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18,401 | Three-dimensional oscillatory magnetic reconnection | Here we detail the dynamic evolution of localised reconnection regions about
three-dimensional (3D) magnetic null points by using numerical simulation. We
demonstrate for the first time that reconnection triggered by the localised
collapse of a 3D null point due to an external MHD wave involves a
self-generated oscillation, whereby the current sheet and outflow jets undergo
a reconnection reversal process during which back-pressure formation at the jet
heads acts to prise open the collapsed field before overshooting the
equilibrium into an opposite-polarity configuration. The discovery that
reconnection at fully 3D nulls can proceed naturally in a time-dependent and
periodic fashion is suggestive that oscillatory reconnection mechanisms may
play a role in explaining periodicity in astrophysical phenomena associated
with magnetic reconnection, such as the observed quasi-periodicity of solar and
stellar flare emission. Furthermore, we find a consequence of oscillatory
reconnection is the generation of a plethora of freely-propagating MHD waves
which escape the vicinity of the reconnection region
| 0 | 1 | 0 | 0 | 0 | 0 |
18,402 | Limits of Risk Predictability in a Cascading Alternating Renewal Process Model | Most risk analysis models systematically underestimate the probability and
impact of catastrophic events (e.g., economic crises, natural disasters, and
terrorism) by not taking into account interconnectivity and interdependence of
risks. To address this weakness, we propose the Cascading Alternating Renewal
Process (CARP) to forecast interconnected global risks. However, assessments of
the model's prediction precision are limited by lack of sufficient ground truth
data. Here, we establish prediction precision as a function of input data size
by using alternative long ground truth data generated by simulations of the
CARP model with known parameters. We illustrate the approach on a model of
fires in artificial cities assembled from basic city blocks with diverse
housing. The results confirm that parameter recovery variance exhibits power
law decay as a function of the length of available ground truth data. Using
CARP, we also demonstrate estimation using a disparate dataset that also has
dependencies: real-world prediction precision for the global risk model based
on the World Economic Forum Global Risk Report. We conclude that the CARP model
is an efficient method for predicting catastrophic cascading events with
potential applications to emerging local and global interconnected risks.
| 1 | 1 | 0 | 0 | 0 | 0 |
18,403 | Self-contracted curves have finite length | A curve $\theta$: $I\to E$ in a metric space $E$ equipped with the distance
$d$, where $I\subset \R$ is a (possibly unbounded) interval, is called
self-contracted, if for any triple of instances of time $\{t_i\}_{i=1}^3\subset
I$ with $t_1\leq t_2\leq t_3$ one has $d(\theta(t_3),\theta(t_2))\leq
d(\theta(t_3),\theta(t_1))$. We prove that if $E$ is a finite-dimensional
normed space with an arbitrary norm, the trace of $\theta$ is bounded, then
$\theta$ has finite length, i.e. is rectifiable, thus answering positively the
question raised in~\cite{Lemenant16sc-rectif}.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,404 | Unsupervised robust nonparametric learning of hidden community properties | We consider learning of fundamental properties of communities in large noisy
networks, in the prototypical situation where the nodes or users are split into
two classes according to a binary property, e.g., according to their opinions
or preferences on a topic. For learning these properties, we propose a
nonparametric, unsupervised, and scalable graph scan procedure that is, in
addition, robust against a class of powerful adversaries. In our setup, one of
the communities can fall under the influence of a knowledgeable adversarial
leader, who knows the full network structure, has unlimited computational
resources and can completely foresee our planned actions on the network. We
prove strong consistency of our results in this setup with minimal assumptions.
In particular, the learning procedure estimates the baseline activity of normal
users asymptotically correctly with probability 1; the only assumption being
the existence of a single implicit community of asymptotically negligible
logarithmic size. We provide experiments on real and synthetic data to
illustrate the performance of our method, including examples with adversaries.
| 1 | 0 | 0 | 1 | 0 | 0 |
18,405 | OPEB: Open Physical Environment Benchmark for Artificial Intelligence | Artificial Intelligence methods to solve continuous- control tasks have made
significant progress in recent years. However, these algorithms have important
limitations and still need significant improvement to be used in industry and
real- world applications. This means that this area is still in an active
research phase. To involve a large number of research groups, standard
benchmarks are needed to evaluate and compare proposed algorithms. In this
paper, we propose a physical environment benchmark framework to facilitate
collaborative research in this area by enabling different research groups to
integrate their designed benchmarks in a unified cloud-based repository and
also share their actual implemented benchmarks via the cloud. We demonstrate
the proposed framework using an actual implementation of the classical
mountain-car example and present the results obtained using a Reinforcement
Learning algorithm.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,406 | The First Measurement of the $2^{3}S_{1} \rightarrow 3^{3}P - 2^{3}P$ Tune-Out Wavelength in He* | The workhorse of atomic physics: quantum electrodynamics is one of the best
tested theories in physics. However recent discrepancies have shed doubt on its
accuracy for complex atomic systems. To facilitate the development of the
theory further we aim to measure transition dipole matrix elements of
metastable helium (He*) (the ideal 3 body test-bed) to the highest accuracy
thus far. We have undertaken a measurement of the `tune-out wavelength' which
occurs when the contributions to the dynamic polarizability from all atomic
transitions sum to zero; thus illuminating an atom with this wavelength of
light then produces no net energy shift. This provides a strict constraint on
the transition dipole matrix elements without the complication and inaccuracy
of other methods.
Using a novel atom-laser based technique we have made the first measurement
of the the tune-out wavelength in metastable helium between the
$3^{3}P_{1,2,3}$ and $2^{3}P_{1,2,3}$ states at 413.07(2)nm which compares well
with the predicted value\cite{Mitroy2013} of 413.02(9). We have additionally
developed many of the methods necessary to improve this measurement to the
100fm level of accuracy where it will form the most accurate determination of
transition rate information ever made in He* and provide a stringent test for
atomic QED simulations. We believe this measurement to be one of the most
sensitive ever made of an optical dipole potential, able to detect changes in
potentials of $\sim200pK$ and is widely applicable to other species and areas
of atom optics.
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18,407 | WheelCon: A wheel control-based gaming platform for studying human sensorimotor control | Feedback control theory has been extensively implemented to theoretically
model human sensorimotor control. However, experimental platforms capable of
manipulating important components of multiple feedback loops lack development.
This paper describes the WheelCon, which is an open source platform aimed at
resolving such insufficiencies. WheelCon enables safely simulation of the
canonical sensorimotor task such as riding a mountain bike down a steep,
twisting, bumpy trail etc., with provided only a computer, standard display,
and an inexpensive gaming steering wheel with a force feedback motor. The
platform provides flexibility, as will be demonstrated in the demos provided,
so that researchers may manipulate the disturbances, delay, and quantization
(data rate) in the layered feedback loops, including a high-level advanced plan
layer and a low-level delayed reflex layer. In this paper, we illustrate
WheelCon's graphical user interface (GUI), the input and output of existing
demos, and how to design new games. In addition, we present the basic feedback
model, and we show the testing results from our demo games which align well
with prediction from the model. In short, the platform is featured as cheap,
simple to use, and flexible to program for effective sensorimotor neuroscience
research and control engineering education.
| 0 | 0 | 0 | 0 | 1 | 0 |
18,408 | Depression and Self-Harm Risk Assessment in Online Forums | Users suffering from mental health conditions often turn to online resources
for support, including specialized online support communities or general
communities such as Twitter and Reddit. In this work, we present a neural
framework for supporting and studying users in both types of communities. We
propose methods for identifying posts in support communities that may indicate
a risk of self-harm, and demonstrate that our approach outperforms strong
previously proposed methods for identifying such posts. Self-harm is closely
related to depression, which makes identifying depressed users on general
forums a crucial related task. We introduce a large-scale general forum dataset
("RSDD") consisting of users with self-reported depression diagnoses matched
with control users. We show how our method can be applied to effectively
identify depressed users from their use of language alone. We demonstrate that
our method outperforms strong baselines on this general forum dataset.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,409 | Quantum dilogarithm identities for the square product of A-type Dynkin quivers | The famous pentagon identity for quantum dilogarithms has a generalization
for every Dynkin quiver, due to Reineke. A more advanced generalization is
associated with a pair of alternating Dynkin quivers, due to Keller. The
description and proof of Keller's identities involves cluster algebras and
cluster categories, and the statement of the identity is implicit. In this
paper we describe Keller's identities explicitly, and prove them by a dimension
counting argument. Namely, we consider quiver representations
$\boldsymbol{\mathrm{Rep}}_\gamma$ together with a superpotential function
$W_\gamma$, and calculate the Betti numbers of the equivariant $W_\gamma$ rapid
decay cohomology algebra of $\boldsymbol{\mathrm{Rep}}_\gamma$ in two different
ways corresponding to two natural stratifications of
$\boldsymbol{\mathrm{Rep}}_\gamma$. This approach is suggested by Kontsevich
and Soibelman in relation with the Cohomological Hall Algebra of quivers, and
the associated Donaldson-Thomas invariants.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,410 | A Probabilistic Linear Genetic Programming with Stochastic Context-Free Grammar for solving Symbolic Regression problems | Traditional Linear Genetic Programming (LGP) algorithms are based only on the
selection mechanism to guide the search. Genetic operators combine or mutate
random portions of the individuals, without knowing if the result will lead to
a fitter individual. Probabilistic Model Building Genetic Programming (PMB-GP)
methods were proposed to overcome this issue through a probability model that
captures the structure of the fit individuals and use it to sample new
individuals. This work proposes the use of LGP with a Stochastic Context-Free
Grammar (SCFG), that has a probability distribution that is updated according
to selected individuals. We proposed a method for adapting the grammar into the
linear representation of LGP. Tests performed with the proposed probabilistic
method, and with two hybrid approaches, on several symbolic regression
benchmark problems show that the results are statistically better than the
obtained by the traditional LGP.
| 1 | 0 | 0 | 1 | 0 | 0 |
18,411 | Trace-free ${\rm SL}(2,\mathbb{C})$-representations of arborescent links | Given a link $L\subset S^3$, a representation $\pi_1(S^3-L)\to{\rm
SL}(2,\mathbb{C})$ is {\it trace-free} if it sends each meridian to an element
with trace zero. We present a method for completely determining trace-free
${\rm SL}(2,\mathbb{C})$-representations for arborescent links. Concrete
computations are done for a class of 3-bridge arborescent links.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,412 | Algorithms for Weighted Sums of Squares Decomposition of Non-negative Univariate Polynomials | It is well-known that every non-negative univariate real polynomial can be
written as the sum of two polynomial squares with real coefficients. When one
allows a weighted sum of finitely many squares instead of a sum of two squares,
then one can choose all coefficients in the representation to lie in the field
generated by the coefficients of the polynomial.
In this article, we describe, analyze and compare both from the theoretical
and practical points of view, two algorithms computing such a weighted sums of
squares decomposition for univariate polynomials with rational coefficients.
