5,558 research outputs found

    Security and privacy requirements engineering for human centric IoT systems using eFRIEND and Isabelle

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    In this paper, we combine a framework for ethical requirement elicitation eFRIEND with automated reasoning. To provide trustworthy and secure IoT for vulnerable users in healthcare scenarios, we need to apply ethics to arrive at suitable system requirements. In order to map those to technical system requirements, we employ high level logical modeling using dedicated Isabelle frameworks for (1) infrastructures with human actors and security policies, (2) attack tree analysis, and (3) security protocol analysis. Following this outline, we apply these frameworks to a case study for supporting Security and Privacy when diagnosing Alzheimer’s patients with smartphone and sensor technolog

    From Zn to Mn: the study of novel manganese-binding groups in the search for new drugs against tuberculosis.

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    In most eubacteria, apicomplexans, and most plants, including the causal agents for diseases such as malaria, leprosy, and tuberculosis, the methylerythritol phosphate pathway is the route for the biosynthesis of the C(5) precursors to the essential isoprenoid class of compounds. Owing to their absence in humans, the enzymes of the methylerythritol phosphate pathway have become attractive targets for drug discovery. This work investigates a new class of inhibitors against the second enzyme of the pathway, 1-deoxy-D-xylulose 5-phosphate reductoisomerase. Inhibition of this enzyme may involve the chelation of a crucial active site Mn ion, and the metal-chelating moieties studied here have previously been shown to be successful in application to the zinc-dependent metalloproteinases. Quantum mechanics and docking calculations presented in this work suggest the transferability of these metal-chelating compounds to Mn-containing 1-deoxy-D-xylulose 5-phosphate reductoisomerase enzyme, as a promising starting point to the development of potent inhibitors

    A framework for distributed interaction in intelligent environments

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    Ubiquitous computing is extending its applications to an increasing number of domains. "Monolithic" approaches use centralised systems, controlling devices and users' requests. A different solution can be found in works proposing "distributed" intelligent devices that communicate, without a central reasoner, creating little communities to support the user. If the former approach uses all the available sensors being more easily context-aware, the latter is scalable and naturally supports multiple users. In this work we introduce a model for a distributed network of entities in Intelligent Environments. Each node satisfies users' requests through Natural User Interfaces. If a node cannot produce the expected output, it communicates with others in the network, generating paths where the final target is undetermined and intermediate nodes do not understand the request; this is the focus of our work. The system learns parameters and connections in the initial topology. We tested the system in two scenarios. Our approach finds paths close to the optimum with reasonable connections

    Interaction patterns for smart spaces: a confident interaction design solution for pervasive sensitive IoT services

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    Smart spaces represent a powerful tool for deploying the new pervasive sensitive services based on Internet of Things products and developed in current Information Society close to users. Researchers have focused their efforts on new techniques to improve systems and products in this area but neglecting the human factors related to psychological aspects of the user and their psycho-social relationship with the deployment space where they live. This research proposes to take into account these cognitive features in early stages of the design of smart spaces by defining a set of interaction patterns. By using this set of interaction patterns it is possible to influence over the confidence that users can develop during the use of IoT products and services based on them. An evaluative verification has been carried out to assess how this design engineering approach provide a real impact on the generation of confidence in the users of this kind of technology

    Integrability to chaos transition through Krylov approach for state evolution

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    The complexity of quantum evolutions can be understood by examining their dispersion in a chosen basis. Recent research has stressed the fact that the Krylov basis is particularly adept at minimizing this dispersion [V. Balasubramanian et al, Physical Review D 106, 046007 (2022)]. This property assigns a central role to the Krylov basis in the investigation of quantum chaos. Here, we delve into the transition from integrability to chaos using the Krylov approach, employing an Ising spin chain and a banded random matrix model as our testing models. Our findings indicate that both the saturation of Krylov complexity and the dispersion of the Lanczos coefficients can exhibit a significant dependence on the initial condition. However, both quantities can gauge dynamical quantum chaos with a proper choice of the initial state.Comment: 10 pages, 10 figure

    Coupling Accelerated Molecular Dynamics Methods with Thermodynamic Integration Simulations

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    In this work we propose a straightforward and efficient approach to improve accuracy and convergence of free energy simulations in condensed-phase systems. We also introduce a new accelerated Molecular Dynamics (MD) approach in which molecular conformational transitions are accelerated by lowering the energy barriers while the potential surfaces near the minima are left unchanged. All free energy calculations were performed on the propane-to-propane model system. The accuracy of free energy simulations was significantly improved when sampling of internal degrees of freedom of solute was enhanced. However, accurate and converged results were only achieved when the solvent interactions were taken into account in the accelerated MD approaches. The analysis of the distribution of boost potential along the free energy simulations showed that the new accelerated MD approach samples efficiently both low- and high-energy regions of the potential surface. Since this approach also maintains substantial populations in regions near the minima, the statistics are not compromised in the thermodynamic integration calculations, and, as a result, the ensemble average can be recovered

    Oil spill Hazard maps

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    This report contains the description of the methodology to produce coastal oil spill hazard mapping for the Atlantic Ocean coastlines and the description of the Web Portal used to disseminate the informatio
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