99,111 research outputs found

    Efficient Ultrasound Image Analysis Models with Sonographer Gaze Assisted Distillation.

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    Recent automated medical image analysis methods have attained state-of-the-art performance but have relied on memory and compute-intensive deep learning models. Reducing model size without significant loss in performance metrics is crucial for time and memory-efficient automated image-based decision-making. Traditional deep learning based image analysis only uses expert knowledge in the form of manual annotations. Recently, there has been interest in introducing other forms of expert knowledge into deep learning architecture design. This is the approach considered in the paper where we propose to combine ultrasound video with point-of-gaze tracked for expert sonographers as they scan to train memory-efficient ultrasound image analysis models. Specifically we develop teacher-student knowledge transfer models for the exemplar task of frame classification for the fetal abdomen, head, and femur. The best performing memory-efficient models attain performance within 5% of conventional models that are 1000× larger in size

    A Description Logic of Typicality for Conceptual Combination

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    We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of combining prototypical concepts, an open problem in the fields of AI and cognitive modelling. Our logic extends the logic of typicality ALC + TR, based on the notion of rational closure, by inclusions p :: T(C) v D (“we have probability p that typical Cs are Ds”), coming from the distributed semantics of probabilistic Description Logics. Additionally, it embeds a set of cognitive heuristics for concept combination. We show that the complexity of reasoning in our logic is EXPTIME-complete as in ALC

    Evolution Equation for Generalized Parton Distributions

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    The extension of the method [arXiv:hep-ph/0503109] for solving the leading order evolution equation for Generalized Parton Distributions (GPDs) is presented. We obtain the solution of the evolution equation both for the flavor nonsinglet quark GPD and singlet quark and gluon GPDs. The properties of the solution and, in particular, the asymptotic form of GPDs in the small x and \xi region are discussed.Comment: REVTeX4, 34 pages, 3 figure

    Multiclass Semi-Supervised Learning on Graphs using Ginzburg-Landau Functional Minimization

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    We present a graph-based variational algorithm for classification of high-dimensional data, generalizing the binary diffuse interface model to the case of multiple classes. Motivated by total variation techniques, the method involves minimizing an energy functional made up of three terms. The first two terms promote a stepwise continuous classification function with sharp transitions between classes, while preserving symmetry among the class labels. The third term is a data fidelity term, allowing us to incorporate prior information into the model in a semi-supervised framework. The performance of the algorithm on synthetic data, as well as on the COIL and MNIST benchmark datasets, is competitive with state-of-the-art graph-based multiclass segmentation methods.Comment: 16 pages, to appear in Springer's Lecture Notes in Computer Science volume "Pattern Recognition Applications and Methods 2013", part of series on Advances in Intelligent and Soft Computin

    Logics of Finite Hankel Rank

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    We discuss the Feferman-Vaught Theorem in the setting of abstract model theory for finite structures. We look at sum-like and product-like binary operations on finite structures and their Hankel matrices. We show the connection between Hankel matrices and the Feferman-Vaught Theorem. The largest logic known to satisfy a Feferman-Vaught Theorem for product-like operations is CFOL, first order logic with modular counting quantifiers. For sum-like operations it is CMSOL, the corresponding monadic second order logic. We discuss whether there are maximal logics satisfying Feferman-Vaught Theorems for finite structures.Comment: Appeared in YuriFest 2015, held in honor of Yuri Gurevich's 75th birthday. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-23534-9_1

    Decentralization in Bitcoin and Ethereum Networks

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    Blockchain-based cryptocurrencies have demonstrated how to securely implement traditionally centralized systems, such as currencies, in a decentralized fashion. However, there have been few measurement studies on the level of decentralization they achieve in practice. We present a measurement study on various decentralization metrics of two of the leading cryptocurrencies with the largest market capitalization and user base, Bitcoin and Ethereum. We investigate the extent of decentralization by measuring the network resources of nodes and the interconnection among them, the protocol requirements affecting the operation of nodes, and the robustness of the two systems against attacks. In particular, we adapted existing internet measurement techniques and used the Falcon Relay Network as a novel measurement tool to obtain our data. We discovered that neither Bitcoin nor Ethereum has strictly better properties than the other. We also provide concrete suggestions for improving both systems.Comment: Financial Cryptography and Data Security 201

    Targeting BTK for the treatment of FLT3-ITD mutated acute myeloid leukemia

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    Approximately 20% of patients with acute myeloid leukaemia (AML) have a mutation in FMS-like-tyrosine-kinase-3 (FLT3). FLT3 is a trans-membrane receptor with a tyrosine kinase domain which, when activated, initiates a cascade of phosphorylated proteins including the SRC family of kinases. Recently our group and others have shown that pharmacologic inhibition and genetic knockdown of Bruton's tyrosine kinase (BTK) blocks AML blast proliferation, leukaemic cell adhesion to bone marrow stromal cells as well as migration of AML blasts. The anti-proliferative effects of BTK inhibition in human AML are mediated via inhibition of downstream NF-κB pro-survival signalling however the upstream drivers of BTK activation in human AML have yet to be fully characterised. Here we place the FLT3-ITD upstream of BTK in AML and show that the BTK inhibitor ibrutinib inhibits the survival and proliferation of FLT3-ITD primary AML blasts and AML cell lines. Furthermore ibrutinib inhibits the activation of downstream kinases including MAPK, AKT and STAT5. In addition we show that BTK RNAi inhibits proliferation of FLT3-ITD AML cells. Finally we report that ibrutinib reverses the cyto-protective role of BMSC on FLT3-ITD AML survival. These results argue for the evaluation of ibrutinib in patients with FLT3-ITD mutated AML

    Effect of sex on meat quality characteristics of Qinchuan cattle

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    A total of 18 Qinchuan cattle, six intact males (IM), six castrated males (CM) and six females (FM), were used to investigate the effect of sex on the physicochemical characteristics (PCC) and fatty acid (FA) composition of the Longissimus dorsi muscle (LDM). Obvious sex differences were found in the PCC of LDM: the IM group had higher shear value, pH, drip and cooking losses, and contents of ash and hydroxyproline (Hyp) than the CM and FM groups, as well as lower ether extract content and lightness. Both the IM and CM groups had lower water content and higher protein content than the FM group. Sex differences were also observed in contents of C14:0, C14:1, C18:1, saturated fatty acids (SFA), monounsaturated fatty acids (MUFA) and unsaturated fatty acids (UFA) between the IM and both the CM and FM groups but not between the CM and FM groups. The results indicated that sex is an importantsource of differences in meat quality of Qinchuan cattle because the castration and the meat characteristics of the CM group were more similar to the FM than the IM group
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