text
null | inputs
dict | prediction
null | prediction_agent
null | annotation
list | annotation_agent
null | multi_label
bool 1
class | explanation
null | id
stringlengths 1
5
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null | status
stringclasses 2
values | event_timestamp
null | metrics
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|---|---|---|---|---|---|---|---|---|---|---|---|---|
null |
{
"abstract": " MRA (Multilingual Report Annotator) is a web application that translates\nRadiology text and annotates it with RadLex terms. Its goal is to explore the\nsolution of translating non-English Radiology reports as a way to solve the\nproblem of most of the Text Mining tools being developed for English. In this\nbrief paper we explain the language barrier problem and shortly describe the\napplication. MRA can be found at this https URL .\n",
"title": "MRA - Proof of Concept of a Multilingual Report Annotator Web Application"
}
| null | null | null | null | true | null |
14901
| null |
Default
| null | null |
null |
{
"abstract": " We consider SIS contagion processes over networks where, a classical\nassumption is that individuals' decisions to adopt a contagion are based on\ntheir immediate neighbors. However, recent literature shows that some\nattributes are more correlated between two-hop neighbors, a concept referred to\nas monophily. This motivates us to explore monophilic contagion, the case where\na contagion (e.g. a product, disease) is adopted by considering two-hop\nneighbors instead of immediate neighbors (e.g. you ask your friend about the\nnew iPhone and she recommends you the opinion of one of her friends). We show\nthat the phenomenon called friendship paradox makes it easier for the\nmonophilic contagion to spread widely. We also consider the case where the\nunderlying network stochastically evolves in response to the state of the\ncontagion (e.g. depending on the severity of a flu virus, people restrict their\ninteractions with others to avoid getting infected) and show that the dynamics\nof such a process can be approximated by a differential equation whose\ntrajectory satisfies an algebraic constraint restricting it to a manifold. Our\nresults shed light on how graph theoretic consequences affect contagions and,\nprovide simple deterministic models to approximate the collective dynamics of\ncontagions over stochastic graph processes.\n",
"title": "Contagions in Social Networks: Effects of Monophilic Contagion, Friendship Paradox and Reactive Networks"
}
| null | null | null | null | true | null |
14902
| null |
Default
| null | null |
null |
{
"abstract": " We propose a multi-layer approach to simulate hyperpycnal and hypopycnal\nplumes in flows with free surface. The model allows to compute the vertical\nprofile of the horizontal and the vertical components of the velocity of the\nfluid flow. The model can describe as well the vertical profile of the sediment\nconcentration and the velocity components of each one of the sediment species\nthat form the turbidity current. To do so, it takes into account the settling\nvelocity of the particles and their interaction with the fluid. This allows to\nbetter describe the phenomena than a single layer approach. It is in better\nagreement with the physics of the problem and gives promising results. The\nnumerical simulation is carried out by rewriting the multi-layer approach in a\ncompact formulation, which corresponds to a system with non-conservative\nproducts, and using path-conservative numerical scheme. Numerical results are\npresented in order to show the potential of the model.\n",
"title": "Derivation of a multilayer approach to model suspended sediment transport: application to hyperpycnal and hypopycnal plumes"
}
| null | null | null | null | true | null |
14903
| null |
Default
| null | null |
null |
{
"abstract": " Here we construct the conformal mappings with the help of continuous\nfractions approximations. These approximations converge to the algebraic roots\n$\\sqrt[N]{z}$ for $N \\in \\mathbb{N}$ and $z$ from the right half-plane of the\ncomplex plane. We estimate both the convergence rate and the compact set of\nconvergence. Also we give the examples that illustrate the introduced technique\nof a conformal mapping construction.\n",
"title": "Continued fractions and conformal mappings for domains with angle points"
}
| null | null | null | null | true | null |
14904
| null |
Default
| null | null |
null |
{
"abstract": " Neural networks are known to be vulnerable to adversarial examples. Carefully\nchosen perturbations to real images, while imperceptible to humans, induce\nmisclassification and threaten the reliability of deep learning systems in the\nwild. To guard against adversarial examples, we take inspiration from game\ntheory and cast the problem as a minimax zero-sum game between the adversary\nand the model. In general, for such games, the optimal strategy for both\nplayers requires a stochastic policy, also known as a mixed strategy. In this\nlight, we propose Stochastic Activation Pruning (SAP), a mixed strategy for\nadversarial defense. SAP prunes a random subset of activations (preferentially\npruning those with smaller magnitude) and scales up the survivors to\ncompensate. We can apply SAP to pretrained networks, including adversarially\ntrained models, without fine-tuning, providing robustness against adversarial\nexamples. Experiments demonstrate that SAP confers robustness against attacks,\nincreasing accuracy and preserving calibration.\n",
"title": "Stochastic Activation Pruning for Robust Adversarial Defense"
}
| null | null | null | null | true | null |
14905
| null |
Default
| null | null |
null |
{
"abstract": " Let K be a field and denote by K[t], the polynomial ring with coefficients in\nK. Set A = K[f1,. .. , fs], with f1,. .. , fs $\\in$ K[t]. We give a procedure\nto calculate the monoid of degrees of the K algebra M = F1A + $\\times$ $\\times$\n$\\times$ + FrA with F1,. .. , Fr $\\in$ K[t]. We show some applications to the\nproblem of the classification of plane polynomial curves (that is, plane\nalgebraic curves parametrized by polynomials) with respect to some oh their\ninvariants, using the module of K{ä}hler differentials.\n",
"title": "Canonical bases of modules over one dimensional k-algebras"
}
| null | null | null | null | true | null |
14906
| null |
Default
| null | null |
null |
{
"abstract": " Deep neural networks (DNNs) are powerful nonlinear architectures that are\nknown to be robust to random perturbations of the input. However, these models\nare vulnerable to adversarial perturbations--small input changes crafted\nexplicitly to fool the model. In this paper, we ask whether a DNN can\ndistinguish adversarial samples from their normal and noisy counterparts. We\ninvestigate model confidence on adversarial samples by looking at Bayesian\nuncertainty estimates, available in dropout neural networks, and by performing\ndensity estimation in the subspace of deep features learned by the model. The\nresult is a method for implicit adversarial detection that is oblivious to the\nattack algorithm. We evaluate this method on a variety of standard datasets\nincluding MNIST and CIFAR-10 and show that it generalizes well across different\narchitectures and attacks. Our findings report that 85-93% ROC-AUC can be\nachieved on a number of standard classification tasks with a negative class\nthat consists of both normal and noisy samples.\n",
"title": "Detecting Adversarial Samples from Artifacts"
}
| null | null | null | null | true | null |
14907
| null |
Default
| null | null |
null |
{
"abstract": " Societies are complex systems which tend to polarize into sub-groups of\nindividuals with dramatically opposite perspectives. This phenomenon is\nreflected -- and often amplified -- in online social networks where, however,\nhumans are no more the only players, and co-exist alongside with social bots,\ni.e. software-controlled accounts. Analyzing large-scale social data collected\nduring the Catalan referendum for independence on October 1 2017, consisting of\nnearly 4 millions Twitter posts generated by almost 1 million users, we\nidentify the two polarized groups of Independentists and Constitutionalists and\nquantify the structural and emotional roles played by social bots. We show that\nbots act from peripheral areas of the social system to target influential\nhumans of both groups, mostly bombarding Independentists with negative and\nviolent contents, sustaining and inflating instability in this online society.\nThese results quantify the potential dangerous influence of political bots\nduring voting processes.\n",
"title": "Bots sustain and inflate striking opposition in online social systems"
}
| null | null | null | null | true | null |
14908
| null |
Default
| null | null |
null |
{
"abstract": " Measurements on a subset of the boundary are common in electrical impedance\ntomography, especially any electrode model can be interpreted as a partial\nboundary problem. The information obtained is different to full-boundary\nmeasurements as modeled by the ideal continuum model. In this study we discuss\nan approach to approximate full-boundary data from partial-boundary\nmeasurements that is based on the knowledge of the involved projections. The\napproximate full-boundary data can then be obtained as the solution of a\nsuitable optimization problem on the coefficients of the Neumann-to-Dirichlet\nmap. By this procedure we are able to improve the reconstruction quality of\ncontinuum model based algorithms, in particular we present the effectiveness\nwith a D-bar method. Reconstructions are presented for noisy simulated and real\nmeasurement data.\n",
"title": "Approximation of full-boundary data from partial-boundary electrode measurements"
}
| null | null | null | null | true | null |
14909
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we propose a new optimization algorithm for sparse logistic\nregression based on a stochastic version of the Douglas-Rachford splitting\nmethod. Our algorithm sweeps the training set by randomly selecting a\nmini-batch of data at each iteration, and it allows us to update the variables\nin a block coordinate manner. Our approach leverages the proximity operator of\nthe logistic loss, which is expressed with the generalized Lambert W function.\nExperiments carried out on standard datasets demonstrate the efficiency of our\napproach w.r.t. stochastic gradient-like methods.\n",
"title": "A Random Block-Coordinate Douglas-Rachford Splitting Method with Low Computational Complexity for Binary Logistic Regression"
}
| null | null | null | null | true | null |
14910
| null |
Default
| null | null |
null |
{
"abstract": " Time domain terahertz spectroscopy typically uses mechanical delay stages\nthat inherently suffer from non-uniform sampling positions. We review,\nsimulate, and experimentally test the ability of corrective cubic spline and\nShannon re-gridding algorithms to mitigate the inherent sampling position\nnoise. We present simulations and experimental results that show re-gridding\nalgorithms can increase the signal to noise ratio within the frequency range of\n100 GHz to 2 THz. We also predict that re-gridding corrections will become\nincreasingly important to both spectroscopy and imaging as THz technology\ncontinues to improve and higher frequencies become experimentally accessible.\n",
"title": "Corrective Re-gridding Techniques for Non-Uniform Sampling in Time Domain Terahertz Spectroscopy"
}
| null | null | null | null | true | null |
14911
| null |
Default
| null | null |
null |
{
"abstract": " Robust Optimization has traditionally taken a pessimistic, or worst-case\nviewpoint of uncertainty which is motivated by a desire to find sets of optimal\npolicies that maintain feasibility under a variety of operating conditions. In\nthis paper, we explore an optimistic, or best-case view of uncertainty and show\nthat it can be a fruitful approach. We show that these techniques can be used\nto address a wide variety of problems. First, we apply our methods in the\ncontext of robust linear programming, providing a method for reducing\nconservatism in intuitive ways that encode economically realistic modeling\nassumptions. Second, we look at problems in machine learning and find that this\napproach is strongly connected to the existing literature. Specifically, we\nprovide a new interpretation for popular sparsity inducing non-convex\nregularization schemes. Additionally, we show that successful approaches for\ndealing with outliers and noise can be interpreted as optimistic robust\noptimization problems. Although many of the problems resulting from our\napproach are non-convex, we find that DCA or DCA-like optimization approaches\ncan be intuitive and efficient.\n",
"title": "Optimistic Robust Optimization With Applications To Machine Learning"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
14912
| null |
Validated
| null | null |
null |
{
"abstract": " Multidimensional time series are sequences of real valued vectors. They occur\nin different areas, for example handwritten characters, GPS tracking, and\ngestures of modern virtual reality motion controllers. Within these areas, a\ncommon task is to search for similar time series. Dynamic Time Warping (DTW) is\na common distance function to compare two time series. The Edit Distance with\nReal Penalty (ERP) and the Dog Keeper Distance (DK) are two more distance\nfunctions on time series. Their behaviour has been analyzed on 1-dimensional\ntime series. However, it is not easy to evaluate their behaviour in relation to\ngrowing dimensionality. For this reason we propose two new data synthesizers\ngenerating multidimensional time series. The first synthesizer extends the well\nknown cylinder-bell-funnel (CBF) dataset to multidimensional time series. Here,\neach time series has an arbitrary type (cylinder, bell, or funnel) in each\ndimension, thus for $d$-dimensional time series there are $3^{d}$ different\nclasses. The second synthesizer (RAM) creates time series with ideas adapted\nfrom Brownian motions which is a common model of movement in physics. Finally,\nwe evaluate the applicability of a 1-nearest neighbor classifier using DTW on\ndatasets generated by our synthesizers.\n",
"title": "High Dimensional Time Series Generators"
}
| null | null | null | null | true | null |
14913
| null |
Default
| null | null |
null |
{
"abstract": " We show that for any positive integer k, the k-th nonzero eigenvalue of the\nLaplace-Beltrami operator on the two-dimensional sphere endowed with a\nRiemannian metric of unit area, is maximized in the limit by a sequence of\nmetrics converging to a union of k touching identical round spheres. This\nproves a conjecture posed by the second author in 2002 and yields a sharp\nisoperimetric inequality for all nonzero eigenvalues of the Laplacian on a\nsphere. Earlier, the result was known only for k=1 (J.Hersch, 1970), k=2\n(N.Nadirashvili, 2002; R.Petrides, 2014) and k=3 (N.Nadirashvili and Y.Sire,\n2017). In particular, we argue that for any k>=2, the supremum of the k-th\nnonzero eigenvalue on a sphere of unit area is not attained in the class of\nRiemannin metrics which are smooth outsitde a finite set of conical\nsingularities. The proof uses certain properties of harmonic maps between\nspheres, the key new ingredient being a bound on the harmonic degree of a\nharmonic map into a sphere obtained by N. Ejiri.\n",
