Fibre embedding in aluminium alloy 3003 using ultrasonic consolidation process-thermo-mechanical analyses

This work presents a computational framework based on finite element methods to simulate the fibre-embedding process using ultrasonic consolidation process. The computational approach comprises of a material model which takes into account thermal and acoustic softening effects and a friction model which indicates the realistic friction behaviour at the interfaces. The derived material model and developed friction model have been incorporated in finite element model. Using the implemented material and friction model, thermo-mechanical analyses of embedding of fibre in aluminium alloy 3003 has been performed. Effect of different process parameters, such as velocity of sonotrode, displacement amplitude of ultrasonic vibration and applied loads, is studied and compared with the experimental results. The presented work has specially focused on the quality of the developed weld which could be evaluated by the friction work and the coverage of the fibre which is estimated by the plastic flow around the fibre. The computed friction work obtained from the thermomechanial analyses performed in this study show a similar trend as that of the experimentally found fracture energies. © Springer-Verlag London Limited 2010.

Learning Effective and Interpretable Semantic Models using Non-Negative Sparse Embedding

In this paper, we introduce an application of matrix factorization to produce corpus-derived, distributional
models of semantics that demonstrate cognitive plausibility. We find that word representations
learned by Non-Negative Sparse Embedding (NNSE), a variant of matrix factorization, are sparse,
effective, and highly interpretable. To the best of our knowledge, this is the first approach which
yields semantic representation of words satisfying these three desirable properties. Though extensive
experimental evaluations on multiple real-world tasks and datasets, we demonstrate the superiority
of semantic models learned by NNSE over other state-of-the-art baselines.

Microstructure and microtexture evolution of aluminum alloy 3003 under ultrasonic welding process for embedding SiC fibre

Ultrasonic welding process can be used for bonding metal foils which is the fundament of ultrasonic consolidation (UC). UC process can be used to embed reinforcement fibres such as SiC fibres within an aluminum matrix materials. In this research we are investigating the phenomena occurring in the microstructure of the parts during ultrasonic welding process to obtain better understanding about how and why the process works. High-resolution electron backscatter diffraction (EBSD) is used to study the effects of the vibration on the evolution of microstructure in AA3003. The inverse pole figures (IPF) and the correlated misorientation angle distribution of the mentioned samples are obtained. The characteristics of the crystallographic orientation, the grain structure and the grain boundary are analyzed to find the effect of ultrasonic vibration on the microstructure and microtexture of the bond. The ultrasonic vibration will lead to exceptional refinement of grains to a micron level along the bond area and affect the crystallographic orientation. Ultrasonic vibration results in a very weak texture. Plastic flow occurs in the grain after welding process and there is additional plastic flow around the fibre which leads to the fibre embedding. © 2009 Editorial Board of CHINA WELDING.

Re-embedding economic and social constitutionalism: Normative Perspectives for the E

This chapter proposes a social re-embedding of European constitutionalism by offering a coherent interpretation of EU constitutional principles as contained in the initial articles of the Treaties and the EU’s economic and social constitution as developed by the Court of Justice. It starts from the assumption that European integration is not merely an inter-state endeavour, but also a process that affects social and economic actors, in other words societies all over Europe. It may well ultimately engender a European society – if we are prepared to conceive of a poly-centric society, consisting of diverse components from a wide range of regions, social actors and cultures. Proceeding from the assumption that constitutionalism can be a relevant notion for such a holistic approach to European integration, the chapter develops elements of European constitutionalism relating to socio-economic reality. As national constitutional law, European constitutional law is presented as necessarily incomplete. European constitutionalism will thus have to offer modes of adapting open norms to an ever changing and developing societal reality. The chapter outlines a framework for such constitutionalism which, at the same time, offers opportunities for reconciling the social and economic dimensions in the European integration project through a re-configured notion of constitutionalism.

Re-embedding economic and social constitutionalism:Normative perspectives for the EU

Introduction Tensions between the economic and the social dimensions of European integration are being perceived as increasing, and so is the potential for conflict between national and European levels of policy-making. Both are well illustrated by a highly controversial line of Court of Justice of the European Union (ECJ) cases on industrial relations: Viking and Laval have become symbols for the continuing dominance of the economic over the social dimension of European integration and for an increasing tendency of the EU to diminish national autonomy. As one consequence, demands to protect Member States’ social policy choices from EU law pressures arise. For such demands to be tenable, isolation of national and EU policy-making and of economic and social dimensions of European integration would have to be possible. This is arguably not the case. Economic and social dimensions of integration will thus have to be reconciled across EU and national levels, if the EU and its Member States are to maintain the ability of enhancing social justice against the pulls of economic globalisation.

A pre-embedding immunogold approach for detection of synaptic endocytic proteins in situ

During the past decade, many molecular components of clathrin-mediated endocytosis have been identified and proposed to play various hypothetical roles in the process [Nat. Rev. Neurosci. 1 (2000) 161; Nature 422 (2003) 37]. One limitation to the evaluation of these hypotheses is the efficiency and resolution of immunolocalization protocols currently in use. In order to facilitate the evaluation of these hypotheses and to understand more fully the molecular mechanisms of clathrin-mediated endocytosis, we have developed a protocol allowing enhanced and reliable subcellular immunolocalization of proteins in synaptic endocytic zones in situ. Synapses established by giant reticulospinal axons in lamprey are used as a model system for these experiments. These axons are unbranched and reach up to 80-100 microm in diameter. Synaptic active zones and surrounding endocytic zones are established on the surface of the axonal cylinder. To provide access for antibodies to the sites of synaptic vesicle recycling, axons are lightly fixed and cut along their longitudinal axis. To preserve the ultrastructure of the synaptic endocytic zone, antibodies are applied without the addition of detergents. Opened axons are incubated with primary antibodies, which are detected with secondary antibodies conjugated to gold particles. Specimens are then post-fixed and processed for electron microscopy. This approach allows preservation of the ultrastructure of the endocytic sites during immunolabeling procedures, while simultaneously achieving reliable immunogold detection of proteins on endocytic intermediates. To explore the utility of this approach, we have investigated the localization of a GTPase, dynamin, on clathrin-coated intermediates in the endocytic zone of the lamprey giant synapse. Using the present immunogold protocol, we confirm the presence of dynamin on late stage coated pits [Nature 422 (2003) 37] and also demonstrate that dynamin is recruited to the coat of endocytic intermediates from the very early stages of the clathrin coat formation. Thus, our experiments show that the current pre-embedding immunogold method is a useful experimental tool to study the molecular mechanisms of synaptic vesicle recycling.

