Lorentz Violation and Short-Baseline Neutrino Experiments

A general discussion is given of signals for broken Lorentz symmetry in short-baseline neutrino experiments. Among the effects that Lorentz violation can introduce are a dependence on energy differing from that of the usual massive-neutrino solution and a dependence on the direction of neutrino propagation. Using the results of the LSND experiment, explicit analysis of the effects of broken Lorentz symmetry yields a nonzero value (3+/-1) x 10^{-19} GeV for a combination of coefficients for Lorentz violation. This lies in the range expected for effects originating from the Planck scale in an underlying unified theory.Comment: 4 pages REVTe

In vivo imaging of the tonoplast intrinsic protein family in Arabidopsis roots

Background: Tonoplast intrinsic proteins (TIPs) are widely used as markers for vacuolar compartments in higher plants. Ten TIP isoforms are encoded by the Arabidopsis genome. For several isoforms, the tissue and cell specific pattern of expression are not known. Results: We generated fluorescent protein fusions to the genomic sequences of all members of the Arabidopsis TIP family whose expression is predicted to occur in root tissues (TIP1;1 and 1;2; TIP2;1, 2;2 and 2;3; TIP4;1) and expressed these fusions, both individually and in selected pairwise combinations, in transgenic Arabidopsis. Analysis by confocal microscopy revealed that TIP distribution varied between different cell layers within the root axis, with extensive co-expression of some TIPs and more restricted expression patterns for other isoforms. TIP isoforms whose expression overlapped appeared to localise to the tonoplast of the central vacuole, vacuolar bulbs and smaller, uncharacterised structures. Conclusion: We have produced a comprehensive atlas of TIP expression in Arabidopsis roots, which reveals novel expression patterns for not previously studied TIPs

Facing up to the challenge of behavioural observation in infant hearing assessment

The ability to assess detection and discrimination of speech by infants has proved elusive. Dr Iain Jackson and colleagues discuss how new technologies and fresh approaches might offer valuable insight into young infants’ behavioural responses to sound

Inference for mixtures of symmetric distributions

This article discusses the problem of estimation of parameters in finite mixtures when the mixture components are assumed to be symmetric and to come from the same location family. We refer to these mixtures as semi-parametric because no additional assumptions other than symmetry are made regarding the parametric form of the component distributions. Because the class of symmetric distributions is so broad, identifiability of parameters is a major issue in these mixtures. We develop a notion of identifiability of finite mixture models, which we call k-identifiability, where k denotes the number of components in the mixture. We give sufficient conditions for k-identifiability of location mixtures of symmetric components when k=2 or 3. We propose a novel distance-based method for estimating the (location and mixing) parameters from a k-identifiable model and establish the strong consistency and asymptotic normality of the estimator. In the specific case of L_2-distance, we show that our estimator generalizes the Hodges--Lehmann estimator. We discuss the numerical implementation of these procedures, along with an empirical estimate of the component distribution, in the two-component case. In comparisons with maximum likelihood estimation assuming normal components, our method produces somewhat higher standard error estimates in the case where the components are truly normal, but dramatically outperforms the normal method when the components are heavy-tailed.Comment: Published at http://dx.doi.org/10.1214/009053606000001118 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Monte Carlo cluster algorithm for fluid phase transitions in highly size-asymmetrical binary mixtures

Highly size-asymmetrical fluid mixtures arise in a variety of physical contexts, notably in suspensions of colloidal particles to which much smaller particles have been added in the form of polymers or nanoparticles. Conventional schemes for simulating models of such systems are hamstrung by the difficulty of relaxing the large species in the presence of the small one. Here we describe how the rejection-free geometrical cluster algorithm (GCA) of Liu and Luijten [Phys. Rev. Lett 92, 035504 (2004)] can be embedded within a restricted Gibbs ensemble to facilitate efficient and accurate studies of fluid phase behavior of highly size-asymmetrical mixtures. After providing a detailed description of the algorithm, we summarize the bespoke analysis techniques of Ashton et al. [J. Chem. Phys. 132, 074111 (2010)] that permit accurate estimates of coexisting densities and critical-point parameters. We apply our methods to study the liquid--vapor phase diagram of a particular mixture of Lennard-Jones particles having a 10:1 size ratio. As the reservoir volume fraction of small particles is increased in the range 0--5%, the critical temperature decreases by approximately 50%, while the critical density drops by some 30%. These trends imply that in our system, adding small particles decreases the net attraction between large particles, a situation that contrasts with hard-sphere mixtures where an attractive depletion force occurs.Comment: 11 pages, 10 figure

Big Data, Big Knowledge: Big Data for Personalized Healthcare.

