945 resultados para Imagerie de diffusion


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In this paper, we investigate the possibility to control a mobile robot via a sensory-motory coupling utilizing diffusion system. For this purpose, we implemented a simulation of the diffusion process of chemicals and the kinematics of the mobile robot. In comparison to the original Braitenberg vehicle in which sensorymotor coupling is tightly realised by hardwiring, our system employs the soft coupling. The mobile robot has two sets of independent sensory-motor unit, two sensors are implemented in front and two motors on each side of the robot. The framework used for the sensory-motor coupling was such that 1) Place two electrodes in the medium 2) Drop a certain amount of Chemical U and V related to the distance to the walls and the intensity of the light 3) Place other two electrodes in the medium 4) Measure the concentration of Chemical U and V to actuate the motors on both sides of the robot. The environment was constructed with four surrounding walls and a light source located at the center. Depending on the design parameters and initial conditions, the robot was able to successfully avoid the wall and light. More interestingly, the diffusion process in the sensory-motor coupling provided the robot with a simple form of memory which would not have been possible with a control framework based on a hard-wired electric circuit.

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The classic vertical advection-diffusion (VAD) balance is a central concept in studying the ocean heat budget, in particular in simple climate models (SCMs). Here we present a new framework to calibrate the parameters of the VAD equation to the vertical ocean heat balance of two fully-coupled climate models that is traceable to the models’ circulation as well as to vertical mixing and diffusion processes. Based on temperature diagnostics, we derive an effective vertical velocity w∗ and turbulent diffusivity k∗ for each individual physical process. In steady-state, we find that the residual vertical velocity and diffusivity change sign in mid-depth, highlighting the different regional contributions of isopycnal and diapycnal diffusion in balancing the models’ residual advection and vertical mixing. We quantify the impacts of the time-evolution of the effective quantities under a transient 1%CO2 simulation and make the link to the parameters of currently employed SCMs.

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The increasing use of nanoparticles in the pharmaceutical industry is generating concomitant interest in developing nanomaterials that can rapidly penetrate into, and permeate through, biological membranes to facilitate drug delivery and improve the bioavailability of active pharmaceutical ingredients. Here, we demonstrate that the permeation of thiolated silica nanoparticles through porcine gastric mucosa can be significantly enhanced by their functionalization with either 5 kDa poly(2-ethyl-2-oxazoline) or poly(ethylene glycol). Nanoparticle diffusion was assessed using two independent techniques; Nanoparticle Tracking Analysis, and fluorescence microscopy. Our results show that poly(2-ethyl-2-oxazoline) and poly(ethylene glycol) have comparable abilities to enhance diffusion of silica nanoparticles in mucin dispersions and through the gastric mucosa. These findings provide a new strategy in the design of nanomedicines, by surface modification or nanoparticle core construction, for enhanced transmucosal drug delivery.

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In this study, we review the literature on the creation and diffusion of innovation in the private sectors (industry and services) in developing countries. In particular, we collect evidence on what are the barriers to innovation creation and diffusion and the channels of innovation diffusion to and within developing countries. We find that innovation in developing countries is about creation or adoption of new ideas and technologies; but the capacity for innovation is embedded in and constituted by dynamics between geographical, socio-economic, political and legal subsystems. We contextualize the findings from the review in the current theoretical framework of diffusion of innovations, and we emphasize how the institutional context typical of developing countries impacts the diffusion itself.

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This chapter seeks to add to the study of innovation diffusion as enacted within the UK construction sector. Whereas using relevant theoretical frames as touch points, the chapter maps out challenges associated with understanding innovation diffusion within the UK construction sector. Central to the argument developed here is just how diverse the UK construction sector is, resulting in the need to focus upon a specific constituent perspective within the sector. It is argued that constituents of the UK construction sector experience the reality of innovation diffusion differently. The chosen focus here is medium-size and typically regionally based construction firms rather than the big guns, because statistics continually demonstrate that this group of smaller firms undertake more than 80% of the sector’s output. As is pointed out in other chapters in the present volume, and as argued theoretically in the industrial network perspective of chapter 7, firms do not innovate in a vacuum. Innovation and diffusion occur within networks of firms typically around a project. A framework drawing upon empirical data is provided to additional insight on the process and the interconnections. It is argued here that the unit of analysis or level of understanding termed the firm can actually be fairly unhelpful for understanding innovation and its manifestation and diffusion within the broader UK construction sector, because this occurs across networks of firms.

