84,591 research outputs found

    Critical behaviours of contact near phase transitions

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    A central quantity of importance for ultracold atoms is contact, which measures two-body correlations at short distances in dilute systems. It appears in universal relations among thermodynamic quantities, such as large momentum tails, energy, and dynamic structure factors, through the renowned Tan relations. However, a conceptual question remains open as to whether or not contact can signify phase transitions that are insensitive to short-range physics. Here we show that, near a continuous classical or quantum phase transition, contact exhibits a variety of critical behaviors, including scaling laws and critical exponents that are uniquely determined by the universality class of the phase transition and a constant contact per particle. We also use a prototypical exactly solvable model to demonstrate these critical behaviors in one-dimensional strongly interacting fermions. Our work establishes an intrinsic connection between the universality of dilute many-body systems and universal critical phenomena near a phase transition.Comment: Final version published in Nat. Commun. 5:5140 doi: 10.1038/ncomms6140 (2014

    Analyticity of the Susceptibility Function for Unimodal Markovian Maps of the Interval

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    In a previous note [Ru] the susceptibility function was analyzed for some examples of maps of the interval. The purpose of the present note is to give a concise treatment of the general unimodal Markovian case (assuming ff real analytic). We hope that it will similarly be possible to analyze maps satisfying the Collet-Eckmann condition. Eventually, as explained in [Ru], application of a theorem of Whitney [Wh] should prove differentiability of the map fρff\mapsto\rho_f restricted to a suitable set.Comment: 8 page

    Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction

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    Visual media are powerful means of expressing emotions and sentiments. The constant generation of new content in social networks highlights the need of automated visual sentiment analysis tools. While Convolutional Neural Networks (CNNs) have established a new state-of-the-art in several vision problems, their application to the task of sentiment analysis is mostly unexplored and there are few studies regarding how to design CNNs for this purpose. In this work, we study the suitability of fine-tuning a CNN for visual sentiment prediction as well as explore performance boosting techniques within this deep learning setting. Finally, we provide a deep-dive analysis into a benchmark, state-of-the-art network architecture to gain insight about how to design patterns for CNNs on the task of visual sentiment prediction.Comment: Preprint of the paper accepted at the 1st Workshop on Affect and Sentiment in Multimedia (ASM), in ACM MultiMedia 2015. Brisbane, Australi

    IKEA: global sourcing and the sustainable leather initiative

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    The leather industry has traditionally been characterized by global operations across both developed and developing countries. Due to the long distance and contextual differences, there are numerous sustainability issues occurring along the global leather supply chain. Addressing these issues is both a responsibility and a challenge for multinational companies, especially in their global sourcing (GS) activities. This teaching case provides an example of implementing the sustainable leather initiative in the global sourcing process at IKEA. The case demonstrates IKEA’s sustainable leather initiative supported by its tailored GS strategy and GS structure and provides a benchmark of Sustainable GS for multinational companies and allows for a thorough discussion of how to implement a sustainability initiative while conducting GS. The case can be used to teach graduate/postgraduate in agricultural business, MBA and executive students on sustainable supply chain management and corporate social responsibility
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