The first algorithm, due to the third author relies on real root isolation,
quadratic approximations of positive polynomials and square-free decomposition
but its complexity was not analyzed. We provide bit complexity estimates, both
on runtime and output size of this algorithm. They are exponential in the
degree of the input univariate polynomial and linear in the maximum bitsize of
its complexity. This analysis is obtained using quantifier elimination and root
isolation bounds.
The second algorithm, due to Chevillard, Harrison, Joldes and Lauter, relies
on complex root isolation and square-free decomposition and has been introduced
for certifying positiveness of polynomials in the context of computer
arithmetics. Again, its complexity was not analyzed. We provide bit complexity
estimates, both on runtime and output size of this algorithm, which are
polynomial in the degree of the input polynomial and linear in the maximum
bitsize of its complexity. This analysis is obtained using Vieta's formula and
root isolation bounds.
Finally, we report on our implementations of both algorithms. While the
second algorithm is, as expected from the complexity result, more efficient on
most of examples, we exhibit families of non-negative polynomials for which the
first algorithm is better.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,413 | The Calkin algebra is $\aleph_1$-universal | We discuss the existence of (injectively) universal C*-algebras and prove
that all C*-algebras of density character $\aleph_1$ embed into the Calkin
algebra, $Q(H)$. Together with other results, this shows that each of the
following assertions is relatively consistent with ZFC: (i) $Q(H)$ is a
$2^{\aleph_0}$-universal C*-algebra. (ii) There exists a
$2^{\aleph_0}$-universal C*-algebra, but $Q(H)$ is not
$2^{\aleph_0}$-universal. (iii) A $2^{\aleph_0}$-universal C*-algebra does not
exist. We also prove that it is relatively consistent with ZFC that (iv) there
is no $\aleph_1$-universal nuclear C*-algebra, and that (v) there is no
$\aleph_1$-universal simple nuclear C*-algebra.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,414 | Learning Structured Semantic Embeddings for Visual Recognition | Numerous embedding models have been recently explored to incorporate semantic
knowledge into visual recognition. Existing methods typically focus on
minimizing the distance between the corresponding images and texts in the
embedding space but do not explicitly optimize the underlying structure. Our
key observation is that modeling the pairwise image-image relationship improves
the discrimination ability of the embedding model. In this paper, we propose
the structured discriminative and difference constraints to learn
visual-semantic embeddings. First, we exploit the discriminative constraints to
capture the intra- and inter-class relationships of image embeddings. The
discriminative constraints encourage separability for image instances of
different classes. Second, we align the difference vector between a pair of
image embeddings with that of the corresponding word embeddings. The difference
constraints help regularize image embeddings to preserve the semantic
relationships among word embeddings. Extensive evaluations demonstrate the
effectiveness of the proposed structured embeddings for single-label
classification, multi-label classification, and zero-shot recognition.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,415 | Estimators for a Class of Bivariate Measures of Concordance for Copulas | In the present paper we propose and study estimators for a wide class of
bivariate measures of concordance for copulas. These measures of concordance
are generated by a copula and generalize Spearman's rho and Gini's gamma. In
the case of Spearman's rho and Gini's gamma the estimators turn out to be the
usual sample versions of these measures of concordance.
| 0 | 0 | 1 | 1 | 0 | 0 |
18,416 | Variational treatment of electron-polyatomic molecule scattering calculations using adaptive overset grids | The Complex Kohn variational method for electron-polyatomic molecule
scattering is formulated using an overset grid representation of the scattering
wave function. The overset grid consists of a central grid and multiple dense,
atom-centered subgrids that allow the simultaneous spherical expansions of the
wave function about multiple centers. Scattering boundary conditions are
enforced by using a basis formed by the repeated application of the free
particle Green's function and potential, $\hat{G}^+_0\hat{V}$ on the overset
grid in a "Born-Arnoldi" solution of the working equations. The theory is shown
to be equivalent to a specific Padé approximant to the $T$-matrix, and has
rapid convergence properties, both in the number of numerical basis functions
employed and the number of partial waves employed in the spherical expansions.
The method is demonstrated in calculations on methane and CF$_4$ in the
static-exchange approximation, and compared in detail with calculations
performed with the numerical Schwinger variational approach based on single
center expansions. An efficient procedure for operating with the free-particle
Green's function and exchange operators (to which no approximation is made) is
also described.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,417 | Geometry of quantum dynamics in infinite dimension | We develop a geometric approach to quantum mechanics based on the concept of
the Tulczyjew triple. Our approach is genuinely infinite-dimensional and
including a Lagrangian formalism in which self-adjoint (Schroedinger) operators
are obtained as Lagrangian submanifolds associated with the Lagrangian. As a
byproduct we obtain also results concerning coadjoint orbits of the unitary
group in infinite dimension, embedding of the Hilbert projective space of pure
states in the unitary group, and an approach to self-adjoint extensions of
symmetric relations.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,418 | Canonical tilting relative generators | Given a relatively projective birational morphism $f\colon X\to Y$ of smooth
algebraic spaces with dimension of fibers bounded by 1, we construct tilting
relative (over $Y$) generators $T_{X,f}$ and $S_{X,f}$ in $\mathcal{D}^b(X)$.
We develop a piece of general theory of strict admissible lattice filtrations
in triangulated categories and show that $\mathcal{D}^b(X)$ has such a
filtration $\mathcal{L}$ where the lattice is the set of all birational
decompositions $f \colon X \xrightarrow{g} Z \xrightarrow{h} Y$ with smooth
$Z$. The $t$-structures related to $T_{X,f}$ and $S_{X,f}$ are proved to be
glued via filtrations left and right dual to $\mathcal{L}$. We realise all such
$Z$ as the fine moduli spaces of simple quotients of $\mathcal{O}_X$ in the
heart of the $t$-structure for which $S_{X,g}$ is a relative projective
generator over $Y$. This implements the program of interpreting relevant smooth
contractions of $X$ in terms of a suitable system of $t$-structures on
$\mathcal{D}^b(X)$.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,419 | Groupwise Structural Parcellation of the Cortex: A Sound Approach Based on Logistic Models | Current theories hold that brain function is highly related to long-range
physical connections through axonal bundles, namely extrinsic connectiv-ity.
However, obtaining a groupwise cortical parcellation based on extrinsic
connectivity remains challenging. Current parcellation methods are
compu-tationally expensive; need tuning of several parameters or rely on ad-hoc
constraints. Furthermore, none of these methods present a model for the
cortical extrinsic connectivity of the cortex. To tackle these problems, we
propose a parsimonious model for the extrinsic connectivity and an efficient
parceling technique based on clustering of tractograms. Our technique allows
the creation of single subject and groupwise parcellations of the whole cortex.
The parcellations obtained with our technique are in agreement with structural
and functional parcellations in the literature. In particular, the motor and
sensory cortex are subdivided in agreement with the human ho-munculus of
Penfield. We illustrate this by comparing our resulting parcels with the motor
strip mapping included in the Human Connectome Project data.
| 0 | 0 | 0 | 1 | 0 | 0 |
18,420 | Modeling Biological Problems in Computer Science: A Case Study in Genome Assembly | As computer scientists working in bioinformatics/computational biology, we
often face the challenge of coming up with an algorithm to answer a biological
question. This occurs in many areas, such as variant calling, alignment, and
assembly. In this tutorial, we use the example of the genome assembly problem
to demonstrate how to go from a question in the biological realm to a solution
in the computer science realm. We show the modeling process step-by-step,
including all the intermediate failed attempts.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,421 | MEC: Memory-efficient Convolution for Deep Neural Network | Convolution is a critical component in modern deep neural networks, thus
several algorithms for convolution have been developed. Direct convolution is
simple but suffers from poor performance. As an alternative, multiple indirect
methods have been proposed including im2col-based convolution, FFT-based
convolution, or Winograd-based algorithm. However, all these indirect methods
have high memory-overhead, which creates performance degradation and offers a
poor trade-off between performance and memory consumption. In this work, we
propose a memory-efficient convolution or MEC with compact lowering, which
reduces memory-overhead substantially and accelerates convolution process. MEC
lowers the input matrix in a simple yet efficient/compact way (i.e., much less
memory-overhead), and then executes multiple small matrix multiplications in
parallel to get convolution completed. Additionally, the reduced memory
footprint improves memory sub-system efficiency, improving performance. Our
experimental results show that MEC reduces memory consumption significantly
with good speedup on both mobile and server platforms, compared with other
indirect convolution algorithms.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,422 | On age of 6070 Rheinland and 54827 (2001 NQ8) asteroid pair | In this paper we present results of our studying of famous very young pair of
asteroids 6070 Rheinland and 54827 (2001 NQ8). We have done numeric integration
of orbits of pair with only planet perturbations and include Ceres and Vesta
effect. We have confirmed results of previous studying, obtained with different
integrators. And we confirm significant effect of Ceres and Vesta perturbation
on dynamic of this pair. We find that effect of other massive asteroids is
insignificant. According our results, more probable age of 6070 Rheinland and
54827 (2001 NQ8) pair is 16.2 kyrs. Our value of age is very close to most
recent age determination by Vokrouhlicky et al [12], obtained with different
method. After the compare our results, we can conclude, that non-gravitational
forces are small and large number of clones is not necessary in studying of
this pair. As an additional way of studying of close orbits dynamics, we
calculate relative velocity in pair during numeric integration. Normal
component of velocity show a very good convergence at epoch of closest
encounter in pair.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,423 | First-Order Reversal Curves of the Magnetostructural Phase Transition in FeTe | We apply the first-order reversal curve (FORC) method, borrowed from studies
of ferromagnetic materials, to the magneto-structural phase transition of FeTe.
FORC measurements reveal two features in the hysteretic phase transition, even
in samples where traditional temperature measurements display only a single
transition. For Fe1.13Te, the influence of magnetic field suggests that the
main feature is primarily structural while a smaller, slightly
higher-temperature transition is magnetic in origin. By contrast Fe1.03Te has a
single transition which shows a uniform response to magnetic field, indicating
a stronger coupling of the magnetic and structural phase transitions. We also
introduce uniaxial stress, which spreads the distribution width without
changing the underlying energy barrier of the transformation. The work shows
how FORC can help disentangle the roles of the magnetic and structural phase
transitions in FeTe.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,424 | Data Analytics on Online Labor Markets: Opportunities and Challenges | The data-driven economy has led to a significant shortage of data scientists.
To address this shortage, this study explores the prospects of outsourcing data
analysis tasks to freelancers available on online labor markets (OLMs) by
identifying the essential factors for this endeavor. Specifically, we explore
the skills required from freelancers, collect information about the skills
present on major OLMs, and identify the main hurdles for out-/crowd-sourcing
data analysis. Adopting a sequential mixed-method approach, we interviewed 20
data scientists and subsequently surveyed 80 respondents from OLMs. Besides
confirming the need for expected skills such as technical/mathematical
capabilities, it also identifies less known ones such as domain understanding,
an eye for aesthetic data visualization, good communication skills, and a
natural understanding of the possibilities/limitations of data analysis in
general. Finally, it elucidates obstacles for crowdsourcing like the
communication overhead, knowledge gaps, quality assurance, and data
confidentiality, which need to be mitigated.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,425 | Analyzing the Robustness of Nearest Neighbors to Adversarial Examples | Motivated by safety-critical applications, test-time attacks on classifiers
via adversarial examples has recently received a great deal of attention.