The idea that the purely phenomenological knowledge that we can extract by analyzing large amounts of data can be useful in healthcare seems to contradict the desire of VPH researchers to build detailed mechanistic models for individual patients. But in practice no model is ever entirely phenomenological or entirely mechanistic. We propose in this position paper that big data analytics can be successfully combined with VPH technologies to produce robust and effective in silico medicine solutions. In order to do this, big data technologies must be further developed to cope with some specific requirements that emerge from this application. Such requirements are: working with sensitive data; analytics of complex and heterogeneous data spaces, including nontextual information; distributed data management under security and performance constraints; specialized analytics to integrate bioinformatics and systems biology information with clinical observations at tissue, organ and organisms scales; and specialized analytics to define the "physiological envelope" during the daily life of each patient. These domain-specific requirements suggest a need for targeted funding, in which big data technologies for in silico medicine becomes the research priority

A simulational and theoretical study of the spherical electrical double layer for a size-asymmetric electrolyte: the case of big coions

Monte Carlo simulations of a spherical macroion, surrounded by a size-asymmetric electrolyte in the primitive model, were performed. We considered 1:1 and 2:2 salts with a size ratio of 2 (i.e., with coions twice the size of counterions), for several surface charge densities of the macrosphere. The radial distribution functions, electrostatic potential at the Helmholtz surfaces, and integrated charge are reported. We compare these simulational data with original results obtained from the Ornstein-Zernike integral equation, supplemented by the hypernetted chain/hypernetted chain (HNC/HNC) and hypernetted chain/mean spherical approximation (HNC/MSA) closures, and with the corresponding calculations using the modified Gouy-Chapman and unequal-radius modified Gouy-Chapman theories. The HNC/HNC and HNC/MSA integral equations formalisms show good concordance with Monte Carlo "experiments", whereas the notable limitations of point-ion approaches are evidenced. Most importantly, the simulations confirm our previous theoretical predictions of the non-dominance of the counterions in the size-asymmetric spherical electrical double layer [J. Chem. Phys. 123, 034703 (2005)], the appearance of anomalous curvatures at the outer Helmholtz plane and the enhancement of charge reversal and screening at high colloidal surface charge densities due to the ionic size asymmetry.Comment: 11 pages, 7 figure

Portable dynamic fundus instrument

A portable diagnostic image analysis instrument is disclosed for retinal funduscopy in which an eye fundus image is optically processed by a lens system to a charge coupled device (CCD) which produces recordable and viewable output data and is simultaneously viewable on an electronic view finder. The fundus image is processed to develop a representation of the vessel or vessels from the output data

Electrophoretic Properties of Highly Charged Colloids: A Hybrid MD/LB Simulation Study

Using computer simulations, the electrophoretic motion of a positively charged colloid (macroion) in an electrolyte solution is studied in the framework of the primitive model. Hydrodynamic interactions are fully taken into account by applying a hybrid simulation scheme, where the charged ions (i.e. macroion and electrolyte), propagated via molecular dynamics (MD), are coupled to a Lattice Boltzmann (LB) fluid. In a recent experiment it was shown that, for multivalent salt ions, the mobility $\mu$ initially increases with charge density $\sigma$, reaches a maximum and then decreases with further increase of $\sigma$. The aim of the present work is to elucidate the behaviour of $\mu$ at high values of $\sigma$. Even for the case of monovalent microions, we find a decrease of $\mu$ with $\sigma$. A dynamic Stern layer is defined that includes all the counterions that move with the macroion while subject to an external electrical field. The number of counterions in the Stern layer, $q_0$, is a crucial parameter for the behavior of $\mu$ at high values of $\sigma$. In this case, the mobility $\mu$ depends primarily on the ratio $q_0/Q$ (with $Q$ the valency of the macroion). The previous contention that the increase in the distortion of the electric double layer (EDL) with increasing $\sigma$ leads to the lowering of $\mu$ does not hold for high $\sigma$. In fact, we show that the deformation of the EDL decreases with increase of $\sigma$. The role of hydrodynamic interactions is inferred from direct comparisons to Langevin simulations where the coupling to the LB fluid is switched off. Moreover, systems with divalent counterions are considered. In this case, at high values of $\sigma$ the phenomenon of charge inversion is found.Comment: accepted in J. Chem Phys., 10 pages, 9 figure