title:
An iteration count estimate for a mesh-dependent steepest descent method
  based on finite elements and Riesz inner product representation

abstract:
  Existing implementations of gradient-based optimisation methods typically
assume that the problem is posed in Euclidean space. When solving optimality
problems on function spaces, the functional derivative is then inaccurately
represented with respect to $\ell^2$ instead of the inner product induced by
the function space. This error manifests as a mesh dependence in the number of
iterations required to solve the optimisation problem. In this paper, an
analytic estimate is derived for this iteration count in the case of a simple
and generic discretised optimisation problem. The system analysed is the
steepest descent method applied to a finite element problem. The estimate is
based on Kantorovich's inequality and on an upper bound for the condition
number of Galerkin mass matrices. Computer simulations validate the iteration
number estimate. Similar numerical results are found for a more complex
optimisation problem constrained by a partial differential equation.
Representing the functional derivative with respect to the inner product
induced by the continuous control space leads to mesh independent convergence.


title:
Two-Dimensional Elastic Scattering Coefficients and Enhancement of
  Nearly Elastic Cloaking

abstract:
  The concept of scattering coefficients has played a pivotal role in a broad
range of inverse scattering and imaging problems in acoustic, and
electromagnetic media. In view of their promising applications in inverse
problems related to mathematical imaging and elastic cloaking, the notion of
elastic scattering coefficients of an inclusion is presented from the
perspective of boundary layer potentials and a few properties are discussed. A
reconstruction algorithm is developed and analyzed for extracting the elastic
scattering coefficients from multi-static response measurements of the
scattered field in order to cater to inverse scattering problems. The decay
rate, stability and error analyses, and the estimate of maximal resolving order
in terms of the signal-to-noise ratio are discussed. Moreover,
scattering-coefficients-vanishing structures are designed and their utility for
enhancement of nearly elastic cloaking is elucidated.


title:
Finite-Size Scaling of Non-Gaussian Fluctuations Near the QCD Critical
  Point

abstract:
  An effective Finite-Size Scaling (FSS) of moment products from recent STAR
measurements of the variance $\sigma$, skewness $S$ and kurtosis $\kappa$ of
net-proton multiplicity distributions, are reported for a broad range of
collision centralities in Au+Au ($\sqrt{s_{NN}}= 7.7 - 200$ GeV) collisions.
The products $S\sigma $ and $\kappa \sigma^2 $, which are directly related to
the hgher-order baryon number susceptibility ratios $\chi^{(3)}_B/\chi^{(2)}_B$
and $\chi^{(4)}_B/\chi^{(2)}_B$, show scaling patterns consistent with earlier
indications for a second order phase transition at a critical end point (CEP)
in the plane of temperature vs. baryon chemical potential ($T,\mu_B$) of the
QCD phase diagram. The resulting scaling functions validate the earlier
estimates of $T^{\text{cep}} \sim 165$ MeV and $\mu_B^{\text{cep}} \sim 95$ MeV
for the location of the CEP, and the critical exponents used to assign its 3D
Ising model universality class.


title:
Computing the Convolution of Analog and Discrete Time Exponential
  Signals Algebraically

abstract:
  We present a procedure for computing the convolution of exponential signals
without the need of solving integrals or summations. The procedure requires the
resolution of a system of linear equations involving Vandermonde matrices. We
apply the method to solve ordinary differential/difference equations with
constant coefficients.


title: Emergent Space-Time via a Geometric Renormalization Method

abstract:
  We present a purely geometric renormalization scheme for metric spaces
(including uncolored graphs), which consists of a coarse graining and a
rescaling operation on such spaces. The coarse graining is based on the concept
of quasi-isometry, which yields a sequence of discrete coarse grained spaces
each having a continuum limit under the rescaling operation. We provide
criteria under which such sequences do converge within a superspace of metric
spaces, or may constitute the basin of attraction of a common continuum limit,
which hopefully, may represent our space-time continuum.
  We discuss some of the properties of these coarse grained spaces as well as
their continuum limits, such as scale invariance and metric similarity, and
show that different layers of spacetime can carry different distance functions
while being homeomorphic.
  Important tools in this analysis are the Gromov-Hausdorff distance functional
for general metric spaces and the growth degree of graphs or networks. The
whole construction is in the spirit of the Wilsonian renormalization group.
  Furthermore we introduce a physically relevant notion of dimension on the
spaces of interest in our analysis, which e.g. for regular lattices reduces to
the ordinary lattice dimension. We show that this dimension is stable under the
proposed coarse graining procedure as long as the latter is sufficiently local,
i.e. quasi-isometric, and discuss the conditions under which this dimension is
an integer. We comment on the possibility that the limit space may turn out to
be fractal in case the dimension is non-integer. At the end of the paper we
briefly mention the possibility that our network carries a translocal far-order
which leads to the concept of wormhole spaces and a scale dependent dimension
if the coarse graining procedure is no longer local.


title:
Algebraic structure and maximal dimension of the symmetry algebra for
  arbitrary systems of ODEs

abstract:
  It is known for scalar ordinary differential equations, and for systems of
ordinary differential equations of order not higher than the third, that their
Lie point symmetry algebras is of maximal dimension if and only if they can be
reduced by a point transformation to the trivial equation $\mathbf{y}^{(n)}$=0.
For arbitrary systems of ordinary differential equations of order $n \geq 3$
reducible by point transformations to the trivial equation, we determine the
complete structure of their Lie point symmetry algebras as well as that for
their variational, and their divergence symmetry algebras. As a corollary, we
obtain the maximal dimension of the Lie point symmetry algebra for any system
of linear or nonlinear ordinary differential equations.


title:
Going Digital: A Survey on Digitalization and Large Scale Data Analytics
  in Healthcare

abstract:
  We provide an overview of the recent trends towards digitalization and large
scale data analytics in healthcare. It is expected that these trends are
instrumental in the dramatic changes in the way healthcare will be organized in
the future. We discuss the recent political initiatives designed to shift care
delivery processes from paper to electronic, with the goals of more effective
treatments with better outcomes; cost pressure is a major driver of innovation.
We describe newly developed networks of healthcare providers, research
organizations and commercial vendors to jointly analyze data for the
development of decision support systems. We address the trend towards
continuous healthcare where health is monitored by wearable and stationary
devices; a related development is that patients increasingly assume
responsibility for their own health data. Finally we discuss recent initiatives
towards a personalized medicine, based on advances in molecular medicine, data
management, and data analytics.


title:
Searches for R-parity-violating supersymmetry in pp collisions at
  sqrt(s) = 8 TeV in final states with 0-4 leptons

abstract:
  Results are presented from searches for R-parity-violating supersymmetry in
events produced in pp collisions at sqrt(s) = 8 TeV at the LHC. Final states
with 0, 1, 2, or multiple leptons are considered independently. The analysis is
performed on data collected by the CMS experiment corresponding to an
integrated luminosity of 19.5 inverse femtobarns. No excesses of events above
the standard model expectations are observed, and 95% confidence level limits
are set on supersymmetric particle masses and production cross sections. The
results are interpreted in models featuring R-parity-violating decays of the
lightest supersymmetric particle, which in the studied scenarios can be either
the gluino, a bottom squark, or a neutralino. In a gluino pair production model
with baryon number violation, gluinos with a mass less than 0.98 and 1.03 TeV
are excluded, by analyses in a fully hadronic and one-lepton final state,
respectively. An analysis in a dilepton final state is used to exclude bottom
squarks with masses less than 307 GeV in a model considering bottom squark pair
production. Multilepton final states are considered in the context of either
strong or electroweak production of superpartners, and are used to set limits
on the masses of the lightest supersymmetric particles. These limits range from
300 to 900 GeV in models with leptonic and up to approximately 700 GeV in
models with semileptonic R-parity-violating couplings.


title: Assigning a Small Agreeable Set of Indivisible Items to Multiple Players

abstract:
  We consider an assignment problem that has aspects of fair division as well
as social choice. In particular, we investigate the problem of assigning a
small subset from a set of indivisible items to multiple players so that the
chosen subset is \emph{agreeable} to all players, i.e., every player weakly
prefers the chosen subset to any subset of its complement. For an arbitrary
number of players, we derive tight upper bounds on the size for which a subset
of that size that is agreeable to all players always exists when preferences
are monotonic. We then present polynomial-time algorithms that find an
agreeable subset of approximately half of the items when there are two or three
players and preferences are responsive. Our results translate to a
2-approximation on the individual welfare of every player when preferences are
subadditive.


title:
Detection of concealed cars in complex cargo X-ray imagery using Deep
  Learning

abstract:
  Non-intrusive inspection systems based on X-ray radiography techniques are
routinely used at transport hubs to ensure the conformity of cargo content with
the supplied shipping manifest. As trade volumes increase and regulations
become more stringent, manual inspection by trained operators is less and less
viable due to low throughput. Machine vision techniques can assist operators in
their task by automating parts of the inspection workflow. Since cars are
routinely involved in trafficking, export fraud, and tax evasion schemes, they
represent an attractive target for automated detection and flagging for
subsequent inspection by operators. In this contribution, we describe a method
for the detection of cars in X-ray cargo images based on trained-from-scratch
Convolutional Neural Networks. By introducing an oversampling scheme that
suitably addresses the low number of car images available for training, we
achieved 100% car image classification rate for a false positive rate of
1-in-454. Cars that were partially or completely obscured by other goods, a
modus operandi frequently adopted by criminals, were correctly detected. We
believe that this level of performance suggests that the method is suitable for
deployment in the field. It is expected that the generic object detection
workflow described can be extended to other object classes given the
availability of suitable training data.


title: Generative Models for Global Collaboration Relationships

abstract:
  When individuals interact with each other and meaningfully contribute toward
a common goal, it results in a collaboration, as can be seen in many walks of
life such as scientific research, motion picture production, or team sports.
The artifacts resulting from a collaboration (e.g. papers, movies) are best
captured using a hypergraph model, whereas the relation of who has collaborated
with whom is best captured via an abstract simplicial complex (SC). In this
paper, we propose a generative algorithm GeneSCs for SCs modeling fundamental
collaboration relations, primarily based on preferential attachment. The
proposed network growth process favors attachment that is preferential not to
an individual's degree, i.e., how many people has he/she collaborated with, but
to his/her facet degree, i.e., how many maximal groups or facets has he/she
collaborated within. Unlike graphs, in SCs, both facet degrees (of nodes) and
facet sizes are important to capture connectivity properties. Based on our
observation that several real-world facet size distributions have significant
deviation from power law-mainly due to the fact that larger facets tend to
subsume smaller ones-we adopt a data-driven approach. We seed GeneSCs with a
facet size distribution informed by collaboration network data and randomly
grow the SC facet-by-facet to generate a final SC whose facet degree
distribution matches real data. We prove that the facet degree distribution
yielded by GeneSCs is power law distributed for large SCs and show that it is
in agreement with real world co-authorship data. Finally, based on our
intuition of collaboration formation in domains such as collaborative
scientific experiments and movie production, we propose two variants of GeneSCs
based on clamped and hybrid preferential attachment schemes, and show that they
perform well in these domains.