However, there is a general lack of understanding on why adversarial examples
arise; whether they originate due to inherent properties of data or due to lack
of training samples remains ill-understood. In this work, we introduce a
theoretical framework analogous to bias-variance theory for understanding these
effects.
We use our framework to analyze the robustness of a canonical non-parametric
classifier - the k-nearest neighbors. Our analysis shows that its robustness
properties depend critically on the value of k - the classifier may be
inherently non-robust for small k, but its robustness approaches that of the
Bayes Optimal classifier for fast-growing k. We propose a novel modified
1-nearest neighbor classifier, and guarantee its robustness in the large sample
limit. Our experiments suggest that this classifier may have good robustness
properties even for reasonable data set sizes.
| 1 | 0 | 0 | 1 | 0 | 0 |
18,426 | Non Uniform On Chip Power Delivery Network Synthesis Methodology | In this paper, we proposed a non-uniform power delivery network (PDN)
synthesis methodology. It first constructs initial PDN using uniform approach.
Then preliminary power integrity analysis is performed to derive IR-safe
candidate window. Congestion map is obtained based global route congestion
estimation. A self-adaptive non-uniform PDN synthesis is then performed to
globally and locally optimize PDN over selected regions. The PDN synthesis is
congestion-driven and IR- guarded. Experimental results show significant timing
important in trade-off small PDN length reduction with no EM/IR impact. We
further explored potential power savings using our non-uniform PDN synthesis
methodology.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,427 | Translating ceRNA susceptibilities into correlation functions | Competition to bind microRNAs induces an effective positive crosstalk between
their targets, therefore known as `competing endogenous RNAs' or ceRNAs. While
such an effect is known to play a significant role in specific conditions,
estimating its strength from data and, experimentally, in physiological
conditions appears to be far from simple. Here we show that the susceptibility
of ceRNAs to different types of perturbations affecting their competitors (and
hence their tendency to crosstalk) can be encoded in quantities as intuitive
and as simple to measure as correlation functions. We confirm this scenario by
extensive numerical simulations and validate it by re-analyzing PTEN's
crosstalk pattern from TCGA breast cancer dataset. These results clarify the
links between different quantities used to estimate the intensity of ceRNA
crosstalk and provide new keys to analyze transcriptional datasets and
effectively probe ceRNA networks in silico.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,428 | Impact of energetic particle orbits on long range frequency chirping of BGK modes | Long range frequency chirping of Bernstein-Greene-Kruskal modes, whose
existence is determined by the fast particles, is investigated in cases where
these particles do not move freely and their motion is bounded to restricted
orbits. An equilibrium oscillating potential, which creates different orbit
topologies of energetic particles, is included into the bump-on-tail
instability problem of a plasma wave. With respect to fast particles dynamics,
the extended model captures the range of particles motion (trapped/passing)
with energy and thus represents a more realistic 1D picture of the long range
sweeping events observed for weakly damped modes, e.g. global Alfven
eigenmodes, in tokamaks. The Poisson equation is solved numerically along with
bounce averaging the Vlasov equation in the adiabatic regime. We demonstrate
that the shape and the saturation amplitude of the nonlinear mode structure
depends not only on the amount of deviation from the initial eigenfrequency but
also on the initial energy of the resonant electrons in the equilibrium
potential. Similarly, the results reveal that the resonant electrons following
different equilibrium orbits in the electrostatic potential lead to different
rates of frequency evolution. As compared to the previous model [Breizman B.N.
2010 Nucl. Fusion 50 084014], it is shown that the frequency sweeps with lower
rates. The additional physics included in the model enables a more complete 1D
description of the range of phenomena observed in experiments.
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18,429 | An Executable Specification of Typing Rules for Extensible Records based on Row Polymorphism | Type inference is an application domain that is a natural fit for logic
programming (LP). LP systems natively support unification, which serves as a
basic building block of typical type inference algorithms. In particular,
polymorphic type inference in the Hindley--Milner type system (HM) can be
succinctly specified and executed in Prolog. In our previous work, we have
demonstrated that more advanced features of parametric polymorphism beyond HM,
such as type-constructor polymorphism and kind polymorphism, can be similarly
specified in Prolog. Here, we demonstrate a specification for records, which is
one of the most widely supported compound data structures in real-world
programming languages, and discuss the advantages and limitations of Prolog as
a specification language for type systems. Record types are specified as
order-irrelevant collections of named fields mapped to their corresponding
types. In addition, an open-ended collection is used to support row
polymorphism for record types to be extensible.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,430 | Seasonal Stochastic Volatility and the Samuelson Effect in Agricultural Futures Markets | We introduce a multi-factor stochastic volatility model for commodities that
incorporates seasonality and the Samuelson effect. Conditions on the seasonal
term under which the corresponding volatility factor is well-defined are given,
and five different specifications of the seasonality pattern are proposed. We
calculate the joint characteristic function of two futures prices for different
maturities in the risk-neutral measure. The model is then presented under the
physical measure, and its state-space representation is derived, in order to
estimate the parameters with the Kalman filter for time series of corn, cotton,
soybean, sugar and wheat futures from 2007 to 2017. The seasonal model
significantly outperforms the nested non-seasonal model in all five markets,
and we show which seasonality patterns are particularly well-suited in each
case. We also confirm the importance of correctly modelling the Samuelson
effect in order to account for futures with different maturities. Our results
are clearly confirmed in a robustness check carried out with an alternative
dataset of constant maturity futures for the same agricultural markets.
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18,431 | A Computational Model of a Single-Photon Avalanche Diode Sensor for Transient Imaging | Single-Photon Avalanche Diodes (SPAD) are affordable photodetectors, capable
to collect extremely fast low-energy events, due to their single-photon
sensibility. This makes them very suitable for time-of-flight-based range
imaging systems, allowing to reduce costs and power requirements, without
sacrifizing much temporal resolution. In this work we describe a computational
model to simulate the behaviour of SPAD sensors, aiming to provide a realistic
camera model for time-resolved light transport simulation, with applications on
prototyping new reconstructions techniques based on SPAD time-of-flight data.
Our model accounts for the major effects of the sensor on the incoming signal.
We compare our model against real-world measurements, and apply it to a variety
of scenarios, including complex multiply-scattered light transport.
| 1 | 1 | 0 | 0 | 0 | 0 |
18,432 | On Certain Tilting Modules for SL2 | We give a complete picture of when the tensor product of an induced module
and a Weyl module is a tilting module for the algebraic group $SL_2$ over an
algebraically closed field of characteristic $p$. Whilst the result is
recursive by nature, we give an explicit statement in terms of the $p$-adic
expansions of the highest weight of each module.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,433 | First-order Methods Almost Always Avoid Saddle Points | We establish that first-order methods avoid saddle points for almost all
initializations. Our results apply to a wide variety of first-order methods,
including gradient descent, block coordinate descent, mirror descent and
variants thereof. The connecting thread is that such algorithms can be studied
from a dynamical systems perspective in which appropriate instantiations of the
Stable Manifold Theorem allow for a global stability analysis. Thus, neither
access to second-order derivative information nor randomness beyond
initialization is necessary to provably avoid saddle points.
| 1 | 0 | 0 | 1 | 0 | 0 |
18,434 | Faster Algorithms for Computing Maximal 2-Connected Subgraphs in Sparse Directed Graphs | Connectivity related concepts are of fundamental interest in graph theory.
The area has received extensive attention over four decades, but many problems
remain unsolved, especially for directed graphs. A directed graph is
2-edge-connected (resp., 2-vertex-connected) if the removal of any edge (resp.,
vertex) leaves the graph strongly connected. In this paper we present improved
algorithms for computing the maximal 2-edge- and 2-vertex-connected subgraphs
of a given directed graph. These problems were first studied more than 35 years
ago, with $\widetilde{O}(mn)$ time algorithms for graphs with m edges and n
vertices being known since the late 1980s. In contrast, the same problems for
undirected graphs are known to be solvable in linear time. Henzinger et al.
[ICALP 2015] recently introduced $O(n^2)$ time algorithms for the directed
case, thus improving the running times for dense graphs. Our new algorithms run
in time $O(m^{3/2})$, which further improves the running times for sparse
graphs.
The notion of 2-connectivity naturally generalizes to k-connectivity for
$k>2$. For constant values of k, we extend one of our algorithms to compute the
maximal k-edge-connected in time $O(m^{3/2} \log{n})$, improving again for
sparse graphs the best known algorithm by Henzinger et al. [ICALP 2015] that
runs in $O(n^2 \log n)$ time.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,435 | Summable Reparameterizations of Wasserstein Critics in the One-Dimensional Setting | Generative adversarial networks (GANs) are an exciting alternative to
algorithms for solving density estimation problems---using data to assess how
likely samples are to be drawn from the same distribution. Instead of
explicitly computing these probabilities, GANs learn a generator that can match
the given probabilistic source. This paper looks particularly at this matching
capability in the context of problems with one-dimensional outputs. We identify
a class of function decompositions with properties that make them well suited
to the critic role in a leading approach to GANs known as Wasserstein GANs. We
show that Taylor and Fourier series decompositions belong to our class, provide
examples of these critics outperforming standard GAN approaches, and suggest
how they can be scaled to higher dimensional problems in the future.
| 1 | 0 | 0 | 1 | 0 | 0 |
18,436 | Fingering instabilities and pattern formation in a two-component dipolar Bose-Einstein condensate | We study fingering instabilities and pattern formation at the interface of an
oppositely polarized two-component Bose-Einstein condensate with strong
dipole-dipole interactions in three dimensions. It is shown that the rotational
symmetry is spontaneously broken by fingering instability when the
dipole-dipole interactions are strengthened. Frog-shaped and mushroom-shaped
patterns emerge during the dynamics due to the dipolar interactions. We also
demonstrate the spontaneous density modulation and domain growth of a
two-component dipolar BEC in the dynamics. Bogoliubov analyses in the
two-dimensional approximation are performed, and the characteristic lengths of
the domains are estimated analytically. Patterns resembling those in magnetic
classical fluids are modulated when the number ratio of atoms, the trap ratio
of the external potential, or tilted polarization with respect to the z
direction is varied.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,437 | Fast Information-theoretic Bayesian Optimisation | Information-theoretic Bayesian optimisation techniques have demonstrated
state-of-the-art performance in tackling important global optimisation
problems. However, current information-theoretic approaches require many
approximations in implementation, introduce often-prohibitive computational
overhead and limit the choice of kernels available to model the objective. We
develop a fast information-theoretic Bayesian Optimisation method, FITBO, that
avoids the need for sampling the global minimiser, thus significantly reducing
computational overhead. Moreover, in comparison with existing approaches, our
method faces fewer constraints on kernel choice and enjoys the merits of
dealing with the output space. We demonstrate empirically that FITBO inherits
the performance associated with information-theoretic Bayesian optimisation,
while being even faster than simpler Bayesian optimisation approaches, such as
Expected Improvement.
| 0 | 0 | 0 | 1 | 0 | 0 |
18,438 | ExoMol molecular line lists XX: a comprehensive line list for H$_3^+$ | H$_3^+$ is a ubiquitous and important astronomical species whose spectrum has
been observed in the interstellar medium, planets and tentatively in the
remnants of supernova SN1897a. Its role as a cooler is important for gas giant
planets and exoplanets, and possibly the early Universe. All this makes the
spectral properties, cooling function and partition function of H$_3^+$ key
parameters for astronomical models and analysis. A new high-accuracy, very
extensive line list for H$_3^+$ called MiZATeP was computed as part of the
ExoMol project alongside a temperature-dependent cooling function and partition
function as well as lifetimes for %individual excited states. These data are
made available in electronic form as supplementary data to this article and at
this http URL
| 0 | 1 | 0 | 0 | 0 | 0 |
18,439 | Robust and Sparse Regression in GLM by Stochastic Optimization | The generalized linear model (GLM) plays a key role in regression analyses.
