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.

Reproducible computing with Tzar and Docker

The potential for sharing environmental data and models is huge, but can be challenging for experts without specific programming expertise. We built an open-source, cross-platform framework (‘Tzar’) to run models across distributed machines. Tzar is simple to set up and use, allows dynamic parameter generation and enhances reproducibility by accessing versioned data and code. Combining Tzar with Docker helps us lower the entry barrier further by versioning and bundling all required modules and dependencies, together with the database needed to schedule work.

Multi-threaded parallel numerical modelling of femtosecond pulse propagation in laser machining

Femtosecond laser microfabrication has emerged over the last decade as a 3D flexible technology in photonics. Numerical simulations provide an important insight into spatial and temporal beam and pulse shaping during the course of extremely intricate nonlinear propagation (see e.g. [1,2]). Electromagnetics of such propagation is typically described in the form of the generalized Non-Linear Schrdinger Equation (NLSE) coupled with Drude model for plasma [3]. In this paper we consider a multi-threaded parallel numerical solution for a specific model which describes femtosecond laser pulse propagation in transparent media [4, 5]. However our approach can be extended to similar models. The numerical code is implemented in NVIDIA Graphics Processing Unit (GPU) which provides an effitient hardware platform for multi-threded computing. We compare the performance of the described below parallel code implementated for GPU using CUDA programming interface [3] with a serial CPU version used in our previous papers [4,5]. © 2011 IEEE.