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null | annotation
list | annotation_agent
null | multi_label
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{
"abstract": " The intermetallic semiconductor FeGa$_{3}$ acquires itinerant ferromagnetism\nupon electron doping by a partial replacement of Ga with Ge. We studied the\nelectron spin resonance (ESR) of high-quality single crystals of\nFeGa$_{3-x}$Ge$_x$ for $x$ from 0 up to 0.162 where ferromagnetic order is\nobserved. For $x = 0$ we observed a well-defined ESR signal, indicating the\npresence of pre-formed magnetic moments in the semiconducting phase. Upon Ge\ndoping the occurrence of itinerant magnetism clearly affects the ESR properties\nbelow $\\approx 40$~K whereas at higher temperatures an ESR signal as seen in\nFeGa$_{3}$ prevails independent on the Ge-content. The present results show\nthat the ESR of FeGa$_{3-x}$Ge$_x$ is an appropriate and direct tool to\ninvestigate the evolution of 3d-based itinerant magnetism.\n",
"title": "Spin dynamics of FeGa$_{3-x}$Ge$_x$ studied by Electron Spin Resonance"
}
| null | null |
[
"Physics"
] | null | true | null |
14301
| null |
Validated
| null | null |
null |
{
"abstract": " We show that topology can protect exponentially localized, zero energy edge\nmodes at critical points between one-dimensional symmetry protected topological\nphases. This is possible even without gapped degrees of freedom in the bulk\n---in contrast to recent work on edge modes in gapless chains. We present an\nintuitive picture for the existence of these edge modes in the case of\nnon-interacting spinless fermions with time reversal symmetry (BDI class of the\ntenfold way). The stability of this phenomenon relies on a topological\ninvariant defined in terms of a complex function, counting its zeros and poles\ninside the unit circle. This invariant can prevent two models described by the\n\\emph{same} conformal field theory (CFT) from being smoothly connected. A full\nclassification of critical phases in the non-interacting BDI class is obtained:\neach phase is labeled by the central charge of the CFT, $c \\in\n\\frac{1}{2}\\mathbb N$, and the topological invariant, $\\omega \\in \\mathbb Z$.\nMoreover, $c$ is determined by the difference in the number of edge modes\nbetween the phases neighboring the transition. Numerical simulations show that\nthe topological edge modes of critical chains can be stable in the presence of\ninteractions and disorder.\n",
"title": "Topology and edge modes in quantum critical chains"
}
| null | null | null | null | true | null |
14302
| null |
Default
| null | null |
null |
{
"abstract": " We find boundaries of Borel-Serre compactifications of locally symmetric\nspaces, for which any filling is incompressible. We prove this result by\nshowing that these boundaries have small singular models and using these models\nto obstruct compressions. We also show that small singular models of boundaries\nobstruct $S^1$-actions (and more generally homotopically trivial $\\mathbb\nZ/p$-actions) on interiors of aspherical fillings. We use this to bound the\nsymmetry of complete Riemannian metrics on such interiors in terms of the\nfundamental group. We also use small singular models to simplify the proofs of\nsome already known theorems about moduli spaces (the minimal orbifold theorem\nand a topological analogue of Royden's theorem).\n",
"title": "Incompressible fillings of manifolds"
}
| null | null |
[
"Mathematics"
] | null | true | null |
14303
| null |
Validated
| null | null |
null |
{
"abstract": " Public speaking is an important aspect of human communication and\ninteraction. The majority of computational work on public speaking concentrates\non analyzing the spoken content, and the verbal behavior of the speakers. While\nthe success of public speaking largely depends on the content of the talk, and\nthe verbal behavior, non-verbal (visual) cues, such as gestures and physical\nappearance also play a significant role. This paper investigates the importance\nof visual cues by estimating their contribution towards predicting the\npopularity of a public lecture. For this purpose, we constructed a large\ndatabase of more than $1800$ TED talk videos. As a measure of popularity of the\nTED talks, we leverage the corresponding (online) viewers' ratings from\nYouTube. Visual cues related to facial and physical appearance, facial\nexpressions, and pose variations are extracted from the video frames using\nconvolutional neural network (CNN) models. Thereafter, an attention-based long\nshort-term memory (LSTM) network is proposed to predict the video popularity\nfrom the sequence of visual features. The proposed network achieves\nstate-of-the-art prediction accuracy indicating that visual cues alone contain\nhighly predictive information about the popularity of a talk. Furthermore, our\nnetwork learns a human-like attention mechanism, which is particularly useful\nfor interpretability, i.e. how attention varies with time, and across different\nvisual cues by indicating their relative importance.\n",
"title": "Multichannel Attention Network for Analyzing Visual Behavior in Public Speaking"
}
| null | null | null | null | true | null |
14304
| null |
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| null | null |
null |
{
"abstract": " Let $k$ be an algebraically closed field of any characteristic. We apply the\nHamburger-Noether process of successive quadratic transformations to show the\nequivalence of two definitions of the {\\L}ojasiewicz exponent\n$\\mathfrak{L}(\\mathfrak{a})$ of an ideal $\\mathfrak{a}\\subset k[[x,y]]$.\n",
"title": "The Łojasiewicz Exponent via The Valuative Hamburger-Noether Process"
}
| null | null | null | null | true | null |
14305
| null |
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| null | null |
null |
{
"abstract": " Bibliometrics offers a particular representation of science. Through\nbibliometric methods a bibliometrician will always highlight particular\nelements of publications, and through these elements operationalize particular\nrepresentations of science, while obscuring other possible representations from\nview. Understanding bibliometrics as representation implies that a bibliometric\nanalysis is always performative: a bibliometric analysis brings a particular\nrepresentation of science into being that potentially influences the science\nsystem itself. In this review we analyze the ways the humanities have been\nrepresented throughout the history of bibliometrics, often in comparison to\nother scientific domains or to a general notion of the sciences. Our review\ndiscusses bibliometric scholarship between 1965 and 2016 that studies the\nhumanities empirically. We distinguish between two periods of bibliometric\nscholarship. The first period, between 1965 and 1989, is characterized by a\nsociological theoretical framework, the development and use of the Price index,\nand small samples of journal publications as data sources. The second period,\nfrom the mid-1980s up until the present day, is characterized by a new\nhinterland, that of science policy and research evaluation, in which\nbibliometric methods become embedded.\n",
"title": "Science and its significant other: Representing the humanities in bibliometric scholarship"
}
| null | null | null | null | true | null |
14306
| null |
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| null | null |
null |
{
"abstract": " Traditional automatic evaluation measures for natural language generation\n(NLG) use costly human-authored references to estimate the quality of a system\noutput. In this paper, we propose a referenceless quality estimation (QE)\napproach based on recurrent neural networks, which predicts a quality score for\na NLG system output by comparing it to the source meaning representation only.\nOur method outperforms traditional metrics and a constant baseline in most\nrespects; we also show that synthetic data helps to increase correlation\nresults by 21% compared to the base system. Our results are comparable to\nresults obtained in similar QE tasks despite the more challenging setting.\n",
"title": "Referenceless Quality Estimation for Natural Language Generation"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14307
| null |
Validated
| null | null |
null |
{
"abstract": " We investigate the effect of explicitly enforcing the Lipschitz continuity of\nneural networks with respect to their inputs. To this end, we provide a simple\ntechnique for computing an upper bound to the Lipschitz constant of a feed\nforward neural network composed of commonly used layer types and demonstrate\ninaccuracies in previous work on this topic. Our technique is then used to\nformulate training a neural network with a bounded Lipschitz constant as a\nconstrained optimisation problem that can be solved using projected stochastic\ngradient methods. Our evaluation study shows that, in isolation, our method\nperforms comparatively to state-of-the-art regularisation techniques. Moreover,\nwhen combined with existing approaches to regularising neural networks the\nperformance gains are cumulative. We also provide evidence that the\nhyperparameters are intuitive to tune and demonstrate how the choice of norm\nfor computing the Lipschitz constant impacts the resulting model.\n",
"title": "Regularisation of Neural Networks by Enforcing Lipschitz Continuity"
}
| null | null | null | null | true | null |
14308
| null |
Default
| null | null |
null |
{
"abstract": " Traditionally, classifying large hierarchical labels with more than 10000\ndistinct traces can only be achieved with flatten labels. Although flatten\nlabels is feasible, it misses the hierarchical information in the labels.\nHierarchical models like HSVM by \\cite{vural2004hierarchical} becomes\nimpossible to train because of the sheer number of SVMs in the whole\narchitecture. We developed a hierarchical architecture based on neural networks\nthat is simple to train. Also, we derived an inference algorithm that can\nefficiently infer the MAP (maximum a posteriori) trace guaranteed by our\ntheorems. Furthermore, the complexity of the model is only $O(n^2)$ compared to\n$O(n^h)$ in a flatten model, where $h$ is the height of the hierarchy.\n",
"title": "HiNet: Hierarchical Classification with Neural Network"
}
| null | null | null | null | true | null |
14309
| null |
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| null | null |
null |
{
"abstract": " We have experimentally quantified the temporal structural diversity from the\ncoordinate fluctuations of a laser beam propagating through isotropic optical\nturbulence. The main focus here is on the characterization of the long-range\ncorrelations in the wandering of a thin Gaussian laser beam over a screen after\npropagating through a turbulent medium. To fulfill this goal, a\nlaboratory-controlled experiment was conducted in which coordinate fluctuations\nof the laser beam were recorded at a sufficiently high sampling rate for a wide\nrange of turbulent conditions. Horizontal and vertical displacements of the\nlaser beam centroid were subsequently analyzed by implementing the symbolic\ntechnique based on ordinal patterns to estimate the well-known permutation\nentropy. We show that the permutation entropy estimations at multiple time\nscales evidence an interplay between different dynamical behaviors. More\nspecifically, a crossover between two different scaling regimes is observed. We\nconfirm a transition from an integrated stochastic process contaminated with\nelectronic noise to a fractional Brownian motion with a Hurst exponent H = 5/6\nas the sampling time increases. Besides, we are able to quantify, from the\nestimated entropy, the amount of electronic noise as a function of the\nturbulence strength. We have also demonstrated that these experimental\nobservations are in very good agreement with numerical simulations of noisy\nfractional Brownian motions with a well-defined crossover between two different\nscaling regimes.\n",
"title": "Multiscale permutation entropy analysis of laser beam wandering in isotropic turbulence"
}
| null | null | null | null | true | null |
14310
| null |
Default
| null | null |
null |
{
"abstract": " Automatic compiler phase selection/ordering has traditionally been focused on\nCPUs and, to a lesser extent, FPGAs. We present experiments regarding compiler\nphase ordering specialization of OpenCL kernels targeting a GPU. We use\niterative exploration to specialize LLVM phase orders on 15 OpenCL benchmarks\nto an NVIDIA GPU. We analyze the generated NVIDIA PTX code for the various\nversions to identify the main causes of the most significant improvements and\npresent results of a set of experiments that demonstrate the importance of\nusing specific phase orders. Using specialized compiler phase orders, we were\nable to achieve geometric mean improvements of 1.54x (up to 5.48x) and 1.65x\n(up to 5.7x) over PTX generated by the NVIDIA CUDA compiler from CUDA versions\nof the same kernels, and over execution of the OpenCL kernels compiled from\nsource with the NVIDIA OpenCL driver, respectively. We also evaluate the use of\ncode-features in the OpenCL kernels. More specifically, we evaluate an approach\nthat achieves geometric mean improvements of 1.49x and 1.56x over the same\nOpenCL baseline, by using the compiler sequences of the 1 or 3 most similar\nbenchmarks, respectively.\n",
"title": "Improving OpenCL Performance by Specializing Compiler Phase Selection and Ordering"
}
| null | null | null | null | true | null |
14311
| null |
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| null | null |
null |
{
"abstract": " Shot noise is an important ingredient to any measurement or theoretical\nmodeling of discrete tracers of the large scale structure. Recent work has\nshown that the shot noise in the halo power spectrum becomes increasingly\nsub-Poissonian at high mass. Interestingly, while the halo model predicts a\nshot noise power spectrum in qualitative agreement with the data, it leads to\nan unphysical white noise in the cross halo-matter and matter power spectrum.\nIn this work, we show that absorbing all the halo model sources of shot noise\ninto the halo fluctuation field leads to meaningful predictions for the shot\nnoise contributions to halo clustering statistics and remove the unphysical\nwhite noise from the cross halo-matter statistics. Our prescription\nstraightforwardly maps onto the general bias expansion, so that the\nrenormalized shot noise terms can be expressed as combinations of the halo\nmodel shot noises. Furthermore, we demonstrate that non-Poissonian\ncontributions are related to volume integrals over correlation functions and\ntheir response to long-wavelength density perturbations. This leads to a new\nclass of consistency relations for discrete tracers, which appear to be\nsatisfied by our reformulation of the halo model. We test our theoretical\npredictions against measurements of halo shot noise bispectra extracted from a\nlarge suite of numerical simulations. Our model reproduces qualitatively the\nobserved sub-Poissonian noise, although it underestimates the magnitude of this\neffect.\n",