In high-dimensional data, the sparse GLM has been used but it is not robust
against outliers. Recently, the robust methods have been proposed for the
specific example of the sparse GLM. Among them, we focus on the robust and
sparse linear regression based on the $\gamma$-divergence. The estimator of the
$\gamma$-divergence has strong robustness under heavy contamination. In this
paper, we extend the robust and sparse linear regression based on the
$\gamma$-divergence to the robust and sparse GLM based on the
$\gamma$-divergence with a stochastic optimization approach in order to obtain
the estimate. We adopt the randomized stochastic projected gradient descent as
a stochastic optimization approach and extend the established convergence
property to the classical first-order necessary condition. By virtue of the
stochastic optimization approach, we can efficiently estimate parameters for
very large problems. Particularly, we show the linear regression, logistic
regression and Poisson regression with $L_1$ regularization in detail as
specific examples of robust and sparse GLM. In numerical experiments and real
data analysis, the proposed method outperformed comparative methods.
| 0 | 0 | 0 | 1 | 0 | 0 |
18,440 | A Hint-Based Technique for System Level Model-Based Test Case Prioritization | Test Case Prioritization (TCP) techniques aim at proposing new test case
execution orders to favor the achievement of certain testing goal, such as
fault detection. Current TCP research focus mainly on code-based regression
testing; however in the Model-Based Testing (MBT) context, we still need more
investigation. General TCP techniques do not use historical information, since
this information is often unavailable. Therefore, techniques use different
sources of information to guide prioritization. We propose a novel technique
that guides its operation using provided hints, the Hint-Based Adaptive Random
Prioritization - HARP. Hints are indications or suggestions provided by
developers about error-prone functionalities. As hints may be hard to collect
automatically, we also propose an approach of collecting them. To validate our
findings, we performed an experiment measuring the effect of introducing hints
to HARP. It shows that hints can improve HARP's performance comparing to its
baseline. Then, we investigated the ability of developers/managers to provide
good hints and used them in a case study. This analysis showed that developers
and managers are able to provide useful hints, which improves HARP's fault
detection comparing to its baseline. Nonetheless, the provided hints should be
consensual among the development team members.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,441 | Control of birhythmicity: A self-feedback approach | Birhythmicity occurs in many natural and artificial systems. In this paper we
propose a self-feedback scheme to control birhythmicity. To establish the
efficacy and generality of the proposed control scheme, we apply it on three
birhythmic oscillators from diverse fields of natural science, namely, an
energy harvesting system, the p53-Mdm2 network for protein genesis (the OAK
model) and a glycolysis model (modified Decroly-Goldbeter model). Using the
harmonic decomposition technique and energy balance method we derive the
analytical conditions for the control of birhythmicity. A detailed numerical
bifurcation analysis in the parameter space establishes that the control scheme
is capable of eliminating birhythmicity and it can also induce transitions
between different forms of bistability. As the proposed control scheme is quite
general, it can be applied for control of several real systems, particularly in
biochemical and engineering systems.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,442 | Forecasting the magnitude and onset of El Nino based on climate network | El Nino is probably the most influential climate phenomenon on interannual
time scales. It affects the global climate system and is associated with
natural disasters and serious consequences in many aspects of human life.
However, the forecasting of the onset and in particular the magnitude of El
Nino are still not accurate, at least more than half a year in advance. Here,
we introduce a new forecasting index based on network links representing the
similarity of low frequency temporal temperature anomaly variations between
different sites in the El Nino 3.4 region. We find that significant upward
trends and peaks in this index forecast with high accuracy both the onset and
magnitude of El Nino approximately 1 year ahead. The forecasting procedure we
developed improves in particular the prediction of the magnitude of El Nino and
is validated based on several, up to more than a century long, datasets.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,443 | Weighted $1\times1$ cut-and-project sets in bounded distance to a lattice | Recent results of Grepstad and Lev are used to show that weighted
cut-and-project sets with one-dimensional physical space and one-dimensional
internal space are bounded distance equivalent to some lattice if the weight
function $h$ is continuous on the internal space, and if $h$ is either
piecewise linear, or twice differentiable with bounded curvature.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,444 | On Ordinal Invariants in Well Quasi Orders and Finite Antichain Orders | We investigate the ordinal invariants height, length, and width of well quasi
orders (WQO), with particular emphasis on width, an invariant of interest for
the larger class of orders with finite antichain condition (FAC). We show that
the width in the class of FAC orders is completely determined by the width in
the class of WQOs, in the sense that if we know how to calculate the width of
any WQO then we have a procedure to calculate the width of any given FAC order.
We show how the width of WQO orders obtained via some classical constructions
can sometimes be computed in a compositional way. In particular, this allows
proving that every ordinal can be obtained as the width of some WQO poset. One
of the difficult questions is to give a complete formula for the width of
Cartesian products of WQOs. Even the width of the product of two ordinals is
only known through a complex recursive formula. Although we have not given a
complete answer to this question we have advanced the state of knowledge by
considering some more complex special cases and in particular by calculating
the width of certain products containing three factors. In the course of
writing the paper we have discovered that some of the relevant literature was
written on cross-purposes and some of the notions re-discovered several times.
Therefore we also use the occasion to give a unified presentation of the known
results.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,445 | Indices in XML Databases | With XML becoming a standard for business information representation and
exchange, stor-ing, indexing, and querying XML documents have rapidly become
major issues in database research. In this context, query processing and
optimization are primordial, native-XML data-bases not being mature yet. Data
structures such as indices, which help enhance performances substantially, are
extensively researched, especially since XML data bear numerous specifici-ties
with respect to relational data. In this paper, we survey state-of-the-art XML
indices and discuss the main issues, tradeoffs and future trends in XML
indexing. We also present an in-dex that we specifically designed for the
particular architecture of XML data warehouses.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,446 | Kernel theorems for modulation spaces | We deal with kernel theorems for modulation spaces. We completely
characterize the continuity of a linear operator on the modulation spaces $M^p$
for every $1\leq p\leq\infty$, by the membership of its kernel to (mixed)
modulation spaces. Whereas Feichtinger's kernel theorem (which we recapture as
a special case) is the modulation space counterpart of Schwartz' kernel theorem
for temperate distributions, our results do not have a couterpart in
distribution theory. This reveals the superiority, in some respects, of the
modulation space formalism upon distribution theory, as already emphasized in
Feichtinger's manifesto for a post-modern harmonic analysis, tailored to the
needs of mathematical signal processing. The proof uses in an essential way a
discretization of the problem by means of Gabor frames. We also show the
equivalence of the operator norm and the modulation space norm of the
corresponding kernel. For operators acting on $M^{p,q}$ a similar
characterization is not expected, but sufficient conditions for boundedness can
be sated in the same spirit.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,447 | On the Performance of Network Parallel Training in Artificial Neural Networks | Artificial Neural Networks (ANNs) have received increasing attention in
recent years with applications that span a wide range of disciplines including
vital domains such as medicine, network security and autonomous transportation.
However, neural network architectures are becoming increasingly complex and
with an increasing need to obtain real-time results from such models, it has
become pivotal to use parallelization as a mechanism for speeding up network
training and deployment. In this work we propose an implementation of Network
Parallel Training through Cannon's Algorithm for matrix multiplication. We show
that increasing the number of processes speeds up training until the point
where process communication costs become prohibitive; this point varies by
network complexity. We also show through empirical efficiency calculations that
the speedup obtained is superlinear.
| 1 | 0 | 0 | 1 | 0 | 0 |
18,448 | Fair Forests: Regularized Tree Induction to Minimize Model Bias | The potential lack of fairness in the outputs of machine learning algorithms
has recently gained attention both within the research community as well as in
society more broadly. Surprisingly, there is no prior work developing
tree-induction algorithms for building fair decision trees or fair random
forests. These methods have widespread popularity as they are one of the few to
be simultaneously interpretable, non-linear, and easy-to-use. In this paper we
develop, to our knowledge, the first technique for the induction of fair
decision trees. We show that our "Fair Forest" retains the benefits of the
tree-based approach, while providing both greater accuracy and fairness than
other alternatives, for both "group fairness" and "individual fairness.'" We
also introduce new measures for fairness which are able to handle multinomial
and continues attributes as well as regression problems, as opposed to binary
attributes and labels only. Finally, we demonstrate a new, more robust
evaluation procedure for algorithms that considers the dataset in its entirety
rather than only a specific protected attribute.
| 1 | 0 | 0 | 1 | 0 | 0 |
18,449 | Discretization of SU(2) and the Orthogonal Group Using Icosahedral Symmetries and the Golden Numbers | The vertices of the four dimensional $120$-cell form a non-crystallographic
root system whose corresponding symmetry group is the Coxeter group $H_{4}$.
