Catabolite repression of beta-galactosidase synthesis in Escherichia coli

Abstract not provided

Estimation of Seasonal Precipitation Tercile-Based Categorical Probabilities from Ensembles

Ensemble simulations and forecasts provide probabilistic information about the inherently uncertain climate system. Counting the number of ensemble members in a category is a simple nonparametric method of using an ensemble to assign categorical probabilities. Parametric methods of assigning quantile-based categorical probabilities include distribution fitting and generalized linear regression. Here the accuracy of counting and parametric estimates of tercile category probabilities is compared. The methods are first compared in an idealized setting where analytical results show how ensemble size and level of predictability control the accuracy of both methods. The authors also show how categorical probability estimate errors degrade the rank probability skill score. The analytical results provide a good description of the behavior of the methods applied to seasonal precipitation from a 53-yr, 79-member ensemble of general circulation model simulations. Parametric estimates of seasonal precipitation tercile category probabilities are generally more accurate than the counting estimate. In addition to determining the relative accuracies of the different methods, the analysis quantifies the relative importance of the ensemble mean and variance in determining tercile probabilities. Ensemble variance is shown to be a weak factor in determining seasonal precipitation probabilities, meaning that differences between the tercile probabilities and the equal-odds probabilities are due mainly to shifts of the forecast mean away from its climatological value

The impact of self-interacting dark matter on the intrinsic alignments of galaxies

The formation and evolution of galaxies is known to be sensitive to tidal processes leading to intrinsic correlations between their shapes and orientations. Such correlations can be measured to high significance today, suggesting that cosmological information can be extracted from them. Among the most pressing questions in particle physics and cosmology is the nature of dark matter. If dark matter is self-interacting, it can leave an imprint on galaxy shapes. In this work, we investigate whether self-interactions can produce a long-lasting imprint on intrinsic galaxy shape correlations. We investigate this observable at low redshift (z < 0.4) using a state-of-the-art suite of cosmological hydro-dynamical simulations where the dark matter model is varied. We find that dark matter self-interactions induce a mass-dependent suppression in the intrinsic alignment signal by up to 50 per cent out to tens of mega-parsecs, showing that self-interactions can impact structure outside the very core of clusters. We find evidence that self-interactions have a scale-dependent impact on the intrinsic alignment signal that is sufficiently different from signatures introduced by differing baryonic physics prescriptions, suggesting that it is detectable with upcoming all-sky surveys

A model to estimate the impact of changes in MMR vaccine uptake on inequalities in measles susceptibility in Scotland

In 1998 an article published by Andrew Wakefield in The Lancet (volume 351, pages 637-641) led to concerns surrounding the safety of the measles, mumps and rubella (MMR) vaccine, by associating it with an increased risk of autism. The paper was later retracted after multiple epidemiological studies failed to fnd any association, but a substantial decrease in UK vaccination rates was observed in the years following publication. This paper proposes a novel spatio-temporal Bayesian hierarchical model with accompanying software (the R package CARBayesST) to simultaneously address three key epidemiological questions about vaccination rates: (i) what impact did the controversy have on the overall temporal trend in vaccination rates in Scotland; (ii) did the magnitude of the spatial inequality in measles susceptibility in Scotland increase due to the MMR vaccination scare; and (iii) are there any covariate effects, such as deprivation, that impacted on measles susceptibility in Scotland. The efficacy of the model is tested by simulation, before being applied to measles susceptibility data in Scotland among a series of cohorts of children who were aged 2-4, in the years 1998 to 2014

Clustering of eastern North Pacific tropical cyclone tracks: ENSO and MJO effects

A probabilistic clustering technique is used to describe tropical cyclone tracks in the eastern North Pacific, on the basis of their shape and location. The best track data set is decomposed in terms of three clusters; these clusters are analyzed in terms of genesis location, trajectory, landfall, intensity, seasonality, and their relationships with the El Niño–Southern Oscillation (ENSO) and Madden-Julian Oscillation (MJO). Longitudinal track location plays a strong discriminating role in the regression mixture model's solution, with the average track orientation becoming more zonal toward the west. This progression encapsulates well the relationship between tropical cyclones over the eastern tropical Pacific and the MJO or ENSO. Two of the clusters describe tropical cyclones (TCs) with tracks that lie near the coast of Mexico and Central America. The most frequent cluster contains tracks that trend west-northwestward, while the second most frequent one has genesis locations that lie slightly to the southeast of those in the most frequent cluster and tracks that run typically parallel to the Central American coast. This second cluster is shown to be significantly associated with the westerly phase of the MJO. The third, least frequent cluster contains TCs with westward trajectories over the central and eastern equatorial Pacific; some of these TCs have an impact on Hawaii and other islands, as far as the central and western North Pacific regions. The least frequent cluster is strongly related to ENSO, while the others are not; it occurs significantly more frequently during El Niño conditions. Examination of the large-scale patterns of atmospheric circulation and sea surface temperature associated with each of our three clusters are consistent with previous studies. Anomalous low-level westerly zonal winds from the monsoon trough and MJO meet anomalous easterlies near the region of genesis in each cluster

Cross-time scales interactions and rainfall extreme events in southeastern South America for the austral summer. Part II: predictive skill

