Collaborative eLearning Assistant Network: caring agents are conscious agents

Would a research assistant - who can search for ideas related to those you are working on, network with others (but only share the things you have chosen to share), doesn’t need coffee and who might even, one day, appear to be conscious - help you get your work done? Would it help your students learn? There is a body of work showing that digital learning assistants can be a benefit to learners. It has been suggested that adaptive, caring, agents are more beneficial. Would a conscious agent be more caring, more adaptive, and better able to deal with changes in its learning partner’s life? Allow the system to try to dynamically model the user, so that it can make predictions about what is needed next, and how effective a particular intervention will be. Now, given that the system is essentially doing the same things as the user, why don’t we design the system so that it can try to model itself in the same way? This should mimic a primitive self-awareness. People develop their personalities, their identities, through interacting with others. It takes years for a human to develop a full sense of self. Nobody should expect a prototypical conscious computer system to be able to develop any faster than that. How can we provide a computer system with enough social contact to enable it to learn about itself and others? We can make it part of a network. Not just chatting with other computers about computer ‘stuff’, but involved in real human activity. Exposed to ‘raw meaning’ – the developing folksonomies coming out of the learning activities of humans, whether they are traditional students or lifelong learners (a term which should encompass everyone). Humans have complex psyches, comprised of multiple strands of identity which reflect as different roles in the communities of which they are part – so why not design our system the same way? With multiple internal modes of operation, each capable of being reflected onto the outside world in the form of roles – as a mentor, a research assistant, maybe even as a friend. But in order to be able to work with a human for long enough to be able to have a chance of developing the sort of rich behaviours we associate with people, the system needs to be able to function in a practical and helpful role. Unfortunately, it is unlikely to get a free ride from many people (other than its developer!) – so it needs to be able to perform a useful role, and do so securely, respecting the privacy of its partner. Can we create a system which learns to be more human whilst helping people learn?

Evaluation of forest snow processes models (SnowMIP2)

Thirty‐three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to two winter snow seasons. Modeled estimates of snow water equivalent (SWE) or depth were compared to observations at forest and open sites at each location. Precipitation phase and duration of above‐freezing air temperatures are shown to be major influences on divergence and convergence of modeled estimates of the subcanopy snowpack. When models are considered collectively at all locations, comparisons with observations show that it is harder to model SWE at forested sites than open sites. There is no universal “best” model for all sites or locations, but comparison of the consistency of individual model performances relative to one another at different sites shows that there is less consistency at forest sites than open sites, and even less consistency between forest and open sites in the same year. A good performance by a model at a forest site is therefore unlikely to mean a good model performance by the same model at an open site (and vice versa). Calibration of models at forest sites provides lower errors than uncalibrated models at three out of four locations. However, benefits of calibration do not translate to subsequent years, and benefits gained by models calibrated for forest snow processes are not translated to open conditions.

In vitro fermentation of carbohydrates by porcine faecal inocula and their influence on Salmonella Typhimurium growth in batch culture systems

The aim of this study was to evaluate in vitro the influence of fermentable carbohydrates on the activity of porcine microbiota and survival of Salmonella Typhimurium in a batch culture system simulating the porcine hindgut. The carbohydrates tested were xylooligosaccharides, a mixture of fructooligosaccharides/inulin (FIN), fructooligosaccharides (FOS), gentiooligosaccharides (GEO) and lactulose (LAC). These ingredients stimulated the growth of selected Bifidobacterium and Lactobacillus species in pure cultures. In batch cultures, the carbohydrates influenced some fermentation parameters. For example, GEO and FIN significantly increased lactic acids compared with the control (no added carbohydrate). With the exception of LAC, the test carbohydrates increased the production of short-chain fatty acid (SCFA) and modified SCFA profiles. Quantitative analysis of bacterial populations by FISH revealed increased counts of the Bifidobacterium group compared with control and, with exception of FOS, increased Lactobacillus, Leuconostoc and Weissella spp. counts. Salmonella numbers were the lowest during the fermentation of LAC. This work has looked at carbohydrate metabolism by porcine microbiota in a pH-controlled batch fermentation system. It provides an initial model to analyse interactions with pathogens.

