Thermoelectric power in one-dimensional Hubbard model

The thermoelectric power S is studied within the one-dimensional Hubbard model using the linear response theory and the numerical exact-diagonalization method for small systems. While both the diagonal and off-diagonal dynamical correlation functions of particle and energy current are singular within the model even at temperature T>0, S behaves regularly as a function of frequency $\omega$ and T. Dependence on the electron density n below the half-filling reveals a change of sign of S at n_0=0.73+/-0.07 due to strong correlations, in the whole T range considered. Approaching half-filling S is hole-like and can become large for U>>t although decreasing with T.Comment: 6 pages, 4 figure

Flux networks in metabolic graphs

A metabolic model can be represented as bipartite graph comprising linked reaction and metabolite nodes. Here it is shown how a network of conserved fluxes can be assigned to the edges of such a graph by combining the reaction fluxes with a conserved metabolite property such as molecular weight. A similar flux network can be constructed by combining the primal and dual solutions to the linear programming problem that typically arises in constraint-based modelling. Such constructions may help with the visualisation of flux distributions in complex metabolic networks. The analysis also explains the strong correlation observed between metabolite shadow prices (the dual linear programming variables) and conserved metabolite properties. The methods were applied to recent metabolic models for Escherichia coli, Saccharomyces cerevisiae, and Methanosarcina barkeri. Detailed results are reported for E. coli; similar results were found for the other organisms.Comment: 9 pages, 4 figures, RevTeX 4.0, supplementary data available (excel

Iron status in 6-y-old children: associations with growth and earlier iron status

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldOBJECTIVE: To investigate the iron status of 6-y-old children and its association with growth and earlier iron status. DESIGN: In a cross-sectional study, children's body size measurements were recorded and blood samples taken near their sixth birthday. SUBJECTS: A sample of 188 children, randomly selected in two previous studies, was contacted, and 139(74%) agreed to participate. RESULTS: No children had iron deficiency anaemia, one was iron-deficient (serum ferritin (SF) or =15 microg/l (258+/-31%; n=49) (P=0.001). MCV at 2 y predicted weight gain from 2 to 6 y (B+/-s.e.=1.721+/-0.581; P=0.005; adj. R2=0.153) (n=44); also, children with SF or =15 microg/l (n=35) gained 9.6+/-2.8 kg (P=0.007), furthermore a difference was seen in proportional weight gain from 2 to 6 y between children with depleted iron stores at 2 y and not, or 156+/-13 vs 169+/-18% (P=0.038). CONCLUSION: The results suggest that low iron status at 1 and 2 y might lead to slower growth up to 6 y of age. Low iron status at 1 and 2 y and/or slower growth from 1 and 2 y up to 6 y might contribute to worse iron status at 6 y, while faster growth in early childhood is related to lower iron status

Complete trails of co-authorship network evolution

The rise and fall of a research field is the cumulative outcome of its intrinsic scientific value and social coordination among scientists. The structure of the social component is quantifiable by the social network of researchers linked via co-authorship relations, which can be tracked through digital records. Here, we use such co-authorship data in theoretical physics and study their complete evolutionary trail since inception, with a particular emphasis on the early transient stages. We find that the co-authorship networks evolve through three common major processes in time: the nucleation of small isolated components, the formation of a tree-like giant component through cluster aggregation, and the entanglement of the network by large-scale loops. The giant component is constantly changing yet robust upon link degradations, forming the network's dynamic core. The observed patterns are successfully reproducible through a new network model

The Regularizing Capacity of Metabolic Networks

Despite their topological complexity almost all functional properties of metabolic networks can be derived from steady-state dynamics. Indeed, many theoretical investigations (like flux-balance analysis) rely on extracting function from steady states. This leads to the interesting question, how metabolic networks avoid complex dynamics and maintain a steady-state behavior. Here, we expose metabolic network topologies to binary dynamics generated by simple local rules. We find that the networks' response is highly specific: Complex dynamics are systematically reduced on metabolic networks compared to randomized networks with identical degree sequences. Already small topological modifications substantially enhance the capacity of a network to host complex dynamic behavior and thus reduce its regularizing potential. This exceptionally pronounced regularization of dynamics encoded in the topology may explain, why steady-state behavior is ubiquitous in metabolism.Comment: 6 pages, 4 figure

Associations of iron status with dietary and other factors in 6-year-old children

