Ethical issues and pervasive computing

There is a growing concern both publicly and professionally surrounding the implementation of Information and Communication Technologies (ICT) and their social and ethical impact. As these technologies become increasingly pervasive and less visible to the user, there is a greater need for professionals to address the concerns in order to regain public trust and maximise the benefits that these technologies can bring. This chapter explores the ethical aspects of the world of pervasive computing and shows the need for an ethical perspective when considering the design and implementation of complex, integrated, multiple systems. We present the background to ethics and technology to give the foundation for our discussion, and refer to current research and ethical principles to provide the argument for ethical consideration. Finally, codes of professional conduct provide the standards, and endorsement, for professional responsibility

ETUDES EN CRISTALLOGRAPHIE DES PROTEINES

Dans les chapitres suivants je présenterai mes travaux dans le domaine de la biologie structurale, qui ont porté, dans un ordre chronologique, sur la neuraminidase du virus de la grippe, le récepteur FcRn du rat, la myrosinase, la protéine P du virus de Sendai et le domaine récepteur de la fibre d’adénovirus. Deux projets n’ont pas pu être achevés à ce jour, et ne seront pas abordés : la base du penton, une protéine de la capside de l’adénovirus, et la protéase du virus Epstein-Barr, une protéine impliquée dans la formation de la capside virale dont la structure est en train d'être résolue.J’ai regroupé ces sujets, et aussi le travail d’installation d’une ligne de lumière à l’ESRF dédiée à la cristallographie des protéines, en trois grands thèmes : méthodes, glycosidases et interactions protéine-protéine

Towards Collaborative Conceptual Exploration

In domains with high knowledge distribution a natural objective is to create principle foundations for collaborative interactive learning environments. We present a first mathematical characterization of a collaborative learning group, a consortium, based on closure systems of attribute sets and the well-known attribute exploration algorithm from formal concept analysis. To this end, we introduce (weak) local experts for subdomains of a given knowledge domain. These entities are able to refute and potentially accept a given (implicational) query for some closure system that is a restriction of the whole domain. On this we build up a consortial expert and show first insights about the ability of such an expert to answer queries. Furthermore, we depict techniques on how to cope with falsely accepted implications and on combining counterexamples. Using notions from combinatorial design theory we further expand those insights as far as providing first results on the decidability problem if a given consortium is able to explore some target domain. Applications in conceptual knowledge acquisition as well as in collaborative interactive ontology learning are at hand.Comment: 15 pages, 2 figure

Algebraic transformation of unary partial algebras II: Single-pushout approach

AbstractThe single-pushout approach to graph transformation is extended to the algebraic transformation of partial many-sorted unary algebras. Such a generalization has been motivated by the need to model the transformation of structures which are richer and more complex than graphs and hypergraphs.The main result presented in this article is an algebraic characterization of the single-pushout transformation in the categories of all conformisms, all closed quomorphisms, and all closed-domain closed quomorphisms of unary partial algebras over a given signature, together with a corresponding operational characterization that may serve as a basis for implementation.Moreover, all three categories are shown to satisfy all of the HLR (high-level replacement) conditions for parallelism, taking as occurrences the total morphisms in each category. Another important result presented in this article is the definition of HLR conditions for amalgamation, which are also satisfied by the categories of partial homomorphisms considered here, taking again the corresponding total morphisms as occurrences

Effects of interaction on an adiabatic quantum electron pump

We study the effects of inter-electron interactions on the charge pumped through an adiabatic quantum electron pump. The pumping is through a system of barriers, whose heights are deformed adiabatically. (Weak) interaction effects are introduced through a renormalisation group flow of the scattering matrices and the pumped charge is shown to {\it always} approach a quantised value at low temperatures or long length scales. The maximum value of the pumped charge is set by the number of barriers and is given by $Q_{\rm max} = n_b -1$. The correlation between the transmission and the charge pumped is studied by seeing how much of the transmission is enclosed by the pumping contour. The (integer) value of the pumped charge at low temperatures is determined by the number of transmission maxima enclosed by the pumping contour. The dissipation at finite temperatures leading to the non-quantised values of the pumped charge scales as a power law with the temperature ($Q-Q_{\rm int} \propto T^{2\alpha}$), or with the system size ($Q-Q_{\rm int} \propto L_s^{-2\alpha}$), where $\alpha$ is a measure of the interactions and vanishes at $T=0 ~(L_s=\infty)$. For a double barrier system, our result agrees with the quantisation of pumped charge seen in Luttinger liquids.Comment: 9 pages, 9 figures, better quality figures available on request from author

Burn wound classification model using spatial frequency-domain imaging and machine learning.

