185 research outputs found

    Bacteria Hunt: A multimodal, multiparadigm BCI game

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    Brain-Computer Interfaces (BCIs) allow users to control applications by brain activity. Among their possible applications for non-disabled people, games are promising candidates. BCIs can enrich game play by the mental and affective state information they contain. During the eNTERFACE’09 workshop we developed the Bacteria Hunt game which can be played by keyboard and BCI, using SSVEP and relative alpha power. We conducted experiments in order to investigate what difference positive vs. negative neurofeedback would have on subjects’ relaxation states and how well the different BCI paradigms can be used together. We observed no significant difference in mean alpha band power, thus relaxation, and in user experience between the games applying positive and negative feedback. We also found that alpha power before SSVEP stimulation was significantly higher than alpha power during SSVEP stimulation indicating that there is some interference between the two BCI paradigms

    The role of Comprehension in Requirements and Implications for Use Case Descriptions

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    Within requirements engineering it is generally accepted that in writing specifications (or indeed any requirements phase document), one attempts to produce an artefact which will be simple to comprehend for the user. That is, whether the document is intended for customers to validate requirements, or engineers to understand what the design must deliver, comprehension is an important goal for the author. Indeed, advice on producing ‘readable’ or ‘understandable’ documents is often included in courses on requirements engineering. However, few researchers, particularly within the software engineering domain, have attempted either to define or to understand the nature of comprehension and it’s implications for guidance on the production of quality requirements. Therefore, this paper examines thoroughly the nature of textual comprehension, drawing heavily from research in discourse process, and suggests some implications for requirements (and other) software documentation. In essence, we find that the guidance on writing requirements, often prevalent within software engineering, may be based upon assumptions which are an oversimplification of the nature of comprehension. Hence, the paper examines guidelines which have been proposed, in this case for use case descriptions, and the extent to which they agree with discourse process theory; before suggesting refinements to the guidelines which attempt to utilise lessons learned from our richer understanding of the underlying discourse process theory. For example, we suggest subtly different sets of writing guidelines for the different tasks of requirements, specification and design

    Bayesian graphical models for regression on multiple data sets with different variables

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    Routinely collected administrative data sets, such as national registers, aim to collect information on a limited number of variables for the whole population. In contrast, survey and cohort studies contain more detailed data from a sample of the population. This paper describes Bayesian graphical models for fitting a common regression model to a combination of data sets with different sets of covariates. The methods are applied to a study of low birth weight and air pollution in England and Wales using a combination of register, survey, and small-area aggregate data. We discuss issues such as multiple imputation of confounding variables missing in one data set, survey selection bias, and appropriate propagation of information between model components. From the register data, there appears to be an association between low birth weight and environmental exposure to NO2, but after adjusting for confounding by ethnicity and maternal smoking by combining the register and survey data under our models, we find there is no significant association. However, NO2 was associated with a small but significant reduction in birth weight, modeled as a continuous variable

    Distribution of moisture in reconstructed oil paintings on canvas during absorption and drying: a neutron radiography and NMR study

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    Moisture is a driving factor in the long-term mechanical deterioration of canvas paintings, as well as for a number of physico–chemical degradation processes. Since the 1990s a number of publications have addressed the equilibrium hygroscopic uptake and the hygro-mechanical deformation of linen canvas, oil paint, animal glue, and ground paint. In order to visualise and quantify the dynamic behaviour of these materials combined in a painting mock-up or reconstruction, we have performed custom-designed experiments with neutron radiography and nuclear magnetic resonance (NMR) imaging. This paper reports how both techniques were used to obtain spatially and temporally resolved information on moisture content, during alternate exposure to high and low relative humidity, or in contact with liquids of varying water activities. We observed how the canvas, which is the dominant component in terms of volumetric moisture uptake, absorbs and dries rapidly, and, due to its low vapour resistance, allows for vapour transfer towards the ground layer. Moisture desorption was generally found to be faster than absorption. The presence of sizing glue leads to a local increase of moisture content. It was observed that lining a painting with an extra canvas results in a damping effect: i.e. absorption and drying are significantly slowed down. The results obtained by NMR are complementary to neutron radiography in that they allow accurate monitoring of water ingress in contact with a liquid reservoir. Quantitative results are in good agreement with adsorption isotherms. The findings can be used for risk analysis of paintings exposed to changing micro-climates or subjected to conservation treatments using water. Future studies addressing moisture-driven deformation of paintings can make use of the proposed experimental techniques

