14,687 research outputs found

    Many Uninsured Children Qualify for Medi-Cal or Healthy Families

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    Examines the public health insurance eligibility of children in California who did not have health insurance coverage for some or all of the year in 2002, to highlight the geographic variations in children's uninsured eligibility rates

    On Using Active Learning and Self-Training when Mining Performance Discussions on Stack Overflow

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    Abundant data is the key to successful machine learning. However, supervised learning requires annotated data that are often hard to obtain. In a classification task with limited resources, Active Learning (AL) promises to guide annotators to examples that bring the most value for a classifier. AL can be successfully combined with self-training, i.e., extending a training set with the unlabelled examples for which a classifier is the most certain. We report our experiences on using AL in a systematic manner to train an SVM classifier for Stack Overflow posts discussing performance of software components. We show that the training examples deemed as the most valuable to the classifier are also the most difficult for humans to annotate. Despite carefully evolved annotation criteria, we report low inter-rater agreement, but we also propose mitigation strategies. Finally, based on one annotator's work, we show that self-training can improve the classification accuracy. We conclude the paper by discussing implication for future text miners aspiring to use AL and self-training.Comment: Preprint of paper accepted for the Proc. of the 21st International Conference on Evaluation and Assessment in Software Engineering, 201

    Hysteresis in the quantum Hall regimes in electron double quantum well structures

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    We present in this paper experimental results on the transport hysteresis in electron double quantum well structures. Exploring the measurement technique of fixing the magnetic field and sweeping a front gate voltage (Vg), we are able to study the hysteresis by varying the top layer Landau level fillings while maintaining a relatively constant filling factor in the bottom layer, allowing us to tackle the question of the sign of Rxx(up)-Rxx(down), where Rxx(up) is the magnetoresistance when Vg is swept up and Rxx(down) when Vg swept down. Furthermore, we observe that hysteresis is generally stronger in the even integer quantum Hall effect (IQHE) regime than in the odd-IQHE regime. This, we argue, is due to a larger energy gap for an even-IQHE state, determined by the Landau level separation, than that for an odd-IQHE state, determined by the Zeeman splitting

    Drug-Loaded, Bivalent-Bottle-Brush Polymers by Graft-through ROMP

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    Graft through ring-opening metathesis polymerization (ROMP) using ruthenium N heterocyclic carbene catalysts has enabled the synthesis of bottle-brush polymers with unprecedented ease and control Here we report the first bivalent-brush polymers, these materials were prepared by graft through ROMP of drug-loaded poly(ethylene glycol) (PEG) based macromonomers (MMs) Anticancer drugs doxorubicin (DOX) and camptothecin (CT) were attached to a norbornene alkyne-PEG MM via a photocleavable linker ROMP of either or both drug loaded MMs generated brush homo and copolymers with low polydispersities and defined molecular weights. Release of free DOX and CT from these materials was initiated by exposure to 365 nm light All of the CT and DOX polymers were at least 10 fold more toxic to human cancer cells after photoinitiated drug release while a copolymer carrying both CT and DOX displayed 30-fold increased toxicity upon irradiation Graft through ROMP of drug loaded macromonomers provides a general method for the systematic study of structure function relationships for stimuli responsive polymers in biological systems

    Coherent population trapping and dynamical instability in the nonlinearly coupled atom-molecule system

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    We study the possibility of creating a coherent population trapping (CPT) state, involving free atomic and ground molecular condensates, during the process of associating atomic condensate into molecular condensate. We generalize the Bogoliubov approach to this multi-component system and study the collective excitations of the CPT state in the homogeneous limit. We develop a set of analytical criteria based on the relationship among collisions involving atoms and ground molecules, which are found to strongly affect the stability properties of the CPT state, and use it to find the stability diagram and to systematically classify various instabilities in the long-wavelength limit.Comment: 11 pages, 8 figure

    Fast multipole networks

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    Two prerequisites for robotic multiagent systems are mobility and communication. Fast multipole networks (FMNs) enable both ends within a unified framework. FMNs can be organized very efficiently in a distributed way from local information and are ideally suited for motion planning using artificial potentials. We compare FMNs to conventional communication topologies, and find that FMNs offer competitive communication performance (including higher network efficiency per edge at marginal energy cost) in addition to advantages for mobility

    Power-law cosmological solution derived from DGP brane with a brane tachyon field

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    By studying a tachyon field on the DGP brane model, in order to embed the 4D standard Friedmann equation with a brane tachyon field in 5D bulk, the metric of the 5D spacetime is presented. Then, adopting the inverse square potential of tachyon field, we obtain an expanding universe with power-law on the brane and an exact 5D solution.Comment: 8 pages, 1 figure, accepted by IJMP

    Model checking ω-regular properties for quantum Markov chains

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    © Yuan Feng, Ernst Moritz Hahn, Andrea Turrini, and Shenggang Ying. Quantum Markov chains are an extension of classical Markov chains which are labelled with super-operators rather than probabilities. They allow to faithfully represent quantum programs and quantum protocols. In this paper, we investigate model checking !-regular properties, a very general class of properties (including, e.g., LTL properties) of interest, against this model. For classical Markov chains, such properties are usually checked by building the product of the model with a language automaton. Subsequent analysis is then performed on this product. When doing so, one takes into account its graph structure, and for instance performs different analyses per bottom strongly connected component (BSCC). Unfortunately, for quantum Markov chains such an approach does not work directly, because super-operators behave differently from probabilities. To overcome this problem, we transform the product quantum Markov chain into a single super-operator, which induces a decomposition of the state space (the tensor product of classical state space and the quantum one) into a family of BSCC subspaces. Interestingly, we show that this BSCC decomposition provides a solution to the issue of model checking ω-regular properties for quantum Markov chains
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