title: A Quantum Version of Sch\"oning's Algorithm Applied to Quantum 2-SAT

abstract:
  We study a quantum algorithm that consists of a simple quantum Markov
process, and we analyze its behavior on restricted versions of Quantum 2-SAT.
We prove that the algorithm solves this decision problem with high probability
for n qubits, L clauses, and promise gap c in time O(n^2 L^2 c^{-2}). If the
Hamiltonian is additionally polynomially gapped, our algorithm efficiently
produces a state that has high overlap with the satisfying subspace. The Markov
process we study is a quantum analogue of Sch\"oning's probabilistic algorithm
for k-SAT.


title:
Spatial Dispersal of Bacterial Colonies Induces a Dynamical Transition
  From Local to Global Quorum Sensing

abstract:
  Bacteria communicate using external chemical signals called autoinducers (AI)
in a process known as quorum sensing (QS). QS efficiency is reduced by both
limitations of AI diffusion and potential interference from neighboring
strains. There is thus a need for predictive theories of how spatial community
structure shapes information processing in complex microbial ecosystems. As a
step in this direction, we apply a reaction-diffusion model to study
autoinducer signaling dynamics in a single-species community as a function of
the spatial distribution of colonies in the system. We predict a dynamical
transition between a local quorum sensing (LQS) regime, with the AI signaling
dynamics primarily controlled by the local population densities of individual
colonies, and a global quorum sensing (GQS) regime, with the dynamics being
dependent on collective inter-colony diffusive interactions. The crossover
between LQS to GQS is intimately connected to a tradeoff between the signaling
network's latency, or speed of activation, and its throughput, or the total
spatial range over which all the components of the system communicate.


title: Knowledge Transfer for Scene-specific Motion Prediction

abstract:
  When given a single frame of the video, humans can not only interpret the
content of the scene, but also they are able to forecast the near future. This
ability is mostly driven by their rich prior knowledge about the visual world,
both in terms of (i) the dynamics of moving agents, as well as (ii) the
semantic of the scene. In this work we exploit the interplay between these two
key elements to predict scene-specific motion patterns. First, we extract patch
descriptors encoding the probability of moving to the adjacent patches, and the
probability of being in that particular patch or changing behavior. Then, we
introduce a Dynamic Bayesian Network which exploits this scene specific
knowledge for trajectory prediction. Experimental results demonstrate that our
method is able to accurately predict trajectories and transfer predictions to a
novel scene characterized by similar elements.


title: On a Shape-Invariant Hazard Regression Model

abstract:
  In survival analysis, Cox model is widely used for most clinical trial data.
Alternatives include the additive hazard model, the accelerated failure time
(AFT) model and a more general transformation model. All these models assume
that the effects for all covariates are on the same scale. However, it is
possible that for different covariates, the effects are on different scales. In
this paper, we propose a shape-invariant hazard regression model that allows us
to estimate the multiplicative treatment effect with adjustment of covariates
that have non-multiplicative effects. We propose moment-based inference
procedures for the regression parameters. We also discuss the risk prediction
and goodness of fit test for our proposed model. Numerical studies show good
finite sample performance of our proposed estimator. We applied our method to
Veteran's Administration (VA) lung cancer data and the HIVNET 012 data. For the
latter, we found that single-dose nevirapine treatment has a significant
improvement for 18-month survival with appropriate adjustment for maternal CD4
counts and virus load.


title: Exploring the nature of broadband variability in the FSRQ 3C 273

abstract:
  Detailed investigation of broadband flux variability in the blazar 3C 273
allows us to probe the location and size of emission regions and their physical
conditions. We report the results on correlation studies of the flaring
activity observed between 2008 and 2012. The observed broadband variations were
investigated using the structure function and the discrete correlation
function, and power spectral density analysis (PSD) methods. The PSD analysis
showed that the optical/IR light curve slopes are consistent with the slope of
white noise processes, while, the PSD slopes at radio, X-ray and gamma-ray
energies are consistent with red-noise processes. The flux variations at
gamma-ray and mm-radio bands are found to be significantly correlated. Using
the estimated time lag of (110\pm27) days between gamma-ray and radio light
curves, we constrained the location of the gamma-ray emission region at a
de-projected distance of 1.2\pm0.9 pc from the jet apex. Flux variations at
X-ray bands were found to have a significant correlation with variations at
both radio and \gamma-rays energies. The correlation between X-rays and
gamma-rays light curves suggests presence of two components responsible for the
X-ray emission. A negative time lag of -(50\pm20) days, where the X-rays are
leading the emission, suggests X-rays are emitted closer to the jet apex from a
compact region at a distance of ~(0.5\pm0.4) pc from the jet apex. A positive
time lag of (110\pm20) days suggests jet-base origin of the other X-ray
component at ~(4--5)~pc from the jet apex. The flux variations at radio
frequencies were found to be well correlated with each other such that the
variations at higher frequencies are leading the lower frequencies, which could
be expected in the standard shock-in-jet model.


title: Cavity design for high-frequency axion dark matter detectors

abstract:
  In an effort to extend the usefulness of microwave cavity detectors to higher
axion masses, above ~8 $\mu$eV (~2 GHz), a numerical trade study of cavities
was conducted to investigate the merit of using variable periodic post arrays
and regulating vane designs for higher-frequency searches. The results show
that both designs could be used to develop resonant cavities for high-mass
axion searches. Multiple configurations of both methods obtained the scanning
sensitivity equivalent to approximately 4 coherently coupled cavities with a
single tuning rod.


title: On the biregular geometry of the Fulton-MacPherson compactification

abstract:
  Let $X[n]$ be the Fulton-MacPherson compactification of the configuration
space of $n$ ordered points on a smooth projective variety $X$. We prove that
if either $n\neq 2$ or $\dim(X)\geq 2$, then the connected component of the
identity of $Aut(X[n])$ is isomorphic to the connected component of the
identity of $Aut(X)$. When $X = C$ is a curve of genus $g(C)\neq 1$ we classify
the dominant morphisms $C[n]\rightarrow C[r]$, and thanks to this we manage to
compute the whole automorphism group of $C[n]$, namely $Aut(C[n])\cong
S_n\times Aut(C)$ for any $n\neq 2$, while $Aut(C[2])\cong S_2\ltimes
(Aut(C)\times Aut(C))$. Furthermore, we extend these results on the
automorphisms to the case where $X = C_1\times ... \times C_r$ is a product of
curves of genus $g(C_i)\geq 2$. Finally, using the techniques developed to deal
with Fulton-MacPherson spaces, we study the automorphism groups of some
Kontsevich moduli spaces $\overline{M}_{0,n}(\mathbb{P}^N,d)$.


title: The complex Airy operator with a semi-permeable barrier

abstract:
  We consider a suitable extension of the complex Airy operator, $-d^2/dx^2 +
ix$, on the real line with a transmission boundary condition at the origin. We
provide a rigorous definition of this operator and study its spectral
properties. In particular, we show that the spectrum is discrete, the space
generated by the generalized eigenfunctions is dense in $L^2$ (completeness),
and we analyze the decay of the associated semi-group. We also present explicit
formulas for the integral kernel of the resolvent in terms of Airy functions,
investigate its poles, and derive the resolvent estimates.


title: Effective quantum gravity observables and locally covariant QFT

abstract:
  Perturbative algebraic quantum field theory (pAQFT) is a mathematically
rigorous framework that allows to construct models of quantum field theories on
a general class of Lorentzian manifolds. Recently this idea has been applied
also to perturbative quantum gravity, treated as an effective theory. The
difficulty was to find the right notion of observables that would in an
appropriate sense be diffeomorphism invariant. In this article I will outline a
general framework that allows to quantize theories with local symmetries (this
includes infinitesimal diffeomorphism transformations) with the use of the BV
(Batalin-Vilkovisky) formalism. This approach has been successfully applied to
effective quantum gravity in a recent paper by R. Brunetti, K. Fredenhagen and
myself. In the same paper we also proved perturbative background independence
of the quantized theory, which is going to be discussed in the present work as
well.


title: Attractors in spacetimes and time functions

abstract:
  We develop a new approach to the existence of time functions on Lorentzian
manifolds, based on Conley's work regarding Lyapunov functions for dynamical
systems. We recover Hawking's result that a stably causal admits a time
function through a more general result giving the existence of a continuous
function that is non decreasing along all future directed causal curves, and
increasing along such curves that lie outside a special region of the
spacetime, called the chain recurrent set, which is empty for stably causal
spacetimes. The construction is based on a notion of attractive sets in
spacetimes.


title: Multi-Scale Convolutional Neural Networks for Time Series Classification

abstract:
  Time series classification (TSC), the problem of predicting class labels of
time series, has been around for decades within the community of data mining
and machine learning, and found many important applications such as biomedical
engineering and clinical prediction. However, it still remains challenging and
falls short of classification accuracy and efficiency. Traditional approaches
typically involve extracting discriminative features from the original time
series using dynamic time warping (DTW) or shapelet transformation, based on
which an off-the-shelf classifier can be applied. These methods are ad-hoc and
separate the feature extraction part with the classification part, which limits
their accuracy performance. Plus, most existing methods fail to take into
account the fact that time series often have features at different time scales.
To address these problems, we propose a novel end-to-end neural network model,
Multi-Scale Convolutional Neural Networks (MCNN), which incorporates feature
extraction and classification in a single framework. Leveraging a novel
multi-branch layer and learnable convolutional layers, MCNN automatically
extracts features at different scales and frequencies, leading to superior
feature representation. MCNN is also computationally efficient, as it naturally
leverages GPU computing. We conduct comprehensive empirical evaluation with
various existing methods on a large number of benchmark datasets, and show that
MCNN advances the state-of-the-art by achieving superior accuracy performance
than other leading methods.


title: Short Literature Review for a General Player Model Based on Behavlets

abstract:
  We present the first in a series of three academic essays which deal with the
question of how to build a generalized player model. We begin with a
proposition: a general model of players requires parameters for the subjective
experience of play, including at least: player psychology, game structure, and
actions of play. Based on this proposition, we pose three linked research
questions, which make incomplete progress toward a generalised player model:
RQ1 what is a necessary and sufficient foundation to a general player model?;
RQ2 can such a foundation improve performance of a computational
intelligence-based player model?; and RQ3 can such a player model improve
efficacy of adaptive artificial intelligence in games? We set out the arguments
behind these research questions in each of the three essays, presented as three
preprints. The first essay, in this preprint, reviews the literature for the
core foundations for a general player model. We then propose a plan for future
work to systematically extend the review and thus provide an empirical answer
to RQ1 above. This work will directly support the proposed approach to address
RQ2 and RQ3 above. This review was developed to support our 'Behavlets'
approach to player modelling; therefore if citing this work, please use the
relevant citation: Cowley B, Charles D. Behavlets: a Method for Practical
Player Modelling using Psychology-Based Player Traits and Domain Specific
Features. User Modelling and User-Adapted Interaction. 2016 Feb 8; online
(Special Issue on Personality in Personalized Systems):1-50.