There are two special coordinate representations of this root system in which
they and their corresponding Coxeter groups involve only rational numbers and
the golden ratio $\tau$. The two are related by the conjugation $\tau
\mapsto\tau' = -1/\tau$. This paper investigates what happens when the two root
systems are combined and the group generated by both versions of $H_{4}$ is
allowed to operate on them. The result is a new, but infinite, `root system'
$\Sigma$ which itself turns out to have a natural structure of the unitary
group $SU(2,\mathcal R)$ over the ring $\mathcal R = \mathbb
Z[\frac{1}{2},\tau]$ (called here golden numbers). Acting upon it is the
naturally associated infinite reflection group $H^{\infty}$, which we prove is
of index $2$ in the orthogonal group $O(4,\mathcal R)$. The paper makes
extensive use of the quaternions over $\mathcal R$ and leads to highly
structured discretized filtration of $SU(2)$. We use this to offer a simple and
effective way to approximate any element of $SU(2)$ to any degree of accuracy
required using the repeated actions of just five fixed reflections, a process
that may find application in computational methods in quantum mechanics.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,450 | Raman spectra of crystalline secondary amides | The study of single-crystal Raman spectra of a series of crystalline
secondary amides (acetanilide, methacetin, phenacetine, orthorhombic and
monoclinic polymorphs of paracetamol) as well as simple amides formanilide and
benzanilide in the temperature range 5-300 K was carried out. The series of
compounds with the same molecular fragment, i.e. acetamide group, can serve as
a model system to study the interrelation between the latter and the properties
of the intermolecular "peptide-type" NH...O=C hydrogen bonds. For all the
"acetamide family" of compounds, similar changes in the Raman spectra were
observed on cooling the samples: an appearance of new Amide I(-) and Amide I(+)
bands that are red and blue shifted respectively from the conventional Amide I
band by around of 5-10 inverse centimeters. An appropriated changes in the same
temperature range were observed for the N-H out-of-plane bending (Amide V) and
N-H stretching vibrations of the N-H...O=C hydrogen bond. All the spectral
changes on cooling the samples can be supposed to result from delocalization of
the Amide I and N-H modes and appearance of dynamical splitting at low
temperature.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,451 | Open-World Visual Recognition Using Knowledge Graphs | In a real-world setting, visual recognition systems can be brought to make
predictions for images belonging to previously unknown class labels. In order
to make semantically meaningful predictions for such inputs, we propose a
two-step approach that utilizes information from knowledge graphs. First, a
knowledge-graph representation is learned to embed a large set of entities into
a semantic space. Second, an image representation is learned to embed images
into the same space. Under this setup, we are able to predict structured
properties in the form of relationship triples for any open-world image. This
is true even when a set of labels has been omitted from the training protocols
of both the knowledge graph and image embeddings. Furthermore, we append this
learning framework with appropriate smoothness constraints and show how prior
knowledge can be incorporated into the model. Both these improvements combined
increase performance for visual recognition by a factor of six compared to our
baseline. Finally, we propose a new, extended dataset which we use for
experiments.
| 1 | 0 | 0 | 1 | 0 | 0 |
18,452 | Mass-Imbalanced Ionic Hubbard Chain | A repulsive Hubbard model with both spin-asymmetric hopping (${t_\uparrow\neq
t_\downarrow}$) and a staggered potential (of strength $\Delta$) is studied in
one dimension. The model is a compound of the mass-imbalanced (${t_\uparrow\neq
t_\downarrow}$, ${\Delta=0}$) and ionic (${t_\uparrow = t_\downarrow}$,
${\Delta>0}$) Hubbard models, and may be realized by cold atoms in engineered
optical lattices. We use mostly mean-field theory to determine the phases and
phase transitions in the ground state for a half-filled band (one particle per
site). We find that a period-two modulation of the particle (or charge) density
and an alternating spin density coexist for arbitrary Hubbard interaction
strength, ${U\geqslant 0}$. The amplitude of the charge modulation is largest
at ${U=0}$, decreases with increasing $U$ and tends to zero for
${U\rightarrow\infty}$. The amplitude for spin alternation increases with $U$
and tends to saturation for ${U\rightarrow\infty}$. Charge order dominates
below a critical value $U_c$, whereas magnetic order dominates above. The
mean-field Hamiltonian has two gap parameters, $\Delta_\uparrow$ and
$\Delta_\downarrow$, which have to be determined self-consistently. For
${U<U_c}$ both parameters are positive, for ${U>U_c}$ they have different
signs, and for ${U=U_c}$ one gap parameter jumps from a positive to a negative
value. The weakly first-order phase transition at $U_c$ can be interpreted in
terms of an avoided criticality (or metallicity). The system is reluctant to
restore a symmetry that has been broken explicitly.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,453 | Optical properties of Xe color centers in diamond | Optical properties of color centers in diamond have been the subject of
intense research due to their promising applications in quantum photonics. In
this work we study the optical properties of Xe related color centers implanted
into nitrogen rich (type IIA) and an ultrapure, electronic grade diamond. The
Xe defect has two zero phonon lines at ~ 794 and 811 nm, which can be
effectively excited using both green and red excitation, however, its emission
in the nitrogen rich diamond is brighter. Near resonant excitation is performed
at cryogenic temperatures and luminescence is probed under strong magnetic
field. Our results are important towards the understanding of the Xe related
defect and other near infrared color centers in diamond.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,454 | Julian Ernst Besag, 26 March 1945 -- 6 August 2010, a biographical memoir | Julian Besag was an outstanding statistical scientist, distinguished for his
pioneering work on the statistical theory and analysis of spatial processes,
especially conditional lattice systems. His work has been seminal in
statistical developments over the last several decades ranging from image
analysis to Markov chain Monte Carlo methods. He clarified the role of
auto-logistic and auto-normal models as instances of Markov random fields and
paved the way for their use in diverse applications. Later work included
investigations into the efficacy of nearest neighbour models to accommodate
spatial dependence in the analysis of data from agricultural field trials,
image restoration from noisy data, and texture generation using lattice models.
| 0 | 0 | 0 | 1 | 0 | 0 |
18,455 | Wake fields in a rectangular dielectric-lined accelerating structure with transversal isotropic loading | Dielectric lined waveguides are under extensive study as accelerating
structures that can be excited by electron beams. Rectangular dielectric
structures are used both in proof of principle experiments for new accelerating
schemes and for studying the electronic properties of the structure loading
material. Analysis of Cherenkov radiation generated by high current
relativistic electron bunch passing through a rectangular waveguide with
transversal isotropic dielectric loading has been carried out. Some of the
materials used for the waveguide loading of accelerating structures (sapphire,
ceramic films) possess significant anisotropic properties. In turn, it can
influence excitation parameters of the wakefields generated by an electron
beam. General solutions for the fields generated by a relativistic electron
beam propagating in a rectangular dielectric waveguide have been derived using
the orthogonal eigenmode decomposition method for the transverse operators of
the Helmholtz equation. The analytical expression for the combined Cherenkov
and Coulomb fields in terms of a superposition of LSM and LSE-modes of
rectangular waveguide with transversal isotropic dielectric loading has been
obtained. Numerical modelling of the longitudinal and transverse (deflecting)
wakefields has been carried out as well. It is shown that the dielectric
anisotropy causes frequency shift in comparison to the dielectric-lined
waveguide with the isotropic dielectric loading.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,456 | Hyperfine Structure of the $B^3Π_1$ State and Predictions of Optical Cycling Behavior in the $X\rightarrow B$ transition of TlF | The rotational and hyperfine spectrum of the $X^1\Sigma^+ \rightarrow
B^3\Pi_1$ transition in TlF molecules was measured using laser-induced
fluorescence from both a thermal and a cryogenic molecular beam. Rotational and
hyperfine constants for the $B$ state are obtained. The large magnetic
hyperfine interaction of the Tl nuclear spin leads to significant mixing of the
lowest $B$ state rotational levels. Updated, more precise measurements of the
$B\rightarrow X$ vibrational branching fractions are also presented. The
combined rovibrational branching fractions allow for the prediction of the
number of photons that can be scattered in a given TlF optical cycling scheme.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,457 | Prevalence of DNSSEC for hospital websites in Illinois | The domain name system translates human friendly web addresses to a computer
readable internet protocol address. This basic infrastructure is insecure and
can be manipulated. Deployment of technology to secure the DNS system has been
slow, reaching about 20% of all web sites based in the USA. Little is known
about the efforts hospitals and health systems make to secure the domain name
system for their websites. To investigate the prevalence of implementing Domain
Name System Security Extensions (DNSSEC), we analyzed the websites of the 210
public hospitals in the state of Illinois, USA. Only one Illinois hospital
website was found to have implemented DNSSEC by December, 2017.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,458 | Mathematical analysis of plasmonic resonance for 2-D photonic crystal | In this article, we study the plasmonic resonance of infinite photonic
crystal mounted by the double negative nanoparticles in two dimensions. The
corresponding physical model is described by the Helmholz equation with so
called Bloch wave condition in a periodic domain. By using the quasi-periodic
layer potential techniques and the spectral theorem of quasi-periodic
Neumann-Poincar{é} operator, the quasi-static expansion of the near field in
the presence of nanoparticles is derived. Furthermore, when the magnetic
permeability of nanoparticles satisfies the Drude model, we give the conditions
under which the plasmonic resonance occurs, and the rate of blow up of near
field energy with respect to nanoparticle's bulk electron relaxation rate and
filling factor are also obtained. It indicates that one can appropriately
control the bulk electron relaxation rate or filling factor of nanoparticle in
photonic crystal structure such that the near field energy attains its maximum,
and enhancing the efficiency of energy utilization.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,459 | Thermo-Optical Chaos and Direct Soliton Generation in Microresonators | We investigate, numerically and experimentally, the effect of thermo-optical
(TO) chaos on direct soliton generation (DSG) in microresonators. When the pump
laser is scanned from blue to red and then stopped at a fixed wavelength, we
find that the solitons generated sometimes remain (survive) and sometimes
annihilate subsequent to the end of the scan. We refer to the possibility of
these different outcomes arising under identical laser scan conditions as
coexistence of soliton annihilation and survival. Numerical simulations that
include the thermal dynamics show that the coexistence of soliton annihilation
and survival is explained by TO chaos accompanying comb generation. The random
fluctuations of the cavity resonance occurring under TO chaos are also found to
trigger spontaneous soliton generation after the laser scan ends. The
coexistence of soliton annihilation and survival as well as spontaneous soliton
generation are observed experimentally in a silicon-nitride microresonator. The
elucidation of the role of TO chaos provides important insights into the
soliton generation dynamics in microresonators, which may eventually facilitate
straightforward soliton generation in fully-integrated microresonators.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,460 | Rigidity of closed metric measure spaces with nonnegative curvature | We show that one-dimensional circle is the only case for closed smooth metric
measure spaces with nonnegative Bakry-Émery Ricci curvature whose spectrum
of the weighted Laplacian has an optimal positive upper bound. This result
extends the work of Hang-Wang in the manifold case (Int. Math. Res. Not. 18
(2007), Art. ID rnm064, 9pp).
| 0 | 0 | 1 | 0 | 0 | 0 |
18,461 | Combining Agile with Traditional V Model for Enhancement of Maturity in Software Development | In the field of software engineering there are many new archetypes are
introducing day to day Improve the efficiency and effectiveness of software
development. Due to dynamic environment organizations are frequently exchanging
their software constraint to meet their objectives. The propose research is a
new approach by integrating the traditional V model and agile methodology to
combining the strength of these models while minimizing their individual
weakness.The fluctuating requirements of emerging a carried software system and
accumulative cost of operational software are imposing researchers and experts
to determine innovative and superior means for emerging software application at
slight business or at enterprise level are viewing for. Agile methodology has
its own benefits but there are deficiency several of the features of
traditional software development methodologies that are essential for success.
