arXiv subjects

Andreas Wagner

Publications and source records attributed to Andreas Wagner.

62 records · Page 4Linked to original sources

arXiv2010

Resonance strengths in the 14N(p, γ)15O and 15N(p, αγ)12C reactions

The 14N(p, γ)15O reaction is the slowest reaction of the carbon-nitrogen-oxygen cycle of hydrogen burning in stars. As a consequence, it determines the rate of the cycle. The 15N(p, αγ)12C reaction is frequently used in inverse kinematics for hydrogen depth profiling in materials. The 14N(p, γ)15O and 15N(p, αγ)12C reactions have been studied simultaneously, using titanium nitride targets of natural isotopic composition and a proton beam. The strengths of the resonances at Ep = 1058 keV in 14N(p, γ)15O and at Ep = 897 and 430 keV in 15N(p, αγ)12C have been determined with improved precision, relative to the well-known resonance at Ep = 278 keV in 14N(p, γ)15O. The new recommended values are ωγ= 0.353$\pm$0.018, 362$\pm$20, and 21.9$\pm$1.0 eV for their respective strengths. In addition, the branching ratios for the decay of the Ep = 1058 keV resonance in 14N(p, γ)15O have been redetermined. The data reported here should facilitate future studies of off-resonant capture in the 14N(p, γ)15O reaction that are needed for an improved R-matrix extrapolation of the cross section. In addition, the data on the 430 keV resonance in 15N(p, αγ)12C may be useful for hydrogen depth profiling.

nucl-ex↗

arXiv2010

Dipole strength in 144Sm studied via (gamma,n), (gamma,p) and (gamma,alpha) reactions

Photoactivation measurements on 144Sm have been performed with bremsstrahlung endpoint energies from 10.0 to 15.5 MeV at the bremsstrahlung facility of the superconducting electron accelerator ELBE of Forschungszentrum Dresden-Rossendorf. The measured activation yield for the 144Sm(gamma,n) reaction is compared with the calculated yield using cross sections from previous photoneutron experiments. The activation yields measured for all disintegration channels 144Sm(gamma,n), (gamma,p) and (gamma,alpha) are compared to the yield calculated by using Hauser-Feshbach statistical models. A new parametrization of the photon strength function is presented and the yield simulated by using the modified photon strength parameters are compared to the experimental data.

nucl-ex↗

arXiv2010

Genotype networks in metabolic reaction spaces

Background: A metabolic genotype comprises all chemical reactions an organism can catalyze via enzymes encoded in its genome. A genotype is viable in a given environment if it is capable of producing all biomass components the organism needs to survive and reproduce. Previous work has focused on the properties of individual genotypes while little is known about how genome-scale metabolic networks with a given function can vary in their reaction content. Results: We here characterize spaces of such genotypes. Specifically, we study metabolic genotypes whose phenotype is viability in minimal chemical environments that differ in their sole carbon sources. We show that regardless of the number of reactions in a metabolic genotype, the genotypes of a given phenotype typically form vast, connected, and unstructured sets -- genotype networks -- that nearly span the whole of genotype space. The robustness of metabolic phenotypes to random reaction removal in such spaces has a narrow distribution with a high mean. Different carbon sources differ in the number of metabolic genotypes in their genotype network; this number decreases as a genotype is required to be viable on increasing numbers of carbon sources, but much less than if metabolic reactions were used independently across different chemical environments. Conclusions: Our work shows that phenotype-preserving genotype networks have generic organizational properties and that these properties are insensitive to the number of reactions in metabolic genotypes.

q-bio.MN↗

arXiv2008

The energy dependence of the electric dipole strength in heavy nuclei

On the basis of new photon scattering measurements and a reevaluation of average neutron resonance capture data we investigate how well Lorentzians adjusted to photo-neutron data in the giant dipole resonances give a good description of the photon strength also below the neutron threshold. If deformation effects are properly taken into account this is verified down to about 5 MeV for various nuclei with A>80 such that the previously employed differentiation between deformed and non-deformed nuclei is no longer necessary.

nucl-ex↗

arXiv2006

New structural variation in evolutionary searches of RNA neutral networks

RNA secondary structure is an important computational model to understand how genetic variation maps into phenotypic (structural) variation. Evolutionary innovation in RNA structures is facilitated by neutral networks, large connected sets of RNA sequences that fold into the same structure. Our work extends and deepens previous studies on neutral networks. First, we show that even the 1-mutant neighborhood of a given sequence (genotype) G0 with structure (phenotype) P contains many structural variants that are not close to P. This holds for biological and generic RNA sequences alike. Second, we analyze the relation between new structures in the 1-neighborhoods of genotypes Gk that are only a moderate Hamming distance k away from G0, and the structure of G0 itself, both for biological and for generic RNA structures. Third, we analyze the relation between mutational robustness of a sequence and the distances of structural variants near this sequence. Our findings underscore the role of neutral networks in evolutionary innovation, and the role that high robustness can play in diminishing the potential for such innovation.

q-bio.PE↗

arXiv2005

Pygmy dipole strength close to particle-separation energies - the case of the Mo isotopes

The distribution of electromagnetic dipole strength in 92, 98, 100 Mo has been investigated by photon scattering using bremsstrahlung from the new ELBE facility. The experimental data for well separated nuclear resonances indicate a transition from a regular to a chaotic behaviour above 4 MeV of excitation energy. As the strength distributions follow a Porter-Thomas distribution much of the dipole strength is found in weak and in unresolved resonances appearing as fluctuating cross section. An analysis of this quasi-continuum - here applied to nuclear resonance fluorescence in a novel way - delivers dipole strength functions, which are combining smoothly to those obtained from (g,n)-data. Enhancements at 6.5 MeV and at ~9 MeV are linked to the pygmy dipole resonances postulated to occur in heavy nuclei.

nucl-ex↗

arXiv2004

Structure and evolution of protein interaction networks: A statistical model for link dynamics and gene duplications

The structure of molecular networks derives from dynamical processes on evolutionary time scales. For protein interaction networks, global statistical features of their structure can now be inferred consistently from several large-throughput datasets. Understanding the underlying evolutionary dynamics is crucial for discerning random parts of the network from biologically important properties shaped by natural selection. We present a detailed statistical analysis of the protein interactions in Saccharomyces cerevisiae based on several large-throughput datasets. Protein pairs resulting from gene duplications are used as tracers into the evolutionary past of the network. From this analysis, we infer rate estimates for two key evolutionary processes shaping the network: (i) gene duplications and (ii) gain and loss of interactions through mutations in existing proteins, which are referred to as link dynamics. Importantly, the link dynamics is asymmetric, i.e., the evolutionary steps are mutations in just one of the binding parters. The link turnover is shown to be much faster than gene duplications. According to this model, the link dynamics is the dominant evolutionary force shaping the statistical structure of the network, while the slower gene duplication dynamics mainly affects its size. Specifically, the model predicts (i) a broad distribution of the connectivities (i.e., the number of binding partners of a protein) and (ii) correlations between the connectivities of interacting proteins.

cond-mat.stat-mech↗

arXiv2000

Small Cycles in Small Worlds

We characterize the distributions of short cycles in a large metabolic network previously shown to have small world characteristics and a power law degree distribution. Compared with three classes of random networks, including Erdoes-Renyi random graphs and synthetic small world networks of the same connectivity, the metabolic network has a particularly large number of triangles and a deficit in large cycles. Short cycles reduce the length of detours when a connection is clipped, so we propose that long cycles in metabolism may have been selected against in order to shorten transition times and reduce the likelihood of oscillations in response to external perturbations.

cond-mat↗