title:
Topological generators for full groups of hyperfinite pmp equivalence
  relations

abstract:
  We give an elementary proof that there are two topological generators for the
full group of every aperiodic hyperfinite probability measure preserving Borel
equivalence relation. Our proof explicitly constructs topological generators
for the orbit equivalence relation of the irrational rotation of the circle,
and then appeals to Dye's theorem and a Baire category argument to conclude the
general case.


title:
Deconstructing the E_0 SCFT to Solve the Orbifold Paradox of the
  Heterotic M Theory

abstract:
  Many heterotic orbifold models have massless twisted-sector particles with
simultaneous E8_1 and E8_2 charges. In the strong-coupling M-theory dual of the
heterotic string this poses a paradox: Since the E8_1 and E8_2 live at opposite
ends of the x^10 dimension, where could a massless particle with both types of
charges possible live? To key to this question are the 5D SCFTs living at the
orbifold fixed planes going through the bulk of the M theory. We use
dimensional deconstruction to understand how such a 5D SCFT (specifically, the
E_0 SCFT at the Z_3 fixed point) works at the superconformal point (rather that
at the Coulomb branch) and how it interacts with the boundaries of the x^10. We
find that the massless twisted states are not localized in the x^10. Instead,
they are non-local meson-like composite particles comprised of a quark living
at one boundary of the x^10, and antiquark living at the other boundary, and
the string of strongly-interacting 5D gluons connecting the quark to the
antiquark.


title: Besov spaces via hyperbolic fillings

abstract:
  We establish a new characterization of the homogeneous Besov spaces
$\dot{\mathcal B}^{s}_{p,q}(Z)$ with smoothness $s \in (0,1)$ in the setting of
doubling metric measure spaces $(Z,d,\mu)$. The characterization is given in
terms of a hyperbolic filling of the metric space $(Z,d)$, a construction which
has previously appeared in the context of other function spaces in [3,1,2]. We
use the characterization to obtain results concerning the density of Lipschitz
functions in the spaces $\dot{\mathcal B}^{s}_{p,q}(Z)$ and a general complex
interpolation formula in the smoothness range $0 < s < 1$.


title: Matrix Balancing in Lp Norms: A New Analysis of Osborne's Iteration

abstract:
  We study an iterative matrix conditioning algorithm due to Osborne (1960).
The goal of the algorithm is to convert a square matrix into a balanced matrix
where every row and corresponding column have the same norm. The original
algorithm was proposed for balancing rows and columns in the $L_2$ norm, and it
works by iterating over balancing a row-column pair in fixed round-robin order.
Variants of the algorithm for other norms have been heavily studied and are
implemented as standard preconditioners in many numerical linear algebra
packages. Recently, Schulman and Sinclair (2015), in a first result of its kind
for any norm, analyzed the rate of convergence of a variant of Osborne's
algorithm that uses the $L_{\infty}$ norm and a different order of choosing
row-column pairs. In this paper we study matrix balancing in the $L_1$ norm and
other $L_p$ norms. We show the following results for any matrix $A =
(a_{ij})_{i,j=1}^n$, resolving in particular a main open problem mentioned by
Schulman and Sinclair.
  1) We analyze the iteration for the $L_1$ norm under a greedy order of
balancing. We show that it converges to an $\epsilon$-balanced matrix in $K =
O(\min\{\epsilon^{-2}\log w,\epsilon^{-1}n^{3/2}\log(w/\epsilon)\})$ iterations
that cost a total of $O(m + Kn\log n)$ arithmetic operations over $O(n\log
w)$-bit numbers. Here $m$ is the number of non-zero entries of $A$, and $w =
\sum_{i,j} |a_{ij}|/a_{\min}$ with $a_{\min} = \min\{|a_{ij}|:\ a_{ij}\neq
0\}$.
  2) We show that the original round-robin implementation converges to an
$\epsilon$-balanced matrix in $O(\epsilon^{-2}n^2\log w)$ iterations totalling
$O(\epsilon^{-2}mn\log w)$ arithmetic operations over $O(n\log w)$-bit numbers.
  3) We demonstrate a lower bound of $\Omega(1/\sqrt{\epsilon})$ on the
convergence rate of any implementation of the iteration.


title: Cyberbullying Identification Using Participant-Vocabulary Consistency

abstract:
  With the rise of social media, people can now form relationships and
communities easily regardless of location, race, ethnicity, or gender. However,
the power of social media simultaneously enables harmful online behavior such
as harassment and bullying. Cyberbullying is a serious social problem, making
it an important topic in social network analysis. Machine learning methods can
potentially help provide better understanding of this phenomenon, but they must
address several key challenges: the rapidly changing vocabulary involved in
cyber- bullying, the role of social network structure, and the scale of the
data. In this study, we propose a model that simultaneously discovers
instigators and victims of bullying as well as new bullying vocabulary by
starting with a corpus of social interactions and a seed dictionary of bullying
indicators. We formulate an objective function based on participant-vocabulary
consistency. We evaluate this approach on Twitter and Ask.fm data sets and show
that the proposed method can detect new bullying vocabulary as well as victims
and bullies.


title:
Sampling and Reconstruction of Sparse Signals on Circulant Graphs - An
  Introduction to Graph-FRI

abstract:
  With the objective of employing graphs toward a more generalized theory of
signal processing, we present a novel sampling framework for (wavelet-)sparse
signals defined on circulant graphs which extends basic properties of Finite
Rate of Innovation (FRI) theory to the graph domain, and can be applied to
arbitrary graphs via suitable approximation schemes. At its core, the
introduced Graph-FRI-framework states that any K-sparse signal on the vertices
of a circulant graph can be perfectly reconstructed from its
dimensionality-reduced representation in the graph spectral domain, the Graph
Fourier Transform (GFT), of minimum size 2K. By leveraging the recently
developed theory of e-splines and e-spline wavelets on graphs, one can
decompose this graph spectral transformation into the multiresolution low-pass
filtering operation with a graph e-spline filter, and subsequent transformation
to the spectral graph domain; this allows to infer a distinct sampling pattern,
and, ultimately, the structure of an associated coarsened graph, which
preserves essential properties of the original, including circularity and,
where applicable, the graph generating set.


title: Influence of Surface Tension on Nuclear Collective Properties

abstract:
  Rigidities of even-even nuclei were estimated and compared with nuclear
charge radii. Correlation of maximal nuclear rigidities with minimal values of
r0 parameters was revealed. Influence of effective surface tension on nuclear
properties was discussed.


title: A width parameter useful for chordal and co-comparability graphs

abstract:
  We investigate new graph classes of bounded mim-width, strictly extending
interval graphs and permutation graphs. The graphs $K_t \boxminus K_t$ and $K_t
\boxminus S_t$ are graphs obtained from the disjoint union of two cliques of
size $t$, and one clique of size $t$ and one independent set of size $t$
respectively, by adding a perfect matching. We prove that : (1) interval graphs
are $(K_3\boxminus S_3)$-free chordal graphs; and $(K_t\boxminus S_t)$-free
chordal graphs have mim-width at most $t-1$, (2) permutation graphs are
$(K_3\boxminus K_3)$-free co-comparability graphs; and $(K_t\boxminus
K_t)$-free co-comparability graphs have mim-width at most $t-1$, (3) chordal
graphs and co-comparability graphs have unbounded mim-width in general. We
obtain several algorithmic consequences; for instance, while Minimum Dominating
Set is NP-complete on chordal graphs, it can be solved in time
$n^{\mathcal{O}(t)}$ on $(K_t\boxminus S_t)$-free chordal graphs. The third
statement strengthens a result of Belmonte and Vatshelle stating that either
those classes do not have constant mim-width or a decomposition with constant
mim-width cannot be computed in polynomial time unless $P=NP$. We generalize
these ideas to bigger graph classes. We introduce a new width parameter
sim-width, of stronger modelling power than mim-width, by making a small change
in the definition of mim-width. We prove that chordal graphs and
co-comparability graphs have sim-width at most 1. We investigate a way to bound
mim-width for graphs of bounded sim-width by excluding $K_t\boxminus K_t$ and
$K_t\boxminus S_t$ as induced minors or induced subgraphs, and give algorithmic
consequences. Lastly, we show that circle graphs have unbounded sim-width, and
thus also unbounded mim-width.


title: In Situ and Ex Situ Formation Models of Kepler 11 Planets

abstract:
  We present formation simulations of the six Kepler 11 planets. Models assume
either in situ or ex situ assembly, the latter with migration, and are evolved
to the estimated age of the system, 8 Gyr. Models combine detailed calculations
of both the gaseous envelope and the condensed core structures, including
accretion of gas and solids, of the disk's viscous and thermal evolution,
including photo-evaporation and disk-planet interactions, and of the planets'
evaporative mass loss after disk dispersal. Planet-planet interactions are
neglected. Both sets of simulations successfully reproduce measured radii,
masses, and orbital distances of the planets, except for the radius of Kepler
11b, which loses its entire gaseous envelope shortly after formation. Gaseous
(H+He) envelopes account for < 18% of the planet masses, and between 35 and 60%
of the planet radii. In situ models predict a very massive inner disk, whose
solids' surface density (sigma_Z) varies from over 1e4 to 1e3 g/cm2 at
stellocentric distances 0.1 < r < 0.5 AU. Initial gas densities would be in
excess of 1e5 g/cm2 if solids formed locally. Given the high disk temperatures
(> 1000 K), planetary interiors can only be composed of metals and highly
refractory materials. Sequestration of hydrogen by the core and subsequent
outgassing is required to account for the observed radius of Kepler 11b. Ex
situ models predict a relatively low-mass disk, whose initial sigma_Z varies
from 10 to 5 g/cm2 at 0.5 < r < 7 AU and whose initial gas density ranges from
1e3 to 100 g/cm2. All planetary interiors are expected to be rich in H2O, as
core assembly mostly occurs exterior to the ice condensation front. Kepler 11b
is expected to have a steam atmosphere, and H2O is likely mixed with H+He in
the envelopes of the other planets. Results indicate that Kepler 11g may not be
more massive than Kepler 11e.


