text
null | inputs
dict | prediction
null | prediction_agent
null | annotation
list | annotation_agent
null | multi_label
bool 1
class | explanation
null | id
stringlengths 1
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{
"abstract": " We study the cyclicity in weighted $\\ell^p(\\mathbb{Z})$ spaces. For $p \\geq\n1$ and $\\beta \\geq 0$, let $\\ell^p\\_\\beta(\\mathbb{Z})$ be the space of\nsequences $u=(u\\_n)\\_{n\\in \\mathbb{Z}}$ such that $(u\\_n |n|^{\\beta})\\in\n\\ell^p(\\mathbb{Z}) $. We obtain both necessary conditions and sufficient\nconditions for $u$ to be cyclic in $\\ell^p\\_\\beta(\\mathbb{Z})$, in other words,\nfor $ \\{(u\\_{n+k})\\_{n \\in \\mathbb{Z}},~ k \\in \\mathbb{Z} \\}$ to span a dense\nsubspace of $\\ell^p\\_\\beta(\\mathbb{Z})$. The conditions are given in terms of\nthe Hausdorff dimension and the capacity of the zero set of the Fourier\ntransform of $u$.\n",
"title": "Cyclicity in weighted $\\ell^p$ spaces"
}
| null | null | null | null | true | null |
13601
| null |
Default
| null | null |
null |
{
"abstract": " In order to achieve a good level of autonomy in unmanned helicopters, an\naccurate replication of vehicle dynamics is required, which is achievable\nthrough precise mathematical modeling. This paper aims to identify a parametric\nstate-space system for an unmanned helicopter to a good level of accuracy using\nInvasive Weed Optimization (IWO) algorithm. The flight data of Align TREX 550\nflybarless helicopter is used in the identification process. The rigid-body\ndynamics of the helicopter is modeled in a state-space form that has 40\nparameters, which serve as control variables for the IWO algorithm. The results\nafter 1000 iterations were compared with the traditionally used Prediction\nError Minimization (PEM) method and also with Genetic Algorithm (GA), which\nserve as references. Results show a better level of correlation between the\nactual and estimated responses of the system identified using IWO to that of\nPEM and GA.\n",
"title": "State-Space Identification of Unmanned Helicopter Dynamics using Invasive Weed Optimization Algorithm on Flight Data"
}
| null | null | null | null | true | null |
13602
| null |
Default
| null | null |
null |
{
"abstract": " We devise an approach for targeted molecular design, a problem of interest in\ncomputational drug discovery: given a target protein site, we wish to generate\na chemical with both high binding affinity to the target and satisfactory\npharmacological properties. This problem is made difficult by the enormity and\ndiscreteness of the space of potential therapeutics, as well as the\ngraph-structured nature of biomolecular surface sites. Using a dataset of\nprotein-ligand complexes, we surmount these issues by extracting a signature of\nthe target site with a graph convolutional network and by encoding the discrete\nchemical into a continuous latent vector space. The latter embedding permits\ngradient-based optimization in molecular space, which we perform using learned\ndifferentiable models of binding affinity and other pharmacological properties.\nWe show that our approach is able to efficiently optimize these multiple\nobjectives and discover new molecules with potentially useful binding\nproperties, validated via docking methods.\n",
"title": "Latent Molecular Optimization for Targeted Therapeutic Design"
}
| null | null |
[
"Quantitative Biology"
] | null | true | null |
13603
| null |
Validated
| null | null |
null |
{
"abstract": " Deep neural networks have achieved increasingly accurate results on a wide\nvariety of complex tasks. However, much of this improvement is due to the\ngrowing use and availability of computational resources (e.g use of GPUs, more\nlayers, more parameters, etc). Most state-of-the-art deep networks, despite\nperforming well, over-parameterize approximate functions and take a significant\namount of time to train. With increased focus on deploying deep neural networks\non resource constrained devices like smart phones, there has been a push to\nevaluate why these models are so resource hungry and how they can be made more\nefficient. This work evaluates and compares three distinct methods for deep\nmodel compression and acceleration: weight pruning, low rank factorization, and\nknowledge distillation. Comparisons on VGG nets trained on CIFAR10 show that\neach of the models on their own are effective, but that the true power lies in\ncombining them. We show that by combining pruning and knowledge distillation\nmethods we can create a compressed network 85 times smaller than the original,\nall while retaining 96% of the original model's accuracy.\n",
"title": "SlimNets: An Exploration of Deep Model Compression and Acceleration"
}
| null | null | null | null | true | null |
13604
| null |
Default
| null | null |
null |
{
"abstract": " We give a new axiomatization of the N-pseudospace, studied in [2]\n(Tent(2014)) and [1] (Baudisch,Martin-Pizarro,Ziegler(2014)) based on the\nzigzags introduced in [2]. We also present a more detailed account of the\ncharacterization of forking given in [2].\n",
"title": "An alternative axiomization of $N$-pseudospaces"
}
| null | null | null | null | true | null |
13605
| null |
Default
| null | null |
null |
{
"abstract": " Radiofrequency multipole traps have been used for some decades in cold\ncollision experiments, and are gaining interest for precision spectroscopy due\nto their low mi-cromotion contribution, and the predicted unusual cold-ion\nstructures. However, the experimental realisation is not yet fully controlled,\nand open questions in the operation of these devices remain. We present\nexperimental observations of symmetry breaking of the trapping potential in a\nmacroscopic octupole trap with laser-cooled ions. Numerical simulations have\nbeen performed in order to explain the appearance of additional local potential\nminima, and be able to control them in a next step. We characterize these\nadditional potential minima, in particular with respect to their position,\ntheir potential depth and their probability of population as a function of the\nradial and angular displacement of the trapping rods.\n",
"title": "Symmetry breaking in linear multipole traps"
}
| null | null | null | null | true | null |
13606
| null |
Default
| null | null |
null |
{
"abstract": " Visual data such as videos are often sampled from complex manifold. We\npropose leveraging the manifold structure to constrain the deep action feature\nlearning, thereby minimizing the intra-class variations in the feature space\nand alleviating the over-fitting problem. Considering that manifold can be\ntransferred, layer by layer, from the data domain to the deep features, the\nmanifold priori is posed from the top layer into the back propagation learning\nprocedure of convolutional neural network (CNN). The resulting algorithm\n--Spatio-Temporal Manifold Network-- is solved with the efficient Alternating\nDirection Method of Multipliers and Backward Propagation (ADMM-BP). We\ntheoretically show that STMN recasts the problem as projection over the\nmanifold via an embedding method. The proposed approach is evaluated on two\nbenchmark datasets, showing significant improvements to the baselines.\n",
"title": "Deep Spatio-temporal Manifold Network for Action Recognition"
}
| null | null | null | null | true | null |
13607
| null |
Default
| null | null |
null |
{
"abstract": " Dynamics of waves generated by scopes in gas centrifuges (GC) for isotope\nseparation is considered. The centrifugal acceleration in the GC reaches values\nof the order of $10^6$g. The centrifugal and Coriolis forces modify essentially\nthe conventional sound waves. Three families of the waves with different\npolarisation and dispersion exist in these conditions. Dynamics of the flow in\nthe model GC Iguasu is investigated numerically. Comparison of the results of\nthe numerical modelling of the wave dynamics with the analytical predictions is\nperformed. New phenomena of the resonances in the GC is found. The resonances\noccur for the waves polarized along the rotational axis having the smallest\ndumping due to the viscosity.\n",
"title": "Gas dynamics in strong centrifugal fields"
}
| null | null | null | null | true | null |
13608
| null |
Default
| null | null |
null |
{
"abstract": " In this paper we deal with a robust Stackelberg strategy for the\nNavier--Stokes system. The scheme is based in considering a robust control\nproblem for the \"follower control\" and its associated disturbance function.\nAfterwards, we consider the notion of Stackelberg optimization (which is\nassociated to the \"leader control\") in order to deduce a local null\ncontrollability result for the Navier--Stokes system.\n",
"title": "Robust Stackelberg controllability for the Navier--Stokes equations"
}
| null | null | null | null | true | null |
13609
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, five different approaches for reduced-order modeling of\nbrittle fracture in geomaterials, specifically concrete, are presented and\ncompared. Four of the five methods rely on machine learning (ML) algorithms to\napproximate important aspects of the brittle fracture problem. In addition to\nthe ML algorithms, each method incorporates different physics-based assumptions\nin order to reduce the computational complexity while maintaining the physics\nas much as possible. This work specifically focuses on using the ML approaches\nto model a 2D concrete sample under low strain rate pure tensile loading\nconditions with 20 preexisting cracks present. A high-fidelity finite\nelement-discrete element model is used to both produce a training dataset of\n150 simulations and an additional 35 simulations for validation. Results from\nthe ML approaches are directly compared against the results from the\nhigh-fidelity model. Strengths and weaknesses of each approach are discussed\nand the most important conclusion is that a combination of physics-informed and\ndata-driven features are necessary for emulating the physics of crack\npropagation, interaction and coalescence. All of the models presented here have\nruntimes that are orders of magnitude faster than the original high-fidelity\nmodel and pave the path for developing accurate reduced order models that could\nbe used to inform larger length-scale models with important sub-scale physics\nthat often cannot be accounted for due to computational cost.\n",
"title": "Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications"
}
| null | null | null | null | true | null |
13610
| null |
Default
| null | null |
null |
{
"abstract": " SrTiO$_{3}$, a quantum paraelectric, becomes a metal with a superconducting\ninstability after removal of an extremely small number of oxygen atoms. It\nturns into a ferroelectric upon substitution of a tiny fraction of strontium\natoms with calcium. The two orders may be accidental neighbors or intimately\nconnected, as in the picture of quantum critical ferroelectricity. Here, we\nshow that in Sr$_{1-x}$Ca$_{x}$TiO$_{3-\\delta}$ ($0.002<x<0.009$,\n$\\delta<0.001$) the ferroelectric order coexists with dilute metallicity and\nits superconducting instability in a finite window of doping. At a critical\ncarrier density, which scales with the Ca content, a quantum phase transition\ndestroys the ferroelectric order. We detect an upturn in the normal-state\nscattering and a significant modification of the superconducting dome in the\nvicinity of this quantum phase transition. The enhancement of the\nsuperconducting transition temperature with calcium substitution documents the\nrole played by ferroelectric vicinity in the precocious emergence of\nsuperconductivity in this system, restricting possible theoretical scenarios\nfor pairing.\n",
"title": "A ferroelectric quantum phase transition inside the superconducting dome of Sr$_{1-x}$Ca$_{x}$TiO$_{3-δ}$"
}
| null | null | null | null | true | null |
13611
| null |
Default
| null | null |
null |
{
"abstract": " In the earliest (so-called \"Class 0\") phase of sunlike (low-mass) star\nformation, circumstellar disks are expected to form, feeding the protostars.\nHowever, such disks are difficult to resolve spatially because of their small\nsizes. Moreover, there are theoretical difficulties in producing such disks in\nthe earliest phase, due to the retarding effects of magnetic fields on the\nrotating, collapsing material (so-called \"magnetic braking\"). With the Atacama\nLarge Millimeter/submillimeter Array (ALMA), it becomes possible to uncover\nsuch disks and study them in detail. HH 212 is a very young protostellar\nsystem. With ALMA, we not only detect but also spatially resolve its disk in\ndust emission at submillimeter wavelength. The disk is nearly edge-on and has a\nradius of ~ 60 AU. Interestingly, it shows a prominent equatorial dark lane\nsandwiched between two brighter features, due to relatively low temperature and\nhigh optical depth near the disk midplane. For the first time, this dark lane\nis seen at submillimeter wavelength, producing a \"hamburger\"-shaped appearance\nthat is reminiscent of the scattered-light image of an edge-on disk in optical\nand near infrared. Our observations open up an exciting possibility of directly\ndetecting and characterizing small disks around the youngest protostars through\nhigh-resolution imaging with ALMA, which provides strong constraints on\ntheories of disk formation.\n",
"title": "First Detection of Equatorial Dark Dust Lane in a Protostellar Disk at Submillimeter Wavelength"
}
| null | null | null | null | true | null |
13612
| null |
Default
| null | null |
null |
{
"abstract": " We consider cosmological dynamics in the theory of gravity with the scalar\nfield possessing the nonminimal kinetic coupling to curvature given as $\\eta\nG^{\\mu\\nu}\\phi_{,\\mu}\\phi_{,\\nu}$, where $\\eta$ is an arbitrary coupling\nparameter, and the scalar potential $V(\\phi)$ which assumed to be as general as\npossible. With an appropriate dimensionless parametrization we represent the\nfield equations as an autonomous dynamical system which contains ultimately\nonly one arbitrary function $\\chi (x)= 8 \\pi \\vert \\eta \\vert V(x/\\sqrt{8\n\\pi})$ with $x=\\sqrt{8 \\pi}\\phi$. Then, assuming the rather general properties\nof $\\chi(x)$, we analyze stationary points and their stability, as well as all\npossible asymptotical regimes of the dynamical system. It has been shown that\nfor a broad class of $\\chi(x)$ there exist attractors representing three\naccelerated regimes of the Universe evolution, including de Sitter expansion\n(or late-time inflation), the Little Rip scenario, and the Big Rip scenario. As\nthe specific examples, we consider a power-law potential\n$V(\\phi)=M^4(\\phi/\\phi_0)^\\sigma$, Higgs-like potential\n$V(\\phi)=\\frac{\\lambda}{4}(\\phi^2-\\phi_0^2)^2$, and exponential potential\n$V(\\phi)=M^4 e^{-\\phi/\\phi_0}$.\n",