title:
Gravity, as a classical regulator for the Higgs field, and the origin of
  rest masses and electric charge

abstract:
  The classical Einstein--Standard Model system with conformally invariant
coupling of the Higgs field to gravity is investigated. We show that the
energy-momentum tensor is not polynomial in the Higgs field, and hence it may
have two singularities: In cosmological spacetimes the usual Big Bang type
singularity with diverging matter field variables, and a second, less violent
one (Small Bang), in which it is only the geometry that is singular but the
matter field variables remain finite. In generic spacetimes, the latter
provides a finite, universal upper bound for the pointwise norm of the Higgs
field in terms of Newton's gravitational constant.
  We also show that, in the presence of Friedman--Robertson--Walker or
Kantowski--Sachs symmetries, the energy density can have finite local minimum
only if the transitivity hypersurfaces of the spacetime symmetries are locally
hyperboloidal and their mean curvature is less than a finite critical value. In
particular, in the very early era of an expanding universe or in a nearly
spherically symmetric black hole near the central singularity, the Higgs sector
does not have any instantaneous vacuum state, and hence its rest mass is not
defined, and, via the Brout--Englert--Higgs (BEH) mechanism, the gauge and
spinor fields do not get non-zero rest mass. For smaller mean curvature
instantaneous symmetry breaking vacuum states of the Higgs sector emerge,
yielding non-zero rest mass and electric charge for some of the gauge and
spinor fields via the BEH mechanism. These rest masses are decreasing with
decreasing mean curvature, but the charge remains constant. It is also shown
that globally defined instantaneous vacuum states that are invariant with
respect to the spacetime symmetries do not exist at all in the $k=1,0$
cosmological models and in Kantowski--Sachs spacetimes (e.g. inside spherically
symmetric black holes).


title:
Locally Conservative Continuous Galerkin FEM for Pressure Equation in
  Two-Phase Flow Model in Subsurfaces

abstract:
  A typical two-phase model for subsurface flow couples the Darcy equation for
pressure and a transport equation for saturation in a nonlinear manner. In this
paper, we study a combined method consisting of continuous Galerkin finite
element methods (CGFEMs) followed by a post-processing technique for Darcy
equation and finite volume method (FVM) with upwind schemes for the saturation
transport equation, in which the coupled nonlinear problem is solved in the
framework of operator decomposition. The postprocessing technique is applied to
CGFEM solutions to obtain locally conservative fluxes which ensures accuracy
and robustness of the FVM solver for the saturation transport equation. We
applied both upwind scheme and upwind scheme with slope limiter for FVM on
triangular meshes in order to eliminate the non-physical oscillations. Various
numerical examples are presented to demonstrate the performance of the overall
methodology.


title:
Construction of Locally Conservative Fluxes for High Order Continuous
  Galerkin Finite Element Methods

abstract:
  We propose a simple post-processing technique for linear and high order
continuous Galerkin Finite Element Methods (CGFEMs) to obtain locally
conservative flux field. The post-processing technique requires solving an
auxiliary problem on each element independently which results in solving a
linear algebra system whose size is low for any order CGFEM. The
post-processing could have been done directly from the finite element solution
that results in locally conservative flux on the element. However, the normal
flux is not continuous at the elemental boundary. To construct locally
conservative flux field whose normal component is also continuous, we propose
to do the post-processing on the nodal-centered control volumes which are
constructed from the original finite element mesh. We show that the
post-processed solution converges in an optimal fashion to the true solution in
an H1 semi-norm. We present various numerical examples to demonstrate the
performance of the post-processing technique.


title: Molecular components in P-wave charmed-strange mesons

abstract:
  Results obtained by various experiments show that the $D_{s0}^{\ast}(2317)$
and $D_{s1}(2460)$ mesons are very narrow states located below the $DK$ and
$D^{\ast}K$ thresholds, respectively. This is markedly in contrast with the
expectations of naive quark models and heavy quark symmetry. Motivated by a
recent lattice study which addresses the mass shifts of the $c\bar{s}$ ground
states with quantum numbers $J^{P}=0^{+}$ ($D_{s0}^{\ast}(2317)$) and
$J^{P}=1^{+}$ ($D_{s1}(2460)$) due to their coupling with $S$-wave
$D^{(\ast)}K$ thresholds, we perform a similar analysis within a
nonrelativistic constituent quark model in which quark-antiquark and
meson-meson degrees of freedom are incorporated. The quark model has been
applied to a wide range of hadronic observables and thus the model parameters
are completely constrained. The coupling between quark-antiquark and
meson-meson Fock components is done using a $^{3}P_{0}$ model in which its only
free parameter $\gamma$ has been elucidated performing a global fit to the
decay widths of mesons that belong to different quark sectors, from light to
heavy. We observe that the coupling of the $0^{+}$ $(1^{+})$ meson sector to
the $DK$ $(D^{\ast}K)$ threshold is the key feature to simultaneously lower the
masses of the corresponding $D_{s0}^{\ast}(2317)$ and $D_{s1}(2460)$ states
predicted by the naive quark model and describe the $D_{s1}(2536)$ meson as the
$1^{+}$ state of the $j_{q}^{P}=3/2^{+}$ doublet predicted by heavy quark
symmetry, reproducing its strong decay properties. Our calculation allows to
introduce the coupling with the $D$-wave $D^{\ast}K$ channel and the
computation of the probabilities associated with the different Fock components
of the physical state.


title: Atomic clocks and dark-matter signatures

abstract:
  Recent developments in searches for dark-matter candidates with atomic clocks
are reviewed. The intended audience is the atomic clock community.


title: Some metric and homotopy properties of partial isometries

abstract:
  We show that ||u*u - v*v|| \leq ||u - v|| for partial isometries u and v.
There is a stronger inequality if both u and v are extreme points of the unit
ball of a C*-algebra, and both inequalities are sharp. If u and v are partial
isometries in a C*-algebra A such that ||u - v|| < 1, then u and v are
homotopic through partial isometries in A. If both u and v are extremal, then
it is sufficient that ||u - v|| < 2. The constants 1 and 2 are both sharp. We
also discuss the continuity points of the map which assigns to each closed
range element of A the partial isometry in its canonical polar decomposition.


title:
A note on finiteness conditions for the non-abelian tensor square of
  groups

abstract:
  Let $G$ be a group. We denote by $\nu(G)$ a certain extension of the
non-abelian tensor square $G \otimes G$ by $G \times G$. We prove that if $G$
is a finitely generated group in which the set of all simple tensors
$T_{\otimes}(G)$ is finite, then the non-abelian tensor square $G \otimes G$
and the group $\nu(G)$ are finite. Moreover, we show that if $G$ is a locally
residually finite group in which the set of simple tensors $T_{\otimes}(H)$ is
finite for every proper finitely generated subgroup $H$ of $G$, then the group
$\nu(G)$ is locally finite.


title:
Magneto-reflection spectroscopy of monolayer transition-metal
  dichalcogenide semiconductors in pulsed magnetic fields

abstract:
  We describe recent experimental efforts to perform polarization-resolved
optical spectroscopy of monolayer transition-metal dichalcogenide
semiconductors in very large pulsed magnetic fields to 65 tesla. The
experimental setup and technical challenges are discussed in detail, and
temperature-dependent magneto-reflection spectra from atomically thin tungsten
disulphide (WS$_2$) are presented. The data clearly reveal not only the valley
Zeeman effect in these 2D semiconductors, but also the small quadratic exciton
diamagnetic shift from which the very small exciton size can be directly
inferred. Finally, we present model calculations that demonstrate how the
measured diamagnetic shifts can be used to constrain estimates of the exciton
binding energy in this new family of monolayer semiconductors.


title:
A formal Riemannian structure on conformal classes and uniqueness for
  the $\sigma_{2}$-Yamabe problem

abstract:
  We define a new formal Riemannian metric on a conformal classes of
four-manifolds in the context of the $\sigma_2$-Yamabe problem. Exploiting this
new variational structure we show that solutions are unique unless the manifold
is conformally equivalent to the round sphere.


title: New proofs of Melzak's identity

abstract:
  In their recent book on combinatorial identities, Quaintance and Gould
devoted one chapter to Melzak's identity. We give new proofs for this identity
and its generalization.


title: The Dimension and Minimum Distance of Two Classes of Primitive BCH Codes

abstract:
  Reed-Solomon codes, a type of BCH codes, are widely employed in communication
systems, storage devices and consumer electronics. This fact demonstrates the
importance of BCH codes -- a family of cyclic codes -- in practice. In theory,
BCH codes are among the best cyclic codes in terms of their error-correcting
capability. A subclass of BCH codes are the narrow-sense primitive BCH codes.
However, the dimension and minimum distance of these codes are not known in
general. The objective of this paper is to determine the dimension and minimum
distances of two classes of narrow-sense primitive BCH codes with design
distances $\delta=(q-1)q^{m-1}-1-q^{\lfloor (m-1)/2\rfloor}$ and
$\delta=(q-1)q^{m-1}-1-q^{\lfloor (m+1)/2\rfloor}$. The weight distributions of
some of these BCH codes are also reported. As will be seen, the two classes of
BCH codes are sometimes optimal and sometimes among the best linear codes
known.


title:
A mixed precision semi-Lagrangian algorithm and its performance on
  accelerators

abstract:
  In this paper we propose a mixed precision algorithm in the context of the
semi-Lagrangian discontinuous Galerkin method. The performance of this approach
is evaluated on a traditional dual socket workstation as well as on a Xeon Phi
and an NVIDIA K80. We find that the mixed precision algorithm can be
implemented efficiently on these architectures. This implies that, in addition
to the considerable reduction in memory, a substantial increase in performance
can be observed as well. Moreover, we discuss the relative performance of our
implementations.