    Following wrong suggestions: self-blame in human and computer scenarios

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    This paper investigates the specific experience of following a suggestion by an intelligent machine that has a wrong outcome and the emotions people feel. By adopting a typical task employed in studies on decision-making, we presented participants with two scenarios in which they follow a suggestion and have a wrong outcome by either an expert human being or an intelligent machine. We found a significant decrease in the perceived responsibility on the wrong choice when the machine offers the suggestion. At present, few studies have investigated the negative emotions that could arise from a bad outcome after following the suggestion given by an intelligent system, and how to cope with the potential distrust that could affect the long-term use of the system and the cooperation. This preliminary research has implications in the study of cooperation and decision making with intelligent machines. Further research may address how to offer the suggestion in order to better cope with user's self-blame.Comment: To be published in the Proceedings of IFIP Conference on Human-Computer Interaction (INTERACT)201

    Sensitization of spinal cord nociceptive neurons with a conjugate of substance P and cholera toxin

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    <p>Abstract</p> <p>Background</p> <p>Several investigators have coupled toxins to neuropeptides for the purpose of lesioning specific neurons in the central nervous system. By producing deficits in function these toxin conjugates have yielded valuable information about the role of these cells. In an effort to specifically stimulate cells rather than kill them we have conjugated the neuropeptide substance P to the catalytic subunit of cholera toxin (SP-CTA). This conjugate should be taken up selectively by neurokinin receptor expressing neurons resulting in enhanced adenylate cyclase activity and neuronal firing.</p> <p>Results</p> <p>The conjugate SP-CTA stimulates adenylate cyclase in cultured cells that are transfected with either the NK1 or NK2 receptor, but not the NK3 receptor. We further demonstrate that intrathecal injection of SP-CTA in rats induces the phosphorylation of the transcription factor cyclic AMP response element binding protein (CREB) and also enhances the expression of the immediate early gene c-Fos. Behaviorally, low doses of SP-CTA (1 μg) injected intrathecally produce thermal hyperalgesia. At higher doses (10 μg) peripheral sensitivity is suppressed suggesting that descending inhibitory pathways may be activated by the SP-CTA induced sensitization of spinal cord neurons.</p> <p>Conclusion</p> <p>The finding that stimulation of adenylate cyclase in neurokinin receptor expressing neurons in the spinal cord produces thermal hyperalgesia is consistent with the known actions of these neurons. These data demonstrate that cholera toxin can be targeted to specific cell types by coupling the catalytic subunit to a peptide agonist for a g-protein coupled receptor. Furthermore, these results demonstrate that SP-CTA can be used as a tool to study sensitization of central neurons in vivo in the absence of an injury.</p

    Ambient air pollution exposure and full-term birth weight in California

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    <p>Abstract</p> <p>Background</p> <p>Studies have identified relationships between air pollution and birth weight, but have been inconsistent in identifying individual pollutants inversely associated with birth weight or elucidating susceptibility of the fetus by trimester of exposure. We examined effects of prenatal ambient pollution exposure on average birth weight and risk of low birth weight in full-term births.</p> <p>Methods</p> <p>We estimated average ambient air pollutant concentrations throughout pregnancy in the neighborhoods of women who delivered term singleton live births between 1996 and 2006 in California. We adjusted effect estimates of air pollutants on birth weight for infant characteristics, maternal characteristics, neighborhood socioeconomic factors, and year and season of birth.</p> <p>Results</p> <p>3,545,177 singleton births had monitoring for at least one air pollutant within a 10 km radius of the tract or ZIP Code of the mother's residence. In multivariate models, pollutants were associated with decreased birth weight; -5.4 grams (95% confidence interval -6.8 g, -4.1 g) per ppm carbon monoxide, -9.0 g (-9.6 g, -8.4 g) per pphm nitrogen dioxide, -5.7 g (-6.6 g, -4.9 g) per pphm ozone, -7.7 g (-7.9 g, -6.6 g) per 10 <it>μ</it>g/m<sup>3 </sup>particulate matter under 10 μm, -12.8 g (-14.3 g, -11.3 g) per 10 <it>μ</it>g/m<sup>3 </sup>particulate matter under 2.5 μm, and -9.3 g (-10.7 g, -7.9 g) per 10 <it>μ</it>g/m<sup>3 </sup>of coarse particulate matter. With the exception of carbon monoxide, estimates were largely unchanged after controlling for co-pollutants. Effect estimates for the third trimester largely reflect the results seen from full pregnancy exposure estimates; greater variation in results is seen in effect estimates specific to the first and second trimesters.</p> <p>Conclusions</p> <p>This study indicates that maternal exposure to ambient air pollution results in modestly lower infant birth weight. A small decline in birth weight is unlikely to have clinical relevance for individual infants, and there is debate about whether a small shift in the population distribution of birth weight has broader health implications. However, the ubiquity of air pollution exposures, the responsiveness of pollutant levels to regulation, and the fact that the highest pollution levels in California are lower than those regularly experienced in other countries suggest that precautionary efforts to reduce pollutants may be beneficial for infant health from a population perspective.</p
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