Potential and real predictive skill of the frequency of extreme rainfall in southeastern South America for the December–February season are evaluated in this paper, finding evidence indicating that mechanisms of climate variability at one time scale contribute to the predictability at another scale; that is, taking into account the interference of different potential sources of predictability at different time scales increases the predictive skill. Part I of this study suggested that a set of daily atmospheric circulation regimes, or weather types, was sensitive to these cross–time scale interferences, conducive to the occurrence of extreme rainfall events in the region, and could be used as a potential predictor. At seasonal scale, a combination of those weather types indeed tends to outperform all the other candidate predictors explored (i.e., sea surface temperature patterns, phases of the Madden–Julian oscillation, and combinations of both). Spatially averaged Kendall’s t improvements of 43% for the potential predictability and 23% for real-time predictions are attained with respect to standard models considering sea surface temperature fields alone. A new subseasonal-to-seasonal predictive methodology for extreme rainfall events is proposed based on probability forecasts of seasonal sequences of these weather types. The cross-validated real-time skill of the new probabilistic approach, as measured by the hit score and the Heidke skill score, is on the order of twice that associated with climatological values. The approach is designed to offer useful subseasonal-to-seasonal climate information to decision-makers interested not only in how many extreme events will happen in the season but also in how, when, and where those events will probably occur

Matter-wave bistability in coupled atom-molecule quantum gases

We study the matter-wave bistability in coupled atom-molecule quantum gases, in which heteronuclear molecules are created via an interspecies Feshbach resonance involving either two-species Bose or two-species Fermi atoms at zero temperature. We show that the resonant two-channel Bose model is equivalent to the nondegenerate parametric down-conversion in quantum optics, while the corresponding Fermi model can be mapped to a quantum optics model that describes a single-mode laser field interacting with an ensemble of inhomogeneously broadened two-level atoms. Using these analogy and the fact that both models are subject to the Kerr nonlinearity due to the two-body s-wave collisions, we show that under proper conditions, the population in the molecular state in both models can be made to change with the Feshbach detuning in a bistable fashion.Comment: 6 pages, 5 figure

Non-equilibrium Enhancement of Cooper Pairing in Cold Fermion Systems

Non-equilibrium stimulation of superfluidity in trapped Fermi gases is discussed by analogy to the work of Eliashberg [G. M. Eliashberg, in "Nonequilibrium Superconductivity," edited by D. N. Langenberg and A. I. Larkin (North-Holland, New York, 1986)] on the microwave enhancement of superconductivity. Optical excitation of the fermions balanced by heat loss due to thermal contact with a boson bath and/or evaporative cooling enables stationary non-equilibrium states to exist. Such a state manifests as a shift of the quasiparticle spectrum to higher energies and this effect effectively raises the pairing transition temperature. As an illustration, we calculate the effective enhancement of Cooper pairing and superfluidity in both the normal and superfluid phases for a mixture of Rb and Li in the limit of small departure from equilibrium. It is argued that in experiment the desirable effect is not limited to such small perturbations and the effective enhancement of the pairing temperature may be quite large.Comment: 7 pages, 6 figure

Exploring extensions to the standard cosmological model and the impact of baryons on small scales

It has been claimed that the standard model of cosmology (ΛCDM) cannot easily account for a number of observations on relatively small scales, motivating extensions to the standard model. Here, we introduce a new suite of cosmological simulations that systematically explores three plausible extensions: warm dark matter, self-interacting dark matter, and a running of the scalar spectral index of density fluctuations. Current observational constraints are used to specify the additional parameters that come with these extensions. We examine a large range of observable metrics on small scales, including the halo mass function, density, and circular velocity profiles, the abundance of satellite subhaloes, and halo concentrations. For any given metric, significant degeneracies can be present between the extensions. In detail, however, the different extensions have quantitatively distinct mass and radial dependencies, suggesting that a multiprobe approach over a range of scales can be used to break the degeneracies. We also demonstrate that the relative effects on the radial density profiles in the different extensions (compared to the standard model) are converged down to significantly smaller radii than are the absolute profiles. We compare the derived cosmological trends with the impact of baryonic physics using the EAGLE and ARTEMIS simulations. Significant degeneracies are also present between baryonic physics and cosmological variations (with both having similar magnitude effects on some observables). Given the inherent uncertainties both in the modelling of galaxy formation physics and extensions to ΛCDM, a systematic and simultaneous exploration of both is strongly warranted

Detecting morphed passport photos : a training and individual differences approach

Our reliance on face photos for identity verification is at odds with extensive research which shows that matching pairs of unfamiliar faces is highly prone to error. This process can therefore be exploited by identity fraudsters seeking to deceive ID checkers (e.g. using a stolen passport which contains an image of similar looking individual to deceive border control officials). In this study we build on previous work which sought to quantify the threat posed by a relatively new type of fraud - morphed passport photos. Participants were initially unaware of the presence of morphs in a series of face photo arrays, and were simply asked to detect which images they thought had been digitally manipulated (i.e. “images that didn’t look quite right”). All participants then received basic information on morph fraud and rudimentary guidance on how to detect such images, followed by a morph detection training task (Training Group, N = 40), or a non-face control task (Guidance Group, N = 40). Participants also completed a post-guidance/training morph detection task, and the Models Face Matching Test (MFMT). Our findings show that baseline morph detection rates were poor, that morph detection training significantly improved the identification of these images over and above basic guidance, and accuracy on the mismatch condition of the MFMT correlated with morph detection ability. The results are discussed in relation to potential counter-measures for morph-based identity fraud