title: Narrow-Sense BCH Codes over $\gf(q)$ with Length $n=\frac{q^m-1}{q-1}$

abstract:
  Cyclic codes over finite fields are widely employed in communication systems,
storage devices and consumer electronics, as they have efficient encoding and
decoding algorithms. BCH codes, as a special subclass of cyclic codes, are in
most cases among the best cyclic codes. A subclass of good BCH codes are the
narrow-sense BCH codes over $\gf(q)$ with length $n=(q^m-1)/(q-1)$. Little is
known about this class of BCH codes when $q>2$. The objective of this paper is
to study some of the codes within this class. In particular, the dimension, the
minimum distance, and the weight distribution of some ternary BCH codes with
length $n=(3^m-1)/2$ are determined in this paper. A class of ternary BCH codes
meeting the Griesmer bound is identified. An application of some of the BCH
codes in secret sharing is also investigated.


title: Practical Encoder and Decoder for Power Constrained QC-LDPC lattices

abstract:
  LDPC lattices were the first family of lattices that equipped with iterative
decoding algorithms under which they perform very well in high dimensions. In
this paper, we introduce quasi cyclic low density parity check (QC-LDPC)
lattices as a special case of LDPC lattices with one binary QC-LDPC code as
their underlying code. These lattices are obtained from Construction A of
lattices providing us to encode them efficiently using shift registers. To
benefit from an encoder with linear complexity in dimension of the lattice, we
obtain the generator matrix of these lattices in "quasi cyclic" form. We
provide a low-complexity decoding algorithm of QC-LDPC lattices based on sum
product algorithm. To design lattice codes, QC-LDPC lattices are combined with
nested lattice shaping that uses the Voronoi region of a sublattice for code
shaping. The shaping gain and shaping loss of our lattice codes with dimensions
$40$, $50$ and $60$ using an optimal quantizer, are presented. Consequently, we
establish a family of lattice codes that perform practically close to the
sphere bound.


title: Graphs Drawing through Fuzzy Clustering

abstract:
  Many problems can be presented in an abstract form through a wide range of
binary objects and relations which are defined over problem domain. In these
problems, graphical demonstration of defined binary objects and solutions is
the most suitable representation approach. In this regard, graph drawing
problem discusses the methods for transforming combinatorial graphs to
geometrical drawings in order to visualize them. This paper studies the
force-directed algorithms and multi-surface techniques for drawing general
undirected graphs. Particularly, this research describes force-directed
approach to model the drawing of a general graph as a numerical optimization
problem. So, it can use rich knowledge which is presented as an established
system by the numerical optimization. Moreover, this research proposes the
multi-surface approach as an efficient tool for overcoming local minimums in
standard force-directed algorithms. Next, we introduce a new method for
multi-surface approach based on fuzzy clustering algorithms.


title: Semi-supervised Word Sense Disambiguation with Neural Models

abstract:
  Determining the intended sense of words in text - word sense disambiguation
(WSD) - is a long standing problem in natural language processing. Recently,
researchers have shown promising results using word vectors extracted from a
neural network language model as features in WSD algorithms. However, a simple
average or concatenation of word vectors for each word in a text loses the
sequential and syntactic information of the text. In this paper, we study WSD
with a sequence learning neural net, LSTM, to better capture the sequential and
syntactic patterns of the text. To alleviate the lack of training data in
all-words WSD, we employ the same LSTM in a semi-supervised label propagation
classifier. We demonstrate state-of-the-art results, especially on verbs.


title: Unifying impacts in granular matter from quicksand to cornstarch

abstract:
  A sharp transition between liquefaction and transient solidification is
observed during impact on a granular suspension depending on the initial
packing fraction. We demonstrate, via high-speed pressure measurements and a
two-phase modeling, that this transition is controlled by a coupling between
the granular pile dilatancy and the interstitial fluid pressure generated by
the impact. Our results provide a generic mechanism for explaining the wide
variety of impact responses in particulate media, from dry quicksand in powders
to impact-hardening in shear-thickening suspensions like cornstarch.


title:
Charge and heat transport of soft nanosystems in the presence of
  time-dependent perturbations

abstract:
  Soft nanosystems are electronic nanodevices, such as suspended carbon
nanotubes or molecular junctions, whose transport properties are modulated by
soft internal degrees of freedom, for example slow vibrational modes. In this
review, effects of the electron-vibration coupling on the charge and heat
transport of soft nanoscopic systems are theoretically investigated in the
presence of time-dependent perturbations, such as a forcing antenna or pumping
terms between the leads and the nanosystem. A well established approach valid
for non-equilibrium adiabatic regimes is generalized to the case where external
time-dependent perturbations are present. Then, a number of relevant
applications of the method are reviewed for systems composed by a quantum dot
(or molecule) described by a single electronic level coupled to a vibrational
mode. Before introducing time-dependent perturbations, the range of validity of
the adiabatic approach is discussed showing that a very good agreement with the
results of an exact quantum calculation is obtained in the limit of low level
occupation. Aim of this review has been to discuss common features of different
soft nanosystems under external drive. The most interesting effects induced by
time-dependent perturbations are obtained when the external forcing is nearly
resonant with the slow vibrational modes. Indeed, not only the external forcing
can enhance the electronic response, but it also induces nonlinear regimes
where the interplay between electronic and vibrational degrees of freedom plays
a major role.


title:
Meaningful timescales from Monte Carlo simulations of molecular systems
  with hard-core interactions

abstract:
  A new Markov Chain Monte Carlo method for simulating the dynamics of
molecular systems characterized by hard-core interactions is introduced. In
contrast to traditional Kinetic Monte Carlo approaches, where the state of the
system is associated with minima in the energy landscape, in the proposed
method, the state of the system is associated with the set of paths traveled by
the atoms and the transition probabilities for an atom to be displaced are
proportional to the corresponding velocities. In this way, the number of
possible state-to-state transitions is reduced to a discrete set, and a direct
link between the Monte Carlo time step and true physical time is naturally
established. The resulting rejection-free algorithm is validated against
event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics
of hard disks converge to the exact results with decreasing displacement size.


title:
Profiling vs. Time vs. Content: What does Matter for Top-k Publication
  Recommendation based on Twitter Profiles? - An Extended Technical Report

abstract:
  So far it is unclear how different factors of a scientific publication
recommender system based on users' tweets have an influence on the
recommendation performance. We examine three different factors, namely
profiling method, temporal decay, and richness of content. Regarding profiling,
we compare CF-IDF that replaces terms in TF-IDF by semantic concepts, HCF-IDF
as novel hierarchical variant of CF-IDF, and topic modeling. As temporal decay
functions, we apply sliding window and exponential decay. In terms of the
richness of content, we compare recommendations using both full-texts and
titles of publications and using only titles. Overall, the three factors make
twelve recommendation strategies. We have conducted an online experiment with
123 participants and compared the strategies in a within-group design. The best
recommendations are achieved by the strategy combining CF-IDF, sliding window,
and with full-texts. However, the strategies using the novel HCF-IDF profiling
method achieve similar results with just using the titles of the publications.
Therefore, HCF-IDF can make recommendations when only short and sparse data is
available.


title: First Passage of a Randomly Accelerated Particle

abstract:
  In the random acceleration process, a point particle is accelerated according
to $\ddot{x}=\eta(t)$, where the right hand side represents Gaussian white
noise with zero mean. We begin with the case of a particle with initial
position $x_0$ and initial velocity $v_0$ and review the statistics of its
first arrival at the origin and its first return to the origin. Multiple
returns to the origin, motion with a constant force in addition to a random
force, and persistence properties for several boundary conditions at the origin
are also considered. Next we review first-exit properties of a randomly
accelerated particle from the finite interval $0<x<1$. Then the close
connection between the extreme value statistics of a randomly accelerated
particle and its first-passage properties is discussed. Finally some
applications where first-passage statistics of the random acceleration process
play a role are considered.


title: The cosmological constant and the energy of gravitational radiation

abstract:
  We propose a definition of mass for characteristic hypersurfaces in
asymptotically vacuum space-times with non-vanishing cosmological constant
$\Lambda \in {\mathbb R}^*$, generalising the definition of Trautman and Bondi
for $\Lambda=0$. We show that our definition reduces to some standard
definitions in several situations. We establish a balance formula linking the
characteristic mass and a suitably defined renormalised volume of the null
hypersurface, generalising the positivity identity of one of us (PTC) and Paetz
proved when $\Lambda=0$.


title: Optimal dividend payments for a two-dimensional insurance risk process

abstract:
  We consider a two-dimensional optimal dividend problem in the context of two
branches of an insurance company with compound Poisson surplus processes
dividing claims and premia in some specified proportions. We solve the
stochastic control problem of maximizing expected cumulative discounted
dividend payments (among all admissible dividend strategies) until ruin of at
least one company. We prove that the value function is the smallest viscosity
supersolution of the respective Hamilton-Jacobi-Bellman equation and we
describe the optimal strategy. We analize some numerical examples.


title:
Cyclical properties of supply-side and demand-side shocks in oil-based
  commodity markets

abstract:
  Oil markets profoundly influence world economies through determination of
prices of energy and transports. Using novel methodology devised in frequency
domain, we study the information transmission mechanisms in oil-based commodity
markets. Taking crude oil as a supply-side benchmark and heating oil and
gasoline as demand-side benchmarks, we document new stylized facts about
cyclical properties of the transmission mechanism generated by volatility
shocks with heterogeneous frequency responses. Our first key finding is that
shocks to volatility with response shorter than one week are increasingly
important to the transmission mechanism over the studied period. Second,
demand-side shocks to volatility are becoming increasingly important in
creating short-run connectedness. Third, the supply-side shocks to volatility
resonating in both the long run and short run are important sources of
connectedness.


title: On the Separability of Stochastic Geometric Objects, with Applications

abstract:
  In this paper, we study the linear separability problem for stochastic
geometric objects under the well-known unipoint/multipoint uncertainty models.
Let $S=S_R \cup S_B$ be a given set of stochastic bichromatic points, and
define $n = \min\{|S_R|, |S_B|\}$ and $N = \max\{|S_R|, |S_B|\}$. We show that
the separable-probability (SP) of $S$ can be computed in $O(nN^{d-1})$ time for
$d \geq 3$ and $O(\min\{nN \log N, N^2\})$ time for $d=2$, while the expected
separation-margin (ESM) of $S$ can be computed in $O(nN^{d})$ time for $d \geq
2$. In addition, we give an $\Omega(nN^{d-1})$ witness-based lower bound for
computing SP, which implies the optimality of our algorithm among all those in
this category. Also, a hardness result for computing ESM is given to show the
difficulty of further improving our algorithm. As an extension, we generalize
the same problems from points to general geometric objects, i.e., polytopes
and/or balls, and extend our algorithms to solve the generalized SP and ESM
problems in $O(nN^{d})$ and $O(nN^{d+1})$ time, respectively. Finally, we
present some applications of our algorithms to stochastic convex-hull related
problems.