Thats why an embedded approach will be the right answer for software industry
rather than a pure agile approach. This research shows how agile embedded
traditional can play a vital role in development of software. A survey
conducted to find the impact of this approach in industry. Both qualitative and
quantitative analysis performed.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,462 | Histograms of Gaussian normal distribution for feature matching in clutter scenes | 3D feature descriptor provide information between corresponding models and
scenes. 3D objection recognition in cluttered scenes, however, remains a
largely unsolved problem. Practical applications impose several challenges
which are not fully addressed by existing methods. Especially in cluttered
scenes there are many feature mismatches between scenes and models. We
therefore propose Histograms of Gaussian Normal Distribution (HGND) for
extracting salient features on a local reference frame (LRF) that enables us to
solve this problem. We propose a LRF on each local surface patches using the
scatter matrix's eigenvectors. Then the HGND information of each salient point
is calculated on the LRF, for which we use both the mesh and point data of the
depth image. Experiments on 45 cluttered scenes of the Bologna Dataset and 50
cluttered scenes of the UWA Dataset are made to evaluate the robustness and
descriptiveness of our HGND. Experiments carried out by us demonstrate that
HGND obtains a more reliable matching rate than state-of-the-art approaches in
cluttered situations.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,463 | The temporalized Massey's method | We propose and throughly investigate a temporalized version of the popular
Massey's technique for rating actors in sport competitions. The method can be
described as a dynamic temporal process in which team ratings are updated at
every match according to their performance during the match and the strength of
the opponent team. Using the Italian soccer dataset, we empirically show that
the method has a good foresight prediction accuracy.
| 1 | 1 | 0 | 0 | 0 | 0 |
18,464 | Introduction to Nonnegative Matrix Factorization | In this paper, we introduce and provide a short overview of nonnegative
matrix factorization (NMF). Several aspects of NMF are discussed, namely, the
application in hyperspectral imaging, geometry and uniqueness of NMF solutions,
complexity, algorithms, and its link with extended formulations of polyhedra.
In order to put NMF into perspective, the more general problem class of
constrained low-rank matrix approximation problems is first briefly introduced.
| 1 | 0 | 1 | 1 | 0 | 0 |
18,465 | Randomized Dynamic Mode Decomposition | This paper presents a randomized algorithm for computing the near-optimal
low-rank dynamic mode decomposition (DMD). Randomized algorithms are emerging
techniques to compute low-rank matrix approximations at a fraction of the cost
of deterministic algorithms, easing the computational challenges arising in the
area of `big data'. The idea is to derive a small matrix from the
high-dimensional data, which is then used to efficiently compute the dynamic
modes and eigenvalues. The algorithm is presented in a modular probabilistic
framework, and the approximation quality can be controlled via oversampling and
power iterations. The effectiveness of the resulting randomized DMD (rDMD)
algorithm is demonstrated on several benchmark examples of increasing
complexity, providing an accurate and efficient approach to extract
spatiotemporal coherent structures from big data in a framework that scales
with the intrinsic rank of the data, rather than the ambient measurement
dimension.
| 1 | 0 | 1 | 0 | 0 | 0 |
18,466 | On the convergence of a fully discrete scheme of LES type to physically relevant solutions of the incompressible Navier-Stokes | Obtaining reliable numerical simulations of turbulent fluids is a challenging
problem in computational fluid mechanics. The Large Eddy Simulations (LES)
models are efficient tools to approximate turbulent fluids and an important
step in the validation of these models is the ability to reproduce relevant
properties of the flow. In this paper we consider a fully discrete
approximation of the Navier-Stokes-Voigt model by an implicit Euler algorithm
(with respect to the time variable) and a Fourier-Galerkin method (in the space
variables). We prove the convergence to weak solutions of the incompressible
Navier-Stokes equations satisfying the natural local entropy condition, hence
selecting the so-called physically relevant solutions
| 0 | 0 | 1 | 0 | 0 | 0 |
18,467 | Hardy-Sobolev-Maz'ya inequalities for higher order derivatives on half spaces | By using, among other things, the Fourier analysis techniques on hyperbolic
and symmetric spaces, we establish the Hardy-Sobolev-Maz'ya inequalities for
higher order derivatives on half spaces. The proof relies on a
Hardy-Littlewood-Sobolev inequality on hyperbolic spaces which is of its
independent interest. We also give an alternative proof of Benguria, Frank and
Loss' work concerning the sharp constant in the Hardy-Sobolev-Maz'ya inequality
in the three dimensional upper half space. Finally, we show the sharp constant
in the Hardy-Sobolev-Maz'ya inequality for bi-Laplacian in the upper half space
of dimension five coincides with the Sobolev constant.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,468 | Smooth invariants of focus-focus singularities and obstructions to product decomposition | We study focus-focus singularities (also known as nodal singularities, or
pinched tori) of Lagrangian fibrations on symplectic $4$-manifolds. We show
that, in contrast to elliptic and hyperbolic singularities, there exist
homeomorphic focus-focus singularities which are not diffeomorphic.
Furthermore, we obtain an algebraic description of the moduli space of
focus-focus singularities up to smooth equivalence, and show that for double
pinched tori this space is one-dimensional. Finally, we apply our construction
to disprove Zung's conjecture which says that any non-degenerate singularity
can be smoothly decomposed into an almost direct product of standard
singularities.
| 0 | 1 | 1 | 0 | 0 | 0 |
18,469 | A note about Euler's inequality and automated reasoning with dynamic geometry | Using implicit loci in GeoGebra Euler's $R\geq 2r$ inequality can be
investigated in a novel way. Some unavoidable side effects of the implicit
locus computation introduce unexpected algebraic curves. By using a mixture of
symbolic and numerical methods a possible approach is sketched up to
investigate the situation.
| 1 | 0 | 1 | 0 | 0 | 0 |
18,470 | The MUSE view of He 2-10: no AGN ionization but a sparkling starburst | We study the physical and dynamical properties of the ionized gas in the
prototypical HII galaxy Henize 2-10 using MUSE integral field spectroscopy. The
large scale dynamics is dominated by extended outflowing bubbles, probably the
results of massive gas ejection from the central star forming regions. We
derive a mass outflow rate dMout/dt~0.30 Msun/yr, corresponding to mass loading
factor eta~0.4, in range with similar measurements in local LIRGs. Such a
massive outflow has a total kinetic energy that is sustainable by the stellar
winds and Supernova Remnants expected in the galaxy. We use classical emission
line diagnostic to study the dust extinction, electron density and ionization
conditions all across the galaxy, confirming the extreme nature of the highly
star forming knots in the core of the galaxy, which show high density and high
ionization parameter. We measure the gas phase metallicity in the galaxy taking
into account the strong variation of the ionization parameter, finding that the
external parts of the galaxy have abundances as low as 12 + log(O/H)~8.3, while
the central star forming knots are highly enriched with super solar
metallicity. We find no sign of AGN ionization in the galaxy, despite the
recent claim of the presence of a super massive active Black Hole in the core
of He~2-10. We therefore reanalyze the X-ray data that were used to propose the
presence of the AGN, but we conclude that the observed X-ray emission can be
better explained with sources of a different nature, such as a Supernova
Remnant.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,471 | Modeling Oral Multispecies Biofilm Recovery After Antibacterial Treatment | Recovery of multispecies oral biofilms is investigated following treatment by
chlorhexidine gluconate (CHX), iodine-potassium iodide (IPI) and Sodium
hypochlorite (NaOCl) both experimentally and theoretically. Experimentally,
biofilms taken from two donors were exposed to the three antibacterial
solutions (irrigants) for 10 minutes, respectively. We observe that (a) live
bacterial cell ratios decline for a week after the exposure and the trend
reverses beyond a week; after fifteen weeks, live bacterial cell ratios in
biofilms fully return to their pretreatment levels; (b) NaOCl is shown as the
strongest antibacterial agent for the oral biofilms; (c) multispecies oral
biofilms from different donors showed no difference in their susceptibility to
all the bacterial solutions. Guided by the experiment, a mathematical model for
biofilm dynamics is developed, accounting for multiple bacterial phenotypes,
quorum sensing, and growth factor proteins, to describe the nonlinear time
evolutionary behavior of the biofilms. The model captures time evolutionary
dynamics of biofilms before and after antibacterial treatment very well. It
reveals the crucial role played by quorum sensing molecules and growth factors
in biofilm recovery and verifies that the source of biofilms has a minimal to
their recovery. The model is also applied to describe the state of biofilms of
various ages treated by CHX, IPI and NaOCl, taken from different donors. Good
agreement with experimental data predicted by the model is obtained as well,
confirming its applicability to modeling biofilm dynamics in general.
| 0 | 0 | 0 | 0 | 1 | 0 |
18,472 | On constant multi-commodity flow-cut gaps for directed minor-free graphs | The multi-commodity flow-cut gap is a fundamental parameter that affects the
performance of several divide \& conquer algorithms, and has been extensively
studied for various classes of undirected graphs. It has been shown by Linial,
London and Rabinovich \cite{linial1994geometry} and by Aumann and Rabani
\cite{aumann1998log} that for general $n$-vertex graphs it is bounded by
$O(\log n)$ and the Gupta-Newman-Rabinovich-Sinclair conjecture
\cite{gupta2004cuts} asserts that it is $O(1)$ for any family of graphs that
excludes some fixed minor.
The flow-cut gap is poorly understood for the case of directed graphs. We
show that for uniform demands it is $O(1)$ on directed series-parallel graphs,
and on directed graphs of bounded pathwidth. These are the first constant upper
bounds of this type for some non-trivial family of directed graphs. We also
obtain $O(1)$ upper bounds for the general multi-commodity flow-cut gap on
directed trees and cycles. These bounds are obtained via new embeddings and
Lipschitz quasipartitions for quasimetric spaces, which generalize analogous
results form the metric case, and could be of independent interest. Finally, we
discuss limitations of methods that were developed for undirected graphs, such
as random partitions, and random embeddings.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,473 | Molecular Gas during the Post-Starburst Phase: Low Gas Fractions in Green Valley Seyfert Post-Starburst Galaxies | Post-starbursts (PSBs) are candidate for rapidly transitioning from
star-bursting to quiescent galaxies. We study the molecular gas evolution of
PSBs at z ~ 0.03 - 0.2. We undertook new CO (2-1) observations of 22 Seyfert
PSBs candidates using the ARO Submillimeter Telescope. This sample complements
previous samples of PSBs by including green valley PSBs with Seyfert-like
emission, allowing us to analyze for the first time the molecular gas
properties of 116 PSBs with a variety of AGN properties. The distribution of
molecular gas to stellar mass fractions in PSBs is significantly different than
normal star-forming galaxies in the COLD GASS survey. The combined samples of
PSBs with Seyfert-like emission line ratios have a gas fraction distribution
which is even more significantly different and is broader (~ 0.03-0.3). Most of
them have lower gas fractions than normal star-forming galaxies. We find a
highly significant correlation between the WISE 12 micron to 4.6 micron flux
ratios and molecular gas fractions in both PSBs and normal galaxies. We detect
molecular gas in 27% of our Seyfert PSBs. Taking into account the upper limits,
the mean and the dispersion of the distribution of the gas fraction in our
Seyfert PSB sample are much smaller (mean = 0.025, std dev. = 0.018) than
previous samples of Seyfert PSBs or PSBs in general (mean ~ 0.1 - 0.2, std dev.