title: This before That: Causal Precedence in the Biomedical Domain

abstract:
  Causal precedence between biochemical interactions is crucial in the
biomedical domain, because it transforms collections of individual
interactions, e.g., bindings and phosphorylations, into the causal mechanisms
needed to inform meaningful search and inference. Here, we analyze causal
precedence in the biomedical domain as distinct from open-domain, temporal
precedence. First, we describe a novel, hand-annotated text corpus of causal
precedence in the biomedical domain. Second, we use this corpus to investigate
a battery of models of precedence, covering rule-based, feature-based, and
latent representation models. The highest-performing individual model achieved
a micro F1 of 43 points, approaching the best performers on the simpler
temporal-only precedence tasks. Feature-based and latent representation models
each outperform the rule-based models, but their performance is complementary
to one another. We apply a sieve-based architecture to capitalize on this lack
of overlap, achieving a micro F1 score of 46 points.


title:
Framework for state and unknown input estimation of linear time-varying
  systems

abstract:
  The design of unknown-input decoupled observers and filters requires the
assumption of an existence condition in the literature. This paper addresses an
unknown input filtering problem where the existence condition is not satisfied.
Instead of designing a traditional unknown input decoupled filter, a
Double-Model Adaptive Estimation approach is extended to solve the unknown
input filtering problem. It is proved that the state and the unknown inputs can
be estimated and decoupled using the extended Double-Model Adaptive Estimation
approach without satisfying the existence condition. Numerical examples are
presented in which the performance of the proposed approach is compared to
methods from literature.


title: Normal forms in Cauchy-Riemann Geometry: a survey

abstract:
  One of effective ways to solve the equivalence problem and describe moduli
spaces for real submanifolds in complex space is the normal form approach. In
this survey, we outline some normal form constructions in CR-geometry and
formulate a number of open problems.


title: Classifying Material Implications over Minimal Logic

abstract:
  The so-called paradoxes of material implication have motivated the
development of many non-classical logics over the years
\cite{aA75,nB77,aA89,gP89,sH96}. In this note, we investigate some of these
paradoxes and classify them, over minimal logic. We provide proofs of
equivalence and semantic models separating the paradoxes where appropriate. A
number of equivalent groups arise, all of which collapse with unrestricted use
of double negation elimination. Interestingly, the principle \emph{ex falso
quodlibet}, and several weaker principles, turn out to be distinguishable,
giving perhaps supporting motivation for adopting minimal logic as the ambient
logic for reasoning in the possible presence of inconsistency.


title:
Characterization of the second- and third-order nonlinear optical
  susceptibilities of monolayer MoS$_2$ using multiphoton microscopy

abstract:
  We report second- and third-harmonic generation in monolayer MoS$_\mathrm{2}$
as a tool for imaging and accurately characterizing the material's nonlinear
optical properties under 1560 nm excitation. Using a surface nonlinear optics
treatment, we derive expressions relating experimental measurements to second-
and third-order nonlinear sheet susceptibility magnitudes, obtaining values of
$|\chi_s^{(2)}|=2.0\times10^{-20}$ m$^2$ V$^{-1}$ and for the first time for
monolayer MoS$_\mathrm{2}$, $|\chi_s^{(3)}|=1.7\times10^{-28}$ m$^3$ V$^{-2}$.
These sheet susceptibilities correspond to effective bulk nonlinear
susceptibility values of $|\chi_{b}^{(2)}|=2.9\times10^{-11}$ m V$^{-1}$ and
$|\chi_{b}^{(3)}|=2.4\times10^{-19}$ m$^2$ V$^{-2}$, accounting for the sheet
thickness. Experimental comparisons between MoS$_\mathrm{2}$ and graphene are
also performed, demonstrating $\sim$3.4 times stronger third-order sheet
nonlinearity in monolayer MoS$_\mathrm{2}$, highlighting the material's
potential for nonlinear photonics in the telecommunications C band.


title: Optimal Down Regulation of mRNA Translation

abstract:
  Down regulation of mRNA translation is an important problem in various
bio-medical domains ranging from developing effective medicines for tumors and
for viral diseases to developing attenuated virus strains that can be used for
vaccination. Here, we study the problem of down regulation of mRNA translation
using a mathematical model called the ribosome flow model (RFM). In the RFM,
the mRNA molecule is modeled as a chain of $n$ sites. The flow of ribosomes
between consecutive sites is regulated by $n+1$ transition rates. Given a set
of feasible transition rates, that models the outcome of all possible
mutations, we consider the problem of maximally down regulating the translation
rate by altering the rates within this set of feasible rates. Under certain
conditions on the feasible set, we show that an optimal solution can be
determined efficiently. We also rigorously analyze two special cases of the
down regulation optimization problem. Our results suggest that one must focus
on the position along the mRNA molecule where the transition rate has the
strongest effect on the protein production rate. However, this rate is not
necessarily the slowest transition rate along the mRNA molecule. We discuss
some of the biological implications of these results.


title: Critical behavior of noise-induced phase synchronization

abstract:
  In this article, we present a systematic study of the critical behavior of
phase oscillators with multiplicative noise from a thermodynamic equilibrium
approach. We have already presented the thermodynamics of phase noise
oscillators and mapped out in detail the behavior of free energy, entropy, and
specific heat in a previous work [P. D. Pinto, F.A. Oliveira, A.L.A. Penna,
Phys. Rev. E 93, 052220 (2016)], in which we also introduced the concept of
synchronization field. This proved to be important in order to understand the
effect of multiplicative noise in the synchronization of the system. Using this
approach, our aim is now to study analytically the critical behavior of this
system from which we derive a fluctuation-dissipation relation as well as the
critical exponents associated with the order parameter, specific heat, and
susceptibility. We show that the exponents obey the Rushbrooke and Widom
scaling laws.


title: Quantum Simulation of a Quantum Stochastic Walk

abstract:
  The study of quantum walks has been shown to have a wide range of
applications in areas such as artificial intelligence, the study of biological
processes, and quantum transport. The quantum stochastic walk, which allows for
incoherent movement of the walker, and therefore, directionality, is a
generalization on the fully coherent quantum walk. While a quantum stochastic
walk can always be described in Lindblad formalism, this does not mean that it
can be microscopically derived in the standard weak-coupling limit under the
Born-Markov approximation. This restricts the class of quantum stochastic walks
that can be experimentally realized in a simple manner. To circumvent this
restriction, we introduce a technique to simulate open system evolution on a
fully coherent quantum computer, using a quantum trajectories style approach.
We apply this technique to a broad class of quantum stochastic walks, and show
that they can be simulated with minimal experimental resources. Our work opens
the path towards the experimental realization of quantum stochastic walks on
large graphs with existing quantum technologies.


title:
Signals induced by charge-trapping in EDELWEISS FID detectors:
  analytical modeling and applications

abstract:
  The EDELWEISS-III direct dark matter search experiment uses cryogenic HP-Ge
detectors Fully covered with Inter-Digitized electrodes (FID). They are
operated at low fields ($<1\;\mathrm{V/cm}$), and as a consequence
charge-carrier trapping significantly affects both the ionization and heat
energy measurements. This paper describes an analytical model of the signals
induced by trapped charges in FID detectors based on the Shockley-Ramo theorem.
It is used to demonstrate that veto electrodes, initially designed for the sole
purpose of surface event rejection, can be used to provide a sensitivity to the
depth of the energy deposits, characterize the trapping in the crystals,
perform heat and ionization energy corrections and improve the ionization
baseline resolutions. These procedures are applied successfully to actual data.


title:
California Reservoir Drought Sensitivity and Exhaustion Risk Using
  Statistical Graphical Models

abstract:
  The ongoing California drought has highlighted the potential vulnerability of
state water management infrastructure to multi-year dry intervals. Due to the
high complexity of the network, dynamic storage changes across the California
reservoir system have been difficult to model using either conventional
statistical or physical approaches. Here, we analyze the interactions of
monthly volumes in a network of 55 large California reservoirs, over a period
of 136 months from 2004 to 2015, and we develop a latent-variable graphical
model of their joint fluctuations. We achieve reliable and tractable modeling
of the system because the model structure allows unique recovery of the
best-in-class model via convex optimization with control of the number of free
parameters. We extract a statewide `latent' influencing factor which turns out
to be highly correlated with both the Palmer Drought Severity Index (PDSI,
$\rho \approx 0.86$) and hydroelectric production ($\rho \approx 0.71$).
Further, the model allows us to determine system health measures such as
exhaustion probability and per-reservoir drought sensitivity. We find that as
PDSI approaches -6, there is a probability greater than 50\% of simultaneous
exhaustion of multiple large reservoirs.


title: Convex functions and means of matrices

abstract:
  In this article, we prove that convex functions and log-convex functions obey
certain general refinements that lead to several refinements and reverses of
well known inequalities for matrices, including Young's inequality, Heinz
inequality, the arithmetic-harmonic and the geometric-harmonic mean
inequalities.


title:
Repeatable Room Temperature Negative Differential Conductance in GaN/AlN
  Resonant Tunneling Diodes

abstract:
  Double barrier GaN/AlN resonant tunneling heterostructures have been grown by
molecular beam epitaxy on the (0001) plane of commercially available bulk GaN
substrates. Resonant tunneling diodes were fabricated; room temperature
current-voltage measurements reveal the presence of a negative differential
conductance region under forward bias with peak current densities of ~6.4
$kA/cm^2$ and a peak to valley current ratio of ~1.3. Reverse bias operation
presents a characteristic turn-on threshold voltage intimately linked to the
polarization fields present in the heterostructure. An analytic electrostatic
model is developed to capture the unique features of
polar-heterostructure-based resonant tunneling diodes; both the resonant and
threshold voltages are derived as a function of the design parameters and
polarization fields. Subsequent measurements confirm the repeatability of the
negative conductance and demonstrate that III-nitride tunneling
heterostructures are capable of robust resonant transport at room temperature.


title:
Real-time Decentralized and Robust Voltage Control in Distribution
  Networks

abstract:
  Voltage control plays an important role in the operation of electricity
distribution networks, especially when there is a large penetration of
renewable energy resources. In this paper, we focus on voltage control through
reactive power compensation and study how different information structures
affect the control performance. In particular, we first show that using only
voltage measurements to determine reactive power compensation is insufficient
to maintain voltage in the acceptable range. Then we propose two fully
decentralized and robust algorithms by adding additional information, which can
stabilize the voltage in the acceptable range. The one with higher complexity
can further minimize a cost of reactive power compensation in a particular
form. Both of the two algorithms use only local measurements and local
variables and require no communication. In addition, the two algorithms are
robust against heterogeneous update rates and delays.