"title": "General dynamical properties of cosmological models with nonminimal kinetic coupling"
}
| null | null |
[
"Physics"
] | null | true | null |
13613
| null |
Validated
| null | null |
null |
{
"abstract": " In this paper, we present some extensions of interpolation between the\narithmetic-geometric means inequality. Among other inequalities, it is shown\nthat if $A, B, X$ are $n\\times n$ matrices, then \\begin{align*}\n\\|AXB^*\\|^2\\leq\\|f_1(A^*A)Xg_1(B^*B)\\|\\,\\|f_2(A^*A)Xg_2(B^*B)\\|, \\end{align*}\nwhere $f_1,f_2,g_1,g_2$ are non-negative continues functions such that\n$f_1(t)f_2(t)=t$ and $g_1(t)g_2(t)=t\\,\\,(t\\geq0)$. We also obtain the\ninequality \\begin{align*}\n\\left|\\left|\\left|AB^*\\right|\\right|\\right|^2\\nonumber&\\leq\n\\left|\\left|\\left|p(A^*A)^{\\frac{m}{p}}+\n(1-p)(B^*B)^{\\frac{s}{1-p}}\\right|\\right|\\right|\\,\\left|\\left|\\left|(1-p)(A^*A)^{\\frac{n}{1-p}}+\np(B^*B)^{\\frac{t}{p}}\\right|\\right|\\right|, \\end{align*} in which $m,n,s,t$ are\nreal numbers such that $m+n=s+t=1$, $|||\\cdot|||$ is an arbitrary unitarily\ninvariant norm and $p\\in[0,1]$.\n",
"title": "Extensions of interpolation between the arithmetic-geometric mean inequality for matrices"
}
| null | null | null | null | true | null |
13614
| null |
Default
| null | null |
null |
{
"abstract": " English to Indian language machine translation poses the challenge of\nstructural and morphological divergence. This paper describes English to Indian\nlanguage statistical machine translation using pre-ordering and suffix\nseparation. The pre-ordering uses rules to transfer the structure of the source\nsentences prior to training and translation. This syntactic restructuring helps\nstatistical machine translation to tackle the structural divergence and hence\nbetter translation quality. The suffix separation is used to tackle the\nmorphological divergence between English and highly agglutinative Indian\nlanguages. We demonstrate that the use of pre-ordering and suffix separation\nhelps in improving the quality of English to Indian Language machine\ntranslation.\n",
"title": "Machine Translation in Indian Languages: Challenges and Resolution"
}
| null | null | null | null | true | null |
13615
| null |
Default
| null | null |
null |
{
"abstract": " The quantitative composition of metal alloy nanowires on InSb(001)\nsemiconductor surface and gold nanostructures on germanium surface is\ndetermined by blind source separation (BSS) machine learning (ML) method using\nnon negative matrix factorization (NMF) from energy dispersive X-ray\nspectroscopy (EDX) spectrum image maps measured in a scanning electron\nmicroscope (SEM). The BSS method blindly decomposes the collected EDX spectrum\nimage into three source components, which correspond directly to the X-ray\nsignals coming from the supported metal nanostructures, bulk semiconductor\nsignal and carbon background. The recovered quantitative composition is\nvalidated by detailed Monte Carlo simulations and is confirmed by separate\ncross-sectional TEM EDX measurements of the nanostructures. This shows that SEM\nEDX measurements together with machine learning blind source separation\nprocessing could be successfully used for the nanostructures quantitative\nchemical composition determination.\n",
"title": "Retrieving the quantitative chemical information at nanoscale from SEM EDX measurements by Machine Learning"
}
| null | null |
[
"Physics"
] | null | true | null |
13616
| null |
Validated
| null | null |
null |
{
"abstract": " We tackle the problem of constructive preference elicitation, that is the\nproblem of learning user preferences over very large decision problems,\ninvolving a combinatorial space of possible outcomes. In this setting, the\nsuggested configuration is synthesized on-the-fly by solving a constrained\noptimization problem, while the preferences are learned itera tively by\ninteracting with the user. Previous work has shown that Coactive Learning is a\nsuitable method for learning user preferences in constructive scenarios. In\nCoactive Learning the user provides feedback to the algorithm in the form of an\nimprovement to a suggested configuration. When the problem involves many\ndecision variables and constraints, this type of interaction poses a\nsignificant cognitive burden on the user. We propose a decomposition technique\nfor large preference-based decision problems relying exclusively on inference\nand feedback over partial configurations. This has the clear advantage of\ndrastically reducing the user cognitive load. Additionally, part-wise inference\ncan be (up to exponentially) less computationally demanding than inference over\nfull configurations. We discuss the theoretical implications of working with\nparts and present promising empirical results on one synthetic and two\nrealistic constructive problems.\n",
"title": "Decomposition Strategies for Constructive Preference Elicitation"
}
| null | null | null | null | true | null |
13617
| null |
Default
| null | null |
null |
{
"abstract": " Recently, two reports have demonstrated the amazing possibility to probe\nvibrational excitations from nanoparticles with a spatial resolution much\nsmaller than the corresponding free-space phonon wavelength using electron\nenergy loss spectroscopy (EELS). While Lagos et al. evidenced a strong spatial\nand spectral modulation of the EELS signal over a nanoparticle, Krivanek et al.\ndid not. Here, we show that discrepancies among different EELS experiments as\nwell as their relation to optical near- and far-field optical experiments can\nbe understood by introducing the concept of confined bright and dark\nFuchs-Kliewer modes, whose density of states is probed by EELS. Such a concise\nformalism is the vibrational counterpart of the broadly used formalism for\nlocalized surface plasmons; it makes it straightforward to predict or interpret\nphenomena already known for localized surface plasmons such as\nenvironment-related energy shifts or the possibility of 3D mapping of the\nrelated surface charge densities.\n",
"title": "Vibrational surface EELS probes confined Fuchs-Kliewer modes"
}
| null | null | null | null | true | null |
13618
| null |
Default
| null | null |
null |
{
"abstract": " We examine the relation between gas-phase oxygen abundance and stellar\nmass---the MZ relation---as a function of the large scale galaxy environment\nparameterized by the local density. The dependence of the MZ relation on the\nenvironment is small. The metallicity where the MZ relation saturates and the\nslope of the MZ relation are both independent of the local density. The impact\nof the large scale environment is completely parameterized by the\nanti-correlation between local density and the turnover stellar mass where the\nMZ relation begins to saturate. Analytical modeling suggests that the\nanti-correlation between the local density and turnover stellar mass is a\nconsequence of a variation in the gas content of star-forming galaxies. Across\n$\\sim1$ order of magnitude in local density, the gas content at a fixed stellar\nmass varies by $\\sim5\\%$. Variation of the specific star formation rate with\nenvironment is consistent with this interpretation. At a fixed stellar mass,\ngalaxies in low density environments have lower metallicities because they are\nslightly more gas-rich than galaxies in high density environments. Modeling the\nshape of the mass-metallicity relation thus provides an indirect means to probe\nsubtle variations in the gas content of star-forming galaxies.\n",
"title": "The Dependence of the Mass-Metallicity Relation on Large Scale Environment"
}
| null | null |
[
"Physics"
] | null | true | null |
13619
| null |
Validated
| null | null |
null |
{
"abstract": " We prove Riemann hypothesis, Generalized Riemann hypothesis, and Ramanujan\n$\\tau$-Dirichlet series hypothesis. Method is to show the convexity of function\nwhich has zeros critical strip the same as zeta function.\n",
"title": "Proof of Riemann hypothesis, Generalized Riemann hypothesis and Ramanujan $τ$-Dirichlet series hypothesis"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13620
| null |
Validated
| null | null |
null |
{
"abstract": " We develop a second order primal-dual method for optimization problems in\nwhich the objective function is given by the sum of a strongly convex twice\ndifferentiable term and a possibly nondifferentiable convex regularizer. After\nintroducing an auxiliary variable, we utilize the proximal operator of the\nnonsmooth regularizer to transform the associated augmented Lagrangian into a\nfunction that is once, but not twice, continuously differentiable. The saddle\npoint of this function corresponds to the solution of the original optimization\nproblem. We employ a generalization of the Hessian to define second order\nupdates on this function and prove global exponential stability of the\ncorresponding differential inclusion. Furthermore, we develop a globally\nconvergent customized algorithm that utilizes the primal-dual augmented\nLagrangian as a merit function. We show that the search direction can be\ncomputed efficiently and prove quadratic/superlinear asymptotic convergence. We\nuse the $\\ell_1$-regularized least squares problem and the problem of designing\na distributed controller for a spatially-invariant system to demonstrate the\nmerits and the effectiveness of our method.\n",
"title": "A second order primal-dual method for nonsmooth convex composite optimization"
}
| null | null | null | null | true | null |
13621
| null |
Default
| null | null |
null |
{
"abstract": " Electronic medical records contain multi-format electronic medical data that\nconsist of an abundance of medical knowledge. Facing with patient's symptoms,\nexperienced caregivers make right medical decisions based on their professional\nknowledge that accurately grasps relationships between symptoms, diagnosis and\ncorresponding treatments. In this paper, we aim to capture these relationships\nby constructing a large and high-quality heterogenous graph linking patients,\ndiseases, and drugs (PDD) in EMRs. Specifically, we propose a novel framework\nto extract important medical entities from MIMIC-III (Medical Information Mart\nfor Intensive Care III) and automatically link them with the existing\nbiomedical knowledge graphs, including ICD-9 ontology and DrugBank. The PDD\ngraph presented in this paper is accessible on the Web via the SPARQL endpoint,\nand provides a pathway for medical discovery and applications, such as\neffective treatment recommendations.\n",
"title": "PDD Graph: Bridging Electronic Medical Records and Biomedical Knowledge Graphs via Entity Linking"
}
| null | null | null | null | true | null |
13622
| null |
Default
| null | null |
null |
{
"abstract": " We give an new arithmetic algorithm to compute the generalized Discrete\nFourier Transform (DFT) over finite groups $G$. The new algorithm uses\n$O(|G|^{\\omega/2 + o(1)})$ operations to compute the generalized DFT over\nfinite groups of Lie type, including the linear, orthogonal, and symplectic\nfamilies and their variants, as well as all finite simple groups of Lie type.\nHere $\\omega$ is the exponent of matrix multiplication, so the exponent\n$\\omega/2$ is optimal if $\\omega = 2$. Previously, \"exponent one\" algorithms\nwere known for supersolvable groups and the symmetric and alternating groups.\nNo exponent one algorithms were known (even under the assumption $\\omega = 2$)\nfor families of linear groups of fixed dimension, and indeed the previous\nbest-known algorithm for $SL_2(F_q)$ had exponent $4/3$ despite being the focus\nof significant effort. We unconditionally achieve exponent at most $1.19$ for\nthis group, and exponent one if $\\omega = 2$. Our algorithm also yields an\nimproved exponent for computing the generalized DFT over general finite groups\n$G$, which beats the longstanding previous best upper bound, for any $\\omega$.\nIn particular, assuming $\\omega = 2$, we achieve exponent $\\sqrt{2}$, while the\nprevious best was $3/2$.\n",
"title": "A new algorithm for fast generalized DFTs"
}
| null | null | null | null | true | null |
13623
| null |
Default
| null | null |
null |
{
"abstract": " We study a superconductor that is coupled to a superfluid via density and\nderivative couplings. Starting from a Lagrangian for two complex scalar fields,\nwe derive a temperature-dependent Ginzburg-Landau potential, which is then used\nto compute the phase diagram at nonzero temperature and external magnetic\nfield. This includes the calculation of the critical magnetic fields for the\ntransition to an array of magnetic flux tubes, based on an approximation for\nthe interaction between the flux tubes. We find that the transition region\nbetween type-I and type-II superconductivity changes qualitatively due to the\npresence of the superfluid: the phase transitions at the upper and lower\ncritical fields in the type-II regime become first order, opening the\npossibility of clustered flux tube phases. These flux tube clusters may be\nrealized in the core of neutron stars, where superconducting protons are\nexpected to be coupled to superfluid neutrons.\n",
"title": "Critical magnetic fields in a superconductor coupled to a superfluid"
}
| null | null |
[
"Physics"
] | null | true | null |
13624
| null |
Validated
| null | null |
null |
{
"abstract": " We introduce multi-colour partition algebras $P_{n,m}(\\delta_0, ...,\n\\delta_{m-1})$, which are generalization of both bubble algebras and partition\nalgebras, then define the bubble algebra $T_{n,m}(\\delta_0, ..., \\delta_{m-1})$\nas a sub-algebra of the algebra $P_{n,m}(\\delta_0, ..., \\delta_{m-1})$. We\npresent general techniques to determine the structure of the bubble algebra\nover the complex field in the non-semisimple case.\n",
"title": "The bubble algebras at roots of unity"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13625
| null |
Validated
| null | null |
null |
{
