Block persistence

We define a block persistence probability $p_l(t)$ as the probability that the order parameter integrated on a block of linear size $l$ has never changed sign since the initial time in a phase ordering process at finite temperature T<T_c. We argue that p_l(t)\sim l^{-z\theta_0}f(t/l^z) in the scaling limit of large blocks, where \theta_0 is the global (magnetization) persistence exponent and f(x) decays with the local (single spin) exponent \theta for large x. This scaling is demonstrated at zero temperature for the diffusion equation and the large n model, and generically it can be used to determine easily \theta_0 from simulations of coarsening models. We also argue that \theta_0 and the scaling function do not depend on temperature, leading to a definition of \theta at finite temperature, whereas the local persistence probability decays exponentially due to thermal fluctuations. We also discuss conserved models for which different scaling are shown to arise depending on the value of the autocorrelation exponent \lambda. We illustrate our discussion by extensive numerical results. We also comment on the relation between this method and an alternative definition of \theta at finite temperature recently introduced by Derrida [Phys. Rev. E 55, 3705 (1997)].Comment: Revtex, 18 pages (multicol.sty), 15 eps figures (uses epsfig), submitted to Eur. Phys. J.

Mapping web personal learning environments

A recent trend in web development is to build platforms which are carefully designed to host a plurality of software components (sometimes called widgets or plugins) which can be organized or combined (mashed-up) at user's convenience to create personalized environments. The same holds true for the web development of educational applications. The degree of personalization can depend on the role of users such as in traditional virtual learning environment, where the components are chosen by a teacher in the context of a course. Or, it can be more opened as in a so-called personalized learning environment (PLE). It now exists a wide array of available web platforms exhibiting different functionalities but all built on the same concept of aggregating components together to support different tasks and scenarios. There is now an overlap between the development of PLE and the more generic developments in web 2.0 applications such as social network sites. This article shows that 6 more or less independent dimensions allow to map the functionalities of these platforms: the screen dimensionmaps the visual integration, the data dimension maps the portability of data, the temporal dimension maps the coupling between participants, the social dimension maps the grouping of users, the activity dimension maps the structuring of end users–interactions with the environment, and the runtime dimensionmaps the flexibility in accessing the system from different end points. Finally these dimensions are used to compare 6 familiar Web platforms which could potentially be used in the construction of a PLE

Graaasp: a web 2.0 research platform for contextual recommendation with aggregated data

In this paper we describe Graaasp, a social software currently under development to support the creation of a real usage database of social artifacts. Our goals are twofold: First to offer a generic aggregation service and user interface to people and communities. Second, to experiment with recommendation and reputation models and algorithms in e-learning

Introducing qualitative dimensions to analyse the usefulness of Web 2.0 platforms as PLEs

The trends in web development of educational applications and of Web 2.0 or social applications are converging. Platforms are designed to host a variety of software components (called widgets or plugins), which can be organised or combined (mashed-up) at user's convenience. Such platforms can be exploited as both personalised learning environment (PLE) and as social network applications. This article argues that six qualitative dimensions can be defined to analyse the main features of these platforms: the screen dimension measures the visual integration, the data dimension measures the portability of data, the temporal dimension measures the rate of data synchronisation, the social dimension measures the networking of users, the activity dimension measures the structuring of users' interactions with the environment, and the runtime dimension measures the flexibility in accessing the environment from different end points. As a proof of concept of the introduced dimensions, a few familiar Web 2.0 platforms are first measured along each dimension and then, using the results visualised as spider diagrams, compared with respect to their usefulness as PLEs

Efficient microplastics extraction from sand. A cost effective methodology based on sodium iodide recycling

International audienceEvaluating the microplastics pollution on the shores requires overcoming the technological and economical challenge of efficient plastic extraction from sand. The recovery of dense microplastics requires the use of NaI solutions, a costly process. The aim of this study is to decrease this cost by recycling the NaI solutions and to determine the impact of NaI storage. For studying the NaI recyclability, the solution density and the salt mass have been monitored during ten life cycles. Density, pH and salt mass have been measured for 40 days to assess the storage effect. The results show that NaI solutions are recyclable without any density alterations with a total loss of 35.9% after the 10 cycles of use. During storage, chemical reactions may appear but are reversible. Consequently, the use of recycling methods allows for a significant cost reduction. How far the plastic extraction by dense solutions is representative is discussed. (C) 2016 Elsevier Ltd. All rights reserved