"title": "An isoperimetric inequality for Laplace eigenvalues on the sphere"
}
| null | null | null | null | true | null |
14914
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we have proposed a modified Marker-And-Cell (MAC) method to\ninvestigate the problem of an unsteady 2-D incompressible flow with heat and\nmass transfer at low, moderate, and high Reynolds numbers with no-slip and slip\nboundary conditions. We have used this method to solve the governing equations\nalong with the boundary conditions and thereby to compute the flow variables,\nviz. $u$-velocity, $v$-velocity, $P$, $T$, and $C$. We have used the staggered\ngrid approach of this method to discretize the governing equations of the\nproblem. A modified MAC algorithm was proposed and used to compute the\nnumerical solutions of the flow variables for Reynolds numbers $Re = 10$, 500,\nand 50,000 in consonance with low, moderate, and high Reynolds numbers. We have\nalso used appropriate Prandtl $(Pr)$ and Schmidt $(Sc)$ numbers in consistence\nwith relevancy of the physical problem considered. We have executed this\nmodified MAC algorithm with the aid of a computer program developed and run in\nC compiler. We have also computed numerical solutions of local Nusselt $(Nu)$\nand Sherwood $(Sh)$ numbers along the horizontal line through the geometric\ncenter at low, moderate, and high Reynolds numbers for fixed $Pr = 6.62$ and\n$Sc = 340$ for two grid systems at time $t = 0.0001s$. Our numerical solutions\nfor u and v velocities along the vertical and horizontal line through the\ngeometric center of the square cavity for $Re = 100$ has been compared with\nbenchmark solutions available in the literature and it has been found that they\nare in good agreement. The present numerical results indicate that, as we move\nalong the horizontal line through the geometric center of the domain, we\nobserved that, the heat and mass transfer decreases up to the geometric center.\nIt, then, increases symmetrically.\n",
"title": "Numerical solutions of an unsteady 2-D incompressible flow with heat and mass transfer at low, moderate, and high Reynolds numbers"
}
| null | null | null | null | true | null |
14915
| null |
Default
| null | null |
null |
{
"abstract": " We propose a dynamic programming solution to image dejittering problems with\nbounded displacements and obtain efficient algorithms for the removal of line\njitter, line pixel jitter, and pixel jitter.\n",
"title": "A Dynamic Programming Solution to Bounded Dejittering Problems"
}
| null | null | null | null | true | null |
14916
| null |
Default
| null | null |
null |
{
"abstract": " We consider the dynamics of overdamped MEMS devices undergoing the pull-in\ninstability. Numerous previous experiments and numerical simulations have shown\na significant increase in the pull-in time under DC voltages close to the\npull-in voltage. Here the transient dynamics slow down as the device passes\nthrough a meta-stable or bottleneck phase, but this slowing down is not well\nunderstood quantitatively. Using a lumped parallel-plate model, we perform a\ndetailed analysis of the pull-in dynamics in this regime. We show that the\nbottleneck phenomenon is a type of critical slowing down arising from the\npull-in transition. This allows us to show that the pull-in time obeys an\ninverse square-root scaling law as the transition is approached; moreover we\ndetermine an analytical expression for this pull-in time. We then compare our\nprediction to a wide range of pull-in time data reported in the literature,\nshowing that the observed slowing down is well captured by our scaling law,\nwhich appears to be generic for overdamped pull-in under DC loads. This\nrealization provides a useful design rule with which to tune dynamic response\nin applications, including state-of-the-art accelerometers and pressure sensors\nthat use pull-in time as a sensing mechanism. We also propose a method to\nestimate the pull-in voltage based only on data of the pull-in times.\n",
"title": "Delayed pull-in transitions in overdamped MEMS devices"
}
| null | null | null | null | true | null |
14917
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we theoretically address three fundamental problems involving\ndeep convolutional networks regarding invariance, depth and hierarchy. We\nintroduce the paradigm of Transformation Networks (TN) which are a direct\ngeneralization of Convolutional Networks (ConvNets). Theoretically, we show\nthat TNs (and thereby ConvNets) are can be invariant to non-linear\ntransformations of the input despite pooling over mere local translations. Our\nanalysis provides clear insights into the increase in invariance with depth in\nthese networks. Deeper networks are able to model much richer classes of\ntransformations. We also find that a hierarchical architecture allows the\nnetwork to generate invariance much more efficiently than a non-hierarchical\nnetwork. Our results provide useful insight into these three fundamental\nproblems in deep learning using ConvNets.\n",
"title": "How ConvNets model Non-linear Transformations"
}
| null | null | null | null | true | null |
14918
| null |
Default
| null | null |
null |
{
"abstract": " In 1992 a puzzling transition was discovered in simulations of randomly\ncoupled limit-cycle oscillators. This so-called volcano transition has resisted\nanalysis ever since. It was originally conjectured to mark the emergence of an\noscillator glass, but here we show it need not. We introduce and solve a\nsimpler model with a qualitatively identical volcano transition and find,\nunexpectedly, that its supercritical state is not glassy. We discuss the\nimplications for the original model and suggest experimental systems in which a\nvolcano transition and oscillator glass may appear.\n",
"title": "Volcano transition in a solvable model of oscillator glass"
}
| null | null | null | null | true | null |
14919
| null |
Default
| null | null |
null |
{
"abstract": " We review different constructions of the supersymmetry subalgebras of the\nchiral de Rham complex on special holonomy manifolds. We describe the\ndifference between the holomorphic-anti-holomorphic sectors based on a local\nfree ghost system vs the decomposition in left-right sectors from a local\nBoson-Fermion system. We describe the topological twist in the case of $G_2$\nand $Spin_7$ manifolds. We describe the construction of these algebras as\nquantum Hamiltonian reduction of Lie superalgebras at the minimal or\nsuperprincipal nilpotent.\n",
"title": "Recent advances and open questions on the susy structure of the chiral de Rham Complex"
}
| null | null |
[
"Mathematics"
] | null | true | null |
14920
| null |
Validated
| null | null |
null |
{
"abstract": " I present a discussion of the hierarchy of Toda flows that gives center stage\nto the associated cocycles and the maps they induce on the $m$ functions. In\nthe second part, these ideas are then applied to canonical systems; an\nimportant feature of this discussion will be my proposal that the role of the\nshift on Jacobi matrices should now be taken over by the more general class of\ntwisted shifts.\n",
"title": "Toda maps, cocycles, and canonical systems"
}
| null | null | null | null | true | null |
14921
| null |
Default
| null | null |
null |
{
"abstract": " It is well known that, in the context of General Relativity, some spacetimes,\nwhen described by a congruence of comoving observers, may consist in a\ndistribution of a perfect (non-dissipative) fluid, whereas the same spacetime\nas seen by a \"tilted\"' (Lorentz-boosted) congruence of observers, may exhibit\nthe presence of dissipative processes. As we shall see, the appearence of\nentropy producing processes are related to the tight dependence of entropy on\nthe specific congruence of observers. This fact is well illustrated by the\nGibbs paradox. The appearance of such dissipative processes, as required by the\nLandauer principle, are necessary, in order to erase the different amount of\ninformation stored by comoving observers, with respect to tilted ones.\n",
"title": "The Gibbs paradox, the Landauer principle and the irreversibility associated with tilted observers"
}
| null | null | null | null | true | null |
14922
| null |
Default
| null | null |
null |
{
"abstract": " The main purpose of this macro-study is to shed light on the broad impact of\nbooks. For this purpose, the impact of a very large collection of books has\nbeen analyzed by using PlumX, an analytical tool providing a great number of\ndifferent metrics provided by various tools.\n",
"title": "PlumX As a Potential Tool to Assess the Macroscopic Multidimensional Impact of Books"
}
| null | null | null | null | true | null |
14923
| null |
Default
| null | null |
null |
{
"abstract": " A policy is said to be robust if it maximizes the reward while considering a\nbad, or even adversarial, model. In this work we formalize two new criteria of\nrobustness to action uncertainty. Specifically, we consider two scenarios in\nwhich the agent attempts to perform an action $\\mathbf{a}$, and (i) with\nprobability $\\alpha$, an alternative adversarial action $\\bar{\\mathbf{a}}$ is\ntaken, or (ii) an adversary adds a perturbation to the selected action in the\ncase of continuous action space. We show that our criteria are related to\ncommon forms of uncertainty in robotics domains, such as the occurrence of\nabrupt forces, and suggest algorithms in the tabular case. Building on the\nsuggested algorithms, we generalize our approach to deep reinforcement learning\n(DRL) and provide extensive experiments in the various MuJoCo domains. Our\nexperiments show that not only does our approach produce robust policies, but\nit also improves the performance in the absence of perturbations. This\ngeneralization indicates that action-robustness can be thought of as implicit\nregularization in RL problems.\n",
"title": "Action Robust Reinforcement Learning and Applications in Continuous Control"
}
| null | null | null | null | true | null |
14924
| null |
Default
| null | null |
null |
{
"abstract": " A vector bundle E on a projective variety X is called finite if it satisfies\na nontrivial polynomial equation with integral coefficients. A theorem of Nori\nimplies that E is finite if and only if the pullback of E to some finite etale\nGalois covering of X is trivial. We prove the same statement when X is a\ncompact complex manifold admitting a Gauduchon astheno-Kahler metric.\n",
"title": "A characterization of finite vector bundles on Gauduchon astheno-Kahler manifolds"
}
| null | null | null | null | true | null |
14925
| null |
Default
| null | null |
null |
{
"abstract": " The APerture SYNthesis SIMulator is a simple interactive tool to help the\nstudents visualize and understand the basics of the Aperture Synthesis\ntechnique, applied to astronomical interferometers. The users can load many\ndifferent interferometers and source models (and also create their own), change\nthe observing parameters (e.g., source coordinates, observing wavelength,\nantenna location, integration time, etc.), and even deconvolve the\ninterferometric images and corrupt the data with gain errors (amplitude and\nphase). The program is fully interactive and all the figures are updated in\nreal time. APSYNSIM has already been used in several interferometry schools and\nhas got very positive feedback from the students.\n",
"title": "APSYNSIM: An Interactive Tool To Learn Interferometry"
}
| null | null |
[
"Physics"
] | null | true | null |
14926
| null |
Validated
| null | null |
null |
{
"abstract": " An expression for the dimensionless dissipation rate was derived from the\nKarman-Howarth equation by asymptotic expansion of the second- and third- order\nstructure functions in powers of the inverse Reynolds number. The implications\nof the time-derivative term for the assumption of local stationarity (or local\nequilibrium) which underpins the derivation of the Kolmogorov `4/5' law for the\nthird-order structure function were studied. It was concluded that neglect of\nthe time-derivative cannot be justified by reason of restriction to certain\nscales (the inertial range) nor to large Reynolds numbers. In principle,\ntherefore, the hypothesis cannot be correct, although it may be a good\napproximation. It follows, at least in principle, that the quantitative aspects\nof the hypothesis of local stationarity could be tested by a comparison of the\nasymptotic dimensionless dissipation rate for free decay with that for the\nstationary case. But in practice this is complicated by the absence of an\nagreed evolution time for making the measurements during the decay. However, we\ncan assess the quantitative error involved in using the hypothesis by comparing\nthe exact asymptotic value of the dimensionless dissipation in free decay\ncalculated on the assumption of local stationarity to the experimentally\ndetermined value (e.g. by means of direct numerical simulation), as this\nrelationship holds for all measuring times. Should the assumption of local\nstationarity lead to significant error, then the `4/5' law needs to be\ncorrected. Despite this, scale invariance in wavenumber space appears to hold\nin the formal limit of infinite Reynolds numbers, which implies that the `-5/3'\nenergy spectrum does not require correction in this limit.\n",
"title": "The dimensionless dissipation rate and the Kolmogorov (1941) hypothesis of local stationarity in freely decaying isotropic turbulence"
}
| null | null | null | null | true | null |
14927
| null |
Default
| null | null |
null |
{
"abstract": " Markov chain Monte Carlo is widely used in a variety of scientific\napplications to generate approximate samples from intractable distributions. A\nthorough understanding of the convergence and mixing properties of these Markov\nchains can be obtained by studying the spectrum of the associated Markov\noperator. While several methods to bound/estimate the second largest eigenvalue\nare available in the literature, very few general techniques for consistent\nestimation of the entire spectrum have been proposed. Existing methods for this\npurpose require the Markov transition density to be available in closed form,\nwhich is often not true in practice, especially in modern statistical\napplications. In this paper, we propose a novel method to consistently estimate\nthe entire spectrum of a general class of Markov chains arising from a popular\nand widely used statistical approach known as Data Augmentation. The transition\ndensities of these Markov chains can often only be expressed as intractable\nintegrals. We illustrate the applicability of our method using real and\nsimulated data.\n",