"abstract": " Materials are central to our way of life and future. Energy and materials as\nresources are connected and the obvious connections between them are the energy\ncost of materials and the materials cost of energy. For both of these\nresilience of the materials is critical; thus a major goal of future chemistry\nshould be to find materials for energy that can last longer, i.e., design\nprinciples for self-repair in these.\n",
"title": "Self-Repairing Energy Materials: Sine Qua Non for a Sustainable Future"
}
| null | null | null | null | true | null |
13626
| null |
Default
| null | null |
null |
{
"abstract": " Lumped-element kinetic inductance detectors (LEKIDs) are an attractive\ntechnology for millimeter-wave observations that require large arrays of\nextremely low-noise detectors. We designed, fabricated and characterized\n64-element (128 LEKID) arrays of horn-coupled, dual-polarization LEKIDs\noptimized for ground-based CMB polarimetry. Our devices are sensitive to two\northogonal polarizations in a single spectral band centered on 150 GHz with\n$\\Delta\\nu/\\nu=0.2$. The $65\\times 65$ mm square arrays are designed to be\ntiled into the focal plane of an optical system. We demonstrate the viability\nof these dual-polarization LEKIDs with laboratory measurements. The LEKID\nmodules are tested with an FPGA-based readout system in a sub-kelvin cryostat\nthat uses a two-stage adiabatic demagnetization refrigerator. The devices are\ncharacterized using a blackbody and a millimeter-wave source. The polarization\nproperties are measured with a cryogenic stepped half-wave plate. We measure\nthe resonator parameters and the detector sensitivity, noise spectrum, dynamic\nrange, and polarization response. The resonators have internal quality factors\napproaching $1\\times 10^{6}$. The detectors have uniform response between\northogonal polarizations and a large dynamic range. The detectors are\nphoton-noise limited above 1 pW of absorbed power. The noise-equivalent\ntemperatures under a 3.4 K blackbody load are $<100~\\mu\\mathrm{K\\sqrt{s}}$. The\npolarization fractions of detectors sensitive to orthogonal polarizations are\n>80%. The entire array is multiplexed on a single readout line, demonstrating a\nmultiplexing factor of 128. The array and readout meet the requirements for 4\narrays to be read out simultaneously for a multiplexing factor of 512. This\nlaboratory study demonstrates the first dual-polarization LEKID array optimized\nfor CMB polarimetry and shows the readiness of the detectors for on-sky\nobservations.\n",
"title": "Design and performance of dual-polarization lumped-element kinetic inductance detectors for millimeter-wave polarimetry"
}
| null | null | null | null | true | null |
13627
| null |
Default
| null | null |
null |
{
"abstract": " Knot Floer homology is an invariant for knots discovered by the authors and,\nindependently, Jacob Rasmussen. The discovery of this invariant grew naturally\nout of studying how a certain three-manifold invariant, Heegaard Floer\nhomology, changes as the three-manifold undergoes Dehn surgery along a knot.\nSince its original definition, thanks to the contributions of many researchers,\nknot Floer homology has emerged as a useful tool for studying knots in its own\nright. We give here a few selected highlights of this theory, and then move on\nto some new algebraic developments in the computation of knot Floer homology.\n",
"title": "An overview of knot Floer homology"
}
| null | null | null | null | true | null |
13628
| null |
Default
| null | null |
null |
{
"abstract": " A new detailed mathematical model for dynamics of immune response to\nhepatitis B is proposed, which takes into account contributions from innate and\nadaptive immune responses, as well as cytokines. Stability analysis of\ndifferent steady states is performed to identify parameter regions where the\nmodel exhibits clearance of infection, maintenance of a chronic infection, or\nperiodic oscillations. Effects of nucleoside analogues and interferon\ntreatments are analysed, and the critical drug efficiency is determined.\n",
"title": "Mathematical model of immune response to hepatitis B"
}
| null | null | null | null | true | null |
13629
| null |
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| null | null |
null |
{
"abstract": " Experiments handling Rydberg atoms near surfaces must necessarily deal with\nthe high sensitivity of Rydberg atoms to (stray) electric fields that typically\nemanate from adsorbates on the surface. We demonstrate a method to modify and\nreduce the stray electric field by changing the adsorbates distribution. We use\none of the Rydberg excitation lasers to locally affect the adsorbed dipole\ndistribution. By adjusting the averaged exposure time we change the strength\n(with the minimal value less than $0.2\\,\\textrm{V/cm}$ at $78\\,\\mu\\textrm{m}$\nfrom the chip) and even the sign of the perpendicular field component. This\ntechnique is a useful tool for experiments handling Ryberg atoms near surfaces,\nincluding atom chips.\n",
"title": "Controlling Stray Electric Fields on an Atom Chip for Rydberg Experiments"
}
| null | null | null | null | true | null |
13630
| null |
Default
| null | null |
null |
{
"abstract": " Quasars at high redshift provide direct information on the mass growth of\nsupermassive black holes and, in turn, yield important clues about how the\nUniverse evolved since the first (Pop III) stars started forming. Yet even\nbasic questions regarding the seeds of these objects and their growth mechanism\nremain unanswered. The anticipated launch of eROSITA and ATHENA is expected to\nfacilitate observations of high-redshift quasars needed to resolve these\nissues. In this paper, we compare accretion-based supermassive black hole\ngrowth in the concordance LCDM model with that in the alternative\nFriedmann-Robertson Walker cosmology known as the R_h=ct universe. Previous\nwork has shown that the timeline predicted by the latter can account for the\norigin and growth of the > 10^9 M_sol highest redshift quasars better than that\nof the standard model. Here, we significantly advance this comparison by\ndetermining the soft X-ray flux that would be observed for Eddington-limited\naccretion growth as a function of redshift in both cosmologies. Our results\nindicate that a clear difference emerges between the two in terms of the number\nof detectable quasars at redshift z > 6, raising the expectation that the next\ndecade will provide the observational data needed to discriminate between these\ntwo models based on the number of detected high-redshift quasar progenitors.\nFor example, while the upcoming ATHENA mission is expected to detect ~0.16\n(i.e., essentially zero) quasars at z ~ 7 in R_h=ct, it should detect ~160 in\nLCDM---a quantitatively compelling difference.\n",
"title": "Unseen Progenitors of Luminous High-z Quasars in the R_h=ct Universe"
}
| null | null |
[
"Physics"
] | null | true | null |
13631
| null |
Validated
| null | null |
null |
{
"abstract": " Acid solutions exhibit a variety of complex structural and dynamical features\narising from the presence of multiple interacting reactive proton defects and\ncounterions. However, disentangling the transient structural motifs of proton\ndefects in the water hydrogen bond network and the mechanisms for their\ninterconversion remains a formidable challenge. Here, we use simulations\ntreating the quantum nature of both the electrons and nuclei to show how the\nexperimentally observed spectroscopic features and relaxation timescales can be\nelucidated using a physically transparent coordinate that encodes the overall\nasymmetry of the solvation environment of the proton defect. We demonstrate\nthat this coordinate can be used both to discriminate the extremities of the\nfeatures observed in the linear vibrational spectrum and to explain the\nmolecular motions that give rise to the interconversion timescales observed in\nrecent nonlinear experiments. This analysis provides a unified condensed-phase\npicture of proton structure and dynamics that, at its extrema, encompasses\nproton sharing and spectroscopic features resembling the limiting Eigen\n[H$_{3}$O(H$_{2}$O)$_{3}$]$^{+}$ and Zundel [H(H$_{2}$O)$_{2}$]$^{+}$ gas-phase\nstructures, while also describing the rich variety of interconverting\nenvironments in the liquid phase.\n",
"title": "Decoding the spectroscopic features and timescales of aqueous proton defects"
}
| null | null | null | null | true | null |
13632
| null |
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| null | null |
null |
{
"abstract": " Generating music has a few notable differences from generating images and\nvideos. First, music is an art of time, necessitating a temporal model. Second,\nmusic is usually composed of multiple instruments/tracks with their own\ntemporal dynamics, but collectively they unfold over time interdependently.\nLastly, musical notes are often grouped into chords, arpeggios or melodies in\npolyphonic music, and thereby introducing a chronological ordering of notes is\nnot naturally suitable. In this paper, we propose three models for symbolic\nmulti-track music generation under the framework of generative adversarial\nnetworks (GANs). The three models, which differ in the underlying assumptions\nand accordingly the network architectures, are referred to as the jamming\nmodel, the composer model and the hybrid model. We trained the proposed models\non a dataset of over one hundred thousand bars of rock music and applied them\nto generate piano-rolls of five tracks: bass, drums, guitar, piano and strings.\nA few intra-track and inter-track objective metrics are also proposed to\nevaluate the generative results, in addition to a subjective user study. We\nshow that our models can generate coherent music of four bars right from\nscratch (i.e. without human inputs). We also extend our models to human-AI\ncooperative music generation: given a specific track composed by human, we can\ngenerate four additional tracks to accompany it. All code, the dataset and the\nrendered audio samples are available at this https URL .\n",
"title": "MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment"
}
| null | null | null | null | true | null |
13633
| null |
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| null | null |
null |
{
"abstract": " We study synaptically coupled neuronal networks to identify the role of\ncoupling delays in network's synchronized behaviors. We consider a network of\nexcitable, relaxation oscillator neurons where two distinct populations, one\nexcitatory and one inhibitory, are coupled and interact with each other. The\nexcitatory population is uncoupled, while the inhibitory population is tightly\ncoupled. A geometric singular perturbation analysis yields existence and\nstability conditions for synchronization states under different firing patterns\nbetween the two populations, along with formulas for the periods of such\nsynchronous solutions. Our results demonstrate that the presence of coupling\ndelays in the network promotes synchronization. Numerical simulations are\nconducted to supplement and validate analytical results. We show the results\ncarry over to a model for spindle sleep rhythms in thalamocortical networks,\none of the biological systems which motivated our study. The analysis helps to\nexplain how coupling delays in either excitatory or inhibitory synapses\ncontribute to producing synchronized rhythms.\n",
"title": "Geometric Analysis of Synchronization in Neuronal Networks with Global Inhibition and Coupling Delays"
}
| null | null | null | null | true | null |
13634
| null |
Default
| null | null |
null |
{
"abstract": " Motion planning for autonomous vehicles requires spatio-temporal motion plans\n(i.e. state trajectories) to account for dynamic obstacles. This requires a\ntrajectory tracking control process which faithfully tracks planned\ntrajectories. In this paper, a control scheme is presented which first\noptimizes a planned trajectory and then tracks the optimized trajectory using a\nfeedback-feedforward controller. The feedforward element is calculated in a\nmodel predictive manner with a cost function focusing on driving performance.\nStability of the error dynamic is then guaranteed by the design of the\nfeedback-feedforward controller. The tracking performance of the control system\nis tested in a realistic simulated scenario where the control system must track\nan evasive lateral maneuver. The proposed controller performs well in\nsimulation and can be easily adapted to different dynamic vehicle models. The\nuniqueness of the solution to the control synthesis eliminates any\nnondeterminism that could arise with switching between numerical solvers for\nthe underlying mathematical program.\n",
"title": "Model predictive trajectory optimization and tracking for on-road autonomous vehicles"
}
| null | null | null | null | true | null |
13635
| null |
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| null | null |
null |
{
"abstract": " We present a tool that primarily supports the ability to check bounded\nproperties starting from a sequence of states in a run. The target design is\ncompiled into an AIGNET which is then selectively and iteratively translated\ninto an incremental SAT instance in which clauses are added for new terms and\nsimplified by the assignment of existing literals. Additional applications of\nthe tool can be derived by the user providing alternative attachments of\nconstrained functions which guide the iterations and SAT checks performed. Some\nVerilog RTL examples are included for reference.\n",
"title": "A Toolbox For Property Checking From Simulation Using Incremental SAT (Extended Abstract)"
}
| null | null | null | null | true | null |
13636
| null |
Default
| null | null |
null |
{
"abstract": " This work leverages recent advances in probabilistic machine learning to\ndiscover conservation laws expressed by parametric linear equations. Such\nequations involve, but are not limited to, ordinary and partial differential,\nintegro-differential, and fractional order operators. Here, Gaussian process\npriors are modified according to the particular form of such operators and are\nemployed to infer parameters of the linear equations from scarce and possibly\nnoisy observations. Such observations may come from experiments or \"black-box\"\ncomputer simulations.\n",
"title": "Machine Learning of Linear Differential Equations using Gaussian Processes"
}
| null | null | null | null | true | null |
13637
| null |
Default
| null | null |
null |
{