title:
Active Detection and Localization of Textureless Objects in Cluttered
  Environments

abstract:
  This paper introduces an active object detection and localization framework
that combines a robust untextured object detection and 3D pose estimation
algorithm with a novel next-best-view selection strategy. We address the
detection and localization problems by proposing an edge-based registration
algorithm that refines the object position by minimizing a cost directly
extracted from a 3D image tensor that encodes the minimum distance to an edge
point in a joint direction/location space. We face the next-best-view problem
by exploiting a sequential decision process that, for each step, selects the
next camera position which maximizes the mutual information between the state
and the next observations. We solve the intrinsic intractability of this
solution by generating observations that represent scene realizations, i.e.
combination samples of object hypothesis provided by the object detector, while
modeling the state by means of a set of constantly resampled particles.
Experiments performed on different real world, challenging datasets confirm the
effectiveness of the proposed methods.


title:
Sums of squares of Krawtchouk polynomials, Catalan numbers, and some
  algebras over the Boolean lattice

abstract:
  Writing the values of Krawtchouk polynomials as matrices, we consider
weighted partial sums along columns. For the general case, we find an identity
that, in the symmetric case yields a formula for such partial sums. Complete
sums of squares along columns involve "Super Catalan" numbers. We look as well
for particular values (matrix entries) involving the Catalan numbers.
Properties considered and developed in this work are applied to calculations of
various dimensions that describe the structure of some *-algebras over the
Boolean lattice based on inclusion/superset relations expressed algebraically
using zeons [zero-square elements].


title: Keck/MOSFIRE spectroscopy of five ULX counterparts

abstract:
  We present H-band spectra of the candidate counterparts of five ULXs (two in
NGC 925, two in NGC 4136, and Holmberg II X-1) obtained with Keck/MOSFIRE. The
candidate counterparts of two ULXs (J022721+333500 in NGC 925 and
J120922+295559 in NGC 4136) have spectra consistent with (M-type) red
supergiants (RSGs). We obtained two epochs of spectroscopy of the candidate
counterpart to J022721+333500, separated by 10 months, but discovered no radial
velocity variations with a 2-$\sigma$ upper limit of 40 km/s. If the RSG is the
donor star of the ULX, the most likely options are that either the system is
seen at low inclination (< 40$^\circ$), or the black hole mass is less than 100
M$_\odot$, unless the orbital period is longer than 6 years, in which case the
obtained limit is not constraining. The spectrum of the counterpart to
J120922+295559 shows emission lines on top of its stellar spectrum, and the
remaining three counterparts do not show absorption lines that can be
associated with the atmosphere of a star; their spectra are instead dominated
by emission lines. Those counterparts with RSG spectra may be used in the
future to search for radial velocity variations, and, if those are present,
determine dynamical constraints on the mass of the accretor.


title:
Averaging Gone Wrong: Using Time-Aware Analyses to Better Understand
  Behavior

abstract:
  Online communities provide a fertile ground for analyzing people's behavior
and improving our understanding of social processes. Because both people and
communities change over time, we argue that analyses of these communities that
take time into account will lead to deeper and more accurate results. Using
Reddit as an example, we study the evolution of users based on comment and
submission data from 2007 to 2014. Even using one of the simplest temporal
differences between users---yearly cohorts---we find wide differences in
people's behavior, including comment activity, effort, and survival. Further,
not accounting for time can lead us to misinterpret important phenomena. For
instance, we observe that average comment length decreases over any fixed
period of time, but comment length in each cohort of users steadily increases
during the same period after an abrupt initial drop, an example of Simpson's
Paradox. Dividing cohorts into sub-cohorts based on the survival time in the
community provides further insights; in particular, longer-lived users start at
a higher activity level and make more and shorter comments than those who leave
earlier. These findings both give more insight into user evolution in Reddit in
particular, and raise a number of interesting questions around studying online
behavior going forward.


title:
Exponential decay estimates and smoothness of the moduli space of
  pseudoholomorphic curves

abstract:
  In this paper, we examine the dependence of standard gluing process for
pseudoholomorphic curves under the change of the length $T$ of the neck-region
with respect to the cylindrical metrics associated to the given analytic
coordinates near the punctures in the setting of bordered open Riemann surface
with boundary punctures. We establish exponential decay of the $T$-derivatives
of the $T$-dependent family of glued solutions under the change of the length
$T$ of the neck-region in a precise manner. This exponential decay estimate is
an important ingredient to prove the smoothness of the Kuranishi structure
constructed on the compactified moduli space of pseudoholomorphic curves given
in the appendix of the authors' book. We also demonstrate the way how this
smoothness follows from the exponential decay.


title:
MOON: A Mixed Objective Optimization Network for the Recognition of
  Facial Attributes

abstract:
  Attribute recognition, particularly facial, extracts many labels for each
image. While some multi-task vision problems can be decomposed into separate
tasks and stages, e.g., training independent models for each task, for a
growing set of problems joint optimization across all tasks has been shown to
improve performance. We show that for deep convolutional neural network (DCNN)
facial attribute extraction, multi-task optimization is better. Unfortunately,
it can be difficult to apply joint optimization to DCNNs when training data is
imbalanced, and re-balancing multi-label data directly is structurally
infeasible, since adding/removing data to balance one label will change the
sampling of the other labels. This paper addresses the multi-label imbalance
problem by introducing a novel mixed objective optimization network (MOON) with
a loss function that mixes multiple task objectives with domain adaptive
re-weighting of propagated loss. Experiments demonstrate that not only does
MOON advance the state of the art in facial attribute recognition, but it also
outperforms independently trained DCNNs using the same data. When using facial
attributes for the LFW face recognition task, we show that our balanced (domain
adapted) network outperforms the unbalanced trained network.


title:
Electronic and Quantum Transport Properties of Substitutionally Doped
  Double-Walled Carbon Nanotubes

abstract:
  A first-principles investigation of the electronic and quantum transport
properties of double-walled carbon nanotubes doped with nitrogen and boron
atoms is presented. Concentric nanotube sidewalls separated by the typical
graphitic van der Waals bond distance are found to strongly interact upon
incorporation of doping atoms in the hexagonal networks. The local perturbation
caused by the doping atoms extends over both shells due to a hybridization of
their electronic states, yielding a reduction of the backscattering efficiency
as compared with two independent single-walled nanotubes. A multi-scale
approach for the study of transport properties in micrometer-long double-walled
carbon nanotubes allows to demonstrate that transitions from the ballistic to
the localized regime can occur depending on the type of doping and the energy
of the charge carrier. These results shed light on the quantum mechanism by
which B and N doping represent an efficient method to create mobility gaps in
metallic concentric carbon nanotubes.


title:
Comparing Human and Automated Evaluation of Open-Ended Student Responses
  to Questions of Evolution

abstract:
  Written responses can provide a wealth of data in understanding student
reasoning on a topic. Yet they are time- and labor-intensive to score,
requiring many instructors to forego them except as limited parts of summative
assessments at the end of a unit or course. Recent developments in Machine
Learning (ML) have produced computational methods of scoring written responses
for the presence or absence of specific concepts. Here, we compare the scores
from one particular ML program -- EvoGrader -- to human scoring of responses to
structurally- and content-similar questions that are distinct from the ones the
program was trained on. We find that there is substantial inter-rater
reliability between the human and ML scoring. However, sufficient systematic
differences remain between the human and ML scoring that we advise only using
the ML scoring for formative, rather than summative, assessment of student
reasoning.


title: Descriptive complexity of graph spectra

abstract:
  Two graphs are co-spectral if their respective adjacency matrices have the
same multi-set of eigenvalues. A graph is said to be determined by its spectrum
if all graphs that are co-spectral with it are isomorphic to it. We consider
these properties in relation to logical definability. We show that any pair of
graphs that are elementarily equivalent with respect to the three-variable
counting first-order logic $C^3$ are co-spectral, and this is not the case with
$C^2$, nor with any number of variables if we exclude counting quantifiers. We
also show that the class of graphs that are determined by their spectra is
definable in partial fixed-point logic with counting. We relate these
properties to other algebraic and combinatorial problems.


title:
Mean-Field Games for Distributed Caching in Ultra-Dense Small Cell
  Networks

abstract:
  In this paper, the problem of distributed caching in dense wireless small
cell networks (SCNs) is studied using mean field games (MFGs). In the
considered SCN, small base stations (SBSs) are equipped with data storage units
and cooperate to serve users' requests either from files cached in the storage
or directly from the capacity-limited backhaul. The aim of the SBSs is to
define a caching policy that reduces the load on the capacity-limited backhaul
links. This cache control problem is formulated as a stochastic differential
game (SDG). In this game, each SBS takes into consideration the storage state
of the other SBSs to decide on the fraction of content it should cache. To
solve this problem, the formulated SDG is reduced to an MFG by considering an
ultra-dense network of SBSs in which the existence and uniqueness of the
mean-field equilibrium is shown to be guaranteed. Simulation results show that
this framework allows an efficient use of the available storage space at the
SBSs while properly tracking the files' popularity. The results also show that,
compared to a baseline model in which SBSs are not aware of the instantaneous
system state, the proposed framework increases the number of served files from
the SBSs by more than 69%.


title: Meaning of the nuclear wave function

abstract:
  Background The intense current experimental interest in studying the
structure of the deuteron and using it to enable accurate studies of neutron
structure motivate us to examine the four-dimensional space-time nature of the
nuclear wave function, and the various approximations used to reduce it to an
object that depends only on three spatial variables.
  Purpose: The aim is to determine if the ability to understand and analyze
measured experimental cross sections is compromised by making the reduction
from four to three dimensions.
  Method: Simple, exactly-calculable, covariant models of a bound-state wave
state wave function (a scalar boson made of two constituent-scalar bosons) with
parameters chosen to represent a deuteron are used to investigate the accuracy
of using different approximations to the nuclear wave function to compute the
quasi-elastic scattering cross section. Four different versions of the wave
function are defined (light-front spectator, light-front, light-front with
scaling and non-relativistic) and used to compute the cross sections as a
function of how far off the mass-shell (how virtual) is the struck constituent.
  Results: We show that making an exact calculation of the quasi-elastic
scattering cross section involves using the light-front spectator wave
function. All of the other approaches fail to reproduce the model exact
calculation if the value of Bjorken $x$ differs from unity. The model is
extended to consider an essential effect of spin to show that constituent
nucleons cannot be treated as being on their mass shell even when taking the
matrix element of a `good' current.
  Conclusions: It is necessary to develop realistic light-front spectator wave
functions to meet the needs of current and planned experiments.