"title": "Consistent estimation of the spectrum of trace class data augmentation algorithms"
}
| null | null | null | null | true | null |
14928
| null |
Default
| null | null |
null |
{
"abstract": " Previous research using evolutionary computation in Multi-Agent Systems\nindicates that assigning fitness based on team vs.\\ individual behavior has a\nstrong impact on the ability of evolved teams of artificial agents to exhibit\nteamwork in challenging tasks. However, such research only made use of\nsingle-objective evolution. In contrast, when a multiobjective evolutionary\nalgorithm is used, populations can be subject to individual-level objectives,\nteam-level objectives, or combinations of the two. This paper explores the\nperformance of cooperatively coevolved teams of agents controlled by artificial\nneural networks subject to these types of objectives. Specifically, predator\nagents are evolved to capture scripted prey agents in a torus-shaped grid\nworld. Because of the tension between individual and team behaviors, multiple\nmodes of behavior can be useful, and thus the effect of modular neural networks\nis also explored. Results demonstrate that fitness rewarding individual\nbehavior is superior to fitness rewarding team behavior, despite being applied\nto a cooperative task. However, the use of networks with multiple modules\nallows predators to discover intelligent behavior, regardless of which type of\nobjectives are used.\n",
"title": "Balancing Selection Pressures, Multiple Objectives, and Neural Modularity to Coevolve Cooperative Agent Behavior"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14929
| null |
Validated
| null | null |
null |
{
"abstract": " Ensemble averaging experiments may conceal many fundamental molecular\ninteractions. To overcome that, a high-throughput detection of single molecules\nor colloidal nanodots is crucial for biomedical, nanoelectronic, and\nsolid-state applications. One-dimensional (1D) discrete flow of nanoscale\nobjects is an efficient approach in this direction. The development of simple\nand cost-effective nanofluidic devices is a critical step to realise 1D flow.\nThis letter presents a nanofabrication technique using\nshadow-angle-electron-beam-deposition for a high-throughput preparation of\nparallel nanofluidic channels. These were used to flow and detect DNA,\ncarbon-nanodots, and organic fluorophores. The 1D molecular mass transport was\nperformed using electro-osmotic flow. The 1D flow behaviour was identified and\nanalysed using two-focus fluorescence correlation spectroscopy (2fFCS). A range\nof flow velocities of single molecules was achieved. The transitions of single\nmolecules or nanodots through the two foci were quantitatively analysed using\nconfocal scanning imaging, correlative photon detection, and burst size\ndistribution analysis. The results suggest an efficient nanofabrication\ntechnique is developed to prepare nanofluidic devices. This first demonstration\nof high-throughput nanochannel fabrication process and using 2fFCS-based single\nmolecule flow detection should have a potential impact on ultra-sensitive\nbiomedical diagnostics and studying biomolecular interactions as well as\nnanomaterials.\n",
"title": "High-throughput nanofluidic device for one-dimensional confined detection of single fluorophores"
}
| null | null | null | null | true | null |
14930
| null |
Default
| null | null |
null |
{
"abstract": " Joint analysis of data from multiple information repositories facilitates\nuncovering the underlying structure in heterogeneous datasets. Single and\ncoupled matrix-tensor factorization (CMTF) has been widely used in this context\nfor imputation-based recommendation from ratings, social network, and other\nuser-item data. When this side information is in the form of item-item\ncorrelation matrices or graphs, existing CMTF algorithms may fall short.\nAlleviating current limitations, we introduce a novel model coined coupled\ngraph-tensor factorization (CGTF) that judiciously accounts for graph-related\nside information. The CGTF model has the potential to overcome practical\nchallenges, such as missing slabs from the tensor and/or missing rows/columns\nfrom the correlation matrices. A novel alternating direction method of\nmultipliers (ADMM) is also developed that recovers the nonnegative factors of\nCGTF. Our algorithm enjoys closed-form updates that result in reduced\ncomputational complexity and allow for convergence claims. A novel direction is\nfurther explored by employing the interpretable factors to detect graph\ncommunities having the tensor as side information. The resulting community\ndetection approach is successful even when some links in the graphs are\nmissing. Results with real data sets corroborate the merits of the proposed\nmethods relative to state-of-the-art competing factorization techniques in\nproviding recommendations and detecting communities.\n",
"title": "Coupled Graphs and Tensor Factorization for Recommender Systems and Community Detection"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
14931
| null |
Validated
| null | null |
null |
{
"abstract": " Algebraic methods have a long history in statistics. The most prominent\nmanifestation of modern algebra in statistics can be seen in the field of\nalgebraic statistics, which brings tools from commutative algebra and algebraic\ngeometry to bear on statistical problems. Now over two decades old, algebraic\nstatistics has applications in a wide range of theoretical and applied\nstatistical domains. Nevertheless, algebraic statistical methods are still not\nmainstream, mostly due to a lack of easy off-the-shelf implementations. In this\narticle we debut m2r, an R package that connects R to Macaulay2 through a\npersistent back-end socket connection running locally or on a cloud server.\nTopics range from basic use of m2r to applications and design philosophy.\n",
"title": "A computer algebra system for R: Macaulay2 and the m2r package"
}
| null | null | null | null | true | null |
14932
| null |
Default
| null | null |
null |
{
"abstract": " We explore theoretically the magnetoresistance of Weyl semimetals in\ntransversal magnetic fields away from charge neutrality. The analysis within\nthe self-consistent Born approximation is done for the two different models of\ndisorder: (i) short-range impurties and (ii) charged (Coulomb) impurities. For\nthese models of disorder, we calculate the conductivity away from charge\nneutrality point as well as the Hall conductivity, and analyze the transversal\nmagnetoresistance (TMR) and Shubnikov-de Haas oscillations for both types of\ndisorder. We further consider a model with Weyl nodes shifted in energy with\nrespect to each other (as found in various materials) with the chemical\npotential corresponding to the total charge neutrality. In the experimentally\nmost relevant case of Coulomb impurities, we find in this model a large TMR in\na broad range of quantizing magnetic fields. More specifically, in the\nultra-quantum limit, where only the zeroth Landau level is effective, the TMR\nis linear in magnetic field. In the regime of moderate (but still quantizing)\nmagnetic fields, where the higher Landau levels are relevant, the rapidly\ngrowing TMR is supplemented by strong Shubnikov-de Haas oscillations,\nconsistent with experimental observations.\n",
"title": "Transversal magnetoresistance and Shubnikov-de Haas oscillations in Weyl semimetals"
}
| null | null | null | null | true | null |
14933
| null |
Default
| null | null |
null |
{
"abstract": " The availability of data sets with large numbers of variables is rapidly\nincreasing. The effective application of Bayesian variable selection methods\nfor regression with these data sets has proved difficult since available Markov\nchain Monte Carlo methods do not perform well in typical problem sizes of\ninterest. The current paper proposes new adaptive Markov chain Monte Carlo\nalgorithms to address this shortcoming. The adaptive design of these algorithms\nexploits the observation that in large $p$ small $n$ settings, the majority of\nthe $p$ variables will be approximately uncorrelated a posteriori. The\nalgorithms adaptively build suitable non-local proposals that result in moves\nwith squared jumping distance significantly larger than standard methods. Their\nperformance is studied empirically in high-dimension problems (with both\nsimulated and actual data) and speedups of up to 4 orders of magnitude are\nobserved. The proposed algorithms are easily implementable on multi-core\narchitectures and are well suited for parallel tempering or sequential Monte\nCarlo implementations.\n",
"title": "In Search of Lost (Mixing) Time: Adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p"
}
| null | null | null | null | true | null |
14934
| null |
Default
| null | null |
null |
{
"abstract": " Several growth models have been proposed in the literature for scale-free\ncomplex networks, with a range of fitness-based attachment models gaining\nprominence recently. However, the processes by which such fitness-based\nattachment behaviour can arise are less well understood, making it difficult to\ncompare the relative merits of such models. This paper analyses an evolutionary\nmechanism that would give rise to a fitness-based attachment process. In\nparticular, it is proven by analytical and numerical methods that in\nhomogeneous networks, the minimisation of maximum exposure to node unfitness\nleads to attachment probabilities that are proportional to node fitness. This\nresult is then extended to heterogeneous networks, with supply chain networks\nbeing used as an example.\n",
"title": "Network growth models: A behavioural basis for attachment proportional to fitness"
}
| null | null | null | null | true | null |
14935
| null |
Default
| null | null |
null |
{
"abstract": " Self-paced learning (SPL) is a new methodology that simulates the learning\nprinciple of humans/animals to start learning easier aspects of a learning\ntask, and then gradually take more complex examples into training. This\nnew-coming learning regime has been empirically substantiated to be effective\nin various computer vision and pattern recognition tasks. Recently, it has been\nproved that the SPL regime has a close relationship to a implicit self-paced\nobjective function. While this implicit objective could provide helpful\ninterpretations to the effectiveness, especially the robustness, insights under\nthe SPL paradigms, there are still no theoretical results strictly proved to\nverify such relationship. To this issue, in this paper, we provide some\nconvergence results on this implicit objective of SPL. Specifically, we prove\nthat the learning process of SPL always converges to critical points of this\nimplicit objective under some mild conditions. This result verifies the\nintrinsic relationship between SPL and this implicit objective, and makes the\nprevious robustness analysis on SPL complete and theoretically rational.\n",
"title": "On Convergence Property of Implicit Self-paced Objective"
}
| null | null | null | null | true | null |
14936
| null |
Default
| null | null |
null |
{
"abstract": " While the emerging evidence indicates that the pathogenesis of Parkinson's\ndisease (PD) is strongly correlated to the accumulation of alpha-synuclein\n({\\alpha}-syn) aggregates, there has been no clinical success in\nanti-aggregation agents for the disease to date. Here we show that graphene\nquantum dots (GQDs) exhibit anti-amyloid activity via direct interaction with\n{\\alpha}-syn. Employing biophysical, biochemical, and cell-based assays as well\nas molecular dynamics (MD) simulation, we find that GQDs have notable potency\nin not only inhibiting fibrillization of {\\alpha}-syn but also disaggregating\nmature fibrils in a time-dependent manner. Remarkably, GQDs rescue neuronal\ndeath and synaptic loss, reduce Lewy body (LB)/Lewy neurite (LN) formation,\nameliorate mitochondrial dysfunctions, and prevent neuron-to-neuron\ntransmission of {\\alpha}-syn pathology induced by {\\alpha}-syn preformed\nfibrils (PFFs) in neurons. In addition, in vivo administration of GQDs protects\nagainst {\\alpha}-syn PFFs-induced loss of dopamine neurons, LB/LN pathology,\nand behavioural deficits through the penetration of the blood-brain barrier\n(BBB). The finding that GQDs function as an anti-aggregation agent provides a\npromising novel therapeutic target for the treatment of PD and related\n{\\alpha}-synucleinopathies.\n",
"title": "Graphene quantum dots prevent alpha-synucleinopathy in Parkinson's disease"
}
| null | null | null | null | true | null |
14937
| null |
Default
| null | null |
null |
{
"abstract": " We study Harmonic Soft Spheres as a model of thermal structural glasses in\nthe limit of infinite dimensions. We show that cooling, compressing and\nshearing a glass lead to a Gardner transition and, hence, to a marginally\nstable amorphous solid as found for Hard Spheres systems. A general outcome of\nour results is that a reduced stability of the glass favors the appearance of\nthe Gardner transition. Therefore using strong perturbations, e.g. shear and\ncompression, on standard glasses or using weak perturbations on weakly stable\nglasses, e.g. the ones prepared close to the jamming point, are the generic\nways to induce a Gardner transition. The formalism that we discuss allows to\nstudy general perturbations, including strain deformations that are important\nto study soft glassy rheology at the mean field level.\n",
"title": "Liu-Nagel phase diagrams in infinite dimension"
}
| null | null | null | null | true | null |
14938
| null |
Default
| null | null |
null |
{
"abstract": " We introduce diffusively coupled networks where the dynamical system at each\nvertex is planar Hamiltonian. The problems we address are synchronisation and\nan analogue of diffusion-driven Turing instability for time-dependent\nhomogeneous states. As a consequence of the underlying Hamiltonian structure\nthere exist unusual behaviours compared with networks of coupled limit cycle\noscillators or activator-inhibitor systems.\n",
"title": "Networks of planar Hamiltonian systems"
}
| null | null | null | null | true | null |
14939
| null |
Default
| null | null |
null |
{
