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.

Measuring the spatial arrangement patterns of pathological lesions in histological sections of brain tissue

The development of abnormal protein aggregates in the form of extracellular plaques and intracellular inclusions is a characteristic feature of many neurodegenerative diseases such as Alzheimer's disease (AD), Creutzfeldt-Jakob disease (CJD) and the fronto-temporal dementias (FTD). An important aspect of a pathological protein aggregate is its spatial topography in the tissue. Lesions may not be randomly distributed within a histological section but exhibit spatial pattern, a departure from randomness either towards regularity or clustering. Information on the spatial pattern of a lesion may be useful in elucidating its pathogenesis and in studying the relationships between different lesions. This article reviews the methods that have been used to study the spatial topography of lesions. These include simple tests of whether the distribution of a lesion departs significantly from random using randomized points or sample fields, and more complex methods that employ grids or transects of contiguous fields and which can detect the intensity of aggregation and the sizes, distribution and spacing of the clusters. The usefulness of these methods in elucidating the pathogenesis of protein aggregates in neurodegenerative disease is discussed.

Can we observe collective neuronal activity from macroscopic aggregate signals?

The fundamental problem faced by noninvasive neuroimaging techniques such as EEG/MEG1 is to elucidate functionally important aspects of the microscopic neuronal network dynamics from macroscopic aggregate measurements. Due to the mixing of the activities of large neuronal populations in the observed macroscopic aggregate, recovering the underlying network that generates the signal in the absence of any additional information represents a considerable challenge. Recent MEG studies have shown that macroscopic measurements contain sufficient information to allow the differentiation between patterns of activity, which are likely to represent different stimulus-specific collective modes in the underlying network (Hadjipapas, A., Adjamian, P., Swettenham, J.B., Holliday, I.E., Barnes, G.R., 2007. Stimuli of varying spatial scale induce gamma activity with distinct temporal characteristics in human visual cortex. NeuroImage 35, 518–530). The next question arising in this context is whether aspects of collective network activity can be recovered from a macroscopic aggregate signal. We propose that this issue is most appropriately addressed if MEG/EEG signals are to be viewed as macroscopic aggregates arising from networks of coupled systems as opposed to aggregates across a mass of largely independent neural systems. We show that collective modes arising in a network of simulated coupled systems can be indeed recovered from the macroscopic aggregate. Moreover, we show that nonlinear state space methods yield a good approximation of the number of effective degrees of freedom in the network. Importantly, information about hidden variables, which do not directly contribute to the aggregate signal, can also be recovered. Finally, this theoretical framework can be applied to experimental MEG/EEG data in the future, enabling the inference of state dependent changes in the degree of local synchrony in the underlying network.

A quest for helpful feedback to programming coursework

The 2011 National Student Survey (NSS) revealed that 40% of full-time students in England did not think that the feedback on their work has been helpful, even though 66% of these students agreed that the feedback was detailed and 62% of them agreed that the feedback has been prompt. Detailed feedback that is not considered helpful by students means a waste of tutors' time while students continue to struggle with their learning. What do students consider as helpful feedback? What are the qualities of helpful feedback? What are the preferred forms of feedback? How should tutors write feedback so that students will find it helpful? Can ICT help to improve the quality of feedback? In our ongoing search for answers to the above questions, we have trialled the use of a novel Internet application, called eCAF, to assess programming coursework from Engineering, Mathematics and Computing students and have collected their views on the feedback received through a survey. The survey reveals that most students prefer electronic feedback as given through eCAF, with verbal feedback ranked second and hand-written feedback ranked even lower. The survey also indicates that the feedback from some tutors is considered more helpful than others. We report on the detailed findings of the survey. By comparing the kinds of feedback given by each tutor who took part in the trial, we explore ways to improve the helpfulness of feedback on programming coursework in a bid to promote learning amongst engineering students.

An aggregate measure of financial ratios using a multiplicative DEA model

This paper examines the problems in the definition of the General Non-Parametric Corporate Performance (GNCP) and introduces a multiplicative linear programming as an alternative model for corporate performance. We verified and tested a statistically significant difference between the two models based on the application of 27 UK industries using six performance ratios. Our new model is found to be a more robust performance model than the previous standard Data Envelopment Analysis (DEA) model.

A quest for helpful feedback to programming coursework

The 2011 National Student Survey (NSS) revealed that 40% of full-time students in England do not think that the feedback on their work has been helpful, even though 66% of these students agreed that the feedback was detailed and 62% of them agreed that the feedback has been prompt. Detailed feedback that is not considered helpful by students means a waste of tutors' time while students continue to struggle with their learning. What do students consider as helpful feedback? What are the qualities of helpful feedback? What are the preferred forms of feedback? How should tutors write feedback so that students will find it helpful? Can ICT help to improve the quality of feedback? In our ongoing search for answers to the above questions, we have trialled the use of a novel online application (eCAF) to assess programming coursework from engineering, mathematics and computing students and, through a survey, have collected their views on the feedback received. The survey reveals that most students prefer electronic feedback as given through eCAF, with verbal feedback ranked second and hand-written feedback ranked even lower. The survey also indicates that the feedback from some tutors is considered more helpful than others. We report on the detailed findings of the survey. By comparing the kinds of feedback given by each tutor who took part in the trial, we explore ways to improve the helpfulness of feedback on programming coursework in a bid to promote learning amongst engineering students.