"abstract": " This paper introduces the YouTube-8M Video Understanding Challenge hosted as\na Kaggle competition and also describes my approach to experimenting with\nvarious models. For each of my experiments, I provide the score result as well\nas possible improvements to be made. Towards the end of the paper, I discuss\nthe various ensemble learning techniques that I applied on the dataset which\nsignificantly boosted my overall competition score. At last, I discuss the\nexciting future of video understanding research and also the many applications\nthat such research could significantly improve.\n",
"title": "YouTube-8M Video Understanding Challenge Approach and Applications"
}
| null | null | null | null | true | null |
13638
| null |
Default
| null | null |
null |
{
"abstract": " Sepsis is a condition caused by the body's overwhelming and life-threatening\nresponse to infection, which can lead to tissue damage, organ failure, and\nfinally death. Common signs and symptoms include fever, increased heart rate,\nincreased breathing rate, and confusion. Sepsis is difficult to predict,\ndiagnose, and treat. Patients who develop sepsis have an increased risk of\ncomplications and death and face higher health care costs and longer\nhospitalization. Today, sepsis is one of the leading causes of mortality among\npopulations in intensive care units (ICUs). In this paper, we look at the\nproblem of early detection of sepsis by using temporal data mining. We focus on\nthe use of knowledge-based temporal abstraction to create meaningful\ninterval-based abstractions, and on time-interval mining to discover frequent\ninterval-based patterns. We used 2,560 cases derived from the MIMIC-III\ndatabase. We found that the distribution of the temporal patterns whose\nfrequency is above 10% discovered in the records of septic patients during the\nlast 6 and 12 hours before onset of sepsis is significantly different from that\ndistribution within a similar period, during an equivalent time window during\nhospitalization, in the records of non-septic patients. This discovery is\nencouraging for the purpose of performing an early diagnosis of sepsis using\nthe discovered patterns as constructed features.\n",
"title": "Temporal Pattern Discovery for Accurate Sepsis Diagnosis in ICU Patients"
}
| null | null | null | null | true | null |
13639
| null |
Default
| null | null |
null |
{
"abstract": " This contribution is devoted to cover some technical aspects related to the\nuse of the recently proposed energy probability distribution zeros in the study\nof phase transitions. This method is based on the partial knowledge of the\npartition function zeros and has been shown to be extremely efficient to\nprecisely locate phase transition temperatures. It is based on an iterative\nmethod in such a way that the transition temperature can be approached at will.\nThe iterative method will be detailed and some convergence issues that has been\nobserved in its application to the 2D Ising model and to an artificial spin ice\nmodel will be shown, together with ways to circumvent them.\n",
"title": "On the use of the energy probability distribution zeros in the study of phase transitions"
}
| null | null | null | null | true | null |
13640
| null |
Default
| null | null |
null |
{
"abstract": " We present a visibility based estimator namely, the Tapered Gridded Estimator\n(TGE) to estimate the power spectrum of the diffuse sky signal. The TGE has\nthree novel features. First, the estimator uses gridded visibilities to\nestimate the power spectrum which is computationally much faster than\nindividually correlating the visibilities. Second, a positive noise bias is\nremoved by subtracting the auto-correlation of the visibilities which is\nresponsible for the noise bias. Third, the estimator allows us to taper the\nfield of view so as to suppress the contribution from the sources in the outer\nregions and the sidelobes of the telescope's primary beam. We first consider\nthe two dimensional (2D) TGE to estimate the angular power spectrum $C_{\\ell}$.\nWe have also extended the TGE to estimate the three dimensional (3D) power\nspectrum $P({\\bf k})$ of the cosmological 21-cm signal. Analytic formulas are\npresented for predicting the variance of the binned power spectrum. Both the\nestimators and their variance predictions are validated using simulations of\n$150 \\, {\\rm MHz}$ GMRT observations. We have applied the 2D TGE to estimate\n$C_{\\ell}$ using visibility data for two of the fields observed by TIFR GMRT\nSky Survey (TGSS). We find that the sky signal, after subtracting the point\nsources, is likely dominated by the diffuse Galactic synchrotron radiation\nacross the angular multipole range $240 \\le \\ell \\lesssim 500$.\n",
"title": "Visibility-based Power Spectrum Estimation for Low-Frequency Radio Interferometric Observations"
}
| null | null | null | null | true | null |
13641
| null |
Default
| null | null |
null |
{
"abstract": " Software has long been established as an essential aspect of the scientific\nprocess in mathematics and other disciplines. However, reliably referencing\nsoftware in scientific publications is still challenging for various reasons. A\ncrucial factor is that software dynamics with temporal versions or states are\ndifficult to capture over time. We propose to archive and reference surrogates\ninstead, which can be found on the Web and reflect the actual software to a\nremarkable extent. Our study shows that about a half of the webpages of\nsoftware are already archived with almost all of them including some kind of\ndocumentation.\n",
"title": "Archiving Software Surrogates on the Web for Future Reference"
}
| null | null | null | null | true | null |
13642
| null |
Default
| null | null |
null |
{
"abstract": " We prove new exact formulas for the generalized sum-of-divisors functions.\nThe formulas for $\\sigma_{\\alpha}(x)$ when $\\alpha \\in \\mathbb{C}$ is fixed and\n$x \\geq 1$ involves a finite sum over all of the prime factors $n \\leq x$ and\nterms involving the $r$-order harmonic number sequences. The generalized\nharmonic number sequences correspond to the partial sums of the Riemann zeta\nfunction when $r > 1$ and are related to the generalized Bernoulli numbers when\n$r \\leq 0$ is integer-valued. A key part of our expansions of the Lambert\nseries generating functions for the generalized divisor functions is formed by\ntaking logarithmic derivatives of the cyclotomic polynomials, $\\Phi_n(q)$,\nwhich completely factorize the Lambert series terms $(1-q^n)^{-1}$ into\nirreducible polynomials in $q$. We also consider applications of our new\nresults to asymptotic approximations for sums over these divisor functions and\nto the forms of perfect numbers defined by the special case of the divisor\nfunction, $\\sigma(n)$, when $\\alpha := 1$.\nKeywords: divisor function; sum-of-divisors function; Lambert series; perfect\nnumber.\nMSC (2010): 30B50; 11N64; 11B83\n",
"title": "Exact Formulas for the Generalized Sum-of-Divisors Functions"
}
| null | null | null | null | true | null |
13643
| null |
Default
| null | null |
null |
{
"abstract": " This paper provides some explicit formulas related to addition theorems for\nelliptic integrals $\\int_0^x dt/R(t)$, where $R(t)$ is the square root from a\npolynomial of degree 4. These integrals are related to complex elliptic genera\nand are motivated by Euler's addition theorem for elliptic integrals of the\nfirst kind.\n",
"title": "On addition theorems related to elliptic integrals"
}
| null | null | null | null | true | null |
13644
| null |
Default
| null | null |
null |
{
"abstract": " Witnesses of medieval literary texts, preserved in manuscript, are layered\nobjects , being almost exclusively copies of copies. This results in multiple\nand hard to distinguish linguistic strata -- the author's scripta interacting\nwith the scriptae of the various scribes -- in a context where literary written\nlanguage is already a dialectal hybrid. Moreover, no single linguistic\nphenomenon allows to distinguish between different scriptae, and only the\ncombination of multiple characteristics is likely to be significant [9] -- but\nwhich ones? The most common approach is to search for these features in a set\nof previously selected texts, that are supposed to be representative of a given\nscripta. This can induce a circularity, in which texts are used to select\nfeatures that in turn characterise them as belonging to a linguistic area. To\ncounter this issue, this paper offers an unsupervised and corpus-based\napproach, in which clustering methods are applied to an Old French corpus to\nidentify main divisions and groups. Ultimately, scriptometric profiles are\nbuilt for each of them.\n",
"title": "Manuscripts in Time and Space: Experiments in Scriptometrics on an Old French Corpus"
}
| null | null | null | null | true | null |
13645
| null |
Default
| null | null |
null |
{
"abstract": " There have been sustained interest in bifacial solar cell technology since\n1980s, with prospects of 30-50% increase in the output power from a stand-alone\nsingle panel. Moreover, a vertical bifacial panel reduces dust accumulation and\nprovides two output peaks during the day, with the second peak aligned to the\npeak electricity demand. Recent commercialization and anticipated growth of\nbifacial panel market have encouraged a closer scrutiny of the integrated\npower-output and economic viability of bifacial solar farms, where mutual\nshading will erode some of the anticipated energy gain associated with an\nisolated, single panel. Towards that goal, in this paper we focus on\ngeography-specific optimizations of ground mounted vertical bifacial solar\nfarms for the entire world. For local irradiance, we combine the measured\nmeteorological data with the clear-sky model. In addition, we consider the\ndetailed effects of direct, diffuse, and albedo light. We assume the panel is\nconfigured into sub-strings with bypass-diodes. Based on calculated light\ncollection and panel output, we analyze the optimum farm design for maximum\nyearly output at any given location in the world. Our results predict that,\nregardless of the geographical location, a vertical bifacial farm will yield\n10-20% more energy than a traditional monofacial farm for a practical\nrow-spacing of 2m (1.2m high panels). With the prospect of additional 5-20%\nenergy gain from reduced soiling and tilt optimization, bifacial solar farm do\noffer a viable technology option for large-scale solar energy generation.\n",
"title": "Vertical Bifacial Solar Farms: Physics, Design, and Global Optimization"
}
| null | null | null | null | true | null |
13646
| null |
Default
| null | null |
null |
{
"abstract": " In the era of big data, reducing data dimensionality is critical in many\nareas of science. Widely used Principal Component Analysis (PCA) addresses this\nproblem by computing a low dimensional data embedding that maximally explain\nvariance of the data. However, PCA has two major weaknesses. Firstly, it only\nconsiders linear correlations among variables (features), and secondly it is\nnot suitable for categorical data. We resolve these issues by proposing\nMaximally Correlated Principal Component Analysis (MCPCA). MCPCA computes\ntransformations of variables whose covariance matrix has the largest Ky Fan\nnorm. Variable transformations are unknown, can be nonlinear and are computed\nin an optimization. MCPCA can also be viewed as a multivariate extension of\nMaximal Correlation. For jointly Gaussian variables we show that the covariance\nmatrix corresponding to the identity (or the negative of the identity)\ntransformations majorizes covariance matrices of non-identity functions. Using\nthis result we characterize global MCPCA optimizers for nonlinear functions of\njointly Gaussian variables for every rank constraint. For categorical variables\nwe characterize global MCPCA optimizers for the rank one constraint based on\nthe leading eigenvector of a matrix computed using pairwise joint\ndistributions. For a general rank constraint we propose a block coordinate\ndescend algorithm and show its convergence to stationary points of the MCPCA\noptimization. We compare MCPCA with PCA and other state-of-the-art\ndimensionality reduction methods including Isomap, LLE, multilayer autoencoders\n(neural networks), kernel PCA, probabilistic PCA and diffusion maps on several\nsynthetic and real datasets. We show that MCPCA consistently provides improved\nperformance compared to other methods.\n",
"title": "Maximally Correlated Principal Component Analysis"
}
| null | null | null | null | true | null |
13647
| null |
Default
| null | null |
null |
{
"abstract": " It is well known that neural networks with rectified linear units (ReLU)\nactivation functions are positively scale-invariant. Conventional algorithms\nlike stochastic gradient descent optimize the neural networks in the vector\nspace of weights, which is, however, not positively scale-invariant. This\nmismatch may lead to problems during the optimization process. Then, a natural\nquestion is: \\emph{can we construct a new vector space that is positively\nscale-invariant and sufficient to represent ReLU neural networks so as to\nbetter facilitate the optimization process }? In this paper, we provide our\npositive answer to this question. First, we conduct a formal study on the\npositive scaling operators which forms a transformation group, denoted as\n$\\mathcal{G}$. We show that the value of a path (i.e. the product of the\nweights along the path) in the neural network is invariant to positive scaling\nand prove that the value vector of all the paths is sufficient to represent the\nneural networks under mild conditions. Second, we show that one can identify\nsome basis paths out of all the paths and prove that the linear span of their\nvalue vectors (denoted as $\\mathcal{G}$-space) is an invariant space with lower\ndimension under the positive scaling group. Finally, we design stochastic\ngradient descent algorithm in $\\mathcal{G}$-space (abbreviated as\n$\\mathcal{G}$-SGD) to optimize the value vector of the basis paths of neural\nnetworks with little extra cost by leveraging back-propagation. Our experiments\nshow that $\\mathcal{G}$-SGD significantly outperforms the conventional SGD\nalgorithm in optimizing ReLU networks on benchmark datasets.\n",
"title": "$\\mathcal{G}$-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space"
}
| null | null | null | null | true | null |