"abstract": " Recent advances in visual tracking showed that deep Convolutional Neural\nNetworks (CNN) trained for image classification can be strong feature\nextractors for discriminative trackers. However, due to the drastic difference\nbetween image classification and tracking, extra treatments such as model\nensemble and feature engineering must be carried out to bridge the two domains.\nSuch procedures are either time consuming or hard to generalize well across\ndatasets. In this paper we discovered that the internal structure of Region\nProposal Network (RPN)'s top layer feature can be utilized for robust visual\ntracking. We showed that such property has to be unleashed by a novel loss\nfunction which simultaneously considers classification accuracy and bounding\nbox quality. Without ensemble and any extra treatment on feature maps, our\nproposed method achieved state-of-the-art results on several large scale\nbenchmarks including OTB50, OTB100 and VOT2016. We will make our code publicly\navailable.\n",
"title": "Robust Tracking Using Region Proposal Networks"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14940
| null |
Validated
| null | null |
null |
{
"abstract": " We construct a fixed parameter algorithm parameterized by d and k that takes\nas an input a graph G' obtained from a d-degenerate graph G by complementing on\nat most k arbitrary subsets of the vertex set of G and outputs a graph H such\nthat G and H agree on all but f(d,k) vertices.\nOur work is motivated by the first order model checking in graph classes that\nare first order interpretable in classes of sparse graphs. We derive as a\ncorollary that if G_0 is a graph class with bounded expansion, then the first\norder model checking is fixed parameter tractable in the class of all graphs\nthat can obtained from a graph G from G_0 by complementing on at most k\narbitrary subsets of the vertex set of G; this implies an earlier result that\nthe first order model checking is fixed parameter tractable in graph classes\ninterpretable in classes of graphs with bounded maximum degree.\n",
"title": "Recovering sparse graphs"
}
| null | null | null | null | true | null |
14941
| null |
Default
| null | null |
null |
{
"abstract": " We formalize the arithmetic topology, i.e. a relationship between knots and\nprimes. Namely, using the notion of a cluster C*-algebra we construct a functor\nfrom the category of 3-dimensional manifolds M to a category of algebraic\nnumber fields K, such that the prime ideals (ideals, resp.) in the ring of\nintegers of K correspond to knots (links, resp.) in M. It is proved that the\nfunctor realizes all axioms of the arithmetic topology conjectured in the\n1960's by Manin, Mazur and Mumford.\n",
"title": "Remark on arithmetic topology"
}
| null | null | null | null | true | null |
14942
| null |
Default
| null | null |
null |
{
"abstract": " Deep neural networks have become invaluable tools for supervised machine\nlearning, e.g., classification of text or images. While often offering superior\nresults over traditional techniques and successfully expressing complicated\npatterns in data, deep architectures are known to be challenging to design and\ntrain such that they generalize well to new data. Important issues with deep\narchitectures are numerical instabilities in derivative-based learning\nalgorithms commonly called exploding or vanishing gradients. In this paper we\npropose new forward propagation techniques inspired by systems of Ordinary\nDifferential Equations (ODE) that overcome this challenge and lead to\nwell-posed learning problems for arbitrarily deep networks.\nThe backbone of our approach is our interpretation of deep learning as a\nparameter estimation problem of nonlinear dynamical systems. Given this\nformulation, we analyze stability and well-posedness of deep learning and use\nthis new understanding to develop new network architectures. We relate the\nexploding and vanishing gradient phenomenon to the stability of the discrete\nODE and present several strategies for stabilizing deep learning for very deep\nnetworks. While our new architectures restrict the solution space, several\nnumerical experiments show their competitiveness with state-of-the-art\nnetworks.\n",
"title": "Stable Architectures for Deep Neural Networks"
}
| null | null |
[
"Computer Science",
"Mathematics"
] | null | true | null |
14943
| null |
Validated
| null | null |
null |
{
"abstract": " We introduce the notion of a \"crystallographic sphere packing,\" defined to be\none whose limit set is that of a geometrically finite hyperbolic reflection\ngroup in one higher dimension. We exhibit for the first time an infinite family\nof conformally-inequivalent such with all radii being reciprocals of integers.\nWe then prove a result in the opposite direction: the \"superintegral\" ones\nexist only in finitely many \"commensurability classes,\" all in dimensions below\n30.\n",
"title": "Geometry and Arithmetic of Crystallographic Sphere Packings"
}
| null | null | null | null | true | null |
14944
| null |
Default
| null | null |
null |
{
"abstract": " The paper analyzes special cyclic Jacobi methods for symmetric matrices of\norder $4$. Only those cyclic pivot strategies that enable full parallelization\nof the method are considered. These strategies, unlike the serial pivot\nstrategies, can force the method to be very slow or very fast within one cycle,\ndepending on the underlying matrix. Hence, for the global convergence proof one\nhas to consider two or three adjacent cycles. It is proved that for any\nsymmetric matrix $A$ of order~$4$ the inequality\n$S(A^{[2]})\\leq(1-10^{-5})S(A)$ holds, where $A^{[2]}$ results from $A$ by\napplying two cycles of a particular parallel method. Here $S(A)$ stands for the\nFrobenius norm of the strictly upper-triangular part of $A$. The result holds\nfor two special parallel strategies and implies the global convergence of the\nmethod under all possible fully parallel strategies. It is also proved that for\nevery $\\epsilon>0$ and $n\\geq4$ there exist a symmetric matrix $A(\\epsilon)$ of\norder $n$ and a cyclic strategy, such that upon completion of the first cycle\nof the appropriate Jacobi method the inequality $S(A^{[1]})>\n(1-\\epsilon)S(A(\\epsilon))$ holds.\n",
"title": "On the global convergence of the Jacobi method for symmetric matrices of order 4 under parallel strategies"
}
| null | null |
[
"Mathematics"
] | null | true | null |
14945
| null |
Validated
| null | null |
null |
{
"abstract": " Applied researchers often construct a network from a random sample of nodes\nin order to infer properties of the parent network. Two of the most widely used\nsampling schemes are subgraph sampling, where we sample each vertex\nindependently with probability $p$ and observe the subgraph induced by the\nsampled vertices, and neighborhood sampling, where we additionally observe the\nedges between the sampled vertices and their neighbors.\nIn this paper, we study the problem of estimating the number of motifs as\ninduced subgraphs under both models from a statistical perspective. We show\nthat: for any connected $h$ on $k$ vertices, to estimate $s=\\mathsf{s}(h,G)$,\nthe number of copies of $h$ in the parent graph $G$ of maximum degree $d$, with\na multiplicative error of $\\epsilon$, (a) For subgraph sampling, the optimal\nsampling ratio $p$ is $\\Theta_{k}(\\max\\{ (s\\epsilon^2)^{-\\frac{1}{k}}, \\;\n\\frac{d^{k-1}}{s\\epsilon^{2}} \\})$, achieved by Horvitz-Thompson type of\nestimators. (b) For neighborhood sampling, we propose a family of estimators,\nencompassing and outperforming the Horvitz-Thompson estimator and achieving the\nsampling ratio $O_{k}(\\min\\{ (\\frac{d}{s\\epsilon^2})^{\\frac{1}{k-1}}, \\;\n\\sqrt{\\frac{d^{k-2}}{s\\epsilon^2}}\\})$. This is shown to be optimal for all\nmotifs with at most $4$ vertices and cliques of all sizes.\nThe matching minimax lower bounds are established using certain algebraic\nproperties of subgraph counts. These results quantify how much more informative\nneighborhood sampling is than subgraph sampling, as empirically verified by\nexperiments on both synthetic and real-world data. We also address the issue of\nadaptation to the unknown maximum degree, and study specific problems for\nparent graphs with additional structures, e.g., trees or planar graphs.\n",
"title": "Counting Motifs with Graph Sampling"
}
| null | null | null | null | true | null |
14946
| null |
Default
| null | null |
null |
{
"abstract": " With the tremendous increase in the number of smart phones, app stores have\nbeen overwhelmed with applications requiring geo-location access in order to\nprovide their users better services through personalization. Revealing a user's\nlocation to these third party apps, no matter at what frequency, is a severe\nprivacy breach which can have unpleasant social consequences. In order to\nprevent inference attacks derived from geo-location data, a number of location\nobfuscation techniques have been proposed in the literature. However, none of\nthem provides any objective measure of privacy guarantee. Some work has been\ndone to define differential privacy for geo-location data in the form of\ngeo-indistinguishability with l privacy guarantee. These techniques do not\nutilize any prior background information about the Points of Interest (PoIs) of\na user and apply Laplacian noise to perturb all the location coordinates.\nIntuitively, the utility of such a mechanism can be improved if the noise\ndistribution is derived after considering some prior information about PoIs.\nIn this paper, we apply the standard definition of differential privacy on\ngeo-location data. We use first principles to model various privacy and utility\nconstraints, prior background information available about the PoIs\n(distribution of PoI locations in a 1D plane) and the granularity of the input\nrequired by different types of apps, in order to produce a more accurate and a\nutility maximizing differentially private algorithm for geo-location data at\nthe OS level. We investigate this for a particular category of apps and for\nsome specific scenarios. This will also help us to verify that whether\nLaplacian noise is still the optimal perturbation when we have such prior\ninformation.\n",
"title": "Optimizing noise level for perturbing geo-location data"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14947
| null |
Validated
| null | null |
null |
{
"abstract": " For an affine toric variety $\\mathrm{Spec}(A)$, we give a convex geometric\ndescription of the Hodge decomposition of its Hochschild cohomology. Under\ncertain assumptions we compute the dimensions of the Hodge summands\n$T^1_{(i)}(A)$, generalizing the existing results about the Andre-Quillen\ncohomology group $T^1_{(1)}(A)$. We prove that every Poisson structure on a\npossibly singular affine toric variety can be quantized in the sense of\ndeformation quantization.\n",
"title": "Hochschild Cohomology and Deformation Quantization of Affine Toric Varieties"
}
| null | null | null | null | true | null |
14948
| null |
Default
| null | null |
null |
{
"abstract": " Machine learning methods in general and Deep Neural Networks in particular\nhave shown to be vulnerable to adversarial perturbations. So far this\nphenomenon has mainly been studied in the context of whole-image\nclassification. In this contribution, we analyse how adversarial perturbations\ncan affect the task of semantic segmentation. We show how existing adversarial\nattackers can be transferred to this task and that it is possible to create\nimperceptible adversarial perturbations that lead a deep network to misclassify\nalmost all pixels of a chosen class while leaving network prediction nearly\nunchanged outside this class.\n",
"title": "Adversarial Examples for Semantic Image Segmentation"
}
| null | null | null | null | true | null |
14949
| null |
Default
| null | null |
null |
{
"abstract": " For a signed cyclic graph G, we can construct a unique virtual link L by\ntaking the medial construction and convert 4-valent vertices of the medial\ngraph to crossings according to the signs. If a virtual link can occur in this\nway then we say that the virtual link is graphical. In the article we shall\nprove that a virtual link L is graphical if and only if it is checkerboard\ncolorable. On the other hand, we introduce a polynomial F[G] for signed cyclic\ngraphs, which is defined via a deletion-marking recursion. We shall establish\nthe relationship between F[G] of a signed cyclic graph G and the bracket\npolynomial of one of the virtual link diagrams associated with G. Finally we\ngive a spanning subgraph expansion for F[G].\n",
"title": "Graphical virtual links and a polynomial of signed cyclic graphs"
}
| null | null | null | null | true | null |
14950
| null |
Default
| null | null |
null |
{
"abstract": " A single-particle mobility edge (SPME) marks a critical energy separating\nextended from localized states in a quantum system. In one-dimensional systems\nwith uncorrelated disorder, a SPME cannot exist, since all single-particle\nstates localize for arbitrarily weak disorder strengths. However, if\ncorrelations are present in the disorder potential, the localization transition\ncan occur at a finite disorder strength and SPMEs become possible. In this\nwork, we find experimental evidence for the existence of such a SPME in a\none-dimensional quasi-periodic optical lattice. Specifically, we find a regime\nwhere extended and localized single-particle states coexist, in good agreement\nwith theoretical simulations, which predict a SPME in this regime.\n",
"title": "Exploring the Single-Particle Mobility Edge in a One-Dimensional Quasiperiodic Optical Lattice"
}
| null | null | null | null | true | null |
14951
| null |
Default
| null | null |
null |
{
"abstract": " (Abridged) Low-luminosity, gas-rich blue compact galaxies (BCG) are ideal\nlaboratories to investigate many aspects of the star formation in galaxies. We\nstudy the morphology, stellar content, kinematics, and the nebular excitation\nand ionization mechanism in the BCG Haro 14 by means of integral field\nobservations with VIMOS in the VLT. From these data we build maps in continuum\nand in the brighter emission lines, produce line-ratio maps, and obtain the\nvelocity and velocity dispersion fields. We also generate the integrated\nspectrum of the major HII regions and young stellar clusters identified in the\nmaps to determine reliable physical parameters and oxygen abundances. We find\nas follows: i) the current star formation in Haro 14 is spatially extended with\nthe major HII regions placed along a linear structure, elongated in the\nnorth-south direction, and in a horseshoe-like curvilinear feature that extends\nabout 760 pc eastward; the continuum emission is more concentrated and peaks\nclose to the galaxy center; ii) two different episodes of star formation are\npresent: the recent starburst, with ages $\\leq$ 6 Myrs and the intermediate-age\nclusters, with ages between 10 and 30 Myrs; these stellar components rest on a\nseveral Gyr old underlying host galaxy; iii) the H$\\alpha$/H$\\beta$ pattern is\ninhomogeneous, with excess color values varying from E(B-V)=0.04 up to\nE(B-V)=1.09; iv) shocks play a significant role in the galaxy; and v) the\nvelocity field displays a complicated pattern with regions of material moving\ntoward us in the east and north galaxy areas. The morphology of Haro 14, its\nirregular velocity field, and the presence of shocks speak in favor of a\nscenario of triggered star formation. Ages of the knots are consistent with the\nongoing burst being triggered by the collective action of stellar winds and\nsupernovae originated in the central clusters.\n",