High pressure induced water uptake characteristics of Thai glutinous rice

Glutinous rice (or sticky rice) has to be soaked in water over an extended period of time before cooking. Soaking provides some of the water needed for starch gelatinisation to occur during cooking. The extent of water uptake during soaking is known to be influenced by temperature. This paper explores the use of very high pressures up to 600 MPa to accelerate water uptake kinetics during soaking. Changes occurring in length, diameter and moisture content were determined as a function of soaking time, pressure and temperature. The results show that length and diameter are positively correlated with all three parameters. However, the expansion ratios are not very high: the maximum length expansion ratio observed was 1.2, while the maximum diameter expansion ratio was 1. 1. Given these low values, it was possible to model water uptake kinetics by using the well-known Fickian model applied to a finite cylinder, assuming uniform average dimensions and effective diffusion coefficient. The results showed that the overall rates of water uptake and the equilibrium moisture content increased with pressure and temperature. The effective diffusion coefficient, on the other hand, did not follow the same trend. Temperature influenced the effective diffusion coefficient below 300 MPa, but had a marginal effect at higher pressures. Moreover, the effective diffusion coefficient increased with temperature between 20 and 50 degrees C, but dropped at higher temperatures. This drop can be attributed to the gelatinisation of starch, which restricts the transport of water. Regardless, it is possible to increase the quantity of water absorbed by rice and the rate at which it is absorbed, by using high pressures and temperatures. (c) 2004 Elsevier Ltd. All rights reserved.

Identification and characterisation of five novel miniature inverted-repeat transposable elements (MITEs) in amphioxus (Branchiostoma floridae)

As the sister group to vertebrates, amphioxus is consistently used as a model of genome evolution for understanding the invertebrate/vertebrate transition. The amphioxus genome has not undergone massive duplications like those in the vertebrates or disruptive rearrangements like in the genome of Ciona, a urochordate, making it an ideal evolutionary model. Transposable elements have been linked to many genomic evolutionary changes including increased genome size, modified gene expression, massive gene rearrangements, and possibly intron evolution. Despite their importance in genome evolution, few previous examples of transposable elements have been identified in amphioxus. We report five novel Miniature Inverted-repeat Transposable Elements (MITEs) identified by an analysis of amphioxus DNA sequence, which we have named LanceleTn-1, LanceleTn-2, LanceleTn-3a, LanceleTn-3b and LanceleTn-4. Several of the LanceleTn elements were identified in the amphioxus ParaHox cluster, and we suggest these have had important implications for the evolution of this highly conserved gene cluster. The estimated high copy numbers of these elements implies that MITEs are probably the most abundant type of mobile element in amphioxus, and are thus likely to have been of fundamental importance in shaping the evolution of the amphioxus genome.

Exploring homeless people’s use of outreach services: applying a social psychological perspective

A number of critiques have been published drawing attention to the gaps in research methods applied to issues surrounding homelessness and service utilisation in Britain. This paper discusses the use of social identity, a theory drawn from the field of applied social psychology, and synthesises it with the pathways model, thereby providing a framework to further explore service utilisation. The synthesised framework was used to predict the uptake of outreach services in a prospective study of 121 homeless people in a major UK city. In general, homeless people's use of intervention services was affected by the extent to which they identified with the support services themselves. The study demonstrates the central role of social identity in understanding service utilisation patterns, and shows the importance of applying fresh techniques to fine-tune our understanding of uptake in the long term.

Testing for significance of phase synchronisation dynamics in the EEG

A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.

A nonlinear oscillator describing storm track variability

We construct a two-variable model which describes the interaction between local baroclinicity and eddy heat flux in order to understand aspects of the variance in storm tracks. It is a heuristic model for diabatically forced baroclinic instability close to baroclinic neutrality. The two-variable model has the structure of a nonlinear oscillator. It exhibits some realistic properties of observed storm track variability, most notably the intermittent nature of eddy activity. This suggests that apparent threshold behaviour can be more accurately and succinctly described by a simple nonlinearity. An analogy is drawn with triggering of convective events.

