Identification of candidate genes at the corticoseptal boundary during development

Cortical midline glia are critical to the formation of the corpus callosum during development. The glial wedge is a Population of midline glia that is located at the corticoseptal boundary and expresses repulsive/growth-inhibitory molecules that guide callosal axons as they cross the midline. The glial wedge are the first cells within the cortex to express GFAP and thus may express molecules specific for glial maturation. The corticoseptal boundary is a genetically defined boundary between the cingulate cortex (dorsal telencephalon) and the septum (ventral telencephalon). The correct dorso-ventral position of this boundary is vital to the formation of both the glial wedge and the corpus callosum. Our aim was to identify genes expressed specifically within the glial wedge that might be involved in either glial differentiation, formation of the corticoseptal boundary or development of the corpus callosum. To identify such genes we have performed a differential display PCR screen comparing RNA isolated from the glial wedge with RNA isolated from control tissues such as the neocortex and septum, of embryonic day 17 mouse brains. Using 200 different combinations of primers, we identified and cloned 67 distinct gene fragments. In situ hybridization analysis confirmed the differential expression of many of the genes, and showed that clones G24F3, G39F8 and transcription factor LZIP have specific expression patterns in the telencephalon of embryonic and postnatal brains. An RNase Protection Assay (RPA) revealed that the expression of G39F8, G24173 and LZIP increase markedly in the telencephalon at E16 and continue to be expressed until at least PO, during the period when the corpus callosum is forming. (c) 2005 Elsevier B.V. All rights reserved.

Predictors of cultural adjustment: Intergroup status relations and boundary permeability

We examined intergroup predictors of cultural adjustment among Asian international students in Australia. Sociostructural beliefs (status, legitimacy, and permeability) and initial adjustment were assessed (N = 113) at Time 1, and measures of adjustment were obtained (N = 80) at Time 2 eight weeks later. International students who perceived their cultural group to be relatively low in status experienced lower levels of psychological adjustment. Also, as expected, the effects of status were moderated by perceptions of both the permeability of intergroup boundaries and the legitimacy of the status differential. At high levels of legitimacy, perceptions of permeable group boundaries were associated with better psychological, sociocultural, and academic adjustment among international students perceiving their group to be low in status, but lower levels of adjustment among students who perceived their group to be high in status. At low levels of legitimacy, irrespective of group status position, perceived permeability was not related to adjustment.

Optimising profitability and environmental trade-offs in managing cropping systems using differential evolution

Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.

Differential diffusion: Often a finite-mising length effect

Many instances of differential diffusion, i e, different species having different turbulent diffusion coefficients in the same flow, can be explained as a finite mixing length effect. That is, in a simple mixing length scenario, the turbulent diffusion coefficient has the form 1 ( m )2 m m c l K w l OL   =  +    where, wm is the mixing velocity, lm the mixing length and Lc the overall distribution scale for a particular species. The first term represents the familiar gradient diffusion while the second term becomes important when lm/Lc is finite. This second term shows that different species will have different diffusion coefficients if they have different overall distribution scales. Such different Lcs may come about due to different boundary conditions and different intrinsic properties (molecular diffusivity, settling velocity etc) for different species. For momentum transfer in turbulent oscillatory boundary layers the second term is imaginary and explains observed phase leads of shear stresses ahead of velocity gradients.

Differential Priors for Elastic Nets

The elastic net and related algorithms, such as generative topographic mapping, are key methods for discretized dimension-reduction problems. At their heart are priors that specify the expected topological and geometric properties of the maps. However, up to now, only a very small subset of possible priors has been considered. Here we study a much more general family originating from discrete, high-order derivative operators. We show theoretically that the form of the discrete approximation to the derivative used has a crucial influence on the resulting map. Using a new and more powerful iterative elastic net algorithm, we confirm these results empirically, and illustrate how different priors affect the form of simulated ocular dominance columns.

A new relaxation method for roll forming problems

Finite element analysis (FEA) of nonlinear problems in solid mechanics is a time consuming process, but it can deal rigorously with the problems of both geometric, contact and material nonlinearity that occur in roll forming. The simulation time limits the application of nonlinear FEA to these problems in industrial practice, so that most applications of nonlinear FEA are in theoretical studies and engineering consulting or troubleshooting. Instead, quick methods based on a global assumption of the deformed shape have been used by the roll-forming industry. These approaches are of limited accuracy. This paper proposes a new form-finding method - a relaxation method to solve the nonlinear problem of predicting the deformed shape due to plastic deformation in roll forming. This method involves applying a small perturbation to each discrete node in order to update the local displacement field, while minimizing plastic work. This is iteratively applied to update the positions of all nodes. As the method assumes a local displacement field, the strain and stress components at each node are calculated explicitly. Continued perturbation of nodes leads to optimisation of the displacement field. Another important feature of this paper is a new approach to consideration of strain history. For a stable and continuous process such as rolling and roll forming, the strain history of a point is represented spatially by the states at a row of nodes leading in the direction of rolling to the current one. Therefore the increment of the strain components and the work-increment of a point can be found without moving the object forward. Using this method we can find the solution for rolling or roll forming in just one step. This method is expected to be faster than commercial finite element packages by eliminating repeated solution of large sets of simultaneous equations and the need to update boundary conditions that represent the rolls.

The programming language python in earth system simulations

-scale vary from a planetary scale and million years for convection problems to 100km and 10 years for fault systems simulations. Various techniques are in use to deal with the time dependency (e.g. Crank-Nicholson), with the non-linearity (e.g. Newton-Raphson) and weakly coupled equations (e.g. non-linear Gauss-Seidel). Besides these high-level solution algorithms discretization methods (e.g. finite element method (FEM), boundary element method (BEM)) are used to deal with spatial derivatives. Typically, large-scale, three dimensional meshes are required to resolve geometrical complexity (e.g. in the case of fault systems) or features in the solution (e.g. in mantel convection simulations). The modelling environment escript allows the rapid implementation of new physics as required for the development of simulation codes in earth sciences. Its main object is to provide a programming language, where the user can define new models and rapidly develop high-level solution algorithms. The current implementation is linked with the finite element package finley as a PDE solver. However, the design is open and other discretization technologies such as finite differences and boundary element methods could be included. escript is implemented as an extension of the interactive programming environment python (see www.python.org). Key concepts introduced are Data objects, which are holding values on nodes or elements of the finite element mesh, and linearPDE objects, which are defining linear partial differential equations to be solved by the underlying discretization technology. In this paper we will show the basic concepts of escript and will show how escript is used to implement a simulation code for interacting fault systems. We will show some results of large-scale, parallel simulations on an SGI Altix system. Acknowledgements: Project work is supported by Australian Commonwealth Government through the Australian Computational Earth Systems Simulator Major National Research Facility, Queensland State Government Smart State Research Facility Fund, The University of Queensland and SGI.