"title": "Shot noise and biased tracers: a new look at the halo model"
}
| null | null | null | null | true | null |
14312
| null |
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| null | null |
null |
{
"abstract": " We establish the sharp growth rate, in terms of cardinality, of the $L^p$\nnorms of the maximal Hilbert transform $H_\\Omega$ along finite subsets of a\nfinite order lacunary set of directions $\\Omega \\subset \\mathbb R^3$, answering\na question of Parcet and Rogers in dimension $n=3$. Our result is the first\nsharp estimate for maximal directional singular integrals in dimensions greater\nthan 2.\nThe proof relies on a representation of the maximal directional Hilbert\ntransform in terms of a model maximal operator associated to compositions of\ntwo-dimensional angular multipliers, as well as on the usage of weighted norm\ninequalities, and their extrapolation, in the directional setting.\n",
"title": "On the maximal directional Hilbert transform in three dimensions"
}
| null | null | null | null | true | null |
14313
| null |
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| null | null |
null |
{
"abstract": " Hypothesis generation is becoming a crucial time-saving technique which\nallows biomedical researchers to quickly discover implicit connections between\nimportant concepts. Typically, these systems operate on domain-specific\nfractions of public medical data. MOLIERE, in contrast, utilizes information\nfrom over 24.5 million documents. At the heart of our approach lies a\nmulti-modal and multi-relational network of biomedical objects extracted from\nseveral heterogeneous datasets from the National Center for Biotechnology\nInformation (NCBI). These objects include but are not limited to scientific\npapers, keywords, genes, proteins, diseases, and diagnoses. We model hypotheses\nusing Latent Dirichlet Allocation applied on abstracts found near shortest\npaths discovered within this network, and demonstrate the effectiveness of\nMOLIERE by performing hypothesis generation on historical data. Our network,\nimplementation, and resulting data are all publicly available for the broad\nscientific community.\n",
"title": "MOLIERE: Automatic Biomedical Hypothesis Generation System"
}
| null | null | null | null | true | null |
14314
| null |
Default
| null | null |
null |
{
"abstract": " We consider several previously studied online variants of bin packing and\nprove new and improved lower bounds on the asymptotic competitive ratios for\nthem. For that, we use a method of fully adaptive constructions. In particular,\nwe improve the lower bound for the asymptotic competitive ratio of online\nsquare packing significantly, raising it from roughly 1.68 to above 1.75.\n",
"title": "Lower bounds for several online variants of bin packing"
}
| null | null | null | null | true | null |
14315
| null |
Default
| null | null |
null |
{
"abstract": " We study black-box attacks on machine learning classifiers where each query\nto the model incurs some cost or risk of detection to the adversary. We focus\nexplicitly on minimizing the number of queries as a major objective.\nSpecifically, we consider the problem of attacking machine learning classifiers\nsubject to a budget of feature modification cost while minimizing the number of\nqueries, where each query returns only a class and confidence score. We\ndescribe an approach that uses Bayesian optimization to minimize the number of\nqueries, and find that the number of queries can be reduced to approximately\none tenth of the number needed through a random strategy for scenarios where\nthe feature modification cost budget is low.\n",
"title": "Query-limited Black-box Attacks to Classifiers"
}
| null | null | null | null | true | null |
14316
| null |
Default
| null | null |
null |
{
"abstract": " This work addresses the problem of kinematic trajectory planning for mobile\nmanipulators with non-holonomic constraints, and holonomic operational-space\ntracking constraints. We obtain whole-body trajectories and time-varying\nkinematic feedback controllers by solving a Constrained Sequential Linear\nQuadratic Optimal Control problem. The employed algorithm features high\nefficiency through a continuous-time formulation that benefits from adaptive\nstep-size integrators and through linear complexity in the number of\nintegration steps. In a first application example, we solve kinematic\ntrajectory planning problems for a 26 DoF wheeled robot. In a second example,\nwe apply Constrained SLQ to a real-world mobile manipulator in a\nreceding-horizon optimal control fashion, where we obtain optimal controllers\nand plans at rates up to 100 Hz.\n",
"title": "Efficient Kinematic Planning for Mobile Manipulators with Non-holonomic Constraints Using Optimal Control"
}
| null | null | null | null | true | null |
14317
| null |
Default
| null | null |
null |
{
"abstract": " Integrated Information Theory (IIT) is a prominent theory of consciousness\nthat has at its centre measures that quantify the extent to which a system\ngenerates more information than the sum of its parts. While several candidate\nmeasures of integrated information (`$\\Phi$') now exist, little is known about\nhow they compare, especially in terms of their behaviour on non-trivial network\nmodels. In this article we provide clear and intuitive descriptions of six\ndistinct candidate measures. We then explore the properties of each of these\nmeasures in simulation on networks consisting of eight interacting nodes,\nanimated with Gaussian linear autoregressive dynamics. We find a striking\ndiversity in the behaviour of these measures -- no two measures show consistent\nagreement across all analyses. Further, only a subset of the measures appear to\ngenuinely reflect some form of dynamical complexity, in the sense of\nsimultaneous segregation and integration between system components. Our results\nhelp guide the operationalisation of IIT and advance the development of\nmeasures of integrated information that may have more general applicability.\n",
"title": "Measuring Integrated Information: Comparison of Candidate Measures in Theory and Simulation"
}
| null | null | null | null | true | null |
14318
| null |
Default
| null | null |
null |
{
"abstract": " Let $M$ be a compact oriented three-manifold whose interior is hyperbolic of\nfinite volume. We prove a variation formula for the volume on the variety of\nrepresentations of $M$ in $\\operatorname{SL}_n(\\mathbb C)$. Our proof follows\nthe strategy of Reznikov's rigidity when $M$ is closed, in particular we use\nFuks' approach to variations by means of Lie algebra cohomology. When $n=2$, we\nget back Hodgson's formula for variation of volume on the space of hyperbolic\nDehn fillings. Our formula also yields the variation of volume on the space of\ndecorated triangulations obtained by Bergeron-Falbel-Guillou and\nDimofte-Gabella-Goncharov.\n",
"title": "Volumes of $\\mathrm{SL}_n\\mathbb{C}$-representations of hyperbolic 3-manifolds"
}
| null | null |
[
"Mathematics"
] | null | true | null |
14319
| null |
Validated
| null | null |
null |
{
"abstract": " In this paper we propose two novel bounds for the log-likelihood based on\nKullback-Leibler and the Rényi divergences, which can be used for\nvariational inference and in particular for the training of Variational\nAutoEncoders. Our proposal is motivated by the difficulties encountered in\ntraining VAEs on continuous datasets with high contrast images, such as those\nwith handwritten digits and characters, where numerical issues often appear\nunless noise is added, either to the dataset during training or to the\ngenerative model given by the decoder. The new bounds we propose, which are\nobtained from the maximization of the likelihood of an interval for the\nobservations, allow numerically stable training procedures without the\nnecessity of adding any extra source of noise to the data.\n",
"title": "Learning in Variational Autoencoders with Kullback-Leibler and Renyi Integral Bounds"
}
| null | null | null | null | true | null |
14320
| null |
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| null | null |
null |
{
"abstract": " In this paper, we design, fabricate and experimentally characterize a\nbroadband acoustic right-angle bend device in air. Perforated panels with\nvarious hole-sizes are used to construct the bend structure. Both the simulated\nand the experimental results verify that acoustic beam can be rotated\neffectively through the acoustic bend in a wide frequency range. This model may\nhave potential applications in some areas such as sound absorption and acoustic\ndetection in pipeline.\n",
"title": "Design and demonstration of an acoustic right-angle bend"
}
| null | null | null | null | true | null |
14321
| null |
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| null | null |
null |
{
"abstract": " Conventional shape sensing techniques using Fiber Bragg Grating (FBG) involve\nfinding the curvature at discrete FBG active areas and integrating curvature\nover the length of the continuum dexterous manipulator (CDM) for tip position\nestimation (TPE). However, due to limited number of sensing locations and many\ngeometrical assumptions, these methods are prone to large error propagation\nespecially when the CDM undergoes large deflections. In this paper, we study\nthe complications of using the conventional TPE methods that are dependent on\nsensor model and propose a new data-driven method that overcomes these\nchallenges. The proposed method consists of a regression model that takes FBG\nwavelength raw data as input and directly estimates the CDM's tip position.\nThis model is pre-operatively (off-line) trained on position information from\noptical trackers/cameras (as the ground truth) and it intra-operatively\n(on-line) estimates CDM tip position using only the FBG wavelength data. The\nmethod's performance is evaluated on a CDM developed for orthopedic\napplications, and the results are compared to conventional model-dependent\nmethods during large deflection bendings. Mean absolute TPE error (and standard\ndeviation) of 1.52 (0.67) mm and 0.11 (0.1) mm with maximum absolute errors of\n3.63 mm and 0.62 mm for the conventional and the proposed data-driven\ntechniques were obtained, respectively. These results demonstrate a significant\nout-performance of the proposed data-driven approach versus the conventional\nestimation technique.\n",
"title": "FBG-Based Position Estimation of Highly Deformable Continuum Manipulators: Model-Dependent vs. Data-Driven Approaches"
}
| null | null | null | null | true | null |
14322
| null |
Default
| null | null |
null |
{
"abstract": " Distributed control, as a potential solution to decreasing communication\ndemands in microgrids, has drawn much attention in recent years. Advantages of\ndistributed control have been extensively discussed, while its impacts on\nmicrogrid performance and stability, especially in the case of communication\nlatency, have not been explicitly studied or fully understood yet. This paper\naddresses this gap by proposing a generalized theoretical framework for\nsmall-signal stability analysis and performance evaluation for microgrids using\ndistributed control. The proposed framework synthesizes generator and load\nfrequency-domain characteristics, primary and secondary control loops, as well\nas the communication latency into a frequency-domain representation which is\nfurther evaluated by the generalized Nyquist theorem. In addition, various\nparameters and their impacts on microgrid dynamic performance are investigated\nand summarized into guidelines to help better design the system. Case studies\ndemonstrate the effectiveness of the proposed approach.\n",
"title": "Small-signal Stability Analysis and Performance Evaluation of Microgrids under Distributed Control"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14323
| null |
Validated
| null | null |
null |
{
"abstract": " All-pay auctions, a common mechanism for various human and agent\ninteractions, suffers, like many other mechanisms, from the possibility of\nplayers' failure to participate in the auction. We model such failures, and\nfully characterize equilibrium for this class of games, we present a symmetric\nequilibrium and show that under some conditions the equilibrium is unique. We\nreveal various properties of the equilibrium, such as the lack of influence of\nthe most-likely-to-participate player on the behavior of the other players. We\nperform this analysis with two scenarios: the sum-profit model, where the\nauctioneer obtains the sum of all submitted bids, and the max-profit model of\ncrowdsourcing contests, where the auctioneer can only use the best submissions\nand thus obtains only the winning bid.\nFurthermore, we examine various methods of influencing the probability of\nparticipation such as the effects of misreporting one's own probability of\nparticipating, and how influencing another player's participation chances\nchanges the player's strategy.\n",
"title": "Agent Failures in All-Pay Auctions"
}
| null | null | null | null | true | null |
14324
| null |
Default
| null | null |
null |
{
"abstract": " We examine volume computation of general-dimensional polytopes and more\ngeneral convex bodies, defined as the intersection of a simplex by a family of\nparallel hyperplanes, and another family of parallel hyperplanes or a family of\nconcentric ellipsoids. Such convex bodies appear in modeling and predicting\nfinancial crises. The impact of crises on the economy (labor, income, etc.)\nmakes its detection of prime interest. Certain features of dependencies in the\nmarkets clearly identify times of turmoil. We describe the relationship between\nasset characteristics by means of a copula; each characteristic is either a\nlinear or quadratic form of the portfolio components, hence the copula can be\nconstructed by computing volumes of convex bodies. We design and implement\npractical algorithms in the exact and approximate setting, we experimentally\njuxtapose them and study the tradeoff of exactness and accuracy for speed. We\nanalyze the following methods in order of increasing generality: rejection\nsampling relying on uniformly sampling the simplex, which is the fastest\napproach, but inaccurate for small volumes; exact formulae based on the\ncomputation of integrals of probability distribution functions; an optimized\nLawrence sign decomposition method, since the polytopes at hand are shown to be\nsimple; Markov chain Monte Carlo algorithms using random walks based on the\nhit-and-run paradigm generalized to nonlinear convex bodies and relying on new\nmethods for computing a ball enclosed; the latter is experimentally extended to\nnon-convex bodies with very encouraging results. Our C++ software, based on\nCGAL and Eigen and available on github, is shown to be very effective in up to\n100 dimensions. Our results offer novel, effective means of computing portfolio\ndependencies and an indicator of financial crises, which is shown to correctly\nidentify past crises.\n",