13648
| null |
Default
| null | null |
null |
{
"abstract": " The aim of this paper is to introduce the notion of fantastic deductive\nsystems on generalizations of fuzzy structures, and to emphasize their role in\nthe probability theory on these algebras. We give a characterization of\ncommutative pseudo-BE algebras and we generalize an axiom system consisting of\nfour identities to the case of commutative pseudo-BE algebras. We define the\nfantastic deductive systems of pseudo-BE algebras and we investigate their\nproperties. It is proved that, if a pseudo-BE(A) algebra $A$ is commutative,\nthen all deductive systems of $A$ are fantastic. Moreover, we generalize the\nnotions of measures, state-measures and measure-morphisms to the case of\npseudo-BE algebras and we also prove that there is a one-to-one correspondence\nbetween the set of all Bosbach states on a bounded pseudo-BE algebra and the\nset of its state-measures. The notions of internal states and state-morphism\noperators on pseudo-BCK algebras are extended to the case of pseudo-BE algebras\nand we also prove that any type II state operator on a pseudo-BE algebra is a\nstate-morphism operator on it. The notions of pseudo-valuation and commutative\npseudo-valuation on pseudo-BE algebras are defined and investigated. For the\ncase of commutative pseudo-BE algebras we prove that the two kind of\npseudo-valuations coincide. Characterizations of pseudo-valuations and\ncommutative pseudo-valuations are given. We show that the kernel of a Bosbach\nstate (state-morphism, measure, type II state operator, pseudo-valuation) is a\nfantastic deductive system.\n",
"title": "Fantastic deductive systems in probability theory on generalizations of fuzzy structures"
}
| null | null | null | null | true | null |
13649
| null |
Default
| null | null |
null |
{
"abstract": " In coming years residential consumers will face real-time electricity tariffs\nwith energy prices varying day to day, and effective energy saving will require\nautomation - a recommender system, which learns consumer's preferences from her\nactions. A consumer chooses a scenario of home appliance use to balance her\ncomfort level and the energy bill. We propose a Bayesian learning algorithm to\nestimate the comfort level function from the history of appliance use. In\nnumeric experiments with datasets generated from a simulation model of a\nconsumer interacting with small home appliances the algorithm outperforms\npopular regression analysis tools. Our approach can be extended to control an\nair heating and conditioning system, which is responsible for up to half of a\nhousehold's energy bill.\n",
"title": "Bayesian Learning of Consumer Preferences for Residential Demand Response"
}
| null | null | null | null | true | null |
13650
| null |
Default
| null | null |
null |
{
"abstract": " Recent work on follow the perturbed leader (FTPL) algorithms for the\nadversarial multi-armed bandit problem has highlighted the role of the hazard\nrate of the distribution generating the perturbations. Assuming that the hazard\nrate is bounded, it is possible to provide regret analyses for a variety of\nFTPL algorithms for the multi-armed bandit problem. This paper pushes the\ninquiry into regret bounds for FTPL algorithms beyond the bounded hazard rate\ncondition. There are good reasons to do so: natural distributions such as the\nuniform and Gaussian violate the condition. We give regret bounds for both\nbounded support and unbounded support distributions without assuming the hazard\nrate condition. We also disprove a conjecture that the Gaussian distribution\ncannot lead to a low-regret algorithm. In fact, it turns out that it leads to\nnear optimal regret, up to logarithmic factors. A key ingredient in our\napproach is the introduction of a new notion called the generalized hazard\nrate.\n",
"title": "Beyond the Hazard Rate: More Perturbation Algorithms for Adversarial Multi-armed Bandits"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
13651
| null |
Validated
| null | null |
null |
{
"abstract": " The ammonium halides present an interesting system for study in view of their\npolymorphism and the possible internal rotation of the ammonium ion. The static\nproperties of the mixed ionic crystal NH$_4$Cl$_{1-x}$Br$_x$ have been recently\ninvestigated, using three-body potential model (TDPM) by the application of\nVegard's law. Here, by using a simple theoretical model, we estimate the bulk\nmodulus of their ternary alloys NH$_4$Cl$_{1-x}$Br$_x$, in terms of the bulk\nmodulus of the end members alone. The calculated values are comparable to those\ndeduced from the three-body potential model (TDPM) by the application of\nVegard's law.\n",
"title": "Calculation of the bulk modulus of mixed ionic crystal NH_4Cl_{1-x}Br_x"
}
| null | null | null | null | true | null |
13652
| null |
Default
| null | null |
null |
{
"abstract": " The linear fractional map $ f(z) = \\frac{az+ b}{cz + d} $ on the Riemann\nsphere with complex coefficients $ ad-bc \\neq 0 $ is called Möbius map. If $\nf $ satisfies $ ad-bc=1 $ and $ -2<a+d<2 $, then $ f $ is called\n$\\textit{elliptic}$ Möbius map. Let $ \\{ b_n \\}_{n \\in \\mathbb{N}_0} $ be the\nsolution of the elliptic Möbius difference equation $ b_{n+1} = f(b_n) $ for\nevery $ n \\in \\mathbb{N}_0 $. Then the sequence $ \\{ b_n \\}_{n \\in\n\\mathbb{N}_0} $ has no Hyers-Ulam stability.\n",
"title": "Hyers-Ulam stability of elliptic Möbius difference equation"
}
| null | null | null | null | true | null |
13653
| null |
Default
| null | null |
null |
{
"abstract": " Differential calculus on Euclidean spaces has many generalisations. In\nparticular, on a set $X$, a diffeological structure is given by maps from open\nsubsets of Euclidean spaces to $X$, a differential structure is given by maps\nfrom $X$ to $\\mathbb{R}$, and a Frölicher structure is given by maps from\n$\\mathbb{R}$ to $X$ as well as maps from $X$ to $\\mathbb{R}$. We illustrate the\nrelations between these structures through examples.\n",
"title": "Diffeological, Frölicher, and Differential Spaces"
}
| null | null | null | null | true | null |
13654
| null |
Default
| null | null |
null |
{
"abstract": " Let $P$ be a finite $p$-group and $p$ be an odd prime. Let\n$\\mathcal{A}_p(P)_{\\geq2}$ be a poset consisting of elementary abelian\nsubgroups of rank at least 2. If the derived subgroup $P'\\cong C_p\\times C_p$,\nthen the spheres occurring in $\\mathcal{A}_p(P)_{\\geq2}$ all have the same\ndimension.\n",
"title": "Elementary abelian subgroups in some special p-groups"
}
| null | null | null | null | true | null |
13655
| null |
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| null | null |
null |
{
"abstract": " In recent years, deep generative models have been shown to 'imagine'\nconvincing high-dimensional observations such as images, audio, and even video,\nlearning directly from raw data. In this work, we ask how to imagine\ngoal-directed visual plans -- a plausible sequence of observations that\ntransition a dynamical system from its current configuration to a desired goal\nstate, which can later be used as a reference trajectory for control. We focus\non systems with high-dimensional observations, such as images, and propose an\napproach that naturally combines representation learning and planning. Our\nframework learns a generative model of sequential observations, where the\ngenerative process is induced by a transition in a low-dimensional planning\nmodel, and an additional noise. By maximizing the mutual information between\nthe generated observations and the transition in the planning model, we obtain\na low-dimensional representation that best explains the causal nature of the\ndata. We structure the planning model to be compatible with efficient planning\nalgorithms, and we propose several such models based on either discrete or\ncontinuous states. Finally, to generate a visual plan, we project the current\nand goal observations onto their respective states in the planning model, plan\na trajectory, and then use the generative model to transform the trajectory to\na sequence of observations. We demonstrate our method on imagining plausible\nvisual plans of rope manipulation.\n",
"title": "Learning Plannable Representations with Causal InfoGAN"
}
| null | null | null | null | true | null |
13656
| null |
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| null | null |
null |
{
"abstract": " We show that the standard stochastic gradient decent (SGD) algorithm is\nguaranteed to learn, in polynomial time, a function that is competitive with\nthe best function in the conjugate kernel space of the network, as defined in\nDaniely, Frostig and Singer. The result holds for log-depth networks from a\nrich family of architectures. To the best of our knowledge, it is the first\npolynomial-time guarantee for the standard neural network learning algorithm\nfor networks of depth more that two.\nAs corollaries, it follows that for neural networks of any depth between $2$\nand $\\log(n)$, SGD is guaranteed to learn, in polynomial time, constant degree\npolynomials with polynomially bounded coefficients. Likewise, it follows that\nSGD on large enough networks can learn any continuous function (not in\npolynomial time), complementing classical expressivity results.\n",
"title": "SGD Learns the Conjugate Kernel Class of the Network"
}
| null | null | null | null | true | null |
13657
| null |
Default
| null | null |
null |
{
"abstract": " Most simulation schemes for partial differential equations (PDEs) focus on\nminimizing a simple error norm of a discretized version of a field. This paper\ntakes a fundamentally different approach; the discretized field is interpreted\nas data providing information about a real physical field that is unknown. This\ninformation is sought to be conserved by the scheme as the field evolves in\ntime. Such an information theoretic approach to simulation was pursued before\nby information field dynamics (IFD). In this paper we work out the theory of\nIFD for nonlinear PDEs in a noiseless Gaussian approximation. The result is an\naction that can be minimized to obtain an informationally optimal simulation\nscheme. It can be brought into a closed form using field operators to calculate\nthe appearing Gaussian integrals. The resulting simulation schemes are tested\nnumerically in two instances for the Burgers equation. Their accuracy surpasses\nfinite-difference schemes on the same resolution. The IFD scheme, however, has\nto be correctly informed on the subgrid correlation structure. In certain\nlimiting cases we recover well-known simulation schemes like spectral Fourier\nGalerkin methods. We discuss implications of the approximations made.\n",
"title": "Towards information optimal simulation of partial differential equations"
}
| null | null | null | null | true | null |
13658
| null |
Default
| null | null |
null |
{
"abstract": " In this paper we present a translation from the quantum programming language\nQuipper to the QPMC model checker, with the main aim of verifying Quipper\nprograms. Quipper is an embedded functional programming language for quantum\ncomputation. It is above all a circuit description language, for this reason it\nuses the vector state formalism and its main purpose is to make circuit\nimplementation easy providing high level operations for circuit manipulation.\nQuipper provides both an high-level circuit building interface and a simulator.\nQPMC is a model checker for quantum protocols based on the density matrix\nformalism. QPMC extends the probabilistic model checker IscasMC allowing to\nformally verify properties specified in the temporal logic QCTL on Quantum\nMarkov Chains. We implemented and tested our translation on several quantum\nalgorithms, including Grover's quantum search.\n",
"title": "Verifying Quantum Programs: From Quipper to QPMC"
}
| null | null | null | null | true | null |
13659
| null |
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| null | null |
null |
{
"abstract": " We report the experimental realization of Dirac semimetal state in NdSb, a\nmaterial with antiferromagnetic ground state. The occurrence of topological\nsemimetal state has been well supported by our band structure calculations and\nthe experimental observation of chiral anomaly induced negative\nmagnetoresistance. A field-induced Fermi surface reconstruction is observed, in\nresponse to the change of spin polarization. The observation of topological\nsemimetal state in a magnetic material provides an opportunity to investigate\nthe magneto-topological phenomena.\n",
"title": "Topological semimetal state and field-induced Fermi surface reconstruction in antiferromagnetic monopnictide NdSb"
}
| null | null | null | null | true | null |
13660
| null |
Default
| null | null |
null |
{
"abstract": " Understanding the 3D structure of a scene is of vital importance, when it\ncomes to developing fully autonomous robots. To this end, we present a novel\ndeep learning based framework that estimates depth, surface normals and surface\ncurvature by only using a single RGB image. To the best of our knowledge this\nis the first work to estimate surface curvature from colour using a machine\nlearning approach. Additionally, we demonstrate that by tuning the network to\ninfer well designed features, such as surface curvature, we can achieve\nimproved performance at estimating depth and normals.This indicates that\nnetwork guidance is still a useful aspect of designing and training a neural\nnetwork. We run extensive experiments where the network is trained to infer\ndifferent tasks while the model capacity is kept constant resulting in\ndifferent feature maps based on the tasks at hand. We outperform the previous\nstate-of-the-art benchmarks which jointly estimate depths and surface normals\nwhile predicting surface curvature in parallel.\n",
"title": "Joint Prediction of Depths, Normals and Surface Curvature from RGB Images using CNNs"
}
| null | null | null | null | true | null |
13661
| null |
Default
| null | null |
null |
{