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldOBJECTIVE: To investigate the associations of iron status at 6 years of age with dietary and other factors. DESIGN: In a cross-sectional study, children's dietary intakes (3-day weighed food record) were recorded, body size was measured and blood samples were taken near their sixth birthday. SUBJECTS: A sample of 188 children, from two previous studies (cohorts 1 and 2), was contacted, and 139 (74%) agreed to participate. RESULTS: Multiple regression analyses with dietary and other factors showed that meat and fish consumption, multivitamin/mineral supplement intake (both positively) and cow's milk product consumption (negatively) were associated with log serum ferritin (SF) (adjusted R (2)=0.125; P=0.028; n=129), and juices and residence (rural>urban) with haemoglobin (Hb) (adjusted R (2)=0.085; P=0.034; n=127). Of 21 multivitamin/mineral consumers, none had depleted iron stores compared to 21 iron-depleted of 108 non-consumers (P=0.024). Children living in rural areas (10,000 inhabitants) (82.1+/-3.2 fl; n=103) (P=0.048). Multiple regression analyses with dietary and other factors and growth showed in cohort 1 that residence (rural>urban), weight gain 0-1years (negatively), and meat and fish intake (positively) were associated with Hb (adjusted R (2)=0.323; P=0.030; n=51), meat and fish (positively) with both log SF (adjusted R (2)=0.069; P=0.035; n=52) and MCV (adjusted R (2)=0.064; P=0.035; n=52), and in cohort 2 cow's milk product consumption (negatively) was associated with log SF (adjusted R (2)=0.119; P=0.017; n=41) and residence (rural>urban) with MCV (adjusted R (2)=0.102; P=0.025; n=41). CONCLUSIONS: Consumption of meat and fish and possibly also juices, as well as multivitamin/mineral intake might affect iron status in 6-year-old children positively, whereas cow's milk product consumption might affect iron status negatively. Slower growth in the first year of life and rural residence are positively related to iron status of 6-year-olds

Structural Kinetic Modeling of Metabolic Networks

To develop and investigate detailed mathematical models of cellular metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, explicit kinetic modeling based on differential equations is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a detailed and quantitative account of the dynamical capabilities of metabolic systems, without requiring any explicit information about the particular functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible, or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a systematic statistical exploration of the comprehensive parameter space. The method is applied to two paradigmatic examples: The glycolytic pathway of yeast and a realistic-scale representation of the photosynthetic Calvin cycle.Comment: 14 pages, 8 figures (color

Using weak values to experimentally determine "negative probabilities" in a two-photon state with Bell correlations

Bipartite quantum entangled systems can exhibit measurement correlations that violate Bell inequalities, revealing the profoundly counter-intuitive nature of the physical universe. These correlations reflect the impossibility of constructing a joint probability distribution for all values of all the different properties observed in Bell inequality tests. Physically, the impossibility of measuring such a distribution experimentally, as a set of relative frequencies, is due to the quantum back-action of projective measurements. Weakly coupling to a quantum probe, however, produces minimal back-action, and so enables a weak measurement of the projector of one observable, followed by a projective measurement of a non-commuting observable. By this technique it is possible to empirically measure weak-valued probabilities for all of the values of the observables relevant to a Bell test. The marginals of this joint distribution, which we experimentally determine, reproduces all of the observable quantum statistics including a violation of the Bell inequality, which we independently measure. This is possible because our distribution, like the weak values for projectors on which it is built, is not constrained to the interval [0, 1]. It was first pointed out by Feynman that, for explaining singlet-state correlations within "a [local] hidden variable view of nature ... everything works fine if we permit negative probabilities". However, there are infinitely many such theories. Our method, involving "weak-valued probabilities", singles out a unique set of probabilities, and moreover does so empirically.Comment: 9 pages, 3 figure

Stochastic Simulations of the Repressilator Circuit

The genetic repressilator circuit consists of three transcription factors, or repressors, which negatively regulate each other in a cyclic manner. This circuit was synthetically constructed on plasmids in {\it Escherichia coli} and was found to exhibit oscillations in the concentrations of the three repressors. Since the repressors and their binding sites often appear in low copy numbers, the oscillations are noisy and irregular. Therefore, the repressilator circuit cannot be fully analyzed using deterministic methods such as rate-equations. Here we perform stochastic analysis of the repressilator circuit using the master equation and Monte Carlo simulations. It is found that fluctuations modify the range of conditions in which oscillations appear as well as their amplitude and period, compared to the deterministic equations. The deterministic and stochastic approaches coincide only in the limit in which all the relevant components, including free proteins, plasmids and bound proteins, appear in high copy numbers. We also find that subtle features such as cooperative binding and bound-repressor degradation strongly affect the existence and properties of the oscillations.Comment: Accepted to PR