"title": "Practical volume computation of structured convex bodies, and an application to modeling portfolio dependencies and financial crises"
}
| null | null | null | null | true | null |
14325
| null |
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| null | null |
null |
{
"abstract": " Diluted mean-field models are spin systems whose geometry of interactions is\ninduced by a sparse random graph or hypergraph. Such models play an eminent\nrole in the statistical mechanics of disordered systems as well as in\ncombinatorics and computer science. In a path-breaking paper based on the\nnon-rigorous `cavity method', physicists predicted not only the existence of a\nreplica symmetry breaking phase transition in such models but also sketched a\ndetailed picture of the evolution of the Gibbs measure within the replica\nsymmetric phase and its impact on important problems in combinatorics, computer\nscience and physics [Krzakala et al.: PNAS 2007]. In this paper we rigorise\nthis picture completely for a broad class of models, encompassing the Potts\nantiferromagnet on the random graph, the $k$-XORSAT model and the diluted\n$k$-spin model for even $k$. We also prove a conjecture about the detection\nproblem in the stochastic block model that has received considerable attention\n[Decelle et al.: Phys. Rev. E 2011].\n",
"title": "Charting the replica symmetric phase"
}
| null | null | null | null | true | null |
14326
| null |
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| null | null |
null |
{
"abstract": " We analyze the clustering problem through a flexible probabilistic model that\naims to identify an optimal partition on the sample X 1 , ..., X n. We perform\nexact clustering with high probability using a convex semidefinite estimator\nthat interprets as a corrected, relaxed version of K-means. The estimator is\nanalyzed through a non-asymptotic framework and showed to be optimal or\nnear-optimal in recovering the partition. Furthermore, its performances are\nshown to be adaptive to the problem's effective dimension, as well as to K the\nunknown number of groups in this partition. We illustrate the method's\nperformances in comparison to other classical clustering algorithms with\nnumerical experiments on simulated data.\n",
"title": "Adaptive Clustering through Semidefinite Programming"
}
| null | null | null | null | true | null |
14327
| null |
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| null | null |
null |
{
"abstract": " Comparison data arises in many important contexts, e.g. shopping, web clicks,\nor sports competitions. Typically we are given a dataset of comparisons and\nwish to train a model to make predictions about the outcome of unseen\ncomparisons. In many cases available datasets have relatively few comparisons\n(e.g. there are only so many NFL games per year) or efficiency is important\n(e.g. we want to quickly estimate the relative appeal of a product). In such\nsettings it is well known that shrinkage estimators outperform maximum\nlikelihood estimators. A complicating matter is that standard comparison models\nsuch as the conditional multinomial logit model are only models of conditional\noutcomes (who wins) and not of comparisons themselves (who competes). As such,\ndifferent models of the comparison process lead to different shrinkage\nestimators. In this work we derive a collection of methods for estimating the\npairwise uncertainty of pairwise predictions based on different assumptions\nabout the comparison process. These uncertainty estimates allow us both to\nexamine model uncertainty as well as perform Empirical Bayes shrinkage\nestimation of the model parameters. We demonstrate that our shrunk estimators\noutperform standard maximum likelihood methods on real comparison data from\nonline comparison surveys as well as from several sports contexts.\n",
"title": "Improving pairwise comparison models using Empirical Bayes shrinkage"
}
| null | null | null | null | true | null |
14328
| null |
Default
| null | null |
null |
{
"abstract": " We generalize the chimney model by introducing nonlinear restoring and\ngravitational forces for the purpose of modeling swaying of trees at high wind\nspeeds. Here we have restricted to the simplest case of a single element and\nthe governing equation we arrive at has not been studied so far. We study the\nonset of fractal basin boundary of the two fixed points and also observe the\nchaotic solutions. We also examine the need for considering the full sine term\nin the gravitational force.\n",
"title": "Single Element Nonlinear Chimney Model"
}
| null | null |
[
"Physics"
] | null | true | null |
14329
| null |
Validated
| null | null |
null |
{
"abstract": " Fast radio bursts are a new class of transient radio phenomena currently\ndetected as millisecond radio pulses with very high dispersion measures. As new\nradio surveys begin searching for FRBs a large population is expected to be\ndetected in real-time, triggering a range of multi-wavelength and\nmulti-messenger telescopes to search for repeating bursts and/or associated\nemission. Here we propose a method for disseminating FRB triggers using Virtual\nObservatory Events (VOEvents). This format was developed and is used\nsuccessfully for transient alerts across the electromagnetic spectrum and for\nmulti-messenger signals such as gravitational waves. In this paper we outline a\nproposed VOEvent standard for FRBs that includes the essential parameters of\nthe event and where these parameters should be specified within the structure\nof the event. An additional advantage to the use of VOEvents for FRBs is that\nthe events can automatically be ingested into the FRB Catalogue (FRBCAT)\nenabling real-time updates for public use. We welcome feedback from the\ncommunity on the proposed standard outlined below and encourage those\ninterested to join the nascent working group forming around this topic.\n",
"title": "VOEvent Standard for Fast Radio Bursts"
}
| null | null | null | null | true | null |
14330
| null |
Default
| null | null |
null |
{
"abstract": " Fine-tuning of a deep convolutional neural network (CNN) is often desired.\nThis paper provides an overview of our publicly available py-faster-rcnn-ft\nsoftware library that can be used to fine-tune the VGG_CNN_M_1024 model on\ncustom subsets of the Microsoft Common Objects in Context (MS COCO) dataset.\nFor example, we improved the procedure so that the user does not have to look\nfor suitable image files in the dataset by hand which can then be used in the\ndemo program. Our implementation randomly selects images that contain at least\none object of the categories on which the model is fine-tuned.\n",
"title": "Fine-tuning deep CNN models on specific MS COCO categories"
}
| null | null | null | null | true | null |
14331
| null |
Default
| null | null |
null |
{
"abstract": " This work investigates the fundamental limits of communication over a noisy\ndiscrete memoryless channel that wears out, in the sense of signal-dependent\ncatastrophic failure. In particular, we consider a channel that starts as a\nmemoryless binary-input channel and when the number of transmitted ones causes\na sufficient amount of damage, the channel ceases to convey signals. Constant\ncomposition codes are adopted to obtain an achievability bound and the\nleft-concave right-convex inequality is then refined to obtain a converse bound\non the log-volume throughput for channels that wear out. Since infinite\nblocklength codes will always wear out the channel for any finite threshold of\nfailure and therefore cannot convey information at positive rates, we analyze\nthe performance of finite blocklength codes to determine the maximum expected\ntransmission volume at a given level of average error probability. We show that\nthis maximization problem has a recursive form and can be solved by dynamic\nprogramming. Numerical results demonstrate that a sequence of block codes is\npreferred to a single block code for streaming sources.\n",
"title": "On the Throughput of Channels that Wear Out"
}
| null | null | null | null | true | null |
14332
| null |
Default
| null | null |
null |
{
"abstract": " I rebut some erroneous statements and attempt to clear up some\nmisunderstandings in a recent set of critical remarks by Marchildon regarding\nthe Relativistic Transactional Interpretation (RTI), showing that his negative\nconclusions regarding the transactional model are ill-founded.\n",
"title": "Reply to Marchildon: absorption and non-unitarity remain well-defined in the Relativistic Transactional Interpretation"
}
| null | null | null | null | true | null |
14333
| null |
Default
| null | null |
null |
{
"abstract": " We demonstrate that a weakly disordered metal with short-range interactions\nexhibits a transition in the quantum chaotic dynamics when changing the\ntemperature or the interaction strength. For weak interactions, the system\ndisplays exponential growth of the out-of-time-ordered correlator (OTOC) of the\ncurrent operator. The Lyapunov exponent of this growth is\ntemperature-independent in the limit of vanishing interaction. With increasing\nthe temperature or the interaction strength, the system undergoes a transition\nto a non-chaotic behaviour, for which the exponential growth of the OTOC is\nabsent. We conjecture that the transition manifests itself in the quasiparticle\nenergy-level statistics and also discuss ways of its explicit observation in\ncold-atom setups.\n",
"title": "Interaction-induced transition in the quantum chaotic dynamics of a disordered metal"
}
| null | null | null | null | true | null |
14334
| null |
Default
| null | null |
null |
{
"abstract": " This is an epidemiological SIRV model based study that is designed to analyze\nthe impact of vaccination in containing infection spread, in a 4-tiered\npopulation compartment comprised of susceptible, infected, recovered and\nvaccinated agents. While many models assume a lifelong protection through\nvaccination, we focus on the impact of waning immunization due to conversion of\nvaccinated and recovered agents back to susceptible ones. Two asymptotic states\nexist, the \"disease-free equilibrium\" and the \"endemic equilibrium\"; we express\nthe transitions between these states as function of the vaccination and\nconversion rates using the basic reproduction number as a descriptor. We find\nthat the vaccination of newborns and adults have different consequences in\ncontrolling epidemics. We also find that a decaying disease protection within\nthe recovered sub-population is not sufficient to trigger an epidemic at the\nlinear level. Our simulations focus on parameter sets that could model a\ndisease with waning immunization like pertussis. For a diffusively coupled\npopulation, a transition to the endemic state can be initiated via the\npropagation of a traveling infection wave, described successfully within a\nFisher-Kolmogorov framework.\n",
"title": "Epidemiological impact of waning immunization on a vaccinated population"
}
| null | null | null | null | true | null |
14335
| null |
Default
| null | null |
null |
{
"abstract": " We study a model of seed dispersal that considers the inclusion of an animal\ndisperser moving diffusively, feeding on fruits and transporting the seeds,\nwhich are later deposited and capable of germination. The dynamics depends on\nseveral population parameters of growth, decay, harvesting, transport,\ndigestion and germination. In particular, the deposition of transported seeds\nat places away from their collection sites produces a delay in the dynamics,\nwhose effects are the focus of this work. Analytical and numerical solutions of\ndifferent simplified scenarios show the existence of travelling waves. The\neffect of zoochory is apparent in the increase of the velocity of these waves.\nThe results support the hypothesis of the relevance of animal mediated seed\ndispersion when trying to understand the origin of the high rates of vegetable\ninvasion observed in real systems.\n",
"title": "Waves of seed propagation induced by delayed animal dispersion"
}
| null | null | null | null | true | null |
14336
| null |
Default
| null | null |
null |
{
"abstract": " We propose a new Integral Probability Metric (IPM) between distributions: the\nSobolev IPM. The Sobolev IPM compares the mean discrepancy of two distributions\nfor functions (critic) restricted to a Sobolev ball defined with respect to a\ndominant measure $\\mu$. We show that the Sobolev IPM compares two distributions\nin high dimensions based on weighted conditional Cumulative Distribution\nFunctions (CDF) of each coordinate on a leave one out basis. The Dominant\nmeasure $\\mu$ plays a crucial role as it defines the support on which\nconditional CDFs are compared. Sobolev IPM can be seen as an extension of the\none dimensional Von-Mises Cramér statistics to high dimensional\ndistributions. We show how Sobolev IPM can be used to train Generative\nAdversarial Networks (GANs). We then exploit the intrinsic conditioning implied\nby Sobolev IPM in text generation. Finally we show that a variant of Sobolev\nGAN achieves competitive results in semi-supervised learning on CIFAR-10,\nthanks to the smoothness enforced on the critic by Sobolev GAN which relates to\nLaplacian regularization.\n",
"title": "Sobolev GAN"
}
| null | null | null | null | true | null |
14337