Molecular insights of p47phox phosphorylation dynamics in the regulation of NADPH oxidase activation and superoxide production

Phagocyte superoxide production by a multicomponent NADPH oxidase is important in host defense against microbial invasion. However inappropriate NADPH oxidase activation causes inflammation. Endothelial cells express NADPH oxidase and endothelial oxidative stress due to prolonged NADPH oxidase activation predisposes many diseases. Discovering the mechanism of NADPH oxidase activation is essential for developing novel treatment of these diseases. The p47phox is a key regulatory subunit of NADPH oxidase; however, due to the lack of full protein structural information, the mechanistic insight of p47phox phosphorylation in NADPH oxidase activation remains incomplete. Based on crystal structures of three functional domains, we generated a computational structural model of the full p47phox protein. Using a combination of in silico phosphorylation, molecular dynamics simulation and protein/protein docking, we discovered that the C-terminal tail of p47phox is critical for stabilizing its autoinhibited structure. Ser-379 phosphorylation disrupts H-bonds that link the C-terminal tail to the autoinhibitory region (AIR) and the tandem Src homology 3 (SH3) domains, allowing the AIR to undergo phosphorylation to expose the SH3 pocket for p22phox binding. These findings were confirmed by site-directed mutagenesis and gene transfection of p47phox_/_ coronary microvascular cells. Compared with wild-type p47phoxcDNAtransfected cells, the single mutation of S379A completely blocked p47phox membrane translocation, binding to p22phox and endothelial O2 . production in response to acute stimulation of PKC. p47phox C-terminal tail plays a key role in stabilizing intramolecular interactions at rest. Ser-379 phosphorylation is a molecular switch which initiates p47phox conformational changes and NADPH oxidase-dependent superoxide production by cells.

Sparse space-time boundary element methods for the heat equation

The goal of this work is the efficient solution of the heat equation with Dirichlet or Neumann boundary conditions using the Boundary Elements Method (BEM). Efficiently solving the heat equation is useful, as it is a simple model problem for other types of parabolic problems. In complicated spatial domains as often found in engineering, BEM can be beneficial since only the boundary of the domain has to be discretised. This makes BEM easier than domain methods such as finite elements and finite differences, conventionally combined with time-stepping schemes to solve this problem. The contribution of this work is to further decrease the complexity of solving the heat equation, leading both to speed gains (in CPU time) as well as requiring smaller amounts of memory to solve the same problem. To do this we will combine the complexity gains of boundary reduction by integral equation formulations with a discretisation using wavelet bases. This reduces the total work to O(h

An LDA and probability-based classifier for the diagnosis of Alzheimer's Disease from structural MRI

In this paper a custom classification algorithm based on linear discriminant analysis and probability-based weights is implemented and applied to the hippocampus measurements of structural magnetic resonance images from healthy subjects and Alzheimer’s Disease sufferers; and then attempts to diagnose them as accurately as possible. The classifier works by classifying each measurement of a hippocampal volume as healthy controlsized or Alzheimer’s Disease-sized, these new features are then weighted and used to classify the subject as a healthy control or suffering from Alzheimer’s Disease. The preliminary results obtained reach an accuracy of 85.8% and this is a similar accuracy to state-of-the-art methods such as a Naive Bayes classifier and a Support Vector Machine. An advantage of the method proposed in this paper over the aforementioned state of the art classifiers is the descriptive ability of the classifications it produces. The descriptive model can be of great help to aid a doctor in the diagnosis of Alzheimer’s Disease, or even further the understand of how Alzheimer’s Disease affects the hippocampus.

Is behavioral ecology important for understanding and predicting population dynamics?

Population ecology is a discipline that studies changes in the number and composition (age, sex) of the individuals that form a population. Many of the mechanisms that generate these changes are associated with individual behavior, for example how individuals defend their territories, find mates or disperse. Therefore, it is important to model population dynamics considering the potential influence of behavior on the modeled dynamics. This study illustrates the diversity of behaviors that influence population dynamics describing several methods that allow integrating behavior into population models and range from simpler models that only consider the number of individuals to complex individual-based models that capture great levels of detail. A series of examples shows the importance of explicitly considering behavior in population modeling to avoid reaching erroneous conclusions. This integration is particularly relevant for conservation, as incorrect predictions regarding the dynamics of populations of conservation interest can lead to inadequate assessment and management. Improved predictions can favor effective protection of species and better use of the limited financial and human conservation resources.

Internalization theory: an unfinished agenda

Internalization theory is usually applied at the firm level to analyse FDI, licensing and subcontracting, but this paper extends it to the industry level. It synthesises internalisation theory and oligopoly theory. It analyses a global industry where firms innovate competitively, and freely enter and exit the industry. It presents a formal model which highlights the inter-dependencies between rival firms. Each firm responds to its rivals by jointly optimising production and innovation through inter-dependent ownership and location decisions. The competitive outcome determines which firms serve which markets, which firms enter or exit the industry, and the internalisation strategy of each firm.