The data type of spatial objects

A spatial object consists of data assigned to points in a space. Spatial objects, such as memory states and three dimensional graphical scenes, are diverse and ubiquitous in computing. We develop a general theory of spatial objects by modelling abstract data types of spatial objects as topological algebras of functions. One useful algebra is that of continuous functions, with operations derived from operations on space and data, and equipped with the compact-open topology. Terms are used as abstract syntax for defining spatial objects and conditional equational specifications are used for reasoning. We pose a completeness problem: Given a selection of operations on spatial objects, do the terms approximate all the spatial objects to arbitrary accuracy? We give some general methods for solving the problem and consider their application to spatial objects with real number attributes. © 2011 British Computer Society.

A Bayesian Spatial Mixture Model for FMRI Analysis

We develop, implement and study a new Bayesian spatial mixture model (BSMM). The proposed BSMM allows for spatial structure in the binary activation indicators through a latent thresholded Gaussian Markov random field. We develop a Gibbs (MCMC) sampler to perform posterior inference on the model parameters, which then allows us to assess the posterior probabilities of activation for each voxel. One purpose of this article is to compare the HJ model and the BSMM in terms of receiver operating characteristics (ROC) curves. Also we consider the accuracy of the spatial mixture model and the BSMM for estimation of the size of the activation region in terms of bias, variance and mean squared error. We perform a simulation study to examine the aforementioned characteristics under a variety of configurations of spatial mixture model and BSMM both as the size of the region changes and as the magnitude of activation changes.

Two-Language, Two-Paradigm Introductory Computing Curriculum Model and its Implementation

This paper analyzes difficulties with the introduction of object-oriented concepts in introductory computing education and then proposes a two-language, two-paradigm curriculum model that alleviates such difficulties. Our two-language, two-paradigm curriculum model begins with teaching imperative programming using Python programming language, continues with teaching object-oriented computing using Java, and concludes with teaching object-oriented data structures with Java.

Integer Programming Approach to HP Folding

One of the most widely studied protein structure prediction models is the hydrophobic-hydrophilic (HP) model, which explains the hydrophobic interaction and tries to maximize the number of contacts among hydrophobic amino-acids. In order to find a lower bound for the number of contacts, a number of heuristics have been proposed, but finding the optimal solution is still a challenge. In this research, we focus on creating a new integer programming model which is capable to provide tractable input for mixed-integer programming solvers, is general enough and allows relaxation with provable good upper bounds. Computational experiments using benchmark problems show that our formulation achieves these goals.

Understanding Computing through Defining its Lexicon

Бойко Банчев - Понятието пресмятане в широкия му смисъл и неговото присъствие в природата, науката, технологията и други области е свързано с редица неизяснени въпроси. Дори в по-тесните рамки на програмирането и използването на компютри то не е адекватно разбрано. Представяме тезата, че един начин за приближаване към такова разбиране е разкриването на дълбинните структури и отношения, свързани с пресмятането, и на тази основа построяване на речник на пресмятането.

A Language for Compositional Programming: A Rationale and Design

Бойко Бл. Банчев - Представена е обосновка и описание на език за програмиране в композиционен стил за опитни и учебни цели. Под “композиционен” имаме предвид функционален стил на програмиране, при който пресмятането е йерархия от композиции и прилагания на функции. Един от данновите типове на езика е този на геометричните фигури, които могат да бъдат получавани чрез прости правила за съотнасяне и така също образуват йерархични композиции. Езикът е силно повлиян от GeomLab, но по редица свойства се различава от него значително. Статията разглежда основните черти на езика; подробното му описание и фигурноконструктивните му възможности ще бъдат представени в съпътстваща публикация.

A Mixed Integer Quadratic Programming Model for the Low Autocorrelation Binary Sequence Problem

In this paper the low autocorrelation binary sequence problem (LABSP) is modeled as a mixed integer quadratic programming (MIQP) problem and proof of the model’s validity is given. Since the MIQP model is semidefinite, general optimization solvers can be used, and converge in a finite number of iterations. The experimental results show that IQP solvers, based on this MIQP formulation, are capable of optimally solving general/skew-symmetric LABSP instances of up to 30/51 elements in a moderate time. ACM Computing Classification System (1998): G.1.6, I.2.8.

Programming and Testing a Two-Tree Algorithm

ACM Computing Classification System (1998): G.2.2, F.2.2.