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we present a number of robust methodologies for an underwater\nrobot to visually detect, follow, and interact with a diver for collaborative\ntask execution. We design and develop two autonomous diver-following\nalgorithms, the first of which utilizes both spatial- and frequency-domain\nfeatures pertaining to human swimming patterns in order to visually track a\ndiver. The second algorithm uses a convolutional neural network-based model for\nrobust tracking-by-detection. In addition, we propose a hand gesture-based\nhuman-robot communication framework that is syntactically simpler and\ncomputationally more efficient than the existing grammar-based frameworks. In\nthe proposed interaction framework, deep visual detectors are used to provide\naccurate hand gesture recognition; subsequently, a finite-state machine\nperforms robust and efficient gesture-to-instruction mapping. The\ndistinguishing feature of this framework is that it can be easily adopted by\ndivers for communicating with underwater robots without using artificial\nmarkers or requiring memorization of complex language rules. Furthermore, we\nvalidate the performance and effectiveness of the proposed methodologies\nthrough extensive field experiments in closed- and open-water environments.\nFinally, we perform a user interaction study to demonstrate the usability\nbenefits of our proposed interaction framework compared to existing methods.\n",
"title": "Understanding Human Motion and Gestures for Underwater Human-Robot Collaboration"
}
| null | null | null | null | true | null |
14338
| null |
Default
| null | null |
null |
{
"abstract": " We calculate the one-loop electron self-energy correction of order\n$\\alpha\\,(Z\\,\\alpha)^5$ to the bound electron $g$ factor. Our result is in\nagreement with the extrapolated numerical value and paves the way for the\ncalculation of the analogous, but as yet unknown two-loop correction.\n",
"title": "One-loop binding corrections to the electron $g$ factor"
}
| null | null | null | null | true | null |
14339
| null |
Default
| null | null |
null |
{
"abstract": " In this paper we consider the problem of finding periodic solutions of\ncertain Euler-Lagrange equations, which include, among others, equations\ninvolving the $p$-Laplace and, more generality, the $(p,q)$-Laplace operator.\nWe employ the direct method of the calculus of variations in the framework of\nanisotropic Orlicz-Sobolev spaces. These spaces appear to be useful in\nformulating a unified theory of existence for the type of problem considered.\n",
"title": "Periodic solutions of Euler-Lagrange equations in an anisotropic Orlicz-Sobolev space setting"
}
| null | null | null | null | true | null |
14340
| null |
Default
| null | null |
null |
{
"abstract": " We show that for each positive integer $k$ there exist right-angled Artin\ngroups containing free-by-cyclic subgroups whose monodromy automorphisms grow\nas $n^k$. As a consequence we produce examples of right-angled Artin groups\ncontaining finitely presented subgroups whose Dehn functions grow as $n^{k+2}$.\n",
"title": "Dehn functions of subgroups of right-angled Artin groups"
}
| null | null | null | null | true | null |
14341
| null |
Default
| null | null |
null |
{
"abstract": " Many real world practical problems can be formulated as\n$\\ell_{0}$-minimization problems with nonnegativity constraints, which seek the\nsparsest nonnegative signals to underdetermined linear systems. They have been\nwidely applied in signal and image processing, machine learning, pattern\nrecognition and computer vision. Unfortunately, this $\\ell_{0}$-minimization\nproblem with nonnegativity constraint is computational and NP-hard because of\nthe discrete and discontinuous nature of the $\\ell_{0}$-norm. In this paper, we\nreplace the $\\ell_{0}$-norm with a non-convex fraction function, and study the\nminimization problem of this non-convex fraction function in recovering the\nsparse nonnegative signals from an underdetermined linear system. Firstly, we\ndiscuss the equivalence between $(P_{0}^{\\geq})$ and $(FP_{a}^{\\geq})$, and the\nequivalence between $(FP_{a}^{\\geq})$ and $(FP_{a,\\lambda}^{\\geq})$. It is\nproved that the optimal solution of the problem $(P_{0}^{\\geq})$ could be\napproximately obtained by solving the regularization problem\n$(FP_{a,\\lambda}^{\\geq})$ if some specific conditions satisfied. Secondly, we\npropose a nonnegative iterative thresholding algorithm to solve the\nregularization problem $(FP_{a,\\lambda}^{\\geq})$ for all $a>0$. Finally, some\nnumerical experiments on sparse nonnegative siganl recovery problems show that\nour method performs effective in finding sparse nonnegative signals compared\nwith the linear programming.\n",
"title": "Recovering Sparse Nonnegative Signals via Non-convex Fraction Function Penalty"
}
| null | null | null | null | true | null |
14342
| null |
Default
| null | null |
null |
{
"abstract": " In various economic environments, people observe those with whom they\nstrategically interact. We can model such information-sharing relations as an\ninformation network, and the strategic interactions as a game on the network.\nWhen any two agents in the network are connected either directly or indirectly,\nempirical modeling using an equilibrium approach is cumbersome, since the\ntestable implications from an equilibrium generally involve all the players of\nthe game, whereas a researcher's data set may contain only a fraction of these\nplayers in practice. This paper develops a tractable empirical model of linear\ninteractions where each agent, after observing part of his neighbors' types,\nnot knowing the full information network, uses best responses that are linear\nin his and other players' types that he observes, based on simple beliefs about\nother players' strategies. We provide conditions on information networks and\nbeliefs such that best responses take an explicit form with multiple intuitive\nfeatures. Furthermore, the best responses reveal how local payoff\ninterdependence among agents is translated into local stochastic dependence of\ntheir actions, allowing the econometrician to perform asymptotic inference\nwithout having to observe all the players in the game or having to know\nprecisely the sampling process.\n",
"title": "Estimating Local Interactions Among Many Agents Who Observe Their Neighbors"
}
| null | null | null | null | true | null |
14343
| null |
Default
| null | null |
null |
{
"abstract": " This paper proposes a new architecture for speaker adaptation of\nmulti-speaker neural-network speech synthesis systems, in which an unseen\nspeaker's voice can be built using a relatively small amount of speech data\nwithout transcriptions. This is sometimes called \"unsupervised speaker\nadaptation\". More specifically, we concatenate the layers to the audio inputs\nwhen performing unsupervised speaker adaptation while we concatenate them to\nthe text inputs when synthesizing speech from text. Two new training schemes\nfor the new architecture are also proposed in this paper. These training\nschemes are not limited to speech synthesis, other applications are suggested.\nExperimental results show that the proposed model not only enables adaptation\nto unseen speakers using untranscribed speech but it also improves the\nperformance of multi-speaker modeling and speaker adaptation using transcribed\naudio files.\n",
"title": "Multimodal speech synthesis architecture for unsupervised speaker adaptation"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
14344
| null |
Validated
| null | null |
null |
{
"abstract": " The purpose of this note is to explain what is \"analytical history\", a\nmodular and testable analysis of historical events introduced in a book\npublished in 2002 (Roehner and Syme 2002). Broadly speaking, it is a\ncomparative methodology for the analysis of historical events. Comparison is\nthe keystone and hallmark of science. For instance, the extrasolar planets are\ncrucial for understanding our own solar system. Until their discovery,\nastronomers could observe only one instance. Single instances can be described\nbut they cannot be understood in a testable way. In other words, if one accepts\nthat, as many historians say, \"historical events are unique\", then no testable\nunderstanding can be developed.\n",
"title": "Analytical history"
}
| null | null |
[
"Physics"
] | null | true | null |
14345
| null |
Validated
| null | null |
null |
{
"abstract": " This paper presents a framework for automatic synthesis of a control sequence\nfor multi-agent systems governed by continuous linear dynamics under timed\nconstraints. First, the motion of the agents in the workspace is abstracted\ninto individual Transition Systems (TS). Second, each agent is assigned with an\nindividual formula given in Metric Interval Temporal Logic (MITL) and in\nparallel, the team of agents is assigned with a collaborative team formula. The\nproposed method is based on a correct-by-construction control synthesis method,\nand hence guarantees that the resulting closed-loop system will satisfy the\nspecifications. The specifications considers boolean-valued properties under\nreal-time. Extended simulations has been performed in order to demonstrate the\nefficiency of the proposed controllers.\n",
"title": "Control Synthesis for Multi-Agent Systems under Metric Interval Temporal Logic Specifications"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14346
| null |
Validated
| null | null |
null |
{
"abstract": " In the first part of this paper we establish a uniqueness result for\ncontinuity equations with velocity field whose derivative can be represented by\na singular integral operator of an $L^1$ function, extending the Lagrangian\ntheory in \\cite{BouchutCrippa13}. The proof is based on a combination of a\nstability estimate via optimal transport techniques developed in \\cite{Seis16a}\nand some tools from harmonic analysis introduced in \\cite{BouchutCrippa13}. In\nthe second part of the paper, we address a question that arose in\n\\cite{FilhoMazzucatoNussenzveig06}, namely whether 2D Euler solutions obtained\nvia vanishing viscosity are renormalized (in the sense of DiPerna and Lions)\nwhen the initial data has low integrability. We show that this is the case even\nwhen the initial vorticity is only in~$L^1$, extending the proof for the $L^p$\ncase in \\cite{CrippaSpirito15}.\n",
"title": "Eulerian and Lagrangian solutions to the continuity and Euler equations with $L^1$ vorticity"
}
| null | null | null | null | true | null |
14347
| null |
Default
| null | null |
null |
{
"abstract": " Recent versions of the observed cosmic star-formation history (SFH) have\nresolved an inconsistency with the stellar mass density history. We show that\nthe revised SFH also scales up the delay-time distribution (DTD) of Type Ia\nsupernovae (SNe Ia), as determined from the observed volumetric SN Ia rate\nhistory, aligning it with other field-galaxy SN Ia DTD measurements. The\nrevised-SFH-based DTD has a $t^{-1.1 \\pm 0.1}$ form and a\nHubble-time-integrated production efficiency of $N/M_\\star=1.3\\pm0.1$ SNe Ia\nper $1000~{\\rm M_\\odot}$ of formed stellar mass. Using these revised histories\nand updated empirical iron yields of the various SN types, we re-derive the\ncosmic iron accumulation history. Core-collapse SNe and SNe Ia have contributed\nabout equally to the total mass of iron in the Universe today. We find the\ntrack of the average cosmic gas element in the [$\\alpha$/Fe] vs. [Fe/H]\nabundance-ratio plane. The track is broadly similar to the observed main locus\nof Galactic stars in this plane, indicating a Milky Way (MW) SFH similar in\nform to the cosmic one. We easily find a simple MW SFH that makes the track\nclosely match this stellar locus. Galaxy clusters appear to have a\nhigher-normalization DTD. This cluster DTD, combined with a short-burst MW SFH\npeaked at $z=3$, produces a track that matches remarkably well the observed\n\"high-$\\alpha$\" locus of MW stars, suggesting the halo/thick-disk population\nhas had a galaxy-cluster-like formation mode. Thus, a simple two-component SFH,\ncombined with empirical DTDs and SN iron yields, suffices to closely reproduce\nthe MW's stellar abundance patterns.\n",
"title": "Star formation, supernovae, iron, and alpha: consistent cosmic and Galactic histories"
}
| null | null | null | null | true | null |
14348
| null |
Default
| null | null |
null |
{
"abstract": " ALFABURST has been searching for Fast Radio Bursts (FRBs) commensally with\nother projects using the Arecibo L-band Feed Array (ALFA) receiver at the\nArecibo Observatory since July 2015. We describe the observing system and\nreport on the non-detection of any FRBs from that time until August 2017 for a\ntotal observing time of 518 hours. With current FRB rate models, along with\nmeasurements of telescope sensitivity and beam size, we estimate that this\nsurvey probed redshifts out to about 3.4 with an effective survey volume of\naround 600,000 Mpc$^3$. Based on this, we would expect, at the 99% confidence\nlevel, to see at most two FRBs. We discuss the implications of this\nnon-detection in the context of results from other telescopes and the\nlimitation of our search pipeline. During the survey, single pulses from 17\nknown pulsars were detected. We also report the discovery of a Galactic radio\ntransient with a pulse width of 3 ms and dispersion measure of 281 pc\ncm$^{-3}$, which was detected while the telescope was slewing between fields.\n",
"title": "ALFABURST: A commensal search for Fast Radio Bursts with Arecibo"
}
| null | null |
[
"Physics"
] | null | true | null |
14349
| null |
Validated
| null | null |
null |
{
"abstract": " Graphitic carbon nitride nanosheets are among 2D attractive materials due to\npresenting unusual physicochemical properties.Nevertheless, no adequate\ninformation exists about their mechanical and thermal properties. Therefore, we\nused classical molecular dynamics simulations to explore the thermal\nconductivity and mechanical response of two main structures of single-layer\ntriazine-basedg-C3N4 films.By performing uniaxial tensile modeling, we found\nremarkable elastic modulus of 320 and 210 GPa, and tensile strength of 47 GPa\nand 30 GPa for two different structures of g-C3N4sheets. Using equilibrium\nmolecular dynamics simulations, the thermal conductivity of free-standing\ng-C3N4 structures were also predicted to be around 7.6 W/mK and 3.5 W/mK. Our\nstudy suggests the g-C3N4films as exciting candidate for reinforcement of\npolymeric materials mechanical properties.\n",
"title": "Mechanical properties and thermal conductivity of graphitic carbon nitride: A molecular dynamics study"
}
| null | null | null | null | true | null |
14350
| null |
Default
| null | null |
null |
{
"abstract": " In this paper we develop a way of obtaining Green's functions for partial\ndifferential equations with linear involutions by reducing the equation to a\nhigher-order PDE without involutions. The developed theory is applied to a\nmodel of heat transfer in a conducting plate which is bent in half.\n",
"title": "Green's Functions of Partial Differential Equations with Involutions"
}
| null | null | null | null | true | null |
14351
| null |
Default
| null | null |
null |
{