title:
Constraints on Cosmic Distance Duality Relation from Cosmological
  Observations

abstract:
  In this paper, we use the model dependent method to revisit the constraint on
the well-known cosmic distance duality relation (CDDR). By using the latest
SNIa samples, such as Union2.1, JLA and SNLS, we find that the SNIa data alone
can not constrain the cosmic opacity parameter $\varepsilon$, which denotes the
deviation from the CDDR, $d_{\rm L} = d_{\rm A}(1+z)^{2+\varepsilon}$, very
well. The constraining power on $\varepsilon$ from the luminosity distance
indicator provided by SNIa and GRB is hardly to be improved at present. When we
include other cosmological observations, such as the measurements of Hubble
parameter, the baryon acoustic oscillations and the distance information from
cosmic microwave background, we obtain the tightest constraint on the cosmic
opacity parameter $\varepsilon$, namely the 68\% C.L. limit:
$\varepsilon=0.023\pm0.018$. Furthermore, we also consider the evolution of
$\varepsilon$ as a function of $z$ using two methods, the parametrization and
the principle component analysis, and do not find the evidence for the
deviation from zero. Finally, we simulate the future SNIa and Hubble
measurements and find the mock data could give very tight constraint on the
cosmic opacity $\varepsilon$ and verify the CDDR at high significance.


title:
State power and elite autonomy in a networked civil society: The board
  interlocking of Chinese non-profits

abstract:
  In response to failures of central planning, the Chinese government has
experimented not only with free-market trade zones, but with allowing
non-profit foundations to operate in a decentralized fashion. A network study
shows how these foundations have connected together by sharing board members,
in a structural parallel to what is seen in corporations in the United States
and Europe. This board interlocking leads to the emergence of an elite group
with privileged network positions. While the presence of government officials
on non-profit boards is widespread, government officials are much less common
in a subgroup of foundations that control just over half of all revenue in the
network. This subgroup, associated with business elites, not only enjoys higher
levels of within-elite links, but even preferentially excludes government
officials from the NGOs with higher degree. The emergence of this structurally
autonomous sphere is associated with major political and social events in the
state-society relationship. Cluster analysis reveals multiple internal
components within this sphere that share similar levels of network influence.
Rather than a core-periphery structure centered around government officials,
the Chinese non-profit world appears to be a multipolar one of distinct elite
groups, many of which achieve high levels of independence from direct
government control.


title: Content-Based Top-N Recommendation using Heterogeneous Relations

abstract:
  Top-$N$ recommender systems have been extensively studied. However, the
sparsity of user-item activities has not been well resolved. While many hybrid
systems were proposed to address the cold-start problem, the profile
information has not been sufficiently leveraged. Furthermore, the heterogeneity
of profiles between users and items intensifies the challenge. In this paper,
we propose a content-based top-$N$ recommender system by learning the global
term weights in profiles. To achieve this, we bring in PathSim, which could
well measures the node similarity with heterogeneous relations (between users
and items). Starting from the original TF-IDF value, the global term weights
gradually converge, and eventually reflect both profile and activity
information. To facilitate training, the derivative is reformulated into matrix
form, which could easily be paralleled. We conduct extensive experiments, which
demonstrate the superiority of the proposed method.


title:
The Dependent Random Measures with Independent Increments in Mixture
  Models

abstract:
  When observations are organized into groups where commonalties exist amongst
them, the dependent random measures can be an ideal choice for modeling. One of
the propositions of the dependent random measures is that the atoms of the
posterior distribution are shared amongst groups, and hence groups can borrow
information from each other. When normalized dependent random measures prior
with independent increments are applied, we can derive appropriate exchangeable
probability partition function (EPPF), and subsequently also deduce its
inference algorithm given any mixture model likelihood. We provide all
necessary derivation and solution to this framework. For demonstration, we used
mixture of Gaussians likelihood in combination with a dependent structure
constructed by linear combinations of CRMs. Our experiments show superior
performance when using this framework, where the inferred values including the
mixing weights and the number of clusters both respond appropriately to the
number of completely random measure used.


title: Prior based model checking

abstract:
  Model checking procedures are considered based on the use of the Dirichlet
process and relative belief. This combination is seen to lead to some unique
advantages for this problem. In particular, it avoids double use of the data
and prior-data conflict. Several examples have been incorporated, in which the
proposed approach exhibits excellent performance.


title:
Consistent analytic approach to the efficiency of collisional Penrose
  process

abstract:
  We propose a consistent analytic approach to the efficiency of collisional
Penrose process in the vicinity of a maximally rotating Kerr black hole. We
focus on a collision with arbitrarily high center-of-mass energy, which occurs
if either of the colliding particles has its angular momentum fine-tuned to the
critical value to enter the horizon. We show that if the fine-tuned particle is
ingoing on the collision, the upper limit of the efficiency is
$(2+\sqrt{3})(2-\sqrt{2})\simeq 2.186$, while if the fine-tuned particle is
bounced back before the collision, the upper limit is $(2+\sqrt{3})^{2}\simeq
13.93$. Despite earlier claims, the former can be attained for inverse Compton
scattering if the fine-tuned particle is massive and starts at rest at
infinity, while the latter can be attained for various particle reactions, such
as inverse Compton scattering and pair annihilation, if the fine-tuned particle
is either massless or highly relativistic at infinity. We discuss the
difference between the present and earlier analyses.


title: Gauge-Higgs EW and Grand Unification

abstract:
  4D Higgs field is identified with the extra-dimensional component of gauge
potentials in the gauge-Higgs unification scenario. $SO(5) \times U(1)$
gauge-Higgs EW unification in the Randall-Sundrum warped space is successful at
low energies. The Higgs field appears as an Aharonov-Bohm phase $\theta_H$ in
the fifth dimension. Its mass is generated at the quantum level and is finite.
The model yields almost the same phenomenology as the standard model for
$\theta_H < 0.1$, and predicts $Z'$ bosons around 6 - 10 TeV with very broad
widths. The scenario is genelarized to $SO(11)$ gauge-Higgs grand unification.
Fermions are introduced in the spinor and vector representations of $SO(11)$.
Proton decay is naturally forbidden.


title:
Can Turing machine be curious about its Turing test results? Three
  informal lectures on physics of intelligence

abstract:
  What is the nature of curiosity? Is there any scientific way to understand
the origin of this mysterious force that drives the behavior of even the
stupidest naturally intelligent systems and is completely absent in their
smartest artificial analogs? Can we build AI systems that could be curious
about something, systems that would have an intrinsic motivation to learn? Is
such a motivation quantifiable? Is it implementable? I will discuss this
problem from the standpoint of physics. The relationship between physics and
intelligence is a consequence of the fact that correctly predicted information
is nothing but an energy resource, and the process of thinking can be viewed as
a process of accumulating and spending this resource through the acts of
perception and, respectively, decision making. The natural motivation of any
autonomous system to keep this accumulation/spending balance as high as
possible allows one to treat the problem of describing the dynamics of thinking
processes as a resource optimization problem. Here I will propose and discuss a
simple theoretical model of such an autonomous system which I call the
Autonomous Turing Machine (ATM). The potential attractiveness of ATM lies in
the fact that it is the model of a self-propelled AI for which the only
available energy resource is the information itself. For ATM, the problem of
optimal thinking, learning, and decision-making becomes conceptually simple and
mathematically well tractable. This circumstance makes the ATM an ideal
playground for studying the dynamics of intelligent behavior and allows one to
quantify many seemingly unquantifiable features of genuine intelligence.


title: Central Limit Theorems for Gaps of Generalized Zeckendorf Decompositions

abstract:
  Zeckendorf proved that every integer can be written uniquely as a sum of
non-adjacent Fibonacci numbers $\{1,2,3,5,\dots\}$. This has been extended to
many other recurrence relations $\{G_n\}$ (with their own notion of a legal
decomposition) and to proving that the distribution of the number of summands
of an $M \in [G_n, G_{n+1})$ converges to a Gaussian as $n\to\infty$. We prove
that for any non-negative integer $g$ the average number of gaps of size $g$ in
many generalized Zeckendorf decompositions is $C_\mu n+d_\mu+o(1)$ for
constants $C_\mu > 0$ and $d_\mu$ depending on $g$ and the recurrence, the
variance of the number of gaps of size $g$ is similarly $C_\sigma n + d_\sigma
+ o(1)$ with $C_\sigma > 0$, and the number of gaps of size $g$ of an
$M\in[G_n,G_{n+1})$ converges to a Gaussian as $n\to\infty$. The proof is by
analysis of an associated two-dimensional recurrence; we prove a general result
on when such behavior converges to a Gaussian, and additionally re-derive other
results in the literature.


title: Differential equations and exact solutions in the moving sofa problem

abstract:
  The moving sofa problem, posed by L. Moser in 1966, asks for the planar shape
of maximal area that can move around a right-angled corner in a hallway of unit
width, and is conjectured to have as its solution a complicated shape derived
by Gerver in 1992. We extend Gerver's techniques by deriving a family of six
differential equations arising from the area-maximization property. We then use
this result to derive a new shape that we propose as a possible solution to the
"ambidextrous moving sofa problem," a variant of the problem previously studied
by Conway and others in which the shape is required to be able to negotiate a
right-angle turn both to the left and to the right. Unlike Gerver's
construction, our new shape can be expressed in closed form, and its boundary
is a piecewise algebraic curve. Its area is equal to $X+\arctan Y$, where $X$
and $Y$ are solutions to the cubic equations $x^2(x+3)=8$ and $x(4x^2+3)=1$,
respectively.


title: Aspects of a nonminimal conformal extension of the standard model

abstract:
  In this article we investigate a conformal extension of the standard model in
which the scalar sector consists of a standard model Higgs doublet, a real
gauge singlet and a real $SU(2)_{L}$ triplet. Focusing on the scenario where
the Higgs boson found at the LHC is identified as the pseudo-Nambu-Goldstone
boson of broken scale invariance, various theoretical and phenomenological
features of the model are discussed. In particular, we analyze the decay
pattern of the new scalar resonance. We also show that when the mass of this
new scalar resonance is far below the $WW$ threshold, the natural regions of
the parameter space are reduced by a constraint associated with the symmetry
enhancement due to the decoupling of the singlet scalar from the rest of the
system.