title: Global solution curves for several classes of singular periodic problems

abstract:
  Using continuation methods and bifurcation theory, we study the exact
multiplicity of periodic solutions, and the global solution structure, for
three classes of periodically forced equations with singularities, including
the equations arising in micro-electro-mechanical systems (MEMS), the ones in
condensed matter physics, as well as A.C. Lazer and S. Solimini's \cite{LS}
problem.


title: GRACES observations of young [alpha/Fe]-rich stars

abstract:
  We measure chemical abundance ratios and radial velocities in four massive
(i.e., young) [alpha/Fe]-rich red giant stars using high-resolution high-S/N
spectra from ESPaDOnS fed by Gemini-GRACES. Our differential analysis ensures
that our chemical abundances are on the same scale as the Alves-Brito et al.
(2010) study of bulge, thin and thick disk red giants. We confirm that the
program stars have enhanced [alpha/Fe] ratios and are slightly metal poor.
Aside from lithium enrichment in one object, the program stars exhibit no
chemical abundance anomalies when compared to giant stars of similar
metallicity throughout the Galaxy. This includes the elements Li, O, Si, Ca,
Ti, Cr, Ni, Cu, Ba, La, and Eu. Therefore, there are no obvious chemical
signatures that can help to reveal the origin of these unusual stars. While our
new observations show that only one star (not the Li-rich object) exhibits a
radial velocity variation, simulations indicate that we cannot exclude the
possibility that all four could be binaries. In addition, we find that two
(possibly three) stars show evidence for an infrared excess, indicative of a
debris disk. This is consistent with these young [alpha/Fe]-rich stars being
evolved blue stragglers, suggesting their apparent young age is a consequence
of a merger or mass transfer. We would expect a binary fraction of ~50% or
greater for the entire sample of these stars, but the signs of the circumbinary
disk may have been lost since these features can have short timescales. Radial
velocity monitoring is needed to confirm the blue straggler origin.


title: Revisiting Unit Fractions That Sum To 1

abstract:
  This paper is a continuation of a previous paper. Here, as there, we examine
the problem of finding the maximum number of terms in a partial sequence of
distinct unit fractions larger than 1/100 that sums to 1. In the previous
paper, we found that the maximum number of terms is 42 and introduced a method
for showing that. In this paper, we demonstrate that there are 27 possible
solutions with 42 terms, and discuss how primes show that no 43-term solution
exists.


title: Part probabilistic cloning of linearly dependent states

abstract:
  From Ref. [Phys. Rev. Lett. 80(1998)4999] one knows that the quantum states
secretly chosen from a certain set can be probabilistically cloned with
positive cloning efficiencies if and only if all the states in the set are
linearly independent. In this paper, we focus on the probabilistic quantum
cloning (PQC) of linearly dependent states with nonnegative cloning
efficiencies. We show that a linearly independent subset of the linearly
dependent quantum states can be probabilistically cloned if and only if any one
state in the subset can not be expressed as the linear superposition of the
other states in the set. The optimal possible cloning efficiencies are also
investigated.


title: Search for $B_c^+$ decays to the $p\bar p\pi^+$ final state

abstract:
  A search for the decays of the $B_c^+$ meson to $p\bar p\pi^+$ is performed
for the first time using a data sample corresponding to an integrated
luminosity of 3.0 $\mathrm{fb}^{-1}$ collected by the LHCb experiment in $pp$
collisions at centre-of-mass energies of $7$ and $8$ TeV. No signal is found
and an upper limit, at 95\% confidence level, is set,
$\frac{f_c}{f_u}\times\mathcal{B}(B_c^+\to p\bar p\pi^+)<3.6\times10^{-8}$ in
the kinematic region $m(p\bar p)<2.85\mathrm{\,Ge\kern -0.1em V\!/}c^2$,
$p_{\rm T}(B)<20\mathrm{\,Ge\kern -0.1em V\!/}c$ and $2.0<y(B)<4.5$, where
$\mathcal{B}$ is the branching fraction and $f_c$ ($f_u$) is the fragmentation
fraction of the $b$ quark into a $B_c^+$ ($B^+$) meson.


title:
Criticality and subcriticality of generalized Schr\"odinger forms with
  non-local perturbations

abstract:
  In this paper, we shall treat the Schr\"odinger forms with non-local
perturbations. We first extend the definitions of subcriticality, criticality
and supercriticality for the Schr\"odinger forms by Takeda in [IJM, 2015] to
the non-local cases in the context of quasi-regular Dirichlet forms. Then we
prove an analytic characterization of these definitions via the bottom of the
spectrum set.


title:
C-Projective Compactification; (quasi--)Kaehler Metrics and CR
  boundaries

abstract:
  For complete complex connections on almost complex manifolds we introduce a
natural definition of compactification. This is based on almost c--projective
geometry, which is the almost complex analogue of projective differential
geometry. The boundary at infinity is a (possibly non-integrable) CR structure.
The theory applies to almost Hermitean manifolds which admit a complex metric
connection of minimal torsion, which means that they are quasi--Kaehler in the
sense of Gray--Hervella; in particular it applies to Kaehler and nearly Kaehler
manifolds. Via this canonical connection, we obtain a notion of c-projective
compactification for quasi--Kaehler metrics of any signature.
  We describe an asymptotic form for metrics that is necessary and sufficient
for c--projective compactness. This metric form provides local examples and, in
particular, shows that the usual complete Kaehler metrics associated to
smoothly bounded, strictly pseudoconvex domains in C^n are c--projectively
compact. For a smooth manifold with boundary and a complete quasi-Kaehler
metric $g$ on the interior, we show that if its almost c--projective structure
extends smoothly to the boundary then so does its scalar curvature. We prove
that $g$ is almost c--projectively compact if and only if this scalar curvature
is non-zero on an open dense set of the boundary, in which case it is, along
the boundary, locally constant and hence nowhere zero there. Finally we
describe the asymptotics of the curvature, showing, in particular, that the
canonical connection satisfies an asymptotic Einstein condition. Key to much of
the development is a certain real tractor calculus for almost c--projective
geometry, and this is developed in the article.


title:
Highly sensitive simple homodyne phase detector for ultrasonic
  pulse-echo measurements

abstract:
  We have designed and built a modern versatile research-grade instrument for
ultrasound pulse-echo probing of the elastic properties of a wide range of
materials under laboratory conditions. The heart of the instrument lies in an
AD8302 microchip: a gain and phase detector from Analog Devices, Inc. To
construct the device, we have implemented a schematic that utilizes the
homodyne principle for signal processing instead of the traditional
superheterodyne approach. This design allows one to measure phase shifts with
high precision and linearity over the entire range of $0-360^\circ$. The system
is simple in construction and usage; it makes ultrasound measurements easily
accessible to a broad range of researchers. It was tested by measuring the
temperature dependence of the ultrasound speed and attenuation in a
KTa$_{0.92}$Nb$_{0.08}$O$_{3}$ (KTN) single crystal at a frequency of $\sim$ 40
MHz. The tests were performed in the vicinity of the ferroelectric transitions
where the large variations of the speed and attenuation demand a detector with
outstanding characteristics. The described detector has a wide dynamic range
and allows for measuring in a single run over the whole temperature range of
the ferroelectric transitions, rather than just in limited intervals available
previously. Moreover, due to the wide dynamic range of the gain measurements
and high sensitivity this instrument was able to reveal previously unresolvable
features associated with the development of the ferroelectric transitions of
KTN crystals.


title:
Augmented Factor Models with Applications to Validating Market Risk
  Factors and Forecasting Bond Risk Premia

abstract:
  We study factor models augmented by observed covariates that have explanatory
powers on the unknown factors. In financial factor models, the unknown factors
can be reasonably well explained by a few observable proxies, such as the
Fama-French factors. In diffusion index forecasts, identified factors are
strongly related to several directly measurable economic variables such as
consumption-wealth variable, financial ratios, and term spread. With those
covariates, both the factors and loadings are identifiable up to a rotation
matrix even only with a finite dimension. To incorporate the explanatory power
of these covariates, we propose a smoothed principal component analysis (PCA):
(i) regress the data onto the observed covariates, and (ii) take the principal
components of the fitted data to estimate the loadings and factors. This allows
us to accurately estimate the percentage of both explained and unexplained
components in factors and thus to assess the explanatory power of covariates.
We show that both the estimated factors and loadings can be estimated with
improved rates of convergence compared to the benchmark method. The degree of
improvement depends on the strength of the signals, representing the
explanatory power of the covariates on the factors. The proposed estimator is
robust to possibly heavy-tailed distributions. We apply the model to forecast
US bond risk premia, and find that the observed macroeconomic characteristics
contain strong explanatory powers of the factors. The gain of forecast is more
substantial when the characteristics are incorporated to estimate the common
factors than directly used for forecasts.


title: HASH: the Hong Kong/AAO/Strasbourg H-alpha planetary nebula database

abstract:
  By incorporating our major recent discoveries with re-measured and verified
contents of existing catalogues we provide, for the first time, an accessible,
reliable, on-line SQL database for essential, up-to date information for all
known Galactic PNe. We have attempted to: i) reliably remove PN mimics/false
ID's that have biased previous studies and ii) provide accurate positions,
sizes, morphologies, multi-wavelength imagery and spectroscopy. We also provide
a link to CDS/Vizier for the archival history of each object and other valuable
links to external data. With the HASH interface, users can sift, select,
browse, collate, investigate, download and visualise the entire currently known
Galactic PNe diversity. HASH provides the community with the most complete and
reliable data with which to undertake new science.


title: On a Quantum Entropy Power Inequality of Audenaert, Datta and Ozols

abstract:
  We give a short proof of a recent inequality of Audenaert, Datta and Ozols,
and determine cases of equality.


