity p for
friendly links in an update event passes through 1/2. A finite network always
falls into a socially-balanced absorbing state where no imbalanced triads
remain. If the additional constraint that the number of imbalanced triads in
the network does not increase in an update is imposed, then the network quickly
reaches a balanced final state.Comment: 10 pages, 7 figures, 2-column revtex4 forma
Heavy Superheated Droplet Detectors as a Probe of Spin-independent WIMP Dark Matter Existence
At present, application of Superheated Droplet Detectors (SDDs) in WIMP dark
matter searches has been limited to the spin-dependent sector, owing to the
general use of fluorinated refrigerants which have high spin sensitivity. Given
their recent demonstration of a significant constraint capability with
relatively small exposures and the relative economy of the technique, we
consider the potential impact of heavy versions of such devices on the
spin-independent sector. Limits obtainable from a -loaded SDD
are estimated on the basis of the radiopurity levels and backgrounds already
achieved by the SIMPLE and PICASSO experiments. With 34 kgd exposure,
equivalent to the current CDMS, such a device may already probe to below
10 pb in the spin-independent cross section.Comment: 9 pages, 4 figures, accepted Phys. Rev.
Statistical relational learning with soft quantifiers
Quantification in statistical relational learning (SRL) is either existential or universal, however humans might be more inclined to express knowledge using soft quantifiers, such as ``most'' and ``a few''. In this paper, we define the syntax and semantics of PSL^Q, a new SRL framework that supports reasoning with soft quantifiers, and present its most probable explanation (MPE) inference algorithm. To the best of our knowledge, PSL^Q is the first SRL framework that combines soft quantifiers with first-order logic rules for modelling uncertain relational data. Our experimental results for link prediction in social trust networks demonstrate that the use of soft quantifiers not only allows for a natural and intuitive formulation of domain knowledge, but also improves the accuracy of inferred results
Influence of heated forming tools on corrosion behavior of high strength aluminum alloys
In this study forming tools temperated at 24 °C and 350 °C were used to systematically investigate the influence of different cooling rates on the mechanical and corrosion properties of a high strength aluminum alloy AA7075 within a novel thermoâmechanical process that combines forming and quenching simultaneously. The samples formed within heated tools reveal higher ductility and lower material strength compared to the parts processed in cold tools. In addition, the corrosion behavior changed between samples formed with 24 °C forming tools and 350 °C forming tools, respectively. Through cyclic polarization in chloride containing aqueous media a change in the hysteresis and shift of open circuit potential was observed. Metallographic investigation revealed that there was also a very different corrosion morphology for the samples formed within the heated tools. No change in average grain size could be detected but changes of the microstructure in subgrain scale that occur during the forming within the heated tools are responsible for this effect. In further research, the effect of various cooling rates on mechanical and corrosion behavior and the microstructure will be investigated by variation of the forming tool temperature
DFT global optimisation of gas-phase and MgO-supported sub-nanometre AuPd clusters
The effect of a MgO support on the structures and energies of AuâPd clusters is calculated at the DFT level.</p
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