title:
Quantum synchronization and quantum state sharing in irregular complex
  network

abstract:
  We investigate quantum synchronization phenomenon within the complex network
constituted by coupled optomechanical systems and prove the unknown identical
quantum states can be shared or distributed in the quantum network even though
the topology is varying. Considering a channel constructed by quantum
correlation, we show that quantum synchronization can sustain and maintain high
levels in Markovian dissipation for a long time. We analyze state sharing
process between two typical complex networks, that is, a small-world network
corresponding to linear motif state sharing and a scale-free network
corresponding to whole network sharing, respectively. Our results predict that
linked nodes can be directly synchronized in small-world network, but the whole
network will be synchronized only if some specific synchronization conditions
are satisfied. Furthermore, we give the synchronization conditions analytically
through analyzing network dynamics. This proposal paves the way for studying
multi-interaction synchronization and achieving an effective quantum
information processing in complex network.


title: TITUS: the Tokai Intermediate Tank for the Unoscillated Spectrum

abstract:
  The TITUS, Tokai Intermediate Tank for Unoscillated Spectrum, detector, is a
proposed Gd-doped Water Cherenkov tank with a magnetised muon range detector
downstream. It is located at J-PARC at about 2 km from the neutrino target and
it is proposed as a potential near detector for the Hyper-Kamiokande
experiment. Assuming a beam power of 1.3 MW and 27.05 x 10^{21}
protons-on-target the sensitivity to CP and mixing parameters achieved by
Hyper-Kamiokande with TITUS as a near detector is presented. Also, the
potential of the detector for cross sections and Standard Model parameter
determination, supernova neutrino and dark matter are shown.


title: Algebraic subellipticity and dominability of blow-ups of affine spaces

abstract:
  Little is known about the behaviour of the Oka property of a complex manifold
with respect to blowing up a submanifold. A manifold is of Class $\mathscr A$
if it is the complement of an algebraic subvariety of codimension at least $2$
in an algebraic manifold that is Zariski-locally isomorphic to $\mathbb C^n$. A
manifold of Class $\mathscr A$ is algebraically subelliptic and hence Oka, and
a manifold of Class $\mathscr A$ blown up at finitely many points is of Class
$\mathscr A$. Our main result is that a manifold of Class $\mathscr A$ blown up
along an arbitrary algebraic submanifold (not necessarily connected) is
algebraically subelliptic. For algebraic manifolds in general, we prove that
strong algebraic dominability, a weakening of algebraic subellipticity, is
preserved by an arbitrary blow-up with a smooth centre. We use the main result
to confirm a prediction of Forster's famous conjecture that every open Riemann
surface may be properly holomorphically embedded into $\mathbb C^2$.


title: Verify LTL with Fairness Assumptions Efficiently

abstract:
  This paper deals with model checking problems with respect to LTL properties
under fairness assumptions. We first present an efficient algorithm to deal
with a fragment of fairness assumptions and then extend the algorithm to handle
arbitrary %fairness assumptions ones. Notably, by making use of some syntactic
transformations, our algorithm avoids to construct corresponding B\"uchi
automata for the whole fairness assumptions, which can be very large in
practice. We implement our algorithm in NuSMV and consider a large selection of
formulas. Our experiments show that in many cases our approach exceeds the
automata-theoretic approach up to several orders of magnitude, in both time and
memory.


title: Improved Recurrent Neural Networks for Session-based Recommendations

abstract:
  Recurrent neural networks (RNNs) were recently proposed for the session-based
recommendation task. The models showed promising improvements over traditional
recommendation approaches. In this work, we further study RNN-based models for
session-based recommendations. We propose the application of two techniques to
improve model performance, namely, data augmentation, and a method to account
for shifts in the input data distribution. We also empirically study the use of
generalised distillation, and a novel alternative model that directly predicts
item embeddings. Experiments on the RecSys Challenge 2015 dataset demonstrate
relative improvements of 12.8% and 14.8% over previously reported results on
the Recall@20 and Mean Reciprocal Rank@20 metrics respectively.


title:
Structural and electrical properties of Sn substituted double sintering
  derived Ni-Zn ferrite

abstract:
  The Sn substituted Ni-Zn ferrites were synthesized by the standard double
sintering technique using nano powders of nickel oxide (NiO), zinc oxide (ZnO),
iron oxide (Fe2O3) and tin oxide (SnO2). The structural and electrical
properties have been investigated by the X-ray diffraction, scanning electron
microscopy, DC resistivity and dielectric measurements. Extra intermediate
phase has been detected along with the inverse cubic spinel phase of Ni-Zn
ferrite. Enhancement of grain size is observed in Sn substituted Ni-Zn
ferrites. DC resistivity as a function of temperature has been investigated by
two probe method. The DC resistivity was found to decrease whereas the
dielectric constants increase with increasing Sn content in Ni-Zn ferrites. The
dielectric constant of the as prepared samples is high enough to use these
materials in miniaturized memory devices based capacitive components or energy
storage principles.


title:
Design and Performance Analysis of Depletion-Mode InSb Quantum-Well
  Field-Effect Transistor for Logic Applications

abstract:
  The design of a 1 micrometer gate length depletion-mode InSb quantum-well
field-effect transistor (QWFET) with a 10 nm-thick Al2O3 gate dielectric has
been optimized using a quantum corrected self-consistent Schrodinger-Poisson
(QCSP) and two dimensional drift-diffusion model. The model predicts a very
high electron mobility of 4.42 m2V-1s-1 at Vg= 0V, a small pinch off gate
voltage (Vp) of -0.25V, a maximum extrinsic transconductance (gm) of 4.94 S/mm
and a drain current density of more than 6.04 A/mm. A short-circuit
current-gain cut-off frequency (fT) of 374 GHz and a maximum oscillation
frequency (fmax) of 645 GHz are predicted for the device. These characteristics
make the device a potential candidate for low power, high-speed logic
electronic device applications.


title:
Thermal effects on the resonance fluorescence of doubly dressed
  artificial atoms

abstract:
  In this work, robustness of controlled density of optical states in doubly
driven artificial atoms is studied under phonon dissipation. By using both
perturbative and polaron approaches, we investigate the influence of
carrier-phonon interactions on the emission properties of a two-level
solid-state emitter, simultaneously coupled to two intense distinguishable
lasers. Phonon decoherence effects on the emission spectra are found modest up
to neon boiling temperatures ($\sim 30$ K), as compared with photon generation
at the Fourier transform limit obtained in absence of lattice vibrations (zero
temperature). These results show that optical switching and photonic modulation
by means of double dressing, do not require ultra low temperatures for
implementation, thus boosting its potential technological applications.


title:
Rank dependent bounds on mixedness and entanglement for quantum
  teleportation

abstract:
  Entanglement and mixedness of a bipartite mixed state resource are crucial
for the success of quantum teleportation. Upper bounds on measures of
mixedness, namely, von Neumann entropy and linear entropy beyond which the
bipartite state ceases to be useful for quantum teleportation are known in the
literature. In this work, we generalize these bounds and obtain rank dependent
upper bounds on von Nuemann entropy and linear entropy for an arbitrary
bipartite mixed state resource. We observe that the upper bounds on measures of
mixedness increase with increase in the rank. For two qubit mixed states, we
obtain rank dependent lower bound on the concurrence, a measure of
entanglement, below which the state is useless for quantum teleportation.
Werner state, which is a fourth rank state, exhibits the theoretical upper
bound on mixedness among two qubit mixed states. We construct Werner like
states of lower ranks and show that these states possess the theoretical rank
dependent upper bounds obtained on the measures of mixedness and theoretical
rank dependent lower bounds on the concurrence.


title:
On which groups can arise as the canonical group of a spherical latin
  bitrade

abstract:
  We address a question of Cavenagh and Wanless asking: which finite abelian
groups arise as the canonical group of a spherical latin bitrade? We prove the
existence of an infinite family of finite abelian groups that do not arise as
canonical groups of spherical latin bitrades. Using a connection between
abelian sandpile groups of digraphs underlying directed Eulerian spherical
embeddings, we go on to provide several, general, families of finite abelian
groups that do arise as canonical groups. These families include: any abelian
group in which each component of the Smith Normal Form has composite order; any
abelian group with Smith Normal Form
$\mathbb{Z}^{n}_p\oplus\left(\bigoplus_{i=1}^k\mathbb{Z}_{pa_i}\right)$, where
$1\leq k$, $2\leq a_1,a_2,\ldots, a_k,p$ and $n\leq 1+2\sum_{i=1}^k(a_i - 1)$;
and with one exception and three potential exceptions any abelian group of rank
two.


title: Parametrization of stochastic multiscale triads

abstract:
  We discuss applications of a recently developed method for model reduction
based on linear response theory of weakly coupled dynamical systems. We apply
the weak coupling method to simple stochastic differential equations with slow
and fast degrees of freedom. The weak coupling model reduction method results
in general in a non-Markovian system, we therefore discuss the Markovianization
of the system to allow for straightforward numerical integration. We compare
the applied method to the equations obtained through homogenization in the
limit of large time scale separation between slow and fast degrees of freedom.
We look at ensemble spread from a fixed initial condition, correlation
functions and exit times from domain. The weak coupling method gives better
results in all test cases, albeit with a higher numerical cost.


title:
Anomalous time delays and quantum weak measurements in optical
  micro-resonators

abstract:
  We study inelastic resonant scattering of a Gaussian wave packet with the
parameters close to a zero of the complex scattering coefficient. We
demonstrate, both theoretically and experimentally, that such near-zero
scattering can result in anomalously-large time delays and frequency shifts of
the scattered wave packet. Furthermore, we reveal a close analogy of these
anomalous shifts with the spatial and angular Goos-H\"anchen optical beam
shifts, which are amplified via quantum weak measurements. However, in contrast
to other beam-shift and weak-measurement systems, we deal with a
one-dimensional scalar wave without any intrinsic degrees of freedom. It is the
non-Hermitian nature of the system that produces its rich and non-trivial
behaviour. Our results are generic for any scattering problem, either quantum
or classical. As an example, we consider the transmission of an optical pulse
through a nano-fiber with a side-coupled toroidal micro-resonator. The zero of
the transmission coefficient corresponds to the critical coupling conditions.
Experimental measurements of the time delays near the critical-coupling
parameters verify our weak-measurement theory and demonstrate amplification of
the time delay from the typical inverse resonator linewidth scale to the pulse
duration scale.