"title": "Integral field observations of the blue compact galaxy Haro14. Star formation and feedback in dwarf galaxies"
}
| null | null | null | null | true | null |
14952
| null |
Default
| null | null |
null |
{
"abstract": " Tuning cellular network performance against always occurring wireless\nimpairments can dramatically improve reliability to end users. In this paper,\nwe formulate cellular network performance tuning as a reinforcement learning\n(RL) problem and provide a solution to improve the signal to\ninterference-plus-noise ratio (SINR) for indoor and outdoor environments. By\nleveraging the ability of Q-learning to estimate future SINR improvement\nrewards, we propose two algorithms: (1) voice over LTE (VoLTE) downlink closed\nloop power control (PC) and (2) self-organizing network (SON) fault management.\nThe VoLTE PC algorithm uses RL to adjust the indoor base station transmit power\nso that the effective SINR meets the target SINR. The SON fault management\nalgorithm uses RL to improve the performance of an outdoor cluster by resolving\nfaults in the network through configuration management. Both algorithms exploit\nmeasurements from the connected users, wireless impairments, and relevant\nconfiguration parameters to solve a non-convex SINR optimization problem using\nRL. Simulation results show that our proposed RL based algorithms outperform\nthe industry standards today in realistic cellular communication environments.\n",
"title": "A Framework for Automated Cellular Network Tuning with Reinforcement Learning"
}
| null | null |
[
"Statistics"
] | null | true | null |
14953
| null |
Validated
| null | null |
null |
{
"abstract": " Navigation has been a popular area of research in both academia and industry.\nCombined with maps, and different localization technologies, navigation systems\nhave become robust and more usable. By combining navigation with augmented\nreality, it can be improved further to become realistic and user friendly. This\npaper surveys existing researches carried out in this area, describes existing\ntechniques for building augmented reality navigation systems, and the problems\nfaced.\n",
"title": "A Survey of Augmented Reality Navigation"
}
| null | null | null | null | true | null |
14954
| null |
Default
| null | null |
null |
{
"abstract": " We investigate the onset of superconductivity in magnetic field for a clean\ntwo-dimensional multiple-band superconductor in the vicinity of the Lifshitz\ntransition when one of the bands is very shallow. Due to small number of\ncarriers in this band, the quasiclassical Werthamer-Helfand approximation\nbreaks down and Landau quantization has to be taken into account. We found that\nthe transition temperature TC2(H) has giant oscillations and is resonantly\nenhanced at the magnetic fields corresponding to full occupancy of the Landau\nlevels in the shallow band. This enhancement is especially pronounced for the\nlowest Landau level. As a consequence, the reentrant superconducting regions in\nthe temperature-field phase diagram emerge at low temperatures near the\nmagnetic fields at which the chemical potential matches the Landau levels. The\nspecific behavior depends on the relative strength of the intraband and\ninterband pairing interactions and the reentrance is most pronounced in the\npurely interband coupling scenario. The reentrant behavior is suppressed by the\nZeeman spin splitting in the shallow band, the separated regions disappear\nalready for very small spin-splitting factors. On the other hand, the\nreentrance is restored in the resonance cases when the spin-splitting energy\nexactly matches the separation between the Landau levels. The predicted\nbehavior may realize in the gate-tuned FeSe monolayer.\n",
"title": "Strong Landau-quantization effects in high-magnetic-field superconductivity of a two-dimensional multiple-band metal near the Lifshitz transition"
}
| null | null | null | null | true | null |
14955
| null |
Default
| null | null |
null |
{
"abstract": " We study the boundary behavior of the so-called ring $Q$-mappings obtained as\na natural generalization of mappings with bounded distortion. We establish a\nseries of conditions imposed on a function $Q(x)$ for the continuous extension\nof given mappings with respect to prime ends in domains with regular boundaries\nin metric spaces.\n",
"title": "On boundary extension of mappings in metric spaces in terms of prime ends"
}
| null | null | null | null | true | null |
14956
| null |
Default
| null | null |
null |
{
"abstract": " In this work, we consider the problem of combining link, content and temporal\nanalysis for community detection and prediction in evolving networks. Such\ntemporal and content-rich networks occur in many real-life settings, such as\nbibliographic networks and question answering forums. Most of the work in the\nliterature (that uses both content and structure) deals with static snapshots\nof networks, and they do not reflect the dynamic changes occurring over\nmultiple snapshots. Incorporating dynamic changes in the communities into the\nanalysis can also provide useful insights about the changes in the network such\nas the migration of authors across communities. In this work, we propose\nChimera, a shared factorization model that can simultaneously account for graph\nlinks, content, and temporal analysis. This approach works by extracting the\nlatent semantic structure of the network in multidimensional form, but in a way\nthat takes into account the temporal continuity of these embeddings. Such an\napproach simplifies temporal analysis of the underlying network by using the\nembedding as a surrogate. A consequence of this simplification is that it is\nalso possible to use this temporal sequence of embeddings to predict future\ncommunities. We present experimental results illustrating the effectiveness of\nthe approach.\n",
"title": "Temporally Evolving Community Detection and Prediction in Content-Centric Networks"
}
| null | null | null | null | true | null |
14957
| null |
Default
| null | null |
null |
{
"abstract": " In many smart infrastructure applications flexibility in achieving\nsustainability goals can be gained by engaging end-users. However, these users\noften have heterogeneous preferences that are unknown to the decision-maker\ntasked with improving operational efficiency. Modeling user interaction as a\ncontinuous game between non-cooperative players, we propose a robust parametric\nutility learning framework that employs constrained feasible generalized least\nsquares estimation with heteroskedastic inference. To improve forecasting\nperformance, we extend the robust utility learning scheme by employing\nbootstrapping with bagging, bumping, and gradient boosting ensemble methods.\nMoreover, we estimate the noise covariance which provides approximated\ncorrelations between players which we leverage to develop a novel correlated\nutility learning framework. We apply the proposed methods both to a toy example\narising from Bertrand-Nash competition between two firms as well as to data\nfrom a social game experiment designed to encourage energy efficient behavior\namongst smart building occupants. Using occupant voting data for shared\nresources such as lighting, we simulate the game defined by the estimated\nutility functions to demonstrate the performance of the proposed methods.\n",
"title": "A Robust Utility Learning Framework via Inverse Optimization"
}
| null | null | null | null | true | null |
14958
| null |
Default
| null | null |
null |
{
"abstract": " When trying to maximize the adoption of a behavior in a population connected\nby a social network, it is common to strategize about where in the network to\nseed the behavior, often with an element of randomness. Selecting seeds\nuniformly at random is a basic but compelling strategy in that it distributes\nseeds broadly throughout the network. A more sophisticated stochastic strategy,\none-hop targeting, is to select random network neighbors of random individuals;\nthis exploits a version of the friendship paradox, whereby the friend of a\nrandom individual is expected to have more friends than a random individual,\nwith the hope that seeding a behavior at more connected individuals leads to\nmore adoption. Many seeding strategies have been proposed, but empirical\nevaluations have demanded large field experiments designed specifically for\nthis purpose and have yielded relatively imprecise comparisons of strategies.\nHere we show how stochastic seeding strategies can be evaluated more\nefficiently in such experiments, how they can be evaluated \"off-policy\" using\nexisting data arising from experiments designed for other purposes, and how to\ndesign more efficient experiments. In particular, we consider contrasts between\nstochastic seeding strategies and analyze nonparametric estimators adapted from\npolicy evaluation and importance sampling. We use simulations on real networks\nto show that the proposed estimators and designs can dramatically increase\nprecision while yielding valid inference. We then apply our proposed estimators\nto two field experiments, one that assigned households to an intensive\nmarketing intervention and one that assigned students to an anti-bullying\nintervention.\n",
"title": "Evaluating stochastic seeding strategies in networks"
}
| null | null | null | null | true | null |
14959
| null |
Default
| null | null |
null |
{
"abstract": " We study a superconducting transmission line (TL) formed by distributed LC\noscillators and excited by external magnetic fluxes which are aroused from\nrandom magnetization (A) placed in substrate or (B) distributed at interfaces\nof a two-wire TL. Low-frequency dynamics of a random magnetic field is\ndescribed based on the diffusion Langevin equation with a short-range source\ncaused by (a) random amplitude or (b) gradient of magnetization. For a TL\nmodeled as a two-port network with open and shorted ends, the effective\nmagnetic flux at the open end has non-local dependency on noise distribution\nalong the TL. The flux-flux correlation function is evaluated and analyzed for\nthe regimes (Aa), (Ab). (Ba), and (Bb). Essential frequency dispersion takes\nplace around the inverse diffusion time of random flux along the TL. Typically,\nnoise effect increases with size faster than the area of TL. The flux-flux\ncorrelator can be verified both via the population relaxation rate of the\nqubit, which is formed by the Josephson junction shunted by the TL with flux\nnoises, and via random voltage at the open end of the TL.\n",
"title": "Flux noise in a superconducting transmission line"
}
| null | null | null | null | true | null |
14960
| null |
Default
| null | null |
null |
{
"abstract": " Relativistic Newtonian Dynamics (RND) was introduced in a series of recent\npapers by the author, in partial cooperation with J. M. Steiner. RND was\ncapable of describing non-classical behavior of motion under a central\nattracting force. RND incorporates the influence of potential energy on\nspacetime in Newtonian dynamics, treating gravity as a force in flat spacetime.\nIt was shown that this dynamics predicts accurately gravitational time\ndilation, the anomalous precession of Mercury and the periastron advance of any\nbinary.\nIn this paper the model is further refined and extended to describe also the\nmotion of both objects with non-zero mass and massless particles, under a\nconservative attracting force. It is shown that for any conservative force a\nproperly defined energy is conserved on the trajectories and if this force is\ncentral, the angular momentum is also preserved. An RND equation of motion is\nderived for motion under a conservative force. As an application, it is shown\nthat RND predicts accurately also the Shapiro time delay - the fourth test of\nGR.\n",
"title": "Relativistic Newtonian Dynamics for Objects and Particles"
}
| null | null | null | null | true | null |
14961
| null |
Default
| null | null |
null |
{
"abstract": " This paper introduces a new sparse spatio-temporal structured Gaussian\nprocess regression framework for online and offline Bayesian inference. This is\nthe first framework that gives a time-evolving representation of the\ninterdependencies between the components of the sparse signal of interest. A\nhierarchical Gaussian process describes such structure and the\ninterdependencies are represented via the covariance matrices of the prior\ndistributions. The inference is based on the expectation propagation method and\nthe theoretical derivation of the posterior distribution is provided in the\npaper. The inference framework is thoroughly evaluated over synthetic, real\nvideo and electroencephalography (EEG) data where the spatio-temporal evolving\npatterns need to be reconstructed with high accuracy. It is shown that it\nachieves 15% improvement of the F-measure compared with the alternating\ndirection method of multipliers, spatio-temporal sparse Bayesian learning\nmethod and one-level Gaussian process model. Additionally, the required memory\nfor the proposed algorithm is less than in the one-level Gaussian process\nmodel. This structured sparse regression framework is of broad applicability to\nsource localisation and object detection problems with sparse signals.\n",
"title": "Spatio-Temporal Structured Sparse Regression with Hierarchical Gaussian Process Priors"
}
| null | null | null | null | true | null |
14962
| null |
Default
| null | null |
null |
{
"abstract": " Parameterized algorithms are a way to solve hard problems more efficiently,\ngiven that a specific parameter of the input is small. In this paper, we apply\nthis idea to the field of answer set programming (ASP). To this end, we propose\ntwo kinds of graph representations of programs to exploit their treewidth as a\nparameter. Treewidth roughly measures to which extent the internal structure of\na program resembles a tree. Our main contribution is the design of\nparameterized dynamic programming algorithms, which run in linear time if the\ntreewidth and weights of the given program are bounded. Compared to previous\nwork, our algorithms handle the full syntax of ASP. Finally, we report on an\nempirical evaluation that shows good runtime behaviour for benchmark instances\nof low treewidth, especially for counting answer sets.\n",
"title": "Answer Set Solving with Bounded Treewidth Revisited"
}
| null | null | null | null | true | null |
14963
| null |
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| null | null |
null |
{