"abstract": " Motivated by applications in social and biological network analysis, we\nintroduce a new form of agnostic clustering termed~\\emph{motif correlation\nclustering}, which aims to minimize the cost of clustering errors associated\nwith both edges and higher-order network structures. The problem may be\nsuccinctly described as follows: Given a complete graph $G$, partition the\nvertices of the graph so that certain predetermined `important' subgraphs\nmostly lie within the same cluster, while `less relevant' subgraphs are allowed\nto lie across clusters. Our contributions are as follows: We first introduce\nseveral variants of motif correlation clustering and then show that these\nclustering problems are NP-hard. We then proceed to describe polynomial-time\nclustering algorithms that provide constant approximation guarantees for the\nproblems at hand. Despite following the frequently used LP relaxation and\nrounding procedure, the algorithms involve a sophisticated and carefully\ndesigned neighborhood growing step that combines information about both edge\nand motif structures. We conclude with several examples illustrating the\nperformance of the developed algorithms on synthetic and real networks.\n",
"title": "Motif and Hypergraph Correlation Clustering"
}
| null | null | null | null | true | null |
13662
| null |
Default
| null | null |
null |
{
"abstract": " We consider a problem of learning the reward and policy from expert examples\nunder unknown dynamics in high-dimensional scenarios. Our proposed method\nbuilds on the framework of generative adversarial networks and introduces the\nempowerment-regularized maximum-entropy inverse reinforcement learning to learn\nnear-optimal rewards and policies. Empowerment-based regularization prevents\nthe policy from overfitting expert demonstration, thus leads to a generalized\nbehavior which results in learning near-optimal rewards. Our method\nsimultaneously learns empowerment through variational information maximization\nalong with the reward and policy under the adversarial learning formulation. We\nevaluate our approach on various high-dimensional complex control tasks. We\nalso test our learned rewards in challenging transfer learning problems where\ntraining and testing environments are made to be different from each other in\nterms of dynamics or structure. The results show that our proposed method not\nonly learns near-optimal rewards and policies that are matching expert behavior\nbut also performs significantly better than state-of-the-art inverse\nreinforcement learning algorithms.\n",
"title": "Adversarial Imitation via Variational Inverse Reinforcement Learning"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
13663
| null |
Validated
| null | null |
null |
{
"abstract": " For a natural social human-robot interaction, it is essential for a robot to\nlearn the human-like social skills. However, learning such skills is\nnotoriously hard due to the limited availability of direct instructions from\npeople to teach a robot. In this paper, we propose an intrinsically motivated\nreinforcement learning framework in which an agent gets the intrinsic\nmotivation-based rewards through the action-conditional predictive model. By\nusing the proposed method, the robot learned the social skills from the\nhuman-robot interaction experiences gathered in the real uncontrolled\nenvironments. The results indicate that the robot not only acquired human-like\nsocial skills but also took more human-like decisions, on a test dataset, than\na robot which received direct rewards for the task achievement.\n",
"title": "Intrinsically motivated reinforcement learning for human-robot interaction in the real-world"
}
| null | null |
[
"Computer Science"
] | null | true | null |
13664
| null |
Validated
| null | null |
null |
{
"abstract": " We propose a novel online alternating minimization (AltMin) algorithm for\ntraining deep neural networks, provide theoretical convergence guarantees and\ndemonstrate its advantages on several classification tasks as compared both to\nstandard backpropagation with stochastic gradient descent (backprop-SGD) and to\noffline alternating minimization. The key difference from backpropagation is an\nexplicit optimization over hidden activations, which eliminates gradient chain\ncomputation in backprop, and breaks the weight training problem into\nindependent, local optimization subproblems; this allows to avoid vanishing\ngradient issues, simplify handling non-differentiable nonlinearities, and\nperform parallel weight updates across the layers. Moreover, parallel local\nsynaptic weight optimization with explicit activation propagation is a step\ncloser to a more biologically plausible learning model than backpropagation,\nwhose biological implausibility has been frequently criticized. Finally, the\nonline nature of our approach allows to handle very large datasets, as well as\ncontinual, lifelong learning, which is our key contribution on top of recently\nproposed offline alternating minimization schemes (e.g., (Carreira-Perpinan\nandWang 2014), (Taylor et al. 2016)).\n",
"title": "Beyond Backprop: Online Alternating Minimization with Auxiliary Variables"
}
| null | null | null | null | true | null |
13665
| null |
Default
| null | null |
null |
{
"abstract": " Sensing in complex systems requires large-scale information exchange and\non-the-go communications over heterogeneous networks and integrated processing\nplatforms. Many networked cyber-physical systems exhibit hierarchical\ninfrastructures of information flows, which naturally leads to a multi-level\ntree-like information structure in which each level corresponds to a particular\nscale of representation. This work focuses on the multiscale fusion of data\ncollected at multiple levels of the system. We propose a multiscale state-space\nmodel to represent multi-resolution data over the hierarchical information\nsystem and formulate a multi-stage dynamic zero-sum game to design a\nmulti-scale $H_{\\infty}$ robust filter. We present numerical experiments for\none and two-dimensional signals and provide a comparative analysis of the\nminimax filter with the standard Kalman filter to show the improvement in\nsignal-to-noise ratio (SNR).\n",
"title": "Minimax Game-Theoretic Approach to Multiscale H-infinity Optimal Filtering"
}
| null | null | null | null | true | null |
13666
| null |
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| null | null |
null |
{
"abstract": " We study the attractors of a class of holomorphic systems with an\nirrationally indifferent fixed point. We prove a trichotomy for the topology of\nthe attractor based on the arithmetic of the rotation number at the fixed\npoint. That is, the attractor is either a Jordan curve, a one-sided hairy\ncircle, or a Cantor bouquet. This has a number of remarkable corollaries on a\nconjecture of M. Herman about the optimal arithmetic condition for the\nexistence of a critical point on the boundary of the Siegel disk, and a\nconjecture of A. Douady on the topology of the boundary of Siegel disks.\nCombined with earlier results on the topic, this completes the topological\ndescription of the behaviors of typical orbits near such fixed points, when the\nrotation number is of high type.\n",
"title": "Topology of irrationally indifferent attractors"
}
| null | null | null | null | true | null |
13667
| null |
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| null | null |
null |
{
"abstract": " Graphene, a honeycomb lattice of carbon atoms ruled by tight-binding\ninteraction, exhibits extraordinary electronic properties due to the presence\nof Dirac cones within its band structure. These intriguing singularities have\nnaturally motivated the discovery of their classical analogues. In this work,\nwe present a general and direct procedure to reproduce the peculiar physics of\ngraphene within a very simple acoustic metamaterial: a double lattice of soda\ncans resonant at two different frequencies. The first triangular sub-lattice\ngenerates a bandgap at low frequency, which induces a tight-binding coupling\nbetween the resonant defects of the second Honeycomb one, hence allowing us to\nobtain a graphene-like band structure. We prove the relevance of this approach\nby showing that both numerical and experimental dispersion relations exhibit\nthe requested Dirac cone. We also demonstrate the straightforward monitoring of\nthe coupling strength within the crystal of resonant defects. This work shows\nthat crystalline metamaterials are very promising candidates to investigate\ntantalizing solid-state physics phenomena with classical waves.\n",
"title": "Crystalline Soda Can Metamaterial exhibiting Graphene-like Dispersion at subwavelength scale"
}
| null | null | null | null | true | null |
13668
| null |
Default
| null | null |
null |
{
"abstract": " The retina is a complex nervous system which encodes visual stimuli before\nhigher order processing occurs in the visual cortex. In this study we evaluated\nwhether information about the stimuli received by the retina can be retrieved\nfrom the firing rate distribution of Retinal Ganglion Cells (RGCs), exploiting\nHigh-Density 64x64 MEA technology. To this end, we modeled the RGC population\nactivity using mean-covariance Restricted Boltzmann Machines, latent variable\nmodels capable of learning the joint distribution of a set of continuous\nobserved random variables and a set of binary unobserved random units. The idea\nwas to figure out if binary latent states encode the regularities associated to\ndifferent visual stimuli, as modes in the joint distribution. We measured the\ngoodness of mcRBM encoding by calculating the Mutual Information between the\nlatent states and the stimuli shown to the retina. Results show that binary\nstates can encode the regularities associated to different stimuli, using both\ngratings and natural scenes as stimuli. We also discovered that hidden\nvariables encode interesting properties of retinal activity, interpreted as\npopulation receptive fields. We further investigated the ability of the model\nto learn different modes in population activity by comparing results associated\nto a retina in normal conditions and after pharmacologically blocking GABA\nreceptors (GABAC at first, and then also GABAA and GABAB). As expected, Mutual\nInformation tends to decrease if we pharmacologically block receptors. We\nfinally stress that the computational method described in this work could\npotentially be applied to any kind of neural data obtained through MEA\ntechnology, though different techniques should be applied to interpret the\nresults.\n",
"title": "Modeling Retinal Ganglion Cell Population Activity with Restricted Boltzmann Machines"
}
| null | null | null | null | true | null |
13669
| null |
Default
| null | null |
null |
{
"abstract": " In {\\em{Holm}, Proc. Roy. Soc. A 471 (2015)} stochastic fluid equations were\nderived by employing a variational principle with an assumed stochastic\nLagrangian particle dynamics. Here we show that the same stochastic Lagrangian\ndynamics naturally arises in a multi-scale decomposition of the deterministic\nLagrangian flow map into a slow large-scale mean and a rapidly fluctuating\nsmall scale map. We employ homogenization theory to derive effective slow\nstochastic particle dynamics for the resolved mean part, thereby justifying\nstochastic fluid partial equations in the Eulerian formulation. To justify the\napplication of rigorous homogenization theory, we assume mildly chaotic fast\nsmall-scale dynamics, as well as a centering condition. The latter requires\nthat the mean of the fluctuating deviations is small, when pulled back to the\nmean flow.\n",
"title": "Stochastic partial differential fluid equations as a diffusive limit of deterministic Lagrangian multi-time dynamics"
}
| null | null | null | null | true | null |
13670
| null |
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| null | null |
null |
{
"abstract": " In this paper, we consider solving a class of convex optimization problem\nwhich minimizes the sum of three convex functions $f(x)+g(x)+h(Bx)$, where\n$f(x)$ is differentiable with a Lipschitz continuous gradient, $g(x)$ and\n$h(x)$ have a closed-form expression of their proximity operators and $B$ is a\nbounded linear operator. This type of optimization problem has wide application\nin signal recovery and image processing. To make full use of the\ndifferentiability function in the optimization problem, we take advantage of\ntwo operator splitting methods: the forward-backward splitting method and the\nthree operator splitting method. In the iteration scheme derived from the two\noperator splitting methods, we need to compute the proximity operator of $g+h\n\\circ B$ and $h \\circ B$, respectively. Although these proximity operators do\nnot have a closed-form solution in general, they can be solved very\nefficiently. We mainly employ two different approaches to solve these proximity\noperators: one is dual and the other is primal-dual. Following this way, we\nfortunately find that three existing iterative algorithms including Condat and\nVu algorithm, primal-dual fixed point (PDFP) algorithm and primal-dual three\noperator (PD3O) algorithm are a special case of our proposed iterative\nalgorithms. Moreover, we discover a new kind of iterative algorithm to solve\nthe considered optimization problem, which is not covered by the existing ones.\nUnder mild conditions, we prove the convergence of the proposed iterative\nalgorithms. Numerical experiments applied on fused Lasso problem, constrained\ntotal variation regularization in computed tomography (CT) image reconstruction\nand low-rank total variation image super-resolution problem demonstrate the\neffectiveness and efficiency of the proposed iterative algorithms.\n",
"title": "A general framework for solving convex optimization problems involving the sum of three convex functions"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13671
| null |
Validated
| null | null |
null |
{
"abstract": " We use information entropy to test the isotropy in the nearby galaxy\ndistribution mapped by the Two Micron All-Sky redshift survey (2MRS). We find\nthat the galaxy distribution is highly anisotropic on small scales. The radial\nanisotropy gradually decreases with increasing length scales and the observed\nanisotropy is consistent with that expected for an isotropic Poisson\ndistribution beyond a length scale of $90 \\, h^{-1}\\, {\\rm Mpc}$. Using mock\ncatalogues from N-body simulations, we find that the galaxy distribution in the\n2MRS exhibits a degree of anisotropy compatible with that of the $\\Lambda$CDM\nmodel after accounting for the clustering bias of the 2MRS galaxies. We also\nquantify the polar and azimuthal anisotropies and identify two directions\n$(l,b)=(150^{\\circ}, -15^{\\circ})$, $(l,b)=(310^{\\circ},-15^{\\circ})$ which are\nsignificantly anisotropic compared to the other directions in the sky. We\nsuggest that their preferential orientations on the sky may indicate a possible\nalignment of the Local Group with two nearby large scale structures. Despite\nthe differences in the degree of anisotropy on small scales, we find that the\ngalaxy distributions in both the 2MRS and the $\\Lambda$CDM model are isotropic\non a scale of $90 \\, h^{-1}\\, {\\rm Mpc}$.\n",