title:
Algebraic solutions of shape-invariant position-dependent effective mass
  systems

abstract:
  Keeping in view the ordering ambiguity that arises due to the presence of
position-dependent effective mass in the kinetic energy term of the
Hamiltonian, a general scheme for obtaining algebraic solutions of quantum
mechanical systems with position-dependent effective mass is discussed. We
quantize the Hamiltonian of the pertaining system by using symmetric ordering
of the operators concerning momentum and the spatially varying mass, initially
proposed by von Roos and Levy-Leblond. The algebraic method, used to obtain the
solutions, is based on the concepts of supersymmetric quantum mechanics and
shape invariance. In order to exemplify the general formalism a class of
non-linear oscillators has been considered. This class includes the particular
example of a one-dimensional oscillator with different position-dependent
effective mass profiles. Explicit expressions for the eigenenergies and
eigenfunctions in terms of generalized Hermite polynomials are presented.
Moreover, properties of these modified Hermite polynomials, like existence of
generating function and recurrence relations among the polynomials have also
been studied. Furthermore, it has been shown that in the harmonic limit, all
the results for the linear harmonic oscillator are recovered.


title:
On the Geometric Regularity Conditions for the 3D Navier-Stokes
  Equations

abstract:
  We prove geometrically improved version of Prodi-Serrin type blow-up
criterion. Let $v$ and $\omega$ be the velocity and the vorticity of solutions
to the 3D Navier-Stokes equations and denote $\{f\}_+=\max\{f, 0\}$ , $Q_T=\Bbb
R^3\times (0, T)$. If $\left\{\left( v \times \frac{\omega}{|\omega|}
\right)\cdot \frac{\Lambda^{\beta}v}{|\Lambda^{\beta}v|}\right\}_+ \in
L^{\gamma, \alpha}_{x,t} (Q_T)$ with $3/\gamma +2/\alpha \leq 1$ for some
$\gamma >3$ and $1 \leq \beta \leq 2$, then the local smooth solution $v$ of
the Navier-Stokes equations on $(0,T)$ can be continued to $(0, T+\delta)$ for
some $\delta >0$. We also prove localized version of a special case of this.
Let $v$ be a suitable weak solution to the Navier-tokes equations in a
space-time domain containing $z_0= (x_0, t_0)$, let $Q_{z_0, r}=B_{x_0, r}
\times (t_0-r^2, t_0)$ be a parabolic cylinder in the domain. We show that if
either $\left\{\left( v \times \frac{\omega}{|\omega|}\right) \cdot
\frac{\nabla \times \omega}{|\nabla \times \omega|}\right\}_{+} \in L^{\gamma,
\alpha}_{x,t}(Q_{z_0, r})$ with $\frac{3}{\gamma}+\frac{2}{\alpha} \leq 1$, or
$\left\{\left(\frac{v}{|v|} \times \omega\right) \cdot \frac{\nabla \times
\omega}{|\nabla \times \omega|}\right\}_{+} \in L^{\gamma,
\alpha}_{x,t}(Q_{z_0, r})$ with $\frac{3}{\gamma}+\frac{2}{\alpha} \leq 2$,
($\gamma \geq 2$, $\alpha \geq 2$), then $z_0$ is a regular point for $v$. This
improves previous local regularity criteria for the suitable weak solutions.


title:
Frequency conversion between UV and telecom wavelengths in a lithium
  niobate waveguide for quantum communication with Yb+ trapped ions

abstract:
  We study and demonstrate the frequency conversion of UV radiation, resonant
with 369.5 nm transition in Yb+ ions to the C-band wavelength 1580.3 nm and
vice-versa using a reverse proton-exchanged waveguide in periodically poled
lithium niobate. Our integrated device can interface trapped Yb+ ions with
telecom infrastructure for the realization of an Yb+ based quantum repeater
protocol and to efficiently distribute entanglement over long distances. We
analyse the single photon frequency conversion efficiency from the 369.525 nm
to the telecom wavelength and its dependence on pump power, device length and
temperature. The single-photon noise generated by spontaneous Raman scattering
of the pump is also measured. From this analysis we estimate a single photon
conversion efficiency of 9% is achievable with our technology with almost
complete suppression of the Raman noise.


title: Beamforming for Full-Duplex Multiuser MIMO Systems

abstract:
  We solve a sum rate maximization problem of full-duplex (FD) multiuser
multiple-input multiple-output (MU-MIMO) systems. Since additional
self-interference (SI) in the uplink channel and co-channel interference (CCI)
in the downlink channel are coupled in FD communication, the downlink and
uplink multiuser beamforming vectors are required to be jointly designed.
However, the joint optimization problem is non-convex and hard to solve due to
the coupled effect. To properly address the coupled design issue, we
reformulate the problem into an equivalent uplink channel problem, using the
uplink and downlink channel duality known as MAC-BC duality. Then, using
minorization maximization (MM) algorithm based on an affine approximation, we
obtain a solution for the reformulated problem. In addition, without any
approximation and thus performance degradation, we develop an alternating
algorithm based on iterative water-filling (IWF) to solve the non-convex
problem. The proposed algorithms warrant fast convergence and low computational
complexity.


title:
Differentiability of the Dirichlet to Neumann map under movements of
  polygonal inclusions with an application to shape optimization

abstract:
  In this paper we derive rigorously the derivative of the Dirichlet to Neumann
map and of the Neumann to Dirichlet map of the conductivity equation with
respect to movements of vertices of triangular conductivity inclusions. We
apply this result to formulate an optimization problem based on a shape
derivative approach.


title: Propagators and Solvers for the Algebra of Modular Systems

abstract:
  To appear in the proceedings of LPAR 21.
  Solving complex problems can involve non-trivial combinations of distinct
knowledge bases and problem solvers. The Algebra of Modular Systems is a
knowledge representation framework that provides a method for formally
specifying such systems in purely semantic terms. Formally, an expression of
the algebra defines a class of structures. Many expressive formalism used in
practice solve the model expansion task, where a structure is given on the
input and an expansion of this structure in the defined class of structures is
searched (this practice overcomes the common undecidability problem for
expressive logics). In this paper, we construct a solver for the model
expansion task for a complex modular systems from an expression in the algebra
and black-box propagators or solvers for the primitive modules. To this end, we
define a general notion of propagators equipped with an explanation mechanism,
an extension of the alge- bra to propagators, and a lazy conflict-driven
learning algorithm. The result is a framework for seamlessly combining solving
technology from different domains to produce a solver for a combined system.


title: Are Discrepancies in RANS Modeled Reynolds Stresses Random?

abstract:
  In the turbulence modeling community, significant efforts have been made to
quantify the uncertainties in the Reynolds-Averaged Navier--Stokes (RANS)
models and to improve their predictive capabilities. Of crucial importance in
these efforts is the understanding of the discrepancies in the RANS modeled
Reynolds stresses. However, to what extent these discrepancies can be predicted
or whether they are completely random remains a fundamental open question. In
this work we used a machine learning algorithm based on random forest
regression to predict the discrepancies. The success of the
regression--prediction procedure indicates that, to a large extent, the
discrepancies in the modeled Reynolds stresses can be explained by the mean
flow feature, and thus they are universal quantities that can be extrapolated
from one flow to another, at least among different flows sharing the same
characteristics such as separation. This finding has profound implications to
the future development of RANS models, opening up new possibilities for
data-driven predictive turbulence modeling.


title: Scaling of foreign attractiveness for countries and states

abstract:
  People's behavior on online social networks, which store geo-tagged
information showing where people were or are at the moment, can provide
information about their offline life as well. In this paper we present one
possible research direction that can be taken using Flickr dataset of publicly
available geo-tagged media objects (e.g., photographs, videos). Namely, our
focus is on investigating attractiveness of countries or smaller large-scale
composite regions (e.g., US states) for foreign visitors where attractiveness
is defined as the absolute number of media objects taken in a certain state or
country by its foreign visitors compared to its population size. We also
consider it together with attractiveness of the destination for the
international migration, measured through publicly available dataset provided
by United Nations. By having those two datasets, we are able to look at
attractiveness from two different perspectives: short-term and long-term one.
As our previous study showed that city attractiveness for Spanish cities
follows a superlinear trend, here we want to see if the same law is also
applicable to country/state (i.e., composite regions) attractiveness. Finally,
we provide one possible explanation for the obtained results.


title:
Using an Artificial Neural Network to Classify Multi-component Emission
  Line Fits

abstract:
  We present The Machine, an artificial neural network (ANN) capable of
differentiating between the numbers of Gaussian components needed to describe
the emission lines of Integral Field Spectroscopic (IFS) observations. Here we
show the preliminary results of the S7 first data release (Siding Spring
Southern Seyfert Spectro- scopic Snapshot Survey, Dopita et al. 2015) and SAMI
Galaxy Survey (Sydney-AAO Multi-object Integral Field Unit, Croom et al. 2012)
to classify whether the emission lines in each spatial pixel are composed of 1,
2, or 3 different Gaussian components. Previously this classification has been
done by individual people, taking an hour per galaxy. This time investment is
no longer feasible with the large spectroscopic surveys coming online.


title: On Some Subclass of Harmonic Close-to-convex Mappings

abstract:
  Let $\mathcal{H}$ denote the class of harmonic functions $f$ in $\mathbb{D}:=
\{z\in \mathbb{C}:|z| < 1\}$ normalized by $f(0) = 0 = f_z(0) -1$. For $\alpha
\geq 0$, we consider the following class
$$\mathcal{W}^0_{\mathcal{H}}(\alpha):= \{f = h + \overline{g}\in\mathcal{H}:
{\rm Re\,}(h'(z) + \alpha z h''(z)) >|g'(z) + \alpha z g''(z)|, \quad z\in
\mathbb{D}\}. $$ In this paper, we first prove the coefficient conjecture of
Clunie and Sheil-Small for functions in the class
$\mathcal{W}^0_{\mathcal{H}}(\alpha)$. We also prove growth theorem,
convolution, convex combination properties for functions in the class
$\mathcal{W}^0_{\mathcal{H}}(\alpha)$. Finally, we determine the value of $r$
so that the partial sums of functions in the class
$\mathcal{W}^0_{\mathcal{H}}(\alpha)$ are close-to-convex in $|z|<r$.


title: Phaseless Rcovery using Gauss-Newton Method

abstract:
  In this paper, we develop a concrete algorithm for phase retrieval, which we
refer to as Gauss-Newton algorithm. In short, this algorithm starts with a good
initial estimation, which is obtained by a modified spectral method, and then
update the iteration point by a Gauss-Newton iteration step. We prove that a
re-sampled version of this algorithm quadratically converges to the solution
for the real case with the number of random measurements being nearly minimal.
Numerical experiments also show that Gauss-Newton method has better performance
over the other algorithms.