title:
Recurrent Neural Network Encoder with Attention for Community Question
  Answering

abstract:
  We apply a general recurrent neural network (RNN) encoder framework to
community question answering (cQA) tasks. Our approach does not rely on any
linguistic processing, and can be applied to different languages or domains.
Further improvements are observed when we extend the RNN encoders with a neural
attention mechanism that encourages reasoning over entire sequences. To deal
with practical issues such as data sparsity and imbalanced labels, we apply
various techniques such as transfer learning and multitask learning. Our
experiments on the SemEval-2016 cQA task show 10% improvement on a MAP score
compared to an information retrieval-based approach, and achieve comparable
performance to a strong handcrafted feature-based method.


title: Multiwave tomography with reflectors: Landweber's iteration

abstract:
  We use the Landweber method for numerical simulations for the multiwave
tomography problem with a reflecting boundary and compare it with the averaged
time reversal method. We also analyze the rate of convergence and the
dependence on the step size for the Landweber iterations on a Hilbert space.


title:
Holographic Algorithm with Matchgates Is Universal for Planar $\#$CSP
  Over Boolean Domain

abstract:
  We prove a complexity classification theorem that classifies all counting
constraint satisfaction problems ($\#$CSP) over Boolean variables into exactly
three categories: (1) Polynomial-time tractable; (2) $\#$P-hard for general
instances, but solvable in polynomial-time over planar graphs; and (3)
$\#$P-hard over planar graphs. The classification applies to all sets of local,
not necessarily symmetric, constraint functions on Boolean variables that take
complex values. It is shown that Valiant's holographic algorithm with
matchgates is a universal strategy for all problems in category (2).


title:
A New Method to Determine the Temperature of CMEs Using a Coronagraph
  Filter System

abstract:
  The coronagraph is an instrument enables the investigation of faint features
in the vicinity of the Sun, particularly coronal mass ejections (CMEs). So far
coronagraphic observations have been mainly used to determine the geometric and
kinematic parameters of CMEs. Here, we introduce a new method for the
determination of CME temperature using a two filter (4025 A and 3934 A)
coronagraph system. The thermal motion of free electrons in CMEs broadens the
absorption lines in the optical spectra that are produced by the Thomson
scattering of visible light originating in the photosphere, which affects the
intensity ratio at two different wavelengths. Thus the CME temperature can be
inferred from the intensity ratio measured by the two filter coronagraph
system. We demonstrate the method by invoking the graduated cylindrical shell
(GCS) model for the 3 dimensional CME density distribution and discuss its
significance.


title:
Interplay of topology and interactions in quantum Hall topological
  insulators: U(1) symmetry, tunable Luttinger liquid, and interaction-induced
  phase transitions

abstract:
  We consider a class of {\em quantum Hall topological insulators}:
topologically nontrivial states with zero Chern number at finite magnetic
field, in which the counter-propagating edge states are protected by a symmetry
(spatial or spin) other than time-reversal. HgTe-type heterostructures and
graphene are among the relevant systems. We study the effect of electron
interactions on the topological properties of the system. We particularly focus
on the vicinity of the topological phase transition, marked by the crossing of
two Landau levels, where the system is a strongly interacting quantum Hall
ferromagnet. We analyse the edge properties using the formalism of the
nonlinear $\sigma$-model. We establish the symmetry requirement for the
topological protection in this interacting system: effective continuous U(1)
symmetry with respect to uniaxial isospin rotations must be preserved. If U(1)
symmetry is preserved, the topologically nontrivial phase persists; its edge is
a helical Luttinger liquid with highly tunable effective interactions. We
obtain explicit analytical expressions for the parameters of the Luttinger
liquid. However, U(1) symmetry may be broken, either spontaneously or by
U(1)-asymmetric interactions. In either case, interaction-induced transitions
occur to the respective topologically trivial phases with gapped edge charge
excitations.


title:
Measuring lifetime of correspondence with classical decay of correlation
  in quantum chaos

abstract:
  A very weakly coupled linear oscillator is proposed as a detector for
observing time-irreversible characteristics of a quantum system, and it is used
to measure the lifetime during which a classically chaotic quantum system shows
decay of correlation. Except for a particular case where the lifetime agrees
with the conventional Heisenberg time, which is proportional to the Hilbert
space dimension $N$, it is in general much longer: the lifetime increases in
proportion to the product of $N$ and the number of superposed eigenstates, and
is proportional to $N^2$ in the case of full superposition.


title:
Relation between irreversibility and entanglement in classically chaotic
  quantum kicked rotors

abstract:
  The relation between the degree of entanglement and time scale of
time-irreversible behavior is investigated for classically chaotic quantum
coupled kicked rotors by comparing the entanglement entropy (EE) and the
lifetime of correspondence with classical decay of correlation, which was
recently introduced. Both increase {\it on average} drastically with a strong
correlation when the strength of coupling between the kicked rotors exceeds a
certain threshold. The EE shows an anomalously large fluctuation resembling a
critical fluctuation around the threshold value of coupling strength where the
entanglement sharply increases toward full entanglement. In this regime it can
be shown that, although the correlation is hidden, EE and the lifetime of {\it
individual eigenfunctions} also have a positive correlation that can be seen
via an another measure.


title:
Cosolver2B: An Efficient Local Search Heuristic for the Travelling Thief
  Problem

abstract:
  Real-world problems are very difficult to optimize. However, many researchers
have been solving benchmark problems that have been extensively investigated
for the last decades even if they have very few direct applications. The
Traveling Thief Problem (TTP) is a NP-hard optimization problem that aims to
provide a more realistic model. TTP targets particularly routing problem under
packing/loading constraints which can be found in supply chain management and
transportation. In this paper, TTP is presented and formulated mathematically.
A combined local search algorithm is proposed and compared with Random Local
Search (RLS) and Evolutionary Algorithm (EA). The obtained results are quite
promising since new better solutions were found.


title:
Cluster Content Caching: An Energy-Efficient Approach to Improve Quality
  of Service in Cloud Radio Access Networks

abstract:
  In cloud radio access networks (C-RANs), a substantial amount of data must be
exchanged in both backhaul and fronthaul links, which causes high power
consumption and poor quality of service (QoS) experience for real-time
services. To solve this problem, a cluster content caching structure is
proposed in this paper, which takes full advantage of distributed caching and
centralized signal processing. In particular, redundant traffic on the backhaul
can be reduced because the cluster content cache provides a part of required
content objects for remote radio heads (RRHs) connected to a common edge cloud.
Tractable expressions for both effective capacity and energy efficiency
performance are derived, which show that the proposed structure can improve QoS
guarantees with a lower power cost of local storage. Furthermore, to fully
explore the potential of the proposed cluster content caching structure, the
joint design of resource allocation and RRH association is optimized, and two
distributed algorithms are accordingly proposed. Simulation results verify the
accuracy of the analytical results and show the performance gains achieved by
cluster content caching in C-RANs.


title:
Gauge Interactions and a Quantum Avatar in a Model with Light Cone
  Reflection Symmetry

abstract:
  We continue the development of a model of neutrinos that possesses a new
symmetry, Light Cone Reflection, interchanging spacelike and timelike
intervals. In this paper we introduce gauge interactions in which only the
physical modes of the theory participate. We also find an avatar of the theory,
involving spinors in two-dimensions that obey equations reproducing the
spectrum of the original, four-dimensional theory, and we discuss the
quantization of the avatar.


title: A Richly Annotated Dataset for Pedestrian Attribute Recognition

abstract:
  In this paper, we aim to improve the dataset foundation for pedestrian
attribute recognition in real surveillance scenarios. Recognition of human
attributes, such as gender, and clothes types, has great prospects in real
applications. However, the development of suitable benchmark datasets for
attribute recognition remains lagged behind. Existing human attribute datasets
are collected from various sources or an integration of pedestrian
re-identification datasets. Such heterogeneous collection poses a big challenge
on developing high quality fine-grained attribute recognition algorithms.
Furthermore, human attribute recognition are generally severely affected by
environmental or contextual factors, such as viewpoints, occlusions and body
parts, while existing attribute datasets barely care about them. To tackle
these problems, we build a Richly Annotated Pedestrian (RAP) dataset from real
multi-camera surveillance scenarios with long term collection, where data
samples are annotated with not only fine-grained human attributes but also
environmental and contextual factors. RAP has in total 41,585 pedestrian
samples, each of which is annotated with 72 attributes as well as viewpoints,
occlusions, body parts information. To our knowledge, the RAP dataset is the
largest pedestrian attribute dataset, which is expected to greatly promote the
study of large-scale attribute recognition systems. Furthermore, we empirically
analyze the effects of different environmental and contextual factors on
pedestrian attribute recognition. Experimental results demonstrate that
viewpoints, occlusions and body parts information could assist attribute
recognition a lot in real applications.


title:
LLR-based Successive-Cancellation List Decoder for Polar Codes with
  Multi-bit Decision

abstract:
  Due to their capacity-achieving property, polar codes have become one of the
most attractive channel codes. To date, the successive cancellation list (SCL)
decoding algorithm is the primary approach that can guarantee outstanding
error-correcting performance of polar codes. However, the hardware designs of
the original SCL decoder have large silicon area and long decoding latency.
Although some recent efforts can reduce either the area or latency of SCL
decoders, these two metrics still cannot be optimized at the same time. This
paper, for the first time, proposes a general log-likelihood-ratio (LLR)-based
SCL decoding algorithm with multi-bit decision. This new algorithm, referred as
LLR-2Kb-SCL, can determine 2K bits simultaneously for arbitrary K with the use
of LLR messages. In addition, a reduced-data-width scheme is presented to
reduce the critical path of the sorting block. Then, based on the proposed
algorithm, a VLSI architecture of the new SCL decoder is developed. Synthesis
results show that for an example (1024, 512) polar code with list size 4, the
proposed LLR-2Kb-SCL decoders achieve significant reduction in both area and
latency as compared to prior works. As a result, the hardware efficiency of the
proposed designs with K=2 and 3 are 2.33 times and 3.32 times of that of the
state-of-the-art works, respectively.