~ 0.1 - 0.2).
| 0 | 1 | 0 | 0 | 0 | 0 |
18,474 | Bit-Reversible Version of Milne's Fourth-Order Time-Reversible Integrator for Molecular Dynamics | We point out that two of Milne's fourth-order integrators are well-suited to
bit-reversible simulations. The fourth-order method improves on the accuracy of
Levesque and Verlet's algorithm and simplifies the definition of the velocity
$v$ and energy $e = (q^2 + v^2)/2$ . ( We use this one-dimensional oscillator
problem as an illustration throughout this paper ). Milne's integrator is
particularly useful for the analysis of Lyapunov ( exponential ) instability in
dynamical systems, including manybody molecular dynamics. We include the
details necessary to the implementation of Milne's Algorithms.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,475 | Solvable Hydrodynamics of Quantum Integrable Systems | The conventional theory of hydrodynamics describes the evolution in time of
chaotic many-particle systems from local to global equilibrium. In a quantum
integrable system, local equilibrium is characterized by a local generalized
Gibbs ensemble or equivalently a local distribution of pseudo-momenta. We study
time evolution from local equilibria in such models by solving a certain
kinetic equation, the "Bethe-Boltzmann" equation satisfied by the local
pseudo-momentum density. Explicit comparison with density matrix
renormalization group time evolution of a thermal expansion in the XXZ model
shows that hydrodynamical predictions from smooth initial conditions can be
remarkably accurate, even for small system sizes. Solutions are also obtained
in the Lieb-Liniger model for free expansion into vacuum and collisions between
clouds of particles, which model experiments on ultracold one-dimensional Bose
gases.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,476 | Compressed sensing and optimal denoising of monotone signals | We consider the problems of compressed sensing and optimal denoising for
signals $\mathbf{x_0}\in\mathbb{R}^N$ that are monotone, i.e.,
$\mathbf{x_0}(i+1) \geq \mathbf{x_0}(i)$, and sparsely varying, i.e.,
$\mathbf{x_0}(i+1) > \mathbf{x_0}(i)$ only for a small number $k$ of indices
$i$. We approach the compressed sensing problem by minimizing the total
variation norm restricted to the class of monotone signals subject to equality
constraints obtained from a number of measurements $A\mathbf{x_0}$. For random
Gaussian sensing matrices $A\in\mathbb{R}^{m\times N}$ we derive a closed form
expression for the number of measurements $m$ required for successful
reconstruction with high probability. We show that the probability undergoes a
phase transition as $m$ varies, and depends not only on the number of change
points, but also on their location. For denoising we regularize with the same
norm and derive a formula for the optimal regularizer weight that depends only
mildly on $\mathbf{x_0}$. We obtain our results using the statistical dimension
tool.
| 1 | 0 | 1 | 1 | 0 | 0 |
18,477 | On minimax nonparametric estimation of signal in Gaussian noise | For the problem of nonparametric estimation of signal in Gaussian noise we
point out the strong asymptotically minimax estimators on maxisets for linear
estimators (see \cite{ker93,rio}). It turns out that the order of rates of
convergence of Pinsker estimator on this maxisets is worse than the order of
rates of convergence for the class of linear estimators considered on this
maxisets. We show that balls in Sobolev spaces are maxisets for Pinsker
estimators.
| 0 | 0 | 1 | 1 | 0 | 0 |
18,478 | Implicit Bias of Gradient Descent on Linear Convolutional Networks | We show that gradient descent on full-width linear convolutional networks of
depth $L$ converges to a linear predictor related to the $\ell_{2/L}$ bridge
penalty in the frequency domain. This is in contrast to linearly fully
connected networks, where gradient descent converges to the hard margin linear
support vector machine solution, regardless of depth.
| 0 | 0 | 0 | 1 | 0 | 0 |
18,479 | Oxidation of clofibric acid in aqueous solution using a non-thermal plasma discharge or gamma radiation | In this work, we study degradation of clofibric acid (CFA) in aqueous
solution using either ionizing radiation from a $^{60}$Co source or a
non-thermal plasma produced by discharges in the air above the solution. The
results obtained with the two technologies are compared in terms of
effectiveness of CFA degradation and its by-products. In both cases the CFA
degradation follows a quasi-exponential decay in time well modelled by a
kinetic scheme which considers the competition between CFA and all reaction
intermediates for the reactive species generated in solution as well as the
amount of the end product formed. A new degradation law is deduced to explain
the results. Although the end-product CO$_2$ was detected and the CFA
conversion found to be very high under the studied conditions, HPLC analysis
reveals several degradation intermediates still bearing the aromatic ring with
the chlorine substituent. The extent of mineralization is rather limited. The
energy yield is found to be higher in the gamma radiation experiments.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,480 | Quenching current by flux-flow instability in iron-chalcogenides thin films | The stability against quench is one of the main issue to be pursued in a
superconducting material which should be able to perform at very high levels of
current densities. Here we focus on the connection between the critical current
$I_c$ and the quenching current $I^*$ associated to the so-called flux-flow
instability phenomenon, which sets in as an abrupt transition from the flux
flow state to the normal state. To this purpose, we analyze several
current-voltage characteristics of three types of iron-based thin films,
acquired at different temperature and applied magnetic field values. For these
samples, we discuss the impact of a possible coexistence of intrinsic
electronic mechanisms and extrinsic thermal effects on the quenching current
dependence upon the applied magnetic field. The differences between the
quenching current and the critical current are reported also in the case of
predominant intrinsic mechanisms. Carrying out a comparison with
high-temperature cuprate superconductors, we suggest which material can be the
best trade-off between maximum operating temperature, higher upper critical
field and stability under high current bias.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,481 | New cardinality estimation algorithms for HyperLogLog sketches | This paper presents new methods to estimate the cardinalities of data sets
recorded by HyperLogLog sketches. A theoretically motivated extension to the
original estimator is presented that eliminates the bias for small and large
cardinalities. Based on the maximum likelihood principle a second unbiased
method is derived together with a robust and efficient numerical algorithm to
calculate the estimate. The maximum likelihood approach can also be applied to
more than a single HyperLogLog sketch. In particular, it is shown that it gives
more precise cardinality estimates for union, intersection, or relative
complements of two sets that are both represented by HyperLogLog sketches
compared to the conventional technique using the inclusion-exclusion principle.
All the new methods are demonstrated and verified by extensive simulations.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,482 | The EUSO@TurLab Project | The TurLab facility is a laboratory, equipped with a 5 m diameter and 1 m
depth rotating tank, located in the Physics Department of the University of
Turin. The tank has been built mainly to study problems where system rotation
plays a key role in the fluid behaviour such as in atmospheric and oceanic
flows at different scales. The tank can be filled with different fluids of
variable density, which enables studies in layered conditions such as sea
waves. The tank can be also used to simulate the terrestrial surface with the
optical characteristics of different environments such as snow, grass, ocean,
land with soil, stones etc., fogs and clouds. As it is located in an extremely
dark place, the light intensity can be controlled artificially. Such
capabilities of the TurLab facility are applied to perform experiments related
to the observation of Extreme Energy Cosmic Rays (EECRs) from space using the
fluorescence technique, as in the case of the JEM-EUSO mission, where the
diffuse night brightness and artificial light sources can vary significantly in
time and space inside the Field of View (FoV) of the telescope. Here we will
report the currently ongoing activity at the TurLab facility in the framework
of the JEM-EUSO mission (EUSO@TurLab).
| 0 | 1 | 0 | 0 | 0 | 0 |
18,483 | A finite element method framework for modeling rotating machines with superconducting windings | Electrical machines employing superconductors are attractive solutions in a
variety of application domains. Numerical models are powerful and necessary
tools to optimize their design and predict their performance. The
electromagnetic modeling of superconductors by finite-element method (FEM) is
usually based on a power-law resistivity for their electrical behavior. The
implementation of such constitutive law in conventional models of electrical
machines is quite problematic: the magnetic vector potential directly gives the
electric field and requires using a power-law depending on it. This power-law
is a non-bounded function that can generate enormous uneven values in low
electric field regions that can destroy the reliability of solutions. The
method proposed here consists in separating the model of an electrical machine
in two parts, where the magnetic field is calculated with the most appropriate
formulation: the H-formulation in the part containing the superconductors and
the A-formulation in the part containing conventional conductors (and possibly
permanent magnets). The main goal of this work is to determine and to correctly
apply the continuity conditions on the boundary separating the two regions.
Depending on the location of such boundary -- in the fixed or rotating part of
the machine -- the conditions that one needs to apply are different. In
addition, the application of those conditions requires the use of Lagrange
multipliers satisfying the field transforms of the electromagnetic quantities
in the two reference systems, the fixed and the rotating one. In this article,
several exemplary cases for the possible configurations are presented. In order
to emphasize and capture the essential point of this modeling strategy, the
discussed examples are rather simple. Nevertheless, they constitute a solid
starting point for modeling more complex and realistic devices.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,484 | Triangular Decomposition of Matrices in a Domain | Deterministic recursive algorithms for the computation of matrix triangular
decompositions with permutations like LU and Bruhat decomposition are presented
for the case of commutative domains. This decomposition can be considered as a
generalization of LU and Bruhat decompositions, because they both may be easily
obtained from this triangular decomposition. Algorithms have the same
complexity as the algorithm of matrix multiplication.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,485 | Practical Bayesian Optimization for Transportation Simulators | We provide a method to solve optimization problem when objective function is
a complex stochastic simulator of an urban transportation system. To reach this
goal, a Bayesian optimization framework is introduced. We show how the choice
of prior and inference algorithm effect the outcome of our optimization
procedure. We develop dimensionality reduction techniques that allow for our
optimization techniques to be applicable for real-life problems. We develop a
distributed, Gaussian Process Bayesian regression and active learning models
that allow parallel execution of our algorithms and enable usage of high
performance computing. We present a fully Bayesian approach that is more sample
efficient and reduces computational budget. Our framework is supported by
theoretical analysis and an empirical study. We demonstrate our framework on
the problem of calibrating a multi-modal transportation network of city of
Bloomington, Illinois. Finally, we discuss directions for further research.
| 0 | 0 | 0 | 1 | 0 | 0 |
18,486 | The Ising distribution as a latent variable model | It is shown that the Ising distribution can be treated as a latent variable
model, where a set of N real-valued, correlated random variables are drawn and
used to generate N binary spins independently. This allows to approximate the
Ising distribution by a simpler model where the latent variables follow a
multivariate normal distribution, the so-called Cox distribution. The
approximation is formally related to an advanced mean field technique known as
adaptive TAP, and its domain of validity is similar. When valid, it allows a
principled replacement of the Ising distribution by a distribution much easier
to sample and manipulate.
| 0 | 0 | 0 | 1 | 1 | 0 |
18,487 | Applying DCOP to User Association Problem in Heterogeneous Networks with Markov Chain Based Algorithm | Multi-agent systems (MAS) is able to characterize the behavior of individual
agent and the interaction between agents. Thus, it motivates us to leverage the
distributed constraint optimization problem (DCOP), a framework of modeling
MAS, to solve the user association problem in heterogeneous networks (HetNets).