"abstract": " The main object of this article is to present an extension of the\nzero-inflated Poisson-Lindley distribution, called of zero-modified\nPoisson-Lindley. The additional parameter $\\pi$ of the zero-modified\nPoisson-Lindley has a natural interpretation in terms of either\nzero-deflated/inflated proportion. Inference is dealt with by using the\nlikelihood approach. In particular the maximum likelihood estimators of the\ndistribution's parameter are compared in small and large samples. We also\nconsider an alternative bias-correction mechanism based on Efron's bootstrap\nresampling. The model is applied to real data sets and found to perform better\nthan other competing models.\n",
"title": "Zero-Modified Poisson-Lindley distribution with applications in zero-inflated and zero-deflated count data"
}
| null | null | null | null | true | null |
14352
| null |
Default
| null | null |
null |
{
"abstract": " It was recently shown that the phase retrieval imaging of a sample can be\nmodeled as a simple convolution process. Sometimes, such a convolution depends\non physical parameters of the sample which are difficult to estimate a priori.\nIn this case, a blind choice for those parameters usually lead to wrong\nresults, e.g., in posterior image segmentation processing. In this manuscript,\nwe propose a simple connection between phase-retrieval algorithms and\noptimization strategies, which lead us to ways of numerically determining the\nphysical parameters\n",
"title": "Phase-Retrieval as a Regularization Problem"
}
| null | null | null | null | true | null |
14353
| null |
Default
| null | null |
null |
{
"abstract": " The VIS instrument on board the Euclid mission is a weak-lensing experiment\nthat depends on very precise shape measurements of distant galaxies obtained by\na large CCD array. Due to the harsh radiative environment outside the Earth's\natmosphere, it is anticipated that the CCDs over the mission lifetime will be\ndegraded to an extent that these measurements will only be possible through the\ncorrection of radiation damage effects. We have therefore created a Monte Carlo\nmodel that simulates the physical processes taking place when transferring\nsignal through a radiation-damaged CCD. The software is based on\nShockley-Read-Hall theory, and is made to mimic the physical properties in the\nCCD as closely as possible. The code runs on a single electrode level and takes\nthree dimensional trap position, potential structure of the pixel, and\nmulti-level clocking into account. A key element of the model is that it also\ntakes device specific simulations of electron density as a direct input,\nthereby avoiding to make any analytical assumptions about the size and density\nof the charge cloud. This paper illustrates how test data and simulated data\ncan be compared in order to further our understanding of the positions and\nproperties of the individual radiation-induced traps.\n",
"title": "Comparing simulations and test data of a radiation damaged charge-couple device for the Euclid mission"
}
| null | null |
[
"Physics"
] | null | true | null |
14354
| null |
Validated
| null | null |
null |
{
"abstract": " For a set of points in the plane, a \\emph{crossing family} is a set of line\nsegments, each joining two of the points, such that any two line segments\ncross. We investigate the following generalization of crossing families: a\n\\emph{spoke set} is a set of lines drawn through a point set such that each\nunbounded region of the induced line arrangement contains at least one point of\nthe point set. We show that every point set has a spoke set of size\n$\\sqrt{\\frac{n}{8}}$. We also characterize the matchings obtained by selecting\nexactly one point in each unbounded region and connecting every such point to\nthe point in the antipodal unbounded region.\n",
"title": "A generalization of crossing families"
}
| null | null | null | null | true | null |
14355
| null |
Default
| null | null |
null |
{
"abstract": " Multinational corporations use highly complex structures of parents and\nsubsidiaries to organize their operations and ownership. Offshore Financial\nCenters (OFCs) facilitate these structures through low taxation and lenient\nregulation, but are increasingly under scrutiny, for instance for enabling tax\navoidance. Therefore, the identification of OFC jurisdictions has become a\npoliticized and contested issue. We introduce a novel data-driven approach for\nidentifying OFCs based on the global corporate ownership network, in which over\n98 million firms (nodes) are connected through 71 million ownership relations.\nThis granular firm-level network data uniquely allows identifying both\nsink-OFCs and conduit-OFCs. Sink-OFCs attract and retain foreign capital while\nconduit-OFCs are attractive intermediate destinations in the routing of\ninternational investments and enable the transfer of capital without taxation.\nWe identify 24 sink-OFCs. In addition, a small set of five countries -- the\nNetherlands, the United Kingdom, Ireland, Singapore and Switzerland -- canalize\nthe majority of corporate offshore investment as conduit-OFCs. Each conduit\njurisdiction is specialized in a geographical area and there is significant\nspecialization based on industrial sectors. Against the idea of OFCs as exotic\nsmall islands that cannot be regulated, we show that many sink and conduit-OFCs\nare highly developed countries.\n",
"title": "Uncovering Offshore Financial Centers: Conduits and Sinks in the Global Corporate Ownership Network"
}
| null | null | null | null | true | null |
14356
| null |
Default
| null | null |
null |
{
"abstract": " Magnetised exoplanets are expected to emit at radio frequencies analogously\nto the radio auroral emission of Earth and Jupiter. We predict the radio\nemission from V830 Tau b, the youngest (2 Myr) detected exoplanet to date. We\nmodel the host star wind using 3DMHD simulations that take into account its\nsurface magnetism. With this, we constrain the local conditions around V830 Tau\nb that we use to then compute its radio emission. We estimate average radio\nflux densities of 6 to 24mJy, depending on the assumed radius of the planet\n(one or two Rjupiter). These radio fluxes are present peaks that are up to\ntwice the average values. We show here that these fluxes are weakly dependent\n(a factor of 1.8) on the assumed polar planetary magnetic field (10 to 100G),\nopposed to the maximum frequency of the emission, which ranges from 18 to\n240MHz. We also estimate the thermal radio emission from the stellar wind. By\ncomparing our results with VLA and VLBA observations of the system, we\nconstrain the stellar mass-loss rate to be <3e-9 Msun/yr, with likely values\nbetween ~1e-12 and 1e-10 Msun/yr. The frequency-dependent extension of the\nradio-emitting wind is around ~ 3 to 30 Rstar for frequencies in the range of\n275 to 50MHz, implying that V830 Tau b, at an orbital distance of 6.1 Rstar,\ncould be embedded in the regions of the host star's wind that are optically\nthick to radio wavelengths, but not deeply so. Planetary emission can only\npropagate in the stellar wind plasma if the frequency of the cyclotron emission\nexceeds the stellar wind plasma frequency. For that, we find that for planetary\nradio emission to propagate through the host star wind, planetary magnetic\nfield strengths larger than ~1.3 to 13 G are required. The V830 Tau system is a\nvery interesting system for conducting radio observations from both the\nperspective of radio emission from the planet as well as from the host star's\nwind.\n",
"title": "Predicting radio emission from the newborn hot Jupiter V830 Tau and its host star"
}
| null | null | null | null | true | null |
14357
| null |
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| null | null |
null |
{
"abstract": " We present a new algorithm having a time complexity of O(N log N) and\ndesigned to retrieve the phase at which an input signal and a set of not\nnecessarily orthogonal templates match best in a weighted chi-squared sense.\nThe proposed implementation is based on an orthogonalization algorithm and thus\nalso benefits from high numerical stability. We apply this method successfully\nto the redshift determination of quasars from the twelfth Sloan Digital Sky\nSurvey (SDSS) quasar catalogue and derive the proper spectral reduction and\nredshift selection methods. Derivations of the redshift uncertainty and the\nassociated confidence are also provided. The results of this application are\ncomparable to the performance of the SDSS pipeline, while not having a\nquadratic time dependence.\n",
"title": "Redshift determination through weighted phase correlation: a linearithmic implementation"
}
| null | null |
[
"Physics"
] | null | true | null |
14358
| null |
Validated
| null | null |
null |
{
"abstract": " Clinically-relevant forms of acute cell injury, which include stroke and\nmyocardial infarction, have been of long-lasting challenge in terms of\nsuccessful intervention and treatments. Although laboratory studies have shown\nit is possible to decrease cell death after such injuries, human clinical\ntrials based on laboratory therapies have generally failed. We suggested these\nfailures are due, at least partially, to the lack of a quantitative theoretical\nframework for acute cell injury. Here we provide a systematic study on a\nnonlinear dynamical model of acute cell injury and characterize the global\ndynamics of a nonautonomous version of the theory. The nonautonomous model\ngives rise to four qualitative types of dynamical patterns that can be mapped\nto the behavior of cells after clinical acute injuries. In addition, the\nconcept of a maximum total intrinsic stress response, $S_{max}^*$, emerges from\nthe nonautonomous theory. A continuous transition across the four qualitative\npatterns has been observed, which sets a natural range for initial conditions.\nUnder these initial conditions in the parameter space tested, the total induced\nstress response can be increased to 2.5-11 folds of $S_{max}^*$. This result\nindicates that cells possess a reserve stress response capacity which provides\na theoretical explanation of how therapies can prevent cell death after lethal\ninjuries. This nonautonomous theory of acute cell injury thus provides a\nquantitative framework for understanding cell death and recovery and developing\neffective therapeutics for acute injury.\n",
"title": "Nonautonomous Dynamics of Acute Cell Injury"
}
| null | null | null | null | true | null |
14359
| null |
Default
| null | null |
null |
{
"abstract": " A two-step photoionization strategy of an ultracold rubidium beam for\napplication in a focused ion beam instrument is analyzed and implemented. In\nthis strategy the atomic beam is partly selected with an aperture after which\nthe transmitted atoms are ionized in the overlap of a tightly cylindrically\nfocused excitation laser beam and an ionization laser beam whose power is\nenhanced in a build-up cavity. The advantage of this strategy, as compared to\nwithout the use of a build-up cavity, is that higher ionization degrees can be\nreached at higher currents. Optical Bloch equations including the\nphotoionization process are used to calculate what ionization degree and\nionization position distribution can be reached. Furthermore, the ionization\nstrategy is tested on an ultracold beam of $^{85}$Rb atoms. The beam current is\nmeasured as a function of the excitation and ionization laser beam intensity\nand the selection aperture size. Although details are different, the global\ntrends of the measurements agree well with the calculation. With a selection\naperture diameter of 52 $\\mu$m, a current of $\\left(170\\pm4\\right)$ pA is\nmeasured, which according to calculations is 63% of the current equivalent of\nthe transmitted atomic flux. Taking into account the ionization degree the ion\nbeam peak reduced brightness is estimated at $1\\times10^7$ A/(m$^2\\,$sr$\\,$eV).\n",
"title": "Cavity-enhanced photoionization of an ultracold rubidium beam for application in focused ion beams"
}
| null | null | null | null | true | null |
14360
| null |
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| null | null |
null |
{
"abstract": " The purpose of the present paper is to investigate a fusion rule algebra\narising from irreducible characters of a compact group $G$ and a closed\nsubgroup $G_0$ of $G$ with finite index. The convolution of this fusion rule\nalgebra is introduced by inducing irreducible representations of $G_0$ to $G$\nand by restricting irreducible representations of $G$ to $G_0$.\n",
"title": "Fusion rule algebras related to a pair of compact groups"
}
| null | null | null | null | true | null |
14361
| null |
Default
| null | null |
null |
{
"abstract": " In this paper we study moment sequences of matrix-valued measures on compact\nintervals. A complete parametrization of such sequences is obtained via a\nsymmetric version of matricial canonical moments. Furthermore, distinguished\nextensions of finite moment sequences are characterized in this framework. The\nresults are applied to the underlying matrix-valued measures, generalizing some\nresults from the scalar theory of canonical moments.\n",
"title": "Matricial Canonical Moments and Parametrization of Matricial Hausdorff Moment Sequences"
}
| null | null | null | null | true | null |
14362
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we propose a novel explanation module to explain the\npredictions made by a deep network. The explanation module works by embedding a\nhigh-dimensional deep network layer nonlinearly into a low-dimensional\nexplanation space while retaining faithfulness, so that the original deep\nlearning predictions can be constructed from the few concepts extracted by the\nexplanation module. We then visualize such concepts for human to learn about\nthe high-level concepts that deep learning is using to make decisions. We\npropose an algorithm called Sparse Reconstruction Autoencoder (SRAE) for\nlearning the embedding to the explanation space. SRAE aims to reconstruct part\nof the original feature space while retaining faithfulness. A pull-away term is\napplied to SRAE to make the explanation space more orthogonal. A visualization\nsystem is then introduced for human understanding of the features in the\nexplanation space. The proposed method is applied to explain CNN models in\nimage classification tasks, and several novel metrics are introduced to\nevaluate the performance of explanations quantitatively without human\ninvolvement. Experiments show that the proposed approach generates interesting\nexplanations of the mechanisms CNN use for making predictions.\n",
"title": "Embedding Deep Networks into Visual Explanations"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14363