Accurate assessment of burn severity is critical for wound care and the course of treatment. Delays in classification translate to delays in burn management, increasing the risk of scarring and infection. To this end, numerous imaging techniques have been used to examine tissue properties to infer burn severity. Spatial frequency-domain imaging (SFDI) has also been used to characterize burns based on the relationships between histologic observations and changes in tissue properties. Recently, machine learning has been used to classify burns by combining optical features from multispectral or hyperspectral imaging. Rather than employ models of light propagation to deduce tissue optical properties, we investigated the feasibility of using SFDI reflectance data at multiple spatial frequencies, with a support vector machine (SVM) classifier, to predict severity in a porcine model of graded burns. Calibrated reflectance images were collected using SFDI at eight wavelengths (471 to 851 nm) and five spatial frequencies (0 to 0.2  mm  -  1). Three models were built from subsets of this initial dataset. The first subset included data taken at all wavelengths with the planar (0  mm  -  1) spatial frequency, the second comprised data at all wavelengths and spatial frequencies, and the third used all collected data at values relative to unburned tissue. These data subsets were used to train and test cubic SVM models, and compared against burn status 28 days after injury. Model accuracy was established through leave-one-out cross-validation testing. The model based on images obtained at all wavelengths and spatial frequencies predicted burn severity at 24 h with 92.5% accuracy. The model composed of all values relative to unburned skin was 94.4% accurate. By comparison, the model that employed only planar illumination was 88.8% accurate. This investigation suggests that the combination of SFDI with machine learning has potential for accurately predicting burn severity

Structure of FcRY, an avian immunoglobulin receptor related to mammalian mannose receptors, and its complex with IgY

Fc receptors transport maternal antibodies across epithelial cell barriers to passively immunize newborns. FcRY, the functional counterpart of mammalian FcRn (a major histocompatibility complex homolog), transfers IgY across the avian yolk sac, and represents a new class of Fc receptor related to the mammalian mannose receptor family. FcRY and FcRn bind immunoglobulins at pH ≤6.5, but not pH ≥7, allowing receptor–ligand association inside intracellular vesicles and release at the pH of blood. We obtained structures of monomeric and dimeric FcRY and an FcRY–IgY complex and explored FcRY's pH-dependent binding mechanism using electron cryomicroscopy (cryoEM) and small-angle X-ray scattering. The cryoEM structure of FcRY at pH 6 revealed a compact double-ring “head,” in which the N-terminal cysteine-rich and fibronectin II domains were folded back to contact C-type lectin-like domains 1–6, and a “tail” comprising C-type lectin-like domains 7–8. Conformational changes at pH 8 created a more elongated structure that cannot bind IgY. CryoEM reconstruction of FcRY dimers at pH 6 and small-angle X-ray scattering analysis at both pH values confirmed both structures. The cryoEM structure of the FcRY–IgY revealed symmetric binding of two FcRY heads to the dimeric FcY, each head contacting the CH4 domain of one FcY chain. FcRY shares structural properties with mannose receptor family members, including a head and tail domain organization, multimerization that may regulate ligand binding, and pH-dependent conformational changes. Our results facilitate understanding of immune recognition by the structurally related mannose receptor family and comparison of diverse methods of Ig transport across evolution

Billiard Systems in Three Dimensions: The Boundary Integral Equation and the Trace Formula

We derive semiclassical contributions of periodic orbits from a boundary integral equation for three-dimensional billiard systems. We use an iterative method that keeps track of the composition of the stability matrix and the Maslov index as an orbit is traversed. Results are given for isolated periodic orbits and rotationally invariant families of periodic orbits in axially symmetric billiard systems. A practical method for determining the stability matrix and the Maslov index is described.Comment: LaTeX, 19 page

Get it together! Synergistic effects of causal and effectual decision-making logics on venture performance

Entrepreneurs rely on different decision-making logics when starting new ventures, including causal and effectual reasoning. Extant research suggests that venture performance is positively associated with both causal business planning and effectual action-orientation, but studies have not yet tested the synergistic potential of these two logics. We contribute to the debate on entrepreneurial decision making by exploring the interrelationship between causation and effectuation, detailing their main and interactive effects on venture performance. Using survey data collected on 1,453 entrepreneurs residing in 25 countries, we find that ventures benefit from using these two entrepreneurial logics in tandem