"abstract": " Discovering community structure in complex networks is a mature field since a\ntremendous number of community detection methods have been introduced in the\nliterature. Nevertheless, it is still very challenging for practioners to\ndetermine which method would be suitable to get insights into the structural\ninformation of the networks they study. Many recent efforts have been devoted\nto investigating various quality scores of the community structure, but the\nproblem of distinguishing between different types of communities is still open.\nIn this paper, we propose a comparative, extensive and empirical study to\ninvestigate what types of communities many state-of-the-art and well-known\ncommunity detection methods are producing. Specifically, we provide\ncomprehensive analyses on computation time, community size distribution, a\ncomparative evaluation of methods according to their optimisation schemes as\nwell as a comparison of their partioning strategy through validation metrics.\nWe process our analyses on a very large corpus of hundreds of networks from\nfive different network categories and propose ways to classify community\ndetection methods, helping a potential user to navigate the complex landscape\nof community detection.\n",
"title": "Community structure: A comparative evaluation of community detection methods"
}
| null | null | null | null | true | null |
14964
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we assume that all isoparametric submanifolds have flat\nsection. The main purpose of this paper is to prove that, if a full irreducible\ncomplete isoparametric submanifold of codimension greater than one in a\nsymmetric space of non-compact type admits a reflective focal submanifold and\nif it of real analytic, then it is a principal orbit of a Hermann type action\non the symmetric space. A hyperpolar action on a symmetric space of non-compact\ntype admits a reflective singular orbit if and only if it is a Hermann type\naction. Hence is not extra the assumption that the isoparametric submanifold\nadmits a reflective focal submanifold. Also, we prove that, if a full\nirreducible complete isoparametric submanifold of codimension greater than one\nin a symmetric space of non-compact type satisfies some additional conditions,\nthen it is a principal orbit of the isotropy action of the symmetric space,\nwhere we need not impose that the submanifold is of real analytic. We use the\nbuilding theory in the proof.\n",
"title": "Classification of isoparametric submanifolds admitting a reflective focal submanifold in symmetric spaces of non-compact type"
}
| null | null | null | null | true | null |
14965
| null |
Default
| null | null |
null |
{
"abstract": " Learning rich and diverse representations is critical for the performance of\ndeep convolutional neural networks (CNNs). In this paper, we consider how to\nuse privileged information to promote inherent diversity of a single CNN model\nsuch that the model can learn better representations and offer stronger\ngeneralization ability. To this end, we propose a novel group orthogonal\nconvolutional neural network (GoCNN) that learns untangled representations\nwithin each layer by exploiting provided privileged information and enhances\nrepresentation diversity effectively. We take image classification as an\nexample where image segmentation annotations are used as privileged information\nduring the training process. Experiments on two benchmark datasets -- ImageNet\nand PASCAL VOC -- clearly demonstrate the strong generalization ability of our\nproposed GoCNN model. On the ImageNet dataset, GoCNN improves the performance\nof state-of-the-art ResNet-152 model by absolute value of 1.2% while only uses\nprivileged information of 10% of the training images, confirming effectiveness\nof GoCNN on utilizing available privileged knowledge to train better CNNs.\n",
"title": "Training Group Orthogonal Neural Networks with Privileged Information"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14966
| null |
Validated
| null | null |
null |
{
"abstract": " Antiunitary representations of Lie groups take values in the group of unitary\nand antiunitary operators on a Hilbert space H. In quantum physics, antiunitary\noperators implement time inversion or a PCT symmetry, and in the modular theory\nof operator algebras they arise as modular conjugations from cyclic separating\nvectors of von Neumann algebras. We survey some of the key concepts at the\nborderline between the theory of local observables (Quantum Field Theory (QFT)\nin the sense of Araki--Haag--Kastler) and modular theory of operator algebras\nfrom the perspective of antiunitary group representations. Here a central point\nis to encode modular objects in standard subspaces V in H which in turn are in\none-to-one correspondence with antiunitary representations of the\nmultiplicative group R^x. Half-sided modular inclusions and modular\nintersections of standard subspaces correspond to antiunitary representations\nof Aff(R), and these provide the basic building blocks for a general theory\nstarted in the 90s with the ground breaking work of Borchers and Wiesbrock and\ndeveloped in various directions in the QFT context. The emphasis of these notes\nlies on the translation between configurations of standard subspaces as they\narise in the context of modular localization developed by Brunetti, Guido and\nLongo, and the more classical context of von Neumann algebras with cyclic\nseparating vectors. Our main point is that configurations of standard subspaces\ncan be studied from the perspective of antiunitary Lie group representations\nand the geometry of the corresponding spaces, which are often fiber bundles\nover ordered symmetric spaces. We expect this perspective to provide new and\nsystematic insight into the much richer configurations of nets of local\nobservables in QFT.\n",
"title": "Antiunitary representations and modular theory"
}
| null | null | null | null | true | null |
14967
| null |
Default
| null | null |
null |
{
"abstract": " Motivation:\nAutomatically testing changes to code is an essential feature of continuous\nintegration. For open-source code, without licensed dependencies, a variety of\ncontinuous integration services exist. The COnstraint-Based Reconstruction and\nAnalysis (COBRA) Toolbox is a suite of open-source code for computational\nmodelling with dependencies on licensed software. A novel automated framework\nof continuous integration in a semi-licensed environment is required for the\ndevelopment of the COBRA Toolbox and related tools of the COBRA community.\nResults:\nARTENOLIS is a general-purpose infrastructure software application that\nimplements continuous integration for open-source software with licensed\ndependencies. It uses a master-slave framework, tests code on multiple\noperating systems, and multiple versions of licensed software dependencies.\nARTENOLIS ensures the stability, integrity, and cross-platform compatibility of\ncode in the COBRA Toolbox and related tools.\nAvailability and Implementation:\nThe continuous integration server, core of the reproducibility and testing\ninfrastructure, can be freely accessed under artenolis.lcsb.uni.lu. The\ncontinuous integration framework code is located in the /.ci directory and at\nthe root of the repository freely available under\ngithub.com/opencobra/cobratoolbox.\n",
"title": "ARTENOLIS: Automated Reproducibility and Testing Environment for Licensed Software"
}
| null | null | null | null | true | null |
14968
| null |
Default
| null | null |
null |
{
"abstract": " We study XXZ spin systems on general graphs. In particular, we describe the\nformation of droplet states near the bottom of the spectrum in the Ising phase\nof the model, where the Z-term dominates the XX-term. As key tools we use\nparticle number conservation of XXZ systems and symmetric products of graphs\nwith their associated adjacency matrices and Laplacians. Of particular interest\nto us are strips and multi-dimensional Euclidean lattices, for which we discuss\nthe existence of spectral gaps above the droplet regime. We also prove a\nCombes-Thomas bound which shows that the eigenstates in the droplet regime are\nexponentially small perturbations of strict (classical) droplets.\n",
"title": "Droplet states in quantum XXZ spin systems on general graphs"
}
| null | null | null | null | true | null |
14969
| null |
Default
| null | null |
null |
{
"abstract": " There is growing interest in estimating and analyzing heterogeneous treatment\neffects in experimental and observational studies. We describe a number of\nmeta-algorithms that can take advantage of any supervised learning or\nregression method in machine learning and statistics to estimate the\nConditional Average Treatment Effect (CATE) function. Meta-algorithms build on\nbase algorithms---such as Random Forests (RF), Bayesian Additive Regression\nTrees (BART) or neural networks---to estimate the CATE, a function that the\nbase algorithms are not designed to estimate directly. We introduce a new\nmeta-algorithm, the X-learner, that is provably efficient when the number of\nunits in one treatment group is much larger than in the other, and can exploit\nstructural properties of the CATE function. For example, if the CATE function\nis linear and the response functions in treatment and control are Lipschitz\ncontinuous, the X-learner can still achieve the parametric rate under\nregularity conditions. We then introduce versions of the X-learner that use RF\nand BART as base learners. In extensive simulation studies, the X-learner\nperforms favorably, although none of the meta-learners is uniformly the best.\nIn two persuasion field experiments from political science, we demonstrate how\nour new X-learner can be used to target treatment regimes and to shed light on\nunderlying mechanisms. A software package is provided that implements our\nmethods.\n",
"title": "Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning"
}
| null | null | null | null | true | null |
14970
| null |
Default
| null | null |
null |
{
"abstract": " We consider the problem of the combinatorial computation of the first Chern\nclass of a circle bundle. N.Mnev found such a formula in terms of canonical\nshellings. It represents certain invariant of a triangulation computed by\nanalyzing cyclic word in 3-character alphabet associated to the bundle. This\ncurvature is a kind of discretization of Konstevich's curvature differential\n2-form.\nWe find a new expression of Mnev's curvature by counting triangles in a\ncyclic word. Our formula is different from that of Mnev. In particular, it is\ncyclically invariant by its very form. We present also some sample computations\nof this invariant and also provide a small Mathematica code for the computation\nof this invariant.\n",
"title": "Counting triangles formula for the first Chern class of a circle bundle"
}
| null | null | null | null | true | null |
14971
| null |
Default
| null | null |
null |
{
"abstract": " We show that standard candles can provide some valuable information about the\ndensity contrast, which could be particularly important at redshifts where\nother observations are not available. We use an inversion method to reconstruct\nthe local radial density profile from luminosity distance observations assuming\nbackground cosmological parameters obtained from large scale observations.\nUsing type Ia Supernovae% (SNe) , Cepheids and the cosmological parameters from\nthe Planck mission we reconstruct the radial density profiles along two\ndifferent directions of the sky. We compare these profiles to other density\nmaps obtained from luminosity density, in particular Keenan et al. 2013 and the\n2M++ galaxy catalogue. The method independently confirms the existence of\ninhomogeneities, could be particularly useful to correctly normalize density\nmaps from galaxy surveys with respect to the average density of the Universe,\nand could clarify the apparent discrepancy between local and large scale\nestimations of the Hubble constant. When better observational supernovae data\nwill be available, the accuracy of the reconstructed density profiles will\nimprove and will allow to further investigate the existence of structures whose\nsize is beyond the reach of galaxy surveys.\n",
"title": "Probing homogeneity with standard candles"
}
| null | null | null | null | true | null |
14972
| null |
Default
| null | null |
null |
{
"abstract": " Understanding exoplanet formation and finding potentially habitable\nexoplanets is vital to an enhanced understanding of the universe. The use of\nnulling interferometry to strongly attenuate the central starlight provides the\nopportunity to see objects closer to the star than ever before. Given that\nexoplanets are usually warm, the 4 microns Mid-Infrared region is advantageous\nfor such observations. The key performance parameters for a nulling\ninterferometer are the extinction ratio it can attain and how well that is\nmaintained across the operational bandwidth. Both parameters depend on the\ndesign and fabrication accuracy of the subcomponents and their wavelength\ndependence. Via detailed simulation it is shown in this paper that a planar\nchalcogenide photonic chip, consisting of three highly fabrication tolerant\nmultimode interference couplers, can exceed an extinction ratio of 60 dB in\ndouble nulling operation and up to 40 dB for a single nulling operation across\na wavelength window of 3.9 to 4.2 microns. This provides a beam combiner with\nsufficient performance, in theory, to image exoplanets.\n",
"title": "Fabrication tolerant chalcogenide mid-infrared multimode interference coupler design with application for Bracewell nulling interferometry"
}
| null | null | null | null | true | null |
14973
| null |
Default
| null | null |
null |
{
"abstract": " We extend the standard Bayesian multivariate Gaussian generative data\nclassifier by considering a generalization of the conjugate, normal-Wishart\nprior distribution and by deriving the hyperparameters analytically via\nevidence maximization. The behaviour of the optimal hyperparameters is explored\nin the high-dimensional data regime. The classification accuracy of the\nresulting generalized model is competitive with state-of-the art Bayesian\ndiscriminant analysis methods, but without the usual computational burden of\ncross-validation.\n",
"title": "Accurate Bayesian Data Classification without Hyperparameter Cross-validation"
}
| null | null |
[
"Computer Science",
"Mathematics",
"Statistics"
] | null | true | null |
14974
| null |
Validated
| null | null |
null |
{