"title": "Testing isotropy in the Two Micron All-Sky redshift survey with information entropy"
}
| null | null | null | null | true | null |
13672
| null |
Default
| null | null |
null |
{
"abstract": " Observations of diffuse starlight in the outskirts of galaxies are thought to\nbe a fundamental source of constraints on the cosmological context of galaxy\nassembly in the $\\Lambda$CDM model. Such observations are not trivial because\nof the extreme faintness of such regions. In this work, we investigate the\nphotometric properties of six massive early type galaxies (ETGs) in the VEGAS\nsample (NGC 1399, NGC 3923, NGC 4365, NGC 4472, NGC 5044, and NGC 5846) out to\nextremely low surface brightness levels, with the goal of characterizing the\nglobal structure of their light profiles for comparison to state-of-the-art\ngalaxy formation models. We carry out deep and detailed photometric mapping of\nour ETG sample taking advantage of deep imaging with VST/OmegaCAM in the g and\ni bands. By fitting the light profiles, and comparing the results to\nsimulations of elliptical galaxy assembly, we identify signatures of a\ntransition between \"relaxed\" and \"unrelaxed\" accreted components and can\nconstrain the balance between in situ and accreted stars. The very good\nagreement of our results with predictions from theoretical simulations\ndemonstrates that the full VEGAS sample of $\\sim 100$ ETGs will allow us to use\nthe distribution of diffuse light as a robust statistical probe of the\nhierarchical assembly of massive galaxies.\n",
"title": "VEGAS: A VST Early-type GAlaxy Survey. II. Photometric study of giant ellipticals and their stellar halos"
}
| null | null | null | null | true | null |
13673
| null |
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| null | null |
null |
{
"abstract": " Let $A= \\Lambda \\oplus C$ be a trivial extension algebra. The aim of this\npaper is to establish formulas for the projective dimension and the injective\ndimension for a certain class of $A$-modules which is expressed by using the\nderived functors $- \\otimes^{\\mathbb{L}}_{\\Lambda}C$ and\n$\\mathbb{R}\\text{Hom}_{\\Lambda}(C, -)$. Consequently, we obtain formulas for\nthe global dimension of $A$, which gives a modern expression of the classical\nformula for the global dimension by Palmer-Roos and Löfwall that is written\nin complicated classical derived functors.\nThe main application of the formulas is to give a necessary and sufficient\ncondition for $A$ to be an Iwanaga-Gorenstein algebra.\nWe also give a description of the kernel $\\text{Ker} \\varpi$ of the canonical\nfunctor $\\varpi: \\mathsf{D}^{\\mathrm{b}}(\\text{mod} \\Lambda) \\to\n\\text{Sing}^{\\mathbb{Z}} A$ in the case $\\text{pd} C < \\infty$.\n",
"title": "Homological dimension formulas for trivial extension algebras"
}
| null | null | null | null | true | null |
13674
| null |
Default
| null | null |
null |
{
"abstract": " We study the spread of Rényi entropy between two halves of a\nSachdev-Ye-Kitaev (SYK) chain of Majorana fermions, prepared in a thermofield\ndouble (TFD) state. The SYK chain model is a model of chaotic many-body\nsystems, which describes a one-dimensional lattice of Majorana fermions, with\nspatially local random quartic interaction. We find that for integer Rényi\nindex $n>1$, the Rényi entanglement entropy saturates at a parametrically\nsmaller value than expected. This implies that the TFD state of the SYK chain\ndoes not rapidly thermalize, despite being maximally chaotic: instead, it\nrapidly approaches a prethermal state. We compare our results to the signatures\nof thermalization observed in other quenches in the SYK model, and to intuition\nfrom nearly-$\\mathrm{AdS}_2$ gravity.\n",
"title": "Spread of entanglement in a Sachdev-Ye-Kitaev chain"
}
| null | null | null | null | true | null |
13675
| null |
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| null | null |
null |
{
"abstract": " We explore lattice structures on integer binary relations (i.e. binary\nrelations on the set $\\{1, 2, \\dots, n\\}$ for a fixed integer $n$) and on\ninteger posets (i.e. partial orders on the set $\\{1, 2, \\dots, n\\}$ for a fixed\ninteger $n$). We first observe that the weak order on the symmetric group\nnaturally extends to a lattice structure on all integer binary relations. We\nthen show that the subposet of this weak order induced by integer posets\ndefines as well a lattice. We finally study the subposets of this weak order\ninduced by specific families of integer posets corresponding to the elements,\nthe intervals, and the faces of the permutahedron, the associahedron, and some\nrecent generalizations of those.\n",
"title": "The weak order on integer posets"
}
| null | null | null | null | true | null |
13676
| null |
Default
| null | null |
null |
{
"abstract": " Undetected overfitting can occur when there are significant redundancies\nbetween training and validation data. We describe AVE, a new measure of\ntraining-validation redundancy for ligand-based classification problems that\naccounts for the similarity amongst inactive molecules as well as active. We\ninvestigated seven widely-used benchmarks for virtual screening and\nclassification, and show that the amount of AVE bias strongly correlates with\nthe performance of ligand-based predictive methods irrespective of the\npredicted property, chemical fingerprint, similarity measure, or\npreviously-applied unbiasing techniques. Therefore, it may be that the\npreviously-reported performance of most ligand-based methods can be explained\nby overfitting to benchmarks rather than good prospective accuracy.\n",
"title": "Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization"
}
| null | null | null | null | true | null |
13677
| null |
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| null | null |
null |
{
"abstract": " We suggest an inverse dispersion method for calculating photonic band diagram\nfor materials with arbitrary frequency-dependent dielectric functions. The\nmethod is able to calculate the complex wave vector for a given frequency by\nsolving the eigenvalue problem with a non-Hermitian operator. The analogy with\n$\\cal{PT}$-symmetric Hamiltonians reveals that the operator corresponds to the\nmomentum as a physical quantity and the singularities at the band edges are\nrelated to the branch points and responses for the features on the band edges.\nThe method is realized using plane wave expansion technique for two-dimensional\nperiodical structure in the case of TE- and TM-polarization. We illustrate the\napplicability of the method by calculation of the photonic band diagrams of an\ninfinite two-dimension square lattice composed of dielectric cylinders using\nthe measured frequency dependent dielectric functions of different materials\n(amorphous hydrogenated carbon, silicon, and chalcogenide glass). We show that\nthe method allows to distinguish unambiguously between Bragg and Mie gaps in\nthe spectra.\n",
"title": "Inverse dispersion method for calculation of complex photonic band diagram and $\\cal{PT}$-symmetry"
}
| null | null | null | null | true | null |
13678
| null |
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| null | null |
null |
{
"abstract": " Vehicle-to-infrastructure (V2I) communication may provide high data rates to\nvehicles via millimeter-wave (mmWave) microcellular networks. This paper uses\nstochastic geometry to analyze the coverage of urban mmWave microcellular\nnetworks. Prior work used a pathloss model with a line-of-sight probability\nfunction based on randomly oriented buildings, to determine whether a link was\nline-of-sight or non-line-of-sight. In this paper, we use a pathloss model\ninspired by measurements, which uses a Manhattan distance pathloss model and\naccounts for differences in pathloss exponents and losses when turning corners.\nIn our model, streets are randomly located as a Manhattan Poisson line process\n(MPLP) and the base stations (BSs) are distributed according to a Poisson point\nprocess. Our model is well suited for urban microcellular networks where the\nBSs are deployed at street level. Based on this new approach, we derive the\ncoverage probability under certain BS association rules to obtain closed-form\nsolutions without much complexity. In addition, we draw two main conclusions\nfrom our work. First, non-line-of-sight BSs are not a major benefit for\nassociation or source of interference most of the time. Second, there is an\nultra-dense regime where deploying active BSs does not enhance coverage.\n",
"title": "MmWave vehicle-to-infrastructure communication: Analysis of urban microcellular networks"
}
| null | null | null | null | true | null |
13679
| null |
Default
| null | null |
null |
{
"abstract": " Manifolds with infinite cylindrical ends have continuous spectrum of\nincreasing multiplicity as energy grows, and in general embedded resonances and\neigenvalues can accumulate at infinity. However, we prove that if geodesic\ntrapping is sufficiently mild, then such an accumulation is ruled out, and\nmoreover the cutoff resolvent is uniformly bounded at high energies. We obtain\nas a corollary the existence of resonance free regions near the continuous\nspectrum.\nWe also obtain improved estimates when the resolvent is cut off away from\npart of the trapping, and along the way we prove some resolvent estimates for\nrepulsive potentials on the half line which may be of independent interest.\n",
"title": "Resolvent estimates on asymptotically cylindrical manifolds and on the half line"
}
| null | null | null | null | true | null |
13680
| null |
Default
| null | null |
null |
{
"abstract": " We give a construction of a real number that is normal to all integer bases\nand continued fraction normal. The computation of the first n digits of its\ncontinued fraction expansion performs in the order of n^4 mathematical\noperations. The construction works by defining successive refinements of\nappropriate subintervals to achieve, in the limit, simple normality to all\ninteger bases and continued fraction normality. The main diffculty is to\ncontrol the length of these subintervals. To achieve this we adapt and combine\nknown metric theorems on continued fractions and on expansions in integers\nbases.\n",
"title": "On absolutely normal and continued fraction normal numbers"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13681
| null |
Validated
| null | null |
null |
{
"abstract": " A strong interaction is known to exist between edge-colored graphs (which\nencode PL pseudo-manifolds of arbitrary dimension) and random tensor models (as\na possible approach to the study of Quantum Gravity). The key tool is the {\\it\nG-degree} of the involved graphs, which drives the {\\it $1/N$ expansion} in the\ntensor models context. In the present paper - by making use of combinatorial\nproperties concerning Hamiltonian decompositions of the complete graph - we\nprove that, in any even dimension $d\\ge 4$, the G-degree of all bipartite\ngraphs, as well as of all (bipartite or non-bipartite) graphs representing\nsingular manifolds, is an integer multiple of $(d-1)!$. As a consequence, in\neven dimension, the terms of the $1/N$ expansion corresponding to odd powers of\n$1/N$ are null in the complex context, and do not involve colored graphs\nrepresenting singular manifolds in the real context.\nIn particular, in the 4-dimensional case, where the G-degree is shown to\ndepend only on the regular genera with respect to an arbitrary pair of\n\"associated\" cyclic permutations, several results are obtained, relating the\nG-degree or the regular genus of 5-colored graphs and the Euler characteristic\nof the associated PL 4-manifolds.\n",
"title": "Combinatorial properties of the G-degree"
}
| null | null | null | null | true | null |
13682
| null |
Default
| null | null |
null |
{
"abstract": " Quasi-random walks show similar features as standard random walks, but with\nmuch less randomness. We utilize this established model from discrete\nmathematics and show how agents carrying out quasi-random walks can be used for\nimage transition and animation. The key idea is to generalize the notion of\nquasi-random walks and let a set of autonomous agents perform quasi-random\nwalks painting an image. Each agent has one particular target image that they\npaint when following a sequence of directions for their quasi-random walk. The\nsequence can easily be chosen by an artist and allows them to produce a wide\nrange of different transition patterns and animations.\n",
"title": "Quasi-random Agents for Image Transition and Animation"
}
| null | null | null | null | true | null |
13683
| null |
Default
| null | null |
null |
{
"abstract": " End-to-end learning treats the entire system as a whole adaptable black box,\nwhich, if sufficient data are available, may learn a system that works very\nwell for the target task. This principle has recently been applied to several\nprototype research on speaker verification (SV), where the feature learning and\nclassifier are learned together with an objective function that is consistent\nwith the evaluation metric. An opposite approach to end-to-end is feature\nlearning, which firstly trains a feature learning model, and then constructs a\nback-end classifier separately to perform SV. Recently, both approaches\nachieved significant performance gains on SV, mainly attributed to the smart\nutilization of deep neural networks. However, the two approaches have not been\ncarefully compared, and their respective advantages have not been well\ndiscussed. In this paper, we compare the end-to-end and feature learning\napproaches on a text-independent SV task. Our experiments on a dataset sampled\nfrom the Fisher database and involving 5,000 speakers demonstrated that the\nfeature learning approach outperformed the end-to-end approach. This is a\nstrong support for the feature learning approach, at least with data and\ncomputation resources similar to ours.\n",
"title": "Deep Speaker Verification: Do We Need End to End?"