Two issues we have to consider when we take DCOP into the application of HetNet
including: (i) How to set up an effective model by DCOP taking account of the
negtive impact of the increment of users on the modeling process (ii) Which
kind of algorithms is more suitable to balance the time consumption and the
quality of soltuion. Aiming to overcome these issues, we firstly come up with
an ECAV-$\eta$ (Each Connection As Variable) model in which a parameter $\eta$
with an adequate assignment ($\eta=3$ in this paper) is able to control the
scale of the model. After that, a Markov chain (MC) based algorithm is proposed
on the basis of log-sum-exp function. Experimental results show that the
solution obtained by DCOP framework is better than the one obtained by the
Max-SINR algorithm. Comparing with the Lagrange dual decomposition based method
(LDD), the solution performance has been improved since there is no need to
transform original problem into a satisfied one. In addition, it is also
apparent that the DCOP based method has better robustness than LDD when the
number of users increases but the available resource at base stations are
limited.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,488 | Linear growth of streaming instability in pressure bumps | Streaming instability is a powerful mechanism which concentrates dust grains
in pro- toplanetary discs, eventually up to the stage where they collapse
gravitationally and form planetesimals. Previous studies inferred that it
should be ineffective in viscous discs, too efficient in inviscid discs, and
may not operate in local pressure maxima where solids accumulate. From a linear
analysis of stability, we show that streaming instability behaves differently
inside local pressure maxima. Under the action of the strong differential
advection imposed by the bump, a novel unstable mode develops and grows even
when gas viscosity is large. Hence, pressure bumps are found to be the only
places where streaming instability occurs in viscous discs. This offers a
promising way to conciliate models of planet formation with recent observations
of young discs.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,489 | On the Gevrey regularity for Sums of Squares of vector fields, study of some models | The micro-local Gevrey regularity of a class of "sums of squares" with real
analytic coefficients is studied in detail. Some partial regularity result is
also given.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,490 | Structure theorems for star-commuting power partial isometries | We give a new formulation and proof of a theorem of Halmos and Wallen on the
structure of power partial isometries on Hilbert space. We then use this
theorem to give a structure theorem for a finite set of partial isometries
which star-commute: each operator commutes with the others and with their
adjoints.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,491 | On free Gelfand--Dorfman--Novikov superalgebras and a PBW type theorem | We construct a linear basis of a free GDN superalgebra over a field of
characteristic $\neq 2$.
As applications, we prove a PBW theorem, that is, any GDN superalgebra can be
embedded into its universal enveloping commutative associative differential
superalgebra. An Engel theorem under some assumptions is given.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,492 | An inexact iterative Bregman method for optimal control problems | In this article we investigate an inexact iterative regularization method
based on generalized Bregman distances of an optimal control problem with
control constraints. We show robustness and convergence of the inexact Bregman
method under a regularity assumption, which is a combination of a source
condition and a regularity assumption on the active sets. We also take the
discretization error into account. Numerical results are presented to
demonstrate the algorithm.
| 0 | 0 | 1 | 0 | 0 | 0 |
18,493 | Mixture Models in Astronomy | Mixture models combine multiple components into a single probability density
function. They are a natural statistical model for many situations in
astronomy, such as surveys containing multiple types of objects, cluster
analysis in various data spaces, and complicated distribution functions. This
chapter in the CRC Handbook of Mixture Analysis is concerned with astronomical
applications of mixture models for cluster analysis, classification, and
semi-parametric density estimation. We present several classification examples
from the literature, including identification of a new class, analysis of
contaminants, and overlapping populations. In most cases, mixtures of normal
(Gaussian) distributions are used, but it is sometimes necessary to use
different distribution functions derived from astrophysical experience. We also
address the use of mixture models for the analysis of spatial distributions of
objects, like galaxies in redshift surveys or young stars in star-forming
regions. In the case of galaxy clustering, mixture models may not be the
optimal choice for understanding the homogeneous and isotropic structure of
voids and filaments. However, we show that mixture models, using astrophysical
models for star clusters, may provide a natural solution to the problem of
subdividing a young stellar population into subclusters. Finally, we explore
how mixture models can be used for mathematically advanced modeling of data
with heteroscedastic uncertainties or missing values, providing two example
algorithms, the measurement error regression model of Kelly (2007) and the
Extreme Deconvolution model of Bovy et al. (2011). The challenges presented by
astronomical science, aided by the public availability of catalogs from major
surveys and missions, are a rich area for collaboration between statisticians
and astronomers.
| 0 | 1 | 0 | 1 | 0 | 0 |
18,494 | Safe Medicine Recommendation via Medical Knowledge Graph Embedding | Most of the existing medicine recommendation systems that are mainly based on
electronic medical records (EMRs) are significantly assisting doctors to make
better clinical decisions benefiting both patients and caregivers. Even though
the growth of EMRs is at a lighting fast speed in the era of big data, content
limitations in EMRs restrain the existed recommendation systems to reflect
relevant medical facts, such as drug-drug interactions. Many medical knowledge
graphs that contain drug-related information, such as DrugBank, may give hope
for the recommendation systems. However, the direct use of these knowledge
graphs in the systems suffers from robustness caused by the incompleteness of
the graphs. To address these challenges, we stand on recent advances in graph
embedding learning techniques and propose a novel framework, called Safe
Medicine Recommendation (SMR), in this paper. Specifically, SMR first
constructs a high-quality heterogeneous graph by bridging EMRs (MIMIC-III) and
medical knowledge graphs (ICD-9 ontology and DrugBank). Then, SMR jointly
embeds diseases, medicines, patients, and their corresponding relations into a
shared lower dimensional space. Finally, SMR uses the embeddings to decompose
the medicine recommendation into a link prediction process while considering
the patient's diagnoses and adverse drug reactions. To our best knowledge, SMR
is the first to learn embeddings of a patient-disease-medicine graph for
medicine recommendation in the world. Extensive experiments on real datasets
are conducted to evaluate the effectiveness of proposed framework.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,495 | Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression | Deep neural networks (DNNs) have achieved great success in solving a variety
of machine learning (ML) problems, especially in the domain of image
recognition. However, recent research showed that DNNs can be highly vulnerable
to adversarially generated instances, which look seemingly normal to human
observers, but completely confuse DNNs. These adversarial samples are crafted
by adding small perturbations to normal, benign images. Such perturbations,
while imperceptible to the human eye, are picked up by DNNs and cause them to
misclassify the manipulated instances with high confidence. In this work, we
explore and demonstrate how systematic JPEG compression can work as an
effective pre-processing step in the classification pipeline to counter
adversarial attacks and dramatically reduce their effects (e.g., Fast Gradient
Sign Method, DeepFool). An important component of JPEG compression is its
ability to remove high frequency signal components, inside square blocks of an
image. Such an operation is equivalent to selective blurring of the image,
helping remove additive perturbations. Further, we propose an ensemble-based
technique that can be constructed quickly from a given well-performing DNN, and
empirically show how such an ensemble that leverages JPEG compression can
protect a model from multiple types of adversarial attacks, without requiring
knowledge about the model.
| 1 | 0 | 0 | 0 | 0 | 0 |
18,496 | Numerical Simulation of Bloch Equations for Dynamic Magnetic Resonance Imaging | Magnetic Resonance Imaging (MRI) is a widely applied non-invasive imaging
modality based on non-ionizing radiation which gives excellent images and soft
tissue contrast of living tissues. We consider the modified Bloch problem as a
model of MRI for flowing spins in an incompressible flow field. After
establishing the well-posedness of the corresponding evolution problem, we
analyze its spatial semidiscretization using discontinuous Galerkin methods.
The high frequency time evolution requires a proper explicit and adaptive
temporal discretization. The applicability of the approach is shown for basic
examples.
| 1 | 0 | 1 | 0 | 0 | 0 |
18,497 | End-to-End Waveform Utterance Enhancement for Direct Evaluation Metrics Optimization by Fully Convolutional Neural Networks | Speech enhancement model is used to map a noisy speech to a clean speech. In
the training stage, an objective function is often adopted to optimize the
model parameters. However, in most studies, there is an inconsistency between
the model optimization criterion and the evaluation criterion on the enhanced
speech. For example, in measuring speech intelligibility, most of the
evaluation metric is based on a short-time objective intelligibility (STOI)
measure, while the frame based minimum mean square error (MMSE) between
estimated and clean speech is widely used in optimizing the model. Due to the
inconsistency, there is no guarantee that the trained model can provide optimal
performance in applications. In this study, we propose an end-to-end
utterance-based speech enhancement framework using fully convolutional neural
networks (FCN) to reduce the gap between the model optimization and evaluation
criterion. Because of the utterance-based optimization, temporal correlation
information of long speech segments, or even at the entire utterance level, can
be considered when perception-based objective functions are used for the direct
optimization. As an example, we implement the proposed FCN enhancement
framework to optimize the STOI measure. Experimental results show that the STOI
of test speech is better than conventional MMSE-optimized speech due to the
consistency between the training and evaluation target. Moreover, by
integrating the STOI in model optimization, the intelligibility of human
subjects and automatic speech recognition (ASR) system on the enhanced speech
is also substantially improved compared to those generated by the MMSE
criterion.
| 1 | 0 | 0 | 1 | 0 | 0 |
18,498 | The connectivity of graphs of graphs with self-loops and a given degree sequence | `Double edge swaps' transform one graph into another while preserving the
graph's degree sequence, and have thus been used in a number of popular Markov
chain Monte Carlo (MCMC) sampling techniques. However, while double edge-swaps
can transform, for any fixed degree sequence, any two graphs inside the classes
of simple graphs, multigraphs, and pseudographs, this is not true for graphs
which allow self-loops but not multiedges (loopy graphs). Indeed, we exactly
characterize the degree sequences where double edge swaps cannot reach every
valid loopy graph and develop an efficient algorithm to determine such degree
sequences. The same classification scheme to characterize degree sequences can
be used to prove that, for all degree sequences, loopy graphs are connected by
a combination of double and triple edge swaps. Thus, we contribute the first
MCMC sampler that uniformly samples loopy graphs with any given sequence.
| 1 | 1 | 1 | 0 | 0 | 0 |
18,499 | The role of the background in past and future X-ray missions | Background has played an important role in X-ray missions, limiting the
exploitation of science data in several and sometimes unexpected ways. In this
presentation I review past X-ray missions focusing on some important lessons we
can learn from them. I then go on discussing prospects for overcoming
background related limitations in future ones.
| 0 | 1 | 0 | 0 | 0 | 0 |
18,500 | Securing Manufacturing Intelligence for the Industrial Internet of Things | Widespread interest in the emerging area of predictive analytics is driving
industries such as manufacturing to explore new approaches to the collection
and management of data provided from Industrial Internet of Things (IIoT)
devices. Often, analytics processing for Business Intelligence (BI) is an
intensive task, and it also presents both an opportunity for competitive
advantage as well as a security vulnerability in terms of the potential for
losing Intellectual Property (IP). This article explores two approaches to
securing BI in the manufacturing domain. Simulation results indicate that a
Unified Threat Management (UTM) model is simpler to maintain and has less
potential vulnerabilities than a distributed security model. Conversely, a
distributed model of security out-performs the UTM model and offers more scope
for the use of existing hardware resources. In conclusion, a hybrid security
model is proposed where security controls are segregated into a multi-cloud
architecture.
| 1 | 0 | 0 | 0 | 0 | 0 |
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