"abstract": " How diverse are sharing economy platforms? Are they fair marketplaces, where\nall participants operate on a level playing field, or are they large-scale\nonline aggregators of offline human biases? Often portrayed as easy-to-access\ndigital spaces whose participants receive equal opportunities, such platforms\nhave recently come under fire due to reports of discriminatory behaviours among\ntheir users, and have been associated with gentrification phenomena that\nexacerbate preexisting inequalities along racial lines. In this paper, we focus\non the Airbnb sharing economy platform, and analyse the diversity of its user\nbase across five large cities. We find it to be predominantly young, female,\nand white. Notably, we find this to be true even in cities with a diverse\nracial composition. We then introduce a method based on the statistical\nanalysis of networks to quantify behaviours of homophily, heterophily and\navoidance between Airbnb hosts and guests. Depending on cities and property\ntypes, we do find signals of such behaviours relating both to race and gender.\nWe use these findings to provide platform design recommendations, aimed at\nexposing and possibly reducing the biases we detect, in support of a more\ninclusive growth of sharing economy platforms.\n",
"title": "Offline Biases in Online Platforms: a Study of Diversity and Homophily in Airbnb"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14975
| null |
Validated
| null | null |
null |
{
"abstract": " We consider the estimation accuracy of individual strength parameters of a\nThurstone choice model when each input observation consists of a choice of one\nitem from a set of two or more items (so called top-1 lists). This model\naccommodates the well-known choice models such as the Luce choice model for\ncomparison sets of two or more items and the Bradley-Terry model for pair\ncomparisons.\nWe provide a tight characterization of the mean squared error of the maximum\nlikelihood parameter estimator. We also provide similar characterizations for\nparameter estimators defined by a rank-breaking method, which amounts to\ndeducing one or more pair comparisons from a comparison of two or more items,\nassuming independence of these pair comparisons, and maximizing a likelihood\nfunction derived under these assumptions. We also consider a related binary\nclassification problem where each individual parameter takes value from a set\nof two possible values and the goal is to correctly classify all items within a\nprescribed classification error.\n",
"title": "Parameter Estimation for Thurstone Choice Models"
}
| null | null | null | null | true | null |
14976
| null |
Default
| null | null |
null |
{
"abstract": " Modeling and parameter estimation for neuronal dynamics are often challenging\nbecause many parameters can range over orders of magnitude and are difficult to\nmeasure experimentally. Moreover, selecting a suitable model complexity\nrequires a sufficient understanding of the model's potential use, such as\nhighlighting essential mechanisms underlying qualitative behavior or precisely\nquantifying realistic dynamics. We present a novel approach that can guide\nmodel development and tuning to achieve desired qualitative and quantitative\nsolution properties. Our approach relies on the presence of disparate time\nscales and employs techniques of separating the dynamics of fast and slow\nvariables, which are well known in the analysis of qualitative solution\nfeatures. We build on these methods to show how it is also possible to obtain\nquantitative solution features by imposing designed dynamics for the slow\nvariables in the form of specified two-dimensional paths in a\nbifurcation-parameter landscape.\n",
"title": "Quantitative modeling and analysis of bifurcation-induced bursting"
}
| null | null |
[
"Physics",
"Mathematics"
] | null | true | null |
14977
| null |
Validated
| null | null |
null |
{
"abstract": " In this paper we prove the uniqueness and radial symmetry of minimizers for\nvariational problems that model several phenomena. The uniqueness is a\nconsequence of the convexity of the functional. The main technique is Fourier\ntransform of tempered distributions.\n",
"title": "Uniqueness and radial symmetry of minimizers for a nonlocal variational problem"
}
| null | null | null | null | true | null |
14978
| null |
Default
| null | null |
null |
{
"abstract": " We consider the problem of differential privacy accounting, i.e. estimation\nof privacy loss bounds, in machine learning in a broad sense. We propose two\nversions of a generic privacy accountant suitable for a wide range of learning\nalgorithms. Both versions are derived in a simple and principled way using\nwell-known tools from probability theory, such as concentration inequalities.\nWe demonstrate that our privacy accountant is able to achieve state-of-the-art\nestimates of DP guarantees and can be applied to new areas like variational\ninference. Moreover, we show that the latter enjoys differential privacy at\nminor cost.\n",
"title": "Improved Accounting for Differentially Private Learning"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
14979
| null |
Validated
| null | null |
null |
{
"abstract": " Scattertext is an open source tool for visualizing linguistic variation\nbetween document categories in a language-independent way. The tool presents a\nscatterplot, where each axis corresponds to the rank-frequency a term occurs in\na category of documents. Through a tie-breaking strategy, the tool is able to\ndisplay thousands of visible term-representing points and find space to legibly\nlabel hundreds of them. Scattertext also lends itself to a query-based\nvisualization of how the use of terms with similar embeddings differs between\ndocument categories, as well as a visualization for comparing the importance\nscores of bag-of-words features to univariate metrics.\n",
"title": "Scattertext: a Browser-Based Tool for Visualizing how Corpora Differ"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14980
| null |
Validated
| null | null |
null |
{
"abstract": " We consider complements of standard Seifert surfaces of special alternating\nlinks. On these handlebodies, we use Honda's method to enumerate those tight\ncontact structures whose dividing sets are isotopic to the link, and find their\nnumber to be the leading coefficient of the Alexander polynomial. The Euler\nclasses of the contact structures are identified with hypertrees in a certain\nhypergraph. Using earlier work, this establishes a connection between contact\ntopology and the Homfly polynomial. We also show that the contact invariants of\nour tight contact structures form a basis for sutured Floer homology. Finally,\nwe relate our methods and results to Kauffman's formal knot theory.\n",
"title": "Tight contact structures on Seifert surface complements"
}
| null | null |
[
"Mathematics"
] | null | true | null |
14981
| null |
Validated
| null | null |
null |
{
"abstract": " We compute the modular transformation formula of the characters for a certain\nfamily of (finitely or uncountably many) simple modules over the simple\n$\\mathcal{N}=2$ vertex operator superalgebra of central charge\n$c_{p,p'}=3\\left(1-\\frac{2p'}{p}\\right),$ where $(p,p')$ is a pair of coprime\npositive integers such that $p\\geq2$. When $p'=1$, the formula coincides with\nthat of the $\\mathcal{N}=2$ unitary minimal series found by F. Ravanini and\nS.-K. Yang. In addition, we study the properties of the corresponding \"modular\n$S$-matrix\", which is no longer a matrix if $p'\\geq2$.\n",
"title": "Modular invariant representations of the $\\mathcal{N}=2$ superconformal algebra"
}
| null | null | null | null | true | null |
14982
| null |
Default
| null | null |
null |
{
"abstract": " Contributions of the CODALEMA/EXTASIS experiment to the 35th International\nCosmic Ray Conference, 12-20 July 2017, Busan, South Korea.\n",
"title": "The CODALEMA/EXTASIS experiment: Contributions to the 35th International Cosmic Ray Conference (ICRC 2017)"
}
| null | null | null | null | true | null |
14983
| null |
Default
| null | null |
null |
{
"abstract": " Clustering samples according to an effective metric and/or vector space\nrepresentation is a challenging unsupervised learning task with a wide spectrum\nof applications. Among several clustering algorithms, k-means and its\nkernelized version have still a wide audience because of their conceptual\nsimplicity and efficacy. However, the systematic application of the kernelized\nversion of k-means is hampered by its inherent square scaling in memory with\nthe number of samples. In this contribution, we devise an approximate strategy\nto minimize the kernel k-means cost function in which the trade-off between\naccuracy and velocity is automatically ruled by the available system memory.\nMoreover, we define an ad-hoc parallelization scheme well suited for hybrid\ncpu-gpu state-of-the-art parallel architectures. We proved the effectiveness\nboth of the approximation scheme and of the parallelization method on standard\nUCI datasets and on molecular dynamics (MD) data in the realm of computational\nchemistry. In this applicative domain, clustering can play a key role for both\nquantitively estimating kinetics rates via Markov State Models or to give\nqualitatively a human compatible summarization of the underlying chemical\nphenomenon under study. For these reasons, we selected it as a valuable\nreal-world application scenario.\n",
"title": "Distributed Kernel K-Means for Large Scale Clustering"
}
| null | null | null | null | true | null |
14984
| null |
Default
| null | null |
null |
{
"abstract": " Solar filaments/prominences are one of the most common features in the\ncorona, which may lead to energetic coronal mass ejections (CMEs) and flares\nwhen they erupt. Filaments are about one hundred times cooler and denser than\nthe coronal material, and physical understanding of their material origin\nremains controversial. Two types of scenarios have been proposed: one argues\nthat the filament plasma is brought into the corona from photosphere or\nchromosphere through a siphon or evaporation/injection process, while the other\nsuggests that the material condenses from the surrounding coronal plasma due to\nthermal instability. The elemental abundance analysis is a reasonable clue to\nconstrain the models, as the siphon or evaporation/injection model would\npredict that the filament material abundances are close to the photospheric or\nchromospheric ones, while the condensation model should have coronal\nabundances. In this letter, we analyze the elemental abundances of a magnetic\ncloud that contains the ejected filament material. The corresponding filament\neruption occurred on 1998 April 29, accompanying an M6.8 class soft X-ray flare\nlocated at the heliographic coordinates S18E20 (NOAA 08210) and a fast halo CME\nwith the linear velocity of 1374 km s$^{-1}$ near the Sun. We find that the\nabundance ratios of elements with low and high First Ionization Potential such\nas Fe/O, Mg/O, and Si/O are 0.150, 0.050, and 0.070, respectively, approaching\ntheir corresponding photospheric values 0.065, 0.081, and 0.066, which does not\nsupport the coronal origin of the filament plasma.\n",
"title": "The Origin of Solar Filament Plasma Inferred from in situ Observations of Elemental Abundances"
}
| null | null | null | null | true | null |
14985
| null |
Default
| null | null |
null |
{
"abstract": " Stochastic convex optimization algorithms are the most popular way to train\nmachine learning models on large-scale data. Scaling up the training process of\nthese models is crucial, but the most popular algorithm, Stochastic Gradient\nDescent (SGD), is a serial method that is surprisingly hard to parallelize. In\nthis paper, we propose an efficient distributed stochastic optimization method\nby combining adaptivity with variance reduction techniques. Our analysis yields\na linear speedup in the number of machines, constant memory footprint, and only\na logarithmic number of communication rounds. Critically, our approach is a\nblack-box reduction that parallelizes any serial online learning algorithm,\nstreamlining prior analysis and allowing us to leverage the significant\nprogress that has been made in designing adaptive algorithms. In particular, we\nachieve optimal convergence rates without any prior knowledge of smoothness\nparameters, yielding a more robust algorithm that reduces the need for\nhyperparameter tuning. We implement our algorithm in the Spark distributed\nframework and exhibit dramatic performance gains on large-scale logistic\nregression problems.\n",
"title": "Distributed Stochastic Optimization via Adaptive SGD"
}
| null | null |
[
"Statistics"
] | null | true | null |
14986
| null |
Validated
| null | null |
null |
{
"abstract": " We combine conditions found in [Wh] with results from [MPR] to show that\nquasi-isometries between uniformly discrete bounded geometry spaces that\nsatisfy linear isoperimetric inequalities are within bounded distance to\nbilipschitz equivalences. We apply this result to regularly branching trees and\nhyperbolic fillings of metric spaces.\n",
"title": "Bilipschitz Equivalence of Trees and Hyperbolic Fillings"
}
| null | null | null | null | true | null |
14987
| null |
Default
| null | null |
null |
{
"abstract": " Direct impact excitation by precipitating electrons is believed to be the\nmain source of 630.0 nm emissions in the cusp ionosphere. However, this paper\ninvestigates a different source, 630.0 emissions caused by thermally excited\natomic oxygen O$(^{1}$D) when high electron temperature prevail in the cusp. On\n22 January 2012 and 14 January 2013, the European Incoherent Scatter Scientific\nAssociation (EISCAT) radar on Svalbard measured electron temperature\nenhancements exceeding 3000 K near magnetic noon in the cusp ionosphere over\nSvalbard. The electron temperature enhancements corresponded to electron\ndensity enhancements exceeding $10^{11}$m$^{-3}$ accompanied by intense 630.0\nnm emissions in a field of view common to both the EISCAT Svalbard radar and a\nmeridian scanning photometer. This offered an excellent opportunity to\ninvestigate the role of thermally excited O$(^{1}$D) 630.0 nm emissions in the\ncusp ionosphere. The thermal component was derived from the EISCAT Radar\nmeasurements and compared with optical data. For both events the calculated\nthermal component had a correlation coefficient greater than 0.8 to the total\nobserved 630.0 nm intensity which contains both thermal and particle impact\ncomponents. Despite fairly constant solar wind, the calculated thermal\ncomponent intensity fluctuated possibly due to dayside transients in the\naurora.\n",
"title": "On the contribution of thermal excitation to the total 630.0 nm emissions in the northern cusp ionosphere"
}
| null | null | null | null | true | null |
14988
| null |
Default
| null | null |
null |
{