title: On the number of cliques in graphs with a forbidden minor

abstract:
  Reed and Wood and independently Norine, Seymour, Thomas, and Wollan proved
that for each positive integer $t$ there is a constant $c(t)$ such that every
graph on $n$ vertices with no $K_t$-minor has at most $c(t)n$ cliques. Wood
asked in 2007 if we can take $c(t) = c^t$ for some absolute constant $c$. This
question was recently answered affirmatively by Lee and Oum. In this paper, we
determine the exponential constant. We prove that every graph on $n$ vertices
with no $K_t$-minor has at most $3^{2t/3+o(t)}n$ cliques. This bound is tight
for $n \geq 4t/3$. More generally, let $H$ be a connected graph on $t$
vertices, and $x$ denote the size (i.e., the number edges) of the largest
matching in the complement of $H$. We prove that every graph on $n$ vertices
with no $H$-minor has at most $\max(3^{2t/3-x/3+o(t)}n,2^{t+o(t)}n)$ cliques,
and this bound is tight for $n \geq \max (4t/3-2x/3,t)$ by a simple
construction. Even more generally, we determine explicitly the exponential
constant for the maximum number of cliques an $n$-vertex graph can have in a
minor-closed family of graphs which is closed under disjoint union.


title:
Do We Really Need to Collect Millions of Faces for Effective Face
  Recognition?

abstract:
  Face recognition capabilities have recently made extraordinary leaps. Though
this progress is at least partially due to ballooning training set sizes --
huge numbers of face images downloaded and labeled for identity -- it is not
clear if the formidable task of collecting so many images is truly necessary.
We propose a far more accessible means of increasing training data sizes for
face recognition systems. Rather than manually harvesting and labeling more
faces, we simply synthesize them. We describe novel methods of enriching an
existing dataset with important facial appearance variations by manipulating
the faces it contains. We further apply this synthesis approach when matching
query images represented using a standard convolutional neural network. The
effect of training and testing with synthesized images is extensively tested on
the LFW and IJB-A (verification and identification) benchmarks and Janus CS2.
The performances obtained by our approach match state of the art results
reported by systems trained on millions of downloaded images.


title: On Bismut Flat Manifolds

abstract:
  In this paper, we give a classification of all compact Hermitian manifolds
with flat Bismut connection. We show that the torsion tensor of such a manifold
must be parallel, thus the universal cover of such a manifold is a Lie group
equipped with a bi-invariant metric and a compatible left invariant complex
structure. In particular, isosceles Hopf surfaces are the only Bismut flat
compact non-K\"ahler surfaces, while central Calabi-Eckmann threefolds are the
only simply-connected compact Bismut flat threefolds.


title:
Closed convex hulls of unitary orbits in certain simple real rank zero
  C$^*$-algebras

abstract:
  In this paper, we characterize the closures of convex hulls of unitary orbits
of self-adjoint operators in unital, separable, simple C$^*$-algebras with
non-trivial tracial simplex, real rank zero, stable rank one, and strict
comparison of projections with respect to tracial states. In addition, an upper
bound for the number of unitary conjugates in a convex combination needed to
approximate a self-adjoint are obtained.


title: Arithmetic exponent pairs for algebraic trace functions and applications

abstract:
  We study short sums of algebraic trace functions via the $q$-analogue of van
der Corput method, and develop methods of arithmetic exponent pairs that
coincide with the classical case while the moduli has sufficiently good
factorizations. As an application, we prove a quadratic analogue of
Brun-Titchmarsh theorem on average, bounding the number of primes $p\leqslant
X$ with $p^2+1\equiv0\pmod q$. The other two applications include a larger
level of distribution of divisor functions in arithmetic progressions and a
sub-Weyl subconvex bound of Dirichlet $L$-functions studied previously by
Irving.


title:
Global Existence and Blowup for Geodesics in Universal Teichm\"uller
  Spaces

abstract:
  In this paper we prove that all initially-smooth solutions of the
Euler-Weil-Petersson equation, which describes geodesics on the universal
Teichm\"uller space under the Weil-Petersson metric, will remain smooth for all
time. This extends the work of Escher-Kolev for strong Riemannian metrics to
the borderline case of $H^{3/2}$ metrics. In addition we show that all
initially-smooth solutions of the Wunsch equation, which describes geodesics on
the universal Teichm\"uller curve under the Velling-Kirillov metric, must blow
up in finite time due to wave breaking, extending work of Castro-C\'ordoba and
Bauer-Kolev-Preston. Finally we illustrate these phenomena in terms of
conformal maps of the unit disc, using the conformal welding representation of
circle diffeomorphisms which is natural in Teichm\"uller theory.


title: Evolution of a Current Sheet in a Solar Flare

abstract:
  We report multi-wavelength and multi-viewpoint observations of a solar
eruptive event which involves loop-loop interactions. During a C2.0 flare,
motions associated with inflowing and outflowing plasma provide evidence for
ongoing magnetic reconnection. The flare loop top and a rising "concave-up"
feature are connected by a current-sheet-like structure (CSLS). The physical
properties (thickness, length, temperature, and density) of the CSLS are
evaluated. In regions adjacent to the CSLS, the EUV emission (characteristic
temperature at 1.6 MK) begins to increase more than ten minutes prior to the
onset of the flare, and steeply decreases during the decay phase. The reduction
of the emission resembles that expected from coronal dimming. The dynamics of
this event imply a magnetic reconnection rate in the range 0.01 -- 0.05.


title: Semantic Object Parsing with Graph LSTM

abstract:
  By taking the semantic object parsing task as an exemplar application
scenario, we propose the Graph Long Short-Term Memory (Graph LSTM) network,
which is the generalization of LSTM from sequential data or multi-dimensional
data to general graph-structured data. Particularly, instead of evenly and
fixedly dividing an image to pixels or patches in existing multi-dimensional
LSTM structures (e.g., Row, Grid and Diagonal LSTMs), we take each
arbitrary-shaped superpixel as a semantically consistent node, and adaptively
construct an undirected graph for each image, where the spatial relations of
the superpixels are naturally used as edges. Constructed on such an adaptive
graph topology, the Graph LSTM is more naturally aligned with the visual
patterns in the image (e.g., object boundaries or appearance similarities) and
provides a more economical information propagation route. Furthermore, for each
optimization step over Graph LSTM, we propose to use a confidence-driven scheme
to update the hidden and memory states of nodes progressively till all nodes
are updated. In addition, for each node, the forgets gates are adaptively
learned to capture different degrees of semantic correlation with neighboring
nodes. Comprehensive evaluations on four diverse semantic object parsing
datasets well demonstrate the significant superiority of our Graph LSTM over
other state-of-the-art solutions.


title: Big Data Spark Solution for Functional Magnetic Resonance Imaging

abstract:
  Recently, Big Data applications have rapidly expanded into different
industries. Healthcare is also one the industries willing to use big data
platforms so that some big data analytics tools have been adopted in this field
to some extent. Medical imaging which is a pillar in diagnostic healthcare
deals with high volume of data collection and processing. A huge amount of 3D
and 4D images are acquired in different forms and resolutions using a variety
of medical imaging modalities. Preprocessing and analyzing imaging data is
currently a long process and cost and time consuming. However, not many big
data platforms have been provided or redesigned for medical imaging purposes
because of some restrictions such as data format. In this paper, we designed,
developed and successfully tested a new pipeline for medical imaging data
(especially functional magnetic resonance imaging - fMRI) using Big Data Spark
/ PySpark platform on a single node which allows us to read and load imaging
data, convert them to Resilient Distributed Datasets in order manipulate and
perform in-memory data processing in parallel and convert final results to
imaging format while the pipeline provides an option to store the results in
other formats such as data frame. Using this new solution and pipeline, we
repeated our previous works in which we extracted brain networks from fMRI data
using template matching and sum of squared differences (SSD) method. The final
results revealed our Spark (PySpark) based solution improved the performance
(in terms of processing time) around 4 times on a single compared to the
previous work developed in Python.


title: Pasting and Reversing Approach to Matrix Theory

abstract:
  The aim of this paper is to study some aspects of matrix theory through
Pasting and Reversing. We start giving a summary of previous results concerning
to Pasting and Reversing over vectors and matrices, after we rewrite such
properties of Pasting and Reversing in matrix theory using linear mappings to
finish with new properties and new sets in matrix theory involving Pasting and
Reversing. In particular we introduce new linear mappings: Palindromicing and
Antipalindromicing mappings, which allow us to obtain palindromic and
antipalindromic vectors and matrices.


title: Phase-Amplitude Separation and Modeling of Spherical Trajectories

abstract:
  This paper studies the problem of separating phase-amplitude components in
sample paths of a spherical process (longitudinal data on a unit two-sphere).
Such separation is essential for efficient modeling and statistical analysis of
spherical longitudinal data in a manner that is invariant to any phase
variability. The key idea is to represent each path or trajectory with a pair
of variables, a starting point and a Transported Square-Root Velocity Curve
(TSRVC). A TSRVC is a curve in the tangent (vector) space at the starting point
and has some important invariance properties under the L2 norm. The space of
all such curves forms a vector bundle and the L2 norm, along with the standard
Riemannian metric on S2, provides a natural metric on this vector bundle. This
invariant representation allows for separating phase and amplitude components
in given data, using a template-based idea. Furthermore, the metric property is
useful in deriving computational procedures for clustering, mean computation,
principal component analysis (PCA), and modeling. This comprehensive framework
is demonstrated using two datasets: a set of bird-migration trajectories and a
set of hurricane paths in the Atlantic ocean.


title: Quadratic polynomials at prime arguments

abstract:
  For a fixed quadratic irreducible polynomial $f$ with no fixed prime factors
at prime arguments, we prove that there exist infinitely many primes $p$ such
that $f(p)$ has at most 4 prime factors, improving a classical result of
Richert who requires 5 in place of 4. Denoting by $P^+(n)$ the greatest prime
factor of $n$, it is also proved that $P^+(f(p))>p^{0.847}$ infinitely often.


title:
A unifying combinatorial approach to refined little G\"ollnitz and
  Capparelli's companion identities

abstract:
  Berkovich-Uncu have recently proved a companion of the well-known
Capparelli's identities as well as refinements of Savage-Sills' new little
G\"ollnitz identities. Noticing the connection between their results and
Boulet's earlier four-parameter partition generating functions, we discover a
new class of partitions, called $k$-strict partitions, to generalize their
results. By applying both horizontal and vertical dissections of Ferrers'
diagrams with appropriate labellings, we provide a unified combinatorial
treatment of their results and shed more lights on the intriguing conditions of
their companion to Capparelli's identities.


title:
Immersing quasi-Fuchsian surfaces of odd Euler characteristic in closed
  hyperbolic 3-manifolds

abstract:
  In this paper, it is shown that every closed hyperbolic 3-manifold contains
an immersed quasi-Fuchsian closed subsurface of odd Euler characteristic. The
construction adopts the good pants method, and the primary new ingredient is an
enhanced version of the connection principle, which allows one to connect any
two frames with a path of frames in a prescribed relative homology class of the
frame bundle. The existence result is applied to show that every uniform
lattice of $\mathrm{PSL}(2,\mathbb{C})$ admits an exhausting nested sequence of
sublattices with exponential homological torsion growth. However, the
constructed sublattices are not normal in general.