| null |
Validated
| null | null |
null |
{
"abstract": " Dynamic models and statistical inference for the diffusion of information in\nsocial networks is an area which has witnessed remarkable progress in the last\ndecade due to the proliferation of social networks. Modeling and inference of\ndiffusion of information has applications in targeted advertising and\nmarketing, forecasting elections, predicting investor sentiment and identifying\nepidemic outbreaks. This chapter discusses three important aspects related to\ninformation diffusion in social networks: (i) How does observation bias named\nfriendship paradox (a graph theoretic consequence) and monophilic contagion\n(influence of friends of friends) affect information diffusion dynamics. (ii)\nHow can social networks adapt their structural connectivity depending on the\nstate of information diffusion. (iii) How one can estimate the state of the\nnetwork induced by information diffusion. The motivation for all three topics\nconsidered in this chapter stems from recent findings in network science and\nsocial sensing. Further, several directions for future research that arise from\nthese topics are also discussed.\n",
"title": "Information Diffusion in Social Networks: Friendship Paradox based Models and Statistical Inference"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14364
| null |
Validated
| null | null |
null |
{
"abstract": " Pre-training of models in pruning algorithms plays an important role in\npruning decision-making. We find that excessive pre-training is not necessary\nfor pruning algorithms. According to this idea, we propose a pruning\nalgorithm---Incremental pruning based on less training (IPLT). Compared with\nthe traditional pruning algorithm based on a large number of pre-training, IPLT\nhas competitive compression effect than the traditional pruning algorithm under\nthe same simple pruning strategy. On the premise of ensuring accuracy, IPLT can\nachieve 8x-9x compression for VGG-19 on CIFAR-10 and only needs to pre-train\nfew epochs. For VGG-19 on CIFAR-10, we can not only achieve 10 times test\nacceleration, but also about 10 times training acceleration. At present, the\nresearch mainly focuses on the compression and acceleration in the application\nstage of the model, while the compression and acceleration in the training\nstage are few. We newly proposed a pruning algorithm that can compress and\naccelerate in the training stage. It is novel to consider the amount of\npre-training required by pruning algorithm. Our results have implications: Too\nmuch pre-training may be not necessary for pruning algorithms.\n",
"title": "Really should we pruning after model be totally trained? Pruning based on a small amount of training"
}
| null | null | null | null | true | null |
14365
| null |
Default
| null | null |
null |
{
"abstract": " Semantic segmentation constitutes an integral part of medical image analyses\nfor which breakthroughs in the field of deep learning were of high relevance.\nThe large number of trainable parameters of deep neural networks however\nrenders them inherently data hungry, a characteristic that heavily challenges\nthe medical imaging community. Though interestingly, with the de facto standard\ntraining of fully convolutional networks (FCNs) for semantic segmentation being\nagnostic towards the `structure' of the predicted label maps, valuable\ncomplementary information about the global quality of the segmentation lies\nidle. In order to tap into this potential, we propose utilizing an adversarial\nnetwork which discriminates between expert and generated annotations in order\nto train FCNs for semantic segmentation. Because the adversary constitutes a\nlearned parametrization of what makes a good segmentation at a global level, we\nhypothesize that the method holds particular advantages for segmentation tasks\non complex structured, small datasets. This holds true in our experiments: We\nlearn to segment aggressive prostate cancer utilizing MRI images of 152\npatients and show that the proposed scheme is superior over the de facto\nstandard in terms of the detection sensitivity and the dice-score for\naggressive prostate cancer. The achieved relative gains are shown to be\nparticularly pronounced in the small dataset limit.\n",
"title": "Adversarial Networks for the Detection of Aggressive Prostate Cancer"
}
| null | null | null | null | true | null |
14366
| null |
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| null | null |
null |
{
"abstract": " The main purpose of this paper is to study multi-parameter singular integral\noperators which commute with Zygmund dilations. We introduce a class of\nsingular integral operators associated with Zygmund dilations and show the\nboundedness for these operators on $L^p, 1<p<\\infty$, which covers those\nstudied by Ricci--Stein \\cite{RS} and Nagel--Wainger \\cite{NW}\n",
"title": "A class of singular integrals associated with Zygmund dilations"
}
| null | null | null | null | true | null |
14367
| null |
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| null | null |
null |
{
"abstract": " High-resolution observations of the solar chromosphere and transition region\noften reveal surge-like oscillatory activities above sunspot light bridges.\nThese oscillations are often interpreted as intermittent plasma jets produced\nby quasi-periodic magnetic reconnection. We have analyzed the oscillations\nabove a light bridge in a sunspot using data taken by the Interface Region\nImaging Spectrograph (IRIS). The chromospheric 2796\\AA{}~images show surge-like\nactivities above the entire light bridge at any time, forming an oscillating\nwall. Within the wall we often see that the Mg~{\\sc{ii}}~k 2796.35\\AA{}~line\ncore first experiences a large blueshift, and then gradually decreases to zero\nshift before increasing to a red shift of comparable magnitude. Such a behavior\nsuggests that the oscillations are highly nonlinear and likely related to\nshocks. In the 1400\\AA{}~passband which samples emission mainly from the\nSi~{\\sc{iv}}~ion, the most prominent feature is a bright oscillatory front\nahead of the surges. We find a positive correlation between the acceleration\nand maximum velocity of the moving front, which is consistent with numerical\nsimulations of upward propagating slow-mode shock waves. The Si~{\\sc{iv}}\n1402.77\\AA{}~line profile is generally enhanced and broadened in the bright\nfront, which might be caused by turbulence generated through compression or by\nthe shocks. These results, together with the fact that the oscillation period\nstays almost unchanged over a long duration, lead us to propose that the\nsurge-like oscillations above light bridges are caused by shocked p-mode waves\nleaked from the underlying photosphere.\n",
"title": "Surge-like oscillations above sunspot light bridges driven by magnetoacoustic shocks"
}
| null | null | null | null | true | null |
14368
| null |
Default
| null | null |
null |
{
"abstract": " Let $Di\\langle X\\rangle$ be the free dialgebra over a field generated by a\nset $X$. Let $S$ be a monic subset of $Di\\langle X\\rangle$. A\nComposition-Diamond lemma for dialgebras is firstly established by Bokut, Chen\nand Liu in 2010 \\cite{Di} which claims that if (i) $S$ is a\nGröbner-Shirshov basis in $Di\\langle X\\rangle$, then (ii) the set of\n$S$-irreducible words is a linear basis of the quotient dialgebra $Di\\langle X\n\\mid S \\rangle$, but not conversely. Such a lemma based on a fixed ordering on\nnormal diwords of $Di\\langle X\\rangle$ and special definition of composition\ntrivial modulo $S$. In this paper, by introducing an arbitrary monomial-center\nordering and the usual definition of composition trivial modulo $S$, we give a\nnew Composition-Diamond lemma for dialgebras which makes the conditions (i) and\n(ii) equivalent. We show that every ideal of $Di\\langle X\\rangle$ has a unique\nreduced Gröbner-Shirshov basis. The new lemma is more useful and convenient\nthan the one in \\cite{Di}. As applications, we give a method to find normal\nforms of elements of an arbitrary disemigroup, in particular, A.V. Zhuchok's\n(2010) and Y.V. Zhuchok's (2015) normal forms of the free commutative\ndisemigroups and the free abelian disemigroups, and normal forms of the free\nleft (right) commutative disemigroups.\n",
"title": "A new Composition-Diamond lemma for dialgebras"
}
| null | null | null | null | true | null |
14369
| null |
Default
| null | null |
null |
{
"abstract": " Discrete event simulators, such as OMNeT++, provide fast and convenient\nmethods for the assessment of algorithms and protocols, especially in the\ncontext of wired and wireless networks. Usually, simulation parameters such as\ntopology and traffic patterns are predefined to observe the behaviour\nreproducibly. However, for learning about the dynamic behaviour of a system, a\nlive interaction that allows changing parameters on the fly is very helpful.\nThis is especially interesting for providing interactive demonstrations at\nconferences and fairs. In this paper, we present a remote interface to OMNeT++\nsimulations that can be used to control the simulations while visualising\nreal-time data merged from multiple OMNeT++ instances. We explain the software\narchitecture behind our framework and how it can be used to build\ndemonstrations on the foundation of OMNeT++.\n",
"title": "A Remote Interface for Live Interaction with OMNeT++ Simulations"
}
| null | null | null | null | true | null |
14370
| null |
Default
| null | null |
null |
{
"abstract": " Social messages classification is a research domain that has attracted the\nattention of many researchers in these last years. Indeed, the social message\nis different from ordinary text because it has some special characteristics\nlike its shortness. Then the development of new approaches for the processing\nof the social message is now essential to make its classification more\nefficient. In this paper, we are mainly interested in the classification of\nsocial messages based on their spreading on online social networks (OSN). We\nproposed a new distance metric based on the Dynamic Time Warping distance and\nwe use it with the probabilistic and the evidential k Nearest Neighbors (k-NN)\nclassifiers to classify propagation networks (PrNets) of messages. The\npropagation network is a directed acyclic graph (DAG) that is used to record\npropagation traces of the message, the traversed links and their types. We\ntested the proposed metric with the chosen k-NN classifiers on real world\npropagation traces that were collected from Twitter social network and we got\ngood classification accuracies.\n",
"title": "Dynamic time warping distance for message propagation classification in Twitter"
}
| null | null | null | null | true | null |
14371
| null |
Default
| null | null |
null |
{
"abstract": " The 3rd International Workshop on Overlay Architectures for FPGAs (OLAF 2017)\nwas held on 22 Feb, 2017 as a co-located workshop at the 25th ACM/SIGDA\nInternational Symposium on Field-Programmable Gate Arrays (FPGA 2017). This\nyear, the program committee selected 3 papers and 3 extended abstracts to be\npresented at the workshop, which are subsequently collected in this online\nvolume.\n",
"title": "Proceedings of the 3rd International Workshop on Overlay Architectures for FPGAs (OLAF 2017)"
}
| null | null | null | null | true | null |
14372
| null |
Default
| null | null |
null |
{
"abstract": " Type 2 diabetes mellitus (T2DM) is a chronic disease that often results in\nmultiple complications. Risk prediction and profiling of T2DM complications is\ncritical for healthcare professionals to design personalized treatment plans\nfor patients in diabetes care for improved outcomes. In this paper, we study\nthe risk of developing complications after the initial T2DM diagnosis from\nlongitudinal patient records. We propose a novel multi-task learning approach\nto simultaneously model multiple complications where each task corresponds to\nthe risk modeling of one complication. Specifically, the proposed method\nstrategically captures the relationships (1) between the risks of multiple T2DM\ncomplications, (2) between the different risk factors, and (3) between the risk\nfactor selection patterns. The method uses coefficient shrinkage to identify an\ninformative subset of risk factors from high-dimensional data, and uses a\nhierarchical Bayesian framework to allow domain knowledge to be incorporated as\npriors. The proposed method is favorable for healthcare applications because in\nadditional to improved prediction performance, relationships among the\ndifferent risks and risk factors are also identified. Extensive experimental\nresults on a large electronic medical claims database show that the proposed\nmethod outperforms state-of-the-art models by a significant margin.\nFurthermore, we show that the risk associations learned and the risk factors\nidentified lead to meaningful clinical insights.\n",
"title": "Simultaneous Modeling of Multiple Complications for Risk Profiling in Diabetes Care"
}
| null | null | null | null | true | null |
14373
| null |
Default
| null | null |
null |
{
"abstract": " In this article, we study the Kapustin-Witten equations on a closed,\nsimply-connected, four-manifold. We using a compactness theorem due to Taubes\nto prove that if $(A,\\phi)$ is a solution of Kapustin-Witten equations and the\nconnection $A$ is closed to a $generic$ ASD connection $A_{\\infty}$, then\n$(A,\\phi)$ must be a trivial solution. We also prove that the moduli space of\nthe solutions of Kapustin-Witten equations is non-connected if the connections\non the compactification of moduli space of ASD connections are all $generic$.\nAs one application, we extend the ideas of Kapustin-Witten equations to other\nequations on gauge theory-- Hitchin-Simpson equations and Vafa-Witten on\ncompact Kähler surface with a Kähler metric $g$.\n",
"title": "On a topology property for moduli space of Kapustin-Witten equations"
}
| null | null |
[
"Mathematics"
] | null | true | null |
14374
| null |
Validated
| null | null |
null |
{
"abstract": " A fundamental challenge in developing semantic parsers is the paucity of\nstrong supervision in the form of language utterances annotated with logical\nform. In this paper, we propose to exploit structural regularities in language\nin different domains, and train semantic parsers over multiple knowledge-bases\n(KBs), while sharing information across datasets. We find that we can\nsubstantially improve parsing accuracy by training a single\nsequence-to-sequence model over multiple KBs, when providing an encoding of the\ndomain at decoding time. Our model achieves state-of-the-art performance on the\nOvernight dataset (containing eight domains), improves performance over a\nsingle KB baseline from 75.6% to 79.6%, while obtaining a 7x reduction in the\nnumber of model parameters.\n",
