Summer snow extent heralding of the winter North Atlantic Oscillation

[1] Winter climate over the North Atlantic and European sector is modulated by the North Atlantic Oscillation (NAO). We find that the summer extent of snow cover over northern North America and northern Eurasia is linked significantly (p < 0.01) to the upcoming winter NAO state. Summers with high/low snow extent precede winters of low/high NAO index phase. We suggest the linkage arises from the summer snow-associated formation of anomalous longitudinal differences in surface air temperature with the subpolar North Atlantic. Our findings indicate the seasonal predictability of North Atlantic winter climate may be higher and extend to longer leads than thought previously

solveME: fast and reliable solution of nonlinear ME models.

BackgroundGenome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (&gt;30 times) larger than corresponding metabolic reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints.ResultsHere, we address these computational challenges. We develop a fast and numerically reliable solution method for growth maximization in ME models using a quad-precision NLP solver (Quad MINOS). Our method was up to 45 % faster than binary search for six significant digits in growth rate. We also develop a fast, quad-precision flux variability analysis that is accelerated (up to 60× speedup) via solver warm-starts. Finally, we employ the tools developed to investigate growth-coupled succinate overproduction, accounting for proteome constraints.ConclusionsJust as genome-scale metabolic reconstructions have become an invaluable tool for computational and systems biologists, we anticipate that these fast and numerically reliable ME solution methods will accelerate the wide-spread adoption of ME models for researchers in these fields

Infant cortex responds to other humans from shortly after birth

A significant feature of the adult human brain is its ability to selectively process information about conspecifics. Much debate has centred on whether this specialization is primarily a result of phylogenetic adaptation, or whether the brain acquires expertise in processing social stimuli as a result of its being born into an intensely social environment. Here we study the haemodynamic response in cortical areas of newborns (1–5 days old) while they passively viewed dynamic human or mechanical action videos. We observed activation selective to a dynamic face stimulus over bilateral posterior temporal cortex, but no activation in response to a moving human arm. This selective activation to the social stimulus correlated with age in hours over the first few days post partum. Thus, even very limited experience of face-to-face interaction with other humans may be sufficient to elicit social stimulus activation of relevant cortical regions

Small-scale CMB Temperature and Polarization Anisotropies due to Patchy Reionization

We study contributions from inhomogeneous (patchy) reionization to arcminute scale ($1000 < \ell < 10,000$) cosmic microwave background (CMB) anisotropies. We show that inhomogeneities in the ionization fraction, rather than in the mean density, dominate both the temperature and the polarization power spectra. Depending on the ionization history and the clustering bias of the ionizing sources, we find that rms temperature fluctuations range from 2 $\mu$K to 8 $\mu$K and the corresponding values for polarization are over two orders of magnitude smaller. Reionization can significantly bias cosmological parameter estimates and degrade gravitational lensing potential reconstruction from temperature maps but not from polarization maps. We demonstrate that a simple modeling of the reionization temperature power spectrum may be sufficient to remove the parameter bias. The high-$\ell$ temperature power spectrum will contain some limited information about the sources of reionization.Comment: 11 pages, 8 figures. Minor changes to match version accepted by Ap

The foundations of statistical mechanics from entanglement: Individual states vs. averages

We consider an alternative approach to the foundations of statistical mechanics, in which subjective randomness, ensemble-averaging or time-averaging are not required. Instead, the universe (i.e. the system together with a sufficiently large environment) is in a quantum pure state subject to a global constraint, and thermalisation results from entanglement between system and environment. We formulate and prove a "General Canonical Principle", which states that the system will be thermalised for almost all pure states of the universe, and provide rigorous quantitative bounds using Levy's Lemma.Comment: 12 pages, v3 title changed, v2 minor change

Distance, Growth Factor, and Dark Energy Constraints from Photometric Baryon Acoustic Oscillation and Weak Lensing Measurements