title: Error bounds for rank constrained optimization problems and applications

abstract:
  This paper is concerned with the rank constrained optimization problem whose
feasible set is the intersection of the rank constraint set
$\mathcal{R}=\!\big\{X\in\mathbb{X}\ |\ {\rm rank}(X)\le \kappa\big\}$ and a
closed convex set $\Omega$. We establish the local (global) Lipschitzian type
error bounds for estimating the distance from any $X\in \Omega$
($X\in\mathbb{X}$) to the feasible set and the solution set, respectively,
under the calmness of a multifunction associated to the feasible set at the
origin, which is specially satisfied by three classes of common rank
constrained optimization problems. As an application of the local Lipschitzian
type error bounds, we show that the penalty problem yielded by moving the rank
constraint into the objective is exact in the sense that its global optimal
solution set coincides with that of the original problem when the penalty
parameter is over a certain threshold. This particularly offers an affirmative
answer to the open question whether the penalty problem (32) in (Gao and Sun,
2010) is exact or not. As another application, we derive the error bounds of
the iterates generated by a multi-stage convex relaxation approach to those
three classes of rank constrained problems and show that the bounds are
nonincreasing as the number of stages increases.


title: Dynamical Evidence for a Late Formation of Saturn's Moons

abstract:
  We explore the past evolution of Saturn's moons using direct numerical
integrations. We find that the past Tethys-Dione 3:2 orbital resonance
predicted in standard models likely did not occur, implying that the system is
less evolved than previously thought. On the other hand, the orbital
inclinations of Tethys, Dione and Rhea suggest that the system did cross the
Dione-Rhea 5:3 resonance, which is closely followed by a Tethys-Dione secular
resonance. A clear implication is that either the moons are significantly
younger than the planet, or that their tidal evolution must be extremely slow
(Q > 80,000). As an extremely slow-evolving system is incompatible with intense
tidal heating of Enceladus, we conclude that the moons interior to Titan are
not primordial, and we present a plausible scenario for the system's recent
formation. We propose that the mid-sized moons re-accreted from a disk about
100 Myr ago, during which time Titan acquired its significant orbital
eccentricity. We speculate that this disk has formed through orbital
instability and massive collisions involving the previous generation of
Saturn's mid-sized moons. We identify the solar evection resonance perturbing a
pair of mid-sized moons as the most likely trigger of such an instability. This
scenario implies that most craters on the moons interior to Titan must have
been formed by planetocentric impactors.


title:
A 3-D Spatial Model for In-building Wireless Networks with Correlated
  Shadowing

abstract:
  Consider orthogonal planes in the 3-D space representing floors and walls in
a large building. These planes divide the space into rooms where a wireless
infrastructure is deployed. This paper is focused on the analysis of the
correlated shadowing field created by this wireless infrastructure through the
set of walls and floors. When the locations of the planes and of the wireless
nodes are governed by Poisson processes, we obtain a simple stochastic model
which captures the non-uniform nature of node deployment and room sizes. This
model, which we propose to call the Poisson building, captures the complex
in-building shadowing correlations, is scalable in the number of dimensions and
is tractable for network performance analysis. It allows an exact mathematical
characterization of the interference distribution in both infinite and finite
buildings, which further leads to closed-form expressions for the coverage
probabilities in in-building cellular networks and the success probability of
in-building underlay D2D transmissions.


title:
On the Diliberto-Straus algorithm for the uniform approximation by a sum
  of two algebras

abstract:
  In 1951, Diliberto and Straus proposed a levelling algorithm for the uniform
approximation of a bivariate function, defined on a rectangle with sides
parallel to the coordinate axes, by sums of univariate functions. In the
current paper, we consider the problem of approximation of a continuous
function defined on a compact Hausdorff space by a sum of two closed algebras
containing constants. Under reasonable assumptions, we show the convergence of
the Diliberto-Straus algorithm. For the approximation by sums of univariate
functions, it follows that Diliberto-Straus's original result holds for a large
class of compact convex sets.


title: On random convex analysis

abstract:
  Recently, based on the idea of randomizing space theory, random convex
analysis has been being developed in order to deal with the corresponding
problems in random environments such as analysis of conditional convex risk
measures and the related variational problems and optimization problems. Random
convex analysis is convex analysis over random locally convex modules. Since
random locally convex modules have the more complicated topological and
algebraic structures than ordinary locally convex spaces, establishing random
convex analysis will encounter harder mathematical challenges than classical
convex analysis so that there are still a lot of fundamentally important
unsolved problems in random convex analysis. This paper is devoted to solving
some important theoretic problems. First, we establish the inferior limit
behavior of a proper lower semicontinuous $L^0$--convex function on a random
locally convex module endowed with the locally $L^0$--convex topology, which
makes perfect the Fenchel--Moreau duality theorem for such functions. Then, we
investigate the relations among continuity, locally $L^0$--Lipschitzian
continuity and almost surely sequent continuity of a proper $L^0$--convex
function. And then, we establish the elegant relationships among
subdifferentiability, G\^ateaux--differentiability and
Fr\'ech\'et--differentiability for a proper $L^0$--convex function defined on
random normed modules. At last, based on the Ekeland's variational principle
for a proper lower semicontinuous $\bar{L}^0$--valued function, we show that
$\varepsilon$--subdifferentials can be approximated by subdifferentials. We
would like to emphasize that the success of this paper lies in simultaneously
considering the $(\varepsilon, \lambda)$--topology and the locally
$L^0$--convex topology for a random locally convex module.


title: Static Scalar Field Solutions in Symmetric Gravity

abstract:
  We derive a family of exact solutions for bi-metric gravity with an exchange
symmetry between the two metrics. In this two-parameter family of solutions the
gravitational field is sourced by a time-independent massless scalar field. We
find that the only limit in which the scalar field entirely vanishes is flat
space. The regular Schwarzschild-solution is left with a scalar field hidden in
the second metric's sector.


title: Towards Viewpoint Invariant 3D Human Pose Estimation

abstract:
  We propose a viewpoint invariant model for 3D human pose estimation from a
single depth image. To achieve this, our discriminative model embeds local
regions into a learned viewpoint invariant feature space. Formulated as a
multi-task learning problem, our model is able to selectively predict partial
poses in the presence of noise and occlusion. Our approach leverages a
convolutional and recurrent network architecture with a top-down error feedback
mechanism to self-correct previous pose estimates in an end-to-end manner. We
evaluate our model on a previously published depth dataset and a newly
collected human pose dataset containing 100K annotated depth images from
extreme viewpoints. Experiments show that our model achieves competitive
performance on frontal views while achieving state-of-the-art performance on
alternate viewpoints.


title: Computing Nonsimple Polygons of Minimum Perimeter

abstract:
  We provide exact and approximation methods for solving a geometric relaxation
of the Traveling Salesman Problem (TSP) that occurs in curve reconstruction:
for a given set of vertices in the plane, the problem Minimum Perimeter Polygon
(MPP) asks for a (not necessarily simply connected) polygon with shortest
possible boundary length. Even though the closely related problem of finding a
minimum cycle cover is polynomially solvable by matching techniques, we prove
how the topological structure of a polygon leads to NP-hardness of the MPP. On
the positive side, we show how to achieve a constant-factor approximation.
  When trying to solve MPP instances to provable optimality by means of integer
programming, an additional difficulty compared to the TSP is the fact that only
a subset of subtour constraints is valid, depending not on combinatorics, but
on geometry. We overcome this difficulty by establishing and exploiting
additional geometric properties. This allows us to reliably solve a wide range
of benchmark instances with up to 600 vertices within reasonable time on a
standard machine. We also show that using a natural geometry-based
sparsification yields results that are on average within 0.5% of the optimum.


title: PRECL: A new method for interferometry imaging from closure phase

abstract:
  For short-wavelength VLBI observations, it is difficult to measure the phase
of the visibility function accurately. The closure phases are reliable
measurements under this situation, though it is not sufficient to retrieve all
of the phase information. We propose a new method, Phase Retrieval from Closure
Phase (PRECL). PRECL estimates all the visibility phases only from the closure
phases. Combining PRECL with a sparse modeling method we have already proposed,
imaging process of VLBI does not rely on dirty image nor self-calibration. The
proposed method is tested numerically and the results are promising.


title: Ramanujan and coefficients of meromorphic modular forms

abstract:
  The study of Fourier coefficients of meromorphic modular forms dates back to
Ramanujan, who, together with Hardy, studied the reciprocal of the weight 6
Eisenstein series. Ramanujan conjectured a number of further identities for
other meromorphic modular forms and quasi-modular forms which were subsequently
established by Berndt, Bialek, and Yee. In this paper, we place these
identities into the context of a larger family by making use of Poincar\'e
series introduced by Petersson and a new family of Poincar\'e series which we
construct here and which are of independent interest. In addition we establish
a number of new explicit identities. In particular, we give the first examples
of Fourier expansions for meromorphic modular form with third-order poles and
quasi-meromorphic modular forms with second-order poles.


title:
CSI-based Fingerprinting for Indoor Localization: A Deep Learning
  Approach

abstract:
  With the fast growing demand of location-based services in indoor
environments, indoor positioning based on fingerprinting has attracted a lot of
interest due to its high accuracy. In this paper, we present a novel deep
learning based indoor fingerprinting system using Channel State Information
(CSI), which is termed DeepFi. Based on three hypotheses on CSI, the DeepFi
system architecture includes an off-line training phase and an on-line
localization phase. In the off-line training phase, deep learning is utilized
to train all the weights of a deep network as fingerprints. Moreover, a greedy
learning algorithm is used to train the weights layer-by-layer to reduce
complexity. In the on-line localization phase, we use a probabilistic method
based on the radial basis function to obtain the estimated location.
Experimental results are presented to confirm that DeepFi can effectively
reduce location error compared with three existing methods in two
representative indoor environments.


title: A simple approach to temporal cloaking

abstract:
  In recent years a remarkable progress was made in the construction of spatial
cloaks using the methods of transformation optics and metamaterials.
  The temporal cloaking, i.e. the cloaking of an event in spacetime, was also
widely studied by using transformations on spacetime domains.
  We propose a simple and general method for the construction of temporal
cloaking using the change of time variables only.