Masses and Mixings in a Grand Unified Toy Model

The generation of the fermion mass hierarchy in the standard model of particle physics is a long-standing puzzle. The recent discoveries from neutrino physics suggests that the mixing in the lepton sector is large compared to the quark mixings. To understand this asymmetry between the quark and lepton mixings is an important aim for particle physics. In this regard, two promising approaches from the theoretical side are grand unified theories and family symmetries. In this note we try to understand certain general features of grand unified theories with Abelian family symmetries by taking the simplest SU(5) grand unified theory as a prototype. We construct an SU(5) toy model with $U(1)_F \otimes Z'_2\otimes Z''_2 \otimes Z'''_2$ family symmetry that, in a natural way, duplicates the observed mass hierarchy and mixing matrices to lowest approximation. The system for generating the mass hierarchy is through a Froggatt-Nielsen type mechanism. One idea that we use in the model is that the quark and charged lepton sectors are hierarchical with small mixing angles while the light neutrino sector is democratic with larger mixing angles. We also discuss some of the difficulties in incorporating finer details into the model without making further assumptions or adding a large scalar sector.Comment: 21 pages, 2 figures, RevTeX, v2: references updated and typos corrected, v3: updated top quark mass, comments on MiniBooNE result, and typos correcte

Quantification of Spatial Parameters in 3D Cellular Constructs Using Graph Theory

Multispectral three-dimensional (3D) imaging provides spatial information for biological structures that cannot be measured by traditional methods. This work presents a method of tracking 3D biological structures to quantify changes over time using graph theory. Cell-graphs were generated based on the pairwise distances, in 3D-Euclidean space, between nuclei during collagen I gel compaction. From these graphs quantitative features are extracted that measure both the global topography and the frequently occurring local structures of the “tissue constructs.” The feature trends can be controlled by manipulating compaction through cell density and are significant when compared to random graphs. This work presents a novel methodology to track a simple 3D biological event and quantitatively analyze the underlying structural change. Further application of this method will allow for the study of complex biological problems that require the quantification of temporal-spatial information in 3D and establish a new paradigm in understanding structure-function relationships

Statistical inference of OH concentrations and air mass dilution rates from successive observations of non-methane hydrocarbons in single air masses

Bayesian inference has been used to determine rigorous estimates of hydroxyl radical concentrations () and air mass dilution rates (K) averaged following air masses between linked observations of nonmethane hydrocarbons (NMHCs) spanning the North Atlantic during the Intercontinental Transport and Chemical Transformation (ITCT)-Lagrangian-2K4 experiment. The Bayesian technique obtains a refined (posterior) distribution of a parameter given data related to the parameter through a model and prior beliefs about the parameter distribution. Here, the model describes hydrocarbon loss through OH reaction and mixing with a background concentration at rate K. The Lagrangian experiment provides direct observations of hydrocarbons at two time points, removing assumptions regarding composition or sources upstream of a single observation. The estimates are sharpened by using many hydrocarbons with different reactivities and accounting for their variability and measurement uncertainty. A novel technique is used to construct prior background distributions of many species, described by variation of a single parameter . This exploits the high correlation of species, related by the first principal component of many NMHC samples. The Bayesian method obtains posterior estimates of , K and following each air mass. Median values are typically between 0.5 and 2.0 × 106 molecules cm−3, but are elevated to between 2.5 and 3.5 × 106 molecules cm−3, in low-level pollution. A comparison of estimates from absolute NMHC concentrations and NMHC ratios assuming zero background (the “photochemical clock” method) shows similar distributions but reveals systematic high bias in the estimates from ratios. Estimates of K are ∼0.1 day−1 but show more sensitivity to the prior distribution assumed

The ABCD of usability testing

We introduce a methodology for tracking and auditing feedback, errors and suggestions for software packages. This short paper describes how we innovate on the evaluation mechanism, introducing an (Antecedent, Barrier, Consequence and Development) ABCD form, embedded within an eParticipation platform to enable end users to easily report on any usability issues. This methodology will be utilised to improve the STEP cloud eParticipation platform (part of the current STEP Horizon2020 project http://step4youth.eu. The platform is currently being piloted in real life contexts, with the participation of public authorities that are integrating the eParticipation platform into their regular decision-making practices. The project is involving young people, through engagement and motivation strategies and giving them a voice in Environmental decision making at the local level. The pilot evaluation aims to demonstrate how open engagement needs to be embedded within public sector processes and the usability methodology reported here will help to identify the key barriers for wide scale deployment of the platform