"abstract": " Current methods to optimize vaccine dose are purely empirically based,\nwhereas in the drug development field, dosing determinations use far more\nadvanced quantitative methodology to accelerate decision-making. Applying these\nestablished methods in the field of vaccine development may reduce the\ncurrently large clinical trial sample sizes, long time frames, high costs, and\nultimately have a better potential to save lives. We propose the field of\nimmunostimulation/immunodynamic (IS/ID) modelling, which aims to translate\nmathematical frameworks used for drug dosing towards optimizing vaccine dose\ndecision-making. Analogous to PK/PD modelling, IS/ID modelling approaches apply\nmathematical models to describe the underlying mechanisms by which the immune\nresponse is stimulated by vaccination (IS) and the resulting measured immune\nresponse dynamics (ID). To move IS/ID modelling forward, existing datasets and\nfurther data on vaccine allometry and dose-dependent dynamics need to be\ngenerated and collate, requiring a collaborative environment with input from\nacademia, industry, regulators, governmental and non-governmental agencies to\nshare modelling expertise, and connect modellers to vaccine data.\n",
"title": "Dose finding for new vaccines: the role for immunostimulation/immunodynamic modelling"
}
| null | null | null | null | true | null |
14989
| null |
Default
| null | null |
null |
{
"abstract": " We consider the problem of efficiently learning mixtures of a large number of\nspherical Gaussians, when the components of the mixture are well separated. In\nthe most basic form of this problem, we are given samples from a uniform\nmixture of $k$ standard spherical Gaussians, and the goal is to estimate the\nmeans up to accuracy $\\delta$ using $poly(k,d, 1/\\delta)$ samples.\nIn this work, we study the following question: what is the minimum separation\nneeded between the means for solving this task? The best known algorithm due to\nVempala and Wang [JCSS 2004] requires a separation of roughly\n$\\min\\{k,d\\}^{1/4}$. On the other hand, Moitra and Valiant [FOCS 2010] showed\nthat with separation $o(1)$, exponentially many samples are required. We\naddress the significant gap between these two bounds, by showing the following\nresults.\n1. We show that with separation $o(\\sqrt{\\log k})$, super-polynomially many\nsamples are required. In fact, this holds even when the $k$ means of the\nGaussians are picked at random in $d=O(\\log k)$ dimensions.\n2. We show that with separation $\\Omega(\\sqrt{\\log k})$, $poly(k,d,1/\\delta)$\nsamples suffice. Note that the bound on the separation is independent of\n$\\delta$. This result is based on a new and efficient \"accuracy boosting\"\nalgorithm that takes as input coarse estimates of the true means and in time\n$poly(k,d, 1/\\delta)$ outputs estimates of the means up to arbitrary accuracy\n$\\delta$ assuming the separation between the means is $\\Omega(\\min\\{\\sqrt{\\log\nk},\\sqrt{d}\\})$ (independently of $\\delta$).\nWe also present a computationally efficient algorithm in $d=O(1)$ dimensions\nwith only $\\Omega(\\sqrt{d})$ separation. These results together essentially\ncharacterize the optimal order of separation between components that is needed\nto learn a mixture of $k$ spherical Gaussians with polynomial samples.\n",
"title": "On Learning Mixtures of Well-Separated Gaussians"
}
| null | null | null | null | true | null |
14990
| null |
Default
| null | null |
null |
{
"abstract": " We prove that if $p \\equiv 4,7 \\pmod{9}$ is prime and $3$ is not a cube\nmodulo $p$, then both of the equations $x^3+y^3=p$ and $x^3+y^3=p^2$ have a\nsolution with $x,y \\in \\mathbb{Q}$.\n",
"title": "Sylvester's Problem and Mock Heegner Points"
}
| null | null | null | null | true | null |
14991
| null |
Default
| null | null |
null |
{
"abstract": " Many social networks exhibit some underlying community structure. In\nparticular, in the context of historical research, clustering of different\ngroups into warring or friendly factions can lead to a better understanding of\nhow conflicts may arise, and whether they could be avoided or not. In this work\nwe study the crisis that started in 1225 when the Emperor of the Holy Roman\nEmpire, Frederick II and his son Henry VII got into a conflict which almost led\nto the rupture and dissolution of the Empire. We use a spin-glass-based\ncommunity detection algorithm to see how good this method is in detecting this\nrift and compare the results with an analysis performed by one of the authors\n(Gramsch) using standard social balance theory applied to History.\n",
"title": "Community Detection in the Network of German Princes in 1225: a Case Study"
}
| null | null | null | null | true | null |
14992
| null |
Default
| null | null |
null |
{
"abstract": " Online social systems have become important platforms for viral marketing\nwhere the advertising of products is carried out with the communication of\nusers. After adopting the product, the seed buyers may spread the information\nto their friends via online messages e.g. posts and tweets. In another issue,\nelectronic coupon system is one of the relevant promotion vehicles that help\nmanufacturers and retailers attract more potential customers. By offering\ncoupons to seed buyers, there is a chance to convince the influential users who\nare, however, at first not very interested in the product. In this paper, we\npropose a coupon based online influence model and consider the problem that how\nto maximize the profit by selecting appropriate seed buyers. The considered\nproblem herein is markedly different from other influence related problems as\nits objective function is not monotone. We provide an algorithmic analysis and\ngive several algorithms designed with different sampling techniques. In\nparticular, we propose the RA-T and RA-S algorithms which are not only provably\neffective but also scalable on large datasets. The proposed theoretical results\nare evaluated by extensive experiments done on large-scale real-world social\nnetworks. The analysis of this paper also provides an algorithmic framework for\nnon-monotone submodular maximization problems in social networks.\n",
"title": "Coupon Advertising in Online Social Systems: Algorithms and Sampling Techniques"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14993
| null |
Validated
| null | null |
null |
{
"abstract": " The presence of very few statistical studies on auroral omega bands motivated\nus to test-use a semi-automatic method for identifying large-scale undulations\nof the diffuse aurora boundary and to investigate their occurrence. Five\nidentical all-sky cameras with overlapping fields of view provided data for 438\nauroral omega-like structures over Fennoscandian Lapland from 1996 to 2007. The\nresults from this set of omega band events agree remarkably well with previous\nobservations of omega band occurrence in magnetic local time (MLT), lifetime,\nlocation between the region 1 and 2 field-aligned currents, as well as current\ndensity estimates. The average peak emission height of omega forms corresponds\nto the estimated precipitation energies of a few keV, which experienced no\nsignificant change during the events. Analysis of both local and global\nmagnetic indices demonstrates that omega bands are observed during substorm\nexpansion and recovery phases that are more intense than average substorm\nexpansion and recovery phases in the same region. The omega occurrence with\nrespect to the substorm expansion and recovery phases is in a very good\nagreement with an earlier observed distribution of fast earthward flows in the\nplasma sheet during expansion and recovery phases. These findings support the\ntheory that omegas are produced by fast earthward flows and auroral streamers,\ndespite the rarity of good conjugate observations.\n",
"title": "Statistical study of auroral omega bands"
}
| null | null |
[
"Physics"
] | null | true | null |
14994
| null |
Validated
| null | null |
null |
{
"abstract": " The future generation networks: Internet of things (IoT), in combination with\nthe advanced computer vision techniques poses new challenges for securing\nvideos for end-users. The visual devices generally have constrained resources\nin respects to their low computation power, small memory with limited power\nsupply. Therefore, to facilitate the video security in smart environment,\nlightweight security schemes are required instead of inefficient existing\ntraditional cryptography algorithms. This research paper provides the solution\nto overcome such problems. A novel lightweight cipher algorithm is proposed\nhere which targets multimedia in IoT with an in-house name EXPer i.e. Extended\npermutation with eXclusive OR (XOR). EXPer is a symmetric stream cipher that\nconsists of simple XOR and left shift operations with three keys of 128 bits.\nThe proposed cipher algorithm has been tested on various sample videos.\nComparison of proposed algorithm has been made with the traditional cipher\nalgorithms XOR and Advanced Encryption Standard (AES). Visual results confirm\nthat EXPer provides security level equivalent to the AES algorithm with less\ncomputational cost than AES. Therefore, it can easily be perceived that the\nEXPer is a better replacement of AES for securing real-time video applications\nin IoT.\n",
"title": "Efficient Lightweight Encryption Algorithm for Smart Video Applications"
}
| null | null | null | null | true | null |
14995
| null |
Default
| null | null |
null |
{
"abstract": " The challenge of understanding high-temperature superconductivity has led to\na plethora of ideas, but 30 years after its discovery in cuprates, very few\nhave achieved convincing experimental validation. While Hubbard and t-J models\nwere given a lot of attention, a number of recent experiments appear to give\ndecisive support to the model of real-space inter-site pairing and percolative\nsuperconductivity in cuprates. Systematic measurements of the doping dependence\nof the superfluid density show a linear dependence on superfluid density -\nrather than doping - over the entire phase diagram, in accordance with the\nmodel's predictions. The doping-dependence of the anomalous lattice dynamics of\nin-plane Cu-O mode vibrations observed by inelastic neutron scattering, gives\nremarkable reciprocal space signature of the inter-site pairing interaction\nwhose doping dependence closely follows the predicted pair density.\nSymmetry-specific time-domain spectroscopy shows carrier localization, polaron\nformation, pairing and superconductivity to be distinct processes occurring on\ndistinct timescales throughout the entire superconducting phase diagram. The\nthree diverse experimental results confirm non-trivial predictions made more\nthan a decade ago by the inter-site pairing model in the cuprates, remarkably\nalso confirming some of the fundamental notions mentioned in the seminal paper\non the discovery of high-temperature superconductivity in cuprates.\n",
"title": "Inter-site pair superconductivity: origins and recent validation experiments"
}
| null | null | null | null | true | null |
14996
| null |
Default
| null | null |
null |
{
"abstract": " In this work, we apply the Cole's non-standard form of the FDTD to solve the\ntime dependent Schrödinger equation. We deduce the equations for the\nnon-standard FDTD considering an electronic wave function in the presence of\npotentials which can be higher or lower in comparison with the energy of the\nelectron. The non-standard term is found to be almost the same, except for a\nsine functions which is transformed to a hyperbolic sine function,as the\nargument is imaginary when the potential has higher energy than the electron.\nPerfectly Matched Layers using this methodology are also presented.\n",
"title": "Non-standard FDTD implementation of the Schrödinger equation"
}
| null | null | null | null | true | null |
14997
| null |
Default
| null | null |
null |
{
"abstract": " Magnetic oxyselenides have been the topic of research for several decades\nbeing first of interest in the context of photoconductivity and\nthermoelectricity owing to their intrinsic semiconducting properties and\nability to tune the energy gap through metal ion substitution. More recently,\ninterest in the oxyselenides has experienced a resurgence owing to the possible\nrelation to strongly correlated phenomena given the fact that many oxyslenides\nshare a similar structure to unconventional superconducting pnictides and\nchalcogenides. The two dimensional nature of many oxyselenide systems also\ndraws an analogy to cuprate physics where a strong interplay between\nunconventional electronic phases and localised magnetism has been studied for\nseveral decades. It is therefore timely to review the physics of the\noxyselenides in the context of the broader field of strongly correlated\nmagnetism and electronic phenomena. Here we review the current status and\nprogress in this area of research with the focus on the influence of\nlanthanides and transition metal ions on the intertwined magnetic and\nelectronic properties of oxyselenides. The emphasis of the review is on the\nmagnetic properties and comparisons are made with iron based pnictide and\nchalcogenide systems.\n",
"title": "The magnetic and electronic properties of Oxyselenides - influence of transition metal ions and lanthanides"
}
| null | null | null | null | true | null |
14998
| null |
Default
| null | null |
null |
{
"abstract": " This paper presents a novel framework for integration of vision and tactile\nsensing by localizing tactile readings in a visual object map. Intuitively,\nthere are some correspondences, e.g., prominent features, between visual and\ntactile object identification. To apply it in robotics, we propose to localize\ntactile readings in visual images by sharing same sets of feature descriptors\nthrough two sensing modalities. It is then treated as a probabilistic\nestimation problem solved in a framework of recursive Bayesian filtering.\nFeature-based measurement model and Gaussian based motion model are thus built.\nIn our tests, a tactile array sensor is utilized to generate tactile images\nduring interaction with objects and the results have proven the feasibility of\nour proposed framework.\n",
"title": "Localizing the Object Contact through Matching Tactile Features with Visual Map"
}
| null | null |
[
"Computer Science"
] | null | true | null |
14999
| null |
Validated
| null | null |
null |
{
"abstract": " To design a uniaxial anisotropic metamaterial a layered cylindrical\nmetamaterial is introduced for TE polarization. Unlike to the previous work,\nwhich the layers were in radial direction, here the layers are in azimuthal\ndirection. Scattering efficiency for this metamaterial in different frequency\nis analyzed with solving Maxwell's wave equation. It is observed that in some\nfrequencies when the effective permittivity of the structure goes to zero the\nscattering efficiency would be negligible. This result approves the previous\npredictions. It is also found out that the scattering cancellation depends on\nthe relative permittivity of the environmental medium for the cylinder. The\nfinite element simulations are also confirmed the results.\n",
"title": "Scattering Cross Section in a Cylindrical anisotropic layered metamaterial"
}
| null | null | null | null | true | null |
15000
| null |
Default
| null | null |
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