}
| null | null | null | null | true | null |
13684
| null |
Default
| null | null |
null |
{
"abstract": " Most real-world document collections involve various types of metadata, such\nas author, source, and date, and yet the most commonly-used approaches to\nmodeling text corpora ignore this information. While specialized models have\nbeen developed for particular applications, few are widely used in practice, as\ncustomization typically requires derivation of a custom inference algorithm. In\nthis paper, we build on recent advances in variational inference methods and\npropose a general neural framework, based on topic models, to enable flexible\nincorporation of metadata and allow for rapid exploration of alternative\nmodels. Our approach achieves strong performance, with a manageable tradeoff\nbetween perplexity, coherence, and sparsity. Finally, we demonstrate the\npotential of our framework through an exploration of a corpus of articles about\nUS immigration.\n",
"title": "Neural Models for Documents with Metadata"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
13685
| null |
Validated
| null | null |
null |
{
"abstract": " Recent years have witnessed great success of convolutional neural network\n(CNN) for various problems both in low and high level visions. Especially\nnoteworthy is the residual network which was originally proposed to handle\nhigh-level vision problems and enjoys several merits. This paper aims to extend\nthe merits of residual network, such as skip connection induced fast training,\nfor a typical low-level vision problem, i.e., single image super-resolution. In\ngeneral, the two main challenges of existing deep CNN for supper-resolution lie\nin the gradient exploding/vanishing problem and large numbers of parameters or\ncomputational cost as CNN goes deeper. Correspondingly, the skip connections or\nidentity mapping shortcuts are utilized to avoid gradient exploding/vanishing\nproblem. In addition, the skip connections have naturally centered the\nactivation which led to better performance. To tackle with the second problem,\na lightweight CNN architecture which has carefully designed width, depth and\nskip connections was proposed. In particular, a strategy of gradually varying\nthe shape of network has been proposed for residual network. Different residual\narchitectures for image super-resolution have also been compared. Experimental\nresults have demonstrated that the proposed CNN model can not only achieve\nstate-of-the-art PSNR and SSIM results for single image super-resolution but\nalso produce visually pleasant results. This paper has extended the mmm 2017\noral conference paper with a considerable new analyses and more experiments\nespecially from the perspective of centering activations and ensemble behaviors\nof residual network.\n",
"title": "Single Image Super-resolution via a Lightweight Residual Convolutional Neural Network"
}
| null | null | null | null | true | null |
13686
| null |
Default
| null | null |
null |
{
"abstract": " We study a class of flat bundles, of finite rank $N$, which arise naturally\nfrom the Donaldson-Thomas theory of a Calabi-Yau threefold $X$ via the notion\nof a variation of BPS structure. We prove that in a large $N$ limit their flat\nsections converge to the solutions to certain infinite dimensional\nRiemann-Hilbert problems recently found by Bridgeland. In particular this\nimplies an expression for the positive degree, genus $0$ Gopakumar-Vafa\ncontribution to the Gromov-Witten partition function of $X$ in terms of\nsolutions to confluent hypergeometric differential equations.\n",
"title": "Variations of BPS structure and a large rank limit"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13687
| null |
Validated
| null | null |
null |
{
"abstract": " Appealing to the 1902 Gibbs' formalism for classical statistical mechanics\n(SM), the first SM axiomatic theory ever that successfully explained\nequilibrium thermodynamics, we will here show that already at the classical\nlevel there is a strong correlation between the Renyi's exponent $\\alpha$ and\nthe number of particles for very simple systems. No reference to heat baths is\nneeded for such a purpose.\n",
"title": "Strong correlations between the exponent $α$ and the particle number for a Renyi-monoatomic gas in Gibbs' statistical mechanics"
}
| null | null |
[
"Physics"
] | null | true | null |
13688
| null |
Validated
| null | null |
null |
{
"abstract": " Smooth backfitting has proven to have a number of theoretical and practical\nadvantages in structured regression. Smooth backfitting projects the data down\nonto the structured space of interest providing a direct link between data and\nestimator. This paper introduces the ideas of smooth backfitting to survival\nanalysis in a proportional hazard model, where we assume an underlying\nconditional hazard with multiplicative components. We develop asymptotic theory\nfor the estimator and we use the smooth backfitter in a practical application,\nwhere we extend recent advances of in-sample forecasting methodology by\nallowing more information to be incorporated, while still obeying the\nstructured requirements of in-sample forecasting.\n",
"title": "Smooth backfitting of proportional hazards -- A new approach projecting survival data"
}
| null | null | null | null | true | null |
13689
| null |
Default
| null | null |
null |
{
"abstract": " Locomotion at low Reynolds numbers is a topic of growing interest, spurred by\nits various engineering and medical applications. This paper presents a novel\nprototype and a locomotion algorithm for the 3-link planar Purcell's swimmer\nbased on Lie algebraic notions. The kinematic model based on Cox theory of the\nprototype swimmer is a driftless control-affine system. Using the existing\nstrong controllability and related results, the existence of motion primitives\nis initially shown. The Lie algebra of the control vector fields is then used\nto synthesize control profiles to generate motions along the basis of the Lie\nalgebra associated with the structure group of the system. An open loop control\nsystem with vision-based positioning is successfully implemented which allows\ntracking any given continuous trajectory of the position and orientation of the\nswimmer's base link. Alongside, the paper also provides a theoretical\ninterpretation of the symmetry arguments presented in the existing literature\nto generate the control profiles of the swimmer.\n",
"title": "Trajectory Tracking Using Motion Primitives for the Purcell's Swimmer"
}
| null | null |
[
"Computer Science"
] | null | true | null |
13690
| null |
Validated
| null | null |
null |
{
"abstract": " Assessment of multimedia quality relies heavily on subjective assessment, and\nis typically done by human subjects in the form of preferences or continuous\nratings. Such data is crucial for analysis of different multimedia processing\nalgorithms as well as validation of objective (computational) methods for the\nsaid purpose. To that end, statistical testing provides a theoretical framework\ntowards drawing meaningful inferences, and making well grounded conclusions and\nrecommendations. While parametric tests (such as t test, ANOVA, and error\nestimates like confidence intervals) are popular and widely used in the\ncommunity, there appears to be a certain degree of confusion in the application\nof such tests. Specifically, the assumption of normality and homogeneity of\nvariance is often not well understood. Therefore, the main goal of this paper\nis to revisit them from a theoretical perspective and in the process provide\nuseful insights into their practical implications. Experimental results on both\nsimulated and real data are presented to support the arguments made. A software\nimplementing the said recommendations is also made publicly available, in order\nto achieve the goal of reproducible research.\n",
"title": "Data Analysis in Multimedia Quality Assessment: Revisiting the Statistical Tests"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
13691
| null |
Validated
| null | null |
null |
{
"abstract": " Suppose that the inverse image of the zero vector by a continuous map\n$f:{\\mathbb R}^n\\to{\\mathbb R}^q$ has an isolated point $P$. There is a local\nobstruction to removing this isolated zero by a small perturbation,\ngeneralizing the notion of index for vector fields, the $q=n$ case. The\nexistence of a continuous map $g$ which approximates $f$ but is nonvanishing\nnear $P$ is equivalent to a topological property we call \"locally inessential,\"\nand for dimensions $n$, $q$ where $\\pi_{n-1}(S^{q-1})$ is trivial, every\nisolated zero is locally inessential. We consider the problem of constructing\nsuch an approximation $g$, and show that there exists a continuous homotopy\nfrom $f$ to $g$ through locally nonvanishing maps. If $f$ is a semialgebraic\nmap, then there exists such a homotopy which is also semialgebraic. For $q=2$\nand $f$ real analytic with a locally inessential isolated zero, there exists a\nHölder continuous homotopy $F(x,t)$ which, for $(x,t)\\ne(P,0)$, is real\nanalytic and nonvanishing. The existence of a smooth homotopy, given a smooth\nmap $f$, is stated as an open question.\n",
"title": "Removing Isolated Zeroes by Homotopy"
}
| null | null | null | null | true | null |
13692
| null |
Default
| null | null |
null |
{
"abstract": " We prove that certain coinduced actions for an inclusion of finitely\ngenerated commensurated subgroups with relative one end are continuous cocycle\nsuperrigid actions. We also show the necessity for the relative end assumption.\n",
"title": "Continuous cocycle superrigidity for coinduced actions and relative ends"
}
| null | null | null | null | true | null |
13693
| null |
Default
| null | null |
null |
{
"abstract": " We study diffusion properties of an inertial Brownian motor moving on a\nratchet substrate, i.e. a periodic structure with broken reflection symmetry.\nThe motor is driven by an unbiased time-periodic symmetric force which takes\nthe system out of thermal equilibrium. For selected parameter sets, the system\nis in a non-chaotic regime in which we can identify a non-monotonic dependence\nof the diffusion coefficient on temperature: for low temperature, it initially\nincreases as temperature grows, passes through its local maximum, next starts\nto diminish reaching its local minimum and finally it monotonically increases\nin accordance with the Einstein linear relation. Particularly interesting is\nthe temperature interval in which diffusion is suppressed by thermal noise and\nwe explain this effect in terms of transition rates of a three-state stochastic\nmodel.\n",
"title": "Brownian ratchets: How stronger thermal noise can reduce diffusion"
}
| null | null | null | null | true | null |
13694
| null |
Default
| null | null |
null |
{
"abstract": " We prove that $\\omega$-languages of (non-deterministic) Petri nets and\n$\\omega$-languages of (non-deterministic) Turing machines have the same\ntopological complexity: the Borel and Wadge hierarchies of the class of\n$\\omega$-languages of (non-deterministic) Petri nets are equal to the Borel and\nWadge hierarchies of the class of $\\omega$-languages of (non-deterministic)\nTuring machines which also form the class of effective analytic sets. In\nparticular, for each non-null recursive ordinal $\\alpha < \\omega\\_1^{\\rm CK}\n$ there exist some ${\\bf \\Sigma}^0\\_\\alpha$-complete and some ${\\bf\n\\Pi}^0\\_\\alpha$-complete $\\omega$-languages of Petri nets, and the supremum of\nthe set of Borel ranks of $\\omega$-languages of Petri nets is the ordinal\n$\\gamma\\_2^1$, which is strictly greater than the first non-recursive ordinal\n$\\omega\\_1^{\\rm CK}$. We also prove that there are some ${\\bf\n\\Sigma}\\_1^1$-complete, hence non-Borel, $\\omega$-languages of Petri nets, and\nthat it is consistent with ZFC that there exist some $\\omega$-languages of\nPetri nets which are neither Borel nor ${\\bf \\Sigma}\\_1^1$-complete. This\nanswers the question of the topological complexity of $\\omega$-languages of\n(non-deterministic) Petri nets which was left open in [DFR14,FS14].\n",
"title": "Wadge Degrees of $ω$-Languages of Petri Nets"
}
| null | null |
[
"Computer Science",
"Mathematics"
] | null | true | null |
13695
| null |
Validated
| null | null |
null |
{
"abstract": " Despite having an important role supporting assessment processes, criticism\ntowards evaluation systems and the categorizations used are frequent.\nConsidering the acceptance by the scientific community as an essential issue\nfor using rankings or categorizations in research evaluation, the aim of this\npaper is testing the results of rankings of scholarly book publishers'\nprestige, Scholarly Publishers Indicators (SPI hereafter). SPI is a public,\nsurvey-based ranking of scholarly publishers' prestige (among other\nindicators). The latest version of the ranking (2014) was based on an expert\nconsultation with a large number of respondents. In order to validate and\nrefine the results for Humanities' fields as proposed by the assessment\nagencies, a Delphi technique was applied with a panel of randomly selected\nexperts over the initial rankings. The results show an equalizing effect of the\ntechnique over the initial rankings as well as a high degree of concordance\nbetween its theoretical aim (consensus among experts) and its empirical results\n(summarized with Gini Index). The resulting categorization is understood as\nmore conclusive and susceptible of being accepted by those under evaluation.\n",
"title": "Is there agreement on the prestige of scholarly book publishers in the Humanities? DELPHI over survey results"
}
| null | null | null | null | true | null |
13696
| null |
Default
| null | null |
null |
{
"abstract": " Zero-shot recognition aims to accurately recognize objects of unseen classes\nby using a shared visual-semantic mapping between the image feature space and\nthe semantic embedding space. This mapping is learned on training data of seen\nclasses and is expected to have transfer ability to unseen classes. In this\npaper, we tackle this problem by exploiting the intrinsic relationship between\nthe semantic space manifold and the transfer ability of visual-semantic\nmapping. We formalize their connection and cast zero-shot recognition as a\njoint optimization problem. Motivated by this, we propose a novel framework for\nzero-shot recognition, which contains dual visual-semantic mapping paths. Our\nanalysis shows this framework can not only apply prior semantic knowledge to\ninfer underlying semantic manifold in the image feature space, but also\ngenerate optimized semantic embedding space, which can enhance the transfer\nability of the visual-semantic mapping to unseen classes. The proposed method\nis evaluated for zero-shot recognition on four benchmark datasets, achieving\noutstanding results.\n",
"title": "Zero-Shot Recognition using Dual Visual-Semantic Mapping Paths"
}
| null | null | null | null | true | null |
13697
| null |
Default
| null | null |
null |
{
"abstract": " In this study we developed an automated system that evaluates speech and\nlanguage features from audio recordings of neuropsychological examinations of\n92 subjects in the Framingham Heart Study. A total of 265 features were used in\nan elastic-net regularized binomial logistic regression model to classify the\npresence of cognitive impairment, and to select the most predictive features.\nWe compared performance with a demographic model from 6,258 subjects in the\ngreater study cohort (0.79 AUC), and found that a system that incorporated both\naudio and text features performed the best (0.92 AUC), with a True Positive\nRate of 29% (at 0% False Positive Rate) and a good model fit (Hosmer-Lemeshow\ntest > 0.05). We also found that decreasing pitch and jitter, shorter segments\nof speech, and responses phrased as questions were positively associated with\ncognitive impairment.\n",
"title": "Spoken Language Biomarkers for Detecting Cognitive Impairment"
}
| null | null | null | null | true | null |
13698
| null |
Default
| null | null |
null |
{
"abstract": " The theoretical analysis of detection and decoding of low-density\nparity-check (LDPC) codes transmitted over channels with two-dimensional (2D)\ninterference and additive white Gaussian noise (AWGN) is provided in this\npaper. The detection and decoding system adopts the joint iterative detection\nand decoding scheme (JIDDS) in which the log-domain sum-product algorithm is\nadopted to decode the LDPC codes. The graph representations of the JIDDS are\nexplained. Using the graph representations, we prove that the message-flow\nneighborhood of the detection and decoding system will be tree-like for a\nsufficiently long code length. We further confirm that the performance of the\nJIDDS will concentrate around the performance in which message-flow\nneighborhood is tree-like. Based on the tree-like message-flow neighborhood, we\nemploy a modified density evolution algorithm to track the message densities\nduring the iterations. A threshold is calculated using the density evolution\nalgorithm which can be considered as the theoretical performance limit of the\nsystem. Simulation results demonstrate that the modified density evolution is\neffective in analyzing the performance of 2D interference systems.\n",
"title": "Performance Analysis of Low-Density Parity-Check Codes over 2D Interference Channels via Density Evolution"
}
| null | null | null | null | true | null |
13699
| null |
Default
| null | null |
null |
{
"abstract": " Future electricity distribution grids will host a considerable share of\nvariable renewable energy sources and local storage resources. Moreover, they\nwill face new load structures due for example to the growth of the electric\nvehicle market. These trends raise the need for new paradigms for distribution\ngrids operation, in which Distribution System Operators will increasingly rely\non demand side flexibility and households will progressively become prosumers\nplaying an active role on smart grid energy management. However, in present\nenergy management architectures, the lack of coordination among actors limits\nthe capability of the grid to enable the mentioned trends. In this paper we\ntackle this problem by proposing an architecture that enables households to\nautonomously exchange energy blocks and flexibility services with neighbors,\noperators and market actors. The solution is based on a blockchain transactive\nplatform. We focus on a market application, where households can trade energy\nwith their neighbors, aimed to locally balancing renewable energy production.\nWe propose a market mechanism and dynamic transport prices that provide an\nincentive for households to locally manage energy resources in a way that\nresponds to both pro-sumer and operator needs. We evaluate the impact of such\nmarkets through comprehensive simulations using power flow analysis and\nrealistic load profiles, providing valuable insight for the design of\nappropriate mechanisms and incentives.\n",
"title": "Novel market approach for locally balancing renewable energy production and flexible demand"
}
| null | null |
[
"Computer Science"
] | null | true | null |
13700
| null |
Validated
| null | null |
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