Baryon acoustic oscillations (BAOs) and weak lensing (WL) are complementary probes of cosmology. We explore the distance and growth factor measurements from photometric BAO and WL techniques and investigate the roles of the distance and growth factor in constraining dark energy. We find for WL that the growth factor has a great impact on dark energy constraints but is much less powerful than the distance. Dark energy constraints from WL are concentrated in considerably fewer distance eigenmodes than those from BAO, with the largest contributions from modes that are sensitive to the absolute distance. Both techniques have some well determined distance eigenmodes that are not very sensitive to the dark energy equation of state parameters w_0 and w_a, suggesting that they can accommodate additional parameters for dark energy and for the control of systematic uncertainties. A joint analysis of BAO and WL is far more powerful than either technique alone, and the resulting constraints on the distance and growth factor will be useful for distinguishing dark energy and modified gravity models. The Large Synoptic Survey Telescope (LSST) will yield both WL and angular BAO over a sample of several billion galaxies. Joint LSST BAO and WL can yield 0.5% level precision on ten comoving distances evenly spaced in log(1+z) between redshift 0.3 and 3 with cosmic microwave background priors from Planck. In addition, since the angular diameter distance, which directly affects the observables, is linked to the comoving distance solely by the curvature radius in the Friedmann-Robertson-Walker metric solution, LSST can achieve a pure metric constraint of 0.017 on the mean curvature parameter Omega_k of the universe simultaneously with the constraints on the comoving distances.Comment: 15 pages, 9 figures, details and references added, ApJ accepte

Characterizing and Propagating Modeling Uncertainties in Photometrically-Derived Redshift Distributions

The uncertainty in the redshift distributions of galaxies has a significant potential impact on the cosmological parameter values inferred from multi-band imaging surveys. The accuracy of the photometric redshifts measured in these surveys depends not only on the quality of the flux data, but also on a number of modeling assumptions that enter into both the training set and SED fitting methods of photometric redshift estimation. In this work we focus on the latter, considering two types of modeling uncertainties: uncertainties in the SED template set and uncertainties in the magnitude and type priors used in a Bayesian photometric redshift estimation method. We find that SED template selection effects dominate over magnitude prior errors. We introduce a method for parameterizing the resulting ignorance of the redshift distributions, and for propagating these uncertainties to uncertainties in cosmological parameters.Comment: 13 pages, 12 figures, version published in Ap

Optimal number of pigments in photosynthetic complexes

We study excitation energy transfer in a simple model of photosynthetic complex. The model, described by Lindblad equation, consists of pigments interacting via dipole-dipole interaction. Overlapping of pigments induces an on-site energy disorder, providing a mechanism for blocking the excitation transfer. Based on the average efficiency as well as robustness of random configurations of pigments, we calculate the optimal number of pigments that should be enclosed in a pigment-protein complex of a given size. The results suggest that a large fraction of pigment configurations are efficient as well as robust if the number of pigments is properly chosen. We compare optimal results of the model to the structure of pigment-protein complexes as found in nature, finding good agreement.Comment: 20 pages, 7 figures; v2.: new appendix, published versio

Functional near infrared spectroscopy (fNIRS) to assess cognitive function in infants in rural Africa

Cortical mapping of cognitive function during infancy is poorly understood in low-income countries due to the lack of transportable neuroimaging methods. We have successfully piloted functional near infrared spectroscopy (fNIRS) as a neuroimaging tool in rural Gambia. Four-to-eight month old infants watched videos of Gambian adults perform social movements, while haemodynamic responses were recorded using fNIRS. We found distinct regions of the posterior superior temporal and inferior frontal cortex that evidenced either visual-social activation or vocally selective activation (vocal > non-vocal). The patterns of selective cortical activation in Gambian infants replicated those observed within similar aged infants in the UK. These are the first reported data on the measurement of localized functional brain activity in young infants in Africa and demonstrate the potential that fNIRS offers for field-based neuroimaging research of cognitive function in resource-poor rural communities