Building professionalism and employability skills: embedding employer engagement within first-year computing modules

This paper outlines a means of improving the employability skills of first-year university students through a closely integrated model of employer engagement within computer science modules. The outlined approach illustrates how employability skills, including communication, teamwork and time management skills, can be contextualised in a manner that directly relates to student learning but can still be linked forward into employment. The paper tests the premise that developing employability skills early within the curriculum will result in improved student engagement and learning within later modules. The paper concludes that embedding employer participation within first-year models can help relate a distant notion of employability into something of more immediate relevance in terms of how students can best approach learning. Further, by enhancing employability skills early within the curriculum, it becomes possible to improve academic attainment within later modules.

Fuzzy Ensembles for Embedding Adaptive Behaviours in Semi-Autonomous Avatars in 3D Virtual Worlds

Semi-autonomous avatars should be both realistic and believable. The goal is to learn from and reproduce the behaviours of the user-controlled input to enable semi-autonomous avatars to plausibly interact with their human-controlled counterparts. A powerful tool for embedding autonomous behaviour is learning by imitation. Hence, in this paper an ensemble of fuzzy inference systems cluster the user input data to identify natural groupings within the data to describe the users movement and actions in a more abstract way. Multiple clustering algorithms are investigated along with a neuro-fuzzy classifier; and an ensemble of fuzzy systems are evaluated.

Enhancing the student experience by embedding personal tutoring in the curriculum

This paper evaluates an initiative to improve the effectiveness of personal tutoring by embedding it into the curriculum. Structured group tutorials help students make the transition to learning in higher education. These tutorials are delivered within a core module and focus on enabling students to develop study skills, reflect on their learning and plan for their future. The tutor has a role in familiarising students with the practices, norms and skills required for learning at university. The system developed provides a structure and rationale for the interaction of tutors and students, with a clear place and value within the curriculum.

Analysis of temperature time-series: embedding dynamics into the MDS method

Global warming and the associated climate changes are being the subject of intensive research due to their major impact on social, economic and health aspects of the human life. Surface temperature time-series characterise Earth as a slow dynamics spatiotemporal system, evidencing long memory behaviour, typical of fractional order systems. Such phenomena are difficult to model and analyse, demanding for alternative approaches. This paper studies the complex correlations between global temperature time-series using the Multidimensional scaling (MDS) approach. MDS provides a graphical representation of the pattern of climatic similarities between regions around the globe. The similarities are quantified through two mathematical indices that correlate the monthly average temperatures observed in meteorological stations, over a given period of time. Furthermore, time dynamics is analysed by performing the MDS analysis over slices sampling the time series. MDS generates maps describing the stations’ locus in the perspective that, if they are perceived to be similar to each other, then they are placed on the map forming clusters. We show that MDS provides an intuitive and useful visual representation of the complex relationships that are present among temperature time-series, which are not perceived on traditional geographic maps. Moreover, MDS avoids sensitivity to the irregular distribution density of the meteorological stations.

Importance of the embedding environment on the strain within small rings in siliceous materials

The effect of the local environment on the energetic strain within small (SiO)N rings (with N=2,3) in silica materials is investigated via periodic model systems employing density functional calculations. Through comparison of the energies of various nonterminated systems containing small rings in strained and relatively unstrained environments, with alpha quartz, we demonstrate how small ring strain is affected by the nature of the embedding environment. We compare our findings with numerous previously reported calculations, often predicting significantly different small-ring strain energies, leading to a critical assessment of methods of calculating accurate localized ring energies. The results have relevance for estimates of the strain-induced response (e.g., chemical, photo, and radio) of small silica rings, and the propensity for them to form in bulk glasses, thin films, and nanoclusters.

Triangulation by Continuous Embedding

When triangulating a belief network we aim to obtain a junction tree of minimum state space. Searching for the optimal triangulation can be cast as a search over all the permutations of the network's vaeriables. Our approach is to embed the discrete set of permutations in a convex continuous domain D. By suitably extending the cost function over D and solving the continous nonlinear optimization task we hope to obtain a good triangulation with respect to the aformentioned cost. In this paper we introduce an upper bound to the total junction tree weight as the cost function. The appropriatedness of this choice is discussed and explored by simulations. Then we present two ways of embedding the new objective function into continuous domains and show that they perform well compared to the best known heuristic.

Embedding Emotional Context in Recommender Systems

Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart prediction assistant (SPA) platform in an intelligent learning guide with more than three million users. While most approaches to recommending have focused on algorithm performance. SPA makes recommendations to users on the basis of emotional information acquired in an incremental way. This article provides a cross-disciplinary perspective to achieve this goal in such recommender systems through a SPA platform. The methodology applied in SPA is the result of a bunch of technology transfer projects for large real-world rccommender systems