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The UK government is mandating the use of building information modelling (BIM) in large public projects by 2016. As a result, engineering firms are faced with challenges related to embedding new technologies and associated working practices for the digital delivery of major infrastructure projects. Diffusion of innovations theory is used to investigate how digital innovations diffuse across complex firms. A contextualist approach is employed through an in-depth case study of a large, international engineering project-based firm. The analysis of the empirical data, which was collected over a four-year period of close interaction with the firm, reveals parallel paths of diffusion occurring across the firm, where both the innovation and the firm context were continually changing. The diffusion process is traced over three phases: centralization of technology management, standardization of digital working practices, and globalization of digital resources. The findings describe the diffusion of a digital innovation as multiple and partial within a complex social system during times of change and organizational uncertainty, thereby contributing to diffusion of innovations studies in construction by showing a range of activities and dynamics of a non-linear diffusion process.

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Little research so far has been devoted to understanding the diffusion of grassroots innovation for sustainability across space. This paper explores and compares the spatial diffusion of two networks of grassroots innovations, the Transition Towns Network (TTN) and Gruppi di Acquisto Solidale (Solidarity Purchasing Groups – GAS), in Great Britain and Italy. Spatio-temporal diffusion data were mined from available datasets, and patterns of diffusion were uncovered through an exploratory data analysis. The analysis shows that GAS and TTN diffusion in Italy and Great Britain is spatially structured, and that the spatial structure has changed over time. TTN has diffused differently in Great Britain and Italy, while GAS and TTN have diffused similarly in central Italy. The uneven diffusion of these grassroots networks on the one hand challenges current narratives on the momentum of grassroots innovations, but on the other highlights important issues in the geography of grassroots innovations for sustainability, such as cross-movement transfers and collaborations, institutional thickness, and interplay of different proximities in grassroots innovation diffusion.

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The Transition Network exemplifies the potential of social movements to create spaces of possibility for alternatives to emerge in the interstices of mainstream, neoliberal economies. Yet, little work has been carried out so far on the Transition Network or other grassroots innovations for sustainability in a way that reveals their actual patterns of diffusion. This graphic of the diffusion of the Transition Network visualises its spatial structure and compare diffusion patterns across Italy, France, Great Britain and Germany. The graphics show that the number of transition initiatives in the four countries has steadily increased over the past eight years, but the rate of increase has slowed down in all countries. The maps clearly show that in all four countries the diffusion of the Transition Network has not been spatially even. The graphic suggests that in each country transition initiatives are more likely to emerge in some geographical areas (hotspots) than in others (cold spots). While the existence of a spatial structure of the Transition Network may result from the combination of place-specific factors and diffusion mechanisms, these graphics illustrate the importance of better comprehending where grassroots innovations emerge.

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The theory of diffusion in many-dimensional Hamiltonian system is applied to asteroidal dynamics. The general formulation developed by Chirikov is applied to the NesvornA1/2-Morbidelli analytic model of three-body (three-orbit) mean-motion resonances (Jupiter-Saturn-asteroid). In particular, we investigate the diffusion along and across the separatrices of the (5, -2, -2) resonance of the (490) Veritas asteroidal family and their relationship to diffusion in semi-major axis and eccentricity. The estimations of diffusion were obtained using the Melnikov integral, a Hadjidemetriou-type sympletic map and numerical integrations for times up to 10(8) years.