title: Data Sketching for Large-Scale Kalman Filtering

abstract:
  In an age of exponentially increasing data generation, performing inference
tasks by utilizing the available information in its entirety is not always an
affordable option. The present paper puts forth approaches to render tracking
of large-scale dynamic processes via a Kalman filter affordable, by processing
a reduced number of data. Three distinct methods are introduced for reducing
the number of data involved in the correction step of the filter. Towards this
goal, the first two methods employ random projections and innovation-based
censoring to effect dimensionality reduction and measurement selection
respectively. The third method achieves reduced complexity by leveraging
sequential processing of observations and selecting a few informative updates
based on an information-theoretic metric. Simulations on synthetic data,
compare the proposed methods with competing alternatives, and corroborate their
efficacy in terms of estimation accuracy over complexity reduction. Finally,
monitoring large networks is considered as an application domain, with the
proposed methods tested on Kronecker graphs to evaluate their efficiency in
tracking traffic matrices and time-varying link costs.


title: Structural and electronic phase evolution of Tin dioxide

abstract:
  We investigate the effect of controlled annealing on the structural and
electronic phase evolution of Tin dioxide from Tin (II) oxyhydroxide prepared
by simple precipitation method. Thermogravimetric analysis suggests a complex
weight loss-gain process involved, passing through an intermediate phase of tin
oxide nanoparticles. The probable structural and electronic phase evolution is
discussed using detailed X-ray diffraction and X-ray photoelectron spectroscopy
investigations.


title:
Chandra observations of the HII complex G5.89-0.39 and TeV gamma-ray
  source HESSJ1800-240B

abstract:
  We present the results of our investigation, using a Chandra X-ray
observation, into the stellar population of the massive star formation region
G5.89-0.39, and its potential connection to the coincident TeV gamma-ray source
HESSJ1800-240B. G5.89-0.39 comprises two separate HII regions G5.89-0.39A and
G5.89-0.39B (an ultra-compact HII region). We identified 159 individual X-ray
point sources in our observation using the source detection algorithm
\texttt{wavdetect}. 35 X-ray sources are associated with the HII complex
G5.89-0.39. The 35 X-ray sources represent an average unabsorbed luminosity
(0.3-10\,keV) of $\sim10^{30.5}$\,erg/s, typical of B7-B5 type stars. The
potential ionising source of G5.89-0.39B known as Feldt's star is possibly
identified in our observation with an unabsorbed X-ray luminosity suggestive of
a B7-B5 star. The stacked energy spectra of these sources is well-fitted with a
single thermal plasma APEC model with kT$\sim$5\,keV, and column density
N$_{\rm H}=2.6\times10^{22}$\,cm$^{-2}$ (A$_{\rm V}\sim 10$). The residual
(source-subtracted) X-ray emission towards G5.89-0.39A and B is about 30\% and
25\% larger than their respective stacked source luminosities. Assuming this
residual emission is from unresolved stellar sources, the total
B-type-equivalent stellar content in G5.89-0.39A and B would be 75 stars,
consistent with an earlier estimate of the total stellar mass of hot stars in
G5.89-0.39. We have also looked at the variability of the 35 X-ray sources in
G5.89-0.39. Ten of these sources are flagged as being variable. Further studies
are needed to determine the exact causes of the variability, however the
variability could point towards pre-main sequence stars. Such a stellar
population could provide sufficient kinetic energy to account for a part of the
GeV to TeV gamma-ray emission in the source HESSJ1800-240B.


title: Some topics on the $Z_3$-graded exterior algebras

abstract:
  A $Z_3$-graded Hopf algebra structure of exterior algebra with two generators
is introduced. Two covariant differential calculus on the $Z_3$-graded exterior
algebra are presented. Using the generators and their partial derivatives a
Grassmann-Heisenberg algebra is constructed. An R-matrix which satisfies graded
Yang-Baxter equations is obtained. A $Z_3$-graded universal enveloping algebra
$U_q(\widetilde{gl}(2))$ is constructed with the quadratic elements of the
Grassmann-Weyl algebra.


title:
STransE: a novel embedding model of entities and relationships in
  knowledge bases

abstract:
  Knowledge bases of real-world facts about entities and their relationships
are useful resources for a variety of natural language processing tasks.
However, because knowledge bases are typically incomplete, it is useful to be
able to perform link prediction or knowledge base completion, i.e., predict
whether a relationship not in the knowledge base is likely to be true. This
paper combines insights from several previous link prediction models into a new
embedding model STransE that represents each entity as a low-dimensional
vector, and each relation by two matrices and a translation vector. STransE is
a simple combination of the SE and TransE models, but it obtains better link
prediction performance on two benchmark datasets than previous embedding
models. Thus, STransE can serve as a new baseline for the more complex models
in the link prediction task.


title: Minimum Fill-In: Inapproximability and Almost Tight Lower Bounds

abstract:
  Given an $n*n$ sparse symmetric matrix with $m$ nonzero entries, performing
Gaussian elimination may turn some zeroes into nonzero values. To maintain the
matrix sparse, we would like to minimize the number $k$ of these changes, hence
called the minimum fill-in problem. Agrawal et al.~[FOCS'90] developed the
first approximation algorithm, based on early heuristics by George [SIAM J
Numer Anal 10] and by Lipton et al.~[SIAM J Numer Anal 16]. The objective
function they used is $m+k$, the number of nonzero elements after elimination.
An approximation algorithm using $k$ as the objective function was presented by
Natanzon et al.~[STOC'98]. These two versions are incomparable in terms of
approximation.
  Parameterized algorithms for the problem was first studied by Kaplan et
al.~[FOCS'94]. Fomin & Villanger [SODA'12] recently gave an algorithm running
in time $2^{O(\sqrt{k} \log k)}+n^{O(1)}$.
  Hardness results of this problem are surprisingly scarce, and the few known
ones are either weak or have to use nonstandard complexity conjectures. The
only inapproximability result by Wu et al.~[IJCAI'15] applies to only the
objective function $m+k$, and is grounded on the Small Set Expansion
Conjecture. The only nontrivial parameterized lower bounds, by Bliznets et
al.~[SODA'16], include a very weak one based on ETH, and a strong one based on
hardness of subexponential-time approximation of the minimum bisection problem
on regular graphs. For both versions of the problem, we exclude the existence
of PTASs, assuming P$\ne$NP, and the existence of $2^{O(n^{1-\delta})}$-time
approximation schemes for any positive $\delta$, assuming ETH. It also implies
a $2^{O(k^{1/2-\delta})} n^{O(1)}$ parameterized lower bound. Behind these
results is a new reduction from vertex cover, which might be of its own
interest: All previous reductions for similar problems are from some kind of
graph layout problems.


title: A new look at Levi-Civita connection in noncommutative geometry

abstract:
  We prove the existence and uniqueness of Levi-Civita connections for strongly
sigma-compatible pseudo-Riemannian metrics on tame differential calculi. Such
pseudo-Riemannian metrics properly contain the classes of bilinear metrics as
well as their conformal deformations. This extends the previous results in
references 9 and 10. Star-compatibility of Levi-Civita connections for bilinear
pseudo-Riemannian metrics are also discussed.


title: (Total) Domination in Prisms

abstract:
  With the aid of hypergraph transversals it is proved that $\gamma_t(Q_{n+1})
= 2\gamma(Q_n)$, where $\gamma_t(G)$ and $\gamma(G)$ denote the total
domination number and the domination number of $G$, respectively, and $Q_n$ is
the $n$-dimensional hypercube. More generally, it is shown that if $G$ is a
bipartite graph, then $\gamma_t(G \square K_2) = 2\gamma(G)$. Further, we show
that the bipartite condition is essential by constructing, for any $k \ge 1$, a
(non-bipartite) graph $G$ such that $\gamma_t (G \square K_2 ) = 2\gamma(G) -
k$. Along the way several domination-type identities for hypercubes are also
obtained.


title: From pseudo-holomorphic functions to the associated real manifold

abstract:
  This paper studies first the differential inequalities that make it possible
to build a global theory of pseudo-holomorphic functions in the case of one or
several complex variables. In the case of one complex dimension, we prove that
the differential inequalities describing pseudo-holomorphic functions can be
used to define a one-real-dimensional manifold (by the vanishing of a function
with nonzero gradient), which is here a 1-parameter family of plane curves. On
studying the associated envelopes, such a parameter can be eliminated by
solving two nonlinear partial differential equations. The classical
differential geometry of curves can be therefore exploited to get a novel
perspective on the equations describing the global theory of pseudo-holomorphic
functions.


title:
Application of Monte Carlo Simulations to Improve Basketball Shooting
  Strategy

abstract:
  The underlying physics of basketball shooting seems to be a straightforward
example of the Newtonian mechanics that can easily be traced by numerical
methods. However, a human basketball player does not make use of all the
possible basketball trajectories. Instead, a basketball player will build up a
database of successful shots and select the trajectory that has the greatest
tolerance to small variations of the real world. We simulate the basketball
player's shooting training as a Monte Carlo sequence to build optimal shooting
strategies, such as the launch speed and angle of the basketball, and whether
to take a direct shot or a bank shot, as a function of the player's court
positions and height. The phase space volume that belongs to the successful
launch velocities generated by Monte Carlo simulations are then used as the
criterion to optimize a shooting strategy that incorporates not only
mechanical, but human factors as well.


title: Properties of the turbulent/non-turbulent interface in boundary layers

abstract:
  The turbulent/non-turbulent interface is analysed in a direct numerical
simulation of a boundary layer in the range $Re_\theta=2800-6600$, with
emphasis on the behaviour of the relatively large-scale fractal intermittent
region. This requires the introduction of a new definition of the distance
between a point and a general surface, which is compared with the more usual
vertical distance to the top of the layer. Interfaces are obtained by
thresholding the enstrophy field and the magnitude of the rate-of-strain
tensor, and it is concluded that, while the former are physically relevant
features, the latter are not. By varying the threshold, a topological
transition is identified as the interface moves from the free stream into the
turbulent core. A vorticity scale is defined that collapses that transition for
different Reynolds numbers, roughly equivalent to the root-mean-squared
vorticity at the edge of the boundary layer. Conditionally averaged flow
variables are analysed as functions of the new distance, both within and
outside the interface. It is found that the interface contains a nonequilibrium
layer whose thickness scales well with the Taylor microscale, enveloping a
self-similar layer spanning a fixed fraction of the boundary-layer thickness.
Interestingly, the straining structure of the flow is similar in both regions.
Irrotational pockets within the turbulent core are also studied. They form a
self-similar set whose size decreases with increasing depth, presumably due to
break-up by the turbulence, but the rate of viscous diffusion is independent of
the pocket size. The raw data used in the analysis are freely available from
our web page (http://torroja.dmt.upm.es).


