Pattern Reification as the Basis for Description-Driven Systems

One of the main factors driving object-oriented software development for information systems is the requirement for systems to be tolerant to change. To address this issue in designing systems, this paper proposes a pattern-based, object-oriented, description-driven system (DDS) architecture as an extension to the standard UML four-layer meta-model. A DDS architecture is proposed in which aspects of both static and dynamic systems behavior can be captured via descriptive models and meta-models. The proposed architecture embodies four main elements - firstly, the adoption of a multi-layered meta-modeling architecture and reflective meta-level architecture, secondly the identification of four data modeling relationships that can be made explicit such that they can be modified dynamically, thirdly the identification of five design patterns which have emerged from practice and have proved essential in providing reusable building blocks for data management, and fourthly the encoding of the structural properties of the five design patterns by means of one fundamental pattern, the Graph pattern. A practical example of this philosophy, the CRISTAL project, is used to demonstrate the use of description-driven data objects to handle system evolution.Comment: 20 pages, 10 figure

Modeling of Polymer Clay Nanocomposite for a Multiscale Approach

The mechanical property enhancement of polymer reinforced with nano-thin clay platelets (of high aspect ratio) is associated with a high polymer-filler interfacial area per unit volume. The ideal case of fully separated (exfoliated) platelets is generally difficult to achieve in practice: a typical nanocomposite also contains multilayer stacks of intercalated platelets. Here we use numerical modelling to investigate how the platelet properties affect the overall mechanical properties. The configuration of platelets is modelled using a statistical interpretation of the Representative Volume Element (RVE) approach, in which an ensemble of "sample" heterogeneous material is generated (with periodic boundary conditions). A simple Monte Carlo algorithm is used to place non-intersecting platelets in the RVE according to a specified set of statistical distributions. The effective stiffness of the platelet-matrix system is determined by measuring the stress (using standard Finite Element analysis) produced as a result of applying a small deformation to the boundaries, and averaging over the entire statistical ensemble. In this work we determine the way in which the platelet properties (curvature, filling fraction, stiffness, aspect ratio) and the number of layers in the stack affect the overall stiffness enhancement of the nanocomposite. Thus, we bridge the gap between behaviour on the macroscopic scale with that on the scale of the nano-reinforcement, forming part of a multi-scale modelling framework.Comment: 39 pages, 19 figure

A reduced-order strategy for 4D-Var data assimilation

This paper presents a reduced-order approach for four-dimensional variational data assimilation, based on a prior EO F analysis of a model trajectory. This method implies two main advantages: a natural model-based definition of a mul tivariate background error covariance matrix $\textbf{B}_r$, and an important decrease of the computational burden o f the method, due to the drastic reduction of the dimension of the control space. % An illustration of the feasibility and the effectiveness of this method is given in the academic framework of twin experiments for a model of the equatorial Pacific ocean. It is shown that the multivariate aspect of $\textbf{B}_r$ brings additional information which substantially improves the identification procedure. Moreover the computational cost can be decreased by one order of magnitude with regard to the full-space 4D-Var method

Impact of Temporary Nitrogen Deprivation on Tomato Leaf Phenolics

Reducing the use of pesticides represents a major challenge of modern agriculture. Plants synthesize secondary metabolites such as polyphenols that participate in the resistance to parasites. The aim of this study was to test: (1) the impact of nitrogen deficiency on tomato (Solanum lycopersicum) leaf composition and more particularly on two phenolic molecules (chlorogenic acid and rutin) as well as on the general plant biomass; and (2) whether this effect continued after a return to normal nitrogen nutrition. Our results showed that plants deprived of nitrogen for 10 or 19 days contained higher levels of chlorogenic acid and rutin than control plants. In addition, this difference persisted when the plants were once again cultivated on a nitrogen-rich medium. These findings offer interesting perspectives on the use of a short period of deprivation to modulate the levels of compounds of interest in a plant

Influence of apical oxygen on the extent of in-plane exchange interaction in cuprate superconductors

In high Tc superconductors the magnetic and electronic properties are determined by the probability that valence electrons virtually jump from site to site in the CuO2 planes, a mechanism opposed by on-site Coulomb repulsion and favored by hopping integrals. The spatial extent of the latter is related to transport properties, including superconductivity, and to the dispersion relation of spin excitations (magnons). Here, for three antiferromagnetic parent compounds (single-layer Bi2Sr0.99La1.1CuO6+delta, double-layer Nd1.2Ba1.8Cu3O6 and infinite-layer CaCuO2) differing by the number of apical atoms, we compare the magnetic spectra measured by resonant inelastic x-ray scattering over a significant portion of the reciprocal space and with unprecedented accuracy. We observe that the absence of apical oxygens increases the in-plane hopping range and, in CaCuO2, it leads to a genuine 3D exchange-bond network. These results establish a corresponding relation between the exchange interactions and the crystal structure, and provide fresh insight into the materials dependence of the superconducting transition temperature.Comment: 9 pages, 4 figures, 1 Table, 42 reference

Cutoff Suppresses RNA Polymerase II Termination to Ensure Expression of piRNA Precursors

Small non-coding RNAs called piRNAs serve as guides for an adaptable immune system that represses transposable elements in germ cells of Metazoa. In Drosophila the RDC complex, composed of Rhino, Deadlock and Cutoff (Cuff) bind chromatin of dual-strand piRNA clusters, special genomic regions, which encode piRNA precursors. The RDC complex is required for transcription of piRNA precursors, though the mechanism by which it licenses transcription remained unknown. Here, we show that Cuff prevents premature termination of RNA polymerase II. Cuff prevents cleavage of nascent RNA at poly(A) sites by interfering with recruitment of the cleavage and polyadenylation specificity factor (CPSF) complex. Cuff also protects processed transcripts from degradation by the exonuclease Rat1. Our work reveals a conceptually different mechanism of transcriptional enhancement. In contrast to other factors that regulate termination by binding to specific signals on nascent RNA, the RDC complex inhibits termination in a chromatin-dependent and sequence-independent manner

On the universality of density profiles

We use the secondary infall model described in Del Popolo (2009), which takes into account the effect of dynamical friction, ordered and random angular momentum, baryons adiabatic contraction and dark matter baryons interplay, to study how in- ner slopes of relaxed LCDM dark matter (DM) halos with and without baryons (baryons+DM, and pure DM) depend on redshift and on halo mass. We apply the quoted method to structures on galactic scales and clusters of galaxies scales. We find that the inner logarithmic density slope, of dark matter halos with baryons has a significant dependence on halo mass and redshift with slopes ranging from 0 for dwarf galaxies to 0.4 for objects of M = 10^13M_solar and 0.94 for M = 10^15M_solar clusters of galaxies. Structures slopes increase with increasing redshift and this trend reduces going from galaxies to clusters. In the case of density profiles constituted just of dark matter the mass and redshift dependence of slope is very slight. In this last case, we used the Merrit et al. (2006) analysis who compared N-body density profiles with various parametric models finding systematic variation in profile shape with halo mass. This last analysis suggests that the galaxy-sized halos obtained with our model have a different shape parameter, i.e. a different mass distribution, than the cluster-sized halos, obtained with the same model. The results of the present paper argue against universality of density profiles constituted by dark matter and baryons and confirm claims of a systematic variation in profile shape with halo mass, for dark matter halos.Comment: 11 pages, 5 figure

Vehicle localization by lidar point correlation improved by change detection

LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany

Deciphering magnetospheric cross‐field currents

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94998/1/grl28658.pd