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The diffusion of astrophysical magnetic fields in conducting fluids in the presence of turbulence depends on whether magnetic fields can change their topology via reconnection in highly conducting media. Recent progress in understanding fast magnetic reconnection in the presence of turbulence reassures that the magnetic field behavior in computer simulations and turbulent astrophysical environments is similar, as far as magnetic reconnection is concerned. This makes it meaningful to perform MHD simulations of turbulent flows in order to understand the diffusion of magnetic field in astrophysical environments. Our studies of magnetic field diffusion in turbulent medium reveal interesting new phenomena. First of all, our three-dimensional MHD simulations initiated with anti-correlating magnetic field and gaseous density exhibit at later times a de-correlation of the magnetic field and density, which corresponds well to the observations of the interstellar media. While earlier studies stressed the role of either ambipolar diffusion or time-dependent turbulent fluctuations for de-correlating magnetic field and density, we get the effect of permanent de-correlation with one fluid code, i.e., without invoking ambipolar diffusion. In addition, in the presence of gravity and turbulence, our three-dimensional simulations show the decrease of the magnetic flux-to-mass ratio as the gaseous density at the center of the gravitational potential increases. We observe this effect both in the situations when we start with equilibrium distributions of gas and magnetic field and when we follow the evolution of collapsing dynamically unstable configurations. Thus, the process of turbulent magnetic field removal should be applicable both to quasi-static subcritical molecular clouds and cores and violently collapsing supercritical entities. The increase of the gravitational potential as well as the magnetization of the gas increases the segregation of the mass and magnetic flux in the saturated final state of the simulations, supporting the notion that the reconnection-enabled diffusivity relaxes the magnetic field + gas system in the gravitational field to its minimal energy state. This effect is expected to play an important role in star formation, from its initial stages of concentrating interstellar gas to the final stages of the accretion to the forming protostar. In addition, we benchmark our codes by studying the heat transfer in magnetized compressible fluids and confirm the high rates of turbulent advection of heat obtained in an earlier study.

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A particle filter method is presented for the discrete-time filtering problem with nonlinear ItA ` stochastic ordinary differential equations (SODE) with additive noise supposed to be analytically integrable as a function of the underlying vector-Wiener process and time. The Diffusion Kernel Filter is arrived at by a parametrization of small noise-driven state fluctuations within branches of prediction and a local use of this parametrization in the Bootstrap Filter. The method applies for small noise and short prediction steps. With explicit numerical integrators, the operations count in the Diffusion Kernel Filter is shown to be smaller than in the Bootstrap Filter whenever the initial state for the prediction step has sufficiently few moments. The established parametrization is a dual-formula for the analysis of sensitivity to gaussian-initial perturbations and the analysis of sensitivity to noise-perturbations, in deterministic models, showing in particular how the stability of a deterministic dynamics is modeled by noise on short times and how the diffusion matrix of an SODE should be modeled (i.e. defined) for a gaussian-initial deterministic problem to be cast into an SODE problem. From it, a novel definition of prediction may be proposed that coincides with the deterministic path within the branch of prediction whose information entropy at the end of the prediction step is closest to the average information entropy over all branches. Tests are made with the Lorenz-63 equations, showing good results both for the filter and the definition of prediction.

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The correlation between the microdilution (MD), Etest (R) (ET), and disk diffusion (DD) methods was determined for amphotericin B, itraconazole and fluconazole. The minimal inhibitory concentration (MIC) of those antifungal agents was established for a total of 70 Candida spp. isolates from colonization and infection. The species distribution was: Candida albicans (n = 27), C. tropicalis (n = 17), C. glabrata (n = 16), C. parapsilosis (n = 8), and C. lusitaniae (n = 2). Non-Candida albicans Candida species showed higher MICs for the three antifungal agents when compared with C. albicans isolates. The overall concordance (based on the MIC value obtained within two dilutions) between the ET and the MD method was 83% for amphotericin B, 63% for itraconazole, and 64% for fluconazole. Considering the breakpoint, the agreement between the DD and MD methods was 71% for itraconazole and 67% for fluconazole. The DD zone diameters are highly reproducible and correlate well with the MD method, making agar-based methods a viable alternative to MD for susceptibility testing. However, data on agar-based tests for itraconazole and amphotericin B are yet scarce. Thus, further research must still be carded out to ensure the standardization to other antifungal agents. J. Clin. Lab. Anal. 23:324-330, 2009. (C) 2009 Wiley-Liss, Inc.