title:
Novel Interplay between High-Tc Superconductivity and Antiferromagnetism
  in Tl-based Six-CuO2-Layered Cuprates : 205 Tl and 63 Cu-NMR Probes

abstract:
  We report $^{63}$Cu- and $^{205}$Tl-NMR studies on six-layered ($n$=6)
high-$T_c$ superconducting (SC) cuprate TlBa$_2$Ca$_5$Cu$_6$O$_{14+\delta}$
(Tl1256) with $T_c\sim$100 K, which reveal that antiferromagnetic (AFM) order
takes place below $T_{\rm N}\sim$170 K. In this compound, four underdoped inner
CuO$_2$ planes ($n$(IP)=4) sandwiched by two outer planes (OPs) are responsible
for the onset of AFM order, whereas the nearly optimally-doped OPs responsible
for the onset of bulk SC. It is pointed out that an increase in the
out-of-plane magnetic interaction within an intra-unit-cell causes $T_{\rm
N}\sim$ 45 K for Tl1245 with $n$(IP)=3 to increase to $\sim$170 K for Tl1256
with $n$(IP)=4. It is remarkable that the marked increase in $T_{\rm N}$ and
the AFM moments for the IPs does not bring about any reduction in $T_c$, since
$T_c\sim 100$ K is maintained for both compounds with nearly optimally doped
OP. We highlight the fact that the SC order for $n\ge5$ is mostly dominated by
the long-range in-plane SC correlation even in the multilayered structure,
which is insensitive to the magnitude of $T_{\rm N}$ and the AFM moments at the
IPs or the AFM interaction among the IPs. These results demonstrate a novel
interplay between the SC and AFM orders when the charge imbalance between the
IPs and OP is significantly large.


title:
Matrix product solution to a 2-species TASEP with open integrable
  boundaries

abstract:
  We present an explicit representation for the matrix product ansatz for some
two-species TASEP with open boundary conditions. The construction relies on the
integrability of the models, a property that constrains the possible rates at
the boundaries. The realisation is built on a tensor product of copies of the
DEHP algebras. Using this explicit construction, we are able to calculate the
partition function of the models. The densities and currents in the stationary
state are also computed. It leads to the phase diagram of the models. Depending
on the values of the boundary rates, we obtain for each species shock waves,
maximal current, or low/high densities phases.


title: Planetary nebulae that cannot be explained by binary systems

abstract:
  We examine the images of hundreds of planetary nebulae (PNe) and find that
for about one in six PNe the morphology is too `messy' to be accounted for by
models of stellar binary interaction. We speculate that interacting triple
stellar systems shaped these PNe. In this preliminary study we qualitatively
classify PNe by one of four categories. (1) PNe that show no need for a
tertiary star to account for their morphology. (2) PNe whose structure
possesses a pronounced departure from axial-symmetry and/or mirror-symmetry. We
classify these, according to our speculation, as `having a triple stellar
progenitor'. (3) PNe whose morphology possesses departure from axial-symmetry
and/or mirror-symmetry, but not as pronounced as in the previous class, and are
classified as `likely shaped by triple stellar system'. (4) PNe with minor
departure from axial-symmetry and/or mirror symmetry that could have been as
well caused by an eccentric binary system or the inter-stellar medium. These
are classified as `maybe shaped by a triple stellar system'. Given a weight
eta_t=1, eta_l=0.67, eta_m=0.33 to classes 2, 3 and 4, respectively, we find
that according to our assumption about 13 - 21% of PNe have been shaped by
triple stellar systems. Although in some evolutionary scenarios not all three
stars survive the evolution, we encourage the search for a triple stellar
systems at the center of some PNe.


title:
Compiler-Assisted Workload Consolidation For Efficient Dynamic
  Parallelism on GPU

abstract:
  GPUs have been widely used to accelerate computations exhibiting simple
patterns of parallelism - such as flat or two-level parallelism - and a degree
of parallelism that can be statically determined based on the size of the input
dataset. However, the effective use of GPUs for algorithms exhibiting complex
patterns of parallelism, possibly known only at runtime, is still an open
problem. Recently, Nvidia has introduced Dynamic Parallelism (DP) in its GPUs.
By making it possible to launch kernels directly from GPU threads, this feature
enables nested parallelism at runtime. However, the effective use of DP must
still be understood: a naive use of this feature may suffer from significant
runtime overhead and lead to GPU underutilization, resulting in poor
performance. In this work, we target this problem. First, we demonstrate how a
naive use of DP can result in poor performance. Second, we propose three
workload consolidation schemes to improve performance and hardware utilization
of DP-based codes, and we implement these code transformations in a
directive-based compiler. Finally, we evaluate our framework on two categories
of applications: algorithms including irregular loops and algorithms exhibiting
parallel recursion. Our experiments show that our approach significantly
reduces runtime overhead and improves GPU utilization, leading to speedup
factors from 90x to 3300x over basic DP-based solutions and speedups from 2x to
6x over flat implementations.


title: Methods for improving estimators of truncated circular parameters

abstract:
  In decision theoretic estimation of parameters in Euclidean space
$\mathbb{R}^p$, the action space is chosen to be the convex closure of the
estimand space. In this paper, the concept has been extended to the estimation
of circular parameters of distributions having support as a circle, torus or
cylinder. As directional distributions are of curved nature, existing methods
for distributions with parameters taking values in $\mathbb{R}^p$ are not
immediately applicable here. A circle is the simplest one-dimensional
Riemannian manifold. We employ concepts of convexity, projection, etc., on
manifolds to develop sufficient conditions for inadmissibility of estimators
for circular parameters. Further invariance under a compact group of
transformations is introduced in the estimation problem and a complete class
theorem for equivariant estimators is derived. This extends the results of
Moors [J. Amer. Statist. Assoc. 76 (1981) 910-915] on $\mathbb{R}^p$ to
circles. The findings are of special interest to the case when a circular
parameter is truncated. The results are implemented to a wide range of
directional distributions to obtain improved estimators of circular parameters.


title:
On the sequence made by the linear combination of k-Fibonacci and
  k-Lucas sequences

abstract:
  The Fibonacci sequence is a sequence of numbers that has been studied for
hundreds of years. In this paper, we introduce the new sequence S_{k,n} with
initial conditions S_{k,0} = 2b and S_{k,1} = bk + a, which is generated by the
recurrence relation S_{k,n} = kS_{k,n-1} +S{k,n-2} for n >= 2, where a, b, k
are real numbers. Using the sequence S_{k,n}, we introduce and prove some
special identities. Also, we deal with the circulant and skew circulant
matrices for the sequence S_{k,n}.


title: Proof of a Conjecture of Z.-W. Sun on Trigonometric Series

abstract:
  Recently, Z. W. Sun introduced a sequence $(S_n)_{n\geq 0}$, where
$S_n=\frac{\binom{6n}{3n} \binom{3n}{n}}{2(2n+1)\binom{2n}{n}}$, and found one
congruence and two convergent series on $S_n$ by {\tt{Mathematica}}.
Furthermore, he proposed some related conjectures. In this paper, we first give
analytic proofs of his two convergent series and then confirm one of his
conjectures by invoking series expansions of $\sin(t\arcsin(x))$ and
$\cos(t\arcsin(x)).$


title:
A Neural Network Approach to Joint Modeling Social Networks and Mobile
  Trajectories

abstract:
  The accelerated growth of mobile trajectories in location-based services
brings valuable data resources to understand users' moving behaviors. Apart
from recording the trajectory data, another major characteristic of these
location-based services is that they also allow the users to connect whomever
they like. A combination of social networking and location-based services is
called as location-based social networks (LBSN). As shown in previous works,
locations that are frequently visited by socially-related persons tend to be
correlated, which indicates the close association between social connections
and trajectory behaviors of users in LBSNs. In order to better analyze and mine
LBSN data, we present a novel neural network model which can joint model both
social networks and mobile trajectories. In specific, our model consists of two
components: the construction of social networks and the generation of mobile
trajectories. We first adopt a network embedding method for the construction of
social networks: a networking representation can be derived for a user. The key
of our model lies in the component of generating mobile trajectories. We have
considered four factors that influence the generation process of mobile
trajectories, namely user visit preference, influence of friends, short-term
sequential contexts and long-term sequential contexts. To characterize the last
two contexts, we employ the RNN and GRU models to capture the sequential
relatedness in mobile trajectories at different levels, i.e., short term or
long term. Finally, the two components are tied by sharing the user network
representations. Experimental results on two important applications demonstrate
the effectiveness of our model. Especially, the improvement over baselines is
more significant when either network structure or trajectory data is sparse.


title:
Blume-Capel ferromagnet driven by propagating and standing magnetic
  field wave: Dynamical modes and nonequilibrium phase transition

abstract:
  The dynamical responses of Blume-Capel (S=1) ferromagnet to the plane
propagating (with fixed frequency and wavelength) and standing magnetic field
waves are studied sepa- rately in two dimensions by extensive Monte Carlo
simulation. Depending on the values of temperature, amplitude of the
propagating magnetic field and the strength of anisotropy, two different
dynamical phases are observed. For a fixed value of anisotropy and the
amplitude of the propagating magnetic field, the system undergoes a dynamical
phase transition from a driven spin wave propagating phase to a pinned or spin
frozen state as the system is cooled down. The time averaged magnetisation over
a full cycle of the propagating magnetic field plays the role of the dynamic
order parameter. A comprehensive phase diagram is plotted in the plane formed
by the amplitude of the propagating wave and the temperature of the system. It
is found that the phase boundary shrinks inward as the anisotropy increases.
The phase boundary, in the plane described by the strength of the anisotropy
and temperature, is also drawn. This phase boundary was observed to shrink
inward as the field amplitude increases.


title:
Efficient Dynamic Pinning of Parallelized Applications by Distributed
  Reinforcement Learning

abstract:
  This paper introduces a resource allocation framework specifically tailored
for addressing the problem of dynamic placement (or pinning) of parallelized
applications to processing units. Under the proposed setup each thread of the
parallelized application constitutes an independent decision maker (or agent),
which (based on its own prior performance measurements and its own prior
CPU-affinities) decides on which processing unit to run next. Decisions are
updated recursively for each thread by a resource manager/scheduler which runs
in parallel to the application's threads and periodically records their
performances and assigns to them new CPU affinities. For updating the
CPU-affinities, the scheduler uses a distributed reinforcement-learning
algorithm, each branch of which is responsible for assigning a new placement
strategy to each thread. According to this algorithm, prior allocations are
going to be reinforced in the future proportionally to their prior performance.
The proposed resource allocation framework is flexible enough to address
alternative optimization criteria, such as maximum average processing speed and
minimum speed variance among threads. We demonstrate analytically that
convergence to locally-optimal placements is achieved asymptotically. Finally,
we validate these results through experiments in Linux platforms.