"title": "Neural Semantic Parsing over Multiple Knowledge-bases"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14375
| null |
Validated
| null | null |
null |
{
"abstract": " There have been many discriminative learning methods using convolutional\nneural networks (CNN) for several image restoration problems, which learn the\nmapping function from a degraded input to the clean output. In this letter, we\npropose a self-committee method that can find enhanced restoration results from\nthe multiple trial of a trained CNN with different but related inputs.\nSpecifically, it is noted that the CNN sometimes finds different mapping\nfunctions when the input is transformed by a reversible transform and thus\nproduces different but related outputs with the original. Hence averaging the\noutputs for several different transformed inputs can enhance the results as\nevidenced by the network committee methods. Unlike the conventional committee\napproaches that require several networks, the proposed method needs only a\nsingle network. Experimental results show that adding an additional transform\nas a committee always brings additional gain on image denoising and single\nimage supre-resolution problems.\n",
"title": "Self-Committee Approach for Image Restoration Problems using Convolutional Neural Network"
}
| null | null | null | null | true | null |
14376
| null |
Default
| null | null |
null |
{
"abstract": " Differential Privacy (DP) has received increasing attention as a rigorous\nprivacy framework. Many existing studies employ traditional DP mechanisms\n(e.g., the Laplace mechanism) as primitives to continuously release private\ndata for protecting privacy at each time point (i.e., event-level privacy),\nwhich assume that the data at different time points are independent, or that\nadversaries do not have knowledge of correlation between data. However,\ncontinuously generated data tend to be temporally correlated, and such\ncorrelations can be acquired by adversaries. In this paper, we investigate the\npotential privacy loss of a traditional DP mechanism under temporal\ncorrelations. First, we analyze the privacy leakage of a DP mechanism under\ntemporal correlation that can be modeled using Markov Chain. Our analysis\nreveals that, the event-level privacy loss of a DP mechanism may\n\\textit{increase over time}. We call the unexpected privacy loss\n\\textit{temporal privacy leakage} (TPL). Although TPL may increase over time,\nwe find that its supremum may exist in some cases. Second, we design efficient\nalgorithms for calculating TPL. Third, we propose data releasing mechanisms\nthat convert any existing DP mechanism into one against TPL. Experiments\nconfirm that our approach is efficient and effective.\n",
"title": "Quantifying Differential Privacy in Continuous Data Release under Temporal Correlations"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14377
| null |
Validated
| null | null |
null |
{
"abstract": " Let $G$ be a finite group with the property that if $a,b$ are powers of\n$\\delta_1^*$-commutators such that $(|a|,|b|)=1$, then $|ab|=|a||b|$. We show\nthat $\\gamma_{\\infty}(G)$ is nilpotent.\n",
"title": "A Sufficient Condition for Nilpotency of the Nilpotent Residual of a Finite Group"
}
| null | null | null | null | true | null |
14378
| null |
Default
| null | null |
null |
{
"abstract": " We study an unbiased estimator for the density of a sum of random variables\nthat are simulated from a computer model. A numerical study on examples with\ncopula dependence is conducted where the proposed estimator performs favourably\nin terms of variance compared to other unbiased estimators. We provide\napplications and extensions to the estimation of marginal densities in Bayesian\nstatistics and to the estimation of the density of sums of random variables\nunder Gaussian copula dependence.\n",
"title": "Monte Carlo Estimation of the Density of the Sum of Dependent Random Variables"
}
| null | null | null | null | true | null |
14379
| null |
Default
| null | null |
null |
{
"abstract": " Variational auto-encoder frameworks have demonstrated success in reducing\ncomplex nonlinear dynamics in molecular simulation to a single non-linear\nembedding. In this work, we illustrate how this non-linear latent embedding can\nbe used as a collective variable for enhanced sampling, and present a simple\nmodification that allows us to rapidly perform sampling in multiple related\nsystems. We first demonstrate our method is able to describe the effects of\nforce field changes in capped alanine dipeptide after learning a model using\nAMBER99. We further provide a simple extension to variational dynamics encoders\nthat allows the model to be trained in a more efficient manner on larger\nsystems by encoding the outputs of a linear transformation using time-structure\nbased independent component analysis (tICA). Using this technique, we show how\nsuch a model trained for one protein, the WW domain, can efficiently be\ntransferred to perform enhanced sampling on a related mutant protein, the GTT\nmutation. This method shows promise for its ability to rapidly sample related\nsystems using a single transferable collective variable and is generally\napplicable to sets of related simulations, enabling us to probe the effects of\nvariation in increasingly large systems of biophysical interest.\n",
"title": "Transferable neural networks for enhanced sampling of protein dynamics"
}
| null | null | null | null | true | null |
14380
| null |
Default
| null | null |
null |
{
"abstract": " Geochemical studies of planetary accretion and evolution have invoked various\ndegrees of collisional erosion to explain differences in bulk composition\nbetween planets and chondrites. Here we undertake a full, dynamical evaluation\nof 'crustal stripping' during accretion and its key geochemical consequences.\nWe present smoothed particle hydrodynamics simulations of collisions between\ndifferentiated rocky planetesimals and planetary embryos. We find that the\ncrust is preferentially lost relative to the mantle during impacts, and we have\ndeveloped a scaling law that approximates the mass of crust that remains in the\nlargest remnant. Using this scaling law and a recent set of N-body simulations,\nwe have estimated the maximum effect of crustal stripping on incompatible\nelement abundances during the accretion of planetary embryos. We find that on\naverage one third of the initial crust is stripped from embryos as they\naccrete, which leads to a reduction of ~20% in the budgets of the heat\nproducing elements if the stripped crust does not reaccrete. Erosion of crusts\ncan lead to non-chondritic ratios of incompatible elements, but the magnitude\nof this effect depends sensitively on the details of the crust-forming melting\nprocess. The Lu/Hf system is fractionated for a wide range of crustal formation\nscenarios. Using eucrites (the products of planetesimal silicate melting,\nthought to represent the crust of Vesta) as a guide to the Lu/Hf of\nplanetesimal crust partially lost during accretion, we predict the Earth could\nevolve to a superchondritic 176-Hf/177-Hf (3-5 parts per ten thousand) at\npresent day. Such values are in keeping with compositional estimates of the\nbulk Earth. Stripping of planetary crusts during accretion can lead to\ndetectable changes in bulk composition of lithophile elements, but the\nfractionation is relatively subtle, and sensitive to the efficiency of\nreaccretion.\n",
"title": "Collisional stripping of planetary crusts"
}
| null | null | null | null | true | null |
14381
| null |
Default
| null | null |
null |
{
"abstract": " Graph Convolutional Networks (GCNs) have shown significant improvements in\nsemi-supervised learning on graph-structured data. Concurrently, unsupervised\nlearning of graph embeddings has benefited from the information contained in\nrandom walks. In this paper, we propose a model: Network of GCNs (N-GCN), which\nmarries these two lines of work. At its core, N-GCN trains multiple instances\nof GCNs over node pairs discovered at different distances in random walks, and\nlearns a combination of the instance outputs which optimizes the classification\nobjective. Our experiments show that our proposed N-GCN model improves\nstate-of-the-art baselines on all of the challenging node classification tasks\nwe consider: Cora, Citeseer, Pubmed, and PPI. In addition, our proposed method\nhas other desirable properties, including generalization to recently proposed\nsemi-supervised learning methods such as GraphSAGE, allowing us to propose\nN-SAGE, and resilience to adversarial input perturbations.\n",
"title": "N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification"
}
| null | null | null | null | true | null |
14382
| null |
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| null | null |
null |
{
"abstract": " For integers $k\\geq 1$ and $n\\geq 2k+1$, the Kneser graph $K(n,k)$ is the\ngraph whose vertices are the $k$-element subsets of $\\{1,\\ldots,n\\}$ and whose\nedges connect pairs of subsets that are disjoint. The Kneser graphs of the form\n$K(2k+1,k)$ are also known as the odd graphs. We settle an old problem due to\nMeredith, Lloyd, and Biggs from the 1970s, proving that for every $k\\geq 3$,\nthe odd graph $K(2k+1,k)$ has a Hamilton cycle. This and a known conditional\nresult due to Johnson imply that all Kneser graphs of the form $K(2k+2^a,k)$\nwith $k\\geq 3$ and $a\\geq 0$ have a Hamilton cycle. We also prove that\n$K(2k+1,k)$ has at least $2^{2^{k-6}}$ distinct Hamilton cycles for $k\\geq 6$.\nOur proofs are based on a reduction of the Hamiltonicity problem in the odd\ngraph to the problem of finding a spanning tree in a suitably defined\nhypergraph on Dyck words.\n",
"title": "Sparse Kneser graphs are Hamiltonian"
}
| null | null | null | null | true | null |
14383
| null |
Default
| null | null |
null |
{
"abstract": " We introduce a class of fixed points of primitive morphisms among aperiodic\nbinary generalized pseudostandard words. We conjecture that this class contains\nall fixed points of primitive morphisms among aperiodic binary generalized\npseudostandard words that are not standard Sturmian words.\n",
"title": "Fixed points of morphisms among binary generalized pseudostandard words"
}
| null | null | null | null | true | null |
14384
| null |
Default
| null | null |
null |
{
"abstract": " R. Beheshti showed that, for a smooth Fano hypersurface $X$ of degree $\\leq\n8$ over the complex number field $\\mathbb{C}$, the dimension of the space of\nlines lying in $X$ is equal to the expected dimension. We study the space of\nconics on $X$. In this case, if $X$ contains some linear subvariety, then the\ndimension of the space can be larger than the expected dimension. In this\npaper, we show that, for a smooth Fano hypersurface $X$ of degree $\\leq 6$ over\n$\\mathbb{C}$, and for an irreducible component $R$ of the space of conics lying\nin $X$, if the $2$-plane spanned by a general conic of $R$ is not contained in\n$X$, then the dimension of $R$ is equal to the expected dimension.\n",
"title": "Dimension of the space of conics on Fano hypersurfaces"
}
| null | null | null | null | true | null |
14385
| null |
Default
| null | null |
null |
{
"abstract": " The structure of a certain subgroup $S$ of the automorphism group of a\npartially commutative group (RAAG) $G$ is described in detail: namely the\nsubgroup generated by inversions and elementary transvections. We define\nadmissible subsets of the generators of $G$, and show that $S$ is the subgroup\nof automorphisms which fix all subgroups $\\langle Y\\rangle$ of $G$, for all\nadmissible subsets $Y$. A decomposition of $S$ as an iterated tower of\nsemi-direct products in given and the structure of the factors of this\ndecomposition described. The construction allows a presentation of $S$ to be\ncomputed, from the commutation graph of $G$.\n",
"title": "Automorphisms of Partially Commutative Groups III: Inversions and Transvections"
}
| null | null | null | null | true | null |
14386
| null |
Default
| null | null |
null |
{
"abstract": " Every Constraint Programming (CP) solver exposes a library of constraints for\nsolving combinatorial problems. In order to be useful, CP solvers need to be\nbug-free. Therefore the testing of the solver is crucial to make developers and\nusers confident. We present a Java library allowing any JVM based solver to\ntest that the implementations of the individual constraints are correct. The\nlibrary can be used in a test suite executed in a continuous integration tool\nor it can also be used to discover minimalist instances violating some\nproperties (arc-consistency, etc) in order to help the developer to identify\nthe origin of the problem using standard debuggers.\n",
"title": "Testing Global Constraints"
}
| null | null | null | null | true | null |
14387
| null |
Default
| null | null |
null |
{
"abstract": " The restricted Boltzmann machine is a network of stochastic units with\nundirected interactions between pairs of visible and hidden units. This model\nwas popularized as a building block of deep learning architectures and has\ncontinued to play an important role in applied and theoretical machine\nlearning. Restricted Boltzmann machines carry a rich structure, with\nconnections to geometry, applied algebra, probability, statistics, machine\nlearning, and other areas. The analysis of these models is attractive in its\nown right and also as a platform to combine and generalize mathematical tools\nfor graphical models with hidden variables. This article gives an introduction\nto the mathematical analysis of restricted Boltzmann machines, reviews recent\nresults on the geometry of the sets of probability distributions representable\nby these models, and suggests a few directions for further investigation.\n",
"title": "Restricted Boltzmann Machines: Introduction and Review"
}
| null | null | null | null | true | null |
14388
| null |
Default
| null | null |
null |
{
"abstract": " 3D Convolutional Neural Networks (3D-CNN) have been used for object\nrecognition based on the voxelized shape of an object. However, interpreting\nthe decision making process of these 3D-CNNs is still an infeasible task. In\nthis paper, we present a unique 3D-CNN based Gradient-weighted Class Activation\nMapping method (3D-GradCAM) for visual explanations of the distinct local\ngeometric features of interest within an object. To enable efficient learning\nof 3D geometries, we augment the voxel data with surface normals of the object\nboundary. We then train a 3D-CNN with this augmented data and identify the\nlocal features critical for decision-making using 3D GradCAM. An application of\nthis feature identification framework is to recognize difficult-to-manufacture\ndrilled hole features in a complex CAD geometry. The framework can be extended\nto identify difficult-to-manufacture features at multiple spatial scales\nleading to a real-time design for manufacturability decision support system.\n",
"title": "Learning and Visualizing Localized Geometric Features Using 3D-CNN: An Application to Manufacturability Analysis of Drilled Holes"
}
| null | null | null | null | true | null |
14389
| null |
Default
| null | null |
null |
{
"abstract": " By excluding some regions, in which each eigenvalue of a matrix is not\ncontained, from the \\alpha\\beta-type eigenvalue inclusion region provided by\nHuang et al.(Electronic Journal of Linear Algebra, 15 (2006) 215-224), a new\neigenvalue inclusion region is given. And it is proved that the new region is\ncontained in the \\alpha\\beta-type eigenvalue inclusion region.\n",
"title": "Note on regions containing eigenvalues of a matrix"
}
| null | null | null | null | true | null |
14390
| null |
Default
| null | null |
null |
{
"abstract": " Variational systems allow effective building of many custom variants by using\nfeatures (configuration options) to mark the variable functionality. In many of\nthe applications, their quality assurance and formal verification are of\nparamount importance. Family-based model checking allows simultaneous\nverification of all variants of a variational system in a single run by\nexploiting the commonalities between the variants. Yet, its computational cost\nstill greatly depends on the number of variants (often huge).\nIn this work, we show how to achieve efficient family-based model checking of\nCTL* temporal properties using variability abstractions and off-the-shelf\n(single-system) tools. We use variability abstractions for deriving abstract\nfamily-based model checking, where the variability model of a variational\nsystem is replaced with an abstract (smaller) version of it, called modal\nfeatured transition system, which preserves the satisfaction of both universal\nand existential temporal properties, as expressible in CTL*. Modal featured\ntransition systems contain two kinds of transitions, termed may and must\ntransitions, which are defined by the conservative (over-approximating)\nabstractions and their dual (under-approximating) abstractions, respectively.\nThe variability abstractions can be combined with different partitionings of\nthe set of variants to infer suitable divide-and-conquer verification plans for\nthe variational system. We illustrate the practicality of this approach for\nseveral variational systems.\n",
"title": "Abstract Family-based Model Checking using Modal Featured Transition Systems: Preservation of CTL* (Extended Version)"
}
| null | null | null | null | true | null |
14391
| null |
Default
| null | null |
null |
{
"abstract": " We consider the problem of nonparametric regression under shape constraints.\nThe main examples include isotonic regression (with respect to any partial\norder), unimodal/convex regression, additive shape-restricted regression, and\nconstrained single index model. We review some of the theoretical properties of\nthe least squares estimator (LSE) in these problems, emphasizing on the\nadaptive nature of the LSE. In particular, we study the behavior of the risk of\nthe LSE, and its pointwise limiting distribution theory, with special emphasis\nto isotonic regression. We survey various methods for constructing pointwise\nconfidence intervals around these shape-restricted functions. We also briefly\ndiscuss the computation of the LSE and indicate some open research problems and\nfuture directions.\n",
"title": "Nonparametric Shape-restricted Regression"
}
| null | null | null | null | true | null |
14392
| null |
Default
| null | null |
null |
{
"abstract": " Using established principles from Statistics and Information Theory, we show\nthat invariance to nuisance factors in a deep neural network is equivalent to\ninformation minimality of the learned representation, and that stacking layers\nand injecting noise during training naturally bias the network towards learning\ninvariant representations. We then decompose the cross-entropy loss used during\ntraining and highlight the presence of an inherent overfitting term. We propose\nregularizing the loss by bounding such a term in two equivalent ways: One with\na Kullbach-Leibler term, which relates to a PAC-Bayes perspective; the other\nusing the information in the weights as a measure of complexity of a learned\nmodel, yielding a novel Information Bottleneck for the weights. Finally, we\nshow that invariance and independence of the components of the representation\nlearned by the network are bounded above and below by the information in the\nweights, and therefore are implicitly optimized during training. The theory\nenables us to quantify and predict sharp phase transitions between underfitting\nand overfitting of random labels when using our regularized loss, which we\nverify in experiments, and sheds light on the relation between the geometry of\nthe loss function, invariance properties of the learned representation, and\ngeneralization error.\n",
"title": "Emergence of Invariance and Disentanglement in Deep Representations"
}
| null | null | null | null | true | null |
14393
| null |
Default
| null | null |
null |
{
"abstract": " In this work, we develop a coupled layer construction of fracton topological\norders in $d=3$ spatial dimensions. These topological phases have sub-extensive\ntopological ground-state degeneracy and possess excitations whose movement is\nrestricted in interesting ways. Our coupled layer approach is used to construct\nseveral different fracton topological phases, both from stacked layers of\nsimple $d=2$ topological phases and from stacks of $d=3$ fracton topological\nphases. This perspective allows us to shed light on the physics of the X-cube\nmodel recently introduced by Vijay, Haah, and Fu, which we demonstrate can be\nobtained as the strong-coupling limit of a coupled three-dimensional stack of\ntoric codes. We also construct two new models of fracton topological order: a\nsemionic generalization of the X-cube model, and a model obtained by coupling\ntogether four interpenetrating X-cube models, which we dub the \"Four Color Cube\nmodel.\" The couplings considered lead to fracton topological orders via\nmechanisms we dub \"p-string condensation\" and \"p-membrane condensation,\" in\nwhich strings or membranes built from particle excitations are driven to\ncondense. This allows the fusion properties, braiding statistics, and\nground-state degeneracy of the phases we construct to be easily studied in\nterms of more familiar degrees of freedom. Our work raises the possibility of\nstudying fracton topological phases from within the framework of topological\nquantum field theory, which may be useful for obtaining a more complete\nunderstanding of such phases.\n",
"title": "Fracton topological order via coupled layers"
}
| null | null | null | null | true | null |
14394
| null |
Default
| null | null |
null |
{
"abstract": " We study local asymptotic normality of M-estimates of convex minimization in\nan infinite dimensional parameter space. The objective function of M-estimates\nis not necessary differentiable and is possibly subject to convex constraints.\nIn the above circumstance, narrow convergence with respect to uniform\nconvergence fails to hold, because of the strength of it's topology. A new\napproach we propose to the lack-of-uniform-convergence is based on\nMosco-convergence that is weaker topology than uniform convergence. By applying\nnarrow convergence with respect to Mosco topology, we develop an\ninfinite-dimensional version of the convexity argument and provide a proof of a\nlocal asymptotic normality. Our new technique also provides a proof of an\nasymptotic distribution of the likelihood ratio test statistic defined on real\nseparable Hilbert spaces.\n",
"title": "Local Asymptotic Normality of Infinite-Dimensional Concave Extended Linear Models"
}
| null | null | null | null | true | null |
14395
| null |
Default
| null | null |
null |
{
"abstract": " The polarization exchange effect in a twisted-nematic Fabry-Pérot resonator\nis experimentally confirmed in the regimes of both uniform and\nelectric-field-deformed twisted structures. The polarization of output light in\nthe transmission peaks is shown to be linear rather than elliptical. The\npolarization deflection from the nematic director grows from $0^\\circ$ to\n$90^\\circ$ angle and exchanges the longitudinal and transverse directions.\nUntwisting of a nematic by a voltage leads to the rotation of the polarization\nplane of light passing through the resonator. The polarization exchange effect\nallows using the investigated resonator as a spectral-selective linear\npolarizer with the voltage-controlled rotation of the polarization plane.\n",
"title": "Polarization exchange of optical eigenmode pair in twisted-nematic Fabry-Pérot resonator"
}
| null | null | null | null | true | null |
14396
| null |
Default
| null | null |
null |
{
"abstract": " Present-day clusters are massive halos containing mostly quiescent galaxies,\nwhile distant protoclusters are extended structures containing numerous\nstar-forming galaxies. We investigate the implications of this fundamental\nchange in a cosmological context using a set of N-body simulations and\nsemi-analytic models. We find that the fraction of the cosmic volume occupied\nby all (proto)clusters increases by nearly three orders of magnitude from z=0\nto z=7. We show that (proto)cluster galaxies are an important, and even\ndominant population at high redshift, as their expected contribution to the\ncosmic star-formation rate density rises (from 1% at z=0) to 20% at z=2 and 50%\nat z=10. Protoclusters thus provide a significant fraction of the cosmic\nionizing photons, and may have been crucial in driving the timing and topology\nof cosmic reionization. Internally, the average history of cluster formation\ncan be described by three distinct phases: at z~10-5, galaxy growth in\nprotoclusters proceeded in an inside-out manner, with centrally dominant halos\nthat are among the most active regions in the Universe; at z~5-1.5, rapid star\nformation occurred within the entire 10-20 Mpc structures, forming most of\ntheir present-day stellar mass; at z<~1.5, violent gravitational collapse drove\nthese stellar contents into single cluster halos, largely erasing the details\nof cluster galaxy formation due to relaxation and virialization. Our results\nmotivate observations of distant protoclusters in order to understand the\nrapid, extended stellar growth during Cosmic Noon, and their connection to\nreionization during Cosmic Dawn.\n",
"title": "Galaxy Protoclusters as Drivers of Cosmic Star-Formation History in the First 2 Gyr"
}
| null | null | null | null | true | null |
14397
| null |
Default
| null | null |
null |
{
"abstract": " Cascading failures may lead to dramatic collapse in interdependent networks,\nwhere the breakdown takes place as a discontinuity of the order parameter. In\nthe cascading failure (CF) model with healing there is a control parameter\nwhich at some value suppresses the discontinuity of the order parameter.\nHowever, up to this value of the healing parameter the breakdown is a hybrid\ntransition, meaning that, besides this first order character, the transition\nshows scaling too. In this paper we investigate the question of universality\nrelated to the scaling behavior. Recently we showed that the hybrid phase\ntransition in the original CF model has two sets of exponents describing\nrespectively the order parameter and the cascade statistics, which are\nconnected by a scaling law. In the CF model with healing we measure these\nexponents as a function of the healing parameter. We find two universality\nclasses: In the wide range below the critical healing value the exponents agree\nwith those of the original model, while above this value the model displays\ntrivial scaling meaning that fluctuations follow the central limit theorem.\n",
"title": "Universality and scaling laws in the cascading failure model with healing"
}
| null | null | null | null | true | null |
14398
| null |
Default
| null | null |
null |
{
"abstract": " The Hamiltonian of the quantum Calogero-Sutherland model of $N$ identical\nparticles on the circle with $1/r^{2}$ interactions has eigenfunctions\nconsisting of Jack polynomials times the base state. By use of the generalized\nJack polynomials taking values in modules of the symmetric group and the matrix\nsolution of a system of linear differential equations one constructs novel\neigenfunctions of the Hamiltonian. Like the usual wavefunctions each\neigenfunction determines a symmetric probability density on the $N$-torus. The\nconstruction applies to any irreducible representation of the symmetric group.\nThe methods depend on the theory of generalized Jack polynomials due to\nGriffeth, and the Yang-Baxter graph approach of Luque and the author.\n",
"title": "Vector-valued Jack Polynomials and Wavefunctions on the Torus"
}
| null | null | null | null | true | null |
14399
| null |
Default
| null | null |
null |
{
"abstract": " We define the {\\it Wirtinger number} of a link, an invariant closely related\nto the meridional rank. The Wirtinger number is the minimum number of\ngenerators of the fundamental group of the link complement over all meridional\npresentations in which every relation is an iterated Wirtinger relation arising\nin a diagram. We prove that the Wirtinger number of a link equals its bridge\nnumber. This equality can be viewed as establishing a weak version of Cappell\nand Shaneson's Meridional Rank Conjecture, and suggests a new approach to this\nconjecture. Our result also leads to a combinatorial technique for obtaining\nstrong upper bounds on bridge numbers. This technique has so far allowed us to\nadd the bridge numbers of approximately 50,000 prime knots of up to 14\ncrossings to the knot table. As another application, we use the Wirtinger\nnumber to show there exists a universal constant $C$ with the property that the\nhyperbolic volume of a prime alternating link $L$ is bounded below by $C$ times\nthe bridge number of $L$.\n",
"title": "Wirtinger systems of generators of knot groups"
}
| null | null |
[
"Mathematics"
] | null | true | null |
14400
| null |
Validated
| null | null |
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