The Use of Supervisory Control in Discovery Matters

The Use of Supervisory Control in Discovery Matter

Forbearance, Endogenous Development, and Aid Work

The international aid industry continues to export paid and unpaid Westerners to undertake development work of questionable and suspect utility to Africa, and to the less-developed countries of other regions. Despite its widespread acceptance in the West and tremendous financial support, this work has been criticized as failing to meaningfully improve the quality of life due to a multitude of systemic challenges within the industry. This range of challenges includes the intrinsic power imbalances found between debtor nations and their creditors; the dominant position of great powers within international organizations and as the funders of international non-governmental organizations; the pathological dysfunction of the developmental bureaucracies; and the state and institutional weakness of developing countries who, despite their inability to create the rule of law, often interpose themselves between the international aid industry and the communities who are the intended beneficiaries of development. It is the regime of international development that inhibits the forbearance necessary to permit an endogenous development which prioritizes the input and direction of the beneficiary communities themselves and would thus encourage the aid industry to formalize self-autonomy and to defend the dignity of the people whose resources the industry has ostensibly mobilized to assist. The structures of the international development regime present an overpowering inertia against reform towards forbearance; however, organizational reform of the aid industry remains the most realistic method of advancing endogenous development

Temporal Evolution of Financial Market Correlations

We investigate financial market correlations using random matrix theory and principal component analysis. We use random matrix theory to demonstrate that correlation matrices of asset price changes contain structure that is incompatible with uncorrelated random price changes. We then identify the principal components of these correlation matrices and demonstrate that a small number of components accounts for a large proportion of the variability of the markets that we consider. We then characterize the time-evolving relationships between the different assets by investigating the correlations between the asset price time series and principal components. Using this approach, we uncover notable changes that occurred in financial markets and identify the assets that were significantly affected by these changes. We show in particular that there was an increase in the strength of the relationships between several different markets following the 2007--2008 credit and liquidity crisis.Comment: 15 pages, 10 figures, 1 table. Accepted for publication in Phys. Rev. E. v2 includes additional section

From evaluation towards an agenda for quality improvement

For many students and lecturers evaluation is confined to some form of survey. Whilst these can provide useful feedback, their focus is likely to reflect the values and norms of those commissioning and undertaking the evaluation. For real improvements in quality to occur both lecturers’ and students’ perspectives of factors that are important need to be made explicit and understood. Drawing upon literature relating to service quality and in particular the Service Template, this article outlines and evaluates an alternative approach for establishing students’ and lecturers’ perspectives, obtaining feedback and developing an agenda for improvement. Using the example of dissertation supervision, it is argued that a revised Template Process operating within a process consultation framework can meet these concerns. The article concludes with a discussion of the applicability of the Template Process to evaluating teaching and learning

Unsupervised discovery of temporal sequences in high-dimensional datasets, with applications to neuroscience.

Identifying low-dimensional features that describe large-scale neural recordings is a major challenge in neuroscience. Repeated temporal patterns (sequences) are thought to be a salient feature of neural dynamics, but are not succinctly captured by traditional dimensionality reduction techniques. Here, we describe a software toolbox-called seqNMF-with new methods for extracting informative, non-redundant, sequences from high-dimensional neural data, testing the significance of these extracted patterns, and assessing the prevalence of sequential structure in data. We test these methods on simulated data under multiple noise conditions, and on several real neural and behavioral datas. In hippocampal data, seqNMF identifies neural sequences that match those calculated manually by reference to behavioral events. In songbird data, seqNMF discovers neural sequences in untutored birds that lack stereotyped songs. Thus, by identifying temporal structure directly from neural data, seqNMF enables dissection of complex neural circuits without relying on temporal references from stimuli or behavioral outputs

First passage time of N excluded volume particles on a line

Motivated by recent single molecule studies of proteins sliding on a DNA molecule, we explore the targeting dynamics of N particles ("proteins") sliding diffusively along a line ("DNA") in search of their target site (specific target sequence). At lower particle densities, one observes an expected reduction of the mean first passage time proportional to 1/N**2, with corrections at higher concentrations. We explicitly take adsorption and desorption effects, to and from the DNA, into account. For this general case, we also consider finite size effects, when the continuum approximation based on the number density of particles, breaks down. Moreover, we address the first passage time problem of a tagged particle diffusing among other particles.Comment